Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Generation-based Approaches of Oversampling using Different Sets of Base and Nearest Neighbor’s Instances

—Standard classification algorithms often face a challenge of learning from imbalanced datasets. While several approaches have been employed in addressing this problem, methods that involve oversampling of minority samples remain more widely used in comparison to algorithmic modifications. Most variants of oversampling are derived from Synthetic Minority Oversampling Technique (SMOTE), which involves generation of synthetic minority samples along a point in the feature space between two minority class instances. The main reasons these variants produce different results lies in (1) the samples they use as initial selection / base samples and the nearest neighbors. (2) Variation in how they handle minority noises. Therefore, this paper presented different combinations of base and nearest neighbor’s samples which never used before to monitor their effect in comparison to the standard oversampling techniques. Six methods; three combinations of Only Danger Oversampling (ODO) techniques, and three combinations of Danger Noise Oversampling (DNO) techniques are proposed. The ODO’s and DNO’s methods use different groups of samples as base and nearest neighbors. While the three ODO’s methods do not consider the minority noises, the three DNO’s include the minority noises in both the base and neighbor samples. The performances of the proposed methods are compared to that of several standard oversampling algorithms. We present experimental results demonstrating a significant improvement in the recall metric.
The Use of Surface Electromyography in Biomechanics

This lecture explores the various uses of surface electromyography in the field of biomechanics. Three groups of applications are considered: those involving the activation timing of muscles, the force/EMG signal relationship, and the use of the EMG signal as a fatigue index. Technical considerations for recording the EMG signal with maximal fidelity are reviewed, and a compendium of all known factors that affect the information contained in the EMG signal is presented. Questions are posed to guide the practitioner in the proper use of surface electromyography. Sixteen recommendations are made regarding the proper detection, analysis, and interpretation of the EMG signal and measured force. Sixteen outstanding problems that present the greatest challenges to the advancement of surface electromyography are put forward for consideration. Finally, a plea is made for arriving at an international agreement on procedures commonly used in electromyography and biomechanics.
The effects of organizational trust and empowering leadership on group conflict: psychological safety as a mediator

Purpose In a knowledge-based economy, employees’ perception of psychological safety in their wok unit is critical for group conflict. The purpose of this study is to investigate the mediating role of psychological safety between the predictors (i.e. organizational trust and empowering leadership) and the outcome variable, group conflict. Design/methodology/approach Data was drawn from 633 employees from a global automobile company headquartered in South Korea. Construct validity of the measurement model was examined using a confirmatory factor analysis. The hypothesized model was tested by a structural equation modeling and the bootstrap analysis. Findings Organizational trust and empowering leadership accounted for 68% of the variance in employees’ psychological safety. The three antecedents (i.e. organizational trust, empowering leadership and psychological safety) explained 20% of the variance in group conflicts. Psychological safety significantly and fully mediated the relationship between organizational trust and group conflict and the relationship between empowering leadership and group conflict. Practical implications Human resources and organization development professionals can help employees feel more psychologically safe in an organization by developing empowering leaders and making more trustworthy organizational culture. When employees perceive a high level of psychological safety, they are likely to feel less conflict in their team. Originality/value This study examined the antecedents and consequences of psychological safety of knowledge workers in a non-Western cultural context. Psychological safety played a pivotal role as a mediator. To the best of the authors’ knowledge, this is the first study that empirically found the direct link between organizational trust and psychological safety and the relationship between empowerment leadership and psychological safety.
Drug Repurposing for Rare Orphan Diseases Using Machine Learning Techniques

New drug discovery is a time-consuming and costly process. Several drugs have been in clinical trials for a very long period. Finding a new target for existing medications can be an effective strategy to reduce the lengthy and costly drug development cycle. Drug repurposing (or repositioning) is a cost-effective approach or finding drugs that can treat diseases for which thosemedications are not currently prescribed. Drug repurposing to treat both common and rare diseases is becoming an attractive option because it involves using already approved drugs. Through drug repurposing, we can identify promising drugs for further clinical investigations. This paper presents machine learning techniques for drug repurposing to find existing drugs as an alternate medication for other diseases through drug-drug, drug-genes, drug-enzymes, and drug-targets interactions. We develop a model to find similar drugs that can treat similar diseases. We then use the model to predict potential candidate drugs for rare orphan diseases.
Testing levels of competencies in biological experimentation

