Miracle-dz/UniFAR-FTUs huggingface dataset:
'Downward control' of the mean meridional circulation and temperature distribution of the polar winter stratosphere

Abstract According to the “downward control” principle, the extratropical mean vertical velocity on a given pressure level is approximately proportional to the meridional gradient of the vertically integrated zonal force per unit mass exerted by waves above that level. In this paper, a simple numerical model that includes parameterizations of both planetary and gravity wave breaking is used to explore the influence of gravity wave breaking in the mesosphere on the mean meridional circulation and temperature distribution at lower levels in the polar winter stratosphere. The results of these calculations suggest that gravity wave drag in the mesosphere can affect the state of the polar winter stratosphere down to altitudes below 30 km. The effect is most important when planetary wave driving is relatively weak: that is, during southern winter and in early northern winter. In southern winter, downwelling weakens by a factor of 2 near the stratopause and by 20% at 30 km when gravity wave drag is not included .
Testing Independence in 2 × 2 Contingency Tables

Three of the potential models for the 2 × 2 contingency table are discussed: the hyper geometric Independence Trial, the double-binomial Comparative Trial, and the multinomial Double Dichotomy Trial. Then the critical regions of seven statistical tests are evaluated within each of these models. The uncorrected Pearson’s Chi-Square test and Upton’s correction are found to be overly liberal in all three models, particularly for the hypergeometric. A continuity correction, when properly applied, is shown to be an extremely good approximation to Fisher’s Exact test, which employs the hypergeometric distribution to evaluate outcome probabilities—but is an extremely conservative approximation to the double binomial and multinomial models. Haber’s test is recommended for these two cases, but the amount of work required may be prohibitive for many investigators.
Social Bots’ Role in the COVID-19 Pandemic Discussion on Twitter

Social bots have already infiltrated social media platforms, such as Twitter, Facebook, and so on. Exploring the role of social bots in discussions of the COVID-19 pandemic, as well as comparing the behavioral differences between social bots and humans, is an important foundation for studying public health opinion dissemination. We collected data on Twitter and used Botometer to classify users into social bots and humans. Machine learning methods were used to analyze the characteristics of topic semantics, sentiment attributes, dissemination intentions, and interaction patterns of humans and social bots. The results show that 22% of these accounts were social bots, while 78% were humans, and there are significant differences in the behavioral characteristics between them. Social bots are more concerned with the topics of public health news than humans are with individual health and daily lives. More than 85% of bots’ tweets are liked, and they have a large number of followers and friends, which means they have influence on internet users’ perceptions about disease transmission and public health. In addition, social bots, located mainly in Europe and America countries, create an “authoritative” image by posting a lot of news, which in turn gains more attention and has a significant effect on humans. The findings contribute to understanding the behavioral patterns of new technologies such as social bots and their role in the dissemination of public health information.
Numerical modeling of axisymmetric electron beam devices using a coupled particle-finite element method

A coupled particle finite-element method is developed for the numerical resolution of the time-dependent relativistic Vlasov-Maxwell equations in axisymmetric geometries. The use of a conforming finite-element method for the Maxwell solver supplemented with a mass-lumping technique leads to an explicit system for the computation of the electromagnetic fields components. For the Vlasov solver, a fully vectorized algorithm is used for the location of the particles in an unstructured mesh made up with triangles. The numerical values of the electromagnetic fields radiated by a dipole are compared with the analytical solution. The whole Vlasov-Maxwell solver is tested on a simplified free-electron laser electron injector, designed for an RF-based free electron laser and the results are compared with those obtained with a finite-difference code. >
A management perspective on threats to Cultural World Heritage Sites

