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A quantitative clue that USU need to be considered is manifested when a calculated global chi-square-perdegree-of-freedom parameter (χ 2 /df ) that exceeds 1 significantly is generated in an evaluation without consideration of an USU contribution. This is the case especially if care has been taken by an evaluator to eliminate clearly discrepant experimental data, and to consider all known sources of uncertainty (as well as their correlations) in a realistic manner. Unfortunately, it is common practice for evaluators to simply multiply all the input **data** uncertainties by the factor χ 2 /df when this happens, and thus artificially force χ 2 /df to be exactly 1, e.g., see [3,23,25]. This is not considered to be good evaluation practice because it treats all input **data** points equally, e.g., see [79]. Doing so may lead to biases owing to the excessive influence of those **data** points that contribute to the large chi square per degree of freedom. So, it is a poor substitute for actually uncovering the specific origin of the problem (e.g., discrepant **data** points, overlooked known sources of uncertainty, failure to consider correlations, etc.), or for performing a detailed examination of the individual terms that contribute to the calculated global value of χ 2 /df , and only then introducing a targeted USU contribution when no other options for eliminating the problem are envisioned.

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Expression profiles comparing relative mRNA and protein abundance Figure 5 Expression profiles comparing relative mRNA and protein abundance. The panels summarize mRNA and protein abundance **data** for individual P. falciparum genes, with PlasmoDB accession numbers indicated below the gene names. Both the relative mRNA and protein abundance levels determined in this study for four schizont-stage time points (TPs) are based on the same parasite samples from a single large-scale in vitro culture and are indicated by gray and colored lines (see panel legends), respectively. In addition, the previously published transcript dynamics across the whole intra-erythrocytic life cycle [2] are included as black lines, with the black dots representing the corresponding raw data. All abundance profiles were mean-centered around zero based on the **data** points between 34 and 46 hours post-invasion. Asterisks in the panel legends denote cases for which analysis of variance (ANOVA) P < 0.01 and maximum fold change >1.4×. The insert in the eukaryotic initiation factor (eIF)5A panel depicts actual two-dimensional gel images to provide an approximate impression of absolute protein abundance levels between the three eIF5A isoforms. (Figure 6d). This pattern mirrors the DIGE expression profiles of spots 2 and 3 ( Figure 5), whereas the differentially expressed spot 1 -because of its low absolute expression level (see inset in Figure 5) -presumably does not contribute significantly to the overall changes in protein abundance.

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Figure 9 : 9(a) Sequences of 400 walkers from the kombine sampler over 150 iterations. Two randomly selected sequences are highlighted in black. All samples to the left of the black dashed line are discarded. (b) The marginal Likelihoods and 2-sigma standard deviations are plotted for both samplers and all models.Finally, we examine the Posterior distribution and uncertainty intervals.Figure 10summarizes the posterior distributions obtained via the kombine (left) and MultiNest (right) samplers. We plot histograms and KDE distributions for each univariate parameter distribution. We provide multivariate summaries for each pair of coefficients via scatter plots of 2000 randomly selected samples. True parameter values are indicated by black markers. We first note that the samplers produce similar posterior parameter distributions. Furthermore, regions of high density in the Posterior closely align with the true parameter values. Figure 11 displays the model prediction and 95 th percentile uncertainty intervals obtained via the kombine (left) and MultiNest (right) samplers versus the synthetic **data** points. The uncertainty intervals are obtained by randomly sampling the Posterior distributions of the model parameters and computing the 2.5 th and 97.5 th percentile levels of the resulting model predictions. The uncertainty intervals show the expected spread of model predictions from the distribution of θ 0 and θ 1 . The models fit the synthetic **data** well, and both the model predictions and uncertainty intervals are nearly indistinguishable between the two samplers. The results of

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As PNIPAM is temperature - responsive , [ 16 ] siRNA - SS - PNIPAM copolymers can self - assemble into nanoparticles upon heating , with al ower critical solution temperature ( LCST ) of 30 8 8C , 31 8 8C , and 32 8 8Cfor PNIPAM components of 7kDa , 13 kDa , and 19 kDa , respectively ( Supporting Information , Table S2 ) . This enables nanoparticles to control drug loading during the self - assembly process . G el retardation assays show that after siRNA - SS - PNIPAM heating , no free siRNAw as released and all siRNAs tayed in the initial position ( Figure 1a ) , further confirming successful nanoparticle formulation . Dynamic light scattering ( DLS ) measurements show that the formulated nanoparticles ranged in particle size from 126 nm to 135 nm ( Figure 1b and Supporting Information , Table S2 ) while exhibiting very narrow polydispersity index ( PDI ) . Tr ansmission electron microscopy ( TEM ) images further confirmed the particle size . M ore importantly , aclear vesicular morphology , w ith an empty interior and as olid layer , was observed in nanoparticles derived from PNIPAMs of three different molecular weights ( Figure 1cand Supporting Information , Figure S4 ) , indicating the successful formation of siRNAsome . F urthermore , t he siRNAsomes are very stable under physiological condition , their particle size was constant and no siRNAr elease was observed even after up to 7days of storage ( Supporting Information , Figure S5 ) . Thes iRNAsomes derived from PNIPAMs of 19 kDa in molecular weight showed the best dilution stability ( lowest critical aggregation concentration , CAC ; Supporting Information , Table S2 ) . Using PNIPAM of this molecular weight , the drug - loading utility of siRNAsome was confirmed by performing an encapsulation experiment using the hydrophilic drug doxorubicin hydrochloride ( Dox·HCl ) , the hydrophobic drug docetaxel ( DTX ) , and the hydrophilic protein bovine serum albumin ( BSA ) . As shown in Tables S3 in the Supporting Information , successful encapsulation of Dox·HCl , DTX , and BSA was achieved during the siRNAsome fabrication process . U sing siRNA - SS - PNIPAM copolymer , upon heating , loading efficacies of approximately 37 % , 43 % , and 33 % ( for Dox·HCl , DTX , and BSA , respectively ) were achieved at at heoretical drug loading content of 20 wt.% . These data confirm that the siRNAsome Scheme 1 . Illustration of siRNAsomef ormation , composition , and function . T > LCST = Temperatureg reater than the lower critical solution temperature . nanostructure can serve as au niquely versatile carrier for therapeutic agents with diverse chemical properties and types .

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*p<0.05; **p<0.005; ***p<0.0005. DOI: 10.7554/eLife.01964.012 The following source **data** and figure supplements are available for figure 5: Source **data** 1. GO analysis for differentially regulated genes (>twofold) in miR-142 −/− MKs. DOI: 10.7554/eLife.01964.013 Source **data** 2. Genes commonly up-regulated (>1.5-fold) in miR-142 −/− MKs and DCs (CD24+ and CD24 − ). DOI: 10.7554/eLife.01964.014 Figure supplement 1. Expression distribution plot of miR-142 putative targets. DOI: 10.7554/eLife.01964.015 Figure supplement 2. qPCR expression analysis of miR-142 putative targets in precursor cell populations. DOI: 10.7554/eLife.01964.016 Figure supplement 3. miR-142-3p directly regulates cytoskeletal genes. DOI: 10.7554/eLife.01964.017 Figure supplement 4. miR-142-3p directly regulates cytoskeletal genes. DOI: 10.7554/eLife.01964.018

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Furthermore, the crystallite size of NC 1 as compared to TZP-pure was determined using the **data** obtained by XRD analysis [48] following the Scherrer Equation (1): D = Kλ βcosθ(1) where D = average size of crystallite size, K = Scherrer constant "(i.e., 0.68 to 2.08, 0.94 for spherical crystallites with cubic symmetry)", λ = wavelength of X-ray, CuKa2 = 1.5406 Å, β = the line broadening at FWHM in radians which describes the transmission characteristics of an optical band-pass filter and θ = Bragg's angle.

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The **data** structure that was generated by simply applying the concepts was not premeditated. In summary, this resulted from the spatial differences between material boundary operations (i.e. those enclosing several distinct occupiable spaces at once, those circumscribing one occupiable space discretely, and those specifying a characteristic persisting for only part of a circumscription of a discrete occupiable space), and the necessarily particular relations of each occupiable space to its outside (consisting of other bounded occupiable spaces). It turned out that **data** identification according to elementary boundary operations as experienced from the human perspective of one side of the boundary and then the other, initially produces further disaggregation into units. These units then constitute each and every occupiable space. Once mapped, this material boundary **data** is at once fully quantifiable (and geospatial) and contains an interpretively rich yet critically delimited description.

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One of the primary objectives of analysis with RMT makes it simple for researchers to understanding **data** with simple ways. The **data** developed by the RMT its equal-interval and linear **data** [29]. This authorizes us to identify all person that takes a high level of NoMoPhobia or vice versa. Detail information of person measure in this research can be achieved via a link https://osf.io/yhg2c/.

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Thematic analysis was chosen to analyze the **data** collected through interviews. This method is appropriate for the research purpose as it identifies the patterns across the data; besides, it helps in identifying the social processes in practice. Questions were revised to clarify and record relevant information, and field notes were recorded after each interview. All the interviews were recorded with the respondents' permission. After that, interviews were transcribed and coded. Themes were identified, analyzed, and developed by all the team members.

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The covariance matrix due to systematic effects for the three energy groups is given in Table VIII. The **data** in Table VIII reveal a relatively strong energy dependence for the uncertainty due to systematic effects. Such an energy dependence is difficult to explain from an experimental point of view, considering the relatively small energy region covered by the **data** points included in the analysis. The values in Table VIII are not consistent with those derived from a MLE analysis.

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The **data** presented in this study are available on request from the corresponding author.

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To investigate the ICP27 RNA binding specificity , HSV-1 RNA sequences that interact with ICP27 were first identified . A yeast three hybrid analysis identified 31 HSV-1 sense RNAs , mapping to 28 different open reading frames , which interacted specifically with ICP27 in vivo ( 26 ) . ICP27 was also found to specifically associate with seven HSV-1 RNAs in in vivo UV - crosslinking studies . The late RNA for the glycoprotein C ( gC ) gene was one of the RNAs that UV - cross - linked to ICP27 in infected cells ( 3 ) . To further refine the pools of possible RNA binding sequences , a yeast three - hybrid screen was performed with an RNA library generated from nucleotides 95 155 - 98 129 of the KOS HSV-1 genome , which encompasses two late genes , UL43 and UL44 ( gC ) . Sequences corresponding to both the mRNA coding and noncoding strands from UL43 and gC were identified in the yeast three hybrid screen as interacting with ICP27 ( data not shown ) . No obvious consensus sequences were identified in these sequences ; consequently EMSA was used to screen these sequences for those that bound to ICP27 with high affinity . A 294 - nt region of gC , corresponding to nucleotides 96 946 - 97 239 of the coding strand of the KOS HSV-1 gC mRNA , was chosen as an EMSA binding substrate . This region of the gC mRNA was chosen over the other sequences because it was within the coding region of the gC mRNA and was small enough to screen . Nineteen overlapping 30 - mer DNA oligonucleotides corresponding to coding strand of the gC RNA were used in EMSA experiments ( Figure 1C ) . RGG box motifs in other proteins recognize both RNA and DNA quadruplex structures ( 30,31 ) , so gC DNA was used instead of gC RNA for this initial screening to provide a more stable substrate for analysis . The ICP27 N - terminus was incubated with individual radiolabeled gC DNA 30mers at 37 C and resolved by nondenaturing acrylamide gel electrophoresis . Figure 2A shows a gC DNA sequence that the ICP27 N - terminus was able to shift its migration to a more slowly migrating band , gC 11 - 40 , and a second sequence , gC 31 - 60 , whose migration was not affected by addition of protein . Some sequences ' migration were moderately affected ( Figure 2B ; 121 - 150 ) , whereas most gC sequences were shifted well by the ICP27 N - terminus ( Figure 2B ; gC 1 - 30 , 91 - 120 and Figure 2C ; 61 - 90 . ) Of the gC DNA oligonucleotides tested , fourteen were shifted , two were shifted moderately and three showed no discernable shift ( Table 1 ) .