Currently, efforts are being made to improve the quality of biology education in Germany and develop tests to assess student achievement. With the introduction of national science education standards in 2005, there has been a growing need for criterion-oriented tests, i.e. tests that assess whether or not a specific level of competency has been reached. Here we present an approach to measuring students levels of competencies in experimentation. In particular, the focus lies on the competencies of forming hypotheses, planning experiments and analysing data. These competencies were selected because they are crucial to experimentation as problem-solving, according to the SDDS model (Klahr 2000), and because they are central to the newly introduced Biology standards. One specific reference point of this study is the international scientific literacy test for PISA 2000. Five levels of competencies were proposed for PISA 2000. Items were mapped onto the levels of competencies by dividing up the maximum total sum score into five segments and by assigning items with a low/high difficulty to a low/high level of competency. The approach chosen in the present study differs, as closed-end test items were developed with response categories that can be directly related to a specific level of competency. Each item could be answered in different ways that are indicative of a particular level of competency. Item development, thus, took into consideration the rich research literature on qualitative differences among levels of competencies in experimentation.
Low-Profile High-Aperture-Efficiency Air-Filled Substrate Integrated Cavity Antenna Array

A cavity antenna array with low-profile and favorable aperture efficiency for Ku-band mobile satellite communication applications (10.9–12.5 GHz) is presented in this letter. Key features are the much reduced loss of the feed network and miniaturized aperture size of the array element, and therefore, the high aperture efficiency of the array. The antenna element operates under an odd mode of a fundamental frequency, miniaturized by about a half compared with the conventional cavity antenna. The waveguide-microstrip (WG-MS) hybrid network is employed for the element feeding. Especially, a corners-shorted patch and stepped-length slot are introduced in the WG-MS transition for better transmission, lowering the loss by about 20% according to simulation. For verification, an antenna array is implemented and tested. The results show aperture efficiency up to 86.1% and a maximum gain of 28.8 dBi in the operation band. Besides, this array achieves a wide bandwidth from 10.5 to 13 GHz (20.8%) based on the standard of voltage standing-wave ratio (VSWR) $< 2$, entirely covering the desired band of 10.9–12.5 GHz.
The “major mea culpa:” Journalistic Discursive Techniques When Professional Norms are Broken

ABSTRACT The “corrections statement” is sufficient for media organizations to address small mistakes. When larger missteps occur, however, more substantive work is needed not only to correct the record, but also to protect the organization’s claim to an authentic journalistic identity. This study analyzes 30 of what it terms “major mea culpa” statements to explore how media organizations talk about their significant professional errors and the tools they use to maintain their journalistic identities when such errors occur. Using content analysis to explore the major themes of journalistic process and journalistic principle, this study concludes that the discursive techniques central to “major mea culpas” seek to assert and affirm journalistic identity when actions may suggest that an organization no longer reflects the ideals of the profession.
Fine-Grained Face Editing via Personalized Spatial-Aware Affine Modulation

Fine-grained face editing, as a special case of image translation task, aims at modifying face attributes according to users’ preference. Although generative adversarial networks (GANs) have achieved great success in general image translation tasks, these models cannot be directly applied in the face editing problem. Ideal face editing is challenging as it has two special requirements – personalization and spatial-awareness. To address these issues, we propose a novel Personalized Spatial-aware Affine Modulation (PSAM) method based on a general GAN structure. The key idea is to modulate the intermediate features in a personalized and spatial-aware manner, which corresponds to the face editing procedure. Specifically, for personalization, we adopt both the face image and the desired attribute as input to generate the modulation tensors. For spatial-aware, we set these tensors to be of the same size as the input image, allowing pixel-wise modulation. Extensive experiments in four fine-grained face editing tasks, i.e., makeup, expression, illumination and aging, demonstrate the effectiveness of the proposed PSAM method. The synthesis results of PSAM can be further boosted by a new transferable training strategy.
CAUSES AND EFFECTS OF POOR COMMUNICATION IN THE CONSTRUCTION INDUSTRY IN THE MENA REGION

The construction industry in the Middle East and North Africa (MENA) faces many challenges throughout the project’s lifecycle; on top of these challenges is poor communication which occasionally results in project failure or at least time and cost overruns. A range of steps and methods must be taken to minimize the causes and effects of poor communication to enhance communication. The main aim of the study is to exploring poor communication in MENA construction industry and defining the causes and effects of poor communication from the perspective of consultants, clients, and contractors in small and medium enterprises in a developed region like MENA. Construction professionals from different project parties were asked to complete a questionnaire listing 32 causes and 21 effects of poor communication identified from the literature. The model was validated by Structural Equation Modelling SEM in terms of convergent and discriminant validities. The results revealed, that out of 54 cause and effect factors of poor communication, only 18 factors were retained. These causes and effects were ranked using the relative importance index RII. Results showed that all causes and effects are highly important, with RII above 0.6. The most important causes of poor communication are lack of communication procedure and training, followed by lack of adequate representation for project stakeholders. However, the least important cause of poor communication is a lack of understanding among the construction parties. Conversely, the most acute effects of poor communication are misinterpretation, followed by conflict among construction parties. However, the least important effect of poor communication is a late response to the disaster. Results and recommendations derived from this study represent the vital need of the MENA construction industry to focus on enhancing the current status of communication. The commitment of all project stakeholders to the drawn recommendations regarding the causes of poor communication will undoubtedly limit or reduce the effects of poor communication. Construction firms looking to improve their performance may benefit from the developed model.
Online instructor scaffolding in enhancing undergraduate students' critical thinking

