Miracle-dz/UniFAR-FTUs huggingface dataset:
Face Recognition Based on Uncorrelated Multilinear PCA Plus Classical LDA

Subspace learning is an important direction in computer vision research. In this paper, a new method of face recognition based on uncorrelated multilinear principal component analysis (UMPCA) and linear discriminant analysis (LDA) is proposed. First, instead of transforming matrices into vectors for principal component analysis (PCA), UMPCA seeks a tensor-to-vector projection that captures most of the variation in the original tensorial input while producing uncorrelated features through successive variance maximization. A subset of features is extracted and the classical LDA is then applied to find the best subspaces. Finally, the comprehensive experiments are provided on AT&T databases and the experiment results show its superiority through the comparison with other PCA plus LDA based algorithms.
Brain Dissection: fMRI-trained Networks Reveal Spatial Selectivity in the Processing of Natural Images

The alignment between deep neural network (DNN) features and cortical responses currently provides the most accurate quantitative explanation for higher visual areas [1, 2, 3, 4]. At the same time, these model features have been critiqued as uninterpretable explanations, trading one black box (the human brain) for another (a neural network). In this paper, we train networks to directly predict, from scratch, brain responses to images from a large-scale dataset of natural scenes [5]. We then use “network dissection” [6], an explainable AI technique used for enhancing neural network interpretability by identifying and localizing the most significant features in images for individual units of a trained network, and which has been used to study category selectivity in the human brain [7]. We adapt this approach to create a hypothesis-neutral model that is then used to explore the tuning properties of specific visual regions beyond category selectivity, which we call “brain dissection”. We use brain dissection to examine a range of ecologically important, intermediate properties, including depth, surface normals, curvature, and object relations across sub-regions of the parietal, lateral, and ventral visual streams, and scene-selective regions. Our findings reveal distinct preferences in brain regions for interpreting visual scenes, with ventro-lateral areas favoring closer and curvier features, medial and parietal areas opting for more varied and flatter 3D elements, and the parietal region uniquely preferring spatial relations. Scene-selective regions exhibit varied preferences, as the retrosplenial complex prefers distant and outdoor features, while the occipital and parahippocampal place areas favor proximity, verticality, and in the case of the OPA, indoor elements. Such findings show the potential of using explainable AI to uncover spatial feature selectivity across the visual cortex, contributing to a deeper, more fine-grained understanding of the functional characteristics of human visual cortex when viewing natural scenes.
Large differences in collateral blood vessel abundance among individuals arise from multiple genetic variants

Collateral blood flow varies greatly among humans for reasons that remain unclear, resulting in significant differences in ischemic tissue damage. A similarly large variation has also been found in mice that is caused by genetic background-dependent differences in the extent of collateral formation, termed collaterogenesis—a unique angiogenic process that occurs during development and determines collateral number and diameter in the adult. Previous studies have identified several quantitative trait loci (QTL) linked to this variation. However, understanding has been hampered by the use of closely related inbred strains that do not model the wide genetic variation present in the “outbred” human population. The Collaborative Cross (CC) multiparent mouse genetic reference panel was developed to address this limitation. Herein we measured the number and average diameter of cerebral collaterals in 60 CC strains, their 8 founder strains, 8 F1 crosses of CC strains selected for abundant versus sparse collaterals, and 2 intercross populations created from the latter. Collateral number evidenced 47-fold variation among the 60 CC strains, with 14% having poor, 25% poor-to-intermediate, 47% intermediate-to-good, and 13% good collateral abundance, that was associated with large differences in post-stroke infarct volume. Genome-wide mapping demonstrated that collateral abundance is a highly polymorphic trait. Subsequent analysis identified: 6 novel QTL circumscribing 28 high-priority candidate genes harboring putative loss-of-function polymorphisms (SNPs) associated with low collateral number; 335 predicted-deleterious SNPs present in their human orthologs; and 32 genes associated with vascular development but lacking protein coding variants. This study provides a comprehensive set of candidate genes for future investigations aimed at identifying signaling proteins within the collaterogenesis pathway whose variants potentially underlie genetic-dependent collateral insufficiency in brain and other tissues.
The Impact of subicular VIP-expressing interneurons on seizure dynamics in temporal lobe epilepsy: Insights from preclinical models

