Miracle-dz/UniFAR-FTUs huggingface dataset:
AGE AND SEX COMPARISON IN DETERMINING BASELINE BLOOD AND COAGULATION PROFILES IN SEMI-EXTENSIVE RUSA DEER (RUSA TIMORENSIS)

The objective of the study was to establish the baseline values for blood and coagulation parameters in normal and healthy rusa deer ( Rusa timorensis ) of different ages and sexes. The sample population consists of 40 rusa deer, divided into four groups of (i) juvenile males (ii) juvenile females (iii) adult males and (iv) adult females. The findings showed significant ( p <0.05) higher values in erythrocyte count, calcium concentration and prothrombin time in the adult males compared to adult female rusa deer. On the other hand, the total protein concentration was significantly higher in adult females than adult male deer. No significant differences in blood or coagulation parameters were observed between sexes in the juvenile deer. Between age group, the adult deer had significantly higher mean cell volume, plasma protein and globulin concentration than juvenile rusa deer. Thus, it is necessary to take into account the age and sex of the rusa deer when using blood reference values for the diagnosis of diseases or health assessment.
Scaling Rules for Microrobots with Full Energetic Autonomy

There is an increasing need for wireless autonomous micro electromechanical systems (MEMS) and microrobots that can perform various functions such as sensing, diagnosis, locomotion, actuation, implantation, material removal, manipulation, and localized drug delivery. A major problem with these systems is the production, storage, and transduction of power at the micro scale. In addition, these miniature devices cannot use existing battery packs that are commonly used to power electronic devices. These MEMS and microrobots need on-board power sources that are miniaturized to their size. Together with the energy of an external source, some basic functions of microrobots can be powered simultaneously. This study seeks to develop a theoretical framework based on a chemo-electromagnetic model for use in the design of microrobots with full energetic autonomy. We first conceive a microrobot design and derive its mathematical model; the design consists of an on-board fuel generator, electrochemical device, electromagnetic device, and a locomotion mechanism. Then we present numerical simulations to show the relationship between the consumption rate of the H2 source, power density, and angular and translational velocities at low Reynolds number. We find that power density decreases approximately linearly with the diameter, while the relative velocity with respect to the body-length is approximately inversely proportional to the size, making downscaling favourable for this class of untethered devices.
SAUDI MOTHERS KNOWLEDGE REGARDING THE TEETHING PROCESS IN THEIR CHILDREN

Introduction : Several other symptoms may also be present when children are teething. They include drooling, swollen gums, rhinorrhea, and loss of appetite. These symptoms can be treated by using several methods, which include gingival massage and comforting bottles. Materials and methods: We used a closed-ended questionnaire, which was constructed online using Google forms. The survey was sent out using emails, social media websites, etc. We used a convenient sampling technique targeting mothers having at least one child under the age of 2 years. Results : We found statistically significant comparisons when inquired about smoking-related to painful teething in babies and teething causing ear infection, in both cases the mothers having 5 or more children had higher responses. Conclusion : Mothers having more experience with children showed slightly better awareness of the overall information and management of teeth process.
N ET X PLAIN : R EAL - TIME EXPLAINABILITY OF G RAPH N EURAL N ETWORKS APPLIED TO C OMPUTER N ETWORKS

Recent advancements in Deep Learning (DL) have revolutionized the way we can efﬁciently tackle complex optimization problems. However, existing DL-based solutions are often considered as black boxes due to their high inner complexity. As a result, there is still certain skepticism among the computer network industry about their practical viability to operate data networks. In this context, explainability techniques have recently emerged to unveil why DL models make each decision . This paper focuses on Graph Neural Network (GNN) models applied to computer networks, which have already shown outstanding performance in different network optimization tasks. We thus present NetXplain, a novel real-time explainability solution that uses a GNN to interpret the output produced by another GNN . In the evaluation, we apply the proposed explainability method to RouteNet –a GNN model that predicts end-to-end performance metrics in computer networks. We show that NetXplain operates more than 3 orders of magnitude faster than state-of-the-art explainability solutions when applied to networks up to 24 nodes, which makes this solution compatible with real-time applications. Moreover, it demonstrated strong generalization capabilities over different network scenarios unseen during training.
Viscoelastic-plastic Material Models: a Comparison Between Numerical Results and Experimental Tests

