A cross-cultural analysis of ridesharing intentions and compliance with COVID-19 health guidelines: The roles of social trust, fear of COVID-19, and trust-in-God

Ridesharing services such as Uber and Lyft have been substantially affected by the ongoing COVID-19 pandemic. Drawing on social capital theory, the current research investigates how social trust relates to three types of trust in compliance with COVID-19 guidelines and consumers\u27 ridesharing intentions. Analyzing data from two economically and culturally distinct countries, the results suggest that social trust positively affects trust in platform companies\u27 compliance with COVID-19 guidelines (TPC), but not (or to a lesser extent) trust in drivers\u27 (TDC) and other riders (TRC) compliance with COVID-19 guidelines in both the United States and Bangladesh. Importantly, TPC, TDC, and TRC are positively related with consumers\u27 ridesharing intentions in the United States but not in Bangladesh. Furthermore, the analysis reveals two counterintuitive moderating effects of fear of COVID-19 and trust in God. The results provide important insights on factors affecting the ridesharing industry in the context of the COVID-19 pandemic, and they emphasize the importance of considering cultural context in understanding consumers’ intentions to engage in the sharing economy

A review on deep-learning-based cyberbullying detection

Bullying is described as an undesirable behavior by others that harms an individual physically, mentally, or socially. Cyberbullying is a virtual form (e.g., textual or image) of bullying or harassment, also known as online bullying. Cyberbullying detection is a pressing need in today’s world, as the prevalence of cyberbullying is continually growing, resulting in mental health issues. Conventional machine learning models were previously used to identify cyberbullying. However, current research demonstrates that deep learning surpasses traditional machine learning algorithms in identifying cyberbullying for several reasons, including handling extensive data, efficiently classifying text and images, extracting features automatically through hidden layers, and many others. This paper reviews the existing surveys and identifies the gaps in those studies. We also present a deep-learning-based defense ecosystem for cyberbullying detection, including data representation techniques and different deep-learning-based models and frameworks. We have critically analyzed the existing DL-based cyberbullying detection techniques and identified their significant contributions and the future research directions they have presented. We have also summarized the datasets being used, including the DL architecture being used and the tasks that are accomplished for each dataset. Finally, several challenges faced by the existing researchers and the open issues to be addressed in the future have been presented

MasonTigers@LT-EDI-2024: An Ensemble Approach Towards Detecting Homophobia and Transphobia in Social Media Comments

In this paper, we describe our approaches and results for Task 2 of the LT-EDI 2024 Workshop, aimed at detecting homophobia and/or transphobia across ten languages. Our methodologies include monolingual transformers and ensemble methods, capitalizing on the strengths of each to enhance the performance of the models. The ensemble models worked well, placing our team, MasonTigers, in the top five for eight of the ten languages, as measured by the macro F1 score. Our work emphasizes the efficacy of ensemble methods in multilingual scenarios, addressing the complexities of language-specific tasks

MasonPerplexity at ClimateActivism 2024: Integrating Advanced Ensemble Techniques and Data Augmentation for Climate Activism Stance and Hate Event Identification

The task of identifying public opinions on social media, particularly regarding climate activism and the detection of hate events, has emerged as a critical area of research in our rapidly changing world. With a growing number of people voicing either to support or oppose to climate-related issues - understanding these diverse viewpoints has become increasingly vital. Our team, MasonPerplexity, participates in a significant research initiative focused on this subject. We extensively test various models and methods, discovering that our most effective results are achieved through ensemble modeling, enhanced by data augmentation techniques like back-translation. In the specific components of this research task, our team achieved notable positions, ranking 5th, 1st, and 6th in the respective sub-tasks, thereby illustrating the effectiveness of our approach in this important field of study

Analyses of variability, euclidean clustering and principal components for genetic diversity of eight Tossa Jute (Corchorus olitorius L.) genotypes

An investigation was done to assess the genetic variability, character associations, and genetic diversity of eight jute genotypes for seven morphological traits in a randomised complete block design at Bangladesh Jute Research Institute during 15 March, 2018 to 31 December, 2019. Analyses results revealed significant differences (P<0.01) among all genotypes for studied traits indicating the presence of variability. All the lines performed better than one control (JRO-524), and the line (O-0412-9-4) provided good results for desired traits than all controls. Jute fibre yield showed the highest broad sense heritability (98.54%). The studied jute morphological traits i.e. Plant population, the plant height, green weight, dry fibre yield and dry stick yield gave high heritability along with high genotypic and phenotypic variances, genetic advances in percent of the mean, highly significant and positive correlations. It indicates the possibility of crop improvement through phenotypic selection and maximum genetic gain, simultaneously at the genotypic-phenotypic level. Clustering analysis grouped all genotypes into three distinct clusters. The cluster II showed the highest mean values for all traits followed by cluster I and III. The first two principal components with higher Eigen values (>1.0) accounted for 90.88% of the total variation in the principal component analysis. PCA and cluster analyses indicated that the advanced breeding line O-0412-9-4 made its individual cluster II with higher inter-cluster distance and higher fibre yield (3.12 t ha-1). The investigation was done to select the genotype(s) with good fibre yield and distinct features in respect of developing high yielding Tossa jute variety for cultivation in the farmers’ field. This genotype O-0412-9-4 was selected based on higher plant height, base diameter, fibre yield content. It will be developed as a high yielding variety considering its’ higher genetic variability, heritability, genetic advance, significant associations for desirable characters

