Miracle-dz/UniFAR-FTUs huggingface dataset:
Research of Website Community Identification Based on Node2vec

In recent years, the world has witnessed massive growth in the field of information technology and intelligent device, giving rise to exponentially expansion of internet websites in terms of quantity as well as complexity. Meanwhile, the public has also enlarged demand for characteristic analysis of internet websites, since they become an indispensable element of everyone's daily life. One significant focus is website community identification, which is able to optimize user experience and resource allocation to a large extent. In this paper, we present a comprehensive solution featuring node2vec algorithm to identify website community, expressly discovered website relationship from vast user behaviors which has been ignored for long. The experiment credibly demonstrates availability and reliability of our solution, which is significative in practical application.
Cycling-Based Synthesis of Robust Output Estimators for Uncertain LPTV Systems

This paper studies a method of designing robust output estimators for discrete-time linear periodically timevarying (LPTV) systems with uncertainties. The key idea is to use not the well-known lifting technique but that called cycling for dealing with LPTV systems in the estimator synthesis. Robustness for uncertainties in the estimation is evaluated with the separator-type robust stability theorem through such cycling-based treatment of systems. An advantage of our cycling-based approach, compared to the lifting-based approach, is that we can easily introduce restrictions on the coefficients of estimators in the synthesis for predetermining the estimator period regardless of the system period.
AGE AT MENARCHE AND ITS BIOSOCIAL CORRELATES IN ADOLESCENTS OF MAZANDARAN PROVINCE IN 2017

The age at which the first menstrual period occurs (menarche) is affected by many environmental and genetic factors. The purpose of this study was to determine the age at menarche and its relationship with some biosocial variables. Materials & Methods: This study was a descriptive-correlational study on 630 middle school students (grade 7-9) in Mazandaran province. Students were selected using randomized multistage cluster sampling. Stadiometer, weight scale, demographic and socioeconomic status questionnaires were used to data collection. Data analysis was performed using SPSS23 software at a significance level of 0.05. Results: The mean age at menarche in adolescent girls was 11.77 ± 1.05 years. The lowest and highest age of menarche was 8.33 and 14.33 years, respectively. The highest and lowest frequency of the start of the menarche was summer (49%) and winter (8%) respectively. The menarcheal age of the girls was correlated with mother’s age at menarche and physical activity directly and body mass index, socioeconomic status and weight inversely. Conclusion: Mean age at menarche in this study was reduced compared to the previous research in adolescent girls Mazandaran cities and the biosocial factors associated with the age of menarche were mother’s age at menarche, physical activity and body mass index as predictor variables, respectively
RAMP AMM-1 SAR Image Mosaic of Antarctica

In 1997, the Canadian RADARSAT-1 satellite was rotated in orbit, so that its synthetic aperture radar (SAR) antenna looked south towards Antarctica. This permitted the first high-resolution mapping of the entire continent of Antarctica. In eighteen days, the satellite acquired a complete coverage of radar image swaths as part of the first Antarctic Mapping Mission (AMM-1). Swath images have been assembled into an image mosaic depicting the entire continent at 25-m resolution. The mosaic provides a detailed look at ice sheet morphology, rock outcrops, research infrastructure, the coastline, and other features of Antarctica, as well as representing calibrated radar backscatter data which may provide insight into climate processes affecting the upper few meters of snow cover. Data are available from both the Alaska Satellite Facility (ASF) and the National Snow and Ice Data Center (NSIDC), and are offered in a variety of formats. A series of approximately 90 image tiles covers the entire continent at 25-m resolution, and single mosaic images derived from these tiles cover the continent at resolutions ranging from 125 m to 1 km. The single images provide good detail in convenient image formats. The tile products preserve the highest resolution of spatial detail, and retain the quantitative measure of backscatter intensity, but are necessarily large files that require assembly by the user.
Diabetes-related social stigma among university students in Saudi Arabia: A cross-sectional study

Diabetes-related stigma encompasses stereotypes, discrimination, and blame, significantly influencing diabetes management and overall well-being. Despite high diabetes-related stigma prevalence in various contexts, there is limited research in Saudi Arabia, especially that perceived/enacted by non-diabetics, the so-called social stigma. This cross-sectional study aimed to assess diabetes-related social stigma (DRSS) and to identify correlates among university students in Jazan, Saudi Arabia. A convenience sampling was employed to collect responses from 536 Jazan University students using an online questionnaire. After excluding participants with diabetes mellitus (n = 17), data from 519 individuals were analyzed. The DRSS questionnaire comprised 2 scales: social distancing and negative attitudes and stereotyping. The study found mixed results regarding the student population’s attitude toward diabetic patients. Most students displayed favorable answers on social distancing scale statements, with the majority of statements showing willingness to engage in different social aspects with diabetics getting a positive response from at least 96% of respondents. The study identified various types of negative attitudes and stereotyping, for example, 46% of the sample agreed that dealing with a diabetic is upsetting or tiring. Correlates of social distancing included academic year, rural residence, and nonmedical field of specialty, while predictors of negative attitude and stereotyping included female gender and higher family income. The findings indicate a need to improve attitudes related to diabetics among university students in Saudi Arabia, with a particular focus on negative attitude stereotyping. Raising awareness about DRSS, especially among future healthcare professionals, is essential. Further refinement of the DRSS measurement scales is recommended through broader testing among the general population to enhance our understanding of this important issue.
Registration and clustering of functional observations

