Miracle-dz/UniFAR-FTUs huggingface dataset:
Let’s Connect: Diversity, Inclusion and Career Development of Veterans Within the Civilian Workforce

: Career transition can be stressful. This stress level is intensified for veterans who are transitioning between not only careers but also, what is perceived to be, transitioning between worlds, military world to the civilian world. Within a civilian workforce, veterans are often misunderstood and stigmatized, that results in misconceptions and misinterpretation regarding transfer of professional experience and training. Subsequently, creating employment challenges, exclusion, and minimal career development of veterans within the civilian workforce. On this premise, this theoretical paper, utilizing the workforce adjustment theory as an underpinning, discusses: (a) transitional challenges of veterans to the civilian workforce,( b) strategies for promoting diversity and inclusion of veterans, and (c) career development of veterans within the civilian workforce.
Board Diversity, Firm Performance, Dividend Payout and Corporate Social Responsibility

Existing research on corporate board diversity has focused on gender and ethnic diversity. This research considers eight dimensions of diversity on board members (gender, education, tenure, professionalism, independence, busyness, political connection and cross-cultural experience). It borrows the Simpson Index from biodiversity in constructing the overall board diversity index. Then, this research examines how the constructed board diversity index affects financial performance, performance volatility, dividend payout and performance on Corporate Social Responsibility (CSR). The samples are listed non-financial companies on the Taiwan Stock Exchange (TWSE), and yearly data of 2010 to 2015 is employed. Through summary statistics, correlation analysis and multiple regression estimations, empirical evidence shows that the higher the diversity of the firm's board of directors, the better the financial performance and the greater the firm's value. The firm's dividend payout and CSR performance are also positively associated with the board diversity index. The empirical result generally shows that diversity on board members should be considered to form a corporate board.
ApkDiff: Matching Android App Versions Based on Class Structure

Reverse engineering an application requires attackers to invest time and effort doing manual and automatic analyses. When a new version of the application is released, this investment could be lost completely, if all the analyses had to be re-done. The gained insights into how an application functions might be transferred from one version to the next, however, if the versions do not differ too much. Diffing tools are thus valuable to reverse engineers attempting to transfer their knowledge across versions, as well as to defenders trying to assess this attack vector, and whether or how much a new version has to be diversified. While such diffing tools exist and are in widespread use for binary applications, they are in short supply for Android apps. This paper presents ApkDiff, a tool for diffing Android apps based on the semantic features of the class structure. To evaluate our tool we selected 20 popular financial apps available in the Google Play Store, and tracked their version updates over eight months. We found that on average 79% of all classes had a unique match across version updates. When we consider only classes for which we detect explicit obfuscations being applied (by applying heuristics on their identifiers), we still find that we can find a match for 56% of the classes (ranging from 23% to 85%), suggesting that these obfuscated apps are not resilient to our matching strategies. Our results suggest that ApkDiff provides a valuable approach to diffing Android apps.
Writing infrastructure with the fabric of digital life platform

Teaching writing involves helping students develop as critical communicators who use writing to question often-unseen systems of power enabled by infrastructures, including digital spaces and technologies. This article uses Walton, Moore, and Jones' (2019) 3Ps Framework---positionality, privilege, and power---to explore how, through assignments we developed incorporating the Fabric of Digital Life digital archive, instructors can make visible to students the invisible layers of infrastructure. Using the 3Ps framework, we illustrate how our pedagogical approach encourages students to use writing to interrogate digital infrastructure and the ways it is entangled with positionality, privilege, and power.
Extracting journeys from truck GPS traces

