bluuebunny/crossref_metadata_2025_split huggingface dataset:
The socioeconomic factors that led to unemployment under COVID-19 pandemic among Japanese workers: a prospective cohort study
Authors: Kuroishi Makiko , Nagata Tomohisa , Hino Ayako , Tateishi Seiichiro , Ogami Akira , Tsuji Mayumi , Matsuda Shinya , Mori Koji , Fujino Yoshihisa ,   the CORoNaWork project
Published: August 2021

AbstractObjectivesTo examine the relationship between socioeconomic factors and unemployment among workers during COVID-19 pandemic in Japan.DesignA prospective cohort study, follow-up from December 22–25, 2020 through February 18–19, 2021.SettingThe panelists registered with an Internet survey companyParticipantsA cluster random sample of 33,087 workers with stratification by sex, job type, and region among Japan’s working populationMain outcomes and measuresUnemployment between December 2020 and February 2021ResultsAmong the 19,941 participants, 725 (3.6%) had experienced unemployment. Multivariate analysis showed that the significant high unemployment for women (compared to men); younger age (compared to older age); being married (spouse not working), bereaved or divorced, and unmarried (compared to married (spouse working)); annual household income less than 6 million yen, (compared to more than 10 million yen); junior high or high school, vocational school, junior college, or technical school (compared to graduate school); and temporary or contract employees, self-employed, agriculture, forestry, or fishing (compared to general employees).ConclusionsCOVID-19 appears to have created difficulties for the vulnerable groups. This suggests the need for employment and economic support for such individuals.Strengths and limitations of this studyUnder the pandemic of COVID-19, we found that unemployment was associated with socioeconomic factors such as age, sex, marriage, income, education and occupation.Our findings suggest that in the event of a major epidemic, resulting in unemployment among vulnerable segments of the labour market, regardless of whether workers themselves are infected.It was unclear why the participants had experienced unemploymentThis study was conducted as an Internet survey, so the generalizability of our results is limited.
Trends and Intensity of Human Rhinovirus Invasions in Kilifi, Coastal Kenya Over a Twelve-Year Period, 2007-2018
Authors: Morobe John Mwita , Kamau Everlyn , Murunga Nickson , Gatua Winfred , Luka Martha M. , Lewa Clement , Cheruiyot Robinson , Mutunga Martin , Odundo Calleb , Nokes D James , Agoti Charles N. 
Published: August 2021

ABSTRACTBackgroundHuman rhinovirus (HRV) is an ubiquitous pathogen and the principal etiologic agent of common cold. Despite the high frequency of HRV infections, data describing its long-term epidemiological patterns in a single population remain limited.MethodsWe analysed 1,070 VP4/VP2 genomic region sequences obtained from samples collected between 2007-2018 from hospitalised paediatric patients (< 60 months) with acute respiratory disease in Kilifi County Hospital on the Kenya Coast.ResultsOf 7,231 children enrolled, HRV was detected in 1,497 (20.7%) andVP4/VP2 sequences were recovered from 1,070 samples (71.5%). A total of 144 different HRV types were identified (67 HRV-A, 18 HRV-B and 59 HRV-C) and at any time-point, several types co-circulated with alternating predominance. Within types multiple genetically divergent variants were observed. Ongoing HRV infections appeared to be a combination of (i) persistent types (observed up to seven consecutive months), (ii) reintroduced genetically distinct variants and (iii) new invasions (average of 8 new types, annually).ConclusionSustained HRV presence in the Kilifi community is mainly due to frequent invasion by new types and variants rather than prolonged circulation of locally established strains.
Strigo-D2 – a bio-sensor for monitoring the spatio-temporal pattern of strigolactone signaling in intact plants
Authors: Song Changzheng , Zhao Jiao , Guichard Marjorie , Shi Dongbo , Grossmann Guido , Schmitt Christian , Jouannet Virginie , Greb Thomas 
Published: August 2021

