Miracle-dz/UniFAR-FTUs huggingface dataset:
Introduction of Implementation Of Direct and Indirect Discrimination Rules for Prevention Of Larger Data in Data Mining

Abstract: Data mining is most necessary technology for extracting useful knowledge and valuable data in large collection of information. There having some negative social aspects about data processing such as invasion, potential privacy, and potential discrimination. The latter consist of affair or unequally treating people on the basis of their cast, religion or specific community. Automatic knowledge collection and data processing techniques such as classification rule mining have paved the way to making automated decision, like loan granting or denial, insurance or premium computation etc. If the given data sets having with discriminatory (sensitive) attributes like gender, race, religion, community, etc . For this reason, antidiscrimination techniques including discrimination discovery and prevention are introduce in data processing . Discrimination either direct or indirect . Here ,we tried for solution to prevent discrimination in data processing and will try to bring new techniques applicable for direct and indirect discrimination prevention separately at the same time. We discussed how to clean training data sets and outsourced data sets in such a way that direct/indirect discriminatory decision rules are converted to non discriminatory classification rule. Also we bring new metrics to gauge the utility of planned approaches and compare these approaches. The proposed techniques are effective at removing direct/indirect discrimination biases in the original data sets while preserving data quality.
Plasma Membrane-Derived Liposomes Exhibit Robust Antiviral Activity against HSV-1

Plasma membranes host a plethora of proteins and glycans on their outer surface that are exploited by viruses to enter the cells. In this study, we have utilized this property to limit a viral infection using plasma membrane-derived vesicles. We show that plasma membrane-derived liposomes are prophylactically and therapeutically competent at preventing herpes simplex virus type-1 (HSV-1) infection. Plasma membrane liposomes derived from human corneal epithelial (HCE) cells, which are natural targets of HSV-1 infection, as well as Vero and Chinese hamster ovary (CHO) cells were used in this study. Our study clearly demonstrates that HCE and Vero-derived cellular liposomes, which express the viral entry-specific cell surface protein receptors, exhibit robust antiviral activity especially when compared to CHO-derived liposomes, which lack the relevant HSV-1 entry receptors. Further experimentation of the plasma membrane-derived liposomes with HSV type-2 (HSV-2) and pseudorabies virus yielded similar results, indicating strong potential for the employment of these liposomes to study viral entry mechanisms in a cell free-environment.
Indulgent Consumption Signals Interpersonal Warmth

People who engage in indulgent consumption often are viewed as having poor self-control. In this research, however, eight studies provide converging support that indulgent consumption can have a positive effect: signaling interpersonal warmth. Specifically, consumers who post indulgent (vs. healthy) consumption content on social media are perceived as warmer (Study 1). The effect occurs because consumers believe that indulgent consumption is what people genuinely prefer, so indulgent (vs. healthy) consumption seems more authentic, and authenticity mediates the effect of indulgent consumption on perceived warmth (Studies 2a and 2b). Providing additional support for the authenticity mechanism, the authors show that the positive effect of indulgent (vs. healthy) consumption on perceived warmth is attenuated when the indulgent content is sponsored, which casts doubt on its authenticity (Study 3). Further, sharing sharing indulgent consumption can increase the appeal of a service provider among consumers who are seeking a warm service provider, but this occurs only when the content is not sponsored (Studies 4a and 4b). Finally, the effect of sharing indulgent (vs. healthy) consumption has downstream consequences for audience engagement on Instagram (Studies 5a and 5b). This research sheds light on how to cultivate interpersonal warmth in marketing communication and personal branding.
Preschool Teachers’ Knowledge, Understanding and Practice towards Higher Order Thinking Skills

Malaysian education system is striving to produce a creative, innovative and intelligent generation to face the competition in the global market. Among the skills that are prioritized to produce this generation is Higher Order Thinking Skills (HOTS). All curricula including the Preschool Curriculum have undergone a transformation due to the HOTS agenda. As an effort to inculcate HOTS among children, preschool teachers have the key trust. Therefore, this study was conducted to examine the level of readiness of preschool teachers towards HOTS in terms of knowledge, understanding and implementation. A quantitative approach with survey study design was used in the study. A total of 367 preschool teachers in Malaysia were selected as study respondents through simple random sampling. The instrument used was a questionnaire adapted from another study. The data obtained were analysed descriptively through SPSS Version 26. Descriptive statistics were used to examine the mean score, standard deviation, frequency and percentage. The findings showed that the level of knowledge (mean = 4.08) of preschool teachers about HOTS, the level of understanding (mean = 3.98) of preschool teachers about HOTS and the level of implementation (mean = 3.96) of HOTS in preschool learning and facilitation were at high level. The results of the study proved that preschool teachers have high level of readiness for the implementation of HOTS. This study can increase the positive perception of HOTS among other preschool teachers and encourage them to demonstrate high commitment in implementing HOTS in learning and facilitation.
Developing Tree Mortality Models Using Bayesian Modeling Approach

