Miracle-dz/UniFAR-FTUs huggingface dataset:
Emerging ExG-based NUI Inputs in Extended Realities: A Bottom-up Survey

Incremental and quantitative improvements of two-way interactions with extended realities (XR) are contributing toward a qualitative leap into a state of XR ecosystems being efficient, user-friendly, and widely adopted. However, there are multiple barriers on the way toward the omnipresence of XR; among them are the following: computational and power limitations of portable hardware, social acceptance of novel interaction protocols, and usability and efficiency of interfaces. In this article, we overview and analyse novel natural user interfaces based on sensing electrical bio-signals that can be leveraged to tackle the challenges of XR input interactions. Electroencephalography-based brain-machine interfaces that enable thought-only hands-free interaction, myoelectric input methods that track body gestures employing electromyography, and gaze-tracking electrooculography input interfaces are the examples of electrical bio-signal sensing technologies united under a collective concept of ExG. ExG signal acquisition modalities provide a way to interact with computing systems using natural intuitive actions enriching interactions with XR. This survey will provide a bottom-up overview starting from (i) underlying biological aspects and signal acquisition techniques, (ii) ExG hardware solutions, (iii) ExG-enabled applications, (iv) discussion on social acceptance of such applications and technologies, as well as (v) research challenges, application directions, and open problems; evidencing the benefits that ExG-based Natural User Interfaces inputs can introduce to the area of XR.
The effects of green supply chain management practices on firm performance: Empirical evidence from restaurants in Egypt

The primary purpose of this study was to investigate the effects of three green supply chain management (GrSCM) dimensions (i.e., green management, green food, green environment, and equipment) on operational performance, competitive advantage, and firm performance, in a convenience sample of international quick-service restaurants (QSRs) in Egypt. The hypotheses of the study were tested empirically by employing a self-administered questionnaire. A total of 600 questionnaires were randomly distributed by hand to QSR managers and supervisors, and 478 usable questionnaires were personally retrieved, representing a usable response rate of 79.7%. The obtained data were analyzed using one-way independent ANOVA and structural equation modeling (SEM). The SEM results revealed that the green management dimension had a significant positive effect on a restaurant's competitive advantage while the green environment and equipment dimension had a significant positive effect on operational performance. Additionally, the operational performance had a significant positive effect on firm performance. The study has significant theoretical and practical implications.
Biomimetics provides lessons from nature for contemporary ways to improve human health

Abstract Homo sapiens is currently living in serious disharmony with the rest of the natural world. For our species to survive, and for our well-being, we must gather knowledge from multiple perspectives and actively engage in studies of planetary health. The enormous diversity of species, one of the most striking aspects of life on our planet, provides a source of solutions that have been developed through evolution by natural selection by animals living in extreme environments. The food system is central to finding solutions; our current global eating patterns have a negative impact on human health, driven climate change and loss of biodiversity. We propose that the use of solutions derived from nature, an approach termed biomimetics, could mitigate the effects of a changing climate on planetary health as well as human health. For example, activation of the transcription factor Nrf2 may play a role in protecting animals living in extreme environments, or animals exposed to heat stress, pollution and pesticides. In order to meet these challenges, we call for the creation of novel interdisciplinary planetary health research teams.
Shifts in the Abundances of Saprotrophic and Ectomycorrhizal Fungi With Altered Leaf Litter Inputs

Ectomycorrhizal (EcM) and saprotrophic fungi interact in the breakdown of organic matter, but the mechanisms underlying the EcM role on organic matter decomposition are not totally clear. We hypothesized that the ecological relations between EcM and saprotroph fungi are modulated by resources availability and accessibility, determining decomposition rates. We manipulated the amount of leaf litter inputs (No-Litter, Control Litter, Doubled Litter) on Trenched (root exclusion) and Non-Trenched plots (with roots) in a temperate deciduous forest of EcM-associated trees. Resultant shifts in soil fungal communities were determined by phospholipid fatty acids and DNA sequencing after 3 years, and CO2 fluxes were measured throughout this period. Different levels of leaf litter inputs generated a gradient of organic substrate availability and accessibility, altering the composition and ecological relations between EcM and saprotroph fungal communities. EcM fungi dominated at low levels of fresh organic substrates and lower organic matter quality, where short-distances exploration types seem to be better competitors, whereas saprotrophs and longer exploration types of EcM fungi tended to dominate at high levels of leaf litter inputs, where labile organic substrates were easily accessible. We were, however, not able to detect unequivocal signs of competition between these fungal groups for common resources. These results point to the relevance of substrate quality and availability as key factors determining the role of EcM and saprotroph fungi on litter and soil organic matter decay and represent a path forward on the capacity of organic matter decomposition of different exploration types of EcM fungi.
Identification of Potential Prognostic Biomarkers Associated With Cancerometastasis in Skin Cutaneous Melanoma

