Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-reported training variables are poor predictors of laboratory measures in cyclists

Purpose: Cycling is an activity that depends on a range of physiological attributes, as well as genetic, dietary, lifestyle and training factors. The aim of this study was to determine what self-reported training-related factors (e.g. intensity, frequency, supervision, etc) might predict laboratory-measured physiological and performance characteristics of a heterogeneous group of male and female self-classified cyclists. Methods: Forty-eight male and fourteen female cyclists completed all aspects of the study including a training questionnaire, incremental cycling test to determine maximal oxygen uptake (VO2max), 30-s Wingate test and a 4-km cycling time-trial. Principle component analysis and LASSO regression modelling were used to analyse laboratory-measures and training variables and the predictive capacity of the latter. Results: Total distance covered across all intensities was the only training variable included in most bootstrap models (63.8%), although the actual contribution was very low with a median f2 effect size equal to 0.01. Self-reported classification of cycling level was weakly correlated to guideline classification of relative VO2max in men (r=0.396, p=0.004), but not women (r=0.024, p=0.925). Conclusions: Self-reported training variables were poor predictors of laboratory-based physiological and performance variables in this heterogeneous group of cyclists. Total distance covered was the only training variable included in most regression models, but the predictive capability of outcomes was low. This suggests that most of these self-report variables are not useful pre-screening tools for categorising non-elite cyclists or raises the potential that non-elite cyclists cannot accurately quantify their own training intensities. Researchers and coaches should be wary that self-reported classification may not directly reflect the level of the cyclist.
A Comparative Economic Study of Tomato Production by Hydroponics and Conventional Agriculture (With Soil) in Greenhouses: A Case Study in the Nubaria Region

One of the most important challenges and obstacles faced by tomato farmers in the new lands is the scarcity of productive resources and their high cost, especially the suppliers of fresh water and arable land, which negatively affects the net yield. Therefore, this research paper aims to make a comparison between tomato production using traditional greenhouses (with soil) and using Hydroponics technology in the new lands with the research sample, aiming to measure the effect of using hydroponics in agricultural greenhouses on the most important indicators of economic returns, by studying and analyzing the cost components of the two production types and studying the most important productive, economic and financial indicators. Original Research Article Abdelmawgoud et al.; AJAEES, 39(2): 126-140, 2021; Article no.AJAEES. 66689 127
FROM EUROPE TO JIHAD-MOTIVATIONS BEHIND JOINING EXTREMIST ORGANISATIONS & THE THREE LEVELS OF IDENTITY

3 INTRODUCTION . 4 Purpose of study . 5 Methods of research . 6 Terminology . 7 1. THE THREE LEVELS OF IDENTITY . 10 2. THE ROAD TO EXTREMISM . 16 2.1. The Islamic State of Iraq and Syria (ISIS) . 16 2.1. 1 The background of ISIS . 16 2.1. 2 Goals and expansion . 18 2.1. 3 Recruitment of followers . 19 2.2. The image of the extremist . 21 2.2.1. Immigrant recruits . 22 2.2.2. Western converts . 27 2.3. Propaganda machinery . 32 2.3.1. Recruitment tactics . 34 2.3.2 Recruitment audiences and locations . 38 3. A SPECIAL LOOK AT CERTAIN COUNTRIES . 42 3.1. The Nordic Countries . 42 3.1. 1. Finland . 42 3.1. 2. Sweden . 45 3.2. Western Europe . 47 3.2.1. The United Kingdom . 47 3.2.2. Belgium . 51 4. WOMEN IN JIHAD THEIR SPECIAL ROLE . 55 5. WHAT COMES AFTER POSSIBLE THREAT AND THE RESPONSE TO RETURNING FIGHTERS . 59 CONCLUSION . 63 Other factors leading to extremist group prevalence . 67 Viewpoints to possible solutions . 68 Looking ahead and possible areas of further study . 69 REFERENCES . 70
Detecting opportunities to moderate the Social Media debate with Adiabatic Quantum Computing: a COVID-19 case