ABSTRACT This study examines factors associated with threats to Cultural World Heritage Sites as perceived by their management. Employed for the analysis are data on 396 UNESCO Cultural World Heritage Sites in North America and Europe as well as 2158 threats identified by the UNESCO Second Cycle of Periodic Reporting for Europe and North America in 2014. One out of seven sites report that there are no threats at all and 2.5% do not provide information on the threats. Probit models show that sites inscribed early, those considered as “masterpieces” and sites located in certain countries are more likely to report a threat. Ordered Probit estimations, including three levels of threats (negligible, minor and major), reveal that the degree of threat perception is highest for entire cultural cities and cultural landscapes. The severity also varies by kind of threat and country of location. Climate change and severe weather as well as sudden geological events have the highest probability of being perceived as major threats. The third group of the most frequently mentioned major threats encompasses factors including local conditions affecting the physical fabric, social/cultural use of the heritage (tourism/visitors/recreation) as well as buildings and development.
A Single Chip SPAD Based Vision Sensing System With Integrated Memristive Spiking Neuromorphic Processing

This paper presents a new scalable $8\times8$ single photon avalanche diode (SPAD) based vision sensor with integrated spiking neuromorphic system on a single chip. The proposed vision sensing system adopts the benefits of SPAD’s high quantum efficiency and energy efficiency of memristive spiking neuromorphic processing. The SPAD based vision sensor includes biologically inspired address event representation (AER) readout to generate asynchronous digital address events at the output reducing computation and making it suitable to process directly with integrated on-chip spiking neuromorphic system in a faster and more energy efficient way. A novel on-chip interface is designed to convert the output events of a SPAD-based event sensor into temporally coded spikes (TCS) that enable on-chip processing with integrated spiking neuromorphic system. We have tested the prototype vision sensing system for imaging characters by SPAD based vision sensor and recognizing them using the integrated memristive spiking neuromorphic system. To help with the evaluation, we have built a complete temporal pulses data set from simulating the SPAD vision sensor with AER readout in imaging characters and applied directly to integrated spiking neuromorphic system via designed novel on-chip interface. The achieved accuracy is 89.54% with a power consumption of $316~\mu \text{W}$ for the memristive neuromorphic processor. The SPAD based vision sensor exhibits array-level dynamic range of 148 dB with a power consumption of 2.8 mW. The designed SPAD-based vision sensing system with an integrated spiking neuromorphic system on a single chip shows great promise for robotics, autonomous vehicles, health, and security applications.
Determining terminal-pair reliability based on edge expansion diagrams using OBDD

For calculating terminal-pair reliability, most published algorithms are based on the sum of disjoint products. However, these tree-based partitions lack the capability to avoid redundant computation due to the isomorphic sub-problems. To overcome these problems, an efficient methodology to evaluate the terminal-pair reliability, based on edge expansion diagrams using OBDD (ordered binary decision diagram) is presented. First, the success path function of a given network is constructed based on OBDD by traversing the network with diagram-based edge expansion. Then the reliability of the network is obtained by directly evaluating on this OBDD recursively. The effectiveness of this approach is demonstrated by performing experiments on benchmarks collected by previous works including the larger networks (from 4 to 2/sup 99/ paths). A dramatic improvement, as demonstrated by the experimental results for a 2-by-n lattice network is that the number of OBDD nodes is only linearly proportional to the number of stages, and is much better than previous algorithms which have exponential complexity by using the sum of disjoint products. The CPU time of reliability calculation for a 100-stage lattice network is only about 2.5 seconds with 595 nodes generated on a SPARC 20 workstation with 128 MBytes of memory. Thus, with this approach, the terminal-pair reliability of large networks can be efficiently evaluated better than thought possible.
Bootstrap calibration to improve the reliability of tests to compare sample means and variances

