Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact and Treatment of Sarcopenia in Patients Undergoing Radiotherapy: A Multidisciplinary, AMSTAR-2 Compliant Review of Systematic Reviews and Metanalyses

Background Sarcopenia (SP) is defined as the quantitative and functional impairment of skeletal muscles. SP is commonly related to older age and is frequent in patients with cancer. To provide an overview of SP in patients treated with radiotherapy (RT) and to evaluate the current evidence, we analyzed the available systematic reviews and meta-analyses. Methods Reviews were identified using PubMed, Scopus, and Cochrane library databases, without date restriction. Only systematic reviews and meta-analyses on the prognostic impact of SP and on any treatments aimed at reducing SP effect, in patients undergoing RT, were included in this review. The analyses not separately reporting the results in patients treated with RT were excluded. The quality assessment was performed using AMSTAR-2 (A MeaSurement Tool to Assess systematic Reviews). Results From the 84 papers identified, five reviews met the inclusion criteria with four reports mainly including non-randomized trials. Three reviews on the effect of SP showed a significantly negative impact on overall survival in patients undergoing RT and/or chemoradiation for H&N cancers (HR: 1.63-2.07). Two reviews on interventional studies showed the possibility of 1) improving physical functions through nutritional and physical interventions and 2) avoiding muscle wasting by means of sufficient protein intake. The quality assessment of the included review showed that two and three analyses are classifiable as having low and moderate overall confidence rating, respectively. Conclusions The analyzed reviews uniformly confirmed the negative impact of SP in patients with H&N tumors undergoing RT and the possibility of improving muscle mass and function through nutritional and physical interventions. These results justify further research on this topic based on a more uniform SP definition and on a complete evaluation of the potentially confounding parameters.
How Corporate Social Responsibility Boosts Corporate Financial and Non-financial Performance: The Moderating Role of Ethical Leadership

Corporate social responsibility has always been considered an important topic, and many studies discuss the association between corporate social responsibility (CSR) and corporate performance, but the results are still inconclusive. This study is to examine the impact of CSR on corporate performance (financial and non-financial) with the moderating impact of ethical leadership. Data is gathered from 222 companies in Morocco using a simple random sampling technique. Moreover, for measuring customer satisfaction and corporate image in the kinds of customers targeted by the CSR activities of the firms, we collected data from customers and got 209 responses. For analyzing the results of this study, structural equation modeling has been used, while for moderation, the hierarchical regression technique has been adopted. Findings revealed a significant positive association found between CSR and corporate finance as well as non-financial performance (corporate image and customer satisfaction). Ethical leadership helps in increasing the financial and non-financial performance of an organization. The findings further revealed that ethical leadership moderates the relationship between CSR and firm financial and non-financial (corporate image and customer satisfaction) performance. This study will assist management in realizing the importance and implementation of CSR practices in organizations, especially in the Moroccan context.
Alpha-Synuclein Strain Variability in Body-First and Brain-First Synucleinopathies

Pathogenic alpha-synuclein (asyn) aggregates are a defining feature of neurodegenerative synucleinopathies, which include Parkinson's disease, Lewy body dementia, pure autonomic failure and multiple system atrophy. Early accurate differentiation between these synucleinopathies is challenging due to the highly heterogeneous clinical profile at early prodromal disease stages. Therefore, diagnosis is often made in late disease stages when a patient presents with a broad range of motor and non-motor symptoms easing the differentiation. Increasing data suggest the clinical heterogeneity seen in patients is explained by the presence of distinct asyn strains, which exhibit variable morphologies and pathological functions. Recently, asyn seed amplification assays (PMCA and RT-QuIC) and conformation-specific ligand assays have made promising progress in differentiating between synucleinopathies in prodromal and advanced disease stages. Importantly, the cellular environment is known to impact strain morphology. And, asyn aggregate pathology can propagate trans-synaptically along the brain-body axis, affecting multiple organs and propagating through multiple cell types. Here, we present our hypothesis that the changing cellular environments, an asyn seed may encounter during its brain-to-body or body-to-brain propagation, may influence the structure and thereby the function of the aggregate strains developing within the different cells. Additionally, we aim to review strain characteristics of the different synucleinopathies in clinical and preclinical studies. Future preclinical animal models of synucleinopathies should investigate if asyn strain morphology is altered during brain-to-body and body-to-brain spreading using these seeding amplification and conformation-specific assays. Such findings would greatly deepen our understanding of synucleinopathies and the potential link between strain and phenotypic variability, which may enable specific diagnosis of different synucleinopathies in the prodromal phase, creating a large therapeutic window with potential future applications in clinical trials and personalized therapeutics.
Long Intergenic Noncoding RNA00265 Enhances Cell Viability and Metastasis via Targeting miR-485-5p/USP22 Axis in Osteosarcoma

