Miracle-dz/UniFAR-FTUs huggingface dataset:
PALM: Probabilistic area loss Minimization for Protein Sequence Alignment

Protein sequence alignment is a fundamental problem in computational structure biology and popu-lar for protein 3D structural prediction and protein homology detection. Most of the developed programs for detecting protein sequence alignments are based upon the likelihood information of amino acids and are sensitive to alignment noises. We present a robust method PALM for modeling pairwise protein structure alignments, using the area distance to reduce the biological measurement noise. PALM generatively learn the alignment of two protein sequences with probabilistic area distance objective, which can denoise the measurement errors and offsets from different biologists. During learning, we show that the optimization is computationally efﬁcient by estimating the gradients via dynamically sampling alignments. Empiri-cally, we show that PALM can generate sequence alignments with higher precision and recall, as well as smaller area distance than the competing methods especially for long protein sequences and remote homologies. This study implies for learning over large-scale protein sequence alignment problems, one could potentially give PALM a try.
Using GAS for Speedy Generation of Hybrid Multi-Cloud Auto Generated AI Services

—Today’s tasks require a plethora of analytics tasks to be conducted to tackle state-of-the-art computational challenges posed in society impacting many areas including health care, automotive, banking, natural language processing, image detection, and many more data analytics related tasks. Sharing existing analytics functions allows reuse and reduces overall effort. However, integrating deployment frameworks in the age of cloud computing is often out of reach for domain experts. Simple frameworks are needed that allow even non-experts to deploy and host services in the cloud. To avoid vendor lock-in, we require a generalized composable analytics service framework that allows users to integrate their services and those offered in clouds, not only by one, but by many cloud compute and service providers. Wereport on work that we conducted to provide a service integration framework for composing generalized analytics frameworks on multi-cloud providers that we call our Generalized AI Service (GAS) Generator. We demonstrate the framework’s usability by showcasing useful analytics workﬂows on various cloud providers, including AWS, Azure, and Google and edge computing IoT devices. The examples are based on Scikit learn to use them also in educational settings that can easily be replicated and expanded upon. Benchmarks are used to compare the different services and showcase general replicability.
Time-Delay Measurements from Antarctic Neutron Monitor Stations Indicate Weak Spectral Changes during 27-day Variations

aMahidol University, Department of Physics, Faculty of Science, Bangkok 10400, Thailand bRajamangala University of Technology Thanyaburi, Division of Physics, Faculty of Science and Technology, Pathum Thani 12110, Thailand cUniversity of Delaware, Department of Physics and Astronomy, Newark, DE 19716, USA dUniversity of Wisconsin River Falls, Department of Physics, River Falls, WI 54022, USA eChungnam National University, Department of Astronomy, Space Science and Geology, Daejeon 34134, South Korea f Chonnam National University, Department of Earth Science Education, Gwangju 61186, South Korea gUniversity of Tasmania, School of Natural Sciences, Hobart, Tasmania 7001, Australia E-mail: fhoone@hotmail.com, david.ruf@mahidol.ac. th,
The Effectiveness of Using Electronic Mind Maps to Develop Students’ Knowledge of Multimedia Concepts at Al Baha University

the emergence of web 2.0 technologies has created new opportunities in the field of multimedia concepts. Electronic mind maps are used to present information in an interesting and fast format, save time and keep learners from becoming bored. Electronic mind maps are a valuable platform for learning multimedia concepts in class activities and as out-of-class assignments to increase learners' achievements. Therefore, this research focuses on designing electronic mind maps (using XMind) to teach multimedia concepts among undergraduate students at the College of Education at Al-Baha University. The study aimed to detect the effect of e-mind maps on increasing students' achievements. The study used a quasi-experimental approach to prepare the literature framework and a measurement tool including an achievement test. The study sample consisted of 40 learners. The researcher used a t-test to measure the differences between the experimental group, which was taught using e-mind maps (text and image), and the control group, which was taught using a traditional method. The results revealed that there was a significant difference in the level of ? 0.05 in relation to the experimental group taught by e-mind maps, with an arithmetic average of 28.25 in the post achievement test. Therefore, the study recommended working with e-mind maps, which contain photos and texts when teaching instructional design at the university, and measuring its effect on acquiring some concepts of multimedia.
Digital Educational Games: Tensioning the Production Process

