Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence of obesity and associated sociodemographic factors among adolescents in Udham Singh Nagar, Uttarakhand, India

Obesity is global health concern due to its steadily rising prevalence and major risk factors for several obesity related comorbidities. This study aimed to determine the prevalence and sociodemographic factors of obesity among adolescents. A school-based cross-sectional study was conducted on 1101 school-going adolescents of 12 – 17 years studying in class 6 to 9. Anthropometric measurements were taken. The overall prevalence of overweight and obesity was estimated to be 10.4% and 4.1%, considering IAP reference standards as cut – offs. Altogether, overweight and obesity involve 14.4% of the sample. Obesity was higher in early adolescents, private school, joint family, lower socio- economic status, higher parental educational level, in high income families and in first birth order adolescents. Overweight/obesity prevalence should be taken into consideration as adolescent obesity is marker of adulthood obesity and is associated with increased rate obesity related comorbidities in adult population. A preventive programmed action considering these factors must be planned for reducing obesity among adolescents in the society.
Leaky-Wave Antenna Array With Bilateral Beamforming Radiation Pattern and Capability of Flexible Beam Switching

A novel leaky-wave antenna (LWA) array capable of bilateral beamforming is investigated for applications in indoor and short-distance mobile communications. The antenna array is designed on a double-layer substrate-integrated waveguide (SIW) with a multiport feeding network. The upper layer is a four-port SIW with a tapered open stopband suppression structure and two tapered radiating slot arrays. By adjusting the periods and widths of slots, the two slot arrays radiate in different directions, and their radiation fields satisfy the cosecant-squared distribution. The lower layer is a single-port SIW power divider with an allocation ratio of 1:5 using a Z-shaped junction. There are transitions at both ends of the lower SIW for coupling energy up into the radiation layer. When feeding the upper layer from its two input ports individually, two dual broad beams with beam directions of ±25° and ±45° can be generated, thus achieving amplitude-shaped dual-beam switching for smart beam switching antenna systems applied in short-distance mobile communication. When feeding the whole double-layer array through the input port of the power divider, the above two dual beams will be superposed together and form a cosecant-squared radiation pattern, which is suitable for uniform radio wave coverage along with straight areas. The proposed array was fabricated and measured to validate its performance, and the results showed the efficiency of the design.
Gene regulatory network analysis identifies key genes and regulatory mechanisms involved in acute myocardial infarction using bulk and single cell RNA-seq data

Cardiovascular and cerebrovascular diseases are leading causes of death worldwide, accounting for more than 40% of all deaths in China. Acute myocardial infarction (AMI) is a common cardiovascular disease and traditionally divided into ST-segment (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI), which are known with different prognoses and treatment strategies. However, key regulatory genes and pathways involved in AMI that may be used as potential biomarker for prognosis are unknown. In this study, we constructed weighted gene co-expression networks for differential expressed genes between STEMI and NSTEMI patients based on whole-blood RNA-seq transcriptomics. Network topological attributes (e.g., node degree, betweenness) were analyzed to identify key genes involved in different functional network modules. Furthermore, we used single-cell RNA-seq data to construct multilayer signaling network to infer regulatory mechanisms of the above key genes. PLAUR (receptor for urokinase plasminogen activator) was found to play a vital role in transducing inter-cellular signals from endothelial cells and fibroblast cells to intra-cellular pathways of myocardial cells, leading to gene expression involved in cellular response to hypoxia. Our study sheds lights on identifying molecular biomarkers for diagnosis and prognosis of AMI, and provides candidate key regulatory genes for further experimental validation.
MONITORING OF EGRESS OF “ESCOLA DO TRABALHADOR” IN THE BRAZILIAN FORMAL LABOR MARKET