Temporal lobe epilepsy (TLE) is a high burden neurological disorder, affecting millions of individuals worldwide. Despite extensive research, the exact mechanisms underlying TLE remain unknown. It has been suggested by recent studies that the subiculum may serve as a hub for seizure generalization in TLE. The need for studying subicular vasoactive intestinal polypeptide expressing interneurons (VIP-INs) has been highlighted in the literature; however, the role of subicular VIP-INs in TLE has not yet been studied. The aim of the current study is to assess the possible role of subicular VIP-INs in the pathophysiology of TLE and its interaction with circadian rhythm. We permanently inhibited neurotransmitter release selectively from VIP-INs of the ventral subiculum by injecting a viral vector expressing tetanus toxin light chain (AAV-TeLC) in epileptic as well as non-epileptic VIP-cre mice. Mice were then subjected to telemetric EEG recording for up to 50 days. In a subset of animals, the effect of bilateral injection of AAV-TeLC was assessed using local field potential recording. Furthermore, the possibility of manipulating seizures via stimulation of VIP-INs was explored by injecting a vector expressing GqDREADD.
Optimizing Cell Therapy by Sorting Cells with High Extracellular Vesicle Secretion

Critical challenges remain in clinical translation of extracellular vesicle (EV)-based therapeutics due to the absence of methods to enrich cells with high EV secretion. Current cell sorting methods are limited to surface markers that are uncorrelated to EV secretion or therapeutic potential. We developed a nanovial technology for enrichment of millions of single cells based on EV secretion. This approach was applied to select mesenchymal stem cells (MSCs) with high EV secretion as therapeutic cells for improving treatment. The selected MSCs exhibited distinct transcriptional profiles associated with EV biogenesis and vascular regeneration and maintained high levels of EV secretion after sorting and regrowth. In a mouse model of myocardial infarction, treatment with high-secreting MSCs improved heart functions compared to treatment with low-secreting MSCs. These findings highlight the therapeutic importance of EV secretion in regenerative cell therapies and suggest that selecting cells based on EV secretion could enhance therapeutic efficacy.
Microhabitat use of northern and southern flying squirrels in a recent hybrid zone

Secondary contact of closely related species may lead to hybridization if reproductive isolation is incomplete. Selection against hybrids may become reinforced if hybrid fitness is low. This can be evident from the divergence of isolating traits. We examined habitat use of northern (Glaucomys sabrinus (Shaw, 1801)) and southern (Glaucomys volans (Linnaeus, 1758)) flying squirrels in an area of secondary contact in Ontario, Canada. We looked at summer microhabitat use within sites of sympatry and allopatry to test for evidence of reinforcement due to diverging habitat use. We also examined differences in broad-scale habitat features at woodlots to determine predictors of species occurrence across sites. We used 18 years (2002 - 2019) of flying squirrel summer capture data from 6 sites along a north-south transect. Vegetation surveys were conducted at trap locations during summer 2016 to characterize the available microhabitats within sites. Site-level habitat variables were calculated using the collected microhabitat variables. We found microhabitat variables to be weak predictors of trap-level flying squirrel presence and we found no evidence of divergence in microhabitat use over the 18 years. Further, we found latitude, not broad-scale habitat, was the strongest predictor of site-level flying squirrel occurrence. Overall, our findings suggest that microhabitat-based isolation is not being reinforced between flying squirrels; however, hybridization may be limited to areas where climate and habitat is suitable for both species.
Unveiling Liquid-Crystalline Lipids in the Urothelial Membrane through Cryo-EM