: Social media has become the most inﬂuential battleground for political and societal 1 debate. The reach, the speed, and the fact that everybody can participate make this medium 2 very popular but also highly manipulative, subject to biases and extremely precious to control. 3 Misinformation spreads in an unforeseeable way. Sometimes it just follows usual non-malicious 4 social interaction patterns, but often a targeted and designed-for-purpose manner. In this paper, 5 we propose a novel method to identify the most effective opportunities to moderate the social 6 media debate at a large scale using the properties of social signed graphs, such as structural 7 balance. After building the topic universe for a particular political debate in a given time frame, 8 we extract the most active and inﬂuential users and mine their position regarding the topic based 9 on their interactions with other users. The result is a signed graph where each edge represents 10 either support or challenge between a pair of users in the context of the topic. This graph can be 11 modelled as an Ising model, with the goal of minimizing its energy state by using the advantages 12 of Adiabatic Quantum Computing. Applying this principle, we use a Quantum Annealing 13 implementation to solve the problem of ﬁnding the edges violating the structural balance of this 14 graph, which in classic computing is known to be an NP-hard problem. We then provide a non-15
Location Identification and Driver Safety System in VANETs

Vehicular Ad-hoc Networks (VANETs) are major popular wireless environment for Intelligence Transport Systems (ITS). This paper concentrates on Location Identification and Driver Safety (LIDS). Location identification is mapping out by using RFID (Radio Frequency Identification) technology to recognize the current location and also corresponding surrounded areas. The additional feature to be included is to control the speed of vehicle, when ever vehicle crosses school and hospital zones. For driver safety can be carried out using grip force sensor and eye-ball sensor. Driver’s drowsiness is detected by the sensors and alerts the buzzer and stops when ever driver comes to normal state and pressing reset button. The complete system is controlled by an effectual low cost version of 8051 microcontroller (AT89S52). On the whole, LIDS suits well for safety vehicle system. The implementation results show better performance than already existing methods.
Proposal for a postdoctoral position at INRIA,

During this century, there has been an ever increasing interest in the development of objective vocal biomarkers to assist in diagnosis and monitoring of neurodegenerative diseases and, recently, respiratory diseases because of the Covid-19 pandemic. The literature is now relatively rich in methods for objective analysis of dysarthria, a class of motor speech disorders [1], where most of the effort has been made on speech impaired by Parkinson’s disease. However, relatively few studies have addressed the challenging problem of discrimination between subgroups of Parkinsonian disorders which share similar clinical symptoms, particularly is early disease stages [2]. As for the analysis of speech impaired by respiratory diseases, the field is relatively new (with existing developments in very specialized areas) but is taking a great attention since the beginning of the pandemic.
Coupling between Sequence-Mediated Nucleosome Organization and Genome Evolution

The nucleosome is a major modulator of DNA accessibility to other cellular factors. Nucleosome positioning has a critical importance in regulating cell processes such as transcription, replication, recombination or DNA repair. The DNA sequence has an influence on the position of nucleosomes on genomes, although other factors are also implicated, such as ATP-dependent remodelers or competition of the nucleosome with DNA binding proteins. Different sequence motifs can promote or inhibit the nucleosome formation, thus influencing the accessibility to the DNA. Sequence-encoded nucleosome positioning having functional consequences on cell processes can then be selected or counter-selected during evolution. We review the interplay between sequence evolution and nucleosome positioning evolution. We first focus on the different ways to encode nucleosome positions in the DNA sequence, and to which extent these mechanisms are responsible of genome-wide nucleosome positioning in vivo. Then, we discuss the findings about selection of sequences for their nucleosomal properties. Finally, we illustrate how the nucleosome can directly influence sequence evolution through its interactions with DNA damage and repair mechanisms. This review aims to provide an overview of the mutual influence of sequence evolution and nucleosome positioning evolution, possibly leading to complex evolutionary dynamics.
Electrical Properties of Functionalized Silicon Nanoparticles

