Miracle-dz/UniFAR-FTUs huggingface dataset:
Students’ Possibilities to Learn From Group Discussions Integrated in Whole-class Teaching in Mathematics

ABSTRACT The aim of this paper is to investigate how small-group and whole-class discussions during whole-class teaching contribute to students’ learning. The study includes 33 video-recorded small-group discussions in four mathematics lessons on enlarging and reducing two-dimensional geometric figures in Grade 8. The results show that different objects of learning were enacted in the different small-groups’ discussions, and that in the majority of the small-group discussions the students did not have the possibility to learn what was intended, since critical aspects were not explored. The combination of group and whole-class discussions contributed to that critical aspects of the specific subject matter came to the fore and thereby were possible to discern. The results indicate that small-group discussions without subsequent whole-class discussions may have less effect on student learning.
The Gig Economy in Times of COVID-19: Designing for Gig Workers’ Needs

ABSTRACT Worldwide, the COVID-19 pandemic has disproportionately affected gig economy workers due to the contingent and precarious nature of their work. Many gig economy workers have had to adapt quickly to new forms of working, and even learn new skills, to sustain their livelihood. At the same time, gig economy companies have prioritised profit and customers’ needs over workers’ safety. In this position paper, we draw insights from recent academic literature, policy papers, and media reports from across the globe to explore broad implications the pandemic has had on gig economy workers. We then discuss how gig economy platforms might be re-designed to support better working conditions and foster workers’ development. CCS Concepts • Human-centered computing → Computer supported cooperative work. Keywords future of work, gig economy, worker-centred design, COVID-19 ABOUT THE AUTHOR/S Juan Carlos Alvarez de la Vega Northumbria University carlos.alvarez@northumbria.ac. uk I am a doctoral researcher at Northumbria University Social Computing Lab, working under the supervision of Dr Marta Cecchinato and Dr John Rooksby. My research focuses on gig economy freelancing platforms and worker-centred design approaches. Using qualitative and participatory methods, I explore how freelancing platforms impact their users’ wellbeing. My professional experience and background are in design, community engagements and social innovation. Website: https://carlosalvarez.org Marta E. Cecchinato Northumbria University marta.cecchinato@northumbria.ac. uk John Rooksby Northumbria University john.rooksby@northumbria.ac. uk New Future of Work 2020, August 3–5, 2020 © 2020 Copyright held by the owner/author(s).
Sharing Economy and Lifestyle Changes, as Exemplified by the Tourism Market

The aim of the article is to analyze the relationship between lifestyle changes and willingness to use sharing economy services in tourism, including peer-to-peer accommodation. On the one hand, knowledge of lifestyle changes can help adapt the product offer to the requirements of consumers. On the other hand, products that consumers use can reflect lifestyle changes. The following classification of motivations for sharing economy activity selection resulting from the subjects’ lifestyles has been proposed: personal motivations—related to economic advantages; social (conformist) motivations—resulting from the need to fit in with others; and ideological motivation—resulting from the understanding of the processes of natural environment degradation and excessive consumption. In order to gather opinions and to understand behaviors, attitudes, and preferences regarding sharing economy activities (i.e., the sharing of transportation, food, clothes, equipment, and accommodation), the focus group interview method was used (6 groups, 5–8 participants each). Discussions were conducted separately for two populations: young with time (YT) and older rich (OR). The study demonstrates lifestyle changes between the generations. YT actions are the consequence of personal and ideological motivations. OR have lifestyles that result from personal and conformist motivations. Neither population sees a relationship between participating in the sharing economy and caring for the environment and preventing excessive consumption.
An improved particle swarm optimization algorithm and its application in solving forward kinematics of a 3-DoF parallel manipulator

This paper proposes an improved particle swarm optimization to study the forward kinematic of a solar tracking device which has two rotational and one translational degree of freedom. The forward kinematics of the parallel manipulator is transformed into an optimization problem by solving the inverse kinematics equations. The proposed method combines inertial weight with the iterations number and the distance between current swarm particles and the optimum to improve convergence ability and speed. The novel cognitive and social parameters are adjusted by the inertia weight to enhance unity and intelligence of the algorithm. A stochastic mutation is used to diversify swarm for faster convergence via local optima evasion in high dimensional complex optimization problems. The performance of the proposed method is demonstrated by applying it to four benchmark functions and comparing convergence with three popular particle swarm optimization methods to verify the feasibility of the improved method. The behaviors of the proposed method using variable cognitive and social parameters and fixed value are also tested to verify fast convergence speed of variable parameters method. And further, an application example uses the method to determine the forward kinematics of a three-degree-of-freedom parallel manipulator. Finally, the mechanism simulations model of the parallel manipulator are carefully built and analyzed to verify the correctness of the proposed algorithm in PTC Creo Parametric software. In all cases tested, the proposed algorithm achieved much faster convergence and either improved or proximal fitness values.
NATURAL COMPOUNDS FROM DJIBOUTIAN MEDICINAL PLANTS AS INHIBITORS OF COVID-19 BY IN SILICO INVESTIGATIONS