—A viscoelastic-plastic material model applicable to three-dimensional stress states has been considered as a viable alternative to describe the behavior of structural systems made of bituminous mixtures in a relatively simple way. Actually, this model, which takes into account both viscous and plastic strains, appears to be suitable for the numerical analysis of systems subjected to time-dependent loads of different nature, although it requires a limited number of parameters and can be implemented in traditional, robust algorithms developed for nonlinear materials. In this paper, we will make use of finite element meshes and, for each sample problem, will carry out an incremental analysis in order to compute the time-dependent viscous strains. To this aim, we will subdivide the load history into a finite number of time-steps. In addition, since the material model also includes plastic deformations, the computer code will exploit an iterative algorithm to determine the non-reversible strains during each time-step. The numerical examples will focus on the response of cylindrical test specimens subjected to compression loads, with special emphasis given to square-wave loading . However, static creep tests will also be considered, in order to check the response of the viscoelastic-plastic material model in the presence of different load conditions. More specifically, we will compare numerical results with experimental data, showing that a convenient choice of seven parameters can lead to accurate results in very different situations, even though the material model is relatively simple and can easily fit in any computer program designed for nonlinear structural analysis.
Key determinants of waste separation intention: empirical application of TPB

Purpose This study aims to identify the key determinants of waste separation intention among the students in Universiti Teknologi Malaysia (UTM). Design/methodology/approach This study adopted the theory of planned behaviour (TPB) as the fundamental framework. The key determinants of waste separation behaviour are attitude, subjective norm (SN) and perceived behavioural control. An elicitation survey has been conducted to explore the students’ beliefs relative to waste separation behaviour. The empirical data collected were analysed using structural equation modelling (SEM) assisted by SmartPLS software. Findings The result shows that only two determinants are significant towards intention, attitude and perceived behavioural control, while SN is not. The results of the study are significant to the organisation, as an identification of the determinants that influence waste separation intention contributes to a more focused waste separation programme aligned to Malaysia’s objective towards a sustainable developing country. Originality/value There are few studies on solid waste separation compared to food waste and industrial waste separation. The authors focus on the identification of the key determinants of solid waste separation intention among students. This study serves as an initial attempt to adopt the TPB in solid waste separation context, hence contributing to existing literature.
Fertilizer recommendation based on soil testing for the targeted yield of coriander ( Coriandrum sativum L . ) in an Inceptisol

Soil Test crop response correlation studies on coriander (Coriandrum Sativum L.) based on targeted yield approach was conducted on Inceptisol of Agricultural Research Farm, Banaras Hindu University, Varanasi during rabi 2018-19 by using integrated plant nutrient management system through which fertilizers recommendation equation for coriander may be achieved. Soil test data, coriander grain yield and NPK uptake by coriander crop were used for achieving four important basic parameters, viz., nutrients required to produce one quintal of coriander grain (NR), contribution of nutrients from fertilizers (%CF), contribution of nutrients from soil (%CS) and contribution of nutrients from organic matter-FYM (%C-OM). Results revealed that 4.83, 0.80 and 4.10 kg of N, P 2 O 5 and K 2 O, respectively were required for producing one quintal coriander grain yield. The per cent contribution of nutrients from soil, fertilizer and FYM were 21.17, 56.63 and 9.56 for N; 60.86, 39.25 and 2.38 for P 2 O 5 and 25.50, 114.41 and 5.22 for K 2 O, respectively. Based on this information fertilizer prescription equations were developed to predict fertilizer recommendation for obtaining specific yield target of coriander. Incorporation of farmyard manure enhanced the recovery of nutrients considerably. After the verification of these equations at farmer’s fields, these can be used for fertilizer recommendations in Eastern Uttar Pradesh having similar soil and climatic conditions.
Beyond Burnout: How Elementary Teachers Cope and Flourish in a Pandemic-Era School