Osteosarcoma is one of the bone malignancies in children and adolescents. Long noncoding RNAs (lncRNAs) have been demonstrated to participate in osteosarcoma development and progression. Linc00265 has been shown to involve in osteosarcoma oncogenesis; however, the underlying mechanism is largely unclear. In this study, we investigated the function of linc00265 in osteosarcoma cells, including cell viability, migration and invasion. Moreover, we elucidated mechanistically the involvement of linc00265 in osteosarcoma. We found that linc00265 overexpression promoted viability, migration and invasion of osteosarcoma cells. Notably, linc00265 sponged miR-485-5p and increased the expression of USP22, one target of miR-485-5p, in osteosarcoma cells. Strikingly, linc00265 exerted its oncogenic function via regulating miR-485-5p and USP22 in osteosarcoma. Taken together, targeting linc00265 is a promising approach for treating osteosarcoma patients.
Mechanosurveillance: Tiptoeing T Cells

Efficient scanning of tissue that T cells encounter during their migratory life is pivotal to protective adaptive immunity. In fact, T cells can detect even a single antigenic peptide/MHC complex (pMHC) among thousands of structurally similar yet non-stimulatory endogenous pMHCs on the surface of antigen-presenting cells (APCs) or target cells. Of note, the glycocalyx of target cells, being composed of proteoglycans and bulky proteins, is bound to affect and even modulate antigen recognition by posing as a physical barrier. T cell-resident microvilli are actin-rich membrane protrusions that puncture through such barriers and thereby actively place the considerably smaller T-cell antigen receptors (TCRs) in close enough proximity to APC-presented pMHCs so that productive interactions may occur efficiently yet under force. We here review our current understanding of how the plasticity of T-cell microvilli and physicochemical properties of the glycocalyx may affect early events in T-cell activation. We assess insights gained from studies on T-cell plasma membrane ultrastructure and provide an update on current efforts to integrate biophysical aspects such as the amplitude and directionality of TCR-imposed mechanical forces and the distribution and lateral mobility of plasma membrane-resident signaling molecules into a more comprehensive view on sensitized T-cell antigen recognition.
Influence of Identity Development on Weight Gain in Adolescent Anorexia Nervosa

