Miracle-dz/UniFAR-FTUs huggingface dataset:
Personality and coping as gendered predictors of distress and well-being in nursing students

Introduction Previous studies about relationship between personality factors and stress related processes mainly focus on relation between these factors and application of coping strategies. Objectives This study expanded previous research by examining the combined contribution of personality traits (NEO-FFI) and coping strategies (Brief COPE) in the prediction of stress, depressive symptoms, anxiety symptoms (DASS-21), and psychological well-being (WHO-5) among undergraduate nursing students. Methods This cross-sectional study was performed in 2017. Participants of this study were 75 nursing students (men=37, women=38) from one Portuguese School of Health Sciences. The students who agreed to participate filled out an informed consent. Then the questionnaires were administered in a random order to avoid order effects in the data. Results Regarding personality, women reported higher conscientiousness and agreeableness than men. There were no gender differences in coping. Among men, openness and agreeableness (inversely) and neuroticism predicted stress. In women, neuroticism and venting predicted stress. Regarding depression, conscientiousness and extraversion (inversely) and neuroticism were predictors for men, whereas neuroticism, self-blame, and denial were predictors for women. Conscientiousness and extraversion (inversely) and venting and denial predicted anxiety in men, as did neuroticism and venting in women. For well-being, conscientiousness and extraversion were predictors among men; neuroticism and seeking instrumental support (inversely) and extraversion were predictors among women. Personality traits dominated the prediction of distress and well-being in men, while both personality and coping were predictors in women. Conclusions These findings indicate that it is not the degree of each personality trait or coping strategy but the pattern of relationship between these phenomena and psychological outcomes that is of relevance. The results could inform gendered preventive and treatment interventions for college students.
Quantification of Ionic Diffusion in Lead Halide Perovskite Single Crystals

Lead halide perovskites are mixed electronic–ionic semiconductors that have recently revolutionized the photovoltaics field. The physical characterization of the ionic conductivity has been rather elusive because of the high intermixing of ionic and electronic current. In this work, the synthesis of low defect density monocrystalline MAPbBr3 (MA = methylammonium) solar cells free of a hole transport layer (HTL) suppresses the effect of electronic current. Impedance spectroscopy reveals the characteristic signature of ionic diffusion (the Warburg element and transmission line equivalent circuit) and ion accumulation at the interface of MAPbBr3 with the external contacts. Diffusion coefficients are calculated based on a good correlation between thickness of MAPbBr3 and characteristic diffusion transition frequency. In addition, reactive external interfaces are studied by comparison of polycrystalline MAPbBr3 devices prepared either with or without a HTL. The low-frequency response in impedance spectroscopy .
Structure-function analysis of distant diphtheria toxin homologs reveals insights into host adaptation

Diphtheria toxin (DT) is the archetype of bacterial exotoxins implicated in human diseases and has played a central role in defining the field of toxinology since its discovery in 1888. Despite being one of the most extensively characterized bacterial toxins, the origins and molecular evolution of DT host specialization remain unknown. Here, we determined high-resolution structures of two recently discovered distant homologs of DT. These DT-like proteins from non-human associated Streptomyces albireticuli (17% identity to DT) and Seinonella peptonophila (20% identity to DT) display remarkable structural similarity to DT enabling a comparative investigation into DT’s unique toxicity toward mammalian cells. We find that the individual domains of DT-like toxins retain two critical features of DT’s activity: full catalytic function and ability to translocate across mammalian cell membranes. However, we show that receptor-binding, pH-dependent pore-formation and proteolytic release of the cytotoxic enzyme into the cytosol are not optimized for human cell physiology and thus unable to efficiently deliver the cytotoxic cargo into human hosts. Our work provides structural insights into DT’s evolutionary history, and implies key transitions required for the emergence of human-specificity of a major bacterial exotoxin with an important history in human disease.
No need to choose: independent regulation of cognitive stability and flexibility challenges the stability-flexibility tradeoff

Adaptive behavior requires the ability to focus on a current task and protect it from distraction (cognitive stability) as well as the ability to rapidly switch to another task in light of changing circumstances (cognitive flexibility). Cognitive stability and flexibility have been conceptualized as opposite endpoints on a stability-flexibility tradeoff continuum, implying an obligatory reciprocity between the two: greater flexibility necessitates less stability, and vice versa. Surprisingly, rigorous empirical tests of this critical assumption are lacking. Here, we acquired simultaneous measurements of cognitive stability (congruency effects) and flexibility (switch costs) on the same stimuli within the same task, while independently varying contextual demands on these functions with block-wise manipulations of the proportion of incongruent trials and task switches, respectively. If cognitive stability and flexibility are reciprocal, increases in flexibility in response to higher switch rates should lead to commensurate decreases in stability, and increases in stability in response to more frequent incongruent trials should result in decreased flexibility. Across three experiments, using classic cued task switching (Experiments 1 and 3) and attentional set shifting (Experiment 2) protocols, we found robust evidence against an obligatory stability-flexibility tradeoff. Although we observed the expected contextual adaptation of stability and flexibility to changing demands, strategic adjustments in stability had little influence on flexibility, and vice versa. These results refute the long-held assumption of a stability-flexibility tradeoff, documenting instead that the cognitive processes mediating these functions can be regulated independently – it is possible to be both stable and flexible at the same time.
Analysis of combinatorial chemokine receptor expression dynamics using multi-receptor reporter mice

