Miracle-dz/UniFAR-FTUs huggingface dataset:
Selecting the Last Substantially Touching Vertebra as Lowest Instrumented Vertebra in Lenke type 2A-R and 2A-L Curves.

STUDY DESIGN A retrospective study. OBJECTIVE The aim of this study was to determine whether the last substantially touching vertebra (LSTV) can be selected as the optimal lowest instrumented vertebra (LIV) for Lenke 2A adolescent idiopathic scoliosis (AIS) with different lumbar modifiers (2A-R and 2A-L) and to investigate its relationship with the distal adding-on. SUMMARY OF BACKGROUND DATA Previous studies have documented good outcomes in Lenke 1A curve when LSTV was selected as LIV. METHODS A total of 101 female patients were included with a minimum of 2-year follow-up after selective posterior surgery. Patients were classified on the basis of the direction of L4 tilt: 2A-L and 2A-R. Patients with LSTV-1, LSTV, or LSTV+1 selected as LIV were assigned to three groups. Factors associated with adding-on were analyzed through comparison among the three groups. RESULTS The level of LSTV was more distal in the 2A-R group than that in the 2A-L group (P = 0.011). Distal adding-on was observed in 24 patients (23.8%). In the 2A-R curves, 26.1% patients were found to have adding-on. The incidence of adding-on was significantly higher in LSTV-1 than LSTV or LSTV+1 group. Logistic regression analysis showed the distance between LIV and LSTV (LIV-LSTV <0) was the independent factor associated with adding-on (odds ratio [OR] = 8.7, 95% confidence interval [CI] = 3.1-45.5, P = 0.011). In the 2A-L curves, 21.8% patients were found to have adding-on. The incidence of adding-on was significantly lower in LSTV+1 than LSTV-1 or LSTV group. Similarly, logistic regression showed the distance between LIV and LSTV (LIV-LSTV ≤0) had significant association with adding-on (OR = 11.9, 95% CI = 2.5-53.2, P = 0.009). CONCLUSION The distance between LIV and LSTV was a significant factor associated with adding-on for both 2A-R and 2A-L patients. The rule of selecting LIV should be different between 2A-R and 2A-L curves. We recommend to extend the fusion level to LSTV in 2A-R curve and to LSTV+1 in 2A-L curve to avoid distal adding-on. LEVEL OF EVIDENCE 3.
A Data-Mining Approach for Energy Behavioural Analysis to Ease Predictive Modelling for the Smart City

Analyzing urban districts to promote energy efficiency and smart cities control could be very complex as big data have to be analyzed filtered to discover unpredictable patterns. Using clustering method, specifically K-means algorithm, allows to create an energy profiling characterization of urban district models with multiple advantages: as first, large quantity of data can be managed and synthesized, easing the creation of algorithm patterns that could be replicable. Thus, it is possible to operate in a large scale and in a small scale in the same time, choosing the level of detail that is more appropriate for the specific analysis. In the large scale, the disadvantages are the dependence from data, i.e. if there are missing input values, it is hard to rebuild them because of the quantity of data. Missing values can confuse the analysis because scripts cannot identify the entire row missing it. Working with clustering analysis it is thus useful when large amount of data should be organized and interpreted and the technique can help the planner to make faster the analyses process. The research aims at demonstrate the efficiency of clustering methods when adopted for energy consumption issues at city level. In the paper, the clustering process concerning building energy profiles of a European city for the identification of building models is described. This means that an energy template on urban scale is used and clusters are applied on energy profiles based on architectural and energy similarity in order to find representative models. In particular, the study is focused on the relationships between building characteristics and actual building energy profiles.
Gap‐filling approaches for eddy covariance methane fluxes: A comparison of three machine learning algorithms and a traditional method with principal component analysis

