Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Performance of Variable Selection and Classification via Rank-Based Classifier

In high-dimensional gene expression data analysis, the accuracy and reliability of cancer classification and selection of important genes play a very crucial role. To identify these important genes and predict future outcomes (tumor vs. non-tumor), various methods have been proposed in the literature. But only few of them take into account correlation patterns and grouping effects among the genes. In this article, we propose a rank-based modification of the popular penalized logistic regression procedure based on a combination of ℓ 1 and ℓ 2 penalties capable of handling possible correlation among genes in different groups. While the ℓ 1 penalty maintains sparsity, the ℓ 2 penalty induces smoothness based on the information from the Laplacian matrix, which represents the correlation pattern among genes. We combined logistic regression with the BH-FDR (Benjamini and Hochberg false discovery rate) screening procedure and a newly developed rank-based selection method to come up with an optimal model retaining the important genes. Through simulation studies and real-world application to high-dimensional colon cancer gene expression data, we demonstrated that the proposed rank-based method outperforms such currently popular methods as lasso, adaptive lasso and elastic net when applied both to gene selection and classification.
Thermo-visco-elasticity at small strains with ¹-data

Existence of a very weak solution to the d-dimensional thermo-viscoelasticity system for Kelvin-Voigt-type material at small strains involving (possibly nonlinear) monotone viscosity of a p-Laplacian type and temperature-dependent heat capacity of an (ω−1)-polynomial growth is proved by a successive passage to a limit in a suitably regularized Galerkin approximation and sophisticated a priori estimates for the temperature gradient performed for the coupled system. A global solution for arbitrarily large data having an L-structure is obtained under the conditions p ≥ 2, ω ≥ 1, and p > 1 + d/(2ω).
Talent Management Strategies and Practices in Five Star Hotels: An Exploratory Study

This research aims to explore the current strategies and practices of talent management (TM) within five star hotels in Egypt. To achieve the research aim, an online questionnaire was used as a tool for data collection. 212 general managers and human resource managers in the investigated hotels were targeted to identify the practices adopted to attract, select, develop, and retain talent employees. The research revealed that the practices of talent management are still at an early stage of development, and the concept and the process require further understanding. One of the key results was that most of the investigated hotels implemented some of the basic principles and components of TM system but the actual practice has not yet been demonstrated as a complete and integrated approach. Most of the managers were aware of the benefit of talent management. This research, therefore, contributes to provide a deeper knowledge and understanding on how human talents are being managed in an important sector of the hospitality industry
Dementia risk genes engage gene networks poised to tune the immune response towards chronic inflammatory states

An emerging challenge in neurodegenerative dementia is understanding how immune-associated genes and pathways contribute to disease. To achieve a refined view of neuroinflammatory signaling across neurodegeneration, we took an integrative functional genomics approach to consider neurodegeneration from the perspective of microglia and their interactions with other cells. Using large-scale gene expression and perturbation data, regulatory motif analysis, and gene knockout studies, we identify and characterize a microglial-centric network involving distinct gene co-expression modules associated with progressive stages of neurodegeneration. These modules, which are conserved from mouse to human, differentially incorporate specific immune sensors of cellular damage and pathways that are predicted to eventually tune the immune response toward chronic inflammation and immune suppression. Notably, common genetic risk for Alzheimer’s disease (AD), Frontotemporal dementia (FTD) and Progressive Supranuclear Palsy (PSP) resides in specific modules that distinguish between the disorders, but also show convergence on pathways related to anti-viral defense mechanisms. These results suggest a model wherein combinatorial microglial-immune signaling integrate specific immune activators and disease genes that lead to the establishment of chronic states of simultaneous inflammation and immunosuppression involving type 1 interferon in these dementias.
A clinical and microbiological profile of urinary tract infection in patients with chronic kidney diseases

Background: Urinary tract infections (UTIs) are a major public health problem in terms of morbidity and financial cost in CKD patients in India. The resistance pattern of community acquired uropathogens in CKD patients has not been extensively studied. Thus, knowledge of local antimicrobial susceptibility patterns of common uropathogens is essential for prudent empiric therapy of community acquired UTIs.Methods: It is a cross sectional study conducted in a tertiary care hospital involving 65 chronic kidney disease patients with UTI who attended general medicine OPD and those admitted in wards after fulfilling the inclusion and exclusion criteria, after obtaining written informed consent. Blood sample and urine samples were collected from these patients and sent for blood analysis, urine analysis and urine culture and sensitivity.Results: Among 65 CKD participants with UTI who were studied, E. coli (47.7%) and K. pneumoniae (15.4%) were the most common isolates which were sensitive in order of colistin, polymyxin B, meropenem (carbapenem) and less sensitive to other commonly used antibiotics.Conclusions: The main purpose of this study was to find the various common local uropathogens in CKD patients and their antibiotic profile which will help in formulating antibiotic therapies. As previously stated, there are very few studies regarding profile and management of UTI in CKD patients. Hence this study can throw some light into this area.
Interdisciplinary Journal of Contemporary Research in Business Considering Factors That Affect Users' Online Purchase Intentions with Using Structural Equation Modeling

