Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypoglycaemia combined with mild hypokalaemia reduces the heart rate and causes abnormal pacemaker activity in a computational model of a human sinoatrial cell

Low blood glucose, hypoglycaemia, has been implicated as a possible contributing factor to sudden cardiac death (SCD) in people with diabetes but it is challenging to investigate in clinical studies. We hypothesized the effects of hypoglycaemia on the sinoatrial node (SAN) in the heart to be a candidate mechanism and adapted a computational model of the human SAN action potential developed by Fabbri et al., to investigate the effects of hypoglycaemia on the pacemaker rate. Using Latin hypercube sampling, we combined the effects of low glucose (LG) on the human ether-a-go-go-related gene channel with reduced blood potassium, hypokalaemia, and added sympathetic and parasympathetic stimulus. We showed that hypoglycaemia on its own causes a small decrease in heart rate but there was also a marked decrease in heart rate when combined with hypokalaemia. The effect of the sympathetic stimulus was diminished, causing a smaller increase in heart rate, with LG and hypokalaemia compared to normoglycaemia. By contrast, the effect of the parasympathetic stimulus was enhanced, causing a greater decrease in heart rate. We therefore demonstrate a potential mechanistic explanation for hypoglycaemia-induced bradycardia and show that sinus arrest is a plausible mechanism for SCD in people with diabetes.
Linking cognition to ecology in wild sympatric mouse lemur species

Cognitive abilities covary with both social and ecological factors across animal taxa. Ecological generalists have been attributed with enhanced cognitive abilities, but which specific ecological factors may have shaped the evolution of which specific cognitive abilities remains poorly known. To explore these links, we applied a cognitive test battery (two personality, ten cognitive tests; n = 1104 tests) to wild individuals of two sympatric mouse lemur species (n = 120 Microcebus murinus, n = 34 M. berthae) varying in ecological adaptations but sharing key features of their social systems. The habitat and dietary generalist grey mouse lemurs were more innovative and exhibited better spatial learning abilities; a cognitive advantage in responding adaptively to dynamic environmental conditions. The more specialized Madame Berthe's mouse lemurs were faster in learning associative reward contingencies, providing relative advantages in stable environmental conditions. Hence, our study revealed key cognitive correlates of ecological adaptations and indicates potential cognitive constraints of specialists that may help explain why they face a greater extinction risk in the context of current environmental changes.
Fitness benefits of dietary restriction

Dietary restriction (DR) improves survival across a wide range of taxa yet remains poorly understood. The key unresolved question is whether this evolutionarily conserved response to temporary lack of food is adaptive. Recent work suggests that early-life DR reduces survival and reproduction when nutrients subsequently become plentiful, thereby challenging adaptive explanations. A new hypothesis maintains that increased survival under DR results from reduced costs of overfeeding. We tested the adaptive value of DR response in an outbred population of Drosophila melanogaster fruit flies. We found that DR females did not suffer from reduced survival upon subsequent re-feeding and had increased reproduction and mating success compared to their continuously fully fed (FF) counterparts. The increase in post-DR reproductive performance was of sufficient magnitude that females experiencing early-life DR had the same total fecundity as continuously FF individuals. Our results suggest that the DR response is adaptive and increases fitness when temporary food shortages cease.
Convergent HIV-1 Evolution upon Targeted Destabilization of the gp120-gp41 Interface

A successful HIV-1 vaccine most likely requires an envelope glycoprotein (Env) component, as Env is the only viral protein on the surface of the virus and the target for neutralizing antibodies. However, HIV Env is metastable and flexible because of the weak interactions between the Env subunits, complicating the generation of recombinant mimics of native Env. ABSTRACT The HIV-1 envelope glycoprotein (Env) trimer is responsible for viral entry into target cells and is the sole target of neutralizing antibodies. The Env protein is therefore the focus of HIV-1 vaccine design. Env consists of two noncovalently linked subunits (gp120 and gp41) that form a trimer of heterodimers and this 6-subunit complex is metastable and conformationally flexible. Several approaches have been pursued to stabilize the Env trimer for vaccine purposes, which include structure-based design, high-throughput screening, and selection by mammalian cell display. Here, we employed directed virus evolution to improve Env trimer stability. Accordingly, we deliberately destabilized the Env gp120-gp41 interface by mutagenesis in the context of replicating HIV-1 LAI virus and virus evolution over time. We identified compensatory changes that pointed at convergent evolution, as they were largely restricted to specific Env regions, namely, the V1V2 domain of gp120 and the HR1 and HR2 domain of gp41. Specifically, S614G in V1V2 and Q567R in HR1 were frequently identified. Interestingly, the majority of the compensatory mutations were at distant locations from the original mutations and most likely strengthen intersubunit interactions. These results show how the virus can overcome Env instability and illuminate the regions that play a dominant role in Env stability. IMPORTANCE A successful HIV-1 vaccine most likely requires an envelope glycoprotein (Env) component, as Env is the only viral protein on the surface of the virus and the target for neutralizing antibodies. However, HIV Env is metastable and flexible because of the weak interactions between the Env subunits, complicating the generation of recombinant mimics of native Env. Here, we used directed viral evolution to study Env stability. We deliberately destabilized the interface between Env subunits and explored the capacity of the virus to repair trimer instability by evolution. We identified compensatory mutations that converged in specific Env locations: the apex and the trimer interface. Selected mutations enhanced the stability of recombinant soluble Env trimer proteins. These results provided clues on understanding the structural mechanisms involved in Env trimer stability, which can guide future immunogen design.
Erbium-doped GeSbSe glassy semiconductors and theoretical analysis of constraint, electronic and thermal properties

