Miracle-dz/UniFAR-FTUs huggingface dataset:
ANALYSIS OF GAMIFICATION FOR TRAINER PERFORMANCE USING MDA FRAMEWORK AND ARCS MODEL

In the current era of knowledge-based technology development, human resources are an essential and valuable asset for the company, so it is necessary to manage them properly and not cause a decrease in productivity. Gamification has been widely used to increase user motivation and performance in various fields, such as education and health. The latest trend is the application of “gamification of work,” which aims to incorporate game design elements into the workplace to increase employee productivity and work motivation. This study will analyze problems related to the absence of a standard trainer rating system, making it difficult for managers to find trainer profiles that match the training to be held. The gamification method combines the MDA framework and the ARCS motivation model to analyze relevant game elements to improve coach performance and assist administrators in assigning training to coaches according to the criteria. The analysis in this study mapping the Mechanics–Dynamics–Aesthetics of the MDA framework with twelve ARCS (Attention, Relevance, Confidence, Satisfaction) subcategories. The results obtained from the relevant mechanics game elements are Achievements (Badges, Rewards), Points (Score), Leaderboard, Level System, Progress Bar, Mission (Task), Tutorial, Feedback, and Chat.
Experimental, surface and computational studies on nicotinic hydroxamic acid as an e�cient and ecofriendly chelating corrosion inhibitor in the gas and oil industry

In the present work, the nicotinic hydroxamic acid (NHA) was first presented as a more effective corrosion resistance in 1 M HCl. The reason for the selection of 1 M HCl solution is that 1 M HCl solution was used in the acid pickling and acid-cleaning processes. During these processes, the mild steel corroded. The carbonyl and the hydroxyl groups of the selected inhibitor molecule are mainly responsible for the formation of a stable five-membered chelate complex with a metal cation. Its inhibition characteristics were first researched by the electrochemical, surface morphology and quantum chemical methods. The density functional theory (DFT) with the 6−31G (d, p) basis sets w ere used to analyse the theoretical characteristics of inhibition for NHA. The corrosion prevention activity was utilized on the steel in 1 M HCl using a variety of electrochemical approaches, including potentiodynamic polarization measurements and EIS. In 1 M HCl solution, the maximum inhibition efficiency of 92.75% was achieved for 200 ppm concentration. The existence of multiple double bonds, as well as numerous oxygen atoms of carbonyl and hydroxyl groups of the phytochemicals, is primarily responsible for its superior anti-corrosive properties.
'I Am not Safe at My Home' Causes and Effects of Intimate Partner Violence during COVID-19 (preprint)

Cases of intimate partner violence increased manifold across the world during COVID-19. Researchers have been trying to find out indigenous factors leading to such behaviors, especially among men. Using the lens of the exosystem factor model of ecological theory, we designed the current study to identify the socioeconomic factors in deciding on the intensity of intimate partner violence and its subsequent impact on the psychological and physical wellbeing of women. In this regard, financial autonomy and asset ownership status of women, as well as financial issues and drug abuse among men, were studied as major factors. The study also investigated the moderating role of the asset ownership status of women. A multistage cluster sampling technique was used to collect data from 1516 females in three waves through trained enumerators. We analyzed the moderated mediation model using the structural equation modeling (SEM) technique in AMOS version 26. Results indicated that financial autonomy and asset ownership status of women are negatively related to intimate partner violence and positively related to the psychological and physical wellbeing of women. Similarly, financial issues and drug abuse among men were found positively related to intimate partner violence and negatively related to the psychological and physical wellbeing of women. The interaction effect of the asset ownership status of women was also significant. Overall, significant moderated mediation was found. The results have several implications for various stakeholders including society, policymakers, and researchers. The study has extended the validity of the exosystem factor model of ecological theory and significantly contributed to the literature on intimate partner violence. Especially the moderating role of the asset ownership status of women based on their inherited assets was a significant contribution, especially in the context of the recent enforcement of “Women’s Property Rights Act 2021” by Pakistan.
squalens partially tailors its molecular responses to the composition of solid wood