In 2018, the Gamer Census conducted in Brazil recorded that the production of digital educational games surpassed entertainment games, showing a growing interest in the production of this type of learning oriented games. This research has an exploratory character and seeks to discuss which elements should be contem-plated in digital educational games, as well as their levels of importance. The results of this research revealed the dichotomy between developers, teachers and players of what should be a digital educational game and what features should be prioritized.
32 PROCEEDINGS OF INTERNATIONAL CONFERENCE ON CONTEMPORARY THEORY AND PRACTICE IN CONSTRUCTION XIV EXPERIMENTAL ANALYSIS OF STRUCTURAL DAMPING FOR BOLTED AND WELDED SPLICE CONNECTION JOINT FOR IPE-80 STEEL

Progress and demands of all types of constructions imposed the need for the development of modern structures that are lightweight, but at the same time have high damping capacity and stiffness. The consequences of these requirements are increased dynamic problems related to vibrations and dissipative processes in structure connection joints. Structural joints are the main reason for the significant reduction of the level of energy dissipation and source of structural damping so therefore they have become a subject of interest to many researchers. The aim of this paper is to present some problems regarding research of structural damping and the importance of study Contact Mechanics to better understand the problem of structural damping.
Reproducibilidad en AGILE: Experiencias, logros y recomendaciones

Este artículo describe las experiencias, actividades realizadas, recursos generados y recomendaciones para la promoción e incentivación de prácticas en investigación reproducible en el campo de la ciencia de la información geográfica. Aunque el artículo se centra en la comunidad y conferencia AGILE (Association of Geographic Information Laboratories in Europe), creemos que los recursos y lecciones aprendidas pueden ser extrapolables a comunidades y asociaciones científicas afines en otras regiones, como puede ser Latinoamérica. En este sentido, hacemos especial hincapié en la descripción de las directrices para la redacción de artículos reproducibles propuestas en el seno de AGILE, así como en una serie de recomendaciones dirigidas principalmente a asociaciones y organizadores de conferencias científicas para la adopción y promoción paulatina de dichas prácticas. Se trata pues de una llamada a la comunidad Latinoamérica de la ciencia de la información geográfica a que consideren los recursos aquí detallados con el fin de incentivar la investigación reproducible en sus comunidades científicas.
Cardiac Effects of Cocaine Use

Cocaine use can precipitate as well as worsen underlying cardiovascular disease. Its impact ranges from a persistent elevation of blood pressure to catastrophic aortic dissection or ventricular tachyarrhythmias. Cocaine’s physiologic effects are primarily driven by its sympathomimetic characteristics through its action on alpha and beta-adrenergic receptors causing elevations in inotropy, heart rate and systemic blood pressure. Paul Obeng-Okyere1; Michael Sun1; Katelynn Lee Alcorn3; Jasmine Mikal Haydel3; Vaskar Mukerji1,2,3* 1Kettering Medical Center, Dayton, OH 45429. 2Veterans Affairs Medical Center, Dayton, OH 45428. 3Wright State University Boonshoft School of Medicine, Dayton, OH 45435.
Radio astronomy locates the neutrino origin in bright blazars

Astro Space Center of Lebedev Physical Institute, Profsoyuznaya 84/32, 117997 Moscow, Russia Moscow Institute of Physics and Technology, Institutsky per. 9, Dolgoprudny 141700, Russia Max-Planck-Institut für Radioastronomie, Auf dem Hügel 69, 53121 Bonn, Germany Institute for Nuclear Research of the Russian Academy of Sciences, 60th October Anniversary Prospect 7a, Moscow 117312, Russia E-mail: alexander@plav.in
Discounting Desirable Gambles