Skin cutaneous melanoma (SKCM) is a highly aggressive tumor. The mortality and drug resistance among it are high. Thus, exploring predictive biomarkers for prognosis has become a priority. We aimed to find immune cell-based biomarkers for survival prediction. Here 321 genes were differentially expressed in immune-related groups after ESTIMATE analysis and differential analysis. Two hundred nineteen of them were associated with the metastasis of SKCM via weighted gene co-expression network analysis. Twenty-six genes in this module were hub genes. Twelve of the 26 genes were related to overall survival in SKCM patients. After a multivariable Cox regression analysis, we obtained six of these genes (PLA2G2D, IKZF3, MS4A1, ZC3H12D, FCRL3, and P2RY10) that were independent prognostic signatures, and a survival model of them performed excellent predictive efficacy. The results revealed several essential genes that may act as significant prognostic factors of SKCM, which could deepen our understanding of the metastatic mechanisms and improve cancer treatment.
Predictors of Stepping Up to Higher Level of Care Among Eating Disorder Patients in a Partial Hospitalization Program

Partial hospitalization programming (PHP) is a treatment option available for individuals with eating disorders (ED) who have made insufficient progress in outpatient settings or are behaviorally or medically unstable. Research demonstrates that this level of care yields efficacy for the majority of patients. However, not all patients achieve recovery in PHP and later admit to a higher level of care (HLOC) including residential treatment or inpatient hospitalization. Although PHP is an increasingly common treatment choice for ED, research concerning outcome predictors in outpatient, stepped levels of care remains limited. Thus, the current study sought to identify the predictors of patients first admitted to PHP that later enter residential or inpatient treatment. Participants were 788 patients (after exclusions) enrolled in adolescent or adult partial hospitalization programs in a specialized ED clinic. When compared to patients who maintained treatment in PHP, a significantly greater proportion of patients who discharged to a HLOC had previously received ED residential treatment. Moreover, patients who discharged to a HLOC were diagnosed with a comorbid anxiety disorder and reported greater anxious and depressive symptomatology. A logistic regression model predicting discharge from PHP to a HLOC was significant, and lower body mass index (BMI) was a significant predictor of necessitating a HLOC. Supplemental programming in partial hospitalization settings might benefit individuals with previous ED residential treatment experience, higher levels of anxiety and depression, and lower BMIs. Specialized intervention for these cases is both practically and economically advantageous, as it might reduce the risk of rehospitalization and at-risk patients needing to step up to a HLOC.
Good Food, Good Mood: Perspectives on the Relationship Between Nutrition and Mental Health With Division I Collegiate Athletic Programs

Research has shown a strong relationship between nutrition and mental health. Packed schedules and little rest time may make student-athletes more susceptible to mental health issues than the general population, but few athletes are fully aware of the effects that nutrition can have on their mental health. While collegiate athletic programs are beginning to recognize the individual contributions of nutrition and mental health to performance and are hiring sport dietitians and psychologists for their athletes, it is unclear whether these topics are ever discussed within the same context. The goal of this study was to understand the perspectives of different athletic personnel on the relationship between nutrition and mental health. 17 athletic personnel (11 Female, 6 Male) from 6 NCAA Division I universities were recruited for a 30–45-min semi-structured WebEx interview. Participants included athletic trainers, coaches, dietitians, sport psychologists, strength and conditioning coaches, and sports medicine physicians. Participants were asked questions about their educational backgrounds, resources, and perspectives on the integration of nutrition and mental health in their programs. Transcribed responses were sorted into four themes: (1) Resources, (2) Education, (3) Department Integration or Collaboration, and (4) Student and Coach Engagement. All participants reported a need for greater monetary resources and staffing. Around 59% of the participants felt they had little more than general or personal interest-level knowledge on topics pertaining to nutrition or mental health, with the exception of sports dietitians or psychologists. Each school varied in the degree to which their athletic staff regularly communicated about their work and athlete health statuses. Athletes were reportedly more or less likely to utilize the resources provided depending on coach attitudes toward nutrition or mental health. Regardless of size, reputation and annual spending, each university was reported to be in the early stages of integrating nutrition and mental health programs into their existing athletic departments. Implications of this work may be to help schools plan for ways to reallocate funding for nutrition or mental health programming.
Online Gambling's Associations With Gambling Disorder and Related Problems in a Representative Sample of Young Swiss Men