White-rot fungi, such as Dichomitus squalens , degrade all wood components and inhabit mixed-wood forests containing both soft-and hardwood species. In this study, we evaluated how D. squalens responded to the compositional differences in soft-wood [guaiacyl (G) lignin and higher mannan content] and hardwood [syringyl/guaiacyl (S/G) lignin and higher xylan content] using semi-natural solid cultures. Spruce (softwood) and birch (hardwood) sticks were degraded by D. squalens as measured by oxidation of the lignins using 2D-NMR. The fungal response as measured by transcriptomics, proteomics and enzyme activities showed a partial tailoring to wood composition. Mannanolytic transcripts and proteins were more abundant in spruce cultures, while a proportionally higher xylanolytic activity was detected in birch cultures. Both wood types induced manganese peroxidases to a much higher level than laccases, but higher transcript and protein levels of the manganese peroxidases were observed on the G-lignin rich spruce. Overall, the molecular responses demonstrated a stronger adaptation to the spruce rather than birch composition, possibly because D. squalens is mainly found degrading softwoods in nature, which supports the ability of the solid wood cultures to re ﬂ ect the natural environment.
Salmonella typhimurium induces intestinal in�ammatory response through activation of Cav-1/Akt/IKK α /NF-κ B signaling pathway

Salmonella, a pathogenic gram-negative bacterium, has been reported to cause intestinal in�ammatory response, which is found in both humans and animals. However, the underlying mechanism is not quite clear. To this end, we used Salmonella typhimurium (ST)-infected mice or intestinal epithelioid cell line 6 (IEC-6 cells) as a model to explore the roles of ST in reducing in�ammatory response and elucidate the potential mechanisms. In in vivo experiments, mice were given ST with different concentrations (2.5×10 6 cfu/mL, 2.5×10 7 cfu/mL and 2.5×10 8 cfu/mL). The in�ammatory markers in the serum were measured and the changes of small intestinal structures were observed. Differentially expressed proteins in the jejunum were screened using TMT-based quantitative proteomic analysis, and veri�ed using real-time quantitative PCR (qPCR) and western blotting. In in vitro experiments, IEC-6 cells were pretreated with particular inhibitor for 24 h and then infected with ST (1×10 3 cfu/mL) for 12 h. The lactic dehydrogenase (LDH), C-reactive protein (CRP), tumor necrosis factor-α (TNF-α ), interleukin-8 (IL-8) and monocyte chemotactic protein-1 (MCP-1) levels in the supernatants were measured by enzyme-linked immunosorbent assay (ELISA) while the protein expression of caveolin-1 (Cav-1), protein kinase B (Akt), inhibitor kappa B kinase α (IKK α ) and nuclear factor-kappaB (NF-κ B) p65 were measured by western blotting. ST promoted the production of serum in�ammatory markers and the disruption of duodenal and jejunal structures in a dose-dependent manner over a speci�c period of time. Proteomic analysis showed that ST-induced intestinal in�ammatory response was associated with the expression of Cav, Akt, IKK and NF-κ B. In addition, we further con�rmed that the activation of Cav-1/Akt/IKK α /NF-κ B signaling pathway played a critical role in ST infection prompting the production of in�ammatory markers and causing in�ammatory response in IEC-6 cells. Taken together, our �nding revealed that ST could induce intestinal in�ammatory response through activating the Cav-1/Akt/IKK α /NF-κ B signaling pathway.
MICROSERVICE ARCHITECTURE DESIGN: PROPOSED for E-OFFICE APPLICATION