AbstractStrigolactones (SLs) are a class of plant hormones modulating developmental programs in response to endogenous and exogenous stimuli and mediating biotic interactions. However, a comprehensive view on the spatio-temporal pattern of SL signaling has not been established and tools for a systematic in planta analysis do not exist. Here, we present Strigo-D2, a genetically encoded ratiometric SL signaling sensor, allowing the examination of SL signaling distribution with cellular resolution and its rapid response to altered SL levels in intact plants. By monitoring the abundance of a truncated and fluorescently labeled SUPPRESSOR OF MAX2 1-LIKE 6 (SMXL6) protein, a proteolytic target of the SL signaling machinery, we show that all cell types investigated have the capacity to respond to changes in SL levels but with very different dynamics. In particular, SL signaling is pronounced in vascular cells but low in guard cells and the meristematic region of the root. We also show that other hormones leave Strigo-D2 activity unchanged indicating that initial SL signaling steps work in isolation from other hormonal signaling pathways. Specificity and spatio-temporal resolution of Strigo-D2 underline the value of the sensor for monitoring SL signaling in a broad range of biological contexts and with highly instructive analytical depth.
The two-component response regulator OrrA confers dehydration tolerance by regulating anaKa expression in the cyanobacterium Anabaena sp. strain PCC 7120
Authors: Kimura Satoshi , Sato Miho , Fan Xingyan , Ohmori Masayuki , Ehira Shigeki 
Published: August 2021

SummaryThe aquatic cyanobacterium Anabaena sp. strain PCC 7120 exhibits dehydration tolerance. The regulation of gene expression in response to dehydration is crucial for the acquisition of dehydration tolerance, but the molecular mechanisms underlying dehydration responses remain unknown. In this study, the functions of the response regulator OrrA in the regulation of salt and dehydration responses were investigated. Disruption of orrA abolished or diminished the induction of hundreds of genes in response to salt stress and dehydration. Thus, OrrA is a principal regulator of both stress responses. In particular, OrrA plays a crucial role in dehydration tolerance because an orrA disruptant completely lost the ability to regrow after dehydration. Moreover, in the OrrA regulon, anaKa encoding a protein of unknown function was revealed to be indispensable for dehydration tolerance. OrrA and AnaK are conserved among the terrestrial cyanobacteria, suggesting their conserved functions in dehydration tolerance in cyanobacteria.
Cooled SPAD array detector for low light-dose fluorescence laser scanning microscopy
Authors: Slenders Eli , Perego Eleonora , Buttafava Mauro , Tortarolo Giorgio , Conca Enrico , Zappone Sabrina , Pierzynska-Mach Agnieszka , Villa Federica , Petrini Enrica Maria , Barberis Andrea , Tosi Alberto , Vicidomini Giuseppe 
Published: August 2021

ABSTRACTThe single-photon timing and sensitivity performance and the imaging ability of asynchronous-readout single-photon avalanche diode (SPAD) array detectors have opened up enormous perspectives in fluorescence (lifetime) laser scanning microscopy (FLSM), such as super-resolution image scanning microscopy and high-information content fluorescence fluctuation spectroscopy (FFS). However, the strengths of these FLSM techniques depend on the many different characteristics of the detector, such as dark-noise, photon-detection efficiency, after-pulsing probability, and optical-cross talk, whose overall optimization is typically a trade-off between these characteristics. To mitigate this trade-off, we present a novel SPAD array detector with an active cooling system, which substantially reduces the dark-noise without significantly deteriorating any other detector characteristics. In particular, we show that lowering the temperature of the sensor to −15°C significantly improves the signal-to-noise ratio due to a 10-fold decrease in the dark-count rate compared to room temperature. As a result, for imaging, the laser power can be decreased by more than a factor of three, which is particularly beneficial for live-cell super-resolution imaging, as demonstrated in fixed and living cells expressing GFP-tagged proteins. For FFS, together with the benefit of the reduced laser power, we show that cooling the detector is necessary to remove artifacts in the correlation function, such as spurious negative correlations observed in the hot elements of the detector, i.e., elements whose dark-noise is substantially higher than the median value. Overall, this detector represents a further step towards the integration of SPAD array detectors in any FLSM system.SIGNIFICANCESingle-photon avalanche diode (SPAD) array detectors are revolutionizing fluorescence laser-scanning microscopy (FLSM). Thanks to their single-photon timing and sensitivity ability and their imaging faculty, a SPAD array detector transforms any FLSM into a super-resolution microscope, and opens a whole range of possibilities for the study of sample dynamics by means of fluorescence fluctuation spectroscopy (FFS). However, dark-noise can be a severe problem for both imaging and FFS. For imaging, the signal overcomes noise only for a relatively high illumination intensity, which can be detrimental for live-cell experiments. For FFS, the noise leads to artifacts in the correlation curves, potentially leading to wrong conclusions about the sample. We show that lowering the temperature of the detector to −15°C solves both problems
Modulating D1 rather than D2 receptor-expressing spiny-projection neurons corresponds to optimal antipsychotic effect
Authors: Yun Seongsik , Yang Ben , Martin Madison M. , Yeh Nai-Hsing , Contractor Anis , Parker Jones G. 
Published: August 2021