Methane flux (FCH4) measurements using the eddy covariance technique have increased over the past decade. FCH4 measurements commonly include data gaps, as is the case with CO2 and energy fluxes. However, gap‐filling FCH4 data are more challenging than other fluxes due to its unique characteristics including multidriver dependency, variabilities across multiple timescales, nonstationarity, spatial heterogeneity of flux footprints, and lagged influence of biophysical drivers. Some researchers have applied a marginal distribution sampling (MDS) algorithm, a standard gap‐filling method for other fluxes, to FCH4 datasets, and others have applied artificial neural networks (ANN) to resolve the challenging characteristics of FCH4. However, there is still no consensus regarding FCH4 gap‐filling methods due to limited comparative research. We are not aware of the applications of machine learning (ML) algorithms beyond ANN to FCH4 datasets. Here, we compare the performance of MDS and three ML algorithms (ANN, random forest [RF], and support vector machine [SVM]) using multiple combinations of ancillary variables. In addition, we applied principal component analysis (PCA) as an input to the algorithms to address multidriver dependency of FCH4 and reduce the internal complexity of the algorithmic structures. We applied this approach to five benchmark FCH4 datasets from both natural and managed systems located in temperate and tropical wetlands and rice paddies. Results indicate that PCA improved the performance of MDS compared to traditional inputs. ML algorithms performed better when using all available biophysical variables compared to using PCA‐derived inputs. Overall, RF was found to outperform other techniques for all sites. We found gap‐filling uncertainty is much larger than measurement uncertainty in accumulated CH4 budget. Therefore, the approach used for FCH4 gap filling can have important implications for characterizing annual ecosystem‐scale methane budgets, the accuracy of which is important for evaluating natural and managed systems and their interactions with global change processes.
Changing food culture for food wellbeing

This study investigates what people, in an urban and a rural setting in England, value about their local and home-grown food culture and how this shapes food choices which contribute to a broad definition of Food Wellbeing. Qualitative, ethnographic methods were used to uncover aspects of food relationships which are positive for the environment, communities and personal health. The connections provided by direct contact with local fresh food are explored. Communities such as those featured in this research, with high levels of food expertise, can contribute towards improving food cultures to attain better health outcomes for the planet, for people and for the individual.
Reduced complexity detection for massive MIMO-OFDM wireless communication systems

The aim of this thesis is to analyze the uplink massive multiple-input multipleoutput with orthogonal frequency-division multiplexing (MIMO-OFDM) communication systems and to design a receiver that has improved performance with reduced complexity. First, a novel receiver is proposed for coded massive MIMO-OFDM systems utilizing log-likelihood ratios (LLRs) derived from complex ratio distributions to model the approximate effective noise (AEN) probability density function (PDF) at the output of a zero-forcing equalizer (ZFE). These LLRs are subsequently used to improve the performance of the decoding of low-density parity-check (LDPC) codes and turbo codes. The Neumann large matrix approximation is employed to simplify the matrix inversion in deriving the PDF. To verify the PDF of the AEN, Monte-Carlo simulations are used to demonstrate the close-match fitting between the derived PDF and the experimentally obtained histogram of the noise in addition to the statistical tests and the independence verification. In addition, complexity analysis of the LLR obtained using the newly derived noise PDF is considered. The derived LLR can be time consuming when the number of receive antennas is very large in massive MIMO-OFDM systems. Thus, a reduced complexity approximation is introduced to this LLR using Newton’s interpolation with different orders and the results are compared to exact simulations. Further simulation results over time-flat frequency selective multipath fading channels demonstrated improved performance over equivalent systems using the Gaussian approximation for the PDF of the noise. By utilizing the PDF of the AEN, the PDF of the signal-to-noise ratio (SNR) is obtained. Then, the outage probability, the closed-form capacity and three approximate expressions for the channel capacity are derived based on that PDF. The system performance is further investigated by exploiting the PDF of the AEN to derive the bit error rate (BER) for the massive MIMO-OFDM system with different M-ary modulations. Then, the pairwise error probability (PEP) is derived to obtain the upper-bounds for the convolutionally coded and turbo coded massive MIMO-OFDM systems for different code generators and receive antennas. Furthermore, the effect of the fixed point data representation on the performance of the massive MIMO-OFDM systems is investigated using reduced detection implementations for MIMO detectors. The motivation for the fixed point analysis is the need for a reduced complexity detector to be implemented as an optimum massive MIMO detector with low precision. Different decomposition schemes are used to build the linear detector based on the IEEE 754 standard in addition to a user-defined precision for selected detectors. Simulations are used to demonstrate the behaviour of several matrix inversion schemes under reduced bit resolution. The numerical results demonstrate improved performance when using QR-factorization and pivoted LDLT decomposition schemes at reduced precision.
Effects of Orientations, Aspect Ratios, Pavement Materials and Vegetation Elements on Thermal Stress inside Typical Urban Canyons

