bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling COVID-19 disease biology to identify drug treatment candidates
Authors: Jessen Walter J. , Gaisenband Stefan Diaz , Quintanilla M’Lissa , Lula Sadiq , McLeroth Patrick , Sullivan Adam , Letovsky Stanley 
Published: April 2022

AbstractCoronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, there are a limited number of effective treatments. A variety of drugs that have been approved for other diseases are being tested for the treatment of COVID-19, and thus far only remdesevir, dexamethasone, baricitinib, tofacitinib, tocilizumab, and sarilumab have been recommended by the National Institutes of Health (NIH) COVID-19 Treatment Guidelines Panel for the therapeutic management of hospitalized adults with COVID-19. Using a disease biology modeling approach, we constructed a protein-protein interactome network based on COVID-19- associated genes/proteins described in research literature together with known protein-protein interactions in epithelial cells. Phenotype and disease enrichment analysis of the COVID-19 disease biology model demonstrated strong statistical enrichments consistent with patients’ clinical presentation. The model was used to interrogate host biological response induced by SARS-CoV-2 and identify COVID-19 drug treatment candidates that may inform on drugs currently being evaluated or provide insight into possible targets for potential new therapeutic agents. We focused on cancer drugs as they are often used to control inflammation, inhibit cell division, and modulate the host microenvironment to control the disease. From the top 30 COVID-19 drug candidates, twelve have a role as an antineoplastic agent, seven of which are approved for human use. Altogether, nearly 40% of the drugs identified by our model have been identified by others for COVID-19 clinical trials. Disease biology modeling incorporating disease-associated genes/proteins discussed in the research literature together with known molecular interactions in relevant cell types is a useful method to better understand disease biology and identify potentially effective therapeutic interventions.
An X-ray beam profile monitoring system at a beamline front-end combining a single-crystal diamond film and energy discrimination using droplet analysis
Authors: Kudo Togo , Sano Mutsumi , Matsumoto Takahiro , Itoga Toshiro , Goto Shunji , Takahashi Sunao 
Published: April 2022

This work has successfully demonstrated a system for monitoring pink-beam X-rays exiting from a beamline front-end, which has a specific spatial distribution based on each energy component. In this study, the X-rays scattered from a single-crystal chemical-vapor-deposited diamond film were converted into a cross-sectional image using pinhole optics, followed by digitization with a direct detection complementary metal-oxide-semiconductor 2D detector. By using single crystals instead of poly-crystals, good quality images were obtained with no diffraction bright spots. As a result of applying photon energy discrimination using the droplet analysis to the image information, the spatial distribution of each energy component of the undulator radiation was successfully visualized. The result was found to be in good agreement with the theoretically calculated result obtained using the synchrotron radiation calculation code SPECTRA. The new synchrotron radiation beam monitor proposed in this paper can serve as a powerful beam diagnostic tool for diffraction-limited rings that require strict light source stability.
Investor communication channels: the case of e-mail and corporate websites – mutually exclusive or complementary?
Authors: Nel George , Baard Roelof 
Published: April 2022

PurposeThe aim of this study was threefold: to examine companies' e-mail handling performance, to ascertain whether companies' view corporate websites and respond to e-mail requests as mutually exclusive or complementary, and finally to gauge the strategic importance of retail investors.Design/methodology/approachThe findings are based on an analysis of the corporate websites and e-mail handling performance of the 77 smallest companies listed on a South African stock exchange. A “mystery investor” approach was employed to measure companies' e-mail handling performance in terms of responsiveness, timeliness and relevance of responses. A disclosure score was calculated for each company based on a content analysis of corporate websites.FindingsThe opportunity for improvement exists, as evidenced in the fact that only 53% of companies responded to an e-mail request from a retail investor. The results suggest that corporate websites and the e-mail functionality are not used in isolation but as complementary. Although the results suggest that companies neglect retail investors, companies that provided a dedicated investor relations (IR) contact address prioritised both their corporate websites aimed to a wide range of stakeholders, as well as responding to an e-mail request received from a retail investor.Originality/valueThis study contributes to research on the association between one-way and two-way communication channels, aimed at retail investors. It is the first study to explore these relationships using data from the smallest companies listed on the stock exchange of an emerging economy.
A deep neural networks-based fusion model for COVID-19 rumor detection from online social media
Authors: Lu Heng-yang , Yang Jun , Fang Wei , Song Xiaoning , Wang Chongjun 
Published: April 2022

