bluuebunny/crossref_metadata_2025_split huggingface dataset:
vPro-MS enables identification of human-pathogenic viruses from patient samples by untargeted proteomics
Authors: Grossegesse Marica , Horn Fabian , Kurth Andreas , Lasch Peter , Nitsche Andreas , Doellinger Joerg 
Published: August 2024

AbstractViral infections are commonly diagnosed by the detection of viral genome fragments or proteins using targeted methods such as PCR and immunoassays. In contrast, metagenomics enables the untargeted identification of viral genomes, expanding its applicability across a broader spectrum. In this study, we introduce proteomics as a complementary approach for the untargeted identification of human-pathogenic viruses from patient samples. The viral proteomics workflow (vPro-MS) is based on anin-silicoderived peptide library covering the human virome in UniProtKB (331 viruses, 20,386 genomes, 121,977 peptides), which was especially designed for diagnostic purposes. A scoring algorithm (vProID score) was developed to assess the confidence of virus identification from proteomics data (https://github.com/RKI-ZBS/vPro-MS). In combination with high-throughput diaPASEF-based data acquisition, this workflow enables the analysis of up to 60 samples per day. The specificity was determined to be > 99,9 % in an analysis of 221 plasma, swab and cell culture samples covering 18 different viruses (e.g. SARS, MERS, EBOV, MPXV). The sensitivity of this approach for the detection of SARS-CoV-2 in nasopharyngeal swabs corresponds to a PCR cycle threshold of 27 with comparable quantitative accuracy to metagenomics. vPro-MS enables the integration of untargeted virus identification in large-scale proteomic studies of biofluids such as human plasma to detect previously undiscovered virus infections in patient specimens.
ActSort: An active-learning accelerated cell sorting algorithm for large-scale calcium imaging datasets
Authors: Jiang Yiqi , Akengin Hakki O. , Zhou Ji , Aslihak Mehmet A. , Li Yang , Hernandez Oscar , Ebrahimi Sadegh , Zhang Yanping , Inan Hakan , Jaidar Omar , Miranda Christopher , Dinc Fatih , Blanco-Pozo Marta , Schnitzer Mark J. 
Published: August 2024

AbstractRecent advances in calcium imaging enable simultaneous recordings of up to a million neurons in behaving animals, producing datasets of unprecedented scales. Although individual neurons and their activity traces can be extracted from these videos with automated algorithms, the results often require human curation to remove false positives, a laborious process calledcell sorting. To address this challenge, we introduce ActSort, an active-learning algorithm for sorting large-scale datasets that integrates features engineered by domain experts together with data formats with minimal memory requirements. By strategically bringing outlier cell candidates near the decision boundary up for annotation, ActSort reduces human labor to about 1–3% of cell candidates and improves curation accuracy by mitigating annotator bias. To facilitate the algorithm’s widespread adoption among experimental neuroscientists, we created a user-friendly software and conducted a first-of-its-kind benchmarking study involving about 160,000 annotations. Our tests validated ActSort’s performance across different experimental conditions and datasets from multiple animals. Overall, ActSort addresses a crucial bottleneck in processing large-scale calcium videos of neural activity and thereby facilitates systems neuroscience experiments at previously inaccessible scales.
Surfactant-laden bubble bursting: Dynamics of capillary waves and Worthington jet at large Bond number
Authors: Pico P. , Kahouadji L. , Shin S. , Chergui J. , Juric D. , Matar O. K. 
Published: August 2024

We present a numerical study of the main substages preceding aerosol formation via bursting bubbles: capillary wave propagation along the bubble, convergence at the bubble's apex, and the ascent of a Worthington jet and its breakup to release liquid drops. We focus on two crucial yet overlooked aspects of the system: the presence of surface-active agents and dynamics driven by non-negligible gravitational effects, quantified by the Bond number. Our results propose a mechanism explaining capillary wave retardation in the presence of surfactants, involving the transition from bi- to unidirectional Marangoni stresses, which pull the interface upwards, countering the motion of the waves. We also quantitatively elucidate the variable nature of the waves' velocity with various surfactant parameters, including surfactant solubility and elasticity, a departure from the constant behavior well documented in clean interfaces.