Inflammatory chemokines and their receptors are central to the development of inflammatory/immune pathologies. The apparent complexity of this system, coupled with lack of appropriate in vivo models, has limited our understanding of how chemokines orchestrate inflammatory responses and has hampered attempts at targeting this system in inflammatory disease. Novel approaches are therefore needed to provide crucial biological, and therapeutic, insights into the chemokine-chemokine receptor family. Here, we report the generation of transgenic multi-chemokine receptor reporter mice in which spectrally-distinct fluorescent reporters mark expression of CCRs 1, 2, 3 and 5, key receptors for myeloid cell recruitment in inflammation. Analysis of these animals has allowed us to define, for the first time, individual and combinatorial receptor expression patterns on myeloid cells in resting and inflamed conditions. Our results demonstrate that chemokine receptor expression is highly specific, and more selective than previously anticipated.
Defining the pig microglial transcriptome reveals their core signature, regional heterogeneity, and similarity with humans

Microglia play key roles in brain homeostasis as well as responses to neurodegeneration and neuroinflammatory processes caused by physical disease and psychosocial stress. The pig is a physiologically-relevant model species for studying human neurological disorders, many of which are associated with microglial dysfunction. Furthermore, pigs are an important agricultural species, and there is a need to understand how microglial function affects their welfare. As a basis for improved understanding to enhance biomedical and agricultural research, we sought to characterise pig microglial identity at genome-wide scale and conduct inter-species comparisons. We isolated pig hippocampal tissue and microglia from frontal cortex, hippocampus and cerebellum, as well as alveolar macrophages from the lungs and conducted RNA-sequencing (RNAseq). By comparing the transcriptomic profiles between microglia, macrophages, and hippocampal tissue, we derived a set of 365 highly-enriched genes defining the porcine core microglial signature. We found brain regional heterogeneity based on 215 genes showing significant (adjusted p<0.01) regional variations and that cerebellar microglia were most distinct. We compared normalized gene expression for microglia from human, mice and pigs using microglia signature gene lists derived from each species and demonstrated that a core microglial marker gene signature is conserved across species, but that species-specific expression subsets also exist. Importantly, pig and human microglia shared greater similarity than pig and murine microglia. Our data provide a valuable resource defining the pig microglial transcriptome signature that highlights pigs as a useful large animal species bridging between rodents and humans in which to study the role of microglia during homeostasis and disease. Main Points - Defined a pig microglial transcriptome signature comprising 365 genes. - Demonstrated regional variance in the pig microglial transcriptome across the brain. - Revealed greater similarity between pig and human microglia than mouse.
Significance of High-Containment Biological Laboratories Performing Work During the COVID-19 Pandemic: Biosafety Level-3 and -4 Labs

High containment biological laboratories (HCBL) are required for work on Risk Group 3 and 4 agents across the spectrum of basic, applied, and translational research. These laboratories include biosafety level (BSL)-3, BSL-4, animal BSL (ABSL)-3, BSL-3-Ag (agriculture livestock), and ABSL-4 laboratories. While SARS-CoV-2 is classified as a Risk Group 3 biological agent, routine diagnostic can be handled at BSL-2. Scenarios involving virus culture, potential exposure to aerosols, divergent high transmissible variants, and zoonosis from laboratory animals require higher BSL-3 measures. Establishing HCBLs especially those at BSL-4 is costly and needs continual investments of resources and funding to sustain labor, equipment, infrastructure, certifications, and operational needs. There are now over 50 BSL-4 laboratories and numerous BSL-3 laboratories worldwide. Besides technical and funding challenges, there are biosecurity and dual-use risks, and local community issues to contend with in order to sustain operations. Here, we describe case histories for distinct HCBLs: representative national centers for diagnostic and reference, nonprofit organizations. Case histories describe capabilities and assess activities during COVID-19 and include capacities, gaps, successes, and summary of lessons learned for future practice.
Changes in essential oil content of Lippia citriodora in response to induction of bio-active compounds and plant growth regulators