The urothelium, a distinct epithelial tissue lining the urinary tract, serves as an essential component in preserving urinary tract integrity and thwarting infections. The asymmetric unit membrane (AUM), primarily composed of the uroplakin complex, constitutes a critical permeability barrier in fulfilling this role. However, the molecular architectures of both the AUM and the uroplakin complex have remained enigmatic due to the paucity of high-resolution structural data. In this study, we utilized cryo-electron microscopy to elucidate the three-dimensional structure of the uroplakin complex within the porcine AUM. While the global resolution achieved was 3.5 Å, we acknowledge that due to orientation bias, the resolution in the vertical direction was determined to be 6.3 Å. Our findings unveiled that the uroplakin complexes are situated within hexagonally arranged crystalline lipid membrane domains, rich in hexosylceramides. Moreover, our research rectifies a misconception in a previous model by confirming the existence of a domain initially believed to be absent, and pinpointing the accurate location of a crucial Escherichia coli binding site implicated in urinary tract infections. These discoveries offer valuable insights into the molecular underpinnings governing the permeability barrier function of the urothelium and the orchestrated lipid phase formation within the plasma membrane.
Application of Computational Fluid Dynamics

Application of Computational Fluid Dynamics to Aerosol Sampling and Concentration. (May 2007) Shishan Hu, B.S., Tsinghua University; M.S., Tsinghua/Shantou University Co-Chairs of Advisory Committee: Dr. Andrew R. McFarland Dr. Yassin A. Hassan An understanding of gas-liquid two-phase interactions, aerosol particle deposition, and heat transfer is needed. Computational Fluid Dynamics (CFD) is becoming a powerful tool to predict aerosol behavior for related design work. In this study, FLUENT 6 is used to analyze the performance of aerosol sampling and concentration devices including inlet components (impactors), cyclones, and virtual impactors. The ω − k model was used to predict particle behavior in Inline Cone Impactor (ICI) and Jet-in-Well impactor (JIW). Simulation provided excellent agreement with experimental test results for a compact ICI. In the JIW, compound impaction is shown to cause the device to have a smaller cutpoint Stokes number than the single impaction unit. The size ratio of the well-to-jet was analyzed to find its influence on the total and side collections. Simulation is used to analyze liquid film, flow structure, particle collection, pressure drop, and heating requirements for a bioaerosol sampling cyclone. A volume of fluid model is used to predict water film in an earlier cyclone. A shell-volume is
Spatial autocorrelation of the environment influences the patterns and genetics of local adaptation

Environmental heterogeneity can lead to spatially varying selection, which can, in turn, lead to local adaptation. Population genetic models have shown that the pattern of environmental variation in space can strongly influence the evolution of local adaptation. In particular, when environmental variation is highly autocorrelated in space local adaptation will more readily evolve. Despite this long-held prediction, the evolutionary genetic consequences of different patterns of environmental variation have not been thoroughly explored. In this study, simulations are used to model local adaptation to different patterns of environmental variation. The simulations confirm that local adaptation is expected to increase with the degree of spatial autocorrelation in the selective environment, but also show that highly heterogeneous environments are more likely to exhibit high variation in local adaptation, a result not previously described. Spatial autocorrelation in the environment also influences the evolution and genetic architecture of local adaptation, with different combinations of allele frequency and effect size arising under different patterns of environmental variation. These differences influence the ability to characterise the genetic basis of local adaptation in different environments. Finally, I analyse a large-scale provenance trial conducted on lodgepole pine and find suggestive evidence that spatially autocorrelated environmental variation leads to stronger local adaptation in natural populations of lodgepole pine. Overall, this work emphasizes the profound importance that the spatial pattern of selection can have on the evolution of local adaptation and how spatial autocorrelation should be considered when formulating hypotheses in ecological and genetic studies. Lay Summary Many species exhibit local adaptation to environmental variation across their ranges. Theoretical population genetics predicts that the evolution of local adaptation and patterns of genetic variation underlying it will be influenced by the spatial pattern of variation across a species’ range. However, this prediction has not been thoroughly explored for cases of complex heterogeneous landscapes. In this paper, I analyse simulations and empirical data to characterise the effects that the spatial pattern of environmental variation can have on the evolution of local adaptation and the genetics underlying it. From these analyses, I show that the pattern of environmental variation influences the average level of local adaptation, variation in local adaptation as well as the genetics underlying this important phenomenon.
Vigilance & Cognitive Flexibility: The Effect of Martial Arts Experience on Task Switching

