Miracle-dz/UniFAR-FTUs huggingface dataset:
Laboratory Diagnosis of Tuberculosis: Conventional and Newer Methods

Tuberculosis is the main cause for loss of life from a single infectious agent known as Mycobacterium tuberculosis (M.tb). Tuberculin skin test (TST) and interferon-gamma release assays (IGRAs) are two approaches available for testing of latent TB infection but none of these can accurately differentiate between active TB disease and TB infection. Emergence of drug resistant tuberculosis particularly multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis is a challenge to eliminate tuberculosis worldwide. The acidfast bacillus (AFB) smear microscopy remains the foremost frequently used microbiological test for detection of TB, however it can neither differentiate between live and dead bacilli, nor give any information regarding drug susceptibility testing (DST). Phenotypic culture remains the gold standard but is time consuming and requires good infrastructure. Therefore, significant efforts have been made in last few years for advancement in molecular/genotypic technologies like line probe assay (LPA), cartridge based nucleic acid amplification test (CBNAAT), Truenat MTB test, loop-mediated amplification (LAMP) test, whole genome sequencing etc. Some of these methods have been endorsed by the WHO and have proven to improve case detection and management of TB patients. Presently there is no single test which can be used for detection of tuberculosis in all patients. We have to depend upon combination of different tests and see how to place them in diagnostic algorithm so as to appropriately use all the available diagnostic modalities taking into account factors such as the capacity of different levels and requirement of infrastructure/man power.
Interface Pressure Distribution in a Bolt-Flange Assembly

The interface pressure distribution of a single bolt-flange assembly was measured for the various surface topographies and the materials of the joint surfaces and also thicknesses of the upper flange by means of ultrasonic waves. The results show that the surface topography, the joint material, and the flange thickness have noticeable influences not only on the form of the interface pressure distribution curve but also upon the effective area of the connecting force. The measured interface pressure distribution and the effective area of the connecting force differ significantly from the analytical values so far presented from the results of theoretical studies using equivalent models with perfect joint surfaces or without joint surfaces.
EFFECTS OF REWARD SYSTEM ON EMPLOYEES’ SATISFACTION: THE CASE OF ASSOSA UNIVERSITY

There is a general consensus that employee satisfaction and commitment is affected by total rewards. The prime intention of this study is to examine the effect of intrinsic and extrinsic rewards on employee’s job satisfaction level in Assosa University. The study has employed both descriptive and explanatory research design and the primary data is collected from 218 academic staff employees in Assosa University. The study results revealed that, the mean employee’s satisfaction level is not too much satisfactory which indicates that academic staff employees are not satisfied with the reward system of Assosa University. It is found that the contribution of extrinsic reward for employee’s job satisfaction is more than intrinsic reward. Based on these results, Assosa University was strongly recommended to do more on to improve employees’ satisfaction toward their job by restructuring the intrinsic rewards that are being in place in the institution. Employees do get more satisfaction when they get good psychological treatment from the institution than just receiving monetary rewards.
Absence of Motor Coactivation in Bimodal Divided Attention: Two Case Studies

When attention is divided across vision and hearing, participants typically respond faster when a visual and an auditory target are presented together as compared to when only one of the visual or auditory targets is presented alone. Coactive models of divided attention account for this so-called bimodal advantage by positing a brain architecture whereby the neural activity inspired independently by concurrently presented auditory and visual targets is first processed in parallel and then pooled into a common resource. However, it remains unclear whether such pooling of activation occurs in the perceptual/cognitive processing of targets or later in the physical (motor) execution of the response. Here, two empirical case studies are reported examining the locus of coactivation in bimodal divided attention by way of planned theoretically driven analysis of each individual’s response times (RTs) and peak response forces (pRFs) to weak and energetic pulses of sound and light. Individually for both participants, RT was found to decrease with increased stimulus intensity and to be faster when both auditory and visual targets were presented together than the fastest RTs obtained when either target was presented alone. In contrast, pRF remained unaffected by either experimental manipulation. The results support current theoretical accounts of the bimodal advantage which posit an early or central locus of coactivation, with a subsequent motor component that ensues in a relatively invariant manner.
Towards Holistic Real-time Human 3D Pose Estimation using MocapNETs