This study aims to investigate the influence of four types of instructor scaffolding (i.e. Technical, Content, Procedural, and Metacognitive) via an asynchronous online discussion forum on students’ (i) Critical Thinking Engagement (CTE), (ii) Cognitive Performance Test (CPT), and (iii) General Critical Thinking (GCT) test. Students’ perceptions of the intensity of instructor scaffolding as well as their own critical thinking engagement performance conducted during the discussion activities within the conversion of explicit and tacit knowledge processes were also studied. This study employs a mixed methods approach, utilizing the preexperimental, one-group pre-test post-test design with the concurrent triangulation of quantitative and qualitative data that facilitate the comparison and corroboration of results. A sample of 56 final year undergraduate students selected via random cluster sampling from the Faculty of Education and enrolled in the CD-ROM-based Multimedia Development course were the subjects of the study. The dominant type of instructor scaffolding offered was the Metacognitive scaffolding, both at individual and group levels. The findings of this study show that students’ higher levels of critical thinking processes could be influenced by instructor scaffolding, with Metacognitive scaffolding having the most impact on students’ CTE while Content scaffolding had the most impact on students’ CPT, although it was not effective in improving students’ GCT. It was also found that Metacognitive scaffolding benefited the high-ability students while Content scaffolding as well as indirect instructor scaffolding benefited the low-ability students. These high-ability students were also likely to improve their CPT and GCT. Students’ perceptions of the influence and benefits of instructor scaffolding on their critical thinking skills were positive, thus suggesting the types of instructor scaffolding influenced the intensity of the explicit and tacit knowledge conversion processes. When considering the students’ individual different needs, closer investigation through the construction of three decision or prediction pathway models revealed the six most important instructor scaffolding sub-type predictors that could enhance the students’ performance in three critical thinking measures: CTE, CPT, and GCT. The findings of this research have implications on online instructors, online course designers and educational technology practice.
Nickel and sodium phosphate composite with wall putty substantive as energy saving decorating material

Abstract The phosphate containing inorganic mixture has been synthesized and various measurement techniques are used to characterize it. Composite mixtures of this mixture are synthesized with assimilation of wall putty. The differential scanning calorimetry of mixture is studied in two thermal cycles from 298 K to 223 K at 10 K min−1 in normal atmosphere and found endothermic behavior after a cycle. The specific heat capacity (C p) of 4.42% composite mixture is found exhibit lower C p value as compared to wall putty by 20% at 343 K. The C p of wall putty is 4.96 Jg−1K−1 at 300 K while C p of 4.42% and 12.11% composite mixture are 2.70 Jg−1K−1 and 4.00 Jg−1K−1 at 300 K, respectively. This composite mixture could be used in exterior walls of the buildings instead of wall putty alone. So, coating material of 4.42% mixture keeps the buildings cooler than expected.
A Gendered Discourse of Third-generation Chinese Migrants on Diaspora Tourism: Implications to Industry Players in Malaysia

ABSTRACT Diaspora tourism refers to the travel of people in diaspora to their ancestral homelands in search of their roots or to feel connected to their heritage. Whereas most tourists become attached to a destination after repeat visits, diaspora tourism is unique because tourists with immigrant origins often feel connected to the people, culture, and heritage of the destination before actually visiting the place. This study examines inter-gender differences concerning the formation of the intention of third-generation Chinese migrants in Malaysia to participate in diaspora tourism. Leveraging the theory of planned behavior, data were collected from 260 third-generation Chinese migrants. Using the partial least squares structural equation modeling technique, our results emphasize the critical roles of attitude and perceived behavioral control in developing intention. It also shows that females have higher expectations than males when becoming diaspora tourists. These findings provide an essential theoretical platform for new interventions to promote the active participation of diaspora tourism.
Terminology in Low power And Lossy Networks

The documents defines a terminology for discussing routing requirements and solutions for networks referred to as Low power and Lossy Networks (LLN). A LLN is typically composed of many embedded devices with limited power, memory, and processing resources interconnected by a variety of links. There is a wide scope of application areas for LLNs, including industrial monitoring, building automation (HVAC, lighting, access control, fire), connected home, healthcare, environmental monitoring, urban sensor networks, energy management, assets tracking, refrigeration.
Crosstalk between macrophage-derived PGE2 and tumor UHRF1 drives hepatocellular carcinoma progression

