Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of NWP results for wintertime nocturnal boundary‐layer temperatures over Europe and Finland

Four operational numerical weather prediction (NWP) models were evaluated in winter conditions against (a) synoptic observations in Europe, (b) observations at a 48 m high micrometeorological mast in Sodankylä, northern Finland, and (c) observations at the Helsinki Testbed stations: (i) to evaluate the skills of the models to compute nocturnal 2 m air temperature (T2m) and the temperature inversion; and (ii) to distinguish between the T2m bias and the subgrid‐scale spatial variability of T2m. The models were (1) the Integrated Forecast System (IFS) of the European Centre for Medium‐Range Weather Forecasts (ECMWF), (2) the High Resolution Limited Area Model (HIRLAM), (3) the Applications of Research to Operations at Mesoscale (AROME) developed by Météo‐France, and (4) the Global Forecasting System (GFS) of the US National Center for Environmental Predictions (NCEP). The results demonstrated a T2m bias increasing with decreasing temperature and strengthening temperature inversion. When a strong temperature inversion was observed in Sodankylä, the models underestimated it, whereas in near‐neutral conditions the stratification was overestimated. Comparison of observed and modelled 3 h temperature tendencies showed that the T2m tendency in the models was on average only 17–20% of the observed one. The warm bias in T2m forecast in Sodankylä during periods of observed temperature inversion partly resulted from a warm bias in the initial conditions. This was due to problems in data assimilation in IFS and HIRLAM, in initialization in AROME, and in either or both procedures in GFS. In particular, the IFS data assimilation increased the T2m bias. Evaluation of modelled T2m against grid‐averaged T2m observed at Helsinki Testbed demonstrated that the T2m model error dominated over the spatial variability of observed T2m. This suggests that over an almost flat terrain horizontal resolution is not a major factor for the accuracy of T2m forecast at low T2m typically associated with temperature inversions. Copyright © 2012 Royal Meteorological Society
Modeling the quiet time inner plasma sheet protons

In order to understand the characteristics of the quiet time inner plasma sheet protons, we use a modified version of the Magnetospheric Specification Model to simulate the bounce averaged electric and magnetic drift of isotropic plasma sheet protons in an approximately self-consistent magnetic field. Proton differential fluxes are assigned to the model boundary to mimic a mixed tail source consisting of hot plasma from the distant tail and cooler plasma from the low latitude boundary layer (LLBL). The source is local time dependent and is based on Geotail observations and the results of the finite tail width convection model. For the purpose of self-consistently simulating plasma motion and a magnetic field, the Tsyganenko 96 magnetic field model is incorporated with additional adjustable ring-current shaped current loops. We obtain equatorial proton flow and midnight and equatorial profiles of proton pressure, number density, and temperature. We find that our results agree well with observations. This indicates that the drift motion dominates the plasma transport in the quiet time inner plasma sheet. Our simulations show that cold plasma from the LLBL enhances the number density and the proton pressure in the inner plasma sheet and decreases the dawn-dusk asymmetry of the equatorial proton pressure. From our approximately force-balanced simulations the magnetic field responds to the increase of pressure gradient force in the inner plasma sheet by changing its configuration to give a stronger magnetic force. At the same time, the plasma dynamics is affected by the changing field configuration and its associated pressure gradient force becomes smaller. Our model predicts a quiet time magnetic field configuration with a local depression in the equatorial magnetic field strength at the inner edge of the plasma sheet and a cross-tail current separated from the ring current, results that are supported by observations. A scale analysis of our results shows that in the inner plasma sheet the magnitude of the Hall term in the generalized Ohm's law is not small compared with the quiet time electric field. This suggests that the frozen-in condition E = −v×B is not valid in the inner plasma sheet and that the Hall term needs to be included to obtain an appropriate approximation of the generalized Ohm's law in that region.
Why Do People Choose Different Social Media Platforms? Linking Use Motives With Social Media Affordances and Personalities

Drawing on uses and gratifications (U&G) theory, the current research investigates how social media users exploit different media affordances to satisfy their motives and how such motives are shaped by their personalities. A cross-sectional survey among college students (N = 190) was conducted to examine their most frequently used social media platforms, use motives, and perceived media affordances. Their personalities were also assessed along the Big Five and narcissism. An exploratory factor analysis yielded five broad categories of social media use motives. Structural equation modeling results revealed that social media use motives were differentially associated with affordances and that personalities play an influential role in shaping individuals’ use motives and affordance preferences. The findings are discussed in relation to the theoretical contributions to the U&G approach as well as the practical implications to social media platform design and development.
Parkinson disease following COVID‐19: Report of six cases