The analysis of local climate conditions to test artificial urban boundaries and related climate hazards through modelling tools should become a common practice to inform public authorities about the benefits of planning alternatives. Different finishing materials and sheltering objects within urban canyons (UCs) can be tested, predicted and compared through quantitative and qualitative understanding of the relationships between the microclimatic environment and subjective thermal assessment. This process can work as support planning instrument in the early design phases as has been done in this study that aims to analyze the thermal stress within typical UCs of Bilbao (Spain) in summertime through the evaluation of Physiologically Equivalent Temperature using ENVI-met. The UCs are characterized by different orientations, height-to-width aspect ratios, pavement materials, trees’ dimensions and planting pattern. Firstly, the current situation was analyzed; secondly, the effects of asphalt and red brick stones as streets’ pavement materials were compared; thirdly, the benefits of vegetation elements were tested. The analysis demonstrated that orientation and aspect ratio strongly affect the magnitude and duration of the thermal peaks at pedestrian level; while the vegetation elements improve the thermal comfort up to two thermophysiological assessment classes. The outcomes of this study, were transferred and visualized into green planning recommendations for new and consolidated urban areas in Bilbao.
Arthropod segmentation

ABSTRACT There is now compelling evidence that many arthropods pattern their segments using a clock-and-wavefront mechanism, analogous to that operating during vertebrate somitogenesis. In this Review, we discuss how the arthropod segmentation clock generates a repeating sequence of pair-rule gene expression, and how this is converted into a segment-polarity pattern by ‘timing factor’ wavefronts associated with axial extension. We argue that the gene regulatory network that patterns segments may be relatively conserved, although the timing of segmentation varies widely, and double-segment periodicity appears to have evolved at least twice. Finally, we describe how the repeated evolution of a simultaneous (Drosophila-like) mode of segmentation within holometabolan insects can be explained by heterochronic shifts in timing factor expression plus extensive pre-patterning of the pair-rule genes. Summary: This Review describes the regulation and evolution of segment patterning in arthropods, covering the experimental discoveries and conceptual advances of the past 15 years.
Mortality, perception, and scale: Understanding how predation shapes space use in a wild prey population

Attempts to assess behavioral responses of prey to predation risk are often confounded by depredation of prey. Moreover, the scale at which the response of prey is assessed has important implications for discovering how predation risk alters prey behavior. Herein, we assessed space use of wild Ring-necked Pheasants (Phasianus colchicus) in response to spatial and temporal variation in recreational hunting. We radio-marked pheasants and monitored space use at two spatial scales: short-term seasonal home range, and nightly resting locations. Additionally, we considered temporal variation in predation risk by monitoring space use prior to and during the pheasant hunting season. Although we found no change in nightly resting location, pheasants subjected to predation risk expanded their home range and shifted home range location even when invulnerable to predation. Home range formation was plastic, with home ranges expanding and contracting as risk fluctuated before and during the hunting season. Depredation reduced the measured response within the population, obscuring the potential importance of perceived predation risk in shaping prey communities, particularly when not measured at the appropriate scale. By assessing space use of a wild prey population at multiple scales, considering spatial and temporal variation in predation risk, we show that not only does predation risk affect space use, but that the effects at the population level may be challenging to assess when not measured at the appropriate ecological scale because of the direct effects of differential mortality on the same behaviors.
Cloning and Functional Characterization of Dihydroflavonol 4-Reductase Gene Involved in Anthocyanidin Biosynthesis of Grape Hyacinth