Many studies describe the pervasiveness of burnout in underserved schools and the factors that lead to burnout, but those studies rarely utilize the voices and lived experiences of teachers (Camacho et al., 2021). Many studies also describe reasons why teachers leave the field, but few explore why teachers remain in the field and what coping strategies they use to persevere through burnout (Turner & Theilking, 2019). These gaps in the literature are particularly pressing as rates of teacher burnout and attrition have reached alarming levels (Kamenetz, 2022). Through in-depth interviews with four teachers at an underserved school in the Bay Area, this study sought to answer the following research questions: (1) How do teachers at underserved schools perceive their experiences of burnout? (2) What coping strategies do teachers use? The findings show that teachers have experienced unprecedented changes since the start of the Covid-19 pandemic and those changes have led to an acutely stressful period in teaching. Most described this year as the most stressful in their careers. Despite extensive stressors, teachers are coping through mindfulness, intentional self-talk, boundaries, and community.
Computer-Aided diagnosis of closely related diseases

It is often observed that certain human diseases exhibit similarities in some form while having different prognoses and requiring treatment strategies. These similarities may be in the form of risk factors towards the diseases, symptoms observed, visual similarity in imaging studies, or in some cases, similarity in molecular associations. Computer-Aided Diagnosis (CAD) of closely related diseases is challenging and requires tailored approaches to discriminate between such closely related diseases accurately. This thesis looks at two sets of closely related diseases of two different organs, identified from two different modalities. It develops novel approaches to achieve explainable and accurate CAD for these two close diseases. These two problems are discrimination of healthy, mild cognitive impairment (MCI) and Alzheimer’s Disease (AD) from brain MRI-derived surface mesh and classifying healthy, non-COVID pneumonia and COVID from chest X-ray images. In the first part of this thesis, we present a novel 2D image representation for the brain mesh surface, called a height map. Further, we explore the use of height maps towards the hierarchical classification of healthy, MCI, and AD cases. We also compare different strategies of extracting features and regions of interest from height maps and their performance towards healthy vs. MCI vs. AD classification. We demonstrate that the proposed method achieves fast classification of AD and MCI with minor loss of accuracy compared to state of the art. In the second half of this thesis, we present a novel deep learning architecture called Multi-scale Attention Learning Residual Learning (MARL) and a new conicity loss for training the MARL architecture. We utilize MARL and the conicity loss for achieving hierarchical classification of normal, non-COVID pneumonia and COVID pneumonia from Chest X-ray images. We present classification results on three public datasets and demonstrate that the proposed method achieves comparable or marginally better performance than state-of-the-art in all cases. Further, we demonstrate that the proposed framework achieves clinically consistent explanations with extensive experimentation. Qualitatively, this is shown by comparing GradCAM heatmaps for the proposed method to those for the state-of-the-art method. It is observed that the heatmaps overlap better with the bounding boxes for pneumonia marked by experts compared to the overlap achieved by the state-of-the-art method. Next, we show quantitatively that the GradCAM heatmaps for the proposed method generally lie within inner regions of the lung for nonCOVID pneumonia. However, the same heatmaps lie in outer regions in the case of COVID pneumonia. Thus, we establish the clinical consistency of explanations provided by the proposed framework.
Design of an X-cut thin-film lithium niobate waveguide as a passive polarization rotator

