Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Awareness and Nutritional Status of Rural Community: A Cross Sectional Study

Background: COVID-19 Pandemic had led to an unprecedented emergency which led to many transformations in all aspects of life including dietary practices. A good and balanced die played a crucial role in prevention of disease and faster recovery. For a good dietary practice, knowledge and awareness is needed. Even the SDG 2 deals with food, nutrition and curbing with hunger. The purpose of this study was to explore the awareness of good dietary habits and the nutritional content of everyday meals among rural communities as well as to assess the nutritional status and physical activity. Methods: This was a observational cross-sectional study conducted amongst the community of from two rural zones in Jalgaon district, Maharashtra in April to June 2022. Convenience sampling with the sample size as 40 households residing in the community was used. The head of the family of each household were surveyed using a pre-designed and pre-tested structured questionnaire. The tool used to explore the daily food consumption, assessment of nutritional status and physical activities of the participants. The study also determined at people's awareness of what a balanced diet is and the concept/effects of malnutrition in addition to anthropometric measurements. Data was entered in spreadsheet and analysis was done with the Microsoft excel using descriptive statistics. Results: Of those surveyed, regarding nutritional awareness, it was found that 92% and 82% of the subjects have not even heard of the term "Balanced diet" and “Malnutrition” respectively. The BMI ranges of the study subjects, showed that majority (22, 55%) of the study participants had normal BMI, followed by (13, 32.5%) as underweight i.e. BMI below 18.5 and (5; 12.5%) as pre-obese category, i.e. BMI above 25. It was observed that the individuals used to undertake around 8 hrs of physical activity per day on an average. Regarding the diet pattern, it was noted that rural communities still follow follows traditional wisdom of a balanced diet from ancestral roots. Due to poverty and lack of resources, they tend to stick to whatever is affordable and locally available. Conclusion: Considering the significant unawareness regarding nutrition and balanced diet as observed, we conclude that the Government’ plans and efforts around food security will be more successful if raising public awareness about the significance of nutrition and food is the first step in this regard. The right to food and the right to health can only reach the rural areas when the awareness index in these areas is enhanced by utilizing all available tools and approaches.
Empirical global model of upper thermosphere winds based on atmosphere and dynamics explorer satellite data

Thermospheric wind data obtained from the Atmosphere Explorer E and Dynamics Explorer 2 satellites have been used to generate an empirical wind model for the upper thermosphere, analogous to the MSIS model for temperature and density, using a limited set of vector spherical harmonics. The model is limited to above approximately 220 km where the data coverage is best and wind variations with height are reduced by viscosity. The data base is not adequate to detect solar cycle (F10.7) effects at this time but does include magnetic activity effects. Mid- and low-latitude data are reproduced quite well by the model and compare favorably with published ground-based results. The polar vortices are present, but not to full detail.
Maximality of the sum of the monotone operator of type (FPV) and a maximal monotone operator

Here, question raised by Borwein and Yao has been settled by establishing that the sum of two maximal monotone operators A and B is maximal monotone with the condition that A is of type (FPV) and satisfies Rockafellar's constraints qualification. Also we have proved that A+B is of type (FPV) without assuming convexity on the domain of A.
The Impact of Celebrity Endorsement on Followers’ Impulse Purchasing

Abstract Although the issue of celebrity endorsement has been the subject of longstanding discussion, little attention has been paid to the impulse purchasing behavior of celebrity followers. This study was conducted from the relationship marketing perspective and tested the impact of parasocial relationships between celebrities and their followers on the impulse purchasing. The proposed model included parasocial relationships, followers’ emotional responses to celebrity-based commercials, impulsive buying tendencies, and the availability of money. Data was collected from people who follow a favorite celebrity who previously endorsed a product. We obtained 323 valid samples and performed data analysis with the Statistical Package for Social Sciences (SPSS) to test the proposed model. The study illustrated how situational, emotional, and personal factors might influence the impulse buying of celebrity-endorsed products and showed that a stronger para-relationship with the celebrity led to the audience’s pleasure and arousal while watching the celebrity endorsement. These two emotions were positively related to the impulse purchasing of celebrity-endorsed products and the purchasing behavior moderated by audiences’ impulse buying tendencies and money availability. This study investigated the celebrity endorsement’s influence on the audience’s impulse purchasing behavior and provided future research directions on celebrity endorsement.
A new synthesis algorithm with application to adaptive beamforming

The new synthesis algorithm iterates the weighting function in a weighted sum of squared pattern errors. At each iteration, the element weights minimize this sum. In a way similar to Olen and Compton's adaptive synthesis algorithm, sidelobe requirements are conveniently met, but unlike their algorithm, mainbeam shaping is provided without the need for multiple constraints. Peak-only iteration makes this synthesis algorithm computationally efficient so that it can be combined with the sample matrix inversion algorithm to create a new real-time adaptive beamforming algorithm with improved beam pattern control in comparison with conventional tapering.
AxPPA: Approximate Parallel Prefix Adders