Background Anorexia Nervosa (AN) typically begins during early adolescence, an important phase of personality development. A substantial proportion of adolescent AN patients shows impaired personality functioning, which might be a relevant but understudied aspect of illness severity. The developmental status of identity as key element of personality is suggested to influence inpatient treatment outcome in adolescents with AN. Methods This study analyzed existing data of N = 60 adolescents with AN. Multilevel models assessed the influence of identity functioning, measured by the Assessment of Identity Development in Adolescence (AIDA) at admission, on weight gain [BMI (body mass index), BMI-SDS (BMI standard deviation score)] during 10 weeks of inpatient treatment. Moreover, the influence of other indicators of illness severity, i.e., eating disorders and comorbid psychopathologies, was explored. Results As expected, higher AIDA scores negatively influenced the course of weight gain. A similar effect was observed for other psychopathology measures, especially body image distortion. In general, higher weight at admission was associated with less weight gain. Higher weight at admission was also predicted by higher other psychopathology measures, but not AIDA scores. Conclusion The course of weight gain during inpatient treatment was hampered in adolescent AN patients who have difficulties developing a stable identity. Unlike other aspects of psychopathology, this was independent of the initial weight. Thus, in addition to the level of underweight and other aspects of psychopathology, difficulties in identity development constitute a relevant aspect of illness severity in AN. This recommends consideration of identity development during treatment.
Total Flavonoids of Rhizoma Drynariae Ameliorate Bone Growth in Experimentally Induced Tibial Dyschondroplasia in Chickens via Regulation of OPG/RANKL Axis

Background: Rhizoma Drynariae, traditional Chinese herb, is widely used to treat and prevent bone disorders. However, experimental evidence on the use of Rhizoma Drynariae extract, total flavonoids of Rhizoma Drynariae (TFRD) to treat tibial dyschondroplasia (TD) in chickens and its underlying mechanisms have not been investigated. Purpose: To evaluate the therapeutic effect of TFRD on leg disease caused by TD and elucidate its mechanisms in modulating the bone status. Methods: Thiram-induced chicken TD model has been established. The tibia status was evaluated by analyzing tibia-related parameters including tibial weight, tibial length and its growth plate width and by performing histopathological examination. The expression of tibial bone development-related genes and proteins was confirmed by western blotting and qRT-PCR. Results: The results showed that administration of TFRD mitigated lameness, increased body weight, recuperated growth plate width in broilers affected by TD and the increase of tibia weight and tibia length is significantly positively correlated with body weight. Compared with the TD group broilers, 500 mg/kg TFRD evidently reduced the damage width of the growth plate and improved its blood vessel distribution by elevating the gene expression levels of BMP-2 and Runx2 and OPG/RANKL ratio. Furthermore, correlation analysis found that the damage width of the growth plate was negatively correlated with the expression levels of BMP-2 and OPG. Conclusion: The present study revealed that TFRD could promote the bone growth via upregulating OPG/RANKL ratio, suggesting that TFRD might be a potential novel drug in the treatment of TD in chickens.
Thermophilic Geobacillus WSUCF1 Secretome for Saccharification of Ammonia Fiber Expansion and Extractive Ammonia Pretreated Corn Stover

A thermophilic Geobacillus bacterial strain, WSUCF1 contains different carbohydrate-active enzymes (CAZymes) capable of hydrolyzing hemicellulose in lignocellulosic biomass. We used proteomic, genomic, and bioinformatic tools, and genomic data to analyze the relative abundance of cellulolytic, hemicellulolytic, and lignin modifying enzymes present in the secretomes. Results showed that CAZyme profiles of secretomes varied based on the substrate type and complexity, composition, and pretreatment conditions. The enzyme activity of secretomes also changed depending on the substrate used. The secretomes were used in combination with commercial and purified enzymes to carry out saccharification of ammonia fiber expansion (AFEX)-pretreated corn stover and extractive ammonia (EA)-pretreated corn stover. When WSUCF1 bacterial secretome produced at different conditions was combined with a small percentage of commercial enzymes, we observed efficient saccharification of EA-CS, and the results were comparable to using a commercial enzyme cocktail (87% glucan and 70% xylan conversion). It also opens the possibility of producing CAZymes in a biorefinery using inexpensive substrates, such as AFEX-pretreated corn stover and Avicel, and eliminates expensive enzyme processing steps that are used in enzyme manufacturing. Implementing in-house enzyme production is expected to significantly reduce the cost of enzymes and biofuel processing cost.
Personality in Soccer: Investigation of the Five-Factor Model of Personality in High-Level Athletes