The Volatility of Dhaka Stock Exchange (DSE) Returns: Evidence and Implications

Abstract The main focus of the study is on detecting the pattern and reasons behind the volatility of the monthly stock returns of the DSE and to search the possible solutions thereto. The data set consists of monthly DSE General Index (DSE-GEN

Crushing Performances of Axially Compressed Woven Kenaf Fiber Reinforced Cylindrical Composites

This paper presents experimental investigations on the crushing performances of axially compressed woven kenaf fibre reinforced cylindrical composites. Based on the literature survey, there are tremendous amount of work are available on the crushing performances regardless whether the composite contained synthetic or natural fibers. However, lack number of work found in discussing the crushing capability for the composite tubes fabricated using woven kenaf mat reinforced composites. Kenaf fibre in the form of yarn is weaved into a woven mat before it is submerged into a resin bath prior the mats are shaped to form a cylindrical tube. There are two important parameters are used such as number of layers and fiber orientations. The composite tubes are then quasi-statically compressed to obtain the force-displacement curves. Energy absorption capability and other crashworthiness parameters are calculated and discussed in term of number of layers and fiber orientations. According to the results, it is found that both number of layer and fiber orientations played an important role in an elastic region or the first region. On the other hand, in the second stage, it is insignificantly affected the plateau stage where the curves seemed not much different

Numerical Simulation in Transient Flow of Non-Newtonian Fluid in Nozzles

The rheological complexities of non-Newtonian fluids can lead to a variety of difficulties including most importantly changes in viscosity during packaging process. In order to give more understanding in this phenomena, the effect of temperature to the viscosity of chili sauce during packaging is investigated. This paper also presents the influence of three different shape of nozzles to the chili sauce flow behavior during filling time. A transient simulation has been conduct in this work using computational fluid dynamics (CFD) ANSYS CFX 15.0. It was found that viscosity is inversely proportional with temperature drop and time. The filling time also improved when using bigger conical angle of the nozzle. The results indicate the increased in production of the chilli sauce and improve packaging process

Identification and characterization of antibacterial compound(s) of cockroaches (Periplaneta americana)

Infectious diseases remain a significant threat to human health, contributing to more than 17 million deaths, annually. With the worsening trends of drug resistance, there is a need for newer and more powerful antimicrobial agents. We hypothesized that animals living in polluted environments are potential source of antimicrobials. Under polluted milieus, organisms such as cockroaches encounter different types of microbes, including superbugs. Such creatures survive the onslaught of superbugs and are able to ward off disease by producing antimicrobial substances. Here, we characterized antibacterial properties in extracts of various body organs of cockroaches (Periplaneta americana) and showed potent antibacterial activity in crude brain extract against methicillin-resistant Staphylococcus aureus and neuropathogenic E. coli K1. The size-exclusion spin columns revealed that the active compound(s) are less than 10 kDa in molecular mass. Using cytotoxicity assays, it was observed that pre-treatment of bacteria with lysates inhibited bacteria-mediated host cell cytotoxicity. Using spectra obtained with LC-MS on Agilent 1290 infinity liquid chromatograph, coupled with an Agilent 6460 triple quadruple mass spectrometer, tissues lysates were analyzed. Among hundreds of compounds, only a few homologous compounds were identified that contained isoquinoline group, chromene derivatives, thiazine groups, imidazoles, pyrrole containing analogs, sulfonamides, furanones, flavanones, and known to possess broad-spectrum antimicrobial properties, and possess anti-inflammatory, anti-tumour, and analgesic properties. Further identification, characterization and functional studies using individual compounds can act as a breakthrough in developing novel therapeutics against various pathogens including superbugs

Understanding the retinal basis of vision across species

The vertebrate retina first evolved some 500 million years ago in ancestral marine chordates. Since then, the eyes of different species have been tuned to best support their unique visuoecological lifestyles. Visual specializations in eye designs, large-scale inhomogeneities across the retinal surface and local circuit motifs mean that all species' retinas are unique. Computational theories, such as the efficient coding hypothesis, have come a long way towards an explanation of the basic features of retinal organization and function; however, they cannot explain the full extent of retinal diversity within and across species. To build a truly general understanding of vertebrate vision and the retina's computational purpose, it is therefore important to more quantitatively relate different species' retinal functions to their specific natural environments and behavioural requirements. Ultimately, the goal of such efforts should be to build up to a more general theory of vision