The comparison of several sample means to see whether they differ significantly is a common analysis, which is not straightforward when the samples may be from non‐normal distributions with different variances. A recent study found that a randomization test that attempts to approximate the distribution of F‐statistics from one‐ and two‐factor analysis of variance in the presence of unequal population variances was the best of 12 alternative tests considered. However, it sometimes suffered from excess size with data from extremely non‐normal distributions. In the present article a method for improving the robustness of the test by bootstrap calibration is described for one‐factor analysis of variance, and shown to be effective by a simulation study. The method is also applied with Levene's test for unequal variance by randomization. In this case the test is very robust without calibration, and calibration does not improve it. Copyright © 2001 John Wiley & Sons, Ltd.
Scaling of Turbulence and Microphysics in a Convection–Cloud Chamber of Varying Height

The convection–cloud chamber enables measurement of aerosol and cloud microphysics, as well as their interactions, within a turbulent environment under steady‐state conditions. Increasing the size of a convection–cloud chamber, while holding the imposed temperature difference constant, leads to increased Rayleigh, Reynolds and Nusselt numbers. Large–eddy simulation coupled with a bin microphysics model allows the influence of increased velocity, time, and spatial scales on cloud microphysical properties to be explored. Simulations of a convection–cloud chamber, with fixed aspect ratio and increasing heights of H = 1, 2, 4, and (for dry conditions only) 8 m are performed. The key findings are: Velocity fluctuations scale as H1/3, consistent with the Deardorff expression for convective velocity, and implying that the turbulence correlation time scales as H2/3. Temperature and other scalar fluctuations scale as H−3/7. Droplet size distributions from chambers of different sizes can be matched by adjusting the total aerosol injection rate as the horizontal cross‐sectional area (i.e., as H2 for constant aspect ratio). Injection of aerosols at a point versus distributed throughout the volume makes no difference for polluted conditions, but can lead to cloud droplet size distribution broadening in clean conditions. Cloud droplet growth by collision and coalescence leads to a broader right tail of the distribution compared to condensation growth alone, and this tail increases in magnitude and extent monotonically as the increase of chamber height. These results also have implications for scaling within turbulent, cloudy mixed‐layers in the atmosphere, such as fog layers.
Human circulating small non-coding RNA signature as a non-invasive biomarker in clinical diagnosis of acute myeloid leukaemia

Background: Acute myeloid leukaemia (AML) is the most common acute leukaemia in adults; AML is highly heterogeneous and involves abnormalities at multiple omics levels. Small non-coding RNAs (sncRNAs) present in body fluids are important regulatory molecules and considered promising non-invasive clinical diagnostic biomarkers for disease. However, the signature of sncRNA profile alteration in AML patient serum and bone marrow supernatant is still under exploration. Methods: We examined data for blood and bone marrow samples from 80 consecutive, newly-diagnosed patients with AML and 12 healthy controls for high throughput small RNA-sequencing. Differentially expressed sncRNAs were analysed to reveal distinct patterns between AML patients and controls. Machine learning methods were used to evaluate the efficiency of specific sncRNAs in discriminating individuals with AML from controls. The altered expression level of individual sncRNAs was evaluated by RT-PCR, Q-PCR, and northern blot. Correlation analysis was employed to assess sncRNA patterns between serum and bone marrow supernatant. Results: We identified over 20 types of sncRNA categories beyond miRNAs in both serum and bone marrow supernatant, with highly coordinated expression patterns between them. Non-classical sncRNAs, including rsRNA (62.86%), ysRNA (14.97%), and tsRNA (4.22%), dominated among serum sncRNAs and showed sensitive alteration patterns in AML patients. According to machine learning-based algorithms, the tsRNA-based signature robustly discriminated subjects with AML from controls and was more reliable than that comprising miRNAs. Our data also showed that serum tsRNAs to be closely associated with AML prognosis, suggesting the potential application of serum tsRNAs as biomarkers to assist in AML diagnosis. Conclusions: We comprehensively characterized the expression pattern of circulating sncRNAs in blood and bone marrow and their alteration signature between healthy controls and AML patients. This study enriches research of sncRNAs in the regulation of AML, and provides insights into the role of sncRNAs in AML.
Count data and treatment heterogeneity in 2×2 crossover trials