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RNA concentration , could allow description of " the real dynamic " of the virus spreading into the population , allowing for a direct comparison between the three waves . Our data showed that in the Greater Paris area , the first wave showed more highly concentrated samples ( i.e. samples with about 1 million UG / L ) than the 2nd and 3rd waves ( see Fig . 3 ) . Quantitative assessment of SARS - CoV-2 genomes in wastewaters demonstrates the impact of prevention measures such as lockdown or curfew which can Fig . 4 . Relationship between log of the concentration of SARS - CoV-2 genome and the log number of incidence number . Panel A regional scale , in blue average of the 5 WWTP , in red Lowess of the same data . Panel B , in blue SEM WWTP , in red MAV . panel C relationship between SEV and departmental incidence number . Panel D relation between STV and the departmental incidence number panel E , relationship for SEC and Paris incidence panel F , linear regression of all WWTP and the regional average . be once again observed in this project . Some general modeling papers have postulated the decrease of the wave intensity in accordance with our data .

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onto gas-distribution model to test for relationships between these apparently different but inherently connected processes. A similar method was followed for the investigation of porosity, permeability and isotope **data** sets, in particular in the context of considering the extent of biogenic recharge into the system, as well as examining the origins of CO 2 gas in the basin.

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It is useful to consider migration to the UK from the perspective of transnationalism, defined as "the process by which immigrants forge and sustain multi-stranded social relations that link together their societies of origin and settlement" 37 . From the 1920s until recently, migration research has tended to focus on the incorporation of migrants in their destination country rather than continued ties with their country of origin. However, since the 1990s, "the transnational turn" has provided "a new analytic optic" 38 . From this perspective, given that migrants maintain ties across the borders of nation-states, return visits to their country of origin and overseas visitors to the UK may result in increased exposure to M.tb. Where **data** was available, 17.2% of TB cases in 2016 in England had travelled outside the UK (excluding Western Europe, US, Canada, New Zealand and Australia) in the two years before diagnosis, and 7.3% had received an overseas visitor. 23.3% of non-UK born cases had travelled outside the UK in 2016 compared with only 4.7% of UK born cases 14 . Such movements are increasing as globalisation leads to the intensification of international interconnectedness: in the UK, travel to visit family and friends abroad increased by 67% between 1998 and 2007 39 . In 2007, UK residents made nearly 900,000 trips to the ISC for the purpose of visiting friends and family 39 .

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Geospatial visualization was carried out to compare and choose a better model for classifying anomalies on the city's streets. The main reason why KNN was a better fit was that it did not require **data** scaling for its inputs. Thus, the KNN accurately handled a street with deep potholes, speed bumps without any paint or signaling, and a generally more chaotic avenue that generated bigger sensor signals.

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FIG. 7 . 7PTH-stimulated cAMP response in osteoblastic cells. Intracellular cAMP responses were measured by radioimmunoassay after 15-min exposures at 37°C to concentrations of rPTH(1-34) from 10 Ϫ7 to 10 Ϫ11 M. In A, cells were plated at 50,000 cells/cm 2 and grown for 60 h. PTH stimulated cAMP accumulation in a concentration-dependent manner in both ROS (thick solid line) and bG (thick dashed line). However, PTH-stimulated cAMP accumulation in RCx4 (thin solid line) and RCx16 (thin dashed line) was dramatically attenuated. The peak cAMP response to 10 Ϫ7 M rPTH(1-34) in RCx4 and RCx16 was only 26.2 and 21.9% of that of ROS, respectively. In B, the intracellular cAMP response of ROS (thin solid line) and bG (thin dashed line) plated at 5-10,000 cells/cm 2 and grown for 48 h are shown. An 80% reduction in functional coupling in these low density cultures resulted in the attenuation of PTH-stimulated cAMP by 50 and 55% in ROS and bG, respectively. Confluent cultures of ROS (thick solid line) and bG (thick dashed line) are shown for comparison and are the same values as those presented in A. The average basal cAMP response from all experiments was 8.1 Ϯ 1.7 pmol/million cells. All **data** represent means Ϯ S.E. of three to six experiments performed in duplicate. *, significantly different from either ROS or bG (p Ͻ 0.05). FIG. 8. Forskolin-stimulated cAMP accumulation in osteoblastic cells. Cells plated at 50,000 cells/cm 2 were exposed to 10 Ϫ7 , 10 Ϫ9 , or 10 Ϫ11 M forskolin for 15 min. Intracellular cAMP was quantified by radioimmunoassay. Forskolin stimulated cAMP accumulation in a concentration-dependent manner in ROS (thick solid line), bG (thick dashed line), RCx4 (thin solid line), and RCx16 (thin dashed line). There were no significant differences in cAMP responses among the cell lines examined. The average basal cAMP response from all experiments was 7.9 Ϯ 0.8 pmol/million cells. The **data** represent means Ϯ S.E. of four experiments performed in duplicate.

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Analysts were asked to run linear regression on AFB and a transformed AFS variable . Since age at first sexual intercourse tends to have a markedly non - normal distribution ( see Fig S1 ) , we asked the analyst for a within - sex inverse rank normal transformation before running statistical models . Analysts were asked to include birth year of the respondent ( represented by birth year -1900/10 ) , its square and cubic to control for non - linear birth cohort effects . For those with family - based data , we suggested controlling for non - independence of family members or only include one family member in the analyses . We furthermore asked studies with family data to run a pooled GWAS on both sexes . Combined analyses that included both men and women also needed to include interactions of birth year and its polynomials with sex . In general , we asked to include top principal components to control for population stratification and cohort specific covariates if appropriate . Some cohorts only used birth year and not its polynomials because of multi - collinearity issues / convergence of the GWA analysis . Omission of these nonlinear birth year effects is unlikely to lead to biased inferences , since genotypes are not usually considered to be truly associated with birth year . However , inferences might be less accurate ( i.e. , have larger standard errors ) , since omission of nonlinear birth year effects can lead to larger residual variation .

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In this paper, the focus is on the formalization of expert knowledge and its use for test design and integration into different machine learning (ML) algorithms. The formalization of expert knowledge from different domains (e.g., expertise regarding plant mechanical Processes 2021, 9, 515 2 of 12 processes and knowledge about thermo-chemical and other physical mechanisms of chemical processes) is particularly challenging and reveals the uniqueness of the presented approach. Due to the lack of data, deep neuronal networks cannot always be trained, and other ML algorithms must be combined to quantify and expand expert knowledge from different domains. Figure 1 shows the continuous learning procedure and the interaction between the different parts of an AI-based hybrid model, i.e., **data** measurement, expert knowledge, and ML algorithms with special metrics for automated evaluation (autoML) [5]. With this procedure, expert knowledge can be continuously quantified, and the understanding of the plant and chemical processes can be expanded.

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ERM. The traditional Empirical Risk Minimization (ERM) algorithm optimizes over the loss on i.i.d. data, i.e., min β,Φ R(β · Φ), where R(β · Φ) = E (x,y)∼D (β Φ(x), y). (1) In the OOD generalization problem, one faces a set of (training) environments E, where each environment e ∈ E corresponds to a unique **data** distribution D e . When facing multiple environments, the ERM objective simply mixes the **data** together and takes the form (ERM) min β,Φ e R e (β · Φ),(2) where R e (β · Φ) = E (x,y)∼De (β Φ(x), y).

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In order to confirm our results from the PI **data** set, we conducted chromosome counts in PMCs. Seed of L. kirkii was not available, so its chromosome number remains unknown.

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(i) to highlight the need for an integrated RI to provide GHG and related environmental **data** with enhanced coverage across Africa;

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Because rodents make up nearly half of the world's mammalian species-and over 70% of taxa on some islands in this study-Millien repeated her analysis on a subset of the **data** with equal numbers of rodent and non-rodent taxa. The overrepresentation of rodents had no effect on the results, which still revealed signifi cant differences between island and mainland evolution rates for the same species or populations.

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We study how visual perception of a target bar can be biased by contextual bars in the image, and how a Bayesian model of object inference can account for the data. Human observers are more likely to perceive a target bar when the contextual contrast, i.e., the luminance difference between the contextual bars and background, is weaker rather than stronger. Relative to the situation without the context, they are biased to perceive the target in a context of weak contrast when the target can perceptually group well with the context, as if the context fills in the target. Meanwhile, they are biased not to perceive the target in a context of strong contrast, as if the context suppresses the perception, regardless of whether it could perceptually group well with the would-be target. The Bayesian model illustrates that the context influences the perception by biasing (1) observers' prior belief that a target should be present and (2) observers' internal model of the likely input contrasts from a target bar. Our **data** suggest that brain areas beyond the primary visual cortex along the visual pathway are responsible for inferring object causes for input images.

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We utilized **data** from an ongoing longitudinal study of behavioral, neuropsychological, social, and family functioning in 228 girls, 140 with rigorously diagnosed childhood ADHD and 88 matched comparison girls. All participated in summer research programs and extensive testing during childhood (baseline: ages 6-12), and they were followed prospectively into adolescence, completing extensive evaluation again 5 years later (see Hinshaw 2002;Hinshaw et al. 2006).