Background & aim: Bioactive compounds and plant growth regulators could change a plant’s essential oil content and composition. In this study, the effect of bioactive compounds and plant growth regulators on lippia citriodora was investigated. Objective: This experiment was done with three replications on the basis of factorial experiment in randomized complete block design. The bio-regulators were sprayed in four levels, i.e. distilled water, 50 ppm gibberellic acid (GA3) + 50 ppm indole-3-butyric acid (IBA), 50 ppm GA3 + 100 ppm IBA, and 100 ppm GA3 + 50 ppm IBA. The chitosan was sprayed in two levels: distilled water and 400 ppm chitosan. The methanol was sprayed in two levels: distilled water and 5% v/v methanol. The essential oil was extracted by hydrodistillation method and analyzed by GC and GC/MS. Results: Thirty-two compounds were identified, representing 95.08% of the total essential oil. The main components were E-citral (geranial) (25.02%), Z-citral (neral) (16.04%), ar-curcumene (10.37%), caryophyllene oxide (9.56%), spathulenol (6.83%), limonene (4.99%) and (E)-caryophyllene (2.29%). The studied traits were significantly affected (p < 0.01) by the interaction of bioregulators, methanol and chitosan application. Conclusion: Foliar application of IBA, GA3, chitosan and methanol could increase aromatic values of L. citriodora essential oil.
Reconstructive phase transitions induced by temperature in gmelinite-Na zeolite

Abstract Gmelinite is a natural zeolite whose framework can be described as a parallel stacking of double six rings of tetrahedra in the ABAB sequence. Its space group is P63/mmc with a = 13.76 and c = 10.08 Å. This study describes the topological transformations of its Na-form |Na6.98K0. 27Ca0.15(H2O22.43)| [Al7.41Si16. 55O48]-GME, which occur when heating in air above 300 °C. Ex situ X-ray single-crystal analysis showed that gmelinite-Na transforms into a new structure with an AFI-type topology at about 300 °C. Its space group is P6/mcc with a = 13.80 and c = 8.50 Å. In situ X-ray powder diffraction patterns highlighted that, in the approximate 330–390 °C temperature range, GME → AFI transformation goes through a new intermediate phase whose topology differs from both GME and AFI. This phase transforms over the space of a few minutes into the AFI-type phase. This new “transient” phase is characterized by the presence of framework tetrahedra, which are only three-connected. Based on real time synchrotron powder diffraction data, the “transient” phase was modeled in space group P31c with a = 13.97 and c = 9.19 Å. Its crystal structure can be seen as an intermediate step between the GME and AFI crystal structures. The existence of this intermediate metastable phase could be due to the ~2 Å difference in the c parameter between the GME and AFI phases. The c parameter value in the “transient” metastable phase, which is roughly intermediate between the c value in GME and AFI, suggests that the “transient” phase exists as a way of avoiding the abrupt collapse of the GME structure along z direction during the GME-AFI topological transformation. The transformation of a natural gmelinite-Na in a material with AFI topology shows that it is possible to obtain Al-rich AFI materials whose properties are of particular importance in evaluating their potential as catalysts and adsorbents.
Yixin-Shu facilitated cardiac-like differentiation of mesenchymal stem cells in vitro

Yixin-Shu capsules (YXS) are a Chinese Materia Medica standardized product used for heart disease and their effectiveness has been demonstrated through both clinical and experimental research. However, the mechanism involved has remained unclear. The effect of YXS on the cardiac-like differentiation of mesenchymal stem cells was investigated in this study. The intestinal absorption liquid of YXS was prepared using an in vitro intestinal absorption method and 62 compounds have been identified. A compound-target-function network constructed by a network pharmacology-based approach indicated that these compounds had an effect on cell differentiation. The effects of YXS on cardiac-like differentiation of mesenchymal stem cells was verified by detecting cardiac-specific protein expression such as α-actinin, cardiac troponin-I and desmin through real time-PCR, western blotting and immunofluorescence staining. A network pharmacology analysis indicated that the facilitation of YXS on the cardiac-like differentiation may be through the TGF-β signaling pathway, Wnt signaling pathway and MAPK signaling pathway. The observed improvements on cardiac differentiation may be due to the novel molecular mechanism for YXS that could also benefit developments in cardiac tissue engineering.
The Polar 5 airborne measurement of turbulence and methane fluxes during the AirMeth campaigns