PurposeThe COVID-19 has become a global pandemic, which has caused large number of deaths and huge economic losses. These losses are not only caused by the virus but also by the related rumors. Nowadays, online social media are quite popular, where billions of people express their opinions and propagate information. Rumors about COVID-19 posted on online social media usually spread rapidly; it is hard to analyze and detect rumors only by artificial processing. The purpose of this paper is to propose a novel model called the Topic-Comment-based Rumor Detection model (TopCom) to detect rumors as soon as possible.Design/methodology/approachThe authors conducted COVID-19 rumor detection from Sina Weibo, one of the most widely used Chinese online social media. The authors constructed a dataset about COVID-19 from January 1 to June 30, 2020 with a web crawler, including both rumor and non-rumors. The rumor detection task is regarded as a binary classification problem. The proposed TopCom model exploits the topical memory networks to fuse latent topic information with original microblogs, which solves the sparsity problems brought by short-text microblogs. In addition, TopCom fuses comments with corresponding microblogs to further improve the performance.FindingsExperimental results on a publicly available dataset and the proposed COVID dataset have shown superiority and efficiency compared with baselines. The authors further randomly selected microblogs posted from July 1–31, 2020 for the case study, which also shows the effectiveness and application prospects for detecting rumors about COVID-19 automatically.Originality/valueThe originality of TopCom lies in the fusion of latent topic information of original microblogs and corresponding comments with DNNs-based models for the COVID-19 rumor detection task, whose value is to help detect rumors automatically in a short time.
A family-oriented view on well-being amongst low-status expatriates in an international workplace
Authors: Haak-Saheem Washika , Liang Xiaoyan , Holland Peter Jeffrey , Brewster Chris 
Published: April 2022

PurposeThe pandemic emphasised the importance for society of the “hidden” workforce – cleaners, delivery drivers, security guards or hospital porters. This paper explores the well-being of low-status expatriates in the international workplace exemplified by the United Arab Emirates (UAE). This is one of the first studies examining the well-being of people at the bottom of the pyramid, living in difficult circumstances, and undertaking work that is hard and sometimes dangerous.Design/methodology/approachThe authors adopt an exploratory approach. Using semi-structured interview data from 21 low-status expatriates, the authors examine their experiences in the UAE in relation to their well-being, allowing the authors to suggest the need to develop our understanding of the concept of well-being and the concept's application.FindingsLow-status expatriates live restrictive lives, away from their family and friends for extended periods, and subject to rigid terms and conditions of employment. Difficult circumstances, long working hours, late or arbitrarily reduced salary payment and a lack of voice affect their personal well-being and sacrificed to consideration for their family well-being. Applying the concept of well-being in such cases requires the authors to develop the notion beyond the individual to encompass the wider family.Research limitations/implicationsThis exploratory analysis opens new avenues for well-being studies and highlights the need for contextualised research. Future research might benefit from quantitative methods being used alongside qualitative methods and collecting multiple perspective data, including the views of managers and policy makers and data from the “left-behind” families of these low-status expatriates.Practical implicationsThere is plenty of scope for managers of low-status expatriates to improve the latter's well-being. Given the lack of interest in doing so, the authors suggest that policy makers may need to modify extant legalisation to ensure a greater focus on low-status expatriates.Originality/valueThe authors believe this to be the first study to examine the impact of family orientation on the well-being of low-status expatriates, encouraging the authors to challenge and suggest developments to current understandings of well-being.
Acculturation stress and social support for international students' adjustment in Malaysia: does language proficiency matter?
Authors: Lashari Sana Anwar , Awang-Hashim Rosna , Lashari Tahira Anwar , Kaur Amrita 
Published: April 2022