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Numerical Stability and Implementation To implement q-paths in practice, we begin by considering the log of the expression in Eq. (25), which is guaranteed to be non-negative becauseπ β,q (z) is an unnormalized density. logπ β,q (z) =(34)log π 0 (z) + 1 1 − q log 1 + (1 − q) · β · ln q π 1 (z) π 0 (z) ,q-path (blue) is still q = 1 − δ for small δ > 0. We focus attention on ln qπ1 (z)/π 0 (z) term, which is potentially unstable for q = 1 since it takes importance weights w =π 1 (z)/π 0 (z) as input. Since we are usually given log weights in practice, we consider the identity mapping w = exp(log w) and reparameterize q = 1 − 1 ρ to obtain ln q (exp log w) = 1 1 − q (exp log w) 1−q − 1 (35) = ρ (exp log w) 1 ρ − 1 (36) = ρ exp{ 1 ρ log w} − 1 .(37) This suggests q should be chosen such that the exponential doesn't overflow or underflow, which can be accomplished by setting ρ on the order of ρ = max i | log w i |.(38) where i indexes a set of particles {z i }. This choice is reminiscent of the log-sum-exp trick and ensures | 1 ρ log w| ≤ 1. In Fig. 6, we explore the impact of changing the scale of log w on the numerical stability of q-paths. For the case of inferring global model parameters over N i.i.d. **data** points p(D) = N n=1 p(x n ), we can see that the scale of the unnormalized densitiesπ 1 (θ, D) = p(θ) N n=1 p(x n |θ) differs based on the number of datapoints, where increasing N decreases the magnitude of log w = logπ 1 (θ, D) with π 0 (θ) = p(θ).

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Our findings emphasize the need for government agencies and local communities to work together to be more strategic in infectious disease containment policy implementation , and enhance health infrastructure in less developed regions to alleviate negative effects on these groups . Despite improvement in tracing measures and privacy regulations , there is room for additional enhancement in public health emergency response system to balance the twin goals of maximizing disease containment and minimizing the negative impacts on individuals . For example , policy makers can consider incorporating the HIPPA regulations during disease control implementation , and provide training to data collectors at government and community levels to promote ethical practices , privacy awareness , and sensitivity to confidentiality issues .

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Krakauer and colleagues bolstered their experimental fi ndings by comparing them with a statistical model of movements of the arm and wrist. The model uses a Bayesian approach, where previous experience and new **data** are combined to form a new parameter estimate. A key aspect of this approach is that greater uncertainty about the parameter leads to faster learning. Crucially, in their model, the investigators assumed that the majority of movements with the arm also include moving the wrist, but not vice versa. This led to a situation where the uncertainty in the parameter estimate-the imposed rotationdepended not only on the current limb context but also on the history of training in previous limb contexts. The model was able to reproduce most of the effects they saw in the experiments, such as the fi nding that learning would transfer from arm to wrist, but not vice versa, and blocking of generalization.

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As arule , when apples , pears , orother fruit ripen , the associated appearance of the appetizing colors of the ripe fruit is av isual indicator of their degree of ripeness . [ 81 ] At the same time , t he Chl originally present in the unripe green fruits is broken down , presumably to produce phyllobilins . C hl breakdown in the peel of Golden Delicious apples ( Malus domestica)a nd of Williams pears ( Pyrus communis)w as shown to yield the nonfluorescent type - I phyllobilins epi-9 and epi-11,also named Md - NCCs and Pc - NCCs . [ 59 ] Thesame ( epi - type , that is , RCCR-2 derived ) NCCs were also found in senescent leaves of the corresponding apple and pear trees , thereby indicating acommon pathway in the leaves and fruit of these fruit trees . [ 59 ] Several NCCs , including Ej - NCC-2 ( epi-29,T able 1 ) , were identified ( on the basis of mass - spectrometric and UV - spectroscopic data ) in quince ( Cydonia oblonga , M iller ) [ 82 ] and in loquat fruit ( Eriobotrya japonica ) . [ 83 ] Likewise , t he NCCs Bo - NCC-1 ( 3)a nd Bo - NCC-2 Figure 19 for the structures of type - II phyllobilins derived from pFCC ) . Figure 21 . Ripening fruit ( left ) and degreening florets of broccoli ( right ) undergo Chl breakdown and accumulate colorlessp hyllobilins . [ 59,61 ] Angewandte Chemie Reviews ( 17 ) , as well as Bo - DNCC-3 ( 30 ) , were characterized in degreening broccoli florets ( Brassica oleracea , v ar . Ital . ) . These three NCCs are known representatives of the normal stereochemical series of type - I and type - II phyllobilins . [ 61 ] Five NCCs were described earlier in senescent spinach leaves ( Spinacia oleracea ) , the so - called So - NCCs ( epi-1 , epi-5 , epi-11 , epi-12 , epi-13 ) , which belong to the epi series of NCCs . [ 50,64 ] As expected , in ripe(ning ) fruit and ( degreening ) vegetables , Chl breakdown follows the common PaO / phyllobilin pathway and furnishes colorless type - I and type - II phyllobilins , inaspecies - dependent way . Clearly , these plantderived components of our food are acommon source of Chl catabolites , w hich , hence , a re part of our daily nutrition . [ 6a ]

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The utility of SODAR measurements for understanding power performance is more apparent when considering turbulent intensity. Power curves for Turbine 1 were stratified by nacelle cup anemometer I U and SODAR I U in figure 5. Stratification by nacelle I U (figure 5(a)) included stable or strongly stable periods (I U < 10%) and convective or strongly convective periods (I U > 13%). Too few **data** points were available to isolate the effects of strongly convective conditions for the nacelle-based parameter. Observed power yields followed the expected power curve regardless of stability class. Power differences were less than 5% and occurred when the nacelle 'true-flux' equivalent wind speed was between 4 and 7 m s −1 .

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Batch sorption, a technique commonly used to obtain **data** on the removal efficiency of a given sorbent under static conditions, was selected as an appropriate technique in the current study. Polypropylene tubes containing 20 mL of metal solution and 3 g/L of limestone powder from the \210 lm-sized samples (S or Z) were shaken at 200 rpm at 25°C for 60 min to reach equilibrium. In single, binary and multi-element systems, 10 mg/L of each metal was used as an initial concentration to achieve similar concentration for all systems (molar concentration: [Pb] = 4.82 9 10 -5 mol/L, [Cd] = 8.89 9 10 -5 mol/L, [Cu] = 1.57 9 10 -4 mol/L and [Zn] = 1.52 9 10 -4 mol/L). For instance, in quadruple system, 5 mL of each metal stock solution (1,000 mg/L) were introduced in 500 mL volumetric flask and then diluted with UPW to obtain an initial concentration of 10 mg/L for each metal. The initial pH of the solution was adjusted to 6 with 0.1 M HCl and 0.1 M NaOH prior to mixing with limestone powder (Sdiri et al. 2012b). After shaking, 10 mL of supernatant were withdrawn and filtered through a 0.2 lm syringe-driven filter (Millex-LG, PTFE, Millipore Corp., Ireland). After the reaction, the sample solutions were stored at 4°C until analysis for Pb 2? , Cd 2? , Cu 2? and Zn 2? with an ICP-AES instrument, Optima 7300 DV series (PerkinElmer Inc., Tokyo, Japan). The amount of a metal removed from the solution was calculated as the difference between initial and final concentrations. The same experimental conditions were maintained for mixed systems (i.e., binary, ternary and quadruple mixtures). All experiments were run in triplicate.

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The presented data was collected as part of a larger project , but only the parts of the questionnaire that are of interest for this study 's research questions were included . The relevant questionnaire sections for this article can be found in Supplement D Questionnaire . The questionnaire comprised other sections that focused on consumer behaviour during the lockdown ( e.g. , acceptance of hoarding food and consumer goods , perception of food security ) . The study was approved by the Ethics Commission of the Federal Institute of Technology ( ETH Zurich ) .

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Validity-'Measures what it is supposed to measure' Comments indicate that a more clear definition or other refinementsto how the **data** would be collected would improve the PC-QIs.⇒ Four PC-QIs received a relatively high proportion of 'no' responses (9%-12%) and could be further refined: ⇒ 'Policy on PCC'; 'Culturally competent care'; 'Use of Patient Reported Outcome Measures'; 'Equitable care'. ⇒ Readiness of organisations to implement PC-QIs

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Law enforcement executives have noted the impact of the pandemic on police activities. Based on survey **data** collected from 989 US and Canadian executive officers who are members of the IACP, Lum et al. (2020a) noted several reported changes in police operations during the initial months of the pandemic. By March 23, 2020, 43% of responding agencies stopped or significantly changed their responses to CFS, 57% reported a decline in CFS, 61% implemented policies to reduce proactive stops, and 73% limited community policing activities. As of May 10, 2020, a second survey wave indicated that 53% of the responding agencies continued to have policies that limited proactivity, and 64% were still limiting community-oriented policing activities-both slight decreases from wave 1 (Lum, Maupin, & Stoltz, 2020b).

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Cloud cover and environmental datasets. The monthly mean MODIS cloud fraction at 0.05°used in this study was computed from the daily cloud mask **data** ("cloudy" label for the bits 0-1 of "state_1 km" band) included in the MODIS Surface Reflectance product (MYD09GA.006, overpass at local time of 13:30) of Aqua from 2002 to 2018, using the reduceResolution function with "mean" aggregation method on Google Earth Engine (https://earthengine.google.com/). The 1-km cloud mask was produced based on the MOD35_L2 cloud mask product, which had been extensively validated 71,72 . Before computing cloud fractions, a snow/ice flag (the bit 12 of "state_1km" band) was used to remove snow or ice pixels in the cloud record because the high reflectivity of snow/ice degrades the accuracy of cloud detection, especially during winter in the northern hemisphere. Therefore, the estimated cloud effect would have larger uncertainty in boreal winter than in summer.

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Thirty-one patients were followed in an intensive care setting after hip surgery, while the other 35 were referred directly to the general ward. Clinical characteristics and echocardiographic **data** of the two groups are reported in Tables 4 and 5

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In recent years the use of supervised methods has shown promising results in segmentation tasks. Supervised machine learning algorithms build mathemat-ical models from a set of labeled data. Example of supervised techniques are convolution neural networks (CNN), support vector machine (SVM) and naive Bayes model. Due to the ability of CNN to capture pattern of **data** in challenging datasets, they have been used in many works. For instance, [15] increases the receptive field by applying 7 × 7 filter size on fully convolutional network (FCN), this results in an outstanding segmentation performance of 99.7% accuracy on feline calicivirus images. In [16], [17], in order to tackle the challenge of imbalance between the foreground and background, a dice coefficient is ap- as SegNet [20] and U-net [21] which are capable of working in small number of datasets, gives us a suitable option for our dataset. Moreover, SegNet shows more superiority for having few parameters and hence faster to train, because it passes pooling indeces to the upsampling layers and does not use the heavy deconvolution layers. U-net has been applied in many works for segmentation of EM. Nevertheless, to the best of our knowledge no any work has been done on segmentation of EMs using SegNet, except for one work which uses SegNet directly without any network changes from the original one on sementation of yeast cells [22]. Thus, in this paper we attempt to leverage SegNet for segmentation of weakly visible microorganisms.