Background and Aims: Internet gambling has recently grown in popularity, but relatively little is known about how online and the combination of online and offline (mixed) gambling are associated with gambling disorder (GD) and related problems. The present research examined in a cohort study sample of young Swiss men how their gambling activities and gambling-related problems differed across the spectrum from offline to online gambling. Sample: A general-population based sample from the Cohort Study on Substance Use Risk Factors (C-SURF), consisting of 5,352 young Swiss men (mean age 28.26 years old). Measures: The spectrum from exclusively offline to almost exclusively online (>90% of gambling money spent online) gambling was measured using one question about the proportion of gambling money spent online. Total money gambled and time spent on gambling were also assessed. GD severity (range 0–9) was measured using items reflecting the nine DSM-5 GD criteria. The number of gambling-related problems (e.g., financial difficulties, range 0–10), other addictive disorders and mental health problems were also inquired about. Methods: We estimated a generalised linear model using a count model (negative binomial link function) for GD severity and gambling-related problems associated with the amounts and proportions of money gambled online and offline. Results: The number of GD criteria were associated with money gambled online (IRR [95%CI] = 2.81 [2.43, 3.24]) and offline (IRR = 2.68 [2.40, 3.00]). This was also found for the number of gambling-related problems (IRR = 2.43 [2.13, 2.79] and IRR = 2.89 [2.59, 3.23]). Compared with exclusively-offline gamblers, mixed gamblers (26–90% of money gambled online) showed the highest levels of GD symptoms and gambling-related problems, followed by the almost-exclusively-online gamblers (≥91% money gambled online) and, overall, these associations were still significant after adjustment for overall involvement in gambling (time spent and money gambled). Levels of other addictive disorders and mental health problems were higher among mixed gamblers than among offline-only gamblers, but levels among almost-exclusively-online gamblers were not. Conclusions: Symptoms of gambling disorder and gambling related problems are highest among gamblers engaging in both offline and online gambling. Prevention efforts need to target the combination of offline and online gambling.
Identification of Somatic Mutation-Driven Immune Cells by Integrating Genomic and Transcriptome Data

Tumor somatic mutations in protein-coding regions may generate neoantigens which may trigger antitumor immune cell response. Increasing evidence supports that immune cell response may profoundly influence tumor progression. However, there are no calculated tools to systematically identify immune cells driven by specific somatic mutations. It is urgent to develop a calculated method to comprehensively detect tumor-infiltrating immune cells driven by the specific somatic mutations in cancer. We developed a novel software package (SMDIC) that enables the automated identification of somatic mutation-driven immune cell. SMDIC provides a novel pipeline to discover mutation-specific immune cells by integrating genomic and transcriptome data. The operation modes include inference of the relative abundance matrix of tumor-infiltrating immune cells, detection of differential abundance immune cells with respect to the gene mutation status, conversion of the abundance matrix of significantly dysregulated cells into two binary matrices (one for upregulated and one for downregulated cells), identification of somatic mutation-driven immune cells by comparing the gene mutation status with each immune cell in the binary matrices across all samples, and visualization of immune cell abundance of samples in different mutation status for each gene. SMDIC provides a user-friendly tool to identify somatic mutation-specific immune cell response. SMDIC may contribute to understand the mechanisms underlying anticancer immune response and find targets for cancer immunotherapy. The SMDIC was implemented as an R-based tool which was freely available from the CRAN website https://CRAN.R-project.org/package=SMDIC.
Combining Imaging Flow Cytometry and Molecular Biological Methods to Reveal Presence of Potentially Toxic Algae at the Ural River in Kazakhstan

Algal blooms occur in freshwater bodies throughout the world, often leading to fish kills. Cases of these kills along the Ural River were reported in 2018–2019, involving significant amount of sturgeon in fish farming areas. In this study, the analysis of algal samples from the delta of the Ural River up to 100 km inland was carried out from August to December 2019 using imaging flow cytometry (IFC), molecular biological, and microscopic techniques. We identified the filamentous cyanobacteria Cuspidothrix issatschenkoi, Dolichospermum cf. flos-aquae, Dolichospermum cf. macrosporum, Pseudanabaena limnetica, and Planktothrix spp. as the dominant potentially toxic phytoplankton species, and we also found minor quantities of Cylindrospermopsis raciborskii. For the first time, molecular phylogenetic investigations of field clones of cyanobacteria from Ural River were carried out to establish the taxa of the dominant species and to identify the presence of genes encoding toxins. The complementary analysis with nanopore-based next-generation sequencing overlapped with the results of IFC and was instrumental in revealing minor cyanobacteria taxa. Real-time PCR analysis and sequencing indicated the presence of Microcystis and ADA-clade spp. as well as genes associated with the production of microcystin (mcyE) and the algal neurotoxin saxitoxin (sxtA) originating from cyanobacteria. These findings suggest that toxin-producing cyanobacteria could become a threat in the Ural River near Atyrau, which can significantly affect aquaculture in the region.
In Patients With Parkinson’s Disease in an OFF-Medication State, Does Bilateral Electrostimulation of Tibialis Anterior Improve Anticipatory Postural Adjustments During Gait Initiation?