Grape hyacinth (Muscari spp.) is a popular ornamental plant with bulbous flowers noted for their rich blue color. Muscari species have been thought to accumulate delphinidin and cyanidin rather than pelargonidin-type anthocyanins because their dihydroflavonol 4-reductase (DFR) does not efficiently reduce dihydrokaempferol. In our study, we clone a novel DFR gene from blue flowers of Muscari. aucheri. Quantitative real-time PCR (qRT-PCR) and anthocyanin analysis showed that the expression pattern of MaDFR had strong correlations with the accumulation of delphinidin, relatively weak correlations with cyanidin, and no correations with pelargonidin. However, in vitro enzymatic analysis revealed that the MaDFR enzyme can reduce all the three types of dihydroflavonols (dihydrokaempferol, dihydroquercetin, and dihydromyricetin), although it most preferred dihydromyricetin as a substrate to produce leucodelphinidin, the precursor of blue-hued delphinidin. This indicated that there may be other functional genes responsible for the loss of red pelargonidin-based pigments in Muscari. To further verify the substrate-specific selection domains of MaDFR, an assay of amino acid substitutions was conducted. The activity of MaDFR was not affected whenever the N135 or E146 site was mutated. However, when both of them were mutated, the catalytic activity of MaDFR was lost completely. The results suggest that both the N135 and E146 sites are essential for the activity of MaDFR. Additionally, the heterologous expression of MaDFR in tobacco (Nicotiana tabacum) resulted in increasing anthocyanin accumulation, leading to a darker flower color, which suggested that MaDFR was involved in color development in flowers. In summary, MaDFR has a high preference for dihydromyricetin, and it could be a powerful candidate gene for genetic engineering for blue flower colour modification. Our results also make a valuable contribution to understanding the basis of color variation in the genus Muscari.
Ash2l interacts with Oct4-stemness circuitry to promote super-enhancer-driven pluripotency network

Abstract Pluripotency and cell fates can be modulated through the regulation of super-enhancers; however, the underlying mechanisms are unclear. Here, we showed a novel mechanism in which Ash2l directly binds to super-enhancers of several stemness genes to regulate pluripotency and self-renewal in pluripotent stem cells. Ash2l recruits Oct4/Sox2/Nanog (OSN) to form Ash2l/OSN complex at the super-enhancers of Jarid2, Nanog, Sox2 and Oct4, and further drives enhancer activation, upregulation of stemness genes, and maintains the pluripotent circuitry. Ash2l knockdown abrogates the OSN recruitment to all super-enhancers and further hinders the enhancer activation. In addition, CRISPRi/dCas9-mediated blocking of Ash2l-binding motifs at these super-enhancers also prevents OSN recruitment and enhancer activation, validating that Ash2l directly binds to super-enhancers and initiates the pluripotency network. Transfection of Ash2l with W118A mutation to disrupt Ash2l–Oct4 interaction fails to rescue Ash2l-driven enhancer activation and pluripotent gene upregulation in Ash2l-depleted pluripotent stem cells. Together, our data demonstrated Ash2l formed an enhancer-bound Ash2l/OSN complex that can drive enhancer activation, govern pluripotency network and stemness circuitry.
Interviewer Effects on Cooperation during Initial and Refusal Conversion Fieldwork Phases in Telephone Panel Surveys

Specific interviewer characteristics, interviewer continuity, or matching interviewer and household characteristics may increase cooperation, especially for difficult-to-convince households. In face-to-face surveys, unobserved heterogeneity often makes a proper analysis of interviewer effects impossible. Although surveys conducted in telephone centers usually assign households to interviewers at random, there is less research on interviewer effects on cooperation, probably because telephone surveys produce smaller effects. Using data from a large telephone panel survey, I find interviewer effects only for households that refused to participate in a previous wave. Interviewer continuity or matching interviewers and households on sociodemographic variables has weak effects for any type of household. Interviewer experience has positive effects for previously refusing households only. Telephone survey organizations therefore only need to worry about using specially trained interviewers for refusal conversion calls, while specific assignments of interviewers to households are not necessary.
Quasi-Dynamic Dissolution of Electrospun Polymeric Nanofibers Loaded with Piroxicam