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We reconstructed the phylogeny for the Lepidium PI **data** set using Bayesian and likelihood analyses. For taxa that had multiple clonal PI sequences, we chose one clonal sequence from each monophyletic group of sequences representing a given taxon that was recovered in a 50% majority rule consensus tree from preliminary Bayesian analyses of all clones and that was representative of the majority of clones from a group. All other clonal sequences not forming monophyletic groups with other clones from the same taxon were included in the final analyses (Appendix 1).

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It may be surmised from the preceding discussion that uncovering the existence of USU, and developing procedures by which these uncertainties can be taken into consideration, requires evaluators to examine features of the **data** points themselves, including both their mean values and assigned uncertainties, and not simply to accept the author-provided mean values and uncertainties as a matter of faith. Failure to consider the possible existence of USU, if the contributions are significant, will result in the very deficiencies that manifest themselves in the aforementioned clues.

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Rainforest tree point process modelling. We consider a subset of the extensive rainforest **data** set credited to Hubbell et al. (2005) In the survey area, the locations of all Trichilia tuberculata (a tree species of the Mahogany family) have been measured (see Fig. 7 in App. J). We tackle this spatial point pattern with a log-Gaussian Cox process model, which is an inhomogeneous Poisson process model for count data. The unknown intensity function λ(x) is modelled with a Gaussian process such that f (x) = log λ(x). We model locally constant intensity in subregions by discretising the region into np bins (Møller et al., 1998). This leads to having a Poisson observation model in each bin (see App. J). This model reaches posterior consistency in the limit of bin width going to zero (Tokdar and Ghosh, 2007). The accuracy thus improves with tighter binning. We use a separable Matérn-5/2 GP prior over f (x 1 , x 2 ), and discretise the area into a n × p = 200×100 grid with np = 20000 grid bins, and treat the first dimension as time.

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We estimated the activation of the transcription factors in our network over time using NCA ( Figure 1B). NCA decomposes a matrix containing gene expression values (E) into a matrix which represents the influence of a transcription factor on a target gene (strength matrix S) and a matrix which contains the transcription factor activities (activity matrix A) [8]. We found that both outputs of NCApredicted factor activities A and regulatory influences Shave added additional insights to gene expression **data** where the underlying regulatory network structure is partially known. Figure 2A and 2B show the estimated activities of our 10 transcription factors. Transcription factor activities clearly showed early-, mid-, and late-phase action in response to LPS. IRF3, NFKB1(p50/p105) and RELA (p60) were activated within 2 hours after the endotoxin was injected. IRF3 activation peaked at 2 hours and returned to its base level at 4 hours. NFKB1 and RELA were also activated early but decreased in activity more slowly. These three factors can induce expression of tumor necrosis factor alpha, which then further activates the NF-B complex [25,26], and could contribute to the extended NF-B activation. JUN and FOS are known to be activated through the JNK pathway [30,31], and had a similar activation profile to NFKB1 and RELA. In contrast, STAT1, STAT3 and CREB1 exhibited a late-phase response. The STAT1 and STAT3 predictions correspond to previous findings that STATs are activated by cytokines transcribed by the NF-B complex [15]. It was surprising that predicted CREB1 activation peaked at four hours, given that previous reports detect phosphorylated CREB at 30 minutes [32]. However, the prediction was the result of late-phase induction of known CREB-dependent gene expression, such as ALAS1 and CEBPD [33,34]. Both STAT6 and MYC were predicted to be somewhat deactivated over nine hours. Deactivation of STAT6 was predicted due to repression of MHC-II class genes which are known to be regulated by STAT6 [35], as well as the expression of SOCS1, which has been reported to lead to deactivation of STAT6 [36]. MYC expression can be decreased through a STAT1-dependent pathway under IFN-γ stimulation conditions [37], and it is possible that the deactivation predicted here depends on STAT1 as well.

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The **data** extracted for each study included the study design, study population, sample size, dosage level of EPA, DHA, and placebo, study duration and outcomes.

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Policy information about availability of data All manuscripts must include a data availability statement . This statement should provide the following information , where applicable :

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Particularly now, the severe hazards that present high risks to humans and the ecosystems are extreme climatic patterns [77]. Hence, with evidence showing that the severity of extreme climatic patterns has increased since the 1990s, these events are under serious consideration and gaining attention. As part of a time series analysis, the recognition of a monotonic trend has prime importance. For applying statistical methods, a speculative composition requires the detection of trends. Due to the repercussions of climate variability, the non-homogeneity in the trends of hydrological series was shown. Statistical tests assist in identifying trends in stochastic or non-random arrangements. Understanding their potential or size permits us to make an accurate decision regarding already present trends [78]. The **data** was analyzed through various procedures, which involved performing tests to detect trends, occurrences, and stationarity of the **data** for the whole Punjab region, the results of which are shown in Table 4. The main concern during trend detection is finding out whether the values of a time series dataset have a familiar fluctuation with the increase of time; to this end, the ADF test aims to evaluate whether the average values or variances of a series change with the time. Almost all analysis techniques must suppose amorphous stationarity in the datasets whether the methods are linear or not. Hence, it is compulsory to check the stationarity using some standard and finite modules. At the same time, the examination of non-stationarity may lead to some awareness of the actual physical implementations.

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Having in mind the important role of respiratory viruses in airway epithelial cell damage , we attempted to assess the indirect effect of respiratory viral infection on epithelial regeneration . Incubation of bronchial epithelial cells with supernatants collected over 72 h from either RV1bor PIV3 - infected cells decreased the repair process 24 h post injury . Preincubation of injured and not - injured cells with the LPS inhibitor decreased supernatant - induced repair inhibition . This effect was also seen in cultures stimulated by conditioned media from RV1b in the presence of either TRIF inhibitor or MyD88 inhibitor . These findings may suggest that supernatants activated TLRs by danger - associated molecular patterns ( DAMPs ) and are consistent with data suggesting that respiratory epithelial cells respond to infection and produce endogenous DAMPs , such as for example ATP , HMGB1 , and S100 proteins [ 37,38 ] . DAMPs activate epithelial cell - intrinsic pattern recognition pathways and also recruit and activate cells of the immune system [ 39 ] .

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Much more remarkable in the figure is qualitative differences between the ONe core and the Fe cores. Among other things, the Fe cores emit a substantial amount of neutrinos from much earlier on than the ONe core. This is simply due to their higher temperatures as mentioned earlier. The electron-positron pairs are more abundant, producing neutrinos copiously. In fact, the ONe core is so cold until the electron capture on Mg is opened that electrons are strongly degenerate and, as a consequence, positrons are scarce, making the neutrino luminosity from the pair annihilation negligibly small. Unfortunately, the plasmon contribution is also tiny as long as the temperature is very low, since only a small amount of plasmons are thermally populated then. It is hence understandable that the neutrino luminosity becomes substantial in the ONe core only after the electron captures and the subsequent burnings of oxygen and silicon heat it up, which occur less than a second before collapse. Even after the formation of the NSE region (T 5 × 10 9 K) inside the core, the number luminosity of the ONe core is much smaller than those of the Fe cores. As a matter of fact, ∼ 10 53 neutrinos are emitted in the 15 M ⊙ model while in the 8.4 M ⊙ model the number of emitted neutrinos is only ∼ 10 51 . Note, however, that the luminosity increases very quickly in the last few hundred milliseconds in the ONe core and It is still increasing rapidly at the end of our calculation. At this point the central density is 10 11 g/cm 3 and no more **data** are available from the stellar evolution calculation. Unlike the Fe cores, the ONe core is rather slowly contracting even at this point, with the NSE region being expanding gradually. We hence expect the luminosity continues to rise further until neutrinos are trapped inside the core, which will be somewhat delayed, since the neutrinos considered here have smaller energies (∼ 5 MeV) than those produced by electron captures during collapse (∼ 10 MeV).

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All of our discussion throughout the paper will be completely model - independent and can be applied to any BSM scenario , including supersymmetry , extra dimensions , little Higgs theory etc . In Section 5 , however , we shall use a specific example in order to illustrate each of our three proposed methods . Instead of considering a decay chain of some BSM model , we chose to select an example which is already present in the Tevatron data , and will soon be tested at the LHC as well : the dilepton event samples from top quark pair production and from W -pair production . Those two dilepton samples satisfy all of our assumptions , and would be a perfect testing ground for any new ideas about mass measurements in missing energy events from new physics . In Section 5 we will show that using any one of our three M T 2 -based mass measurement methods , one can in principle determine the mass of each of the three particles : top quark , W -boson , and neutrino , independently and in a completely modelindependent fashion . Section 6 contains a summary and a discussion of our main results . In Appendix A we collect all relevant formulas for the endpoint functions M ( n , p , c ) T 2,max ( M c , p T ) .

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Herein , we present the synthesis of ac ubic ferric catecholate framework material coined Fe - HHTP - MOF . TheF e - HHTP - MOF is obtained in as olvothermal reaction as ad ark black powder consisting of intergrown tetrahedral crystallites in the 300 - 500 nm size range . T he structure was solved from powder X - ray diffraction data using aM o - K a source by indexing and as ubsequent simulated annealing step . T he unit cell obtained was subjected to aD FT optimization and Rietveld refinement to give af inal structure model with the cubic space group F23 . Thes tructure of Fe - HHTP - MOF is composed of iron - connected supertetrahedra to give ad iamond - like topology . T he tetrahedra are composed of four triphenylene units that form the facets and are interconnected by ad efined trinuclear iron - oxo cluster . T he Fe - HHTP - MOF is microporous with aB ET surface area exceeding 1400 m 2 g À1 .M oreover , F e - HHTP - MOF combines this high surface area with electrical conductivity of about 10 À3 Scm À1 , t hus establishing an exceptionally high intrinsic conductivity for a3 D - connected framework . Thed eep black appearance of the material was studied by reflectance measurements , g iving ar emarkably low degree of reflection up to 1.5 % i nt he visible spectral regime for ap orous framework . Then ature of the ferric repeat unit was elucidated by means of XPS , E PR , SQUID , a nd 57 Fe Mçssbauer measurements , i ndicating the presence of ap urely ferric , high - spin Fe III framework . To gain further insights into the electrical conductivity of Fe - HHTP - MOF , w ep erformed quantum mechanical calculations , w hich suggest the Fe - HHTP - MOF to be an efficient electron conductor that exhibits continuous paths through the conducting framework atoms . T his work sheds light on the subtle interplay of the structure , p orosity , e lectronic properties , e lectrical conductance , and broad - band optical absorption of novel framework materials , which serves as ablueprint for the future design of electrically conducting metal - organic frameworks . T he combination of the substantial porosity of Fe - HHTP - MOF with high electrical conductivity and an arrow direct band gap offers exciting opportunities for the design of novel chemical sensors , o rganic optoelectronics , a nd for electric control of mass transport in porous systems , such as microfluidics . Figure 7 . A ) Calculated hole - and B ) electron - transport paths . Isocontour plots for 8time steps ( 24 fs each ) of the electron ( green to blue ) and hole density ( green to red;c ontour level = 1.2 10 À5 e - Bohr À3 ) . The initial Gaussian functioni sshown as transparentsphere . Isocontour plots of C ) the PM6 local electron affinity ( contour level = 0kcal mol À1 ) a nd D ) local ionization energy ( contour level = 330 kcal mol À1 = 14.3 eV ) .