ABSTRACT Erbium-doped Ge–Sb–Se (GSS) chalcogenide glasses have potential applications in environment sensing and are good candidates for mid-infrared (IR) laser. This article includes the theoretical study of Ge17Sb8Se75-x Er x (x = 0, 0.2, 0.4, 0.6, 0.8 and 1) chalcogenide system for physical parameters. The physical parameters include the calculation of the average coordination number, total number of constraints, electron lone pair, mean bond energy, glass transition temperature, packing fraction, deviation from stoichiometry, cohesive energy (CE) and energy band gap. It is observed that the average coordination number, total constraints, lone pair of electrons, mean bond energy and CE increase on increasing the erbium content, while the deviation from stoichiometry and band gap decrease. The covalent character of the alloy is more than 90% which suggests the system can form stable glasses and may be explored for IR application.
Longitudinal Analysis of HIV Risk and Substance Use Patterns for Men Who Have Sex With Men and Women and Men Who Have Sex With Men Only

Abstract Men who have sex with men and women (MSMW) experience discrimination from same-sex and heterosexual communities partially because of perceptions that they engage in high-risk sexual behavior, have elevated polysubstance use levels, and constitute an HIV bridge population. We used a longitudinal multivariate generalized linear mixed model comparing sexual risk and substance use patterns for men who have sex with men only (MSMO) with MSMW in the same cohort study. Data consisted of 771 men reporting 3,705 sexual partnerships from 2012 to 2017. For high-risk sexual behavior, multivariate results showed nonsignificant (p > .05) differences for partner number and commercial sex work and significantly less (p < .05) HIV prevalence and condomless anal sex. However, MSMW had significantly higher levels of hallucinogen and prescription opioid use as well as substance treatment histories. Only one HIV-positive MSMW had a transmittable viral load, negating the concept of MSMW being an HIV bridge population. Results indicate the need for additional longitudinal studies comparing MSMO and MSMW.
Microaggressions and Health Outcomes among Racially and Ethnically Diverse Bisexual Women

Abstract This study assessed the relationship between microaggressions and health outcomes among bisexual women. Participants came from the Women’s Daily Experiences Study, a mixed method study of bisexual women recruited in Chicago (N = 112). Using cross-sectional data, we tested bivariate and multivariate associations of lifetime and past year sexual orientation microaggressions with depression, anxiety, self-assessed mental and physical health, and substance use. We also tested relationships between intersectional microaggressions, related to racial and sexual minority identities, and health outcomes among a sub-sample of women of color (n = 64). The majority of participants reported experiences of microaggressions in their lifetime and in the past year. Multivariate analyses revealed significant associations between lifetime and past year sexual orientation microaggressions, mental health and substance use. Among bisexual women of color, intersectional microaggressions were significantly associated with higher levels of depression, anxiety, and poorer self-assessed mental health. Implications and future directions are discussed.
Preliminary Findings from the Implementation of Behavioral Parent Training in a Partial Hospitalization Program

ABSTRACT There is limited research on outcomes of partial hospitalization programs (PHPs). Questions remain regarding necessary treatment components for favorable outcomes including how to involve parents. There is growing consensus regarding the importance of parent participation in youth mental health treatment. Behavioral parent training (BPT) is an evidenced-based approach based on operant conditioning to target youth behavior through active skills training for parents that has demonstrated benefits across a range of diagnoses. BPT is one of the most extensively studied and effective treatments for reducing oppositional and disruptive behavior in youth. Modifying BPT for use in a youth PHP is appealing given its effectiveness in outpatient settings and its impact across a range of diagnoses. The present study examines the impact of brief BPT within a PHP that serves patients 5–17 years of age. Results demonstrated that patients who received BPT were significantly less likely to visit the emergency department (ED), be admitted to the inpatient psychiatric unit, or be readmitted to the PHP within 1 month of discharge. The results held at six-month post-discharge from the PHP. These results suggest that the addition of BPT to a PHP provides targeted support to optimize parent involvement, which may reduce revisiting the ED and/or acute psychiatric care service utilization following discharge. These results may be particularly useful in revealing crucial treatment components when establishing best practices and/or standards of care for PHPs, though further investigation is required.
Coupling the K-nearest neighbors and locally weighted linear regression with ensemble Kalman filter for data-driven data assimilation