In this work, we extend a method originally devised for 3D body pose estimation to tackle the 3D hand pose estimation task. Due to its compositionality and compact Bio Vision Hierarchy (BVH) output, the resulting method can be combined with the original 3D body pose estimation method. This is achieved based on a novel neural network architecture combining key design characteristics of DenseNets, ResNets and MocapNETs trainable to accommodate both bodies and hands. The resulting method is assessed quantitatively in well-established hand and body pose estimation datasets. The obtained results show that the proposed enhancements result in competitive performance for hands, as well as on accuracy and performance beneﬁts for the original body estimation task. Moreover, we show qualitatively that due to its real-time performance and easy deployment using off-the-shelf webcam equipped PCs, the proposed solution can become a valuable perceptual building block supporting a variety of applications.
Construction of a Macrophage Infiltration Regulatory Network and Related Prognostic Model of High-Grade Serous Ovarian Cancer

Background High-grade serous ovarian cancer (HGSOC) carries the highest mortality in the gynecological cancers; however, therapeutic outcomes have not significantly improved in recent decades. Macrophages play an essential role in the occurrence and development of ovarian cancer, so the mechanisms of macrophage infiltration should be elucidated. Method We downloaded transcriptome data of ovarian cancers from the Gene Expression Omnibus and The Cancer Genome Atlas. After rigorous screening, 1566 HGSOC were used for data analysis. CIBERSORT was used to estimate the level of macrophage infiltration and WGCNA was used to identify macrophage-related modules. We constructed a macrophage-related prognostic model using machine learning LASSO algorithm and verified it using multiple HGSOC cohorts. Results In the GPL570-OV cohort, high infiltration level of M1 macrophages was associated with a good outcome, while high infiltration level of M2 macrophages was associated with poor outcomes. We used WGCNA to select genes correlated with macrophage infiltration. These genes were used to construct protein-protein interaction maps of macrophage infiltration. IFL44L, RSAD2, IFIT3, MX1, IFIH1, IFI44, and ISG15 were the hub genes in the network. We then constructed a macrophage-related prognostic model composed of CD38, ACE2, BATF2, HLA-DOB, and WARS. The model had the ability to predict the overall survival rate of HGSOC patients in GPL570-OV, GPL6480-OV, TCGA-OV, GSE50088, and GSE26712. In exploring the immune microenvironment, we found that CD4 memory T cells and activated mast cells showed that the degree of infiltration was higher in the high-risk group, while M1 macrophages were the opposite, and HLA molecules were overexpressed in the high-risk group. Conclusion We constructed a macrophage infiltration-related protein interaction network that provides a basis for studying macrophages in HGSOC. Our macrophage-related prognostic model is robust and widely applicable. It predicts overall survival in HGSOC patients and may improve HGSOC treatment.
INFLUENCE OF INQUIRY LEARNING MODEL ON LEARNING OUTCOMES OF FAMILY PLANNING SERVICES AND REPRODUCTIVE HEALTH STUDY COURSES FOR MIDWIFERY UNGRADUATE STUDENTS OF ASSOCIATE’S DEGREE EDUCATION

Conventional learning that often used has not been achieved appropriate learning outcomes of students in higher education due to its one-way learning approach confines the access of more knowledge information. In conventional models lecturers more actively dominate learning and college students tend to be passive. One of the innovative, adaptive and creative learning models is inquiry learning. The aim of the present study was to analyze the influence of inquiry learning model on learning outcomes of family planning services and reproductive health study courses for midwifery students of associate’s degree education. The study was a quantitative study using the quasi-experimental design, One-group Design with Non-Equivalent Control Group Design. The locations of the study were conducted at Poltekkes Kemenkes Kendari and Stikes Pelita Ibu Kendari. The data analysis techniques used are Mann-Whitney and Wilcoxon. Learning process variables of lecturers’ activities, students’ activities, lecturers’ characteristics, and students’ responsses demonstrated significant differences of learning outcomes between the two learning models. Conventional learning and inquiry learning demonstrated significant influences on the increase of learning outcomes of midwifery students. However, the effectiveness of inquiry learning model was better in comparison to conventional learning model.
ROBUST CONTROL FOR REUSABLE ROCKETS VIA STRUCTURED H∞ SYNTHESIS

