Denigrate Comment Detection in Low-Resource Hindi Language Using Attention-Based Residual Networks

Cyberspace has been recognized as a conducive environment for use of various hostile, direct, and indirect behavioural tactics to target individuals or groups. Denigration is one of the most frequently used cyberbullying ploys to actively damage, humiliate, and disparage the online reputation of target by sending, posting, or publishing cruel rumours, gossip, and untrue statements. Previous pertinent studies report detecting profane, vulgar, and offensive words primarily in the English language. This research puts forward a model to detect online denigration bullying in low-resource Hindi language using attention residual networks. The proposed model Hindi Denigrate Comment–Attention Residual Network (HDC-ARN) intends to uncover defamatory posts (denigrate comments) written in Hindi language which stake and vilify a person or an entity in public. Data with 942 denigrate comments and 1499 non-denigrate comments is scraped using certain hashtags from two recent trending events in India: Tablighi Jamaat spiked Covid-19 (April 2020, Event 1) and Sushant Singh Rajput Death (June 2020: Event 2). Only text-based features, that is, the actual content of the post, are considered. The pre-trained word embedding for Hindi language from fastText is used. The model has three ResNet blocks with an attention layer that generates a post vector for a single input, which is passed through a sigmoid activation function to get the final output as either denigrate (positive class) or non-denigrate (negative class). An F-1 score of 0.642 is achieved on the dataset.

Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale

The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods. Additionally, there are few examples of broad bioinformatics workflows that can process metagenome, metatranscriptome, metaproteome and metabolomic data at scale, and no central hub that allows processing, or provides varied omics data that are findable, accessible, interoperable and reusable (FAIR). Here, we review some of the challenges that exist in analyzing omics data within the microbiome research sphere, and provide context on how the National Microbiome Data Collaborative has adopted a standardized and open access approach to address such challenges.

Trajectories of frailty with aging: Coordinated analysis of five longitudinal studies

Background and Objectives There is an urgent need to better understand frailty and it’s predisposing factors. Although numerous cross-sectional studies have identified various risk and protective factors of frailty, there is a limited understanding of longitudinal frailty progression. Furthermore, discrepancies in the methodologies of these studies hamper comparability of results. Here, we use a coordinated analytical approach in five independent cohorts to evaluate longitudinal trajectories of frailty and the effect of three previously identified critical risk factors: sex, age, and education. Research Design and Methods We derived a frailty index (FI) for five cohorts based on the accumulation of deficits approach. Four linear and quadratic growth curve models were fit in each cohort independently. Models were adjusted for sex/gender, age, years of education, and a sex/gender-by-age interaction term. Results Models describing linear progression of frailty best fit the data. Annual increases in FI ranged from 0.002 in the InCHIANTI cohort to 0.009 in the LASA. Women had consistently higher levels of frailty than men in all cohorts, ranging from an increase in the mean FI in women from 0.014 in the HRS cohort to 0.046 in the LASA cohort. However, the associations between sex/gender and rate of frailty progression were mixed. There was significant heterogeneity in within-person trajectories of frailty about the mean curves. Discussion and Implications Our findings of linear longitudinal increases in frailty highlight important avenues for future research. Specifically, we encourage further research to identify potential effect modifiers or groups that would benefit from targeted or personalized interventions.

Preimmunization correlates of protection shared across malaria vaccine trials in adults

Identifying preimmunization biological characteristics that promote an effective vaccine response offers opportunities for illuminating the critical immunological mechanisms that confer vaccine-induced protection, for developing adjuvant strategies, and for tailoring vaccination regimens to individuals or groups. In the context of malaria vaccine research, studying preimmunization correlates of protection can help address the need for a widely effective malaria vaccine, which remains elusive. In this study, common preimmunization correlates of protection were identified using transcriptomic data from four independent, heterogeneous malaria vaccine trials in adults. Systems-based analyses showed that a moderately elevated inflammatory state prior to immunization was associated with protection against malaria challenge. Functional profiling of protection-associated genes revealed the importance of several inflammatory pathways, including TLR signaling. These findings, which echo previous studies that associated enhanced preimmunization inflammation with protection, illuminate common baseline characteristics that set the stage for an effective vaccine response across diverse malaria vaccine strategies in adults.

Potential Pitfalls of Using Fractional Anisotropy, Axial Diffusivity, and Radial Diffusivity as Biomarkers of Cerebral White Matter Microstructure

Fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) are commonly used as MRI biomarkers of white matter microstructure in diffusion MRI studies of neurodevelopment, brain aging, and neurologic injury/disease. Some of the more frequent practices include performing voxel-wise or region-based analyses of these measures to cross-sectionally compare individuals or groups, longitudinally assess individuals or groups, and/or correlate with demographic, behavioral or clinical variables. However, it is now widely recognized that the majority of cerebral white matter voxels contain multiple fiber populations with different trajectories, which renders these metrics highly sensitive to the relative volume fractions of the various fiber populations, the microstructural integrity of each constituent fiber population, and the interaction between these factors. Many diffusion imaging experts are aware of these limitations and now generally avoid using FA, AD or RD (at least in isolation) to draw strong reverse inferences about white matter microstructure, but based on the continued application and interpretation of these metrics in the broader biomedical/neuroscience literature, it appears that this has perhaps not yet become common knowledge among diffusion imaging end-users. Therefore, this paper will briefly discuss the complex biophysical underpinnings of these measures in the context of crossing fibers, provide some intuitive “thought experiments” to highlight how conventional interpretations can lead to incorrect conclusions, and suggest that future studies refrain from using (over-interpreting) FA, AD, and RD values as standalone biomarkers of cerebral white matter microstructure.