In this paper we propose a method called START for automatically extracting journeys from truck GPS traces. Each journey represents a movement of a truck from a task place (e.g., a cargo station) to another task place, possibly with multiple stops in between for non-task purposes (resting, eating, refueling, etc.). The START method begins with detecting stops. Then it classifies each detected stop as a task stop or a non-task stop. For stop classification, START utilizes a novel feature called route-detour and combines it with a set of temporal features and place category features. The method further clusters detected stops and applies a majority voting to consolidate the classification of the member stops in each cluster. We evaluate START using real-world data and compare it with a baseline method that uses only temporal and place category features. The results show that START achieves a better stop classification accuracy than the baseline method. Finally, we demonstrate the utility of START via using the journeys extracted by START to build and evaluate an ML-based ETA prediction model.
Cortical Activation Reorganization of Cerebral Regions in Charcot– Marie–Tooth Patients: A Task-state Functional Magnetic Resonance Imaging Study

Background : Evidence of altered brain functional activation in response to different tasks has been reported in some peripheral neuropathies. The aim of this study was to investigate possible central nervous system modifications using task-state Functional Magnetic Resonance Imaging (FMRI) in Charcot–Marie–Tooth patients. Methods: A design of ankle dorsiflexion-plantarflexion and fist clutching paradigm was adopted at a frequency of 1 Hz in the FMRI portion in CMT patients and healthy controls. We acquired 3.0T MRI brain scans. The brain activation MR signals were recorded and a paired voxel-wise t-test was performed. The correlations between FMRI measurement and clinical variables were calculated.
Application and prospects of robotic surgery in children: a scoping review

As an innovative minimally invasive surgical technology, robot-assisted surgery (RAS) has greatly improved the accuracy and safety of surgery through the advantages of three-dimensional magnification, tremor filtering, precision and flexibility, and has been carried out by an increasing number of surgeries. In recent years, robots have been gradually applied to children, bringing new ideas and challenges to pediatric surgeons. This review will describe the advantages and limitations of robotic surgery in children, summarize its application in pediatric surgery, and provide an outlook. It is believed that clinicians should actively carry out RAS under the premise of rigorously ensuring surgical indications and strive to improve the efficacy of surgical treatment for children.
Neotelomere formation by human telomerase

The maintenance of genome integrity requires that telomerase action be limited to telomeres and not convert DSBs into neotelomeres. Using the breakpoint sequence from an apparent germline neotelomere formation event, we developed an assay to detect and quantify telomeric repeat addition at Cas9-programmed DSBs in human cells. The data show that telomerase can add telomeric repeats to DSBs and that this process can generate functional neotelomeres. Neotelomere formation is increased when telomerase is overexpressed, suggesting that in most human cells, low (or absent) telomerase activity limits the deleterious effects of de novo telomere addition. We show that neotelomere formation at DSBs is inhibited by long-range resection and the accompanying activation of ATR signaling. Our findings reveal that telomerase can cause genome instability by generating neotelomeres at DSBs. We propose that neotelomere formation can promote tumorigenesis by ending detrimental breakage-fusion-bridge cycles in cancer cells whose genome alterations engender dicentric chromosomes.
Copper-independent lysosomal localization of the Wilson disease protein ATP7B 3

Synopsis: Excess copper is toxic to the cell. In Hepatocytes, the Wilson disease protein, ATP7B has been reported 15 to recycle between the trans-Golgi network and lysosomes to export copper in elevated copper condition. We for 16 the first time show that a large fraction of ATP7B constitutively reside on the lysosome and rather the position of 17 the lysosome shifts from TGN-proximal to peripheral region of the cell in high copper to facilitate ATP7B- 18 mediated lysosomal exocytosis of copper. Abstract 23 24 In hepatocytes, the Wilson disease protein, ATP7B resides on trans-Golgi network and traffics to peripheral 25 lysosomes to export excess intracellular copper by means of lysosomal exocytosis. We found that in basal copper 26 or even upon copper chelation, a significant amount of ATP7B persists on endolysosomal compartment of 27 hepatocytes but not in non-hepatic cells. These ATP7B-harboring lysosomes lie in close proximity of < 40 nm to 28 the TGN. ATP7B constitutively distributes itself between the the sub-domain of the TGN with a lower pH and 29 the TGN-proximal lysosomal compartments. Localization of ATP7B on TGN-Lysosome hybrid compartments 30 upon Golgi disruption suggested possible exchange of ATP7B directly between the TGN and its proximal 31 lysosomes. Manipulating lysosomal positioning significantly alters the localization of ATP7B in the cell. Contrary 32 to previous understanding, we found that upon copper chelation in a copper replete hepatocyte, ATP7B is not 33 retrieved back to TGN from peripheral lysosomes; rather ATP7B recycles to these TGN-proximal lysosomes to 34 initiate the next cycle of copper transport. We report a hitherto unknown copper-independent localization of 35 ATP7B i.e., at the lysosomes and also the importance of TGN-proximal lysosomes but not TGN as the terminal 36 acceptor organelle of ATP7B in its retrograde pathway. 37
Phase leads between oscillatory visual stimuli induce a salience illusion