Published by the American Physical Society
2024
Exploring healthcare professional’s engagements and experiences towards people who use new psychoactive substances in different addiction and mental healthcare services
Authors: Solomon David , Guirguis Amira 
Published: August 2024

Purpose
New psychoactive substance (NPS) use in mental health and addiction health-care services is a common co-morbidity. This paper aims to explore the survey responses with health-care professional’s (HCPs) engagements and experiences towards people who use NPS in five health-care services.

Design/methodology/approach
A theoretically adapted online survey design explored the engagements and experiences of participants towards people who use NPS across (n = 3) community and (n = 2) rehabilitation mental health and addiction health-care services consisting of (n = 1,027) service users.

Findings
A total of 92 participants (of 120 participants) completed the survey and 28 did not. Most (56.33%) reported neutral to poor experiences and engagements and a lack of NPS-related policies, procedures and educational training. Participants (99%) recognised the harmful effects of NPSs and (87%) requested clinical assessment procedures. The participants are unable to identify and manage acute intoxication by NPS, lack knowledge of NPS adverse effects and requested NPS-specific training on drug legislation.

Research limitations/implications
The sample may not be representative with the broader UK population. The study’s methods are comparable to similar research surrounding NPS in health-care services. Similar studies may advance the findings.

Practical implications
The implications for practice include NPS awareness trainings, educational updates through seminars and conferences. Participants requested clearer NPS assessment, referral and management processes. Several policy-making and procedural opportunities exist to ensure a better health outcome for people who use NPS.

Originality/value
To the best of the authors’ knowledge, this is the first theoretically adapted survey to explore participant’s engagements and experiences with people who use NPS in addiction and mental health settings.
Distributed safety flight control for LAV swarm in a hostile environment under multi-constraints and sudden appearing risks
Authors: Zhao Meijiao , Wang Yidi , Zheng Wei 
Published: August 2024

Purpose
Loitering aerial vehicle (LAV) swarm safety flight control is an unmanned system control problem under multiple constraints, which are derived to prevent the LAVs from suffering risks inside and outside the swarms. The computational complexity of the safety flight control problem grows as the number of LAVs and of the constraints increases. Besides some important constraints, the swarms will encounter with sudden appearing risks in a hostile environment. The purpose of this study is to design a safety flight control algorithm for LAV swarm, which can timely respond to sudden appearing risks and reduce the computational burden.

Design/methodology/approach
To address the problem, this paper proposes a distributed safety flight control algorithm that includes a trajectory planning stage using kinodynamic rapidly exploring random trees (KRRT*) and a tracking stage based on distributed model predictive control (DMPC).

Findings
The proposed algorithm reduces the computational burden of the safety flight control problem and can fast find optimal flight trajectories for the LAVs in a swarm even there are multi-constraints and sudden appearing risks.

Originality/value
The proposed algorithm did not handle the constraints synchronously, but first uses the KRRT* to handle some constraints, and then uses the DMPC to deal with the rest constraints. In addition, the proposed algorithm can effectively respond to sudden appearing risks by online re-plan the trajectories of LAVs within the swarm.
Sustainability reporting assurance practice in Indonesia: assuror and academician perspective
Authors: Kurniawan Putu Sukma , Basuki Basuki 
Published: August 2024

Purpose
This study aims to uncover fundamental challenges pertaining to sustainability reporting assurance practice (SRAP) in Indonesia. This study uses assuror and academician perspectives to examine the SRAP discourse in Indonesia.

Design/methodology/approach
The research method was qualitative approach by conducting online semi-structured interviews with ten informants, including four from assuror representatives and six from academician representatives. Qualitative data analysis, such as codification process and data triangulation, was used to understand the opinions of each informant and to develop a comprehensive discussion.