Core clinical manifestations of COVID‐19 include influenza‐like and respiratory symptoms. However, it is now evident that neurological involvement may occur during SARS‐CoV‐2 infection, covering an extensive spectrum of phenotypical manifestations. A major challenge arising from this pandemic is represented by detecting emerging neurological complications following recovery from SARS‐CoV‐2 infection. To date, a few post‐COVID‐19‐infected subjects diagnosed with Parkinson disease (PD) have been described, raising the possibility of a connection between the infection and neurodegenerative processes. Here, we describe a case series of six subjects who developed PD after COVID‐19.
Novel time-stamped pixel structure for high-speed 2D CMOS visual motion sensor

A 32x32 visual motion sensor based on the time stamped pixel structure is proposed. The sensor pixel is formed by a time stamp component and a compact spatial based edge detector with a pixel size of 70x70μm2 in standard 0. 35μm CMOS process. It measures up to 6000 degree/s with focal length f = 10mm. Less than 5% rms variation for middle range velocity measurement and less than 10% rms variation for high and low velocity measurement have been achieved. This structure is good for scaling down with new fabrication processes to implement large scale 2D arrays with low power consumption in the near future.
Continuous decision to wait for a future reward is guided by fronto-hippocampal anticipatory dynamics

Deciding whether to wait for a future reward is crucial for acquiring rewards in an uncertain world and involves anticipating future reward attainment. While seeking for a reward in natural environments, behavioral agents constantly face a trade-off between staying in their current environment or leaving it. It remains unclear, however, how humans make continuous decisions in such situations. Here we show that anticipatory brain activity in the anterior prefrontal cortex (aPFC) and hippocampus underpins continuous stay-leave decision making. Human participants awaited for real liquid rewards available after tens of seconds, and continuous decision was tracked by monitoring dynamic patterns of brain activity. Participants stopped waiting more frequently and sooner after they experienced longer delays and received smaller rewards. When dynamic activity reflecting the anticipation of a future reward was enhanced in the aPFC, participants remained in their current environment, but when this activity diminished, they left the environment for a new one. The anticipatory activity in the aPFC and hippocampus was associated with distinct decision strategies; aPFC activity was enhanced in participants adopting a leave strategy, whereas those remaining stationary showed enhanced activity in the hippocampus. Our results suggest that fronto-hippocampal anticipatory dynamics underlie continuous decision making while anticipating a future reward.
Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities

Gene regulation plays a critical role in the cellular processes that underlie human health and disease. The regulatory relationship between transcription factors (TFs), key regulators of gene expression, and their target genes, the so called TF regulons, can be coupled with computational algorithms to estimate the activity of TFs. However, to interpret these findings accurately, regulons of high reliability and coverage are needed. In this study, we present and evaluate a collection of regulons created using the CollecTRI meta-resource containing signed TF-gene interactions for 1,183 TFs. In this context, we introduce a workflow to integrate information from multiple resources and assign the sign of regulation to TF-gene interactions that could be applied to other comprehensive knowledge bases. We find that the signed CollecTRI-derived regulons outperform other public collections of regulatory interactions in accurately inferring changes in TF activities in perturbation experiments. Furthermore, we showcase the value of the regulons by investigating hallmarks of TF activity profiles inferred from the transcriptomes of three different cancer types. Overall, the CollecTRI-derived TF regulons enable the accurate and comprehensive estimation of TF activities and thereby help to interpret transcriptomics data. GRAPHICAL ABSTRACT
Role of pioneer neurons and neuroblast behaviors on otic ganglion assembly

Cranial ganglia are aggregates of sensory neurons that mediate distinct types of sensation. It is little understood how individual neurons coalesce, distribute and shape the ganglion. The statoacoustic ganglion (SAG) displays several lobes spatially arranged to properly connect with hair cells of the inner ear. To investigate the cellular behaviors involved in the 3D organization of the SAG, we use high resolution confocal imaging of single cell labeled zebrafish neuroblasts (NB), photoconversion, photoablation and genetic perturbations. We find that otic NB delaminate out of the otic epithelium in an EMT-like manner, rearranging apical polarity and primary cilia proteins. We also show that, once delaminated, NB migrate directionally and actively, requiring RhoGTPases. Interestingly, cell tracking of individual delaminated NB reveals that NB migrate and coalesce around a small population of pioneer SAG neurons. These pioneer SAG neurons are not from otic placode origin and populate the coalescence region before otic neurogenesis begins. Upon ablation of these cells, migratory pathways of delaminated NB are disrupted and, consequently, SAG shape is affected. Altogether, this work shows for the first time the role of pioneer SAG neurons in orchestrating SAG development. Summary Statement Little is known how cranial sensory ganglia organize in 3D. We unveil the repertoire of cellular behaviours underlying statoacoustic morphogenesis and its dependence on relevant pioneer neurons.
Research in Disease-Gene Network Based on Bipartite Network Projection