Background In high-level sports, rapid screening and diagnostic instruments are necessary considering limited access that researchers have to these athletes. In the area of sport psychological diagnostics, the NEO-FFI is a promising tool to gain information about an athlete's personality traits. The current study investigated the NEO-FFI's scientific quality criteria and general application to elite-level soccer. Methods Personality traits of 378 elite-level soccer athletes were assessed using the NEO-FFI. Analysis focused on internal consistency, factor structure and gender differences. Additionally, a second measurement with a 6-week interval was conducted with a sub-sample of 86 athletes to analyse test-retest reliability. Results Overall, the results are in line with previous findings outside high-level sports. For the total sample, alpha-levels from 0.68 to 0.84 and intraclass correlation coefficients (ICC) for test-retest measures from 0.86 to 0.91 could be found. Item-level principal component analysis using both oblimin and oblique rotation showed better stability in neuroticism (N) and conscientiousness (C) than in extraversion (E), openness (O), and agreeableness (A). Gender differences could be found in values of internal consistency, ICC and NEO-FFI traits. Conclusion The results of this study demonstrate good transferability of the NEO-FFI from settings outside high-level sports into this specific niche of sport psychological assessment. However, the same weaknesses of the applied instrument in general populations were also replicated in the sporting population.
Identification of COVID-19 and Pneumonia in X-Ray Images using Transfer Learning

Background: The spread of novel corona virus disease (COVID-19) contributed to a global crisis in the world. The virus was identified a pandemic by the World Health Organization on 11 March 20. And also more than 200 countries have been affected by the outbreak, with more than 37 million cases reported and over 1 million fatalities as of 10 October 2020. The SARS-CoV-2 virus triggered the COVID-19 disease. The human respiratory system deteriorates from this severe disease. In the first four to ten days after infection, patients with COVID-19 may develop symptoms similar to pneumonia as well as other respiratory diseases. As a reason, there could be a misdiagnosis between COVID-19 and common pneumonia patients. So for that, Computer-Aided Diagnosis (CAD) system can be considered an effective technique for physicians to use medical imaging methods to help the detection of pneumonia and COVID-19. Method: Some methods of deep learning can assist doctors in achieving an accurate pre-diagnosis. This paper proposed a specific and precise method for classification of pneumonia, COVID- 19 and healthy patients using x-ray images, even in the case of a small number of labeled samples being available. EfficientNet-B4 is used to train & predict precise result it is a transfer learning approach. To bring the proposed model to reality, additional layers are added to the EfficientNet-B4 model. Results: The proposed work has procured a high training accuracy of 99% by 3886 (1200:COVID-19, 1345: pneumonia and 1341: healthy) X-ray images. And it accurately classifies the classes of Covid 19, Pneumonia and Healthy images with testing accuracy 99%, 93% and 100% respectively. Conclusion: Due to a high spreading of corona- virus, the identification of COVID-19 in early age plays an important role in implementing preventive steps. The developed model will accurately identify The diseases called COVID-19 and Pneumonia in X- Ray images at early stages. The obtained results specify that the proposed work attained best results compared with the previous approaches.
Earthquake analysis of structures using nonlinear models

Throughout the governing design codes, several different methods are presented for the evaluation of seismic problems. This thesis assesses the non-linear static and dynamic procedures presented in EN 1998-1 through the structural response of a RC wall-frame building. The structure is designed in detail according to the guidelines for high ductility (DCH) in EN 1998-1. The applied procedures are meticulously evaluated and the requirements in EN 1998-1 are reviewed. In addition, the finite element softwares SeismoStruct and OpenSees are utilized and evaluated. The results revealed that even though expecting, and designing for, high ductility, the structural response remained nearly in the elastic range. The elastic behaviour was a result of outsized and heavily reinforced members, with emphasis on the lower storey walls. The reduction of global stiffness caused by the selected time-history ground motions was greater than the recommendation in EN 1998-1. The non-linear static analysis rendered reasonable results in terms of displacements for the first-mode dominated structure. However, it has been demonstrated that the structure’s natural sensitivity to multi-degree-of-freedom effects limited the static analysis in terms of revealing possible structural behaviour.
A 4.6-μm, 127-dB Dynamic Range, Ultra-Low Power Stacked Digital Pixel Sensor With Overlapped Triple Quantization