Analysis and design of e-office application on ministry health of Republic of Indonesia based on microservice architecture. The system is converting from monolithic architecture into microservice architecture by using domain driven design framework to breaking the domain business of the system. Microservice architecture is an important part to agile, resilience, and high-availability. By improvement the feature and the high intention to use to the system by regulation of e-government of Republic of Indonesia at Ministry bureaucracy. By using the Microservice Architecture will improve the productivity of employee, increase the public services, adaptable in current condition of pandemic covid-19 cases in Indonesia. © 2022 Little Lion Scientific
AUTOMATION OF INCIDENT RESPONSE AND IT TICKET MANAGEMENT BY ML AND NLP MECHANISMS

In today’s digital world, Ticket Management Systems are widely utilized in various businesses and organizations since they are essential for efficiently resolving client requests and difficulties. Moreover, in real-world application contexts (e.g., technology support platforms and defect detection systems), properly labeling new requests is essential to improving ticket handling quality, grade and productivity. This research aims to discover the factors affecting customers’ online ticket purchasing behaviors and proposes an effective technique for systematic ticket categorization that effectively clusters and labels. Information technology (IT) tickets quickly using Machine Learning and Natural Language Processing techniques. The framework’s performance in numerous ticket categorization jobs has been indicated by experimental results based on a specific usage situation that involves data from ticket mining the ServiceNow platform and filtering a vast dataset, among other things. To develop a Machine Learning model that significantly predicts an incident resolution category with supervised ML algorithms. The models’ performance was estimated using various NLP techniques LDA with TF-IDF and 3 Gram, and stop-word removal and lemmatization produced the best results, with a precision of 96.46 percent.
Explorer Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

—Convolutional Neural Networks (CNNs) are extremely computationally demanding, presenting a large barrier to their deployment on resource-constrained devices. Since such systems are where some of their most useful applications lie (e.g. obstacle detection for mobile robots, vision-based medical assistive technology), signiﬁcant bodies of work from both machine learning and systems communities have attempted to provide optimisations that will make CNNs available to edge devices. In this paper we unify the two viewpoints in a Deep Learning Inference Stack and take an across-stack approach by implementing and evaluating the most common neural network compression techniques (weight pruning, channel pruning, and quantisation) and optimising their parallel execution with a range of programming approaches (OpenMP, OpenCL) and hardware architectures (CPU, GPU). We provide comprehensive Pareto curves to instruct trade-offs under constraints of accuracy, execution time, and memory space.
J ENA E CONOMIC R ESEARCH P APERS

In our experiment, a dictator game variant, the reported outcome of a die roll determines the endowment (low/high) in a subsequent dictator game. In one treatment the experimenter is present and no cheating is possible, while in another subjects can enter the result of the roll themselves. Moral self-image is also manipulated in the experiment preceding ours. The aim of this experimental set up is to analyze dynamic aspects of moral behavior. When cheating is possible, substantially more high endowments are claimed and transfers of high-endowed dictators are bigger than when cheating is not possible (mediated by the preceding moral self-image manipulation). The preceding manipulations also have a direct eﬀect on generosity, when subjects have to report the roll of the die truth-fully. Moral balancing appears to be an important factor in individual decision making.
University of Birmingham Long-term (2005–2014) trends in formaldehyde (HCHO) columns across North America as seen by the OMI satellite instrument: Evidence of changing emissions of volatile organic compounds

Satellite observations of formaldehyde (HCHO) columns provide top-down information on emissions of highly reactive volatile organic compounds (VOCs). We examine the long-term trends in HCHO columns observed by the Ozone Monitoring Instrument from 2005 to 2014 across North America. Biogenic isoprene is the dominant source of HCHO, and its emission has a large temperature dependence. After correcting for this dependence, we ﬁ nd a general pattern of increases in much of North America but decreases in the southeastern U.S. Over the Houston-Galveston-Brazoria industrial area, HCHO columns decreased by 2.2% a (cid:1) 1 from 2005 to 2014, consistent with trends in emissions of anthropogenic VOCs. Over the Cold Lake Oil Sands in the southern Alberta in Canada, HCHO columns increased by 3.8% a (cid:1) 1 , consistent with the increase in crude oil production there. HCHO variability in the northwestern U.S. and Midwest could be related to afforestation and corn silage production. Although NO x levels can affect the HCHO yield from isoprene oxidation, we ﬁ nd that decreases in anthropogenic NO x emissions made only a small contribution to the observed HCHO trends.
DETECTING ANOMALIES IN AOA DATA MEASURED FOR INDOOR POSITIONING TO IMPROVE ACCURACY