The objective of this work is to follow the egress from “Escola do Trabalhador”, analyzing its dynamics in the job market. The understanding of this dynamic can be very useful for future actions within and beyond the School, including proposing new actions, and more comprehensively in the professional qualification policy. Using the official databases of formal employment, RAIS and CAGED, the performance of workers trained in the “Escola do Trabalhador” was compared to others. The results indicate that the egress from the School has achieved better results of employability in relation to others.
Conditional Mutual Information Neural Estimator

Several recent works in communication systems have proposed to leverage the power of neural networks in the design of encoders and decoders. In this approach, these blocks can be tailored to maximize the transmission rate based on aggregated samples from the channel. Motivated by the fact that, in many communication schemes, the achievable transmission rate is determined by a conditional mutual information term, this paper focuses on neural-based estimators for this information-theoretic quantity. Our results are based on variational bounds for the KL-divergence and, in contrast to some previous works, we provide a mathematically rigorous lower bound. However, additional challenges with respect to the un-conditional mutual information emerge due to the presence of a conditional density function which we address here.
The Plectic Weight Filtration on Cohomology of Shimura Varieties and Partial Frobenius

Abstract We prove that there is a natural plectic weight filtration on the cohomology of Hilbert modular varieties in the spirit of Nekovář and Scholl. This is achieved with the help of Morel’s work on weight t-structures and a detailed study of partial Frobenius. We prove in particular that the partial Frobenius extends to toroidal and minimal compactifications.
MBCAL: A Simple and Efficient Reinforcement Learning Method for Recommendation Systems

It has been widely regarded that only considering the immediate user feedback is not sufficient for modern industrial recommendation systems. Many previous works attempt to maximize the long term rewards with Reinforcement Learning(RL). However, model-free RL suffers from problems including significant variance in gradient, long convergence period, and requirement of sophisticated online infrastructures. While model-based RL provides a sample-efficient choice, the cost of planning in an online system is unacceptable. To achieve high sample efficiency in practical situations, we propose a novel model-based reinforcement learning method, namely the model-based counterfactual advantage learning(MBCAL). In the proposed method, a masking item is introduced in the environment model learning. With the masking item and the environment model, we introduce the counterfactual future advantage, which eliminates most of the noises in long term rewards. The proposed method selects through approximating the immediate reward and future advantage separately. It is easy to implement, yet it requires reasonable cost in both training and inference processes. In the experiments, we compare our methods with several baselines, including supervised learning, model-free RL, and other model-based RL methods in carefully designed experiments. Results show that our method transcends all the baselines in both sample efficiency and asymptotic performance.
Variational Constraints on Masses and Radii of $B_c$ Mesons along with Properties of $B_c$ Mesons

Within the non-relativistic quark model framework, the spectrum, radii, radial wave function at origin and decay constants for $B_c$ mesons are derived through finding the numerical solution of the Schrodinger equation by shooting method. Momentum width is determined for $B_c$ meson states with angular momentum quantum numbers and radii. Masses of $B_c$ meson states are calculated through constraints on mass and $r_{rms}$ derived with uncertainty and variational principles. Results are compared with the experimentally observed and theoretically available results. These results have implications for scalar form factors and leptonic decays of $B_c$ mesons.
TiO2 Surface Hybridisation with Noble Metals (Ag and CuxO) for Solar De-NOx and VOC Removal

Indoor and outdoor air pollution remains a major health risk for human beings. Nitrogen oxides and volatile organic compounds are amongst the major pollutant found outdoor. Thus, actions to diminish such risks and to provide safer outdoor / indoor environment are required. In this research work, we have decorated the surface of TiO2 with noble-metal oxides (Ag and/or CuxO) to improve the photocatalytic performances (removal of nitrogen oxides and benzene) under simulated solar-light irradiation. By means of advanced X-ray methods it has been shown that noble metals did not enter the TiO2 crystal structure, although they retarded the anatase-to-rutile phase transition and crystal growth. Photocatalytic activity was assessed in the gas-solid phase, monitoring the degradation of NOx and benzene, using a lamp simulating the solar radiation. Results showed that TiO2 modified with an Ag:Cu molar ratio equal to 1:1 (with Ag+Cu = 0.5+0.5 mol% = 1 mol%), was that exhibiting best de-NOx and benzene removal performances.
Forced Degradation Studies of Alverine Citrate in Bulk and Formulation by UV, IR Spectrophotometry, TLC, and RP-HPLC Method.