AbstractOveractive dopamine transmission in psychosis is predicted to unbalance striatal output via D1- and D2-dopamine receptor-expressing spiny-projection neurons (SPNs). Antipsychotic drugs are thought to re-balance this output by blocking D2-receptor signaling. Here we imaged D1- and D2-SPN Ca2+dynamics in mice to determine the neural signatures of antipsychotic effect. Initially we compared effective (clozapine and haloperidol) antipsychotics to a candidate drug that failed in clinical trials (MP-10). Clozapine and haloperidol normalized hyperdopaminergic D1-SPN dynamics, while MP-10 only normalized D2-SPN activity. Clozapine, haloperidol or chemogenetic manipulations of D1-SPNs also normalized sensorimotor gating. Given the surprising correlation between clinical efficacy and D1-SPN modulation, we evaluated compounds that selectively target D1-SPNs. D1R partial agonism, antagonism, or positive M4 cholinergic receptor modulation all normalized the levels of D1-SPN activity, locomotion, and sensorimotor gating. Our results suggest that D1-SPN activity is a more relevant therapeutic target than D2-SPN activity for the development of effective antipsychotics.
Phenotyping Antidepressant Treatment Response with Deep Learning in Electronic Health Records
Authors: Sheu Yi-han , Magdamo Colin , Miller Matthew , Das Sudeshna , Blacker Deborah , Smoller Jordan W. 
Published: August 2021

ABSTRACTEfficient, accurate phenotyping for antidepressant treatment response in electronic health records (EHRs) could facilitate precision psychiatry applications but remains a challenge. Increasingly, artificial intelligence methods using “deep learning” applied to clinical data have shown promise in complex classification problems. Here, we systematically evaluate the performance of eight deep-learning-based natural language processing models in classifying response to antidepressants in a large real-world healthcare setting. We obtained data spanning 1990-2018 for adults with depression and a co-occurring antidepressant prescription from the EHR data warehouse of the Mass General Brigham healthcare system (n=111,572). Clinical notes were collected for the following time windows after antidepressant initiation: (1) 2 days to 4 weeks, (2) 4–12 weeks, and (3) 12–26 weeks. A stratified random sample of these note sets (total 4,299 across time periods) were manually reviewed to classify response status as “improved” or “no evidence of improvement” in depression symptoms. All models performed well, with areas under the receiver operator curve (AUROC) of at least 0.80. Positive predictive values (PPVs) ranged from 0.72 – 0.91. In general, models incorporating more information-dense and longer text sequences performed better than others. The best performing model (Longformer-large with sliding window) had an AUROC = 0.88 and PPV = 0.84 at a specificity of 0.88. Our results indicate that deep learning methods applied to EHR data can accurately classify antidepressant response in a real-world healthcare setting. Automated treatment response classification may facilitate a range of research and clinical decision support applications.
Assessing ventilation strategies in a school with observed indoor air problems
Authors: Uotila Ulrika , Saari Arto , Junnonen Juha-Matti Kalevi , Eskola Lari 
Published: August 2021