As an important exploratory analysis, curves of similar shape are often classified into groups, which we call clustering of functional data. Phase variations or time distortions are often encountered in the biological processes, such as growth patterns or gene profiles. As a result of time distortion, curves of similar shape may not be aligned. Regular clustering methods for functional data usually ignore the presence of phase variations, which may result in low clustering accuracy. However, it is difficult to account for phase variation without knowing the cluster structure. In this dissertation, we first propose a Bayesian method that simultaneously clusters and registers functional data. We model a warping function with a discrete approximation generated from the family of Dirichlet distributions, which allows great flexibility and computational simplicity. Then, we modify our Bayesian algorithm to obtain a fast registration method, which does not require any template curve. We propose a distance-based clustering method that uses a “derivative sign” to measure the dissimilarity between two curves after potential phase variations are removed. Finally, we derive a modified variational approximation for our Bayesian method for simultaneous registration and clustering, which produces a faster alternative for the full Markov chain Monte Carlo (MCMC) sampling. We demonstrate our proposed methods on simulated data as well as the famous Berkeley growth data, a set of yeast gene profile data, and a set of response of human fibroblasts to serum data.
Use of nonlinear chaos inversion in predicting deep thin lithologic hydrocarbon reservoirs: A case study from the Tazhong oil field of the Tarim Basin, China

ABSTRACTWith the gradual disappearance of traditional structural reservoirs, widely distributed deep thin lithologic reservoirs developed in continental and transitional sedimentary environments may offer significant petroleum reserves. Reservoir characterization through conventional impedance inversion methods without appropriate selection of regularization parameters and other empirical constraints cannot easily detect and assess these reserves, however, due to their size, variation, and features that conceal them. We have evaluated a nonlinear chaos inversion method that uses well data and seismic facies to characterize the oil and gas reservoirs of the Tazhong oil field in the Tarim Basin, China. The inverted results exhibited high agreement with the well data in highlighting the interfaces and lithologic bodies. This integrated method also provided enhanced resolution of depositional contacts and variable lithologic bodies. Specifically, the approach was able to describe a highly variable, approximat.
Bi-parental mapping and genome-wide association studies for grain quality traits in winter wheat under contrasting soil moisture conditions

ii ACKNOWLEDGEMENTS . v DEDICATION . vi TABLE OF CONTENTS . vii LIST OF TABLES . xii LIST OF FIGURES . xvi CHAPTER 1: LITERATURE REVIEW . 1 1.1. Wheat . 1 1.2. Drought stress and wheat . 3 1.3. Molecular markers . 4 1.4. Construction of linkage maps . 7 1.4. 1. Linkage maps . 7 1.4. 2. Mapping populations . 8 1.4. 3. Identification of marker polymorphism . 9 1.4. 4. Genotyping of polymorphic markers . 9 1.4. 5. Linkage analysis of markers . 10 1.5. QTL analysis . 11 1.6. Investigated traits and their genetic control . 13
What are the determinants of older people adopting communicative e-health services: a meta-ethnography

Background Gradually, society has shifted more services online, with COVID-19 highlighting digital inequalities in access to services such as healthcare. Older adults can experience such digital inequalities, yet this group is also more likely to need medical appointments, compared to younger people. With the growing digitalisation of healthcare, it is increasingly important to understand how older people can best use communicative e-health services to interact with healthcare services. This is especially if older adults are to access, and actively interact with health professionals/clinicians due to their general health decline. This review aims to synthesise older adults’ experiences and perceptions of communicative e-health services and, in turn, identify barriers and facilitators to using communicative e-health services. Methods A meta-ethnography was conducted to qualitatively synthesise literature on older adults’ experiences of using communicative e-health services. A systematic search, with terms relating to ‘older adults’, ‘e-health’, ‘technology’, and ‘communication’, was conducted on six international databases between January 2014 and May 2022. The search yielded a total of 10 empirical studies for synthesis. Results The synthesis resulted in 10 themes that may impact older adults’ perceptions and/or experiences of using communicative e-health services. These were: 1) health barriers, 2) support networks, 3) application interface/design, 4) digital literacy, 5) lack of awareness, 6) online security, 7) access to digital devices and the internet, 8) relationship with healthcare provider(s), 9) in-person preference and 10) convenience. These themes interlink with each other. Conclusion The findings suggest older adults’ experiences and perceptions of communicative e-health services are generally negative, with many reporting various barriers to engaging with online services. However, many of these negative experiences are related to limited support networks and low digital literacy, along with complicated application interfaces. This supports previous literature identifying barriers and facilitators in which older adults experience general technology adoption and suggests a greater emphasis is needed on providing support networks to increase the adoption and usage of communicative e-health services. Supplementary Information The online version contains supplementary material available at 10.1186/s12913-023-10372-3.
A Novel Remote Authentication Scheme with Smart Cards Based On Chaotic Maps