The desirable gambles framework offers the most com-prehensive foundations for the theory of lower previsions, which in turn affords the most general account of imprecise probabilities. Nevertheless, for all its generality, the theory of lower previsions rests on the notion of linear utility. This commitment to linearity is clearest in the coherence axioms for sets of desirable gambles. This paper considers two routes to relaxing this commitment. The ﬁrst preserves the additive structure of the desirable gambles framework and the machinery for coherent inference but detaches the interpretation of desirability from the multiplicative scale invariance axiom. The second strays from the additive combination axiom to accommodate repeated gambles that return rewards by a non-stationary processes that is not necessarily additive. Unlike the ﬁrst approach, which is a conservative amendment to the desirable gambles framework, the second is a radical departure. Yet, common to both is a method for describing rewards called discounted utility .
Online survey into developing a model for a legal cannabis market in the United Kingdom

Background Despite rescheduling of cannabis to Schedule 2 and amendments to the law permitting legal availability of cannabis for the treatment of medical conditions, access to cannabis for medical use remains challenging for patients in the United Kingdom (UK). Recreational use is widespread despite laws stating users can be sentenced to prison for up to 5 years for possession. Objective The aim of the study was to develop a model for a legal cannabis market in the UK building upon the results of a preceding study in which a UK population sample determined that pharmacies are the most suitable primary legal vendor of cannabis as opposed to regulated shops or the black market. Methods An online survey was developed using Qualtrics software and advertised via the Multidisciplinary Association for Psychedelic Studies’ Facebook, Twitter and Instagram social media accounts and monthly newsletter. Results Three hundred and ninety seven individuals, a majority having used cannabis at least once, consented to participate in the study. The participants concluded that there is enough evidence for cannabis to be prescribed to treat a range of medical conditions. In addition to pharmacies providing cannabis to patients with a prescription, a majority of participants supported cannabis being sold in pharmacies for harm reduction purposes and allowing access to medicinal cannabis in cases where supporting evidence is insufficient to merit a prescription. Participants supported greater integration between dispensing pharmacies and mental health services. Overall, the participants did not oppose a consultation or screening for potential cannabis users prior to obtaining access from licensed vendors. UK participants were supportive of the concept of a cannabis card, which users can present to licensed vendors such as pharmacies, with specific recommendations (such as strains relevant to a patient’s medical condition) being coded into the card. A majority of participants supported the existence of shisha-type bars for the purchase and onsite consumption of cannabis and determined that such vendors should not be part of a pharmacy chain of stores or regulated by pharmacy regulators. The participants generally preferred that laws regarding public consumption are in line with existing smoking legislation. Participants determined that it should be legally permitted to grow cannabis at home for personal medical and non-medical purposes but not to sell for profit. Conclusion The results are suggestive of a regulatory system that medical and non-medical cannabis users can use which aims to maximise therapeutic applications, minimise harms and respect individual liberty.
HIGH INTENSITY INTERVAL TRAININGS IN SCHOOLCHILDREN

