Twitter’s pulse on hydrogen energy in 280 characters: a data perspective

Abstract

Uncovering the public discourse on hydrogen energy is essential for understanding public behaviour and the evolving nature of conversations over time and across different regions. This paper presents a comprehensive analysis of a large multilingual dataset pertaining to hydrogen energy collected from Twitter spanning a decade (2013–2022) using selected keywords. The analysis aims to explore various aspects, including the temporal and spatial dimensions of the discourse, factors influencing Twitter engagement, user engagement patterns, and the interpretation of conversations through hashtags and ngrams. By delving into these aspects, this study offers valuable insights into the dynamics of public discourse surrounding hydrogen energy and the perceptions of social media users.

Mathematical Model and AI Integration for COVID-19: Improving Forecasting and Policy-Making

Abstract

In this work, a new susceptible–exposed–infectious–recovered (SEIR) compartmental model is proposed which has additional media influence for precise quantization of the coronavirus disease 2019 (COVID-19). In the proposed model, first-order ordinary differential equations (ODEs) are used for the formulation of basic reproduction number, whereas genetic algorithm (GA) is used for its estimation. The inclusion of climatic parameters, governmental impact, and human behavioral response toward the disease provides an upper hand in determining the dynamics of its transmissibility, thereby indicating their significance in precising the outcomes. In addition, the future trends for the new normalized confirmed cases of COVID-19 are predicted using the long short-term memory (LSTM) model which helps in evaluating and modifying the current preventive actions taken to improve the situation. The robustness of the proposed model is measured by five different error functions which are tested in five different countries. According to the experimental results, this is observed that the proposed model has a smaller prediction deviation as well and the proposed scheme outperforms state-of-the-art models of COVID-19.

Mathematical Model and AI Integration for COVID-19: Improving Forecasting and Policy-Making

Abstract

In this work, a new susceptible–exposed–infectious–recovered (SEIR) compartmental model is proposed which has additional media influence for precise quantization of the coronavirus disease 2019 (COVID-19). In the proposed model, first-order ordinary differential equations (ODEs) are used for the formulation of basic reproduction number, whereas genetic algorithm (GA) is used for its estimation. The inclusion of climatic parameters, governmental impact, and human behavioral response toward the disease provides an upper hand in determining the dynamics of its transmissibility, thereby indicating their significance in precising the outcomes. In addition, the future trends for the new normalized confirmed cases of COVID-19 are predicted using the long short-term memory (LSTM) model which helps in evaluating and modifying the current preventive actions taken to improve the situation. The robustness of the proposed model is measured by five different error functions which are tested in five different countries. According to the experimental results, this is observed that the proposed model has a smaller prediction deviation as well and the proposed scheme outperforms state-of-the-art models of COVID-19.

How cultural competence is conceptualised, developed and delivered in pharmacy education: a systematic review

Abstract

Background

It is important to have a pharmacy workforce that is culturally competent to recognise a patient’s health beliefs to improve medication adherence and reduce poor treatment outcomes.

Aim

This systematic review aimed to identify, critically appraise and summarise how cultural competency is conceptualised, developed and embedded in pre-qualification pharmacy education.

Method

Medline, Scopus, PsychInfo, Web of Knowledge, CINAHL, and Embase databases were searched for relevant papers published in English between January 2012 and December 2021, following PRISMA guidelines. Data from included papers were thematically analysed. Educational quality of papers was appraised using the GREET criteria. This systematic review was registered on PROSPERO, CRD42021295875.

Results

The review included 47 papers (46 studies) with 18 papers meeting ≥ 9 points on the GREET criteria thus considered of good educational quality. Forty papers focused on educational interventions implemented to pharmacy students only, the remaining included students from different health disciplines. Half of the educational interventions focused on cultural competence in general. Most educational interventions lasted over a week and 21 were compulsory. Cultural competence conceptualisation varied; a focus on knowledge about different cultures or on culturally competent behaviours or a continuum with knowledge at one end and behaviour at the other.

Conclusion

There is variation in how cultural competence is embedded in pharmacy programmes, which could be a reflection of the differences in how educators conceptualised cultural competence. Further research is needed to develop a unified understanding of the meaning of cultural competence and how it can be embedded in pharmacy education.