Abstract. Low level flights over tundra wetlands in Alaska and Canada have been conducted during the AirMeth campaigns to measure turbulent methane fluxes into the atmosphere. In this paper we describe the instrumentation and new calibration procedures for the essential pressure parameters required for turbulence sensing by an aircraft that exploit suitable regular measurement flight legs without the need for dedicated calibration patterns. We estimate the accuracy of the mean wind and the turbulence measurements. We show that airborne measurements of turbulent fluxes of methane and carbon dioxide using cavity ring down spectroscopy trace gas analysers together with established turbulence equipment achieves a relative accuracy similar to that of measurements of sensible heat flux if applied during low level flights over natural area sources. The inertial subrange of the trace gas fluctuations cannot be resolved due to insufficient high frequency precision of the analyser but since this scatter is uncorrelated with the vertical wind velocity, the covariance and thus the flux is reproduced correctly. In the covariance spectra the −7/3 drop-off in the inertial subrange can be reproduced if sufficient data are available for averaging. For convective conditions and flight legs of several tens of kilometers we estimate the flux detection limit to about 4 mg/m 2 /d for w'CH 4 ' , 1.4 g/m 2 /d for w'CO 2 ' , and 4.2 W/m 2 /s for the sensible heat flux.
Estimating the Variance of Estimator of the Latent Factor Linear Mixed Model Using Supplemented Expectation-Maximization Algorithm

This paper deals with symmetrical data that can be modelled based on Gaussian distribution, such as linear mixed models for longitudinal data. The latent factor linear mixed model (LFLMM) is a method generally used for analysing changes in high-dimensional longitudinal data. It is usual that the model estimates are based on the expectation-maximization (EM) algorithm, but unfortunately, the algorithm does not produce the standard errors of the regression coefficients, which then hampers testing procedures. To fill in the gap, the Supplemented EM (SEM) algorithm for the case of fixed variables is proposed in this paper. The computational aspects of the SEM algorithm have been investigated by means of simulation. We also calculate the variance matrix of beta using the second moment as a benchmark to compare with the asymptotic variance matrix of beta of SEM. Both the second moment and SEM produce symmetrical results, the variance estimates of beta are getting smaller when number of subjects in the simulation increases. In addition, the practical usefulness of this work was illustrated using real data on political attitudes and behaviour in Flanders-Belgium.
Dual Attention Network for Pitch Estimation of Monophonic Music

The task of pitch estimation is an essential step in many audio signal processing applications. In this paper, we propose a data-driven pitch estimation network, the Dual Attention Network (DA-Net), which processes directly on the time-domain samples of monophonic music. DA-Net includes six Dual Attention Modules (DA-Modules), and each of them includes two kinds of attention: element-wise and channel-wise attention. DA-Net is to perform element attention and channel attention operations on convolution features, which reflects the idea of "symmetry". DA-Modules can model the semantic interdependencies between element-wise and channel-wise features. In the DA-Module, the element-wise attention mechanism is realized by a Convolutional Gated Linear Unit (ConvGLU), and the channel-wise attention mechanism is realized by a Squeeze-and-Excitation (SE) block. We explored three kinds of combination modes (serial mode, parallel mode, and tightly coupled mode) of the element-wise attention and channel-wise attention. Element-wise attention selectively emphasizes useful features by re-weighting the features at all positions. Channel-wise attention can learn to use global information to selectively emphasize the informative feature maps and suppress the less useful ones. Therefore, DA-Net adaptively integrates the local features with their global dependencies. The outputs of DA-Net are fed into a fully connected layer to generate a 360-dimensional vector corresponding to 360 pitches. We trained the proposed network on the iKala and MDB-stem-synth datasets, respectively. According to the experimental results, our proposed dual attention network with tightly coupled mode achieved the best performance.
Symmetry of Dressed Photon

Motivated by describing the symmetry of a theoretical model of dressed photons, we introduce several spaces with Lie group actions and the morphisms between them depending on three integer parameters n≥r≥s on dimensions. We discuss the symmetry on these spaces using classical invariant theory, orbit decomposition of prehomogeneous vector spaces, and compact reductive homogeneous space such as Grassmann manifold and flag variety. Finally, we go back to the original dressed photon with n=4,r=2,s=1.
Biomechanical Study and Prediction of Lower Extremity Joint Movements Using Bayesian Regularization-Based Backpropagation Neural Network

This work aims to estimate the lower-limb joint angles in the sagittal plane using Microsoft Kinect-based experimental setup and apply an efficient machine learning technique for predicting the same based on kinematic, spatiotemporal, and biological parameters. Ten healthy participants from 19 to 50 years (33 ± 11.24 years) were asked to walk in front of the Kinect camera. Based on the skeleton image, the biomechanical hip, knee, and ankle joint angles of the lower-limb were measured using ni-labview. Thereafter, two Bayesian regularization-based backpropagation multilayer perceptron neural network models were designed to predict the joint angles in the stance and swing phase. The joint angles of two individuals, as a testing dataset, were predicted and compared with the experimental results. The test correlation coefficient for predicted joint angles has shown a promising effect of the proposed neural network models. Finally, a qualitative comparison was presented between the joint angles of healthy people and unhealthy people of similar age groups.