Martial Arts can be considered both a sport and a therapy, combining physical exercise with intense periods of concentration (similar to meditation). Previous research suggests that both exercise and meditation can lead to improvements in executive functions (i.e., cognitive flexibility) in adult participants. Results from our lab have previously suggested that martial artists show improvements in the alerting attentional network – a measure of vigilance. The current research aims to investigate the impact of Martial Arts training on a task-switching protocol to measure both vigilance and cognitive flexibility in typical adults. Here we recruited adult martial artists with at least two years of experience, and control participants with no experience. Participants had to respond to either the shape or the colour of a figure in pure and mixed blocks to provide measures of mixing costs (sustained vigilance) and switching costs (cognitive flexibility). Results demonstrated martial artists did not differ from controls in the pure block, but displayed improved performance in the mixed block, revealing an improvement in mixing costs (vigilance). These benefits in vigilance mirror those previously found in attentional tasks, providing convergent evidence on the impact of Martial Arts training on vigilance.
Eﬀect of sheared E × B ﬂow on the blob dynamics in the scrape-oﬀ layer of HL-2A tokamak

The effect of sheared E × B ﬂow on the blob dynamics in the scrape-off layer (SOL) of HL-2A tokamak has been studied during the plasma current ramp-up in ohmically heated deuterium plasmas by the combination of poloidal and radial Langmuir probe arrays. The experimental results indicate that the SOL sheared E × B ﬂow is substantially enhanced as the plasma current exceeds a certain value and the strong sheared E × B ﬂow has the ability to slow the blob radial motion via stretching its poloidal correlation length. The locally accumulated blobs are suggested to be responsible for the increase of plasma density just outside the Last Closed Flux Surface (LCFS) observed in this experiment. The results presented here reveal the signiﬁcant role played by the strong sheared E × B ﬂow on the blob dynamics, which provides a potential method to control the SOL width by modifying the sheared E × B ﬂow in future tokamak plasmas.
Perfectionism and writing anxiety as predictors of Iranian EFL learners’ performance in IELTS writing module: a multi-dimensional perspective

This study aimed to investigate the relationship between Iranian EFL Learners’ perfectionism and writing anxiety and their performance in the IELTS Writing Module. To this end, sixty-eight Iranian EFL learners were selected via convenience sampling. Multidimensional Perfectionism Scale developed and validated by Hewitt and Flett (1991) and Second Language Writing Anxiety Inventory devised by Cheng (2004) were administered to the participants. The participants were then asked to write on an assigned topic from IELTS Writing Task 2. The findings of the study indicated that of the three dimensions of perfectionism (i.e., self-oriented, other-oriented and socially prescribed), none were associated with the learners’ writing performance, while a significant negative relationship was found between the learners’ writing anxiety consisting of somatic anxiety, cognitive anxiety, and avoidance behavior and their writing performance. The results of multiple regression analysis suggested that somatic anxiety, and avoidance behavior were significant predictors of writing performance. The implications highlight the strategies that should be deployed by educational policy-makers, practitioners, and examiners to alleviate anxiety in L2 classrooms, promoting a safe and stress-free educational environment.
Correlating nanoscale motion and ATP production in healthy and favism erythrocytes: a real-time nanomotion sensor study