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In order to minimize the effects of potential laboratory and transcription errors, the **data** were analyzed separately by 3 independent analysts and evaluated based on known phylogeny. Extraction and genotyping were repeated at least 3 times, and consensus sequences were obtained from the replicates.

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If the limiting slope were less steep than we measured, then we should have seen orders of magnitude greater activity at the most negative potentials. For example, a "limiting" slope of e-fold/4 mV (six charges) fits our **data** between -60 and -40 mV. Extending this curve to -80 mV would give a Po of 8 * 10 -5, or 400-fold higher than we actually saw. Since this extra activity was absent, we must conclude that the slope could not have been as low as six effective charges.

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Author Contributions: Conceptualization, H.W. and J.D.; methodology, J.D.; software, J.D.; validation, J.D. and H.W.; formal analysis, H.W.; investigation, J.D.; resources, H.W.; **data** curation, J.D.; writing-original draft preparation, J.D.; writing-review and editing, H.W.; visualization, J.D.; supervision, H.W.; project administration, H.W.; funding acquisition, H.W. All authors have read and agreed to the published version of the manuscript.

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Data on admissions were extracted from the hospital records at the end of the trial . The number of admissions identified was cross referenced with the admissions reported by the patients to ensure that we captured events occurring away from the patients ' usual hospital . The cause of the admission ( and thus whether the event counted as a primary outcome ) was assessed independently from the hospital discharge summary by HP and BM with disagreements resolved by discussion ( with WM arbitrating , if necessary ) . Questionnaires were administered by a research nurse at a home visit arranged within two weeks of the calendar year during which the participant was in the trial . Healthcare resource use was collected by questionnaire posted to the participants three , six , and nine months ( one reminder ) and by the research nurse at baseline and the 12 month assessment . Healthcare resource use included consultations with GPs and nurses , respiratory and nursing teams , out of hours services , emergency services , telephone calls to the NHS 24 health information and self care advice service , and courses of oral steroids and antibiotics . The respiratory physiotherapy service in Edinburgh and the nurses in Midlothian maintained detailed timesheets of all patient contacts . All data were entered manually onto the trial database , with 10 % checked for accuracy by an external assessor .

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Having arrived at this stage, we are able to examine archaeological built environment maps for the physical information they contain and identify the boundaries shaping the entities of which the built environment consists. We must now move from bona fide physical presence of boundaries to fiat, to address how we understand their presence interpretively. Analysing physical presence results in little more than dimensions: information about the geometry, topology, morphology, and topography of built space. The difficulty with such information is that it is entirely contingent whether it has any bearing on social understanding. 5 The evidence base of archaeology is distinctly material, which is arguably why the discipline has struggled to contribute more substantially to social theory and synthesis has traditionally shown little attention to material integration (Sherratt 1993;Vis 2009). What this foregrounds is that our precise understanding of empirically derived (mechanical objectivity) archaeological evidence as physical evidence (judgmental objectivity) (cf. Galison 1998Galison , 2000Galison , 2010) has yet to transition into material evidence. This deliberate distinction of material evidence is meant to alert to us that **data** which captures material evidence must directly be of an interpretive nature. The next step towards social interpretation of built space is thus to construct interpretive data. Interpretive **data** redirects traditional **data** interpretation with precision and rigour, because it structurally links the empirical origins of spatial **data** to the ideas we have about them. These structural links provide the bridges that resolve the leaps between ontological registers (cf. Lucas 2015) that trouble and restrict the value of many archaeological interpretations. Rigorous use of interpretive **data** also carefully delimits the ontological register of interpretation, i.e. it ensures that **data** is commensurate with the understanding sought through analysis.

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Olivetti et al . [ 57 ] synthesized the available data on consumption rates relative to available reserves for nickel ( Ni ) , manganese ( Mn ) , cobalt ( Co ) , lithium , ( Li ) , and natural graphite . They found that the ratio of known reserves to primary mine production ( also known as the static depletion index ) has increased for Co , Li , and natural graphite , suggesting that continued demand has resulted in additional exploration and extraction . Mn and Ni did not show an upward or downward trend , indicating that the ratio of production to known reserves has remained relatively constant . This highlights the challenge of attempting to place a single number on finite resource depletion as part of an LCA ; society 's understanding of available resources is not static . Increased demand drives advancements in exploration and recovery technologies . Material recovery potential through recycling adds another layer of complexity . As Olivetti et al . [ 57 ] rightly point out , there is a time lag between when batteries are manufactured and when they reach the end of their life , so regardless of what can be recovered , recycling is unlikely to address any near - term ( 10 - 20 year ) material supply constraints . If battery technologies do not evolve away from reliance on these critical materials in coming decades , recycling can be an important long - term strategy . Pyrometallurgical recycling facilities will recover Ni , Co , Mn , and Copper ( Cu ) , [ 58 ] while hydrometallurgical recycling facilities will recover all of the aforementioned metals , as well as Li and aluminum ( Al ) . Direct recycling will recover an even larger range of materials , many of which can be reused without further processing . Given this context , it is worth revisiting the assertion by Peters et al . [ 11 ] that abiotic depletion ( an impact category representing depletion of non - renewable resources , such as minerals and fossil fuels ) is the most important impact of batteries on a normalized basis , exceeding the importance of GWP . Many of the nuances in critical material use and supply outlooks are lost in typical LCA practices and reducing these impacts to a single score is more likely to create confusion than generate useful insights , particularly when fossil fuel and critical material depletion are combined in a single score . This is particularly true for materials like Co and Li , for which demand is growing rapidly . In fact , a greater cause for concern is the geographic diversification , or lack thereof , in reserves and supply for some of these materials .

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For example,Andriollo et al. (2018) used F IS to examine diversity across bat species andWogan et al. (2020) used this same metric to examine subpopulation differentiation in a generalist bird. A methodological clarification to the original manuscript would have appropriately addressed these concerns.Prof. Hedrick cites supplementary materials from a dissertation chapter(Winkler, 2017) to make claims about **data** and analyses in the related article published in Ecology and Evolution at the center of this discussion(Winkler et al., 2019). These claims are unsupported because the **data** mentioned were written in 2017, almost two years beforeWinkler et al. (2019) was accepted for publication in Ecology and Evolution. Methods were revised, **data** were rescrutinized, and supplementary materials were all updated during the peer review process at two journals before being accepted by Ecology and Evolution.

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It should be emphasized that USU refers to "unrecognized" sources of uncertainties as the term implies. That means that before considering the possibility of USU effects, all known sources of biases and uncertainties should be addressed, estimated, and corrected for to the best of our knowledge. A detailed analysis of uncertainty evaluation by the experimentalists may hopefully reduce the need for hidden errors or unrecognized sources of uncertainty (USU ). More specifically, clearly wrong **data** should be rejected as they have the potential to bias the resulting mean values as well as significantly affecting the evaluated uncertainties. Known biases should be corrected, e.g., by updating to the newest standard reference cross-section or half-life values. A detailed uncertainty quantification (UQ) exercise should be undertaken using the literature that is pertinent to the respective **data** set. Furthermore, it should be investigated whether known sources of uncertainties for this particular measurement type are missing and should be added. Templates of expected uncertainties [59][60][61][62][63] for specific measurement types can help identify and estimate these missing covariances. Once all these steps have been completed for all input **data** of an evaluation, and still an unexplained scatter in the **data** considering their standard deviations is observed, one should take recourse to identifying whether USU components are present and estimate them.

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Location was determined from the difference in times of arrival of the two outer sensors, t. In addition, the speed of sound of the extensional wave or the time it takes for sound to travel between the outer sensors, tx, was required, where x is the distance between the two outer sensors. The speed of sound (tx/x) increases throughout the test as damage develops [6,24]. This was accounted for by determining the tx from events which occurred outside the outer sensors, presumably in the grips [25]. There was a period of no AE activity between 100,000 and 130,000 s (Figure 4a). For the following, only the location **data** after 130,000 s is presented since it leads up to failure. The location of the events prior to 100,000 s were evenly distributed across the gage section. The AIC derived t values typically differed less than 1 s of the actual first peak t. However, to get the most accurate t, the times of arrival of the first peaks on sensors 1 and 2 for events which occurred after 130,000 s were determined manually [13] and used to determine location. Examples of valley and peak waveforms are shown in Figure 6 with arrows indicating first peaks for sensors 1 and 2, top and bottom, respectively. Note that the first peak for the valley event on the top and bottom sensor is negative and the first peak for the peak event is positive; this is significant and is explained below.

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The Agricultural , Forestry and Fishing sector ( A ) , has been the least affected economic compartment with a GDP variation accounting for 0.13 % ( −584 million euro ) of the total change . According to data provide by OECD ( 2020a ) , the COVI-19 related spike in the consumption of vegetable and citrus fruits has contributed to boost a significant increase in the demand of agricultural products , with Spain experiencing the major sectoral gains ( +587 million euro ) . In line with the analysis provided by Eurostat for the food - related retail sector , the demand of agricultural products increased during the two first months of the pandemic and stabilized in the following period ( Eurostat retail trade database ) . The non - closure of supermarkets and essential shops , together with the panic buying behaviours has contributed to sustain the demand of the agricultural compartment ( Jaspal et al . , 2020 ) . Consequently , minor variations have taken place for the related carbon dioxide emissions change , that reduced by 338 thousand tons ( −0.17 % of the total change ) .

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A pile-up rejection procedure is applied to the set of **data** taken at √ s = 7 TeV: events with more than one distinct reconstructed primary vertex are rejected. This cut has a negligible effect on simulated events without pile-up: only 0.06% of the events are removed. We have compared a selection of high pile-up probability runs (see section 3) with a sample of low pile-up probability runs. The UE distributions differ by 20-25% between the two -4 - samples. After the above mentioned rejection procedure, the difference is reduced to less than 2%. Therefore, in the runs considered in the analysis, the effect of pile-up is negligible.