Abstract Machine learning-based data-driven methods are increasingly being used to extract structures and essences from the ever-increasing pool of geoscience-related big data, which are often used in relation to the atmosphere, oceans, and land surfaces. This study focuses on applying a data-driven forecast model to the classical ensemble Kalman filter process to reconstruct, analyze, and elucidate the model. In this study, a nonparametric sampler from a catalog of historical datasets, namely, a nearest neighbor or analog sampler, is given by numerical simulations. Based on this catalog (sampler), the dynamics physics model is reconstructed using the K-nearest neighbors algorithm. The optimal values of the surrogate model are found, and the forecast step is performed using locally weighted linear regression. Several numerical experiments carried out using the Lorenz-63 and Lorenz-96 models demonstrate that the proposed approach performs as good as the ensemble Kalman filter for larger catalog sizes. This approach is restricted to the ensemble Kalman filter form. However, the basic strategy is not restricted to any particular version of the Kalman filter. It is found that this combined approach can outperform the generally used sequential data assimilation approach when the size of the catalog is substantially large. Graphical abstract
Development of Quran Reciter Identification System Using MFCC and Neural Network

Currently, the Quran is recited by so many reciters with different ways and voices. Some people like to listen to this reciter and others like to listen to other reciters. Sometimes we hear a very nice recitation of al-Quran and want to know who the reciter is. Therefore, this paper is about the development of Quran reciter recognition and identification system based on Mel Frequency Cepstral Coefficient (MFCC) feature extraction and artificial neural network (ANN). From every speech, characteristics from the utterances will be extracted through neural network model. In this paper a database of five Quran reciters is created and used in training and testing. The feature vector will be fed into Neural Network back propagation learning algorithm for training and identification processes of different speakers. Consequently, 91.2% of the successful match between targets and input occurred with certain number of hidden layers which shows how efficient are Mel Frequency Cepstral Coefficient (MFCC) feature extraction and artificial neural network (ANN) in identifying the reciter voice perfectly.
The integration of work process knowledge into human resources development

In this contribution the relationship between work process knowledge and human resources development is discussed. The concept of work process knowledge is described as it evolved as an outcome of a research network involving research institutions from 10 European countries (N. C. Boreham, R. Samurçay, & M. Fischer, 2002). Historical origins of the concept are mentioned and different dimensions of work process knowledge are depicted as a topic of ongoing research. How work process knowledge is considered within current research activities focusing on measures of organizational learning is also defined. In this respect, research results from the European research project OrgLearn (“Ways of Organisational Learning in the Chemical Industry and Their Impact on Vocational Education and Training,” funded under the Fifth Framework Programme of the European Union and coordinated by the author) are reported. Finally, the implications of the concept of work process knowledge are discussed, which have become apparent in recent developments within vocational education and training in Germany. © 2005 Wiley Periodicals, Inc. Hum Factors Man 15: 369–384, 2005.
Multi-paradigmatic approaches in cybersecurity economics

In cybersecurity economics, the selection of a particular methodology is a matter of interest and importance for the researchers. Methodologically sophisticated research forms an essential basis for understanding the challenges and opportunities for the richer descriptions of the behavior of cybersecurity practitioners (i.e., what they are doing and why they are doing it). This requires a broad and self-reflective approach to understand the use of a technique in socio-technical research within cybersecurity economics. Such understanding recognizes that research in this field involves more than just applying a method to create knowledge and diffuse it throughout society, organizations, and governments. This paper argues in favor of a multi-paradigmatic approach to cy-bersecurity economics research. Rather than adopting a single paradigm, this study suggests that results will be more prosperous and reliable if different methods from different existing paradigms are combined. Hence, it puts forward the desirability and feasibility of the multi-paradigmatic approach in cybersecurity economics research. It also outlines several practical guidelines that help design multi-paradigmatic research studies. These are illustrated with a critical evaluation of three examples of studies.
Reliability considerations and fault handling strategies for multi-MW modular drive systems