Objective: The new coronavirus type SARS-Cov 2 (severe acute respiratory syndrome), which appeared in autumn 2019 in China, became a global pandemic in a few months. In this work, we looked for the potential anti SARS-Cov 2 of the compounds isolated from three Djiboutian medicinal plants, namely Acacia seyal, Cymbopogon commutatus, and Indigofera caerulea. Methods: We carried out a molecular docking with nine biomolecules, β-Sitosterol, Quercetin, Catechin, Lupeol, Rutin, Kaempferol, Gallic acid, Piperitone and Limonene on three target sites which are SARS-CoV-2 main protease (Mp), SARS-CoV-2 receptor-binding domain (RBD) and human furin protease. These targets are chosen because of their role in the process of penetration of the virus into human cells and its multiplication. Moreover, the predictions of pharmacokinetic parameters as well as toxicological properties have been determined using an online bioinformatics tool named SwissADME and AdmetSAR respectively. Results: The phenolic compounds have a very good affinity on these three target sites with binding energies of up to-9.098 kcal/mol for rutin on SARS-CoV-2 Mp, much better than the two reference drugs hydroxychloroquine (-5.816 kcal/mol) and remdesivir (-7.194 kcal/mol). Except for β-Sitosterol, the tested biomolecules have weak toxicity. Conclusion: These natural compounds can be used against covid 19 pending In vitro and In vivo evaluations.
Persation: an IoT Based Personal Safety Prediction Model Aided Solution

The number of attacks on innocent victims in moving vehicles, and abduction of individuals in their vehicles has risen alarmingly in the past few years. One common scenario evident from the modus operandi of this kind of attack is the random motion of these vehicles, due to the driver’s unpredictable behaviours. To save the victims in such kinds of assault, it is essential to offer help promptly. An effective strategy to save victims is to predict the future location of the vehicles so that the rescue mission can be actioned at the earliest possibility. We have done a comprehensive survey of the state-of-the-art personal safety solutions and location prediction technologies and proposes an Internet of Things (IoT) based personal safety model, encompassing a prediction framework to anticipate the future vehicle locations by exploiting complex analytics of current and past data variables including the speed, direction and geolocation of the vehicles. Experiments conducted based on real-world datasets demonstrate the feasibility of our proposed framework in accurately predicting future vehicle locations. In this paper, we have a risk assessment of our safety solution model based on the OCTAVE ALLEGRO model and the implementation of our prediction model.
Interpretation of Simulation Results Including a Dynamic Capillary Pressure Relationship

Over the past years, the study of multiphase flow has gained in interest, as it is involved in many field situations, such as unsaturated water flow in the subsurface, remediation of contaminated sites and water-oil displacement during oil recovery. Capillarity plays an important role in a multiphase system, as it defines the distribution of the phases and thus the overall behavior of the system. Until today, an empirical relationship between capillary pressure and saturation, obtained by means of laboratory experiments carried out on soil samples, is used to describe capillary pressure. However, this relationship assumes equilibrium in the distribution of the phases in the porous medium. This assumption is valid in cases where saturation varies slowly, however it may not be appropriate for application in faster processes. In such cases, dynamic effects may have an influence on the system. Different theories have been proposed for the inclusion of dynamic effects in the modeling of multiphase flow. In this work, a dynamic capillary pressure relationship is included in the mathematical and numerical model of the numerical simulation of imbibition processes. Set-ups with different boundary conditions are used. The results of the ”dynamic” cases, meaning cases that include the dynamic capillary pressure relationship, are compared to results of reference cases, where the classical capillary pressure-saturation relationship is included. The results reveal that for the different set-ups, the inclusion of the dynamic capillary pressure relationship has a different influence. Author’s Statement I herewith certify that I have prepared this master thesis independently, and that only sources, aids, and advisors that are duly noted herein have been used and / or consulted. Signature Date I would like to thank my supervisor Prof. Dr.-Ing. Rainer Helmig for giving me the opportunity to write this Master’s Thesis, for his constant support and the interest he showed each time I needed his advice. Very special thanks to Sabine Manthey for the guidance, the help, the patience and her good will during the last months that we worked together. I would like to thank also my colleagues Hartmut Eichel and Anongnart Assteerawatt, who shared their office at the Institut fur Wasserbau with me, for helping me always when I needed their support. My thanks to all the people in the group, for the friendly atmosphere and for helping me to solve the every day problems that came up during the last few months. Finally, I would like to thank my family and my friends for being there for me. Stuttgart, 10/11/2004 Alexandros Papafotiou
Pulling Illusion Based on the Phase Difference of the Frequency Components of Asymmetric Vibrations