ARTICLE Abstract: High-intensity interval training is used to improve maximum oxygen intake and aerobic functional capacity of school children. So far, it has been discovered that high-intensity interval training (HIIT) is effective in improving anaerobic capacity. Aim of the study was to determine the effectiveness and impact of HIIT training on the improvement of VO2 in schoolchildren based on a systematic review of a large number of studies that have addressed the impact of high-intensity interval training. Following electronic databases were searched: Google Scholar, PubMed, Web of Science and Research Gate, using all papers available by April 30, 2020. The following keywords were used: "high-intensity interval", "training", "HIIT", "training". The search was mostly related to English and original scientific papers from available journals. In the first phase of the search, the relevance of the titles and abstracts of the identified papers was checked. In the second phase of the search, the complete papers were downloaded and considered for inclusion. References from all collected papers were reviewed to obtain more research that studied this area. Total of 10 studies met the criteria and were included into the systematic review. High-intensity interval training leads to the improvement of VO2, VO2max, O2 and other physiological parameters in school children by applying various high-intensity interval training programs. Programs in duration of six, ten and twelve weeks lead to the improvement of physiological parameters of school children, while the seven-week program of high-interval training proved to be the best program in relation to the duration and intensity of the program. Based on the analysis and discussion of the papers observed in the systematic research, it can be concluded that, according to the duration of the program, the minimum period where VO2 and VO2max and other physiological abilities can improve is six weeks, and the usual weekly load is two to three workouts per week.
Paper— Information Extraction from Binary Skill Assessment Data with Machine Learning Information Extraction from Binary Skill Assessment Data with Machine Learning

— Strength training exercises are essential for rehabilitation, improving our health as well as in sports. For optimal and safe training, educators and trainers in the industry should comprehend exercise form or technique. Currently, there is a lack of tools measuring in-depth skills of strength training experts. In this study, we investigate how data mining methods can be used to identify novel and useful skill patterns from a binary multiple choice questionnaire test designed to measure the knowledge level of strength training experts. A skill test assessing exercise technique expertise and comprehension was answered by 507 fitness professionals with varying backgrounds. A triangulated approach of clustering and non-negative matrix factorization (NMF) was used to discover skill patterns among participants and patterns in test questions. Four distinct participant sub-groups were identified in data with clustering and further question patterns with NMF. The results can be used to, for example, identify missing skills and knowledge in participants and subgroups of participants and form general and personalized or background specific guidelines for future education. In addition, the test can be optimized based on, for example, if some questions can be answered correct even without the required skill or if they seem to be measuring overlapping skills. Finally, this approach can be utilized with other multiple choice test data in future educational research.
LocalNewton: Reducing communication rounds for distributed learning

To address the communication bottleneck problem in distributed optimization within a master-worker framework, we propose LocalNewton, a distributed second-order algorithm with local averaging . In LocalNewton, the worker machines update their model in every iteration by ﬁnding a suitable second-order descent direction using only the data and model stored in their own local memory. We let the workers run multiple such iterations locally and communicate the models to the master node only once every few (say L ) iterations. Lo-calNewton is highly practical since it requires only one hyperparameter, the number L of local iterations. We use novel matrix concentration based techniques to obtain theoretical guarantees for Lo-calNewton, and we validate them with detailed empirical evaluation. To enhance practicability, we devise an adaptive scheme to choose L , and we show that this reduces the number of local iterations in worker machines between two model syn-chronizations as the training proceeds, successively reﬁning the model quality at the master. Via extensive experiments using several real-world datasets with AWS Lambda workers and an AWS EC2 master, we show that LocalNewton requires fewer than 60% of the communication rounds (between master and workers) and less than 40% of the end-to-end running time, compared to state-of-the-art algorithms, to reach the same training loss.
Implementation of Green IoT using Intelligent Energy Controlling System

: This paper studies about hardware implementation of green IoT network using an intelligent energy controlling system. The proposed IoT system focuses on energy reduction techniques at the hardware level. Process scheduling, sleep modes, data volume reduction, etc. are used for energy controlling purposes. Using energy controlling techniques, can decrease the energy consumption of the IoT system and increase the efficiency of the IoT system. It is useful for green IoT implementation at the hardware level.
An Analysis Of Inter-Device Transmission In Wireless Connections