This paper discusses the problem of synthesizing robust controllers for reusable rockets during the aerodynamic descent phase. Emphasis is given to a well-established subset of methods, specifically robust control techniques based on the H∞ concept. A thorough description of how this family of methods can be used for the descent phase of reusable rockets is provided, together with a comparison of the fulland structured-version of H∞ methods. The methodology, the problem faced and the performance that can be obtained are discussed. Some results are shown for CALLISTO, a reusable rocket demonstrator jointly developed by DLR, JAXA, and CNES.
Relaciones padre-hijo en los emiratos Ã¡rabes unidos (EAU)

The family plays a crucial role throughout the child’s life, being responsible for raising him/her according to certain values, beliefs, attitudes, and behaviors accepted both in the family and respective society/culture. Specifically, parent-child relationship is proved to affect interpersonal skills and relationships, behaviors, academic achievement and professional, amongst others. Research shows that for a healthy, positive, and adaptive development, a close, warm, supportive, and accepting parent-child relationship should have place. In this research, it was aimed to analyze parent–child relationships in a very specific and idiosyncratic context that has been under lots of recent economic, social, cultural, and, we assume, familiar changes and that has been understudied: United Arab Emirates. Concretely, we explored Emirati parents’ perceptions on seven main dimensions of parent–child relationships: parental support and satisfaction, involvement, communication, limiting setting, autonomy and role orientation. The participants were 122 Emirati parents, mostly mothers (73.8%) and married (96.3%), with ages between 21 and 63 years old (M=35.98, SD= 9.172), and with different levels of education (50% of the parents have a bachelor degree). The instrument used was the Parent-Child Relationship Inventory (PCRI), a standardized instrument published by the Western Psychological Services that integrates 78 items with a 4-point agreement Likert scale, divided by the dimensions previously presented plus a validity indicator (social desirability). All the questionnaires were individually administered, and descriptive and correlational analyses were performed to understand Emirati parents’ attitudes towards their children and explore how the PCRI dimensions interrelate. Overall, Emirati parents perceive themselves as satisfied, involved and communicative with their children, meanwhile they face some difficulties in establishing limits and promoting autonomy, and tend to accept and apply within their families traditional gender roles. The dimensions of the PCRI exhibit a global pattern of positive and moderate intercorrelation, consistent with the theoretical background of this instrument. International Journal of Developmental and Educational Psychology INFAD Revista de Psicología, No1-Vol.3, 2014. ISSN: 0214-9877. pp:363-374 363 DIFICULTADES EDUCATIVAS PARENT-CHILD RELATIONSHIPS IN THE UNITED ARAB EMIRATES RELACIONES PADRE-HIJO EN LOS EMIRATOS ÁRABES UNIDOS (EAU) Joana Novaes Machado Stocker Assistant Professor at Zayed University – Dubai (joana.stocker@zu.ac.ae) Khairia Ghuloum Ali Mohamed Hassan Ali Fecha de Recepción: 21 Febrero 2014 Fecha de Admisión: 30 Marzo 2014 http://dx.doi. org/10.17060/ijodaep.2014. n1.v3. 514
THE DISTRESS RISK PREMIUM AND CROSS-SECTIONAL STOCK RETURNS

This article employs the Fama and Macbeth regressions and portfolio sorting methodologies to analyze the distress risk premium in the Taiwan stock market. The author collects collect the data of listed non-financial firms from 2008 to 2018. The new method effectiveness evaluation indicates that the Fama-French three-factor model could explain the bankruptcy risk premium in the Taiwan stock exchange. The findings show that firms with higher book-to-market risk earn more substantial returns for the same level of distress risk. The results also figure out the existence of distress risk premium in the Taiwan stock exchange. Specifically, firms with higher bankruptcy risk generate higher returns. The new findings extend the existing literature and provide investment strategies based on distress risk in the Taiwan stock exchange. The findings are also consistent with the risk-return hypothesis and prior literature.
Learning and Interactive Design of Shared Control Templates