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While our study provides insightful implications, it is important to keep in mind its limitations. A key ingredient in an event study involves the date(s). Regarding the emergence of COVID-19, we make use of the official date of the declaration of the disease as a global pandemic by the WHO, i.e., March 11, 2020. Other studies look at the impact of other important different dates related to COVID-19 (e.g., Ashraf, 2020a, Ashraf, 2020bHeyden and Heyden, 2021), such as: (i) the date of the first COVID-19 confirmed case in the country; or (ii) the date of the first COVID-19 death in the country. Regarding key **data** on COVID-19 vaccines, we use a single date for each vaccine: when the vaccine effectiveness was announced as against the dates of vaccine trials. This choice is justified by the fact that vaccine development is a lengthy and uncertain process that generally takes around 10-15 years to complete before the vaccine can be mass-produced for public use (e.g., Chan et al., 2021). Despite the fact that the start of each phase marks a milestone in vaccine development because it (i) indicates the successful completion of the previous phase and (ii) boosts people's belief that the vaccine has a higher likelihood of progressing to the next stage, industry statistics show that only one-sixth of all vaccine candidates that undergo human clinical trials obtain final approval for mass production (Chan et al., 2021). Therefore, a more significant impact is to be expected when the vaccine is accepted by the regulators for mass population vaccination. We are aware that the magnitude of the impact of the emergence of COVID-19 and vaccine effectiveness announcements was influenced by the chosen dates.

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The ( 2 , 1 ) metric can be calculated in two parts . The first part is due to the ( 2 , ) monopole . This metric includes the effects of the ( , 1)-monopole on the ( 2 , ) -monopole but does not include the ( , 1)-monopole itself . The second part of the metric is due to the ( , 1)-monopole . This is described in Section 2 . First , the Nahm data are introduced along with the groups acting on them . Gauge - invariant coordinates on M ( 2,1 ) are then defined from the Nahm data and a set of one - forms defined from the exterior derivatives of these coordinates . Tangent vectors dual to these one - forms are calculated and the metric expressed in terms of the tangent vectors . The calculation of the explicit metric is presented in Section 3 . In Section 4.1 another way of calculating the metric is discussed in which the physical description given above is very apparent . In this Section , the hyperKähler quotient construction is used to construct the metric on M ( 2,1 ) from the direct product of the ( 2 , [ 1])-monopole and 1 - monopole metrics .

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We also compared PAL levels for " top-10 " lists of the most and the least correlated molecular pathways in Lung Adenocarcinoma biosamples ( Figure 14 ) for the transcriptomic and proteomic data . All of the most and the least correlated pathways showed common activation or inhibition trends for the RNA and protein expression data .

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Although our measurements for these Na § channels extend the measurable range and show a higher limiting slope, they do not contradict previous estimates. As indicated above, our **data** also show a slope of six charges in the range of 0.1 to 0.001, where most previous estimates of limiting slope were derived. For skeletal muscle Na + channels, however, this range is not sufficiently negative to reach the true limit.

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on transformed **data** (X + 0.5 ). d Artificial diet (Greene et al. 1976). e There were no survivors. f There was no emergence of adults from the pupae (no survivors). ns Not significant.

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The exclusion criteria for the CID patients and HCs were as follows: (1) clinical evidence of other sleep disorders, such as restless legs syndrome, narcolepsy, or obstructive sleep apnea; (2) abnormal sleep-wake rhythms determined by sleep-wake cycles of sleep (such as day and night alternating work); (3) severe general medical disorders, including diabetes, hypertension, cerebrovascular disease, heart diseases, or respiratory diseases; (4) other neurological disease, eg, traumatic head injury, local brain lesions, epilepsy, neurodegenerative or psychiatric diseases, including anxiety (Hamilton Anxiety Scale29), depression (Hamilton Depression Scale35), psychosis, or illicit alcohol or drug abuse; (5) MRI contraindications, such as metallic implants, claustrophobia or devices in the body; (6) Epworth sleepiness scale show doze off or fall asleep in the fMRI scanning; and (7) MRI **data** quality that did not meet the requirements, which included head movement in the rs-fMRI **data** that was less than 2 mm of translation along any axis and less than 2° of angular rotation along any axis.

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In a series of irradiations at Karlsruhe Intitute of Technology (KIT), neutron capture reactions for a 25-keV Maxwell-Boltzmann neutron energy distribution were studied, mainly for reactions that are relevant for s-process nucleosynthesis. AMS **data** obtained from such identical activations are used here, but they were converted into 30-keV MACS values for a direct comparison with TOF data. TOF measurement techniques have been well-established for several decades. In TOF, usually the prompt signature from the de-excitation of the reaction product is measured and used to generate a cross-section value. This approach involves different and also more sophisticated **data** processing procedures compared to AMS. The TOF **data** plotted here are based on measurements at ORELA ( 35 Cl, 40 Ca and 58 Ni) and n TOF/CERN ( 54 Fe and 58 Ni). In the activation reaction studies for AMS, the irradiation setup was designed such that the integrated neutron energy distribution resembled closely a Maxwellian distribution. Thus the measured cross section approximated an energy-averaged value. In TOF the energy-dependent cross sections are folded with the respective neutron flux energy-distribution for the MACS. There are no correlations between these two techniques. We find a systematic deviation between the two methods as seen in Table X. AMS **data** are systematically lower by about 11% compared to TOF **data** for these four reactions. In general, AMS measurements are normalized to reference materials which are independent from each other, and thus there is no correlation in AMS between different reactions. AMS and TOF **data** were both acquired at two different laboratories (Univ. of Vienna and TU Munich, and ORELA and n TOF, respectively). Currently, it is not known what the cause for this systematic deviation could be. The uncertainties of these ratios are generally lower than the observed deviation, leading to a potential estimate of an USU value. For instance, a numerical value for an USU contribution could be assumed to be the minimum deviation that make all measured **data** statistically consistent. If so, this could be estimated to be 5-7%.

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Figure 2 : 2Non-metric multidimensional scaling of the yeast gene expression **data** in

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The complete automation of smart farming is achieved by ISO 7798-2 security specifica tions-heterogeneous swarms are used in cloud middleware to operate drones, autonomous vehicles, etc. Autonomous-vehicle secure connectivity using IoT devices and key management framework is demonstrated by Jha S. et al. [22]. The vehicular network authentication is performed by blockchain based on hash graphs that can perform thousands of transactions per second and a framework designed using batch rekeying and logical key hierarchy (LKH). The 5G cooperative autonomous connectedness and driving is presented by Bagheri H. et al. [23]. This system uses 5G-based extensive authentication protocol (EAP) supporting 3GPP and non-3GPP communication networks, independent access, and mobility management function with session management function. The autonomous communication within the P2P network is demonstrated by Rahmani L. et al. [24]. A distributed hash table for agent lookup is shared by all the communicating agents and uses public-key cryptography for secure P2P communication with end-to-end encryption. An IoT mutual authentication protocol for Things-To-Things (T2T) is presented by Lounis K. et al. [25]. The T2T protocol uses physical unclonable functions (PUFs) with dual-level-challenge response pairs for the IoT authentication. V2X communication-based efficient authentication for protection against DDOS is demonstrated by Ko T. et al. [26]. The V2X system uses a security credential management system (SCMS), which classifies multiple similar messages in different categories for authentication and uses advanced verify-on-demand (AVoD) for signature verification with threat analysis. An improved isolation forest method for autonomous-vehicles-attack detection is presented by X. Duan et al. [27]. The detection of data-tampering attack is performed here using **data** mass and scoring for anomaly detection as a part of intrusion detection. An autonomous vehicle smart-parking system with the fog-blockchain architecture is presented by Shahzad A. et al. [28]. Smart parking helps to recognize the parking location with the help of fog nodes to IoT, the proof-of-concept by lightweight blockchain and a cryptographic module is utilized. Blockchain-based autonomous vehicle platoon management in 5G is demonstrated by Wu B. et al. [29]. This real-time system improves traffic management with public-key cryptography and 5Genabled revocable attribute-based encryption (RABE) with key distribution and revocation. P2P drone communication using blockchain is presented by Kumar M.S. et al. [30]. The drone base communication uses blockchain with GPS coordinates to avoid spoofing attacks and keeps the blacklisted database.

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After the samples were mixed thoroughly, we collected 1 kg of each sample; 1297 topsoil (0-20 cm) samples were collected in this study ( Figure 1). The GPS **data** of all samples were recorded before samples were air-dried naturally at room temperature. After removing plant residues and stones, all samples were passed through a 100-mesh nylon sieve (0.2 mm). The determination of soil total nitrogen (TN) was measured by the method described by Walkley and Black [30]; the soil available phosphorus (AP) was extracted by 0.5 mol L −1 NaHCO 3 and then measured via the Mo-Sb colorimetric method; and soil available potassium (AK) was extracted by 1 mol L −1 NH 4 -OAc with 1:5 weight-to-volume ratio and then measured by flame photometry [31].

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AQP2 Interaction with 14-3-3 Is Regulated by AVP-To examine if the AQP2 and 14-3-3 interaction was regulated by AVP, mpkCCD 14 cells were cultured in dDAVP for 3 days (to increase AQP2 levels), followed by acute stimulation with dDAVP (see "Experimental Procedures"). Following 20 min dDAVP stimulation, the interaction between AQP2 and 14-3-3 was enhanced, with a greater quantity of 14-3-3 immunoisolated using an AQP2 antibody, or conversely, a greater quantity of AQP2 immunoisolated using a 14-3-3 antibody (Fig. 5A). Quantification **data** from 3 individual immunoprecipitations is shown in Fig. 5, B and C.

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To control for potential confounding effects of geography , 16 temporal trends in outcomes , and hospital characteristics , we used a concurrent control group for comparison . This group consisted of all hospital admissions with an intensive care unit stay from hospitals located across the other 11 states in the US Midwest region ( as defined by the US Census Bureau ) , with hospital selection based on a random sampling methodology stratified by hospital bed size and teaching status Unadjusted and adjusted population level data on hospital mortality and average length of stay in Michigan hospitals and comparison hospitals ( 364 hospitals ) . Using this sampling methodology , we initially selected 64 % ( n=631 ) of hospitals in the Midwest region for the comparison group , including all large teaching , large non - teaching , and small teaching hospitals in the region . After exclusions , the final comparison group represented 37 % ( n=364 ) of Midwest hospitals . The sample size calculation was conservatively based on the number of hospitals , rather than hospital admissions , because the analysis accounted for clustering of admissions within hospitals . The sample size calculation assumed a power of 0.80 , a two tailed α of 0.05 , detection of a difference in reduction in length of stay between study and comparison group hospitals of 0.1 days ( group standard deviation 0.3 ) , and a fixed study group size of 90 hospitals ( an initial conservative estimate of the number of Michigan hospitals during the study period ) , resulting in a 4:1 ratio of comparison to study group hospitals .

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In this paper, we address these problems by extending the work of Baader and Krcmar [3] in multiple ways: We first extend the requirements for synthetic ERP **data** layed out by Baader et al. [4] to include further requirements of ERP fraud detection approaches [7]. We secondly propose to use an established serious game [9] to simulate not only fraudulent scenarios but also normal operation of a make-to-stock production company through user interaction in a real ERP system, generating both normal and fraudulent behavior simultaneously. Additionally, this allows us to extend the business processes investigated by previous **data** generators from the purchase-to-pay (P2P) process to modeling normal and fraudulent activity in the well established order-to-cash (O2C) process as well. Based on our extended requirements, we then design multiple fraud scenarios in cooperation with auditing experts. We conduct multiple runs of our proposed **data** generation scheme and produce ERP system **data** of multiple fiscal years of operation, extracting raw **data** from the ERP system. The resulting **data** contains many multi-relational tables that offer different views on the recorded company's business process. Since many fraud detection approaches require single tables to operate, we additionally create ready to use datasets from a subset of our multi-relational **data** that can be directly used for measuring and comparing the performance of fraud detection systems. We further extend these datasets by providing expert-created annotations for fraud cases that highlight the problematic entries of individual frauds for use in debugging and assessing performance of algorithms that focus on the detection of anomalous entries specifically.