Silicon nanoparticles are a promising, non-toxic material with respect to printed electronics and quantum size effects. As silicon nanoparticles tend to form a native oxide shell when handled in air, a stable surface functionalization is required to make them applicable for semiconductor purposes. The most favorable way is the stabilization by means of alkylation and hydrosilylation. Therefore, the natural oxide of silicon nanoparticles was removed by etching the particles with hydrofluoric acid. In order to prevent the particles from re-oxidation, the surface of freshly etched particles was functionalized with different alkenes via thermal alkylation. The electrical conductivity of as-prepared, freshly etched, and functionalized Si-NPs was measured using impedance spectroscopy in the temperature range between 323 K and 673 K. The electrical properties of silicon nanoparticles stabilized with n-alkenes ranging from C6 to C18 are investigated.
Author response for "Innate and adaptive immune proteins in the preen gland secretions of male house sparrows"

2020: e 556 Recent studies have demonstrated that preen oil acts to reduce or eliminate featherassociated bacteria. The mechanisms underlying this antibacterial activity, however, are incompletely understood. In addition to the activity of alcohols (i.e. 3,7-dimethyloctan-1-ol), recent research has suggested that antimicrobial peptides may underlie the antibacterial activity of preen oil. Here, we document the presence of innate and adaptive immune proteins, lysozyme and immunoglobulin Y (IgY), in the preen oil of house sparrows Passer domesticus. We suggest lysozyme functions as an antimicrobial agent, with potentially important impacts against Gram-positive feather degrading bacteria. Furthermore, both lysozyme and IgY likely act in local immune defence of the preen gland, and may also play a role in regulating the local microbiome, with potentially important consequences for chemical communication and signalling. Our findings suggest that the preen gland and its secretions should be considered an integral part of the body’s first line of defence against invading infections.
University of Groningen Using Interviewer-respondent Interaction Coding as a Manipulation Check on Interviewer Behavior in Persuading CATI Respondents. Ongena,

This paper shows how interaction coding of interviewer-respondent interactions was used to perform manipulation checks of CATI interviewer behavior in experimental studies. An experiment in which interviewers were instructed to persuade potential respondents by means of a personal style or a formal style showed no significant effects of the persuasion style on survey participation. By means of interviewer-respondent interaction analysis, we studied the interviews in more depth focusing on the compliance of interviewers with the instructions. First, we found that many respondents immediately complied, but when respondents were reluctant, using any form of persuasion was better than none. Second, interviewers also had success in gaining cooperation when they referred to an argument that they had not been instructed to use. In conclusion, we assume that interviewers using arguments in which they were trained develop too much of an unauthentic routine in expressing these arguments, whereas using arguments outside instructions are likely to be expressed in a more natural, spontaneous way and are therefore more convincing. In addition, this study shows that it is useful to include behavior coding as a manipulation check in experiments involving interviewer behavior.
Conservation of the Kinaselike Regulatory Domain

The natriuretic peptide receptors, NPR-A and NPR-B, are two members of the newly described class of receptor guanylyl cyclases. The kinaselike domain of these proteins is an important regulator of the guanylyl cyclase activity. To begin to understand the molecular nature of this type of regulation, we made complete and partial deletions of the kinase domain in NPR-A and NPR-B. We also made chimeric proteins in which the kinase domains of NPR-A and NPR-B were exchanged or replaced with kinase domains from structurally similar proteins. Complete deletion of the kinase homology domain in NPR-A and NPR-B resulted in constitutive activation of the guanylyl cyclase. Various partial deletions of this region produced proteins that had no ability to activate the enzyme with or without hormone stimulation. The kinase homology domain can be exchanged between the two subtypes with no effect on regulation. However, structurally similar kinaselike domains, such as from the epidermal growth factor receptor or from the heat-stable enterotoxin receptor, another member of the receptor guanylyl cyclase family, were not able to regulate the guanylyl cyclase activity correctly. These findings suggest that the kinaselike domain of NPR-A and NPR-B requires strict sequence conservation to maintain proper regulation of their guanylyl cyclase activity.
On Covidiots and Covexperts: Stupidity and the Politics of Health