Addition units are widely used in many computational kernels of several error-tolerant applications such as machine learning and signal, image, and video processing. Besides their use as stand-alone, additions are essential building blocks for other math operations such as subtraction, comparison, multiplication, squaring, and division. The parallel prefix adders (PPAs) is among the fastest adders. It represents a parallel prefix graph consisting of the carry operator nodes, called prefix operators (POs). The PPAs, in particular, are among the fastest adders because they optimize the parallelization of the carry generation ( $G$ ) and propagation ( $P$ ). In this work, we introduce approximate PPAs (AxPPAs) by exploiting approximations in the POs. To evaluate our proposal for approximate POs (AxPOs), we generate the following AxPPAs, consisting of a set of four PPAs: approximate Brent–Kung (AxPPA-BK), approximate Kogge–Stone (AxPPA-KS), Ladner-Fischer (AxPPA-LF), and Sklansky (AxPPA-SK). We compare four AxPPA architectures with energy-efficient approximate adders (AxAs) [i.e., Copy, error-tolerant adder I (ETAI), lower-part OR adder (LOA), and Truncation (trunc)]. We tested them generically in stand-alone cases and embedded them in two important signal processing application kernels: a sum of squared differences (SSDs) video accelerator and a finite impulse response (FIR) filter kernel. The AxPPA-LF provides a new Pareto front in both energy-quality and area-quality results compared to state-of-the-art energy-efficient AxAs.
Predictors of Reactive Agility in Early Puberty: A Multiple Regression Gender-Stratified Study

Reactive agility (RAG) is a crucial factor of success in sports, but there are practically no studies dealing with RAG among children. The main aim of this study was to identify predictors of RAG among early pubescent boys and girls. The participants were primary school boys (n = 73) and girls (n = 59) aged 11–12. The criterion variable was the originally developed “Triangle” test of reactive agility (Triangle-RAG). Predictors included anthropometric/body composition indices (body height, seated height, body mass, and body fat percentage) and motor abilities (10 and 20 m sprint, broad jump, squat jump, countermovement jump, drop jump, and two tests of change of direction speed—CODS (Triangle-CODS, and 20 yards)). The results of the univariate analysis showed that anthropometric/body composition indices were not significantly correlated to TRAG (0–4% of the common variance), while all motor abilities were significantly associated with TRAG (7–43% of the common variance) in both genders. Among boys, 64% of the TRAG variance was explained by multiple regression, with TCODS as the only significant predictor. Among girls, multiple regression explained 59% of the TRAG-variance with TCODS, countermovement jump, and drop jump as significant predictors. Differences in multivariate results between genders can be explained by (i) greater involvement in agility-saturated sports (i.e., basketball, tennis, soccer) in boys, and (ii) advanced maturity status in girls. The lack of association between anthropometric/body built and TRAG was influenced by the short duration of the TRAG (3.54 ± 0.4 s). Our findings suggest that pre-pubescent and early pubescent children should be systematically trained on basic motor abilities to achieve fundamentals for further developing RAG. Since in this study we observed predictors including only athletic abilities and anthropometric/body composition, in future studies, other motor abilities, as well as cognitive, perceptual, and decision-making parameters as potential predictors of RAG in children should be investigated.
A Posteriori Error Estimation of hp-dG Finite Element Methods for Highly Indefinite Helmholtz Problems (extended version)

In this paper, we will consider an $hp$-finite elements discretization of a highly indefinite Helmholtz problem by some dG formulation which is based on the ultra-weak variational formulation by Cessenat and Depr\'{e}s. We will introduce an a posteriori error estimator and derive reliability and efficiency estimates which are explicit with respect to the wavenumber and the discretization parameters $h$ and $p$. In contrast to the conventional conforming finite element method for indefinite problems, the dG formulation is unconditionally stable and the adaptive discretization process may start from a very coarse initial mesh. Numerical experiments will illustrate the efficiency and robustness of the method.
Evaluation of Long-Term Radar-Derived Precipitation for Water Balance Estimates: A Case Study for Multiple Catchments in Saxony, Germany