The present study a degradation product is defined as a chemical change in the drug molecule brought about over time and/or by action of, e.g., light, temperature, pH, or water or by reaction with an excipient and/or the immediate container/closure system. Stress testing is conducted to provide data on forced decomposition products and decomposition mechanisms. The severe conditions that may be encountered during distribution can be covered by stress testing. Aim of the study is to conduct “FORCED DEGRADATION STUDIES OF ALVERINE CITRATE IN BULK AND FORMULATION BY UV, IR SPECTROPHOTOMETRY, TLC, AND RP-HPLC METHOD”. The study comprises of the following: To perform the Alkali hydrolysis, Oxidative degradation, and Thermal and Photolytic degradation. Quantification of degraded samples by UV and HPLC. Comparing the results of bulk and sample with standard. Identification of degraded samples by TLC. Identification of changes in functional group present in the degraded samples by IR. The study comprises of Alkali hydrolysis, Oxidative degradation, and Thermal and Photolytic degradation were performed. Degraded samples were quantified by UV spectroscopy and HPLC. The results of bulk and sample compared with standard. Degraded samples were identified by TLC. Functional group changes in degraded samples were identified by IR. Every procedure was repeated three times. Various stress conditions were tried to study the stability of Alverine citrate. The stress conditions used are Alkali, Acid hydrolysis, Oxidative degradation, Thermal and Photolytic degradation. The results of the studies are In intraday hydrolytic degradation, bulk underwent more degradation compared to sample from 30mins to 90mins study. In interday acid degradation, the assay values of bulk and sample were found to be 15.1% and 56.0% respectively, at the end of 5th day degradation. Complete degradation was observed in interday oxidative degradation. It shows that Alverine citrate is vulnerable to oxidative condition. Moderate amount of degradation was observed in both Photolytic and Thermal degradation. IR spectrum shows that no functional group changes were observed in both Photolytic and Thermal degradation. HPLC chromatogram shows that formation of impurities in intraday oxidative degradation. Interday oxidative degradation chromatogram shows complete degradation and more amounts of degradation products. No impurity peak was observed in both Photolytic and Thermal degradation chromatogram. No secondary spots were observed in TLC but difference in Rf value was observed. All the observations show Alverine citrate is vulnerable to Alkali hydrolysis, Oxidation, Thermal and Photolytic degradation.
A mechanically robust transparent coating for anti-icing and self-cleaning applications

Mechanically robust, transparent coatings that display very low affinity with ice and various liquids are promising for applications in outdoor facilities and marine and aerospace structures. However, such coatings are extremely challenging to prepare because some material properties required for diverse functionalities are contradictory. In this study, we demonstrated a sol-gel-derived transparent coating with superior performance compared to the well-studied superhydrophobic coatings in terms of transmittance (∼97.8%), ice-adhesion strength, anti-frost accumulation, and self-cleaning properties. We comprehensively investigated the mechanical properties of the transparent solid coating by nano-indentation, pencil scratch, cross-cut adhesion, and dolly pull-off tests according to the respective ASTM/ISO standards. The coating displayed higher hardness and better scratch resistance than the state-of-the-art slippery liquid-infused porous surfaces and polymer coatings. Furthermore, the coating showed good durability after sand erosion.
Growth Performance of Lettuce Using Fermented Products as Organic Fertilizers