A network of disorders and disease genes linked by disorder-gene associations offers a platform to explore all known phenotype and disease gene associations using graph theory.In this paper,we analyze the diseasome graph using a method called bipartite network projection which can explore the connection of nodes in the same group.The results show that genes associated with similar disorders show both higher likelihood of physical interactions between their products and higher expression profiling similarity for their transcripts.And this also indicates more clearly the common genetic origin of many diseases,which makes sense in disease prevention and medical diagnose.
An Analysis of Rht Parameters in 2d Numerical Simulation of Concrete Penetration with Composite Projectiles

The RHT concrete strength model and failure model are employed for the numerical simulations of composite projectile penetrating concrete targets. The simulations show that RHT parameters, specially the failure parameters, greatly influence the penetration depth, exit velocity. The failure mode of concrete should be paid great attentions in numerical analysis. If the crushing failure is the primary mechanism, RHT model seems effective. For the cracking process of concrete, the model should be tensile failure description. Reasonable material parameters are important in penetration simulations. Comparison between numerical analysis and experimental date is made for discussion about the parameter effects.
Oxaliplatin Inhibits RNA Polymerase I via DNA Damage Signaling Targeted to the Nucleolus

Platinum (Pt) compounds are an important class of anti-cancer therapeutics, but outstanding questions remain regarding their mode of action. In particular, emerging evidence indicates that oxaliplatin, a Pt drug used to treat colorectal cancer, kills cells by inducing ribosome biogenesis stress rather than through DNA damage generation, but the underlying mechanism is unknown. Here, we demonstrate that oxaliplatin-induced ribosomal RNA (rRNA) transcriptional silencing and nucleolar stress occur downstream of DNA damage signaling involving ATM and ATR. We show that NBS1 and TOPBP1, two proteins involved in the nucleolar DNA damage response (n-DDR), are recruited to nucleoli upon oxaliplatin treatment. However, we find that rRNA transcriptional inhibition by oxaliplatin does not depend upon NBS1 or TOPBP1, nor does oxaliplatin induce substantial amounts of nucleolar DNA damage, distinguishing it from previously characterized n-DDR pathways. Taken together, our work indicates that oxaliplatin induces a distinct DDR signaling pathway that functions in trans to inhibit Pol I transcription in the nucleolus, demonstrating how nucleolar stress can be linked to DNA damage signaling and highlighting an important mechanism of Pt drug cytotoxicity.
Movement and Alignment of Microtubules in Electric Fields and Electric-Dipole-Moment Estimates

The effects of both constant (up to 2 × 103 V/m) and high-frequency alternating fields (up to 2.1 × 105 V/m, 200 kHz to 2 MHz) on suspended microtubules are investigated. At pH 6.8 and 120 mM ionic strength, constant fields cause a motion of microtubules toward the anode. The electrophoretic mobility amounts to 2.6 × 10−4 cm2/Vs, reflecting a negative net charge of approximately 0.2 elementary charges per tubulin dimer. The moving microtubules are randomly space oriented. Alternating high-frequency fields induce electric dipoles and align the microtubules parallel to the field direction. By determining the angular velocity of the turning microtubules, we estimate a dipole moment of roughly 34,000 Debye at 2.1 × 105 V/m and 2 MHz. By comparing the potential energy of the dipole in the applied field with the thermal energy of microtubules, we obtain a minimum value of 6,000 Debye as necessary for an efficient alignment.
Induced neural phase precession through exogeneous electric fields

The gradual shifting of preferred neural spiking relative to local field potentials (LFPs), known as phase precession, plays a prominent role in neural coding. Correlations between the phase precession and behavior have been observed throughout various brain regions. As such, phase precession is suggested to be a global neural mechanism that promotes local neuroplasticity. However, causal evidence and neuroplastic mechanisms of phase precession are lacking so far. Here we show a causal link between LFP dynamics and phase precession. In three experiments, we modulated LFPs in humans, a non-human primate, and computational models using alternating current stimulation. We show that continuous stimulation of motor cortex oscillations in humans lead to a gradual phase shift of maximal corticospinal excitability by ∼90°. Further, exogenous alternating current stimulation induced phase precession in a subset of entrained neurons (∼30%) in the non-human primate. Multiscale modeling of realistic neural circuits suggests that alternating current stimulation-induced phase precession is driven by NMDA-mediated synaptic plasticity. Altogether, the three experiments provide mechanistic and causal evidence for phase precession as a global neocortical process. Alternating current-induced phase precession and consequently synaptic plasticity is crucial for the development of novel therapeutic neuromodulation methods.
Divergent proinflammatory immune responses associated with the differential susceptibility of cattle breeds to tuberculosis