Ships are made of steel. The space of ship’s environments is generally narrow. In the ship’s environments noises are included in the signal. Accurate indoor positioning technology can contribute to preventing infectious diseases by identifying and locating infected people at an early stage. As a method, this paper makes the Angle of Arrival using Bluetooth 5.1 to locate infected people. The function of Anomaly Detection methods as filters may be used to eliminate outliers in elevation and azimuth angles when measuring the Angle of Arrival. Three different Anomaly Detection methods are evaluated in this paper, they are Generalized Extreme Studentized Deviation, LevelShift, and Persist. As a result, LevelShift shows an improvement by 14% in Root Mean Square Error (RMSE) and Generalized Extreme Studentized Deviation shows by 5%. Persist, however, gets worse by 2%.
Widespread distribution in polar oceans of a 16S rRNA gene Widespread distribution in polar oceans of a 16S rRNA gene sequence with affinity to Nitrosospira-like ammonia-oxidizing sequence with affinity to Nitrosospira-like ammonia-oxidizing bacteria bacteria

We analyzed the phylogenetic compositions of ammonia-oxidizing bacteria of the (cid:1) subclass of Proteobacteria from 42 Southern Ocean samples. We found a Nitrosospira -like 16S rRNA gene sequence in all 20 samples that yielded PCR products (8 of 30 samples from the Ross Sea and 12 of 12 samples from the Palmer Peninsula). We also found this sequence in Arctic Ocean samples, indicating a transpolar, if not global, distribution; however, slight differences between Arctic and Antarctic sequences may be evidence of polar endemism. Most studies of ammonia-oxidizing bacteria (AOB) have focused on bioreactors, soils, freshwater, estuaries, and coastal sediments. Two groups of chemolithotrophic bacteria ( Nitro-somonas and Nitrosospira spp.) with phylogenetic afﬁnity to the (cid:2) subclass of
ON DYNAMIC SHEAR MODULI AND POISSON'S RATIOS OF SOIL DEPOSITS

ABSTRACT From statistical analyses of accumulated data on dynamic characteristics of various soil deposits measured by means of seismic exploration, it has been found that shear moduli for small shear strain level are well correlated with N-values of the standard penetration test, and that their interrelation may be expressed by a simple, approximate Eq. G = 1200N0.8 (tons/sq. meter) regardless of soil types and depths from the ground surface. A few matters related to dynamic Poisson’s ratios of soil deposits are also discussed from a statistical viewpoint.
A SYSTEMATIC REVIEW OF BUSINESS INTELLIGENCE THE SENTIMENTAL ANALYSIS ON THE ONLINE MARKET

Obviously, social networking voices (VoC) for analysts able to perform customer-driven business intelligence (BI) analysis have emerged as quality evidence. However, to the best of the understanding of scholars, there is still a shortage of study that deals with such impressive content sources and deals with different accessible data from the BI science viewpoint (e.g., social media, intellectual property). This analysis has therefore been aimed at evaluating the applicability of social network data in BI research and systematically reviewing the primary research papers in this area. This research contrasts social network data in terms of data quality, processing, updating capability and framework, with other accessible data (e.g. grey literature, public service data), which is decided through a cautious discussion with experts. Then, the research collected 57 papers from the Web of Science (WoS) website centered on social networking, and three questions on details, methodology, and findings have been examined with a view to unraveling the field of analysis. The results are to educate current researchers regarding potential research recommendations, encourage entrants to gain insight into the overall analysis process of social media data, and offer practitioners environmentally friendly approaches to social media analysis.
WHO ARE THE MESSENGERS ON SOCIAL MEDIA THAT THE YOUNG GENERATION TRUST?