: The transverse-electric and transverse-magnetic modes of an X-cut thin-film lithium niobate waveguide vary in effective indices and exchange power when the waveguide makes an oblique angle with its crystallographic Z-axis, i.e. its optics axis. We leverage this phenomenon to design a passive fundamental-mode polarization rotator. In our design, the lithium niobate waveguide is tilted at an optimum angle with respect to its Z-axis, such that material anisotropy induces phase-matched polarization conversion. We discuss the rotator’s ideal-device length, crosstalk, and bandwidth. The proposed design yields compact (shorter than 1 mm), low-loss, passive polarization rotators for telecom wavelengths.
PREVALENCE OF TEMPOROMANDIBULAR DISORDERS AMONG ORTHODONTIC PATIENTS (CROSS-SECTIONAL CLINICAL SURVEY)

Orthodontic treatment as a risk factor for the development of temporomandibular disorders (TMD) has been a controversy in literature. The aim of this study was to evaluate the prevalence of TMD, as defined in the Diagnostic Criteria (DC)/TMD Axis II, among orthodontic patients. A cross-sectional study (N=180) consisted of 3 groups: 60 control patients seeking orthodontic consultation, 60 patients undergoing orthodontic treatment for 3-5 months, 60 patients undergoing orthodontic treatment for 10-14 months. Patients answered a structured questionnaire that rated their oral parafunctions according to the Oral Behavior Checklist (OBC), pain intensity levels according to the Graded Chronic Pain Scale (GCPS), jaw functional limitations according to the Jaw Functional Limitation Scale 20 (JFLS-20), psychosocial factors (PHQ-9) and somatization levels (PHQ-15). The Chi Square test showed a statistically significant difference p-value=0.001 among both active orthodontic groups (3-5 months/10-14 months) regarding masticatory limitation (53.3%), vertical mobility limitation (41.7% for 3-5 months and 55.0% 10-14 months) and verbal & emotional expression limitation (53.3% 3-5 months and 66.7% 10-14 months). The findings revealed that as orthodontic treatment progresses, the limitation increases. Moreover, no statistical significance was observed between the three groups regarding oral parafunctional habits, chronic pain levels, psychosocial status and somatization. Orthodontic treatment is not a major factor associated with the symptoms of the TMD. Further prospective studies are needed to evaluate the true role of orthodontic treatment in the development of TMD.
Estimation of Games under No Regret

We develop a method to estimate a game’s primitives in complex dynamic environments. Because of the environment’s complexity, agents may not know or understand some key features of their interaction. Instead of equilibrium assumptions, we impose an asymptotic ε-regret (ε-AR) condition on the observed play. According to ε-AR, the time average of the counterfactual increase in past payoffs, had each agent changed each past play of a given action with its best replacement in hindsight, becomes small in the long run. We first prove that the time average of play satisfies εAR if and only if it converges to the set of Bayes correlated ε-equilibrium predictions of the stage game. Next, we use the static limiting model to construct a set estimator of the parameters of interest. The estimator’s coverage properties directly arise from the theoretical convergence results. The method applies to panel data as well as to cross-sectional data interpreted as long-run outcomes of learning dynamics. We apply the method to pricing data in an online marketplace. We recover bounds on the distribution of sellers’ marginal costs that are useful to inform policy experiments.
Macroscopical and Scanning Electrone Microscopical Studies on the Rectal Caeca of Three Different Habitually Feeding Birds

The present investigation was carried out to study the variations of the morphology and scanning electron microscopy of rectal caeca in three birds, Coturnix coturnix, Cairina moschata and Athene noctua to understand the role of caeca in digestion. This study shows that, there is a great difference in the caecal morphology and structures between the three selected birds. The present findings revealed that the rectal caeca are composed of three regions, proximal, middle and distal. Also the caeca show different colours as well as asymmetrical lengths. At the level of the scanning electron microscope study there is a great difference in the mucosal sculpturing (micro-ornamentation) between the three selected birds. These differences can be related to the environmental habits preferences of the birds and support those of other studies that the caecal development is related to diet.
The Mediating Effects of Perceived Value Between the Relationship of Social Media Marketing and Purchase Intention