Exploring the Impact of Incivility on Psychological Distress: The Unique Lived Experiences of Women Identifying as Indigenous and as part of the LGBTQ + Community

Abstract

Organizations are increasingly facing complex issues related to diversity and inclusion. Although overt forms of discrimination might have declined significantly, researchers are now alarmed in the face of insidious forms of “modern” discrimination that are flying under organizational radars despite policies and laws. While incivility has been broadly conceptualized and examined as “generalized” behaviors in organizations, less attention has been dedicated to the “selective” form it can take. The present study tested different aspects of Cortina’s theory of selective incivility as a “modern” manifestation of discrimination. This study extends the theory by being the first to investigate uncivil experiences Indigenous employees might be confronted with in organizations and how it might lead to experiencing higher symptoms of psychological distress. To do so, we collected data from 6706 employees working in a large Canadian public organization who were asked to complete measures of psychological distress and incivility from co-workers and supervisors. According to analyses of parallel mediation, women were less likely to report uncivil treatment from co-workers and direct supervisors than men. Evidence of moderated mediation also emerged, with target gender and Indigenous identity interacting to predict uncivil experiences, such that Indigenous women reported worse treatment from direct supervisors (b = .92, p = .03, ΔR2 = .0007), impacting their level of psychological distress (index = -.21, 95% CI [.01, .41]). Overall, our findings suggest that incivility does not work consistently against women in organizations and that intersectionality plays a role in predicting identity-based mistreatment. Our results also suggest that practitioners should consider an intersectional approach when implementing policies and interventions regarding identity-based mistreatment.

Prevalence of helmintic infections in Brazilian Maxakali indigenous: a repeated cross-sectional design

Abstract

Background

The prevalence of intestinal parasites is known to be high among Amerindian populations; further, there are serious problems in the healthcare of these populations in Brazil. The Maxakali, located in the northeastern region of Minas Gerais, Brazil, is an indigenous group that still preserves many of its cultural aspects. This study aimed to compare the positivity rate of schistosomiasis and soil-transmitted helminths in this ethnic group in epidemiological surveys conducted in 1972 and 2014.

Methods

Stool parasitological examinations were performed by the Kato-Katz technique during both periods in this population. In 2014, the parasitological diagnosis was also realized with the TF-Test® technique.

Results

In 1972, 270 inhabitants were examined. The positivity rates were 67.4% for Schistosoma mansoni, 72.9% for hookworms, 43.7% for Ascaris lumbricoides, and 23.7% for Trichuris trichiura. In 2014, 545 individuals were examined, and the positivity rates obtained were 45.7% for S. mansoni, 22.8% for hookworms, 0.6% for A. lumbricoides, and 2.8% for T. trichiura.

Conclusions

The comparison of the parasitological surveys conducted in 1972 and 2014, indicates that the indigenous Maxakali remained neglected by the health and indigenous protection authorities during these four decades. The infection rate observed in 2014 for schistosomiasis and hookworm remains high, considering the current epidemiological view of these diseases in the Brazilian population.

Psquad: Plagiarism detection and document similarity of Hindi text

Abstract

Plagiarism is a significant issue, especially among students, in the education field, where the internet has made a vast amount of information easily accessible. Although numerous plagiarism detection tools are available for English text, detecting plagiarism in low-resource languages such as Hindi remains a challenge. This study proposes a novel case-based approach to evaluate the effectiveness of various plagiarism detection tools on Hindi documents. The proposed approach maps similarities between Hindi documents at the word, phrase, and sentence levels, and generates diverse cases using stopword removal and stemming pre-processing techniques. The study calculates the similarity score between the original Hindi document and its paraphrased version at the word, sentence, and document levels. The results show that the proposed approach outperforms existing plagiarism detection tools for Hindi text, indicating its potential to enhance academic integrity and prevent plagiarism.