Count data are routinely assumed to have a Poisson distribution, especially when there are no straightforward diagnostic procedures for checking this assumption. We reanalyse two data sets from crossover trials of treatments for angina pectoris, in which the outcomes are counts of anginal attacks. Standard analyses focus on treatment effects, averaged over subjects; we are also interested in the dispersion of these effects (treatment heterogeneity). We set up a log‐Poisson model with random coefficients to estimate the distribution of the treatment effects and show that the analysis is very sensitive to the distributional assumption; the population variance of the treatment effects is confounded with the (variance) function that relates the conditional variance of the outcomes, given the subject's rate of attacks, to the conditional mean. Diagnostic model checks based on resampling from the fitted distribution indicate that the default choice of the Poisson distribution for the analysed data sets is poorly supported. We propose to augment the data sets with observations of the counts, made possibly outside the clinical setting, so that the conditional distribution of the counts could be established.
Insects in water towers: Hibernating flies could compromise microbial drinking water quality

Providing safe and qualitative drinking water is becoming increasingly important due to climate change and population growth. Water towers are often used to provide storage and ensure water pressure for drinking water distribution. However, microbial regrowth of water is still a challenge during storage and distribution. Moreover, water towers can be used as an aggregation site by insects, mainly flies (Diptera). In this study, ten water towers in Belgium were monitored for 8 months with sticky traps to evaluate fly species diversity, abundances and activity. The results showed the presence of three fly species: Thaumatomyia notata (yellow swarming fly), Musca autumnalis (face fly) and Pollenia spp. (cluster fly). The flies entered the towers in autumn and took shelter against wintering conditions in cracks and crevices, especially on the highest floors where the water tank is located. In this way, flies can come into contact with the drinking water. Based on the monitoring campaign, a risk assessment matrix was set up to determine risks of possible microbial water contaminations caused by flies in water towers. This was validated by a worst-case experiment in laboratory conditions. Face flies (living and dead) were added to tap water to evaluate their influence on microbial water quality and safety using several techniques such as 16S rRNA amplicon sequencing, flow cytometric cell counts and fingerprinting. Our research showed that flies in drinking water promote bacterial growth and change the phenotypic resident drinking water community. Furthermore, new genera such as Pseudomonas and Acinetobacter as well as the coliforms Serratia fonticola and S. liquefaciens were detected when flies were added to tap water. Hence, prevention and intervention measures are important in water quality management to avoid contact between flies and drinking water in water towers. In this study, several effective prevention methods are discussed, such as sealing ventilation, overflow and weep holes with insect screens with adequate mesh size and covering water tanks.
Statistical study of M 51-type galaxies

We present a statistical analysis of a new sample of M 51-type galaxies. Using the MCG and VV catalogues, we selected 32 such binary systems. We found that a typical M 51-type pair consists of a bright L spiral galaxy and a satellite with blue luminosity 1/30{1/3 of the primary one. The main galaxies in such pairs are often barred and have two well-dened spiral arms. M 51-type systems show an enhanced star formation rate (from FIR luminosities). We found a weak dependence of the star formation rate of the system on relative luminosity of the companion. M 51-type galaxies are relatively frequent: about 1/12 of all pairs are of M 51-type.
Cloud formation from large-scale instabilities

Abstract We discuss recent advances in cloud formation via gravitational instability under the action of self-gravity, magnetic fields, rotational shear, active stars, and/or stellar spiral arms. When shear is strong and the spiral arms are weak, applicable to flocculent galaxies at large, swing amplification exhibits nonlinear threshold behavior such that disks with a Toomre parameter Q < Qc experience gravitational runaway. For most realistic conditions, local models yield Qc ~ 1.4, similar to the observed star formation thresholds. When shear is weak, on the other hand, as in galactic central parts or inside spiral arms, magneto-Jeans instability is very powerful to form spiral-arm substructures including gaseous spurs and giant clouds. The wiggle and Parker instabilities proposed for cloud formation appear to be suppressed by strong non-steady motions inherent in vertically-extended spiral shocks, suggesting that gravitational instability is a primary candidate for cloud formation.
Astrophysical potentials of the MIDI VLTI instrument