Neuronal populations often engage in oscillations, and corresponding theories and computational models propose that this affects their impact on other neurons. Specifically, when two neuronal populations oscillating at similar frequencies compete for impact, the phase-leading one might have an advantage by providing inputs to target neurons earlier. Here, we provide direct empirical support by driving visual neuronal responses with oscillating stimuli. We superimposed two orthogonal grating stimuli of temporally oscillating intensities, whose phase relations were precisely controlled. The leading stimulus was perceived as oscillating more intensely. This held for phase leads of a few milliseconds, and for each participant and almost every trial. Thus, we found a strong perceptual illusion directly predicted by theories on the functional role of oscillations for neuronal interactions.
Polarization tagging of two-photon double ionization by elliptically polarized XUV pulses

This work was supported by the WWTF through Project No. MA14-002, and the FWF through Projects No. FWF-SFB041-VICOM, No. FWF-SFB049-NEXTlite, and No. FWF-W1243-Solids4Fun, as well as the IMPRS-APS. J.F. acknowledges support by the Spanish MINECO through a Ramon y Cajal grant and the “Maria de Maeztu” program for Units of Excellence in R&D (MDM-2014-0377)
Mouse Behavior on the Trial-Unique Nonmatching-to-Location (TUNL) Touchscreen Task Reflects a Mixture of Distinct Working Memory Codes and Response Biases

The trial-unique nonmatching to location (TUNL) touchscreen task shows promise as a translational assay of working memory (WM) deficits in rodent models of autism, ADHD, and schizophrenia. However, the low-level neurocognitive processes that drive behavior in the TUNL task have not been fully elucidated. In particular, it is commonly assumed that the TUNL task predominantly measures spatial WM dependent on hippocampal pattern separation, but this proposition has not previously been tested. In this project, we tested this question using computational modeling of behavior from male and female mice performing the TUNL task (N = 163 across three datasets; 158,843 trials). Using this approach, we empirically tested whether TUNL behavior solely measured retrospective WM, or whether it was possible to deconstruct behavior into additional neurocognitive subprocesses. Overall, contrary to common assumptions, modeling analyses revealed that behavior on the TUNL task did not primarily reflect retrospective spatial WM. Instead, behavior was best explained as a mixture of response strategies, including both retrospective WM (remembering the spatial location of a previous stimulus) and prospective WM (remembering an anticipated future behavioral response) as well as animal-specific response biases. These results suggest that retrospective spatial WM is just one of a number of cognitive subprocesses that contribute to choice behavior on the TUNL task. We suggest that findings can be understood within a resource-rational framework, and use computational model simulations to propose several task-design principles that we predict will maximize spatial WM and minimize alternative behavioral strategies in the TUNL task. SIGNIFICANCE STATEMENT Touchscreen tasks represent a paradigm shift for assessment of cognition in nonhuman animals by automating large-scale behavioral data collection. Their main relevance, however, depends on the assumption of functional equivalence to cognitive domains in humans. The trial-unique, delayed nonmatching to location (TUNL) touchscreen task has revolutionized the study of rodent spatial working memory. However, its assumption of functional equivalence to human spatial working memory is untested. We leveraged previously untapped single-trial TUNL data to uncover a novel set of hierarchically ordered cognitive processes that underlie mouse behavior on this task. The strategies used demonstrate multiple cognitive approaches to a single behavioral outcome and the requirement for more precise task design and sophisticated data analysis in interpreting rodent spatial working memory.
Association of intrinsic functional connectivity between the locus coeruleus and salience network with attentional ability