Controlling a robotic arm to achieve manipulation tasks is challenging for humans. Especially if only low-dimensional input signals can be provided, as is often the case for users with motor impairments. Using shared control to provide task-specific guidance and constraints facilitates control – for instance with the Shared Control Templates (SCT) framework – and enables even complex activities of daily living to be performed successfully. However, designing SCTs is a laborious task requiring robotic expertise. To make such design easier and faster, we propose a method for semi-automatically designing SCTs on the basis of demonstrations. Furthermore, we propose two similarity metrics, and demonstrate how these can be used to transfer knowledge from one SCT to another. We demonstrate that the SCTs so acquired can be successfully used in shared control for everyday tasks such as opening a drawer or a cupboard on our assistive robot EDAN.
Elements of Health Consciousness in Consumer Behavior : A Post Covid Study

This article investigates how the demographic profiles of consumers influence their buying behavior in the organized food retail industry in India in the post Covid era, and how this outcome may assist the health management system. Data was procured by using a selfadministered survey of a convenient sample of 175 organized food retail consumers of India. The results exhibit that income is the most significant demographic profile of consumers which impacts their buying behaviorwith respect to seeking health and quality for better health consciousness. The article concludes that gender is another demographic profile of consumers which significantly impacts their buying behavior with respect to health consciousness. Managerial implications of this research find that the causal relationship between the demographic profiles (income and gender) and buying behavior of consumers enable the health marketers and retail managers in better planning and execution of retail strategies, with a better understanding of consumer’s health and safety concern.
Immunological evaluation of ( HSP 20 ) concentration in an aborted woman Infected with Toxoplasmosis

Background: Toxoplasmosis is one of the most common zoonotic pathogens worldwide; Immune response against this parasite was affected by synthesis of specific interleukins like HSP20. Objectives: This study aims to detect the prevalence of expression of HSP20 among women in Kufa city. Methodology: Case-control study, purposive (probability) sample was done among hindered and forty eight miscarriages women were attended to the Central Health Laboratory . The data collected from October 2020 to January 2021. The concentration levels of HSP20 in women were measured by ELISA technique according to many parameters such as age, residence and number of abortion. Results: The current study revealed that the high (4.179±8.793) ng/ml concentration of Hsp 20 was recorded in cases with age 19-23 years through measuring its serum level. Conclusion: HSP20 play a significant role in immunity against infection with Toxoplasma gondii. Recommendation: Further studies are recommended to know the concentration of HSP20 among against another type of parasitic infection.
Differentiable Architecture Search Meets Network Pruning at Initialization: A More Reliable, Efﬁcient, and Flexible Framework

Although Differentiable ARchiTecture Search (DARTS) has become the mainstream paradigm in Neural Architecture Search (NAS) due to its simplicity and efﬁciency, more recent works found that the performance of the searched architecture barely increases with the optimization proceeding in DARTS, and the ﬁnal magnitudes obtained by DARTS could hardly indicate the importance of operations. The above observation reveal that the supervision signal in DARTS may be a poor or unreliable indicator for the architecture search, in-spiring an interesting and promising direction: can we measure the operation importance without any training under the differentiable paradigm ? We provide an afﬁrmative answer by customizing the NAS as a network pruning at initialization problem. With leveraging recently-proposed synaptic saliency criteria in the network pruning at initialization, we seek to score the importance of candidate operations in differentiable NAS without any training, and proposed a novel framework called training free differentiable architecture search ( FreeDARTS ) accordingly. We show that, without any training, FreeDARTS with different proxy metrics can outperform most NAS baselines in different search spaces. More importantly, FreeDARTS is extremely memory-efﬁcient and computational-efﬁcient as it abandons the training in the architecture search phase, enabling FreeDARTS to perform architecture search on a more ﬂexible space and eliminate the depth gap between architecture search and evaluation. We hope our work inspires more attempts in solving NAS from the perspective of pruning at initialization.
Mid-infrared Outbursts in Nearby Galaxies (MIRONG). II. Optical Spectroscopic Follow-up