This study evaluates the growth performance of lettuce (Lactuca sativa L.) utilizing various fermented products as organic fertilizers. Growth performance is determined through the plant’s weight and leaves and significant differences in growth among various treatments: (a) fish trash, (b) scrap seaweeds, (c) kangkong, and control groups urea (positive) and water (negative) was also determined. Kangkong leaves are fermented for 10 days, fish trash for 14 days and 1 month for seaweeds. Lettuce seeds are sown before transplanting (15 days after germination) into pots and placed in raised beds. Randomized complete block design is utilized in the experiment. Growth performance is measured through the number of leaves 10, 20, and 30 days after transplant and mass of plant upon harvest. After 30 days, the lettuce was harvested. Based on the findings, the soil and fermented products are acidic and the needed organic matter for optimum growth of lettuce are not sufficient as well as some nutrients of the fermented products. Among the organic fertilizers, kangkong at 30 ml performs best in terms of the growth performance of lettuce. Urea performs best in terms of the mass upon harvest. Significant differences exist in the mean number of leaves of lettuce treated with various amounts of organic fertilizers with the plants that receive urea. Lettuce produce more number of leaves and with the highest mass upon harvest when treated with urea compared with organic fertilizers applied after 30 days from transplant. Keywords: fermented kangkong; fish trash; growth performance; lettuce; scrap seaweeds
Possibility of application nuclear magnetic resonance to measure fluid flow

The paper considers the application of nuclear magnetic resonance to measure fluid flow. The paper is of an experimental nature. Flowmeter based on nuclear magnetic resonance is extremely precise. The combined measurement uncertainty can be 0.1 %. Such a value of measurement uncertainty indicates that it is a matter of a deterministic and not of a stochastic quantity. This high degree of reliability of the method is theoretically and mathematically described. The paper presents a measurement scheme for flow measurement. Water flow measurement was performed on the principle of nuclear magnetic resonance and on the basis of tritiated water (which is considered to be the most accurate classical method). The obtained results show that the measurement of flow based on nuclear magnetic resonance is more accurate (especially at higher flow). This is explained by the higher inertial mass of HTO tritiated water molecules than the standard H2O water mass and the possible transition of tritiated water to H3HeO. In this way, it has been proven that tracing water based on nuclear magnetic resonance is the only real tracing of water by water. The obtained results shows that tracing water with tritiated or heavy water is not tracing water by water which is explained by different inertial masses.
The relationship between corporate governance characteristics and agency costs

The present study aims to evaluate the contributing factors to agency costs in Iran. In this regard, 112 companies were studied over 2010 - 2016. Since the model is dynamic and the dependent variable suffers from a lag, the generalized method of moments is employed to free the independent variables and the disruptive component. The findings indicate a significant lag in the dependent variable of all three models. An audit committee’s presence significantly affects the decline of agency costs in all three models. Moreover, results suggest that family companies and the state shareholders of all three models have no significant impact on the agency costs. The existence of financial leverage matching with all three models causes the decline of agency costs. In terms of assets, Larger companies based on the three models have more agency costs as well.
A Randomized Clinical Study on Acupuncture Therapy for Relieving Sciatica Caused by Lumbar Disc Herniation

Acupuncture has been proved to be effective in many diseases, but the effect of acupuncture on sciatica caused by lumbar disc herniation is not clear. Our aim was to explore the efficacy and safety of acupuncture on sciatica caused by lumbar disc herniation. A total of 73 lumbar disc herniation patients with sciatica in our hospital were selected and randomly divided into the study group (acupuncture, n=37) and control group (sham acupuncture, n=36). The results showed that there were no significant differences in leg pain visual analogue scale, low back pain visual analogue scale or Oswestry Disability Index score at baseline between the study group and the control group. Compared with baseline, patients in both groups improved significantly in leg pain visual analogue scale, low back pain visual analogue scale and Oswestry Disability Index score. During treatment, improvements in leg pain visual analogue scale, low back pain visual analogue scale and Oswestry Disability Index score were all faster for patients in the study group. However, this short term benefit of acupuncture therapy was no longer significant by 16th w. In addition, acupuncture therapy achieved a faster rate of perceived recovery. In terms of safety, acupuncture has been proved to be safe without obvious side effects. In acupuncture can effectively relieve sciatica caused by lumbar disc herniation in the early stage and can be used as an important auxiliary means of early treatment.
Robotic Manipulation Skill Acquisition Via Demonstration Policy Learning