Quality of water balance estimations are strongly dependent on the precipitation input. The key limitation here is typically a lack of spatial representation in precipitation data. Quantitative precipitation estimation (QPE) using radar is recognized as capable to significantly enhance the spatial representation of precipitation compared to conventional rain gauge-based methods by calibrating radar pixels with surrounding rain gauges. However, the measured precipitation is often underestimated due to wind drift or funnel evaporation, particularly in mountainous areas. Thus, a post-correction is required before applying radar precipitation in water balance models. Here, we applied the Richter correction for the first time to a radar-based QPE, to model the water balance in ten catchments in Saxony, Germany. The hydrological responses for the period 2001–2017 from the model were validated with discharge observations. The results show that radar data application yielded reliable simulations of water balance (KGE = 0.53 and 0.70 at daily and monthly resolutions, respectively). However, a simple compensation such as the Richter method to conventional precipitation should be used with caution. This study shows that radar-based precipitation has immense potential to advance quality of the precipitation input to distributed hydrologic models not only for flood events but also for climatological analyses.
Statistical Ranging of Asteroid Orbits

We present a new orbit determination method, termed statistical ranging, applicable to poorly observed single-apparition asteroids having two or more observations. We examine the Bayesian a posteriori probability density of the orbital elements using a Monte Carlo technique that maps an unbiased hypervolume in element phase space. We select two observations randomly from the full set, and after introducing random deviations to the observations and generating random topocentric ranges (distances), compute a sample orbit from the Cartesian positions available. Repeating the procedure allows us to obtain a large set of orbital elements compatible with the observations. To distinguish between realistic and unrealistic orbit solutions, we can incorporate the three- or four-dimensional distribution of semimajor axes, eccentricities, inclinations, and, in some cases, the absolute magnitudes of multi-apparition asteroids as a priori information in the Bayesian technique. The application of the method to both near-Earth and main-belt asteroids clearly indicates that there may exist a broad variety of orbits, all of which are compatible with the observations. The resulting distributions of the orbital elements allow recovery attempts for lost asteroids and linkage to existing observations of single-apparition asteroids. The Bayesian approach can prove useful in constraining the broad distribution of orbits for problematic newly discovered asteroids.
Homogenization of the stochastic Navier–Stokes equation with a stochastic slip boundary condition

The two-dimensional Navier–Stokes equation in a perforated domain with a dynamical slip boundary condition is considered. We assume that the dynamic is driven by a stochastic perturbation on the interior of the domain and another stochastic perturbation on the boundaries of the holes. We consider a scaling ( for the viscosity and 1 for the density) that will lead to a time-dependent limit problem. However, the noncritical scaling () is considered in front of the nonlinear term. The homogenized system in the limit is obtained as a Darcy’s law with memory with two permeabilities and an extra term that is due to the stochastic perturbation on the boundary of the holes. The nonhomogeneity on the boundary contains a stochastic part that yields in the limit an additional term in the Darcy’s law. We use the two-scale convergence method after extending the solution with 0 inside the holes to pass to the limit. By Itô stochastic calculus, we get uniform estimates on the solution in appropriate spaces. Due to the stochastic integral, the pressure that appears in the variational formulation does not have enough regularity in time. This fact made us rely only on the variational formulation for the passage to the limit on the solution. We obtain a variational formulation for the limit that is solution of a Stokes system with two pressures. This two-scale limit gives rise to three cell problems, two of them give the permeabilities while the third one gives an extra term in the Darcy’s law due to the stochastic perturbation on the boundary of the holes.
Internationality of value chain activities and the export orientation of micro- and small family businesses in Western Austria

Based on a sample of 461 micro- and small family businesses in Western Austria, this study aimed to analyze the degree of internationalization of individual activities in the value chain and their influence on the export probability of family firms. The results show that exporting and non-exporting micro- and small family businesses are internationalized in different value chain activities and can partly explain the export probability. The resource-based view (RBV) can only be used to a limited extent to explain the export activities of micro- and small family firms, and certain firm-specific and individual-decision-maker characteristics can significantly explain export probability. The findings suggest that a) micro- and small family firms take different paths of internationalization concerning their value chain and b) that the global value chain (GVC) approach should be integrated into theoretical concepts to obtain an improved explanatory model of the internationalization behavior of (family) businesses.
Image classification of lung nodules by requiring the integration of Attention Mechanism into ResNet model

In this research, in order to accurately diagnose lung nodules using the LUNA16 dataset, a deep learning model, ResNetl01, is analyzed and chosen. The paper includes: (1) demonstrating the efficiency of the ResNetl01 network on the LUNA16; (2) analyzing the benefits and drawbacks of Attention modules before selecting the best Attention module to integrate into the ResNetl01 model in the classification of lung nodules in CT scans challenge; (3) comparing the efficacy of the proposed model to prior outcomes to demonstrate the model’s feasibility.
Approximation Methods for a Nonlinear Competitive Facility Cost Optimization Problem