This article proposes a novel remote authentication scheme with smart card based on chaotic maps, where BAN-Logic is used to verify the security of the structure. Just like an RSA system, the chaotic map-based code system suffers from chosen-message forgery attacks. However, such attacks will not influence the security of the proposed scheme. The proposed scheme, which has higher security than the existed methods has the following advantages: 1) the user can select password at will; 2) any legal owner can use the smart card to perform online registration at the password center; 3) there is a one-to-one relationship between each user and his smart card so creating an identification code for each user is unnecessary; 4) the authentication server (AS) can confirm the remote login request from a user without any difficulties even without the verification table or any private information; 5) no forger can successfully cheat the scheme by resending stolen registration information; 6) no illegal owner can successfully log in to the scheme using the smart card.
A Novel Approach for Analyzing the Public Sentiment Variations on Twitter Using Multi-Core Programming

Now a days, social contacts are vital to find relevant content. We need to connect with people with similar interests because they provide content that matters. Every day is more clear that in the future of document recommendations will be necessary to cross the traditional data with the data obtained from twitter. For instance, in order to provide the best content available we can use sentiment analysis techniques to prioritize content with good reviews. The aim of this project is to offer a better sentiment recognition strategy. analyzing short messages about brands in Twitter trying to classify them between positive and negative using Sentiwordnet. Based on this observation, we propose a Latent Dirichlet Allocation (LDA) based model, Foreground and Background LDA (FB-LDA), to distill foreground topics and filter out longstanding background topics. We examine sentiment analysis on Twitter data. The contributions of this paper is : (1) we use Parts Of Speech (POS)-specific prior polarity features and used the multi- core programming to perform parallel processing in multi-core way to get the output in minimum time.
Minimization of the E. coli ribosome, aided and optimized by community science

The ribosome is a ribonucleoprotein complex found in all domains of life. Its role is to catalyze protein synthesis, the messenger RNA (mRNA)-templated formation of amide bonds between α-amino acid monomers. Amide bond formation occurs within a highly conserved region of the large ribosomal subunit known as the peptidyl transferase center (PTC). Here we describe the stepwise design and characterization of mini-PTC 1.1, a 284-nucleotide RNA that recapitulates many essential features of the Escherichia coli PTC. Mini-PTC 1.1 folds into a PTC-like structure under physiological conditions, even in the absence of r-proteins, and engages small molecule analogs of A- and P-site tRNAs. The sequence of mini-PTC 1.1 differs from the wild type E. coli ribosome at 12 nucleotides that were installed by a cohort of citizen scientists using the on-line video game Eterna. These base changes improve both the secondary structure and tertiary folding of mini-PTC 1.1 as well as its ability to bind small molecule substrate analogs. Here, the combined input from Eterna citizen-scientists and RNA structural analysis provides a robust workflow for the design of a minimal PTC that recapitulates many features of an intact ribosome.
A Geometry Recognition-Based Strategy for Locomotion Transitions Early Prediction of Prosthetic Devices

Prediction of locomotion modes is an integral part of control system that determines the kinematics and dynamics of powered prosthetic and orthotic devices for lower limb amputees. The traditional prediction strategies exhibit a transitional delay while detecting the transition of locomotion modes, which is undesirable. In this paper, we propose a novel prediction strategy that recognizes the geometry of the terrains (i.e., plane, wall, stairs, sloping surface, and obstacle) lying ahead of the user in order to identify the locomotion mode transitions in advance. Using this methodology, the transitional delay is eliminated. To achieve this goal, a wearable prototype, which is equipped with an array of range sensors, a force sensitive resistor (FSR), and a microcontroller, is developed. A classification algorithm along with a postprocessing technique is utilized to achieve a prediction accuracy almost equal to 99%. The proposed strategy has been successfully tested in real time on normal human subjects. Moreover, the performance of the proposed methodology is found to be robust to the transition of locomotion modes, change in dimensions of the terrains and different subjects. In addition, it also gives some rough idea about the dimensions of the terrains.
Les Odonata fossiles: état actuel des connaissances. VIII: Les Calopterygoidea fossiles (Odonata, Zygoptera)