The LC is a brainstem region associated with broad physiological and neural arousal as part of the release of norepinephrine, but it has increasingly been associated with multiple specific cognitive processes. These include sustained attention, deficits in which are associated with a variety of neuropsychological disorders. Neural models of attention deficits to date have focused on interrupted dynamics between the salience network (SAL) with the fronto-parietal network (FPN), which has been associated with task-switching and processing of external stimuli, respectively. Conflicting findings based on these regions suggest the possibility of upstream signaling leading to attention dysfunction, and recent research suggest the LC may play this role. In this study, resting-state functional connectivity (FC) and behavioral performance on an attention task was examined within 584 individuals. Analysis revealed significant clusters connected to the LC activity in the bilateral insula, anterior cingulate cortex (ACC), and bilateral ventral striatum, all regions associated with the SAL. Given previous findings that attention deficits may be caused by dysfunctions in network switching by the SAL, our findings here further suggest that dysfunction in LC signaling to the SAL may interfere with attention.
An Artificial Intelligence Framework for Optimal Drug Design

We introduce the concept of optimal drug design (ODD) as the use of an AI framework to optimize the exposure, safety, and efficacy of drugs. To exemplify the concept of ODD, we developed an artificial intelligence framework that integrates de novo molecular design, quantitative structure activity relationships, and pharmacokinetic-pharmacodynamic modeling. Specifically, our computational architecture has integrated a generative algorithm for small molecule design with a hybrid physiologically-based pharmacokinetic machine learning (PBPK-ML) model, which was applied to generate and optimize drug candidates for enhanced brain exposure. Publicly sourced data on the plasma and brain pharmacokinetics of 77 small molecule drugs in rats was used for model development. We have observed an approximate 30-fold and 120-fold increase on average in predicted brain exposure for AI generated molecules compared to known central nervous system drugs and randomly selected small organic molecules. We believe that with additional data and mechanistic modeling this in silico pipeline could facilitate the discovery of a new wave of optimally designed medicines for the treatment of CNS diseases. Graphical Abstract Artificial Intelligence Framework for the Optimization of Brain Pharmacokinetics. A genetic algorithm consisting of cross-breeding, mutating, scoring, and refining was used for de novo generation of a population of new molecular structures. SELFIE representations of molecules were used as input to a variational autoencoder for de novo generation/refinement of individual drug candidates. Molecular descriptors of individual drug candidates are generated and used as input into a trained neural network to generate drug-specific pharmacokinetic (PK) parameters. PK parameters are used as input into a physiologically-based pharmacokinetic (PBPK) model of the brain to predict brain PK of the drug candidate. Brain concentration-time profiles are integrated to obtain an area-under the curve (AUC), a metric of brain exposure, which is used to score and inform the design of new generations of molecules. Iterations of this framework generate novel drug candidates optimized for greater brain exposure. Created with BioRender.
First identification and investigation of piRNAs in the larval guts of Asian honey bee, Apis cerana