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We use a crossover rate of 0.6 and a mutation rate of 0.001 (these are the default settings in GENESIS). Each experiment is repeated with three different levels of noise in the training **data** (that is, three values for p), 0.1%, 0.5%, and 1% (see Table 1 above).

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The goal of our paper is to identify areas of intergenerational change in the lives of Ghanaian women that have relevance for psychological indicators such as determinants of self-worth and sources of distress. Our **data** exploring social change in women comes from two distinct sources. Proverbs served as a source of information about "the traditional Ghanaian woman." Contemporary information was obtained from the results of the Everyday Lives Survey from the Pathways of Women's Empowerment Ghana project.

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Although the ADR was introduced into LoRaWAN as a solution towards improving the efficiency of the end devices' transmissions, studies have shown that the algorithm leads to increases in traffic collisions, especially in large networks [6][7][8]. These findings have received significant attention from academia: numerous studies and proposals have been produced as potential solutions to this problem. These solutions have been critically studied and summarized by the authors in [4]. The authors showed that these solutions have constantly brought improvements to the ADR. However, the authors also have argued that these improvements are still not adequate and that arriving at an ideal implementation of the ADR remains an open research area. Therefore, in this paper, the researchers used the knowledge gained from studying the findings in [4] to design an enhanced version of the ADR that uses congestion statuses of spreading factors to determine optimized **data** rates for end devices. The proposed algorithm was then evaluated in a series of simulated experiments and its performance was compared against four other algorithms with the same characteristics from the papers [7][8][9] in terms of **data** extraction rate (DER) and energy consumption (EC) [4]. The evaluation results show that the proposed algorithm achieves at least 40 per cent better DER performance and at least 100 per cent better EC performance over the other four algorithms. The process of evaluating the proposed algorithm was guided by the following research objectives:

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Conventional ITV+5/midV: Actual target position **data** are ignored for delivery, but incorporated in dose accumulation: the dose is calculated based on the doseinfluence **data** for the reported phase and warped onto the reference phase using EMT. This mode simulates current clinical practice: substantial motion occurs, but ITV/midV margins prevent cold-spots in the dose to the GTV.

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The path analysis describes routes from input to output, but can't reveal synergism between nonoverlapping paths. To do this, Li et al. used a dynamic modeling technique based on binary (active/on or inactive/off) assumptions about the state of interacting nodes to predict the probability of stomatal closure. Stomata don't usually open or shut completely, however, but close to varying degrees. The researchers captured this individual variability in the model by measuring stomatal apertures in Arabidopsis plants in the presence or absence of ABA application. These experiments provided population-level **data** to set a threshold between the open and closed state. With scant **data** on interaction times, component decay rates and initial states, they randomly assigned these values to cover the range of possibilities in over 10,000 simulations. They found that ABA induces complete closure in eight time steps; without ABA, the probability of closure is zero by the sixth step.

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The remainder of this paper is structured as follows. Section 2 gives the problem setting and fixes some basic notation for the rest of the paper. Section 3 formally introduces the precomposition operator, investigates its mathematical properties and its establishes its connection to the infinite-dimensional regression problem. In Section 4, we lay the groundwork for a detailed statistical analysis of regression with Hilbert-Schmidt operators by combining spectral regularisation techniques with concentration bounds for sub-exponential Hilbertian random variables. In particular, we derive basic rates under the assumption of Hölder-type source conditions. Section 5 discusses the consequences of our results for specific statistical fields and connects them to the relevant literature. Section 6 recapitulates the key points of our work and their implications in the abstract context of learning infinite-dimensional information from **data** by comparing the infinite-dimensional response setting to standard regression with real-valued responses.

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NAISC-L advances the state-of-the-art by presenting an interlinking framework that facilitates the creation of relationship and identity links, and that is accessible via a GUI designed to support IPs. It is envisaged that the NAISC-L framework will have an impact on the adoption of LD in LAMs by facilitating IPs to create LD interlinks with greater ease and efficacy than existing LD tooling allows. NAISC-L is complementary to existing interlinking frameworks as it supports the creation of relationship links through an interlinking process that encourages the application of domain expert knowledge. Facilitating the application of domain expertise allows IPs to use their specialist knowledge of particular subject areas, as well as their tacit knowledge of the needs and interests of LAM users, for the creation of useful, interesting and creative interlinks. Additionally, the provision of provenance data, detailing IPs as the creators and curators of these interlinks, increases user trustworthiness. In sum, LAM metadata that has been enriched with authoritative interlinks, created by IPs, would improve **data** discovery and promote increased use of LAM resources by allowing users to navigate seamlessly between related entities held in internal and external datasets.

Is data availability statement

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Recent studies have shown that patient-specific **data** can be utilized for the development of intelligent Healthcare Information Management Systems (HIMS), that support a wide range of supporting applications that enhance healthcare delivery platforms. The application of natural language processing, sophisticated **data** modeling, and predictive algorithms make it a highly interesting area of research. Patient **data** is continuously generated in large volume and variety, given the multiple modalities, it is available in (e.g., discharge summaries, physician's notes, clinical reports, lab reports etc). With an abundance of such diverse information sources available in the medical domain, sophisticated solutions that can adapt to the heterogeneity and specific manifold nature of health-related information are a critical requirement for HIMS development.

Is data availability statement

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SI Figure 16 . Simulation of two site chemical exchange at 400 MHz for a system with 1 ppm ( 400 Hz ) separation . Both symmetric ( 1:1 ) and 8:2 population were computed using the DNMR subprogram in Topspin 3.5 . In addition , calculated coalescence points ( 1:1 ) exchange at different field strengths with a 1 ppm separation of exchanging species are : Figure 18 . Representative imino proton exchange and base opening calculation graphs . A ) A representative graph of the imino proton T1 inversion recovery data ( graph is of the UB sequence G4 imino proton recovery with 6.5 mM NH3 at 3 ° C ) . X axis is recovery time in seconds ; Y axis is peak intensity ( arbitrary units ) . B ) A representative graph of τex vs. 1 / catalyst . ( graph is of the UB sequence G4 imino proton ) .

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Fully annotated microarray **data** has been deposited in ArrayExpress (E-MTAB-162).

Is data availability statement

yes

Corollary 2. Suppose Assumptions 1, 4 to 7, 10 and 11 hold and Y (a) ⊥ G | S(a), U, X. Then Equation (11) in Theorem 1, Equation (15) in Theorem 2 and Equation (16) in Theorem 3 all identify the average long-term treatment effect over the experimental **data** distribution, i.e., τ E = E [Y (1) − Y (0) | G = E] , In Corollary 2, we still assume the weaker conditions in Assumptions 10 and 11. But we additionally require that the experimental and observational **data** share a common conditional distribution of the potential long-term outcome. This additional assumption ensures that the bridge functions defined in terms of the observational **data** distribution can also be used to identify the average long-term treatment effect over the experimental **data** distribution.

Is data availability statement

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Illumina's HumanHT-12 v4 BeadArrays were used to generate expression profiles of more than 48,000 probes using 500 ng of labeled cRNA for each sample following the manufacturer's recommended protocols. All expression **data** are available at NCBI Gene Expression Omnibus (GEO) under the series number GSE35007. The individual expression arrays are listed as GSM860207 through GSM860517. To minimize chip and batch effects, a randomized design was used. Hybridization was performed on two different dates and 4 samples from the first hybridization batch were re-hybridized with the second batch. These technical replicates clustered adjacent to one another in hierarchical analysis, indicating a negligible batch effect on the data. This was confirmed by testing for batch effect in the probe-by-probe analysis of variance. The expression intensities were averaged for each probe in the statistical analysis. The raw intensities were extracted using the Gene Expression Module in Illumina's BeadStudio software. Expression intensities were log2 transformed and quantile normalized using JMP Genomics v5.0 (SAS) after an outlier filtering procedure was applied. In total, 28,595 probes with expression at or above background levels averaged across all the arrays were retained for further analyses. These represent probes remaining after removal of 18,404 probe measurements that were considered to lay below background detection levels indicated by the inflection point in a plot of rank-ordered normalized intensities. Also, 427 probes overlaying SNPs included in the Illumina's OmniExpress BeadChip were removed from the analysis. Pathway and gene ontology analysis was performed using Gene Set Enrichment Analysis (GSEA) (Subramanian et al., 2005).

Is data availability statement

yes

Previous reports have consistently shown that tau seeds can be transported into lysosomes after neuronal internalization (15,18,62) and some linked lysosomal dysfunction to Tau aggregation (26,63). Our lab has previously shown that internalized tau aggregates can result in the subsequent rupture of unidentified vesicles in neurons (14), enabling tau seeds to promote tau aggregation in the cytosol. Now, our present work identified the lysosomal delivery of Tau seeds as a key step in the process of seeded Tau aggregation. Based on our **data** we hypothesize that by reducing the transport of tau seeds into lysosomes via PIKfyve inhibition, tau seeding can be halted. In line with this idea it has been recently shown that exosomes containing Tau seeds require transport into the lysosome as well as lysosomal rupture to promote Tau aggregation (64). Whereas tau-seeds-induced rupture of lysosomes has not been shown yet, other protein oligomers such as α-synuclein fibrils are known to induce rupture of the lysosomal compartment and induce seeding (65).

Is data availability statement

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Our results showed that both the sloped (SD) drip culture platform design, and the multi-level horizontal design (MLHD) produced significantly higher rates of NO 3 uptake when compared to the totally submerged controls (SUB). Additionally, the bag-pouch vertical drip culture Table 2. Biomass **data** passed normality (Shapiro-Wilk; P = 0.087) after log transformation and equal variance tests (Brown-Forsythe; p = 0.682). Two-way Analysis of variance of the JSM fertilizer concentrations (1X, 2X, 4 X and 8X) and cultivation design (MLHD, BPVD, SD, SUB) on the daily growth rate of U. compressa. Ã The mean difference is significant at the 0.05 level. Land-based drip-irrigated culture of Ulva compressa Table 3.

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When studying statistical characteristics of sand waves, some authors (18) investigated the nature of the lower escarpment angles distribution and did not find the influence of the flow hydraulic characteristics on its value. The above works do not generalize the **data** obtained, do not conduct a quantitative and qualitative analysis of the works devoted to the ridges' lower escarpment, and the conclusions drawn are local in nature.