This article presents a global shutter (GS), stacked digital pixel sensor (DPS) to meet the ultra-low power, ultra high dynamic range (HDR) requirements for battery-powered, always-on mobile computer vision (CV) applications. The <inline-formula> <tex-math notation="LaTeX">$4.6~\mu \text{m}$ </tex-math></inline-formula> DPS pixel is partitioned into two layers; a dual conversion gain (CG) pixel with a backside-illuminated photodiode (PD) on the top layer and an in-pixel ADC circuit with 10 bit SRAM on the bottom layer. A Cu-to-Cu hybrid-bonding (HB) technology is used to connect the two layers via pixel-level interconnect. The sensor features an overlapped triple quantization (3Q) scheme that performs a time-to-saturation (TTS) quantization and the dual-CG linear ADC mode sequentially in the same frame and extends the dynamic range (DR) with a small number of ADC bits. The DPS with a <inline-formula> <tex-math notation="LaTeX">$512\times512$ </tex-math></inline-formula> pixel array has achieved an ultra-HDR of 127 dB and low power consumption of 5.75 mW at 30 frames per second. The nonlinear conversion characteristics of the TTS mode provide an equivalent full well capacity (FWC) of 9000 ke<sup>−</sup>, while the high CG linear ADC mode realizes a low noise floor of 4.2 e<sup>−</sup>.
Refiner GAN Algorithmically Enabled Deep-RL for Guaranteed Traffic Packets in Real-time URLLC B5G Communication Systems

Ultra-reliable and Low-latency Communications (URLLC) is expected to be one of the most critical characteristics in Beyond fifth-Generation (B5G) cellular networks with stringent low latency and high-reliability requirements. The Deep Reinforcement Learning (deep-RL) framework has been applied to predict the optimization of a Resource Block (RB) and minimize Power Allocation (PA) to guarantee a high End-to-End (E2E) reliability and low E2E latency under rate constraints. This paper proposes a novel Policy Gradient-based Actor-Critic Learning (PGACL) algorithm to optimize the policy gradient for optimal rate allocation to solve the RB, minimize power, and guarantee a solution for URLLC scheduling. The purpose of a PGACL algorithm is to provide a good policy with a closer convergence rate and a low computational cost depending on the reduced action space for every user. URLLC systems need to operate in highly reliable systems and account for extreme network conditions. Therefore, we proposed the refiner Generative Adversarial Networks (GANs) that apply enough extreme events for the deep-RL agent to generate synthetic data with high reliability similar to real data based on the regulated number of extreme events in the dataset. This refiner GAN method enables a deep-RL approach to generate large amounts of data practically used in real-time operation. Simulation results showed that the proposed deep-RL for refiner-GAN can omit the transient training time and develop deep-learning based on a controlled set of unlabeled real traffic at a relatively short time. Furthermore, the refiner GAN demonstrated 99.9999% reliability and E2E latency of less than 1.4ms.
Impact of a 47 MVA Aeroderivative Gas Turbine Generator on a 346 MW Bulk Wind Farm - Case Study on Voltage & Frequency Response

This paper demonstrates the impact of a single GE LM2500XPRESS* Aeroderivative gas turbine generator (GTG), when operated in parallel with a bulk wind power plant, with regards to the latter's power transfer capacity, by providing the necessary voltage and reactive power support at the point of interconnection (POI). The hybrid application also improves the transient voltage response during large disturbances at the POI. It further demonstrates the GTG's positive impact on the network frequency profile during short-term load adjustment and loss of generation events.