Internet has fundamentally changed the way of businesses, consumers communication, interact and consumer transactions in worldwide . Vendors also must face reality of the complex behavior of consumers and should consider using data and information in the online market. The purpose of this paper is to explore a conceptual model for analyzing customers' perceptions of using online shopping. This paper provides insights into consumer behavior, and the results have important implications for designers, managers and marketers. This study identified factors that influence consumer purchase decisions.In order to show relations between variables structural equation modeling is used. This special issue, forming development of new knowledge, models and theories of consumer behavior in e-commerce.250 samples is chosen randomly from students of Isfahan University because young student is represented as the majority of internet users in Iran. The results show that perceived risk, which is an affective barrier against using new systems, is a key negative predictor of a customer's intentions to use online shopping. Also, trust is more important factor that influences consumer behaviors. Furthermore, perceived enjoyment, perceived usefulness, firm reputation and social influence have an impact on a customer's behavioral intentions. Introduction: Electronic commerce over the internet or online shopping first started in 1994 (Chua et al.2006). This new concept of retailing has captured the interest of many retailers and merchants because of the recognition that online shopping will is considered as an alternative channel alongside traditional offline retail channels such as physical retail stores (Chua et al., 2006). Advances with the internet and e-commerce have further diminished trade boundaries. Retailers tend to establish online storefronts as an online retailing method when the product brand names and reputations are well established and widely known among consumers (Chua et al., 2006) Internet retailing is one of the fastest Growing sectors in the UK, and is having significant effects on traditional retail Provision (Gunawan et al., 2008. Despite the statistics and success stories of many online merchants elsewhere, many
TEnet: target speaker extraction network with accumulated speaker embedding for automatic speech recognition

It is challenging to perform automatic speech recognition when multiple people talk simultaneously. To solve this problem, speaker-aware selective methods have been proposed to extract the speech of the target speaker, relying on the auxiliary speaker characteristics provided by an anchor (a clean audio sample of the target speaker). However, the extraction performance depends on the duration and quality of the anchors, which is unstable. To address this limitation, the authors propose a target speaker extraction network (TEnet) which applies the robust speaker embedding to extract the target speech from the speech mixture. To get more stable speaker characteristics during training, the robust speaker embeddings are accumulated over all the speech of each target speaker, rather than utilising the embedding produced by a single anchor. As for testing, very few anchors are enough to get decent extraction performance. Results show the TEnet trained with accumulated embedding achieves better performance and robustness compared with the single-anchored TEnet. Moreover, to exploit the potential of the speaker embedding, the authors propose to feed the extracted target speech as anchor and train a feedback TEnet, whose results are superior to the short-anchored baseline for 22.5% on word error rate and 15.5% on signal-to-distortion rate.
Design of Information Systems Customer Relationship Management to Improve Services Sales Approach System Development Life Cycle (SDLC)

: Insurance is a necessity that is increasingly favored by the people of Indonesia, one of the newly established company but has more than two million customers, PT Axa Mandiri, which is one of the subsidiaries and joint PT Bank Mandiri Axa Group. PT Axa Mandiri has a problem in three levels, namely, operational, analytical and strategy. From an operational perspective, client and financial advisor to the difficulty in obtaining information on insurance policy especially for unit linked products. A higher level, in the analytical segment, area sales manager difficulty identifying the bank employee profile that helps to get customers to give reward programs in the absence of previous data due to area sales manager often rotational workplace. And strategic segmented, regional sales manager can not know the customer data that has great potential to be treated specifically so as not to close an insurance policy before maturity closure. The purpose of this research is to know the design of Customer Relationship Management Information System to improve customer service with the System Development Life Cycle. Design feasibility analysis shows that the system has been designed according to user requirements so that the system design is feasible to be implemented in the Regional Sales. Besides the benefits of customer relationship management are viewed from three aspects, namely get customers, increase profits and retain customers is also approved by the regional sales manager, area sales manager, financial advisor and the client.
Femtosecond lasers: the ultimate tool for high-precision 3D manufacturing