Is data availability statement

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Because many of the participants that had COVID-19 were medical providers, we addressed this limitation by exploring the combined impact of these factors. Future research should incorporate a confirmation of COVID-19 diagnosis and consider the timing and severity of illness as there were small differences in our sample between those who had COVID-19 at the time of **data** collection and those who had been previously diagnosed.

Is data availability statement

no

As pointed out above, **data** for eight children could not be included in the final analyses. Due to technical issues for 2 children (one in each group) during the testing of ESCS at T2 no material was available for analysis. Further, 6 children (2 in the Novel group and 4 in the TAU group) declined to participate in the testing of ESCS at T3. As the attrition rate in our study was 26 %, we examined possible effects due to attrition closer. No differences in eye gaze and gesture behaviors were found when comparing T1 and T2 scores between children that could be included in the final analysis (n = 22) and children that could not (n = 8), all p's > 0.60. However, the chronological age of the attrition group (M = 43.9 months, SD = 3.2) was significantly higher than the chronological age of the included children (M = 39.8 months, SD = 6.7), t (25.34) = 2.22, p = 0.035, equal variances not assumed. Overall, the two final intervention groups were not statistical different from each other at T1 on chronological age (see Table 1), language measures (see Table 1), or IJA measures (independent t-test for eye gaze: p = 0.92, gestures: p = 0.46, see also repeated-measure analyses above).

Is data availability statement

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On the basis of highly accurate laboratory rest frequencies , and the first data release ( DR1 ) from a largescale , high sensitivity spectral line survey , GBT Observations of TMC-1 : Hunting for Aromatic Molecules ( GOTHAM ) , predominately in the K ( 18 - 27 GHz ) and K a bands ( 26 - 40 GHz ) , a number of the authors here recently reported the astronomical detection of 1 - cyano - CPD using spectral stacking and matched filtering techniques ( McCarthy et al . 2020b ) . From these observations , which represent ∼30 % of the project goal , an upper limit for 2 - cyano - CPD relative to 1 - cyano - CPD was estimated to be roughly 1/3 . Because the abundance ratio in the laboratory ranges from 1/2 to 1/4 ( Sakaizumi et al . 1987;McCarthy et al . 2020a ) , it was unclear if 1 - cyano - CPD is formed selectively in TMC-1 or if the apparent absence of 2 - cyano - CPD is simply a question of sensitivity , given its somewhat lower stability and consequently lower abundance . With the second data release ( DR2 ) and additional laboratory measurements , this ambiguity has now been resolved , and in doing so a common formation for this isomeric pair is implicated .

Is data availability statement

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Separate HPLC fractions of the extractable peaks were dried using a Büchi Rotavapor R-124 rotary evaporator (Brinkmann Instruments, Inc., Westbury, NY), redissolved in 0.5 mL of 0.5 M methanolic HCl, and the resulting solution was heated for 1 hour at 70 • C. The hydrolysates were then dried and dissolved in 40 μL of 0.2 M TMAH in methanol to produce the methyl derivatives, which were subsequently analyzed using Agilent 6890/5973 gas chromatograph-mass spectrometry detector, GC-MSD (Wilmington, DE) equipped with a Gerstel MultiPurpos-eSampler MPS (Baltimore, MD). The gas chromatograph was fitted with Agilent DB-5MS capillary column (0.25 μm × 30 m, 0.25 μ film) and operated with temperature programming from 50 • C (held for 1 min) to 300 • C at 10 • C/minutes, and held at 300 • C for 6 min using helium as the carrier gas at a constant flow rate of 1 mL/min. The GC injector port was set at 280 • C in a splitless mode and the MSD was maintained at 280 • C. All the GC/MS **data** were acquired with MSD ChemStation Version D.01.02.16 (Agilent Technologies, Wilmington, DE) in the m/z range of 30-500 at a rate of 1 scan/sec under electron ionization (EI) mode. laminate extract was analyzed by LC/MS in full-scan positiveion mode using a 50 to 1500 m/z scan range. Following the assignment of MS ions for the identified peaks, the extract was reanalyzed using full-scan MS/MS experiments to obtain product ion spectra.

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Fig. 9 9Axial variation of flow variables in SDTV (left column) and BKTV (right column) cores obtained using S1 through S4, and mean code with P E jj bars is compared with experimental **data** with U D bars for b 5 20 deg. The SDTV onset at x 5 0.077 and BKTV onset at x 5 0.4 are shown in radial location (R) subplot.

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We thank an anonymous referee for providing crucial comments and suggestions that greatly improved the manuscript . We thank Luis Aguilar for fruitful discussions and advice . VRP acknowledges support from a CONACYT / UNAM scholarship . CRZ , VRP , MT and JH acknowledge support from UNAM - DGAPA - PAPIIT grants IN108117 , IN104316 and IA103017 , Mexico . ARL acknowledges support from program FONDECYT 1170476 , Chile and a PREI - DGAPA - UNAM academic exchange scholarship . This work has made use of data from the European Space Agency ( ESA ) mission Gaia ( https://www . cosmos.esa.int/gaia ) , processed by the Gaia Data Processing and Analysis Consortium ( DPAC , https://www . cosmos.esa.int/web/gaia/dpac/consortium ) . Funding for the DPAC is provided by the institutions participating in the Gaia Multilateral Agreement .

Is data availability statement

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We then surveyed what turned out to be a massive literature in order to assess G7 performance with respect to Summit commitments , and the health implications of the policies reflected by those commitments . The literature comprised : quantitative data assembled by organizations including the World Bank , OECD , and several United Nations agencies ; an extensive body of research by civil society organizations ( CSOs ) such as Oxfam and Jubilee Research ; and an expanding research literature on determinants of population health in the developing world . These categories tend to overlap , in particular as the work of key CSO - affiliated researchers is published by '' mainstream '' agencies ( Third World Network , 2001;Pettifor & Greenhill , 2002 ; . We carried out our own calculations and policy evaluations using these data , but did not check on their accuracy beyond the identification of clear inadequacies in the data as published . It must be noted that at least as many questions have been raised about the accuracy of data generated by agencies such as the World Bank and the World Health Organization ( e.g. Musgrove , 2003;Reddy & Pogge , 2003 ) as about the research and policy recommendations of CSOs .

Is data availability statement

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Many researchers in dispersive partial differential equations have recently examined whether blow-up behaviour, such as the norm-inflation described above, occurs for generic or only exceptional sets of rough initial data. To quantify this, one is quickly lead to random initial data. Indeed, one natural form of rough initial **data** is pu 0`f ω 0 , u 1`f ω 1 q, where the functions pu 0 , u 1 q P 9 H 1ˆL2 are regular and deterministic, while the functions pf ω 0 , f ω 1 q P H sˆH s´1 are rough and random. An analogue of Theorem 1.1 in this case would imply the stability of the scattering mechanism under a perturbation by noise. The literature on random dispersive partial differential equations is vast. We refer the interested reader to the survey [6], and mention the related works [2,4,8,9,11,12,14,15,16,38,39,41,42,44]. In the following discussion, we focus on the Wiener randomization [3,38] of a function f P H s pR d q. Let ϕ P C 8 pR d q be a smooth and symmetric function satisfying ϕ| r´3{8,3{8s d " 1, ϕ| R d zr´5{8,5{8s d " 0, and ř kPZ d ϕpξ´kq " 1 for all ξ P R d . We then define the associated operator P k by y P k f pξq :" ϕpξ´kq p f pξq .

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Some suggestions are presented for researchers and practitioners with regards to the findings of this study. Studies related to motivation and experience in the context of dark tourism have examined the phenomenon both from the supply-side and the demand-side. The **data** obtained from this study show that there are some cultural differences which constitute a component that affects both motivation and tourism experiences. Therefore, it would be beneficial for future studies to aim to develop a deeper understanding of the motivations and experiences of tourists who visit the site, from an anthropological perspective.

Is data availability statement

no

Key parameters of tunnel cross passages can be determined in 4 steps: collect basic **data** on the tunnel; preliminarily determine design parameters of cross passages; evaluate safety risks of tunnel evacuation; and analyze risk evaluation results. The flowchart is given in Fig. 1.

Is data availability statement

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Mixed methods were used for **data** collection. The qualitative **data** collection was carried out first, making use of semi-structured interviews and focus group discussions (FGDs). A total of 26 semi-structured interviews were conducted with eight livestock owners, four shepherds, and a further five with livestock owners' wives, and five with shepherd wives. A One Health approach was applied by jointly discussing animal and public health workers and their respective roles in knowledge production and transfer to pastoral communities. Four semi-structured interviews were conducted with health workers, one with a male nurse, another with a physician and two with veterinarians. Eight FGD were conducted with six people per group. Three focus groups were organised with sedentary livestock owners, whilst two discussion groups involved transhumant pastoralists, and participants of the three other FGD comprised respectively herdsmen, livestock owners' wives and herdsmen' wives. Printed pictures of hygromas and orchitis in ruminants were used during those interviews to structure the discussion on symptoms of brucellosis in animals. All interviews were recorded using a digital voice recorder. For the quantitative **data** collection, 320 questionnaires were completed. Interviews and questionnaires were prepared and conducted in Malinké (the local language commonly called Dioula), by a trained research assistant under a close supervision of the main researcher to ensure the accuracy of the translation of each discussion to French. The answers were then analysed and translated from French to English in this manuscript. Names and expressions from pastoral communities in local languages used to identify brucellosis symptoms were called Popular Nosological Entities (PNE). During the various interviews, brucellosis in animals was presented by the interviewer through its clinical symptoms such as hygromas, orchitis, drop in milk production and spontaneous abortions. Participants were also asked if they were familiar with the term brucellosis to describe this disease during the quantitative survey.

Is data availability statement

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With a proper definition of energy in hand , in the third section we consider a large class of time symmetric initial data generalizing the form of solutions considered by [ 9 ] . The fourth section describes some particular negative energy solutions , and the fifth section discusses the time evolution of this data . We point out that while bubbles such as ours and those of [ 9 ] may become large , as long as the standard boundary conditions are preserved they never reach infinity . We conclude with a discussion of some open problems for the gravitational theory and with regards to the AdS - CFT conjecture .

Is data availability statement

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Additionally, Maskály et al. (2021) collected survey **data** from police executives in 27 countries around the world to assess the effects of COVID-19 on police organizations and activities. Their findings indicated that, by summer 2020, responding organizations experienced at least some changes to problem-solving or community policing activities (83%), patrol strategies (78.3%), traffic stops (68.2%), officer-initiated activities (60.9%), special operations teams' activities (54.1%), handling CFS (43.4%), and use of tactical teams (34.8%). Collectively, these results demonstrate that routine police activities have been impacted by the COVID-19 pandemic. Such changes have also led to empirical investigations of how police activities have changed since the start of the pandemic.

Is data availability statement

no