The forest mortality models developed so far have ignored the effects of spatial correlations and climate, which lead to the substantial bias in the mortality prediction. This study thus developed the tree mortality models for Prince Rupprecht larch (Larix gmelinii subsp. principis-rupprechtii), one of the most important tree species in northern China, by taking those effects into account. In addition to these factors, our models include both the tree—and stand—level variables, the information of which was collated from the temporary sample plots laid out across the larch forests. We applied the Bayesian modeling, which is the novel approach to build the multi-level tree mortality models. We compared the performance of the models constructed through the combination of selected predictor variables and explored their corresponding effects on the individual tree mortality. The models precisely predicted mortality at the three ecological scales (individual, stand, and region). The model at the levels of both the sample plot and stand with different site condition (block) outperformed the other model forms (model at block level alone and fixed effects model), describing significantly larger mortality variations, and accounted for multiple sources of the unobserved heterogeneities. Results showed that the sum of the squared diameter was larger than the estimated diameter, and the mean annual precipitation significantly positively correlated with tree mortality, while the ratio of the diameter to the average of the squared diameter, the stand arithmetic mean diameter, and the mean of the difference of temperature was significantly negatively correlated. Our results will have significant implications in identifying various factors, including climate, that could have large influence on tree mortality and precisely predict tree mortality at different scales.
Spread of West Nile Virus and Usutu Virus in the German Bird Population, 2019–2020

West Nile virus (WNV) and Usutu virus (USUV) are important flaviviruses circulating in Germany. While USUV was first reported more than 10 years ago, WNV has only reached the country in 2018. Wild birds are important amplifying hosts for both viruses. Therefore, we have been monitoring the bird population in different regions of Germany by a previously established network for many years. This report summarizes the results of molecular and/or serological methods of 2345 blood samples from birds of 22 different orders and over 2900 bird carcasses from 2019 and 2020. USUV RNA circulation was found in different regions of Germany, with emphasis on USUV lineages Europe 3 and Africa 3. Increased evidence of USUV lineage Europe 2 was detected in eastern Germany. WNV RNA was found only in birds from the eastern part of the country. The seroprevalence for USUV was between 3.11% and 7.20% in all three regions investigated, whereas the WNV seroprevalence spanned from 14.77% to 16.15% in eastern Germany, with a noticeable tendency for a westward and southward expansion in both years. Thus, wild bird monitoring for WNV and USUV can serve as an early warning system for a human exposure risk.
Technological affordances of e-learning: An analysis of students' perceptions in tertiary ICT education

In this article, we attempt to investigate the affordances of e-learning in supporting tertiary teaching and learning. Using an interpretive qualitative study, we analyzed a total of 46 students from three different programme, namely Chemistry, Physics and Mathematics education through questionnaires and interviews. The findings revealed that students’ views were generally positive towards the technical aspects based on technology and tools used in the e-learning environment, the pedagogical aspects of e-learning approach involved, and the social aspects of e-learning environment. However, while e-learning environment can help students to learn from one another in the class, it requires preparation in terms of technology and tools, collaborative learning tasks, and collaborative learning approach. Thus, this article also offers practical suggestions for implementing teaching and learning with e-learning within a tertiary classroom.
Intelligent Dynamic Test System for Vehicle Engine Based on 5G Internet of Things

With the development of the automobile industry, the improvement of the reliability test level and the intelligent fault diagnosis level of the engine, as the heart component of the automobile and the assembly with the highest failure rate, becomes more and more important. In a context where technology is being upgraded, the development of intelligent automotive engine inspection system based on IoT thinking is set to become the major trend in the future. The objective of this article would be to have better knowledge about smart car engine system in the 5G IoT era. It is also through the study, a dynamic testing and characterization of the engine. The performance of the automobile engine, especially the dynamic performance, is further optimized. In this article, we focus on the PUMAOPEN test system of AVL and the system under test, the state management of the test process, and the intelligent transformation of key components. The results show that: studies and analyses the dynamic working conditions of intelligent vehicles on the Internet of Things, and compares the dynamic working conditions with the steady working conditions from qualitative to quantitative. By analyzing the influence of throttle opening change rate and speed change rate on dynamic performance and engine dynamic torque estimation, the fast sensing and response-ability in the engine testing process is improved. When the engine is accelerated by the experimental method presented in this article, and when the throttle opening is more than 30% and the engine speed varies at 100 and 200 rpm/s, the output value of the torque is higher than the output value of the steady-state torque or has little difference with the output value of the steady-state torque, and tends to be stable. In deceleration performance, the dynamic output torque of the engine is asymmetric. And it will deviate from the steady-state output torque, showing different dynamic response characteristics in different working sections. Throttle delay, overshoot characteristics, mechanical inertia, inflation coefficient, air–fuel ratio, and ignition advance angle when engine speed changes sharply will make engine dynamic characteristics deviate from steady-state characteristics.
Internet use behaviour model for predicting students' performance