A complete lack of bilateral activation of tibialis anterior (TA) during gait initiation (GI), along with bradykinetic anticipatory postural adjustments (APAs), often occurs in patients with Parkinson’s disease (PD) in their OFF-medication state. Functional electrical stimulation (FES) is a non-pharmacological method frequently used in neurorehabilitation to optimize the effect of L-DOPA on locomotor function in this population. The present study tested the potential of bilateral application of FES on TA to improve GI in PD patients. Fourteen PD patients (OFF-medication state, Hoehn and Yahr state 2-3) participated in this study. They performed series of 10 GI trials on a force-plate under the following experimental conditions: (1) GI without FES (control group), (2) GI with 2Hz-FES (considered as a very low FES frequency condition without biomechanical effect; placebo group) and (3) GI with 40Hz-FES (test group). In (2) and (3), FES was applied bilaterally to the TA during APAs (300 mA intensity/300 μs pulse width). Main results showed that the peak of anticipatory backward center of pressure shift, the forward center of mass (COM) velocity and shift at foot off were significantly larger in the 40 Hz FES condition than in the control condition, while the duration of step execution was significantly shorter. In contrast, the capacity of participants to brake the fall of their COM remained unchanged across conditions. Globally taken, these results suggest that acute application of 40-Hz FES to the TA may improve the capacity of PD patients to generate APAs during GI, without altering their balance capacity. Future studies are required before considering that TA FES application might be a valuable tool to improve GI in PD patients and be relevant to optimize the effects of L-DOPA medication on locomotor function.
Analysis of Htra Gene from Zebrafish (Danio Rerio)

HtrA which is characterized by the combination of a trypsin-like catalytic domain with at least one C-terminal PDZ domain is a highly conserved family of serine proteases found in a wide range of organisms. However the identified HtrA family numbers varies among spesies, for example the number of mammalian, Eschericia coli, fruit fly-HtrA family are 4, 3 and 1 gene respectively. One gene is predicted exist in zebrafish. Since no complete information available on zebrafish HtrA, in this paper zebrafish HtrA (zHtrA) gene was analyzed. The zHtrA is belonged to HtrA1 member and predicted encodes 478 amino acids with a signal peptide, a IGF binding domain, a Kazal-type inhibitor domain in the up stream of HtrA-bacterial homolog. At the amino acid sequence the zHtrA1 showed the 69%, 69%, 68%, 54% and 54% with the rat HtrA1, mouse HtrA1, human HtrA1, human HtrA3 and mouse HtrA4 respectively. The zHtrA1 is firstly expressed at 60 hpf and mainly in the vertebral rudiments in the tail region.
Modeling of Threshold Voltage Distribution in 3D NAND Flash Memory

3D NAND flash memory faces unprecedented complicated interference than planar NAND flash memory, resulting in more concern regarding reliability and performance. Stronger error correction code (ECC) and adaptive reading strategies are proposed to improve the reliability and performance taking a threshold voltage (Vth) distribution model as the backbone. However, the existing modeling methods are challenged to develop such a Vth distribution model for 3D NAND flash memory. To facilitate it, in this paper, we propose a machine learning-based modeling method. It employs a neural network taking advantage of the existing modeling methods and fully considers multiple interferences and variations in 3D NAND flash memory. Compared with state-of-the-art models, evaluations demonstrate it is more accurate and efficient for predicting Vth distribution.
On the Potential Game of Packet Reception Ratio Utility Functions in Wireless Sensor Networks

Wireless Sensor Networks channel exhibits significant complexity when attempting to analyse theoretically the network layer of the wireless stack. A parameter of this layer is the Packet Reception Ratio (PRR). Optimising PRR can result in transmission reliability and high throughput. Considering wireless nodes as players, we can construct game-theoretic models that can be utilised to solve transmission reception problems in a distributed nature. In this paper, we give necessary conditions to use potential game approaches with PRR utility functions.
On Control and Data Plane Programmability for Data-Driven Networking

The soaring complexity of networks has led to more and more complex methods to manage and orchestrate efficiently the multitude of network environments. Several solutions exist, such as OpenFlow, NetConf, P4, DPDK, etc., that allow net-work programmability at both control and data plane level, driving innovation in many focused high-performance networked applications. However, with the increase of strict requirements in critical applications, also the networking architecture and its operations should be redesigned. In particular, recent advances in machine learning have opened new opportunities to the automation of network management, exploiting existing advances in software-defined infrastructures. We argue that the design of effective data-driven network management solutions needs to collect, merge, and process states from both data and control planes. This paper sheds light upon the benefits of utilizing such an approach to support feature extraction and data collection for network automation.