Introduction Red blood cells (RBCs) are among the simplest, yet physiologically relevant biological specimens, due to their peculiarities, such as their lack of nucleus and simplified metabolism. Indeed, erythrocytes can be seen as biochemical machines, capable of performing a limited number of metabolic pathways. Along the aging path, the cells’ characteristics change as they accumulate oxidative and non-oxidative damages, and their structural and functional properties degrade. Methods In this work, we have studied RBCs and the activation of their ATP-producing metabolism using a real-time nanomotion sensor. This device allowed time-resolved analyses of the activation of this biochemical pathway, measuring the characteristics and the timing of the response at different points of their aging and the differences observed in favism erythrocytes in terms of the cellular reactivity and resilience to aging. Favism is a genetic defect of erythrocytes, which affects their ability to respond to oxidative stresses but that also determines differences in the metabolic and structural characteristic of the cells. Results Our work shows that RBCs from favism patients exhibit a different response to the forced activation of the ATP synthesis compared to healthy cells. In particular, the favism cells, compared to healthy erythrocytes, show a greater resilience to the aging-related insults which was in good accord with the collected biochemical data on ATP consumption and reload. Conclusion This surprisingly higher endurance against cell aging can be addressed to a special mechanism of metabolic regulation that permits lower energy consumption in environmental stress conditions.
Aberrant brain entropy in posttraumatic stress disorder comorbid with major depressive disorder during the coronavirus disease 2019 pandemic

Aim Previously, neuroimaging studies on comorbid Posttraumatic-Major depression disorder (PTSD-MDD) comorbidity found abnormalities in multiple brain regions among patients. Recent neuroimaging studies have revealed dynamic nature on human brain activity during resting state, and entropy as an indicator of dynamic regularity may provide a new perspective for studying abnormalities of brain function among PTSD-MDD patients. During the COVID-19 pandemic, there has been a significant increase in the number of patients with PTSD-MDD. We have decided to conduct research on resting-state brain functional activity of patients who developed PTSD-MDD during this period using entropy. Methods Thirty three patients with PTSD-MDD and 36 matched TCs were recruited. PTSD and depression symptoms were assessed using multiple clinical scales. All subjects underwent functional magnetic resonance imaging (fMRI) scans. And the brain entropy (BEN) maps were calculated using the BEN mapping toolbox. A two-sample t-test was used to compare the differences in the brain entropy between the PTSD-MDD comorbidity group and TC group. Furthermore, correlation analysis was conducted between the BEN changes in patients with PTSD-MDD and clinical scales. Results Compared to the TCs, PTSD-MDD patients had a reduced BEN in the right middle frontal orbital gyrus (R_MFOG), left putamen, and right inferior frontal gyrus, opercular part (R_IFOG). Furthermore, a higher BEN in the R_MFOG was related to higher CAPS and HAMD-24 scores in the patients with PTSD-MDD. Conclusion The results showed that the R_MFOG is a potential marker for showing the symptom severity of PTSD-MDD comorbidity. Consequently, PTSD-MDD may have reduced BEN in frontal and basal ganglia regions which are related to emotional dysregulation and cognitive deficits.
An advanced total variation model in H-1 space for image inpainting

Image inpainting is to restore a damaged image with missing information – a fundamental problem and a hot research area in image processing. Many approaches, both geometry oriented and texture oriented, have been proposed on inpainting such as total variation (TV), Criminisi algorithm, etc. However, these approaches suffer from either limitations such as only suitable for small areas (cracks), staircase effect (discontinuity), or inefficient (time-consuming) to search the best matched patch (for filling-in). In this paper we propose a novel approach based on partial differential equation (PDE) and isophotes direction, named as Isophotes-TV-H-1. A corrupted image is first decomposed into two parts: the cartoon (smooth parts and edges of the image) and the texture. The cartoon part is inpainted through Isophotes- TV-H-1 while the texture part is done by an enhanced Criminisi algorithm which reduces the searching time for match and gives more reasonable match patches. The results of experiments on several images have demonstrated that, compared to existing methods, the proposed solution can recover the texture (of the damaged region) better, suppress error propagation and solve the problem of intensity discontinuity.