Delinking from Monolingual Norms: A Case Study of Chinese Postgraduate Students’ Translanguaging Practices in English Academic Writing

Abstract

This study explores the decolonial potential of Chinese bilingual postgraduate students’ translanguaging practices in English academic writing. It investigates the ways that students enact translanguaging to delink from monolingual standard English norms and integrate their authentic bilingual voices in the writing process. A case study was conducted to collect the students’ written products and record and analyze their approaches and views to language use in academic writing in an English for academic purpose course. The findings reveal that students could employ the integrated multilingual repertoires to enhance learning outcomes, negotiate deficit linguistic views, and voice cultural identities in the writing process. Their translanguaging enactment transcends linguistic boundaries and English-dominated norms, providing empirical support for the decolonization of academic writing in Chinese higher education. The study underscores the importance of student-led negotiation of linguistic and cultural differences, advocating for critical engagement with translanguaging to deconstruct social inequalities perpetuated by hegemonic ideologies and promote bilingual subjectivities in non-Anglophone academic contexts.

The influence of bias correction of global climate models prior to dynamical downscaling on projections of changes in climate: a case study over the CORDEX-Australasia domain

Abstract

We investigate the influence of bias correction of Global Climate Models (GCMs) prior to dynamical downscaling using regional climate models (RCMs), on the change in climate projected. We use 4 GCMs which are bias corrected against ERA-Interim re-analysis as a surrogate truth, and carry out bias corrected and non-bias corrected simulations over the CORDEX Australasia domain using the Weather Research and Forecasting model. Our results show that when considering the effect of bias correction on current and future climate separately, bias correction has a large influence on precipitation and temperature, especially for models which are known to have large biases. However, when considering the change in climate, i.e the \(\Delta\) change (future minus current), we found that while differences between bias-corrected and non-corrected RCM simulations can be substantial (e.g. more than \(1\,^\circ\) C for temperatures) these differences are generally smaller than the models’ inter-annual variability. Overall, averaged across all variables, bias corrected boundary conditions produce an overall reduction in the range, standard deviation and mean absolute deviation of the change in climate projected by the 4 models tested, over 61.5%, 62% and 58% of land area, with a larger reduction for precipitation as compared to temperature indices. In addition, we show that changes in the \(\Delta\) change for DJF tasmax are broadly linked to precipitation changes and consequently soil moisture and surface sensible heat flux and changes in the \(\Delta\) changefor JJA tasmin are linked to downward longwave heat flux. This study shows that bias correction of GCMs against re-analysis prior to dynamical downscaling can increase our confidence in projected future changes produced by downscaled ensembles.

How climate change is affecting the summer monsoon extreme rainfall pattern over the Indo-Gangetic Plains of India: present and future perspectives

Abstract

The Indo-Gangetic Plain (IGP), the source of grains for around 40% Indian population, is known as the breadbasket of India. The Indian Summer Monsoon Rainfall (ISMR) plays a vital role in the agricultural activities in this region. The rapid urbanization, land use and land cover change have significantly impacted the region’s agriculture, water resources, and socioeconomic facets. The present study has investigated the observed and regional modeling aspects of ISMR characteristics, associated extremes over the IGP, and future perspectives under the high-emission RCP8.5-scenario. Future projections suggest a 10–20% massive decrease during pre-monsoon (March–May) and earlier ISM season months (i.e., June and July). A significant 40–70% decline in mean monsoon rainfall during the June–July months in the near future (NF; 2041–2060) has been projected compared to the historical period (1986–2005). An abrupt increase of 80–170% in mean monsoon rainfall during the post-monsoon (October–December) in the far future (FF; 2080–2099) is also projected. The distribution of projected extreme rainfall events shows a decline in moderate or rather heavy events (5 or more) in NF and FF. Further, an increase in higher rainfall category events such as very heavy (5–10) and extremely heavy rainfall (5 or more) events in NF and FF under the warmer climate is found. However, the changes are less prominent during FF compared to the NF. The mean thresholds for extremely heavy rainfall may increase by 1.9–4.9% during NF and FF. Further, the evolution patterns of various quantities, such as tropospheric temperature gradient (TG), specific humidity, and mean sea level pressure, have been analyzed to understand the physical processes associated with rainfall extremes. The strengthening in TG and enhanced atmospheric moisture content in NF and FF support the intensification in projected rainfall extremes over IGP.