PurposeInternational students with low proficiency in the English language remain at high risk of academic, social and psychological maladjustment. Using an acculturation theoretical framework, this study aims to show that acculturation stress and social support mediate the relationship between language proficiency and academic, social, and psychological adjustment among 675 international postgraduate students in Malaysian public universities.Design/methodology/approachCorrelational research design was employed to gather data from 227 females and 448 males aged between 22–45 years belonging to Asian, Middle Eastern or African countries. Out of these, 292 students were enrolled in master's degrees, and 383 students were enrolled in Ph.D. Self-administered questionnaires were used which includes Student Adjustment to the College Questionnaire (SACQ) to measure students' academic adjustment, Kwak to assess students' English language proficiency, Multidimensional Scale of Perceived Social Support (MSPSS) to assess perceived availability of social support from friends and Acculturative Stress Scale for International Students (ASSIS) to measure acculturation stress.FindingsThe hypothesized model was tested using path analysis with manifest variables in Analysis of Moment Structures (AMOS) 23.0. The findings suggest that language proficiency is a significant predictor of academic, social and psychological adjustment of international students, and this relationship is partially mediated by acculturation stress and social support.Research limitations/implicationsThe article concludes with implications and recommendations for international student offices and program organizers to ensure conditions for successful academic, social and psychological adjustment of the international students.Originality/valueThe manuscript has not been published or submitted elsewhere.
The effect of entrepreneurial characteristics on attitude and intention: an empirical study among technical undergraduates
Authors: Dubey Pushkar 
Published: April 2022

PurposeUnemployment is the biggest issue for all the developing countries, especially India, where millions of educated people are passed out every year from different educational institutes, but against this, the jobs are not being generated. This situation will only be addressed effectively when the government/authorities make more efforts to identify/create potential entrepreneurs. The present study investigates the relationship of entrepreneurial characteristics on entrepreneurial attitude and intention among engineering undergraduates engaged in various technical institutions in Chhattisgarh state.Design/methodology/approachStratified random sampling was used to collect sample of 1,000 engineering undergraduates enrolled in third and fourth year at different technical institutions of Chhattisgarh state.FindingsStructural equation modelling and hierarchal multiple regression analysis were incorporated, and the analysis revealed that the entrepreneurial characteristic was found to be a significant predictor of entrepreneurial attitude and intention of engineering undergraduates. The study also discusses managerial implications, limitations and avenues for future research.Originality/valueLooking at the current scenario, the present study discusses with several factors influencing entrepreneurial attitude and intention of engineering undergraduates, which might be the only solution to a significant issue, i.e. unemployment. In addition, there is a huge lack of research in addressing unemployment issue through entrepreneurship in the state of Chhattisgarh.
Supporting management of new product development via a novel conceptual model: an interview driven approach
Authors: Ball Zachary , Cagan Jonathan , Kotovsky Kenneth 
Published: April 2022

Purpose
This study aims to gain a deeper understanding of the industry practice to guide the formation of support tools with a rigorous theoretical backing. Cross-functional teams are an essential component in new product development (NPD) of complex products to promote comprehensive coverage of product design, marketing, sales, support as well as many other activities of business. Efficient use of teams can allow for greater technical competency coverage, increased creativity, reduced development times and greater consideration of ideas from a variety of stakeholders. While academics continually aspire to propose methods for improved team composition, there exists a gap between research directions and applications found within industry practice.

Design/methodology/approach
Through interviewing product development managers working across a variety of industries, this paper investigates the common practices of team utilization in an organizational setting. Following these interviews, this paper proposes a conceptual two-dimensional management support model aggregating the primary drivers of team success and providing direction to systematically address features of team management and composition.

Findings
Based on this work, product managers are recommended to continually address the positioning of members throughout the entire NPD process. In the early stages, individuals are to be placed to work on project components with explicit consideration toward the perceived complexity of tasks and individual competency. Throughout the development process, individuals’ positions vary based on new information while continued emphasis is placed on maintaining a shared understanding.

Originality/value
Bridging the gap between theory and application within product development teams is a necessary step toward improved product develop. Industrial settings require practical solutions that can be applied economically and efficiently within their organization. Theoretical reflections postulated by academia support improved team design; however, to achieve true success, they must be applicable when considering product development.
Assessing the AI-CRM technology capability for sustaining family businesses in times of crisis: the moderating role of strategic intent
Authors: Chaudhuri Ranjan , Chatterjee Sheshadri , Kraus Sascha , Vrontis Demetris 
Published: April 2022