The Influence of Decision Making on Social Inclusion of Persons with Disabilities: A Case Study of Khyber Pakhtunkhwa

Decision making is an essentially social process adopted by individuals or groups to identify and choose the best choice among several alternatives. Decision-making choices are influenced by the preferences, values, and beliefs of the individuals or groups involved in the decision-making process. This study was conducted to analyze the social inclusion of Persons with Disabilities (PWDs) in the context of their participation in decision making. The study area consisted of 8028 PWDs registered with the government of Pakistan, from which a sample of 488 PWDs was selected through a multistage stratified random sampling technique. These PWDs included physically disabled, blind, crippled, and deaf persons; however, the data were collected from those who were able to be interviewed. Chi-square and Kendall’s Tau-b tests were used to determine the strength, level, and direction of association among variables. At the multivariate level, the study found a spurious relation between social inclusion and participation in decision making when controlling for gender, monthly family income, and level of disability of the PWDs. The results highlighted that participation in decision making improved the social inclusion of male and moderately disabled PWDs more positively. However, participation in decision making was a universal feature explaining the social inclusion of PWDs irrespective of their monthly family income. The logistic regression model explained that the social inclusion of PWDs was more likely to occur when PWDs were married, had high monthly family income (PKR 16,500 and above), belonged to a joint family, and actively participated in decision making. The study recommends that ensuring the participation of PWDs in decision making in family, community, school, and other relevant institutions ultimately enhances their social inclusion.

An Empirical Analysis of the Common Factors Influencing the Sharing and Green Economies

The digital revolution, driven and accelerated by the current pandemic, involves changes to known business models. The innovative model of the sharing economy can be a real and sustainable solution for long-term green economic development. The aim of our research was to determine the common factors of the sharing economy and the green economy and the perceptions of Romanian users regarding them. Our research questionnaire was based on the elements we found in the academic literature. To evaluate the collected data, we used the factor analysis method with the support of the SPSS program. As our study reveals, digitalization as well as inclinations towards saving are factors impacting both the propensity towards sharing and support for the green economy. The demarcation line between the sharing and the green economies is rather fluid, the two realities being under a reciprocal influence. In our model, the green economy develops according to the principles of the sharing economy, going a step further in considering the relationship between society and environment, society and sustainable, eco-friendly behaviour. Although the sharing economy is not necessarily a prerequisite of the green economy, it is, nevertheless, easy for societies or groups that have internalized the lessons of the sharing economy to move forward towards the green economy. This study can be an important tool and a first step for businesses, and, more importantly, for the Romanian public institutions to accelerate the implementation of necessary measures, including legislative ones, in order to promote the further development of these economies.

The Development of the Concept of Social Capital

Social capital is assumed as an alternative form of other modalities. Theoretically, there is a debate about social capital leading to social relations. The debate relates to the conceptualization of social capital as concrete capital where individuals or groups are able to utilize social relations including values, social networks and trust to obtain economic benefits and social benefits. Using a qualitative approach with a literature study method, this article aims to explain social capital as a theoretical concept. The presentation of the study shows that there is a relationship between social capital and inclusiveness and community empowerment, especially in the context of sustainable inclusive development. This article concludes that the concept of social capital serves as a useful framework for successful development and policy formulation.

Is 'Not Different' Enough to Conclude Similar Cardiovascular Responses Across Sexes?

The number of research studies investigating whether similar or different cardiovascular responses or adaptations exist between males and females are increasing. Traditionally, difference-based statistical methods (e.g., t-test, ANOVA, etc.) have been implemented to compare cardiovascular function between males and females, with a P-value >0.05 used to denote similarity between sexes. However, an absence of evidence (i.e., large P-value) is not evidence of absence (i.e., no sex differences). Equivalence testing determines whether two measures or groups provide statistically equivalent outcomes, in that they differ by less than an 'ideally prespecified' smallest effect size of interest. Our perspective discusses the applicability and utility of integrating equivalence testing when conducting sex comparisons in cardiovascular research. An emphasis is placed on how cardiovascular researchers may conduct equivalence testing across multiple study designs (e.g., cross-sectional comparisons, repeated measures intervention, etc.). The strengths and weaknesses of this statistical tool are discussed. Equivalence analyses are relatively simple to conduct, may be used in conjunction with traditional hypothesis testing to interpret findings, and permits the determination of statistically equivalent responses between sexes. We recommend that cardiovascular researchers consider implementing equivalence testing to better our understanding of similar and different cardiovascular processes between sexes.

Systematic Review of Socio-Emotional Values Within Organizations

The theory of separation assumes, with provocation, that an organization cannot reconcile profits and social function. Organizations can reconcile these two, apparently contrasting, missions, by considering emotions, especially moral emotions, to create a genuine motivation for focusing on goals beyond simple economic earnings and protecting organizations or groups of people from dysfunctional attitudes and behaviors, as well as considering the important role of the stakeholder accountability. Using the PRISMA method, we created a review of records using keywords relating to a socio-emotional value within organizations, with a particular focus on the last 20 years. We used the SCOPUS database and, after removing irrelevant records, we used the VOSviewer tool to create a cluster map of different areas in this topic. Some records cite the socio-emotional value that is related to organizational and employee suffering, while other articles consider it a positive factor that improves performance and prevents problems in organizations.