The COVID-19 pandemic has highlighted the significance of the politics of health as an ongoing interpretative event. The effectiveness of delivering prevention strategies is in negotiation with day-to-day arguments in the public sphere, not just by “experts” in peer-reviewed papers, but also in the everyday interpretations and discussions of available expertise on print and digital media platforms. In this paper I explore ae particular facet of these public debate over the politics of health: the deployment of the commonplace of stupidity. I argue that the growth of this commonplace within discussion is rooted in particular models of interpretation which limit self-understanding, by over-emphasising certain points of significance within the interpretative horizon over more banal (and “stupid”) aspects that are, nevertheless, influential on health interventions.
Modeling and Adaptive Backstepping Control for Quadrotor Aerial Robots with Blade Flapping

Dynamics modeling and control for quadrotor aerial robots are considered in this paper. The three-dimensional dynamics model of the quadrotor is first derived using the Newton-Euler approach. When the propelling rotor rotating with respect to the moving robot, the rotating blades could be deflected with an effect on the aerial vehicles known as flapping. The modeling with blade flapping is considered. Then a nonlinear stable adaptive control with flapping parameters estimation is proposed using the backstepping technique for the position and yaw angle trajectory tracking. Finally, computer simulation is used to validate the performance of the proposed control strategy. In the simulation study, the desired trajectory is constructed using the cubic spline interpolation.
Exploring Direct Convolution Performance on the Gemmini Accelerator

Convolutional Neural Network (CNN) algorithms are becoming a recurrent solution to solve Computer Vision related problems. These networks employ convolutions as main building block, which greatly impact their performance since convolution is a costly operation. Due to its importance in CNN algorithms, this work evaluates convolution performance in the Gemmini accelerator and compare it to a conventional lightlyand heavily-loaded desktop CPU in terms of execution time and energy consumption. We show that Gemmini can achieve lower execution time and energy consumption when compared to a CPU even for small convolutions, and this performance gap grows with convolution size. Furthermore, we analyze the minimum Gemmini required frequency to match the same CPU execution time, and show that Gemmini can achieve the same runtime while working in much lower frequencies. Resumo. Algoritmos de Redes Neurais Convolucionais (CNN do inglês Convolutional Neural Network) tem se tornado uma solução recorrente para solucionar problemas de Visão Computacional. Estas redes empregam convoluções como principal bloco de construção, o que impacta a performance, pois convolução é um operação cara computacionalmente. Devido a sua importância nos algoritmos de CNN, este trabalho avalia o desempenho de convoluções no acelerador Gemmini e os compara com a execução em uma CPU convencional com cargas leves e pesadas de trabalho. Nós mostramos que o Gemmini pode atingir melhores tempos de execução e consumos energéticos até mesmo para pequenas convoluções e a diferença de desempenho cresce com o tamanho da convolução. Além disso, nós analisamos a frequência mı́nima necessária que o Gemmini deve ter para obter o mesmo tempo de execução de uma CPU e mostramos que o Gemmini é capaz de atingir o mesmo resultado mesmo quando trabalhando em frequências muito mais baixas.
Neural Auto-Exposure for High-Dynamic Range Object Detection

Real-world scenes have a dynamic range of up to 280 dB that todays imaging sensors cannot directly capture. Existing live vision pipelines tackle this fundamental challenge by relying on high dynamic range (HDR) sensors that try to recover HDR images from multiple captures with different exposures. While HDR sensors substantially increase the dynamic range, they are not without disadvantages, including severe artifacts for dynamic scenes, reduced fill-factor, lower resolution, and high sensor cost. At the same time, traditional auto-exposure methods for low-dynamic range sensors have advanced as proprietary methods relying on image statistics separated from downstream vision algorithms. In this work, we revisit auto-exposure control as an alternative to HDR sensors. We propose a neural net-work for exposure selection that is trained jointly, end-to-end with an object detector and an image signal processing (ISP) pipeline. To this end, we use an HDR dataset for automotive object detection and an HDR training procedure. We validate that the proposed neural auto-exposure control, which is tailored to object detection, outperforms conventional auto-exposure methods by more than 6 points in mean average precision (mAP).
HYBRIDIZATION IN THE ENSATINA RING SPECIES STRONG SELECTION AGAINST HYBRIDS AT A HYBRID ZONE IN THE ENSATINA RING SPECIES COMPLEX AND ITS EVOLUTIONARY IMPLICATIONS