L'inventaire critique des Calopterygoidea fossiles est realise. Il en ressort que nombres de taxa attribues aux Calopterygoidea ont des positions incertaines. Leurs types devront etre redecrits. Les Calopterygoidea sont peu representes a l'etat fossile, en particulier durant le Mesozoique. Les taxa du Jurassique superieur ont des positions systematiques peu precises. Ceux du Cenozoiques sont mieux connus et plus varies, avec la presence de groupes de rangs superieurs eteints dans l'Oligo-miocene. Les Calopterygoidea fossiles tertiaires sont de precieux indicateurs de paleoclimats chauds et des temoins privilegies de la paleobiogeographie de ce groupe
Chimp

Radio links in wireless body area networks (WBANs) commonly experience highly time-varying attenuation due to the dynamic network topology and frequent occlusions caused by body movements, making it challenging to design a reliable, energy-efficient, and real-time communication protocol for WBANs. In this article, we present Chimp, a learning-based power-aware communication protocol in which each sending node can self-learn the channel quality and choose the best transmission power level to reduce energy consumption and interference range while still guaranteeing high communication reliability. Chimp is designed based on learning automata that uses only the acknowledgment packets and motion data from a local gyroscope sensor to infer the real-time channel status. We design a new cost function that takes into account the energy consumption, communication reliability and interference and develop a new learning function that can guarantee to select the optimal transmission power level to minimize the cost function for any given channel quality. For highly dynamic postures such as walking and running, we exploit the correlation between channel quality and motion data generated by a gyroscope sensor to fastly estimate channel quality, eliminating the need to use expensive channel sampling procedures. We evaluate the performance of Chimp through experiments using TelosB motes equipped with the MPU-9250 motion sensor chip and compare it with the state-of-the-art protocols in different body postures. Experimental results demonstrate that Chimp outperforms existing schemes and works efficiently in most common body postures. In high-date-rate scenarios, it achieves almost the same performance as the optimal power assignment scheme in which the optimal power level for each transmission is calculated based on the collected channel measurements in an off-line manner.
Advertising, the Matchmaker

We empirically study the informational role of advertising in matching consumers with products when consumers are uncertain about both observable and unobserved program attributes. Our focus is on the network television industry, in which the products are television shows. We estimate a model that allows us to distinguish between the direct effect of advertising on utility and its effect through the information set. A notable behavioral implication is that exposure to informational advertising can decrease the consumer’s tendency to purchase the promoted product. The structural estimates imply that an exposure to a single advertisement decreases the consumer’s probability of not choosing her best alternative by approximately 10%. Our results are relevant for industries characterized by product proliferation and horizontal differentiation.
Staphylococcus aureus mutants resistant to the feed-additive monensin show increased virulence and altered purine metabolism

ABSTRACT Ionophores are antibacterial compounds that affect bacterial growth by changing intracellular concentrations of the essential cations, sodium and potassium. They are extensively used in animal husbandry to increase productivity and reduce infectious diseases, but our understanding of the potential for and effects of resistance development to ionophores is poorly known. Thus, given their widespread global usage, it is important to determine the potential negative consequences of ionophore use on human and animal health. In this study, we demonstrate that exposure to the ionophore monensin can select for resistant mutants in the human and animal pathogen Staphylococcus aureus, with a majority of the resistant mutants showing increased growth rates in vitro and/or in mice. Whole-genome sequencing and proteomic analysis of the resistant mutants show that the resistance phenotype is associated with de-repression of de novo purine synthesis, which could be achieved through mutations in different transcriptional regulators including mutations in the gene purR, the repressor of the purine de novo synthesis pathway. This study shows that mutants with reduced susceptibility to the ionophore monensin can be readily selected and highlights an unexplored link between ionophore resistance, purine metabolism, and fitness in pathogenic bacteria. IMPORTANCE This study demonstrates a novel link between ionophore resistance, purine metabolism, and virulence/fitness in the key human and animal pathogen Staphylococcus aureus. The results show that mutants with reduced susceptibility to the commonly used ionophore monensin can be readily selected and that the reduced susceptibility observed is associated with an increased expression of the de novo purine synthesis pathway. This study increases our understanding of the impact of the use of animal feed additives on both human and veterinary medicine. This study demonstrates a novel link between ionophore resistance, purine metabolism, and virulence/fitness in the key human and animal pathogen Staphylococcus aureus. The results show that mutants with reduced susceptibility to the commonly used ionophore monensin can be readily selected and that the reduced susceptibility observed is associated with an increased expression of the de novo purine synthesis pathway. This study increases our understanding of the impact of the use of animal feed additives on both human and veterinary medicine.