Abstract The ever-growing trend of device multifunctionality and miniaturization puts enormous burden on existing manufacturing technologies. The requirements for precision, throughput, and cost become increasingly harder to achieve with minimal room for compromises. Femtosecond lasers, which saw immense development throughout the last few decades, have been proven time and time again to be a superb tool capable of standing up to the challenges posed by modern science and the industry for ultrahigh-precision material processing. Thus, this paper is dedicated to provide an outlook on how femtosecond pulses are revolutionizing modern manufacturing. We will show how they are exploited for various kinds of material processing, including subtractive (ablation, cutting, and etching), additive (lithography and laser-induced forward transfer), or hybrid subtractive-additive cases. The advantages of using femtosecond lasers in such applications, with main focus on how they enable the most precise kinds of material processing, will be highlighted. Future prospects concerning emerging industrial applications and the future of the technology itself will be discussed.
Studying the effect of Metformin and Enzyme inhibitor drags on the level of aromatase Enzyme in the women have hormone disorder the Kirkuk city

This study included ( 100 ) samples of women used drugs Metformin, enzyme inhibitor in (Azadi General Hospital) (20) blood samples aspirated from healthy women as control sample. The samples were divided into three groups; the first group (40) women used Metformin (have primary infertilits), the second group (40) women used Letrazole (have Secondary infertilits). The third group was the healthy women(control). The results of the study indicated a significant decrease (p<0.05) in the Activity of Aromatase level in Primary infertile women age groups (18-25), (26-35) and (36-45). the results of this study reveal that three is significant decrease in the Activity of Aromatase (p<0.05) in women who have Secondary infertility with age groups (18-25), (26-35) and (36-45). This Drugs causes decreasing the level of the Estrogen by inhibiting the Aromatase Enzyme . The Drugs also called as (Enzyme inhibitor) because they inhibit Aromatase enzyme, This proves that the Letrazole Drugs has an effective role in stimulating ovulation in women who have primary and secondary infertility.
Back to the origins: early interpersonal trauma and the intergenerational transmission of violence within the context of urban poverty

This chapter explores the effects of exposure to violence during childhood in contexts of poverty, as well as some of the psychosocial mechanisms involved in the intergenerational transmission of violence. Essential processes of child-parent attachment in the early years are explored, as well as the disorganization of early attachment related to violence. Among the effects of early attachment disorganization are failures in emotion regulation, social agency, and mentalization, all of which tend to distort future parent-child relationships, thus exposing the next generation to violence. Principles and policies to promote resilience among children in contexts of poverty are discussed in the last section of the chapter.
Double isolation: Identity expression threat predicts greater gender disparities in computer science

ABSTRACT Three studies examine the relationship between women’s expression of interest in computer science and identity expression threat, the concern about conveying an identity inconsistent with one's gender role. Undergraduates perceive academic majors to signal who they are to peers (Study 1). Women imagining majoring in computer science report greater identity expression threat from their peers outside computer science than from those inside the field (Study 2). Women report greater identity expression threat in computer science (but not biology or English) than do men. Identity expression threat mediates gender differences in reported likelihood of downplaying interest in computer science (Study 3). Women considering computer science perceive they will be doubly isolated, both from those within and outside the field.
Nonlinear Few‐Layer MXene‐Assisted All‐Optical Wavelength Conversion at Telecommunication Band

Optical signal processing based on 2D materials is a hot topic which has attracted rising interests. As a novel class of 2D material, MXene is becoming a promising nonlinear photonics material. In this contribution, MXene Ti3C2Tx, prepared by liquid acid etching method, is developed as a novel all‐optical device by depositing on a microfiber, which shows an excellent nonlinear optical response at the telecommunication band. The as‐fabricated device is employed as a wavelength converter based on the nonlinear four‐wave mixing effect with a conversion efficiency of –59 dB carrying a 10 GHz signal. The proposed all‐optical wavelength converter based on MXene Ti3C2Tx can play a remarkable role in the future of optical communications and optical information processing.
Environmental Contamination with Methicillin Resistant Staphylococci in Food animal carcasses

One hundred random samples of cattle and sheep meat, equipment and workers hands swabs (25 samples of each) were collected from different abattoirs in Kalyobia governorates. The obtained results indicated that the mean values of APC, and S. aureus counts in the examined samples were 1.5 x 104 ± 0.9 x 104, 1.77 x 103 ± 1 x 103CFU /g for cattle meat, 1 x 104 ± 0.65 x 104, 1.57 x 105 ± 0.83 x 105 CFU /g for sheep meat, 7.4 x 103 ± 0.29 x 104, 1.1 x 103 ± 0.33 x 103 CFU /g for equipment swab and 5.77 x 103 ± 0.3 x 104, 7.4 x 103 ± 0.49 x 104CFU /g, for workers hands swab, respectively. The incidence of S. aureus was 52%, 48%, 56% and 64% in the examined samples of cattle and sheep meat, equipments and workers hands swabs, respectively. On the other hand, Methicillin Resistant S. aureus (MRSA) was isolated from 32%, 24%, 40% and 44% of the examined samples of cattle and sheep meat, equipments and workers hands swab respectively. The significance of the isolated bacteria in the examined animal carcasses at abattoir level and possible sources of contamination as well as some recommendations to improve the quality of these carcasses were discussed.
Healing Traumatic Reenactment: Psyche's Return from Soma's Underworld