We investigated and monitored in situ the wetting and dissolution properties of polymeric nanofibers and determined the solid-state of a drug during dissolution. Piroxicam (PRX) was used as a low-dose and poorly-soluble model drug, and hydroxypropyl methylcellulose (HPMC) and polydextrose (PD) were used as carrier polymers for electrospinning (ES). The initial-stage dissolution of the nanofibers was monitored in situ with three-dimensional white light microscopic interferometry (SWLI) and high-resolution optical microscopy. The physical solid-state characterization of nanofibers was performed with Raman spectroscopy, X-ray powder diffraction (XRPD), and scanning electron microscopy (SEM). We showed that PRX recrystallizes in a microcrystalline form immediately after wetting of nanofibers, which could lead to enhanced dissolution of drug. Initiation of crystal formation was detected by SWLI, indicating: (1) that PRX was partially released from the nanofibers, and (2) that the solid-state form of PRX changed from amorphous to crystalline. The amount, shape, and size of the PRX crystals depended on the carrier polymer used in the nanofibers and dissolution media (pH). In conclusion, the present nanofibers loaded with PRX exhibit a quasi-dynamic dissolution via recrystallization. SWLI enables a rapid, non-contacting, and non-destructive method for in situ monitoring the early-stage dissolution of nanofibers and regional mapping of crystalline changes (re-crystallization) during wetting. Such analysis is crucial because the wetting and dissolution of nanofibers can greatly influence the performance of nanofibrous drug delivery systems in pharmaceutical and biomedical applications.
Ustekinumab as Induction and Maintenance Therapy for Ulcerative Colitis.

BACKGROUND The efficacy of ustekinumab, an antagonist of the p40 subunit of interleukin-12 and interleukin-23, as induction and maintenance therapy in patients with ulcerative colitis is unknown. METHODS We evaluated ustekinumab as 8-week induction therapy and 44-week maintenance therapy in patients with moderate-to-severe ulcerative colitis. A total of 961 patients were randomly assigned to receive an intravenous induction dose of ustekinumab (either 130 mg [320 patients] or a weight-range-based dose that approximated 6 mg per kilogram of body weight [322]) or placebo (319). Patients who had a response to induction therapy 8 weeks after administration of intravenous ustekinumab were randomly assigned again to receive subcutaneous maintenance injections of 90 mg of ustekinumab (either every 12 weeks [172 patients] or every 8 weeks [176]) or placebo (175). The primary end point in the induction trial (week 8) and the maintenance trial (week 44) was clinical remission (defined as a total score of ≤2 on the Mayo scale [range, 0 to 12, with higher scores indicating more severe disease] and no subscore >1 [range, 0 to 3] on any of the four Mayo scale components). RESULTS The percentage of patients who had clinical remission at week 8 among patients who received intravenous ustekinumab at a dose of 130 mg (15.6%) or 6 mg per kilogram (15.5%) was significantly higher than that among patients who received placebo (5.3%) (P<0.001 for both comparisons). Among patients who had a response to induction therapy with ustekinumab and underwent a second randomization, the percentage of patients who had clinical remission at week 44 was significantly higher among patients assigned to 90 mg of subcutaneous ustekinumab every 12 weeks (38.4%) or every 8 weeks (43.8%) than among those assigned to placebo (24.0%) (P = 0.002 and P<0.001, respectively). The incidence of serious adverse events with ustekinumab was similar to that with placebo. Through 52 weeks of exposure, there were two deaths (one each from acute respiratory distress syndrome and hemorrhage from esophageal varices) and seven cases of cancer (one each of prostate, colon, renal papillary, and rectal cancer and three nonmelanoma skin cancers) among 825 patients who received ustekinumab and no deaths and one case of cancer (testicular cancer) among 319 patients who received placebo. CONCLUSIONS Ustekinumab was more effective than placebo for inducing and maintaining remission in patients with moderate-to-severe ulcerative colitis. (Funded by Janssen Research and Development; UNIFI ClinicalTrials.gov number, NCT02407236.).