Internet technology is vital in education as it is an enabler tool used by students for information exchange, communication and creation of knowledge. However, issues related to Internet use behaviour (IUB) and effects on students' performance are still being debated due to inconsistent results. Thus, the main aim of this paper is to propose a specific IUB classification model to discover comprehensive prediction models on students' performance by using educational data mining (EDM). Data related to the students' CGPA and their internet usage activities were collected from 469 undergraduate students. Primarily, in this study several techniques were ensembled to predict students' performance based on IUB. An EDM approach comprising of clustering, classification, correlation, and regression was used. The base classifiers including decision tree (j48) ensembled with EM clustering technique were exploited to develop a high accuracy of prediction results. At first, the usage of clustering technique was to cluster the dataset into smaller variable and applied classification technique to solve the complexity of the variables. Correlation come across to measure the degree of IUB and students' performance and later regression was applied to produce predictive results. Based on 11 IUB categories, the results indicate that online gaming has a negative significant effect on the students' performance. Additionally, the prediction model revealed a high correlation, which generates good predictions of 92%. The prediction model would enable higher learning institutions to detect as early as possible those students who are at risk. This will then help them in taking timely and proactive measures to improve their performance.
Criteria Selection Using Machine Learning (ML) for Communication Technology Solution of Electrical Distribution Substations

In the future, as populations grow and more end-user applications become available, the current traditional electrical distribution substation will not be able to fully accommodate new applications that may arise. Consequently, there will be numerous difficulties, including network congestion, latency, jitter, and, in the worst-case scenario, network failure, among other things. Thus, the purpose of this study is to assist decision makers in selecting the most appropriate communication technologies for an electrical distribution substation through an examination of the criteria’s in-fluence on the selection process. In this study, nine technical criteria were selected and processed using machine learning (ML) software, RapidMiner, to find the most optimal technical criteria. Several ML techniques were studied, and Naïve Bayes was chosen, as it showed the highest performance among the rest. From this study, the criteria were ranked in order of importance from most important to least important based on the average value obtained from the output. Seven technical criteria were identified as being important and should be evaluated in order to determine the most appropriate communication technology solution for electrical distribution substation as a result of this study.
CFD analysis for mixing performance of different types of household biodigesters

Household biodigesters are self-mixing anaerobic digesters used mostly in rural areas of developing countries as a reliable source of clean cooking energy. For an efficient anaerobic digestion process, the mixing of slurry inside the digester is regarded as one of the most important parameters. In this study, the mixing of slurry in three different designs of household digesters, namely the fixed-dome digester (GGC 2047 model), plug-flow digester and prefabricated plastic digester, are investigated and compared using computational fluid dynamics. A 3D transient simulation is performed using a multiphase volume of fluid (VOF) model in Ansys® Fluent release 16.0. The rheological properties of the feedstock are considered identical for all three digesters. The volume of the plug-flow and prefabricated plastic digesters is designed to be 1 m3 while the volume of the GGC 2047 digester was 6 m3 as the standard size of the household digester. The regions inside the digester where the velocity of slurry is <0.02 m/s are regarded as dead zones and the obtained results were analysed and compared using velocity patterns and dead-zone formation. It is found that the prefabricated plastic digester model has a relatively higher percentage of dead volume (74.6%) and the plug-flow digester has the lowest percentage (54%) of dead volume among digesters that were compared in this study. The study will serve as the basis for designers and researchers to improve the design of household digesters for better mixing performances.
Grafting Modification of Natural Fibres with Cyclodextrin