Shunt-interleaved electrical drive systems consisting of several parallel medium-voltage back to back converters enable power ratings of tens of MVA, low current distortions and a very smooth airgap torque. In order to meet stringent reliability and availability goals despite the large parts count, the modularity of the drive system needs to be exploited and a suitable fault handling strategy that allows the exclusion and isolation of faulted threads is required. This avoids the shutdown of the complete system and enables the drive system to continue operating. If full power capability is also required in degraded mode operation, redundancy on a thread level needs to be added. Experimental results confirm that thread exclusion allows the isolation of the majority of faults without affecting the mechanical load. As the drive system continues to run, faulted threads can be repaired and then added on-the-fly to the running system by thread inclusion. As a result, the downtime of such a modular drive system is expected to not exceed a few hours per year.
MOVEMENT PREPARATION AND LOUD ACOUSTIC STIMULATION 1 Title: Evolving Changes in Cortical and Sub-Cortical Excitability during Movement Preparation: A Study of Brain Potentials and Eye-Blink Reflexes during Loud Acoustic Stimulation

The presentation of Loud Acoustic Stimuli (LAS) during preparation can trigger motor actions at very short latencies in a phenomenon called the StartReact effect. It was initially proposed that a special, separate sub-cortical mechanism which by-passes slower cortical processes could be involved. We sought to examine the evidence for a separate mechanism against the alternative that responses to LAS can be explained by a combination of stimulus intensity effects and preparatory-states – as proposed by activation models of motor control. To investigate whether cortically mediated preparatory processes are involved in shaping reactions to LAS, we used an auditory reaction task where we manipulated preparation-level within each trial. We contrasted responses to non-intense tones and LAS and examined whether cortical activation, sub-cortical excitability (measured by pre-stimulus EEG and eye-blink startle reflexes, respectively) and the motor response were influenced by preparation-level. As predicted by the activation model, increases in preparation-level were marked by gradual reductions in RT coupled with increases in cortical activation and sub-cortical excitability – at both conditionand trial-levels. Changes in cortical activation influenced motor and auditory but not visual areas – highlighting the wide-spread yet selective nature of preparation. RTs were shorter to LAS than tones, but the overall pattern of preparation-level effects were the same for both stimuli. These results demonstrate that LAS responses are indeed shaped by cortically mediated preparatory processes. The concurrent changes observed in brain and behaviour with increasing preparation reinforces the notion that preparation is marked by evolving brain states which shape the motor response.
Selectively targeting myeloid-derived suppressor cells through TRAIL receptor 2 to enhance the efficacy of CAR T cell therapy for treatment of breast cancer

Background Successful targeting of solid tumors such as breast cancer (BC) using chimeric antigen receptor (CAR) T cells has proven challenging, largely attributed to the immunosuppressive tumor microenvironment (TME). Myeloid-derived suppressor cells (MDSCs) inhibit CAR T cell function and persistence within the breast TME. To overcome this challenge, we have developed CAR T cells targeting tumor-associated mucin 1 (MUC1) with a novel chimeric costimulatory receptor that targets tumor necrosis factor–related apoptosis-inducing ligand receptor 2 (TR2) expressed on MDSCs. Methods The function of the TR2.41BB costimulatory receptor was assessed by exposing non-transduced (NT) and TR2.41BB transduced T cells to recombinant TR2, after which nuclear translocation of NFκB was measured by ELISA and western blot. The cytolytic activity of CAR.MUC1/TR2.41BB T cells was measured in a 5-hour cytotoxicity assay using MUC1+ tumor cells as targets in the presence or absence of MDSCs. In vivo antitumor activity was assessed using MDSC-enriched tumor-bearing mice treated with CAR T cells with or without TR2.41BB. Results Nuclear translocation of NFκB in response to recombinant TR2 was detected only in TR2.41BB T cells. The presence of MDSCs diminished the cytotoxic potential of CAR.MUC1 T cells against MUC1+ BC cell lines by 25%. However, TR2.41BB expression on CAR.MUC1 T cells induced MDSC apoptosis, thereby restoring the cytotoxic activity of CAR.MUC1 T cells against MUC1+ BC lines. The presence of MDSCs resulted in an approximately twofold increase in tumor growth due to enhanced angiogenesis and fibroblast accumulation compared with mice with tumor alone. Treatment of these MDSC-enriched tumors with CAR.MUC1. TR2.41BB T cells led to superior tumor cell killing and significant reduction in tumor growth (24.54±8.55 mm3) compared with CAR.MUC1 (469.79±81.46 mm3) or TR2.41BB (434.86±64.25 mm3) T cells alone. CAR.MUC1. TR2.41BB T cells also demonstrated improved T cell proliferation and persistence at the tumor site, thereby preventing metastases. We observed similar results using CAR.HER2. TR2.41BB T cells in a HER2+ BC model. Conclusions Our findings demonstrate that CAR T cells that coexpress the TR2.4-1BB receptor exhibit superior antitumor potential against breast tumors containing immunosuppressive and tumor promoting MDSCs, resulting in TME remodeling and improved T cell proliferation at the tumor site.