The objective of this study is to test the mediating role of the dimensions of perceived value—conditional, epistemic, monetary, social, convenience, and emotional—between the relationship of social media marketing and purchase intention, in online hotel booking sites. Partial least square structural equation modeling (PLS-SEM) was employed to test all 19 hypotheses. Results revealed that social media marketing positively and significantly influences the dimensions of perceived value, as well as purchase intention. Also, convenience value and conditional value are positively and significantly related to purchase intention. In terms of the mediating effects, it was found that both convenience value and conditional value have a mediating effect on the relationship between social media marketing and purchase intention. This study has implications for hospitality marketers and hoteliers.
The U.S Monetary Policy Spillover Effect in China and Its Transmission Mechanism

With the rapid development and continuous advancement of economic globalization, the links between countries around the world have become increasingly tight. Among them, the United States, as the world's largest economy, its monetary policy is bound to cause significant spillover effects on other economies around the world. By constructing a Threshold SVAR model with monthly data from 1996 to 2019, this paper empirically investigates the spillover effects of US monetary policy on China's economy during different U.S policy regimes. The transmission mechanism of such effects has been examed through different channels including policy channel, trade channel, asset value channel and information channel. The estimated threshold values of the Fed Fund rates/Shadow rates are between 0.905-0.990, which coincides with the unconventional policy period of U.S monetary policy. Also, the responses of different channels to U.S. monetary shocks in the lower regime(unconventional time) are different from those responses in the upper regime(conventional time). and Transmission Zhuo Besides spillover effects, various studies are using the Threshold SVAR model to address the nonlinear response effects under different regimes. Balke (2000) is the first to employ the Threshold SVAR model in the literature of macroeconomics. He tests and estimates a threshold vector autoregression that changes the structure if credit conditions cross a critical threshold. Then he uses nonlinear impulse-response analysis to isolate the relative effects of shocks. The author finds that shocks tight-credit regime. adopt U.S monetary In addition, the estimated long run coefficients and the error-correction parameter are shown. The significant error correction parameter implies that there is a relatively quick adjustment in the Chinese EPU when the U.S EPU changes, which in turn confirms the intensity of the information channel.
ASSESSMENT OF NUTRITIONAL STATUS AND OBESITY OF COLLEGE GOING GIRLS IN TRANSYAMUNA AREA, PRAYAGRAJ

Obesity is one of the most serious public health challenges of the 21st century. The problem is global and is steadily affecting many low- and middle-income countries, particularly in urban settings. The prevalence has increased at an alarming rate. (Ashok, 2014). Aim: the objective is to assess the nutritional status and find out life style pattern of college going girls. Methods: In the present study, an attempt has been made to assess the obesity among 50 college going girl of Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj. For this purpose height and weight measurements were taken on each subject. The rate of obesity was calculated according to the critical limits of body mass index (BMI). Dietary intake and physical activity levels were collected by interviewing the subjects using a validated questionnaire. Statistical analysis: Mean test was applied for figuring out the relevant results. Result: the present study revealed that out of total, 18 percent girls were overweight followed by 24 percent who were grade I obese then 12 percent who were grade II obese whereas, 32 percent of girls were having normal BMI . Study also reveal that most of them were not doing any kind of physical activity and 100 percent girls were having sedentary lifestyle which includes 62 percent girls had 6 hours sleeping time, followed by 26 percent girls who had 7 hours sleeping time. Food habbits include junk food consumption that is 62 percent on daily basis, and 40 percent girls were following vegetarian diet. Uptake of high calorie, fat, carbohydrate were seen whereas, protein and fibre were found to be deficit in the study when compared with RDA (2010). Conclusion: All girls were following sedentary lifestyle and were consuming junk food on regular basis. Obese respondents were significantly higher than non-obese group respondents. The intake of protein, fiber was deficit (according to RDA, 2010) whereas the consumption of energy, fat and carbohydrate to