PurposePoor indoor air quality in schools is a worldwide challenge that poses health risks to pupils and teachers. A possible response to this problem is to modify ventilation. Therefore, the purpose of this paper is to pilot a process of generating alternatives for ventilation redesign, in an early project phase, for a school to be refurbished. Here, severe problems in indoor air quality have been found in the school.Design/methodology/approachVentilation redesign is investigated in a case study of a school, in which four alternative ventilation strategies are generated and evaluated. The analysis is mainly based on the data gathered from project meetings, site visits and the documents provided by ventilation and condition assessment consultants.FindingsFour potential strategies to redesign ventilation in the case school are provided for decision-making in refurbishment in the early project phase. Moreover, the research presents several features to be considered when planning the ventilation strategy of an existing school, including the risk of alterations in air pressure through structures; the target number of pupils in classrooms; implementing and operating costs; and the size of the space that ventilation equipment requires.Research limitations/implicationsAs this study focusses on the early project phase, it provides viewpoints to assist decision-making, but the final decision requires still more accurate calculations and simulations.Originality/valueThis study demonstrates the decision-making process of ventilation redesign of a school with indoor air problems and provides a set of features to be considered. Hence, it may be beneficial for building owners and municipal authorities who are engaged in planning a refurbishment of an existing building.
Influences on the career intentions of millennials; a view from the United Arab Emirates
Authors: Kemp Linzi J. , McLoughlin Linda 
Published: August 2021

PurposeThe study aims to discover influences on the career intentions of millennials in the United Arab Emirates (UAE).Design/methodology/approachQualitative data about career intentions were collected from a sample group (#50) of students at an international university in the UAE. Participant's responses were recorded in five groups, composed of undergraduates, males and females, expatriates and citizens. Transcripts were formed of these data, which were thematically analysed to identify influences on career intentions.FindingsFour emergent themes were identified of influences on career intentions: (1) influenced by societal obligations, (2) influenced by a traditional approach to career plans; (3) influenced by own aspirations; (4) influenced by country considerations. Findings recognised career intentions for this sample group resulted from cultural orientation and millennial's characteristics.Research limitations/implicationsThe study was limited by the one country/one university context and a direction is to replicate for an expanded sample group and/or to extend this research scope to other countries.Practical implicationsThese findings have implications for university career advising, and the recruitment and retention of millennials in the UAE by international companies.Originality/valueThis is an original study in its exploration of influences on millennial's career intentions in the UAE. Research value lies in the addition of academic knowledge about those millennials' future career intentions.
Coffee tourism in Portugal: an attraction case study
Authors: Dinis Maria Gorete , Melo Carla Salgueiro , Sousa João Miguel Batista Miguéns 
Published: August 2021

Purpose
This paper aims to demonstrate how attractions and experiences associated with coffee can contribute to dissemination and knowledge of its culture and to the development of coffee tourism in Portugal.

Design/methodology/approach
A case study methodology is applied, focusing on the Coffee Science Centre – Delta Interpretation, Scientific and Technological Promotion and Tourism Promotion Centre (CCC).

Findings
Results indicate that this type of attraction can be used to disseminate coffee culture by providing differentiating and enriching experiences to tourists, and most importantly, by developing tourism in a sustainable way.

Originality/value
This study contributes to expanding the knowledge on coffee tourism, an under-explored field of study, particularly in Portugal, where to the authors knowledge, there is no applied research within this scope.
A priority action roadmap for women's economic empowerment (PARWEE) amid COVID-19: a co-creation approach
Authors: Bonin Sandrine , Singh Wafa , Suresh Veena , Rashed Tarek , Uppaal Kuiljeit , Nair Rajiv , Bhavani Rao R. 
Published: August 2021

Purpose
The study aims to co-create a “priority action roadmap for women's economic empowerment” based on women's top priorities to charting recovery directions. Doing so contributes to the growing body of knowledge on COVID-19 literature in at least four areas: assessing COVID-19 impacts on women entrepreneurs; mapping these impacts with four interdependent women's entrepreneurial ecosystem components; innovating a co-creation methodology based on remote participatory research; and providing a replicable model to perform action-oriented research in the context of COVID-19 impacts.