Over the years, a multiplicity of grafting modification techniques have been studied to combine the adsorption and wettability of natural fibres with the capacity of cyclodextrins (CDs) to form inclusion complexes. The fixation of CDs on fibres is possible using crosslinking agents or reactive derivatives of cyclodextrins. Various crosslinking chemicals are suitable to bind the hydroxyl groups of non-reactive cyclodextrins with those of natural fibres by way of spraying, padding, surface coating, and impregnation. Nano-composite dense polymer film could also be formed to anchor the cyclodextrin on the natural fibre surface by the methods of hydrogen binding or covalent binding in sol-gel. A vinyl monomer such as glycidyl methacrylate was used to form polymer coatings due to the pendant epoxy group coupled with the –OH of cyclodextrin and natural fibres. This review also focused on the derivatives of CDs with the reactive group reacting with the hydroxyl groups of natural fibres.
The species chromatogram, a new graphical method to represent, characterize, and compare the ecological niches of different species

Abstract The ecological niche sensu Hutchinson is defined as the set of environmental conditions allowing a species to grow, maintain, and reproduce. This conception of the niche, which is assimilated to a p‐dimensional hypervolume, with p representing all environmental variables, has been widely applied in ecology. However, displaying the niche hypervolume has proved challenging when more than three environmental dimensions are considered simultaneously. We propose a simple method (implemented in the specieschrom R package) that displays the full multidimensionality of the ecological niche of a species into a two‐dimensional space by means of a graphic we call species chromatogram. This method gives a graphical summary of the niche by representing together abundance gradients with respect to all environmental variables. A chromatogram enables niche optimums and breaths to be rapidly quantified, and when several chromatograms are examined (one per species), rapid comparisons can be made. From our chromatograms, we proposed a procedure that quantifies niche optimum and breadth as well as niche overlapping (index D) and the identification of the most discriminant combination of environmental variables. We apply these analyses on eight planktonic species collected by the Continuous Plankton Recorder (CPR) survey in the North Atlantic Ocean using 10 environmental variables. We display their full multidimensional niches and quantify their niche optimums and breadths along each dimension. We also compare our index D with other indices by means of hypervolume and dynRB R packages. By catching the full complexity of the niche, species chromatograms allow many different niche properties to be rapidly assessed and compared among species from niche optimums and breadths to the identification of the most relevant environmental parameters and the degree of niche overlapping among species. Species chromatograms may be seen as species’ fingerprint and may also allow a better identification of the mechanisms involved in species assembly.
Going Green and Socially Responsible – Textile Industry in Transition to Sustainability and a Circular Economy

The textile industry is faced with many problems today. In addition to having to meet customers’ changing preferences and expectations, who wish to stay abreast of fashion trends and stand out from the crowd, it also needs to make efforts to change its image of one the biggest polluters in the world it has earned due to production processes consuming large amounts of resources that end up as piles of household waste. The circular economy (CE) model to reduce the environmental footprint seems to be the right solution for textile companies implementing sustainable development strategies. This paper discusses the principles of the CE model and makes an attempt at explaining how textile companies transition to it. It is based on the analysis of 34 textile companies sampled from among the members of the European Circular Economy Stakeholder Platform, which was conducted using a special analytical checklist compiled from the ReSOLVE and BECE frameworks. Because of the proportions and degree of integration between strategic and operational practices they used to achieve circularity, they were divided into integrated, hybrid, and selective organisations.
Ties for the phases: tie formation and educator life phases in urban fringe and rural schools

ABSTRACT Friendships and close relationships within organisations and schools are integral for developing trust, engagement, and a sense of community. That said, few studies exclusively look at tie formation in friendship networks in K-12 contexts. In this study, we explore the relationship between Day and Gu’s teacher life phases and the formation of friendship ties in four schools—two elementary and two high schools—in urban fringe and rural settings. Using exponential random graph models (ERGMs), we found that across contexts there were some life phases during which educators were more likely to form friendship ties with others in the same life phase. Also, there were notable differences in the factors that contributed to friendship ties and in the odds of friendship tie formation in the elementary versus high schools. The findings have implications for those interested in supporting professional capital-building among teachers as well as those looking to establish conditions necessary to nurture and sustain teacher resilience.
The mighty abstract: An overlooked element of peer review

At QSW, we have an established record of providing readers with insights into the peerreview process (Morriss, 2019; Piedra, 2019, 2020; Piedra and Lanesskog, 2022; Ruckdeschel and Shaw, 2013; Staller, 2007, 2012, 2017, 2019a), and have offered advice on what generates a successful submission (Staller, 2015, 2019b, 2022; Staller and Krumer-Nevo, 2013). Here, I continue in this tradition of seeking to demystify the peerreview process while imparting suggestions for success.