Tuberculosis (TB) in the bovine is one of the most predominant chronic debilitating infectious diseases primarily caused by Mycobacterium bovis. Besides, the incidence of TB in humans due to M. bovis, and that in bovines due to M. tuberculosis-indicates cattle as a major reservoir of zoonotic TB. While India accounts for the highest global burden of both TB and multidrug-resistant TB in humans, systematic evaluation of bovine TB (bTB) prevalence in India is largely lacking. Recent reports emphasized markedly greater bTB prevalence in exotic and crossbred cattle compared to indigenous cattle breeds that represent more than one-third of the total cattle population in India, which is the largest globally. This study aimed at elucidating the immune responses underlying the differential bTB incidence in prominent indigenous (Sahiwal), and crossbred (Sahiwal x Holstein Friesian) cattle reared in India. Employing the standard Single Intradermal Tuberculin Test (SITT), and mycobacterial gene-targeting single as well as multiplex-PCR-based screening revealed higher incidences of bovine tuberculin reactors as well as Mycobacterium tuberculosis Complex specific PCR positivity amongst the crossbred cattle. Further, ex vivo mycobacterial infection in cultures of bovine peripheral blood mononuclear cells (PBMC) from SITT, and myco-PCR negative healthy cattle exhibited significantly higher intracellular growth of M. bovis BCG, and M. tuberculosis H37Ra in the crossbred cattle PBMCs compared to native cattle. In addition, native cattle PBMCs induced higher pro-inflammatory cytokines and signaling pathways, such as interferon-gamma (IFN-γ), interleukin-17 (IL-17), and tank binding kinase-1 (TBK-1) upon exposure to live mycobacterial infection in comparison to PBMCs from crossbred cattle that exhibited higher expression of IL-1β transcripts. Together, these findings highlight that differences in the innate immune responses of these cattle breeds might be contributing to the differential susceptibility to TB infection, and the resultant disparity in bTB incidence amongst indigenous, and crossbred cattle.
Determining epitope specificity of T-cell receptors with transformers

Motivation T-cell receptors (TCR) on T cells recognize and bind to epitopes presented by the major histocompatibility complex (MHC) in case of an infection or cancer. However, the high diversity of TCRs, as well as their unique and complex binding mechanisms underlying epitope recognition, make it difficult to predict the binding between TCR and epitope. Here, we present the utility of transformers, a deep learning strategy that incorporates an attention mechanism that learns the informative features, and show that these models pretrained on a large set of protein sequences outperform current strategies. Method We compared three pre-trained auto-encoder transformer models (ProtBERT, ProtAlbert, ProtElectra) and one pre-trained auto-regressive transformer model (ProtXLNet) to predict the binding specificity of TCRs to 25 epitopes from the VDJdb database (human and murine). Two additional modifications were performed to incorporate gene usage of the TCRs in the four transformer models. Results Of all 12 transformer implementations (4 models with 3 different modifications), a modified version of the ProtXLNet model could predict TCR-epitope pairs with the highest accuracy (weighted F1 score 0.55 simultaneously considering all 25 epitopes). The modification included additional features representing the gene names for the TCRs. We also showed that the basic implementation of transformers outperformed the previously available methods, i.e. TCRGP, TCRDist and DeepTCR, developed for the same biological problem, especially for the hard-to-classify labels. Conclusion We show that the proficiency of transformers in attention learning can indeed be made operational in a complex biological setting like TCR binding prediction. Further ingenuity in utilizing the full potential of transformers, either through attention head visualization or introducing additional features, can further extend T-cell research avenues. Availability Data and code are available on https://github.com/InduKhatri/tcrformer
The Influence of Coupled Sea Surface Temperatures on the Madden–Julian Oscillation: A Model Perturbation Experiment

Abstract In this study, the authors compare the Madden–Julian oscillation (MJO) variability in the Goddard Laboratory for Atmospheres atmospheric general circulation model for two different sea surface temperature (SST) boundary conditions. In the “control” simulation, the model employs specified annual cycle SSTs. In the “coupled” simulation, the model employs the same annual cycle SSTs but in addition is coupled to a slab ocean mixed layer that provides prognostic SST anomalies equatorward of 24°. The results show that the simplified interactive SST facilitates a better simulation with respect to a number of general model shortcomings associated with the MJO that were recently documented by Slingo et al. in an Atmospheric Model Intercomparison Project study. These improvements include 1) increased variability associated with the MJO, 2) a tendency for the timescales of the modeled intraseasonal variability to more closely match and consolidate around the timescales found in the observations, 3) a reduce.