When presented with asymmetric vibrations, humans experience an illusory force, similar to the sensation of being pulled in a particular direction. A pulling illusion has also been used in new display elements for a virtual reality content and a pedestrian navigation system. However, the basic design of asymmetric vibration stimuli that can induce this illusion has not yet been determined. In particular, it is unclear as to which part of the vibration waveform should be asymmetric to induce an illusion. To better understand the design of asymmetric vibration stimuli that can induce a pulling illusion, we evaluated the effect of the illusion corresponding to the waveform deformation due to a change in phase difference of asymmetric-vibration frequency components. The results of a psychophysical experiment demonstrate that when the phase differences of the fundamental and second harmonic waves of the asymmetric vibration are close to 0<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> or <inline-formula><tex-math notation="LaTeX">$-$</tex-math></inline-formula>180<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula>, the illusion is more likely to occur. This result implies that the difference in the rate by which the acceleration changes at each polarity contributes to the illusion.
Parameters Estimation Of Rayleigh Distribution In Survival Analysis On Type Ii Censored Data Using The Bayesian Method

This research aims to determine the estimation of Rayleigh’s distribution parameters on the data survival analysis of type II of tuberculosis patients. The method used in this research is the Bayesian method to perform estimate parameters. The process estimation parameter using the Bayesian method requires information from the likelihood function and the prior distribution. The prior distribution used was the prior distribution of Jeffreys. In this study, estimates of Rayleigh’s distribution parameters were applied in the survival analysis data of tuberculosis sufferers. And the value of estimated parameters in patients with tuberculosis acquired θ = 0.001097324 and the changes of the survival value decreased near to zero.
Physical-Layer Arithmetic for Federated Learning in Uplink MU-MIMO Enabled Wireless Networks

Federated learning is a very promising machine learning paradigm where a large number of clients cooperatively train a global model using their respective local data. In this paper, we consider the application of federated learning in wireless networks featuring uplink multiuser multiple-input and multiple-output (MU-MIMO), and aim at optimizing the communication efficiency during the aggregation of client-side updates by exploiting the inherent superposition of radio frequency (RF) signals. We propose a novel approach named Physical-Layer Arithmetic (PhyArith), where the clients encode their local updates into aligned digital sequences which are converted into RF signals for sending to the server simultaneously, and the server directly recovers the exact summation of these updates as required from the superimposed RF signal by employing a customized sum-product algorithm. PhyArith is compatible with commodity devices due to the use of full digital operation in both the client-side encoding and the server-side decoding processes, and can also be integrated with other updates compression based acceleration techniques. Simulation results show that PhyArith further improves the communication efficiency by 1.5 to 3 times for training LeNet-5, compared with solutions only applying updates compression.
Character-based identification system of scombrids from Indian waters for authentication and conservation purposes

Abstract Scombrids are the important component of pelagic fishery resources which include 54 species under 15 genera commonly known as mackerels, bonitos, and tunas. Due to the high commercial value attained, there are real chances of fraudulent substitution by species of inferior value. DNA based species identification methods can be applied to detect product adulteration, as well as to better contribute to the conservation and management of these species by providing accurate species identification independently of the age of the individuals or the tissue processed. In this study, a total of 15 commercially important scombrid species from Indian waters were analyzed. Due to the inadequacy of mitochondrial COI barcoding gene in discriminating between some Thunnus species, cytochrome b sequences were used instead. For all the 15 species, we propose a DNA character-based keys which uses a diagnostic combination of nucleotides and respective probes, including the first character-based keys and probes to differentiate between Thunnus albacares and T. obsesus.
Morphism classification of a family of transcendent functions arising from pharmacokinetic modelling