Infrared echo has proven to be an effective means to discover transient accretion events of supermassive black holes (SMBHs), such as tidal disruption events (TDEs) and changing-look active galactic nuclei (AGNs), in dusty circumnuclear environments. To explore the dusty populations of SMBH transient events, we have constructed a large sample of mid-infrared outbursts in nearby galaxies (MIRONG) and performed multiwavelength observations. Here we present the results of multiepoch spectroscopic follow-up observations of a subsample of 54 objects spanning a timescale of 4 yr. Emission-line variability was detected in 22 of them with either emergence or enhancement of broad Balmer emission lines in comparison with pre-outburst spectra. Coronal lines, He ii λ4686, and Bowen line N iii λ4640 appeared in the spectra of nine, seven, and two sources, respectively. These results suggest that MIRONG is a mixed bag of different transient sources. We have tentatively classified them into different subclass according to their spectral evolution and light curves. Two sources have been in a steady high broad Hα flux up to the latest observation and might be turn-on AGNs. Broad lines faded out in the remaining sources, indicating a transient ionizing source ignited by TDE or sporadic gas accretion. Thirty-one sources do not show noticeable spectral change with respect to their pre-outburst spectra. They have a statistically redder MIR color and lower MIR luminosity of the outbursts, which are consistent with heavily obscured events.
TRIP: Refining Image-to-Image Translation via Rival Preferences

Relative attribute (RA), referring to the preference over two images on the strength of a specific attribute, can enable fine-grained image-to-image translation due to its rich semantic information. Existing work based on RAs however failed to reconcile the goal for fine-grained translation and the goal for high-quality generation. We propose a new model TRIP to coordinate these two goals for high-quality fine-grained translation. In particular, we simultaneously train two modules: a generator that translates an input image to the desired image with smooth subtle changes with respect to the interested attributes; and a ranker that ranks rival preferences consisting of the input image and the desired image. Rival preferences refer to the adversarial ranking process: (1) the ranker thinks no difference between the desired image and the input image in terms of the desired attributes; (2) the generator fools the ranker to believe that the desired image changes the attributes over the input image as desired. RAs over pairs of real images are introduced to guide the ranker to rank image pairs regarding the interested attributes only. With an effective ranker, the generator would"win"the adversarial game by producing high-quality images that present desired changes over the attributes compared to the input image. The experiments on two face image datasets and one shoe image dataset demonstrate that our TRIP achieves state-of-art results in generating high-fidelity images which exhibit smooth changes over the interested attributes.
Amortized Prompt: Lightweight Fine-Tuning for CLIP in Domain Generalization

Domain generalization (DG) is a diﬃcult transfer learning problem aiming to learn a generalizable model to unseen domains. Recent massive pre-trained models such as CLIP and GPT-3, i.e. foundation models (FMs), have been shown to be robust to many distribution shifts and therefore should lead to substantial improvements in DG. In this work, we study generic ways to adopt CLIP for DG problems in image classiﬁcation, where we evaluate on naive zero-shot learning and full DG learning settings. For the latter, we propose AP (Amortized Prompt), as a novel approach for domain inference in the form of prompt generation. Using several standard datasets on domain generalization benchmark, namely PACS, VLCS, OﬃceHome, and TerraIncog-nita, CLIP provides comparable performance without ﬁne-tuning any parameters , suggesting the applicability and importance of FM in DG. In addition, we show that combining domain prompt inference with CLIP enables AP to outperform strong baselines and the naive CLIP baselines by a large margin, raising accuracy from 71.3% to 79.3%. We hope the simplicity and success of our approach emphasizes the importance of and leads to wider more adoption and analysis of foundation models in the ﬁeld of domain generalization.