In this paper, we study a facility cost optimization problem in a competitive market. Our objective is to distribute an available budget to some newly opened facilities to maximize an expected captured customer demand, assuming that customers will select a facility to visit according to a random utility maximization model. In this work, given the fact that the objective function of this problem is highly non-convex and challenging to solve exactly, we propose a technique to approximate the objective function by piece-wise linear functions, making it possible to reformulate the problem as a mixed-integer linear or conic program, which can further be solved by a commercial solver such as CPLEX. We also explore an outer-approximation algorithm to solve the approximate problem. Computational results are provided to demonstrate the performances of our approaches.
Self-similar solutions of shallow water equations with porosity

Simulated free surface transients in periodic urban layouts have been reported to be self-similar in the space-time domain when averaged on the scale of the building period. Such self-similarity is incompatible with the head loss model formulae used in most porosity-based shallow water models. Verifying it experimentally is thus of salient importance. New dam-break flow laboratory experiments are reported, where two different configurations of idealized periodic buildings layouts are explored. A space-time analysis of the experimental water level fields validates the self-similar character of the flow. Simulating the experiment using the two-dimensional shallow water model also yields self-similar period-averaged flow solutions. Then, the Single Porosity (SP), Integral Porosity (IP) and Dual Integral Porosity (DIP) models are applied. Although all three models behave in a similar fashion when the storage and connectivity porosities are close to each other, the DIP model is the one that upscales best the refined 2D solution.
Phenotypic and molecular detection of biofilm formation in clinical methicillin-resistant Staphylococcus aureus isolates from Malaysia

ABSTRACT Methicillin-resistant Staphylococcus aureus (MRSA) is among the top threats to global public health and biofilm production is one of the factors attributed to its pathogenesis. This study aims to investigate the biofilm forming ability of 89 clinical MRSA isolated from various sources in Malaysia and to investigate the presence of biofilm-associated and regulatory genes among these isolates. A total of 89.9% (80/89) isolates produced slime layer via Congo red assay while 57.3% (51/89) isolates produced strong biofilm via crystal violet assay. PCR assay revealed 97.8% (87/89) isolates carried at least one of the MSCRAMM with icaBC genes detected at the highest rate (92.1%, 82/89) and highest frequency of agr-I (68.5%, 61/89). Clinical isolates isolated from pus were significantly associated with strong biofilm (p = 0.0449). The obtained results revealed the varying ability of clinical MRSA isolates to form biofilms and highlighted the genetic background associated with biofilms from different sources and clinical presentations.
Complexity of Decision-Making!: Case Studies of Cadaveric Organ Donations in Ahmedabad, India

Background The disequilibrium in the demand-supply nexus of organ donation prevails an urgent need for understanding the process and cascade of the donation. There is a lack of evidence in organ donation literature within India that focuses on factors influencing familial consent, the decision-making process, and psychosocial factors that can predict successful organ donation. Such evidence can assist in designing interventions and policy dialogue focusing on the discussion on enhancing donation decisions with relatives. Thus, the present study is an effort to document the decision-making complexity systematically among successful cadaveric organ donation cases. Methods A qualitative exploratory, including the network assessment was implemented between October 2021 and February 2022 in one of the western states of India, Gujarat. A semi-structured interview guide that was comprised of thematic, open-ended questions focused on understanding the network for the decision-making process was prepared, and trained interviewers conducted the interview at the suitable place of the donor’s relative. Results The 10 interviews among the closest relatives of the deceased were conducted and the decision-making process indicated the involvement of multiple actors. The social network analysis reveals a minimum node of 2 to 7, with the highest ties of 22. The maximal degree was 3.6, and the density of 1 of these networks. Out of 10, in most cases, the ties were more than 2, with a maximum of 22 ties, which shows that more people communicated to each other before the final decision-making. Conclusion The analysis indicates that the decision-making for deceased organ donation is a complex process as in most cases, multiple family members were involved and interaction happened before the final decision-making. The study explains the decision-making during the cadaveric organ donation process by exploring families’ experiences. Further research is recommended to generate evidence on the factors and the family dynamics, including the complexity of successful organ donation.
The Schur-Horn theorem in von Neumann algebras

A few years ago, Richard Kadison thoroughly analysed the diagonals of projection operators on Hilbert spaces and asked the following question: Let $\mathcal{A}$ be a masa in a type $II_1$ factor $\mathcal{M}$ and let $A \in \mathcal{A}$ be a positive contraction. Letting $E$ be the canonical normal conditional expectation from $\mathcal{M}$ to $\mathcal{A}$, can one find a projection $P \in \mathcal{M}$ so that [E(P) = A? ] In a later paper, Kadison and Arveson, as an extension, conjectured a Schur-Horn theorem in type $II_1$ factors. In this paper, I give a proof of this conjecture of Arveson and Kadison. I also prove versions of the Schur-Horn theorem for type $II_{\infty}$ and type $III$ factors as well as finite von Neumann algebras.