Design/methodology/approach
A co-creation methodology is proposed, combining systems-thinking and remote participatory research to engage women entrepreneurs and institutional stakeholders to prioritize impact, response actions and recovery needs in the wake of COVID-19. A ranking exercise using the analytic hierarchy process was used to derive ranking and assess user inputs' consistency.

Findings
The study exemplifies the integration of participatory methods and mathematical tool to engage stakeholders in prioritizing recovery work. PARWEE action items ranked by entrepreneurs and vetted by institutional stakeholders cover: access to finances, capacity building, health care, public and private partnership, marketing opportunities and formation of active advocacy groups to voice out women entrepreneurs' needs to institutional stakeholders. Results show a slight difference in the ranking of priority actions between experience owners and fresh starters.

Originality/value
This study innovated a new co-creation methodology for remotely engaging stakeholders of the women's entrepreneurial ecosystem, which is grounded in evidence and provides a replicable model for performing action-oriented research.
Optimized scheduling techniques focused on powerful heuristics leveraging cloud services soft computing
Authors: P. Veerendra , Rao Thirupathi 
Published: August 2021

Purpose
Determining the roles of multiple CSPs is important because it affects job costs and time off. The primary objective of this work is to ensure an efficient and complex distribution of resources in cloud-based computing. Workflow study of various algorithms such as ant colony optimization (ACO), differential evolution algorithm, genetic algorithm, particle swarm optimization (PSO), hybridization of the above algorithms (ADGP). For research, CSP’s tools are put all over the world.

Design/methodology/approach
The main objective of this study is to effectively introduce cloud-based computing in CSPs. The algorithm minimizes resource response time and overall workflow tasks. It seeks to improve load balancing by modifying the algorithm to support load balancing. In the proposed multipurpose scheduling methods, the ADGP algorithm performs better than any other proposed algorithm during the resource response. This algorithm was found to be superior to the selected 200 sources and thousands of tasks. It reduces resource response time by copying service nodes through several sites. As this algorithm moves faster to the best solution, the response time of the resource is reduced compared to other algorithms.

Findings
Hybrid ACOs perform best when it comes to resource management when workloads are uniformly spread across multiple virtual machines. However, hybrids PSOs are better suited to choosing the best options to minimize costs. Overall, an optimal cloud-based scheduling solution can be successfully simulated using CloudSim in CSP to share resources between end-users to support consumers and users effectively.

Originality/value
Hybrid ACOs perform best when it comes to resource management when workloads are uniformly spread across multiple virtual machines. However, hybrids PSOs are better suited to choosing the best options to minimize costs. Overall, an optimal cloud-based scheduling solution can be successfully simulated using CloudSim in CSP to share resources between end-users to support consumers and users effectively.
Business to business (B2B) alliances in the healthcare industry: a review of research trends and pertinent issues
Authors: Madanaguli Arun Thirumalesh , Dhir Amandeep , Talwar Shalini , Singh Gurmeet , Escobar Octavio 
Published: August 2021

Purpose
This study aims to find, analyse and synthesise the body of literature on how different health-care businesses form business-to-business (B2B) alliances. By doing so, this study seeks to identify visible research gaps to suggest future research questions and develop a conceptual framework to set a future research agenda.

Design/methodology/approach
The study uses the time-tested systematic literature review method to identify 57 studies that have addressed B2B relationships in the health-care industry. Thereafter, a qualitative analysis is performed to delineate the research profile and synthesise the key themes examined in the selected studies.

Findings
The qualitative analysis uncovers two key thematic foci: types and purposes of B2B relationships and pertinent issues in continued B2B relationships. Within these themes, the authors highlight different types of firms and their reasons for engaging in B2B relationships. The authors also summarise various issues that these firms deal with in such relationships. Finally, the authors highlight the limitations in the existing research and suggest future research questions to address them. The findings are summarised in a conceptual framework.

Originality/value
Although several reviews exist that evaluate the state-of-the-art research on B2B relationships, very few have examined the same in the context of health care. This review adds value to the research by providing a comprehensive overview of the existing findings in the area to encourage future research through a conceptual framework.