Interweaving somatic, Jungian, and psychodynamic treatment approaches with affective neurobiology, this article offers a clinical application of regulation theory to a specific case of traumatic reenactment. This integrated treatment model for patients with chronically impaired self-regulation emerges out of the author's interest in early attachment trauma, its impact on the developing brain and body, and its long-term psychological and physiological effects. 1 Every year in October, with an almost biological urgency, a young woman I'll call Beth would descend into the underworld of tumultuous relationship loss on the anniversary of her father's death. Freud (1961/1920) first conceptualized such behavioral reenactments as "repetition compulsion. " He believed they were caused by unconscious conflict paired with repression. Jung (1960/1934), however, following Janet, recognized that overwhelming affects in the body trigger dissociation. When part of the psyche splits off to form an unconscious "traumatic complex," it behaves autonomously, sometimes like a wild animal, reenacting the trauma. From Schore's (2002) perspective, the attachment relationship directly shapes the maturation of an infant's developing brain. Traumatic reenactment (TR) belies structural and functional deficits in the stress coping mechanisms of the right brain, resulting from early attachment trauma (pediatric PTSD) that often goes undiagnosed. Physiological contributors to TR probably include a combination of both nature (innate vulnerability) and nurture (early attachment deficits). Eagle (1984) notes that such developmental deficits, rather than dynamic conflict, are now being viewed in psychoanalytic theory as the source of this and various other pathologies. According to Levine (1997), traumatic reenactment is the psychesoma's attempt to repair this deficit by completing the nervous system's unfinished "fight-flight-freeze" survival cycle. This paper emerges out of my interest in early attachment trauma, its impact on the developing brain and body, and its long-term effects as manifested in a variety of psychological and physiological conditions. After a brief overview of the neurobiology of TR, I'll present a treatment vignette and commentary. Weaving together somatic and analytic approaches, this article offers an integrated treatment model for patients with chronically impaired self-regulation.
Vestige Theory: Sociolinguistic Evidence for Output-output Constraints

This article proposes a model of variation and change within the Optimality Theory framework. Previous attempts to account for variation in Optimality Theory have a common flaw; they fail to include a link to the external world where demographic factors such as gender, age, style, register, and social class play a material role in linguistic behavior. I propose Vestige Theory as a means of using Optimality Theoretic architecture to license the influence of language external factors. Vestige Theory claims that language change is always the result of constraint demotion and that the demotion of a constraint leaves behind a vestige of itself. This vestige constraint is a kind of output-output constraint. It differs from the “true” constraint that is demoted as part of language change. As an output-output constraint, a vestige constraint has the link to the outside world (i.e. to external factors) that previous models have failed to incorporate.
Real-Time Quality-Aware PPG Waveform Delineation and Parameter Extraction for Effective Unsupervised and IoT Health Monitoring Systems

In this paper, we present a real-time quality-aware pulse waveform delineation and parameter extraction method for accurate and reliable measurements of pulse parameters from photoplethysmogram (PPG) signals. It consists of three major stages: the PPG signal quality assessment (PPG-SQA) using autocorrelation function (ACF) and number of threshold-crossings (NTC) features, the zero-frequency resonator (ZFR) based pulse onset and peak determination, and the pulse parameter extraction. The method is implemented on the Arduino Due with a 32-bit Atmel SAM3X8E ARM Cortex-M3 CPU, 512-kB flash memory, 96-kB SRAM, and 84-MHz clock speed. The method is evaluated on the recorded PPG signals and three standard PPG databases. The PPG-SQA algorithm achieves an average sensitivity (Se)=98.62%, specificity (Sp)=97.37%, and overall accuracy (OA)=98.09%. The algorithm achieves an average Se=99.88%, positive predictivity (Pp)=99.89, Se=99.82%, and Pp=99.95%, respectively with the delineation errors (mean ± standard deviation) of 8.45 ± 9.39 $ms$ and 0.23 ± 1.33 $ms$ for finding onsets and peaks, respectively. The statistical analysis demonstrates that the parameter measurement errors are minimum for most of the pulse cycles. Results show that our quality-aware PPG analysis scheme can achieve a false alarm rate reduction (FARR) of 97.36% which outperforms the other existing SQA algorithms. It can lead to save transmission and processing energy from 8.33% to 95.63% and 8.33% to 59.77% for a duration from 5 to 60 s, respectively. The method has great potential for low-energy IoT and unsupervised health monitoring devices.