Trust in the traditional media has declined. Likewise, social media, which has become an alternative source of information has significantly lost the trust of its users even though it has been an integrated part of social life. In this study, social media position was a medium/tool to disseminating information to users. Then this information is interpreted based on the perceptions of each individual. So what information on social media does the young generation believe? This study aims to answer this question. An online survey was conducted using cluster random sampling. The respondents were 365 young people of social media users living in the area of Greater Jakarta. Research result show that Religious leaders became the most dominant opinion leader compared to other opinion leaders, followed by public officers who have authority being among the most trusted source of information. Information from the outer circle of social media users is more trusted than that from the inner circle. Furthermore, popularity of mass media remains a reliable source of information. The actors behind information proliferation in social media significantly influence perception and trust in the information received by the users.
A FUZZY INFERENCE MODEL FOR DIAGNOSIS OF DIABETES AND LEVEL OF CARE

Diagnosis of diabetes is a complex decision-making process. The creation of diabetes diagnosis models is vital in the decision-making process and requires adequate information for fast detection and treatment. Diabetes is detected from a set of symptoms. The symptoms data are an important reference to diagnose diabetes which are collected and stored in datasets. Diabetes datasets are prone to vagueness and uncertainty. In addition, insufficient information on the diagnosis of diabetes exists and this problem is not addressed in previous research. This research work analyzes a simulated diabetes treatments dataset that were validated by medical expert [1]. A new fuzzy inference model based on Mamdani method is designed to provide interpretable understanding and sufficient information on diabetes diagnosis which is combied with the level of care to support the vagueness, uncertainty, and insufficient information problems.
MACHINE LEARNING-BASED OPTIMAL SEGMENTATION SYSTEM FOR WEB DATA USING GENETIC APPROACH

The rapid emergence of computer technology has led to the storage of vast amounts of information in databases. The increasing popularity of electronic data has also created vast amounts of unlabeled information. The potential of extracting valuable knowledge from such digital data has created the basis for the researchers towards important research areas such as Web engineering, Data Science, Big Data Analytics etc. Web engineering is a process utilized for exploring patterns in large databases. However, finding intrinsic structures in large amounts of data becomes a distinctive challenge to organize them into meaningful groups. Many of the existing clustering algorithms are not appropriately suitable for all kinds of web applications. This prompted the present researchers to develop a machine algorithm that is more applicable and robust in real-time to get technological intelligence especially from web data sources. The authors propose an Optimal Segmentation System using a Machine Learning approach (MLOSS) with twin objectives. Initially, MLOSS performs the pre-processing step on the unstructured and semi-structured web documents to prepare efficient data representation structure for applying either supervised and unsupervised techniques. Later as a part of second objective, the proposed system emphasizes on the segment of the preprocessed web data using clustering techniques with an hybridization of the Genetic Approach, that mimic the biological evaluation process having the self-learning proficiency. To validate the performance results of the proposed framework in numerous orders of magnitude, much experimentation is done and, the results have proven this as claimed.
ADIABATIC LOGIC GATES FOR ULTRA-LOW-POWER OPERATION USING CONTACTLESS CAPACITIVE MEMS

We propose a concept of ultra-low-power logic gates based on flexural capacitive MEMS. Contactless operation avoids reliability issues faced by micro-electromechanical relays and allows for elimination of static losses. Furthermore, capacitive information encoding allows recovery of the invested charges, which makes adiabatic operation possible. This new paradigm is thus expected to be much more energy efficient than any CMOS logics that inherently presents static and dynamic losses. The design of an inverter (NOT) gate based on a complementary architecture of combdrives is detailed. They operate in the unconventional configuration where the initial overlap of the comb fingers is zero for the sake of a minimum usage of energy of the gate. Fabrication of proof-of-concept devices is presented using a silicon-on-insulator technology with 0.5 µm critical dimensions.