- It is anticipated that communication between two or more computing devices (Inter-Device) would piece together an important part of any forthcoming wireless link by way of its assurances in providing extremely low latency on behalf of messaging amongst operators. Such innovative approach would possibly function in a spectrum that is either certified or prohibited. Inter Device linkage therefore emerges as a unique addition to the old-fashioned cell phone messaging architype, whose underlying merits are nonetheless, supplemented by many practical and commercial concerns that are essential to a prompt resolution, in advance of assimilating it into a cellular connection. The main aim of this paper is to ascertain some core features of inter device links together with its procedural set-ups, design, practical features and the extent of any other active study. Research papers, Journals, Internet Sites, and books were used to organise the subject's relevant content. The analysis conducted by this study indicates that momentary overview of (ID) communication has been offered above in relations to its functionalities, design and the key technical experiments to its execution.
Biallelic ADPRHL2mutations in complex neuropathy affect ADP ribosylation and DNA damage response

ADP ribosylation is a reversible posttranslational modification mediated by poly(ADP-ribose)transferases (e.g., PARP1) and (ADPribosyl)hydrolases (e.g., ARH3 and PARG), ensuring synthesis and removal of mono-ADP-ribose or poly-ADP-ribose chains on protein substrates. Dysregulation of ADP ribosylation signaling has been associated with several neurodegenerative diseases, including Parkinson’s disease, amyotrophic lateral sclerosis, and Huntington’s disease. Recessive ADPRHL2/ARH3 mutations are described to cause a stress-induced epileptic ataxia syndrome with developmental delay and axonal neuropathy (CONDSIAS). Here, we present two families with a neuropathy predominant disorder and homozygous mutations in ADPRHL2. We characterized a novel C26F mutation, demonstrating protein instability and reduced protein function. Characterization of the recurrent V335G mutant demonstrated mild loss of expression with retained enzymatic activity. Although the V335G mutation retains its mitochondrial localization, it has altered cytosolic/nuclear localization. This minimally affects basal ADP ribosylation but results in elevated nuclear ADP ribosylation during stress, demonstrating the vital role of ADP ribosylation reversal by ARH3 in DNA damage control.
Optimal Defined Contribution Pension Plans: One-Size Does Not Fit All

Since Bitcoin’s introduction in 2009, interest in cryptocurrencies has soared. One manifestation of this interest has been the explosion of newly created coins and tokens. In this paper, we analyze the dynamics of this burgeoning industry. We consider both cryptocurrency coins and tokens. The paper examines the dynamics of coin and token creation, competition and destruction in the cryptocurrency industry. In order to conduct the analysis, we develop a methodology to identify peaks in prices and trade volume, as well as when coins and tokens are abandoned and subsequently “resurrected”. We also study trading activity. Our data spans nearly five years: there are 1 082 coins and 725 tokens in the data. While there are some similarities between coins and tokens regarding dynamics, there are some striking differences as well. Overall, we find that 44% of publicly-traded coins are abandoned, at least temporarily. 71% of abandoned coins are later resurrected, leaving 18% of coins to fail permanently. Tokens experience abandonment less frequently, with only 7% abandonment and 5% permanent token abandonment at the end of the data. Further, in the case of tokens, the correlation between creation (new entrants) and trade volume is very high (0.71) while the same correlation is virtually zero for coins. Additionally, in the case of tokens, the correlation between abandonment and trade volume is relatively high (0.35) while the same correlation is much smaller (0.07) for coins. We provide some possible explanations for these trends. We then examine the effect that the bursting of the Bitcoin bubble in December 2017 had on the dynamics in the industry. Unlike the end of the 2013 bubble, some alternative cryptocurrencies continue to flourish after the bursting of this bubble. We gratefully
Analysis of 5G Communication using V-BLAST Technique

The mobile communication systems with data rates farther than 1gbps has dramatically increased in recent bits. New technologies are employed to help the performance of 5G MIMO systems. 5G MIMO systems with multiple antenna fundamentals at the transmitter side and receiver side is the promising technology and future for the 5G wireless systems. The recipes that can be applied to MIMO-OFDM systems are V-BLAST and STBC. Space time processing falls into data rate maximization and diversity gain. In this paper we will compare BER of V-BLAST and STBC using BPSK modulation in Matlab performance of 2016b