Background: Tumor-associated macrophages (TAMs) and dysregulated tumor epigenetics contribute to hepatocellular carcinoma (HCC) progression. However, the mechanistic interactions between TAMs and tumor epigenetics remain poorly understood. Methods: Immunohistochemistry and multiplexed fluorescence staining were performed to evaluate the correlation between TAMs numbers and UHRF1 expression in human HCC tissues. PGE2 neutralizing antibody and COX-2 inhibitor were used to analyze the regulation of TAMs isolated from HCC tissues on UHRF1 expression. Multiple microRNA prediction programs were employed to identify microRNAs that target UHRF1 3'UTR. Luciferase reporter assay was applied to evaluate the regulation of miR-520d on UHRF1 expression. Chromatin immunoprecipitation (ChIP) assays were performed to assess the abundance of H3K9me2 in the KLF6 promoter and DNMT1 in the CSF1 promoter regulated by UHRF1. The functional roles of TAM-mediated oncogenic network in HCC progression were verified by in vitro colony formation assays, in vivo xenograft experiments and analysis of clinical samples. Results: Here, we find that TAMs induce and maintain high levels of HCC UHRF1, an oncogenic epigenetic regulator. Mechanistically, TAM-derived PGE2 stimulates UHRF1 expression by repressing miR-520d that targets the 3'-UTR of UHRF1 mRNA. In consequence, upregulated UHRF1 methylates H3K9 to diminish tumor KLF6 expression, a tumor inhibitory transcriptional factor that directly transcribes miR-520d. PGE2 reduces KLF6 occupancy in the promoter of miR-520d, dampens miR-520d expression, and sustains robust UHRF1 expression. Moreover, UHRF1 promotes CSF1 expression by inducing DNA hypomethylation of the CSF1 promoter and supports TAM accumulation. Conclusions: Capitalizing on studies on HCC cells and tissues, animal models, and clinical information, we reveal a previously unappreciated TAM-mediated oncogenic network via multiple reciprocal enforcing molecular nodes. Targeting this network may be an approach to treat HCC patients.
SARS-CoV-2 Virion Infectivity and Cytokine Production in Primary Human Airway Epithelial Cells

The emergence of new SARS-CoV-2 variants and the replacement of preceding isolates have been observed through B.1. 1.7, B.1. 351, B.1. 617.2, and B.1. 1.529 lineages (corresponding to alpha, beta, delta, and omicron variants of concern (VoC), respectively). However, there is still a lack of biological evidence to which extent those VoC differ from the ancestral lineages. By exploiting human airway epithelial cell (HAEC) cultures, which closely resemble the human airway architecture and physiology, we report distinctive SARS-CoV-2 tropism in different respiratory tissues. In general, SARS-CoV-2 VoC predominantly infect and replicate in HAEC better than the progenitor USA-WA1 isolate or the BavPat1 isolate, which contains the D614G mutation, even though there is little to no difference between variants regarding their infectivity (i.e., virion-per-vRNA copy ratio). We also observe differential tissue-specific innate immunity activation between the upper and lower respiratory tissues in the presence of the virus. Our study provides better comprehension of the behavior of the different VoC in this physiologically relevant ex vivo model.
Improving Intrusion Detection for Imbalanced Network Traffic using Generative Deep Learning

—Network security has become a serious issue since networks are vulnerable and subject to increasing intrusive activities. Therefore, network intrusion detection systems (IDSs) are an essential component to defend against these activities. One of the biggest issues encountered by IDSs is the class imbalance problem which leads to a biased performance by most machine learning models to normal activities (majority class). Several techniques were proposed to overcome the class-imbalance problem such as resampling, cost-sensitive, and en- semble learning techniques. Other issues related to intrusion detection data include mixed data types, and non-Gaussian and multimodal distributions. In this study, we employed a conditional tabular generative adversarial network (CTGAN) model with common machine learning algorithms to construct more effective detection systems while addressing the imbalance issue. CTGAN can generate samples of the minority class during training to make the dataset more balanced. To assess the effectiveness of the proposed IDS, we combined CTGAN with three machine learning algorithms: support vector machine (SVM), K-nearest neighbor (KNN), and decision tree (DT). The imbalanced NSL-KDD dataset was used and several experiments were conducted. The results showed that CTGAN can improve the performance of imbalance learning for intrusion detection with SVM and DT. On the other hand, KNN showed no improvement in the performance since it is less sensitive to the class imbalance problem. Moreover, the results proved that CTGAN can capture the distribution of discrete features better than continuous features.