PurposeThis study assesses the capability of artificial intelligence integrated customer relationship management (AI-CRM) technology for sustaining family businesses in times of crisis, such as the COVID-19 pandemic. The study also investigates the moderating role of strategic intent in sustaining family businesses in times of crisis.Design/methodology/approachThe authors used dynamic capability view theory and related literature on family business and technology adoption to develop a conceptual model. This model has been validated using the structural equation modeling technique considering 332 usable responses from people of India involved in family businesses and technology adoption. The study also uses multigroup analysis to examine the moderating role of strategic intent.FindingsThe study finds that adoption of AI-CRM technology significantly and positively impacts dynamic capabilities of the family businesses, such as sensing, seizing and transforming capabilities, which in turn positively and significantly influences their sustainability during crises. The study also highlights the significant moderating impact of strategic intent for sustaining family business firms in uncertain times.Practical implicationsThis study has highlighted the importance for family businesses to adopt AI-CRM technology and its influence on their dynamic capabilities. The study also provides important inputs to the management of family businesses regarding adoption of new technologies and their significance during crises. The study also documents that strategic intent could help family businesses to survive during such times. The study is conducted in India and thus cannot be generalized.Originality/valueThis study table is unique in that it investigates the influence of AI-CRM technology and the moderating role of strategic intent on family business sustainability in times of crisis. Moreover, the proposed theoretical model is a unique model with explanative power of 71%.
The effect of business intelligence practices on job satisfaction in the Saudi Electricity Company in the Asir Region
Authors: Binzafrah Faiz , Taleedi Faisal 
Published: April 2022

PurposeThe purpose of this study is to determine the effect of business intelligence on job satisfaction in the Saudi Electricity Company in the Asir. It aims to evaluate employee job satisfaction after adopting a BI system for job practices.Design/methodology/approachA mixed-method including descriptive, questionnaire for data collection and analytical approach was used. The random sample population consists of 354 employees out of 3,000.FindingsIt is found that the implementation of a BI system and the associated practices have a statistically significant effect on employee job satisfaction. The study recommends the adoption of BI systems for organizational activities. Such organizations must consider the latest BI tools for solving business problems.Originality/valueTo the best of authors' knowledge, the current study is the first attempt to evaluate the performance of BI practices in the region and in context of employee job satisfaction. This will contribute to understanding the job satisfaction in similar organizational environment.
Variants of drill as preparations for responding to surprising events
Authors: Born Eva , Lehner Johannes M. 
Published: April 2022

PurposeThis paper aims to contribute to research on management training and development by exploring the impact of extensive training labeled as drill on coping with critical situations. More specifically, it inquires into conditions and supplements for drill to move from mere adaptation to exaptation, relating to the transfer of drilled procedures to serve novel requirements, in events involving different types of surprise.Design/methodology/approachThe paper adopts an interpretive research approach. Data were collected through semi-structured interviews with members of the Austrian Military on cases of resilient field action in manifold situations of surprise.FindingsThe paper reveals that two different kinds of drill lead to properties that are essential for recovery from shock during critical events: the pure drill and the preaptative drill. Pure drill enables automatized action in situations when time or emotional pressure is too high for reflection or consideration of different options. Preaptative drill, pertaining to drill enhanced with background knowledge, leads to adaption or even exaptation of automatized action through reflection.Originality/valueThe present paper is the first to show the potential impact of drill on the ability to deal with specific kinds of surprise. It suggests that incorporating explanatory background knowledge about why and how rules and learned behaviors that were created into training programs can be of vital importance for dealing with surprise successfully.
A pedagogical model for STEAM education
Authors: Bertrand Marja G. , Namukasa Immaculate K. 
Published: April 2022

PurposeCertain researchers have expressed concerns about inequitable discipline representations in an integrated STEM/STEAM (science, technology, engineering, arts and mathematics) unit that may limit what students gain in terms of depth of knowledge and understanding. To address this concern, the authors investigate the stages of integrated teaching units to explore the ways in which STEAM programs can provide students with a deeper learning experience in mathematics. This paper addresses the following question: what learning stages promote a deeper understanding and more meaningful learning experience of mathematics in the context of STEAM education?Design/methodology/approachThe authors carried out a qualitative case study and collected the following data: interviews, lesson observations and analyses of curriculum documents. The authors took a sample of four different STEAM programs in Ontario, Canada: two at nonprofit organizations and two at in-school research sites.FindingsThe findings contribute to a curriculum and instructional model which ensures that mathematics curriculum expectations are more explicit and targeted, in both the learning expectations and assessment criteria, and essential to the STEAM learning tasks. The findings have implications for planning and teaching STEAM programs.Originality/valueThe authors derived four stages of the STEAM Maker unit or lesson from the analysis of data collected from the four sites, which the authors present in this paper. These four stages offer a model for a more robust integrated curriculum focusing on a deeper understanding of mathematics curriculum content.