Piwi-interacting RNAs (piRNAs), a kind of small non-coding RNAs (ncRNAs), play pivotal parts in maintaining the genomic stability and modulating biological processes such as growth and development via regulation of gene expression. However, piRNAs in Asian honey bee (Apis cerana) is still largely unknown at present. In this current work, on basis of previously gained high-quality small RNA-seq datasets, piRNAs in the larval guts of Apis cerana cerana, the nominate species of A. cerana, was for the first time identified, followed by in-depth investigation of the regulatory roles of differentially expressed piRNAs (DEpiRNAs) in the developmental process of the A. c. cerana. Here, a total of 621 piRNAs were identified in the A. c. cerana larval guts, among which 499 piRNAs were shared by 4- (Ac4 group), 5- (Ac5 group), and 6-day-old (Ac6 group) larval guts, while the numbers of unique ones were 79, 37, and 11, respectively. piRNAs each group were ranged from 24 nt to 33 nt in length, and the first base of piRNAs had a cytosine (C) bias. Additionally, five up-regulated and five down-regulated piRNAs were identified in the Ac4 vs. Ac5 comparison group, 9 of which could target 9, 011 mRNAs; these targets were involved in 41 GO terms and 137 pathways. Comparatively, 22 up-regulated piRNAs were detected in the Ac5 vs. Ac6 comparison group, 21 of which could target 28, 969 mRNAs; these targets were engaged in 46 functional terms and 164 pathways. The results suggested the overall alteration of expression pattern of piRNAs during the developmental process of A. c. cerana larvae. Regulatory network analysis showed that piR-bmo-748815 and piR-bmo-512574 in the Ac4 vs. Ac5 comparison group as well as piR-bmo-716466 and piR-bmo-828146 in the Ac5 vs. Ac6 comparison group linked to the highest number of targets. Further investigation indicated that targets of DEpiRNAs in the above-mentioned two comparison groups could be annotated to several growth and development-associated pathways, such as Jak/STAT, TGF-β, and Wnt signaling pathways, indicating the involvement of DEpiRNAs in modulating larval gut development via these crucial pathways. Moreover, the expression trends of six randomly selected DEpiRNAs were verified using a combination of stem-loop RT-PCR and RT-qPCR. These results not only provide a novel insight into the development of the A. c. cerana larval guts, but also lay a foundation for uncovering the epigenetic mechanism underlying the larval gut development.
SMDT1 variants impair EMRE-mediated mitochondrial calcium uptake in patients with muscle involvement

Ionic calcium (Ca2+) is a key messenger in signal transduction and its mitochondrial uptake plays an important role in cell physiology. This uptake is mediated by the mitochondrial Ca2+ uniporter (MCU), which is regulated by EMRE (essential MCU regulator) encoded by the SMDT1 (single-pass membrane protein with aspartate rich tail 1) gene. This work presents the genetic, clinical and cellular characterization of two patients harbouring SMDT1 variants and presenting with muscle problems. Analysis of patient fibroblasts and complementation experiments provide evidence that these variants lead to absence of EMRE protein, induce MCU subcomplex formation and impair mitochondrial Ca2+ uptake. However, the activity of the oxidative phosphorylation enzymes, mitochondrial morphology and membrane potential, as well as routine/ATP-linked respiration were not affected. We hypothesize that the muscle-related symptoms in the patients with SMDT1 variants result from aberrant mitochondrial Ca2+ uptake.
Automated community ecology using deep learning: a case study of planktonic foraminifera

The development of deep learning methods using convolutional neural networks (CNNs) has revolutionised the field of computer vision in recent years. The automation of taxonomic identification using CNNs leads naturally to the use of such technology for rapidly generating large organismal datasets in order to study the evolutionary and ecological dynamics of biological communities across time and space. While CNNs have been used to train machine learning classifiers that can identify organisms to the species level for several groups, this vision of automated community ecology has yet to be thoroughly tested or fulfilled. Here, we present a case study of automated community ecology using a large dataset of Atlantic planktonic foraminifera for which the generation of species labels and morphometric measurements was completely automated. We compare standard community diversity metrics between the fully automated dataset and a “traditional” dataset with human-identified specimens. We show that there is high congruence between the results, and that machine classifications help avoid biases that can result in the inference of misleading biodiversity patterns. Our study demonstrates the viability and potential of fully automated community ecology and sets the stage for a new era of ecological and evolutionary inquiry driven by artificial intelligence.