Current robots can perform repetitive tasks well, but are constrained to environment and task variations. Teaching a robot by demonstration is a powerful approach to solve the problem. The learning methods using large sensory and joint state information are extremely difficult to efficiently learn the demonstration policy. This article proposes a learning-by-imitation approach that learns demonstration policy for robotic manipulation skill acquisition from what-where-how interaction data. The method can improve the robotic adaptability to the environment and tasks with fewer training inputs. RGB-D image interaction demonstration is used. At each time step, we interact with an object and select a high-level action. The demonstration is formed through multistep interactions. An imitation learning architecture (OPLN) consisting of the objects list network (OLN) and policy learning network (PLN) is proposed. OLN and PLN are constructed, respectively, with long short-term memory (LSTM) neural networks. OLN learns objects sequence feature extracted from demonstration data while PLN learns policy. An action and a target object are obtained as outputs to control robot’s manipulation. The experiments show that the Block Stacking skill and Pick and Place skill can be successfully acquired, and the method can adapt to environment variations and generalize to similar tasks.
Asymptotic formulas for generalized gcd-sum and lcm-sum functions over $ r $-regular integers $ (\bmod\ n^{r}) $

In this paper we perform a further investigation for $ r $-gcd-sum function over $ r $-regular integers $ (\bmod\ n^{r}) $, and we derive two kinds of asymptotic formulas by making use of Dirichlet product, Euler product and some techniques. Moreover, we also establish estimates for the generalized $ r $-lcm-sum function over $ r $-regular integers $ (\bmod\ n) $.
Seismic Data Interpolation Based on Simultaneously Sparse and Low-Rank Matrix Recovery

Seismic data interpolation is a highly ill-posed problem. Therefore, designing an appropriate regulating method, aiming to reduce multi-solutions, is of utmost importance. Sparse and low-rank priors or constraints, which consider certain kinds of redundant data structures from different viewpoints, are widely used to constrain recovered seismic data to achieve a better fit. Considering that additional information enables us to obtain more accurate reconstructions, we formulated a seismic data interpolation model with irregular missing traces as a joint sparse and low-rank matrix approximation problem. The result is a solution that fits the given data, while simultaneously being sparse and low-rank. Subsequently, an efficient alternating algorithm is developed to solve the proposed objective function. Our proposed model called joint sparse and low-rank priors (JSLRP) model performs better on synthetic and field 3-D seismic data when compared to the classic low-rank methods, such as multichannel singular spectrum analysis (MSSA) and damped MSSA.
An Anonymous Reputation Management System for Mobile Crowdsensing Based on Dual Blockchain

In mobile crowdsensing (MCS), sensing data uploaded by dishonest workers may be false or even malicious. Thus, a reputation management system is often set up by using workers’ historical behaviors to indicate the quality of sensing data. As existing management schemes usually protect the reputation update process, reputation scores are generally stored in plaintext, which may destroy the fair bidding property of an MCS system. To address this issue, we propose an anonymous reputation management system based on the dual blockchain architecture, where reputation scores are masked. More precisely, one chain is used to store and update reputation scores, and another chain is responsible for publishing tasks and storing task-related data. To anonymously update and verify the reputation scores without affecting their usages in data sensing process, a kind of ring signature and Pedersen commitment is employed in smart contracts. In addition, a Schnorr signature is generated to make the reputation scores verifiable in the MCS system. We implement a prototype system on Hyperledger Fabric, and simulation results are provided for comparisons with two existing schemes.