—The analysis of interactions between lineages at varying levels of genetic divergence can provide insights into the process of speciation through the accumulation of incompatible mutations. Ring species, and especially the Ensatina eschscholtzii system exemplify this approach. The plethodontid salamanders Ensatina eschscholtzii xanthoptica and Ensatina eschscholtzii platensis hybridize in the Central Sierran foothills of California. We compared the genetic structure across two transects (southern and northern Calaveras Co.), one of which was re-sampled over 20 years, and examined diagnostic molecular markers (eight allozyme loci and mitochondrial DNA) and a diagnostic quantitative trait (color pattern). Key results across all studies were: i) cline centers for all markers were coincident and the zones were narrow, with width estimates of 730m to 2000m; ii) cline centers at the northern Calaveras transect were coincident between 1981 and 2001, demonstrating repeatability over 5 generations; iii) there are very few if any putative F1’s, but a relatively high number of backcrossed individuals (57–86%) in the central portion of transects; iv) we found substantial linkage disequilibrium in all three studies and strong heterozygote deficit both in northern Calaveras, in 2001, and southern Calaveras. Both linkage disequilibrium and heterozygote deficit show maximum values near the center of the zones ( R and Fis, ≈ 0.5). Using estimates of cline width and dispersal, we infer strong selection against hybrids (s* ≈ 46-75%). This is sufficient to promote accumulation of differences at loci that are neutral or under divergent selection, but would still allow for introgression of adaptive alleles. The evidence for strong, but incomplete isolation across this centrally located contact is consistent with theory suggesting a gradual increase in postzygotic incompatibility between allopatric populations subject to divergent selection and reinforces the value of Ensatina as a system for the study of divergence and speciation at multiple stages.
Estimation of the main dimensions of the traction permanent magnet-assisted synchronous reluctance motor

Goal. The goal of the research is to develop an algorithm for selecting the main dimensions of a traction permanent magnet-assisted synchronous reluctance motor. Methodology. A method for determining the main dimensions of the motor, which combines the analytical selection of stator parameters and numerical field calculations for the selection of rotor parameters. The need to check the mechanical strength of a rotor with permanent NdFeB magnets in flux barriers is shown. Results. The article proposes an algorithm for selecting the main dimensions of a traction permanent magnet-assisted synchronous reluctance motor, which combines analytical expressions for selecting stator parameters and numerical field calculations for selecting rotor parameters. It is determined that analytical methods for calculating the magnetic circuit need to be developed in order to reduce the time to select the main dimensions of the motor. Originality. For the first time the sizes of active parts of the permanent magnet-assisted synchronous reluctance motor with power of 180 kW for the drive of wheels of the trolleybus are defined. Practical significance. As a result of research the sizes of active parts, stator winding data and a design of a rotor of the electric motor are defined. The obtained results can be applied when creating an electric motor for a trolleybus. References 17, tables 3, figures 5.
Working of various routing protocols in Vehicular Ad-hoc Network: A Survey

: Vehicular Ad-hoc Networks (VANETs) is an improved form of Mobile Ad-hoc Networks (MANETs), where the vehicles moving in a predefined route with relatively high speed. Due to high rate of topology changes in VANETs, frequent disruption in link and excessive overhead occurs. An intelligent transportation system (ITS) is being approached by using VANET therefore the need of efficient VANET routing protocol is crucial. In VANET routing protocols, an efficient route must be established between nodes before communication can take place and it should adapt dynamic topology changes caused by rapid movement of vehicles. In this paper, different routing protocols in VANET are described which may help in designing improved routing protocols.