Many transcendental functions were constructed through finding closed‐form solutions of algebraic or differential equations and become ubiquitous gradually with increasing awareness of applications in specific problems naturally arising from life science. Motivated by Lambert W function, a family of transcendent X functions was introduced recently to express the closed‐form solutions of some nonlinear pharmacokinetic models. Unfortunately, its mathematical properties have not been completely studied. For the purposes of mathematical point of views and the use of wider applications, our objective in this paper is to characterize morphism classification of X functions at the scope of real branches.
Explanatory Diagnosis of Discrete-Event Systems with Temporal Information and Smart Knowledge-Compilation

Model-based diagnosis is typically set-oriented. In static systems, such as combinational circuits, a candidate (or diagnosis) is a set of faulty components that explains a set of observations. In discrete-event systems (DESs), a candidate is a set of faulty events occurring in a sequence of state changes that conforms with a sequence of observations. Invariably, a candidate is a set. This set-oriented perspective makes diagnosis of DESs narrow in explainability, owing to the lack of any temporal knowledge relevant to the faults within a candidate, along with the inability to discriminate between single and multiple occurrences of the same fault. Embedding temporal knowledge in a candidate, such as the relative temporal ordering of faults and the multiplicity of the same fault, may be essential for critical decision making. To favor explainability, the notions of temporal fault, explanation, and explainer are introduced in diagnosis of DESs. The explanation engine reacts to a given sequence of observations by generating and refining in real-time a sequence of regular expressions, where the language of each expression is a set of temporal faults. Moreover, to avoid total knowledge compilation, the explainer can be generated incrementally either offline, based on meaningful behavioral scenarios, or online, when being operated in solving specific diagnosis problems.
On the Pitfalls of Estimating and Using Standardized Reliability Coefficients

The population discrepancy between unstandardized and standardized reliability of homogeneous multicomponent measuring instruments is examined. Within a latent variable modeling framework, it is shown that the standardized reliability coefficient for unidimensional scales can be markedly higher than the corresponding unstandardized reliability coefficient, or alternatively substantially lower than the latter. Based on these findings, it is recommended that scholars avoid estimating, reporting, interpreting, or using standardized scale reliability coefficients in empirical research, unless they have strong reasons to consider standardizing the original components of utilized scales.
Ultrasound-Guided Percutaneous Neuromodulation in Patients with Unilateral Anterior Knee Pain: A Randomized Clinical Trial

The objective of this study was to evaluate the short-term and crossover effects of a percutaneous neuromodulation (PNM) intervention on the femoral nerve, regarding the pain, knee flexion motion (range of motion (ROM)), and functionality, in patients with unilateral anterior knee pain (AKP). Our study used a randomized clinical trial design. Thirty patients were divided into two groups: one asymptomatic knee group in which patients received stimulation in the femoral nerve corresponding to the nonsymptomatic knee; and one symptomatic knee group, in which patients received stimulation in the femoral nerve corresponding to the painful knee. Pain, knee flexion ROM, Victorian Institute of Sport Assessment-Patella (VISA-P) and Kujala questionnaires were evaluated. Twenty-eight patients completed the study. Compared to their baseline values, both groups showed an increase immediately at 24 h, and at 1 week for the knee flexion ROM variable. In addition, the symptomatic knee group showed an increase for the Kujala score and a decrease for the numeric rating scale (NRS) variable from baseline to 1 week. VISA-P score did not show statistically significant differences for the time-group interaction. After the intervention, there were no differences between the groups in any measured time. Conclusion: a single-shot ultrasound-guided PNM intervention per week in the femoral nerve may be an effective treatment for improving the pain, knee flexion ROM, and knee functionality. In addition, this technique produces crossover benefits in the nonintervention limb.
The Analysis of Customer Satisfaction with Online Banking In China: The Impact of Experience

Our research is study on the antecedents of customer satisfaction with online banking in China, and explores the effects of experience on the relationships between the antecedents and customer satisfaction. Based on prior study, the six kinds of experience of customer satisfaction – ease of use, design, speed, security, information content, and customer support service – are proposed, and the effects of experience on the relationships between these and customer satisfaction are analyzed using a structural multi-group(a high-experience group and a low-experience group) model. The results show that design, speed, security, information content, and customer support service have a significant influence on customer satisfaction in the high-experience group or the lowexperience group, but ease of use does not have a significant influence on customer satisfaction in either of the groups. Also, the results relating to the influence of the level of customer experience reveal that the effects of design, security, speed, and information content on customer satisfaction were significantly higher in the high-experience group, whereas the effect of customer support service on customer satisfaction was significantly higher in the low-experience group.