The mid-infrared interferometric instrument (MIDI) is planned to become operative at the ESO Very Large Telescope Interferometer (VLTI) during the year 2001. The first version of MIDI is designed for use of two telescope beams at 10 micrometers wavelength. We here present an overview of some of the scientific objectives. The preparatory work under progress, before first VLTI observations, consists in studying the feasibility of different astrophysical projects (expected visibility, required absolute accuracy of the measurement, required observing time, procedure of observation, and VLTI baseline configuration). As examples we will discuss the observations of disks around young stellar objects, of active galactic nuclei, of extrasolar planets and of some evolved stars.
First in vivo fluorine-19 magnetic resonance imaging of the multiple sclerosis drug siponimod

Theranostic imaging methods could greatly enhance our understanding of the distribution of CNS-acting drugs in individual patients. Fluorine-19 magnetic resonance imaging (19F MRI) offers the opportunity to localize and quantify fluorinated drugs non-invasively, without modifications and without the application of ionizing or other harmful radiation. Here we investigated siponimod, a sphingosine 1-phosphate (S1P) receptor antagonist indicated for secondary progressive multiple sclerosis (SPMS), to determine the feasibility of in vivo 19F MR imaging of a disease modifying drug. Methods: The 19F MR properties of siponimod were characterized using spectroscopic techniques. Four MRI methods were investigated to determine which was the most sensitive for 19F MR imaging of siponimod under biological conditions. We subsequently administered siponimod orally to 6 mice and acquired 19F MR spectra and images in vivo directly after administration, and in ex vivo tissues. Results: The 19F transverse relaxation time of siponimod was 381 ms when dissolved in dimethyl sulfoxide, and substantially reduced to 5 ms when combined with serum, and to 20 ms in ex vivo liver tissue. Ultrashort echo time (UTE) imaging was determined to be the most sensitive MRI technique for imaging siponimod in a biological context and was used to map the drug in vivo in the stomach and liver. Ex vivo images in the liver and brain showed an inhomogeneous distribution of siponimod in both organs. In the brain, siponimod accumulated predominantly in the cerebrum but not the cerebellum. No secondary 19F signals were detected from metabolites. From a translational perspective, we found that acquisitions done on a 3.0 T clinical MR scanner were 2.75 times more sensitive than acquisitions performed on a preclinical 9.4 T MR setup when taking changes in brain size across species into consideration and using equivalent relative spatial resolution. Conclusion: Siponimod can be imaged non-invasively using 19F UTE MRI in the form administered to MS patients, without modification. This study lays the groundwork for more extensive preclinical and clinical investigations. With the necessary technical development, 19F MRI has the potential to become a powerful theranostic tool for studying the time-course and distribution of CNS-acting drugs within the brain, especially during pathology.
Gain-scheduled inverse system and filtering system without derivatives of scheduling parameters

This paper considers a gain-scheduled inverse system for an LPV (linear parameter-varying) system based on the induced L/sub 2/ norm and proposes a method for its design. Usually, a gain-scheduled dynamic controller designed with a parameter-dependent Lyapunov function either requires derivatives of the scheduling parameters, or its existence condition is formulated with BMIs (bilinear matrix inequalities). However, in this paper we consider a gain-scheduled inverse system without derivatives of the scheduling parameters, and formulate the existence condition of a full-order gain-scheduled inverse system only with LMIs (linear matrix inequalities) despite using a parameter-dependent Lyapunov function. A gain-scheduled filtering system without derivatives of the scheduling parameters for an LPV system is also derived similarly. To demonstrate the effectiveness of the gain-scheduled right inverse system as a model-matching controller, a simple numerical example is presented and compared with an LTI (linear time-invariant) right inverse system.