Findings
This study has identified the issues in the context of SRAP in Indonesia. Several recommendations have been made for the relevant stakeholders to improve the quality of SRAP in the Indonesian context.

Practical implications
The results of this study can be used by the stakeholders to improve the quality of SRAP in Indonesia.

Social implications
The results of this study can be used by the stakeholders in Indonesia, for example, the authority of the financial services industry, to formulate policies related to SRAP in Indonesia.

Originality/value
There are still few previous studies that include an academician’s perspective related to the SRAP and examine SRAP in a developing country context.
Using photovoice to investigate the impact of place attachment on community resilience in Iceland
Authors: Lyons Aine , Gísladóttir Jóhanna , Kokorsch Matthias 
Published: August 2024

PurposeGlobally, climate change is exacerbating the impacts of climate-related, natural hazards including avalanches. However, there is limited knowledge about how small and remote communities are affected by and perceive the effects of a changing climate with hazards that increase in intensity and/or frequency. Consequently, there is a call for more actionable and interdisciplinary climate adaptation research, which takes its starting point in understanding the local concerns of people living in small remote communities.Design/methodology/approachThis paper test the photovoice method to gather respondents’ perceptions of the place in which they live and the hazards they face through personal narratives of photographs.FindingsDespite its limitations, the photovoice method was found to be a suitable tool for gaining valuable insights into the communities while ensuring comfort and enjoyment for both participants and the researcher.Research limitations/implicationsThe findings also show that despite its limitations photovoice is a useful method for shedding light on risk perception, place attachment and resiliency in communities facing the risk of natural hazards. The study found that place attachment is an important factor to consider in disaster risk management, policy and decision making.Originality/valueThe paper adds to a growing body of literature surrounding the relationship between place attachment and community resilience to climate-related natural hazards. The authors examined the impact of place attachment on community resilience, focusing on two rural and remote villages located in the Westfjords in Iceland – Patreksfjörður and Flateyri. Societal aspects of natural hazards have hitherto been hardly addressed in Iceland and to our knowledge the applied method has not been tested before in such a setting. The photovoice method is tested to gather respondents’ perceptions of the place in which they live and the hazards they face through personal narratives of photographs.
Multi-dimensional feature fusion-based expert recommendation in community question answering
Authors: Ye Guanghui , Li Songye , Wu Lanqi , Wei Jinyu , Wu Chuan , Wang Yujie , Li Jiarong , Liang Bo , Liu Shuyan 
Published: August 2024

Purpose
Community question answering (CQA) platforms play a significant role in knowledge dissemination and information retrieval. Expert recommendation can assist users by helping them find valuable answers efficiently. Existing works mainly use content and user behavioural features for expert recommendation, and fail to effectively leverage the correlation across multi-dimensional features.

Design/methodology/approach
To address the above issue, this work proposes a multi-dimensional feature fusion-based method for expert recommendation, aiming to integrate features of question–answerer pairs from three dimensions, including network features, content features and user behaviour features. Specifically, network features are extracted by first learning user and tag representations using network representation learning methods and then calculating questioner–answerer similarities and answerer–tag similarities. Secondly, content features are extracted from textual contents of questions and answerer generated contents using text representation models. Thirdly, user behaviour features are extracted from user actions observed in CQA platforms, such as following and likes. Finally, given a question–answerer pair, the three dimensional features are fused and used to predict the probability of the candidate expert answering the given question.

Findings
The proposed method is evaluated on a data set collected from a publicly available CQA platform. Results show that the proposed method is effective compared with baseline methods. Ablation study shows that network features is the most important dimensional features among all three dimensional features.

Practical implications
This work identifies three dimensional features for expert recommendation in CQA platforms and conducts a comprehensive investigation into the importance of features for the performance of expert recommendation. The results suggest that network features are the most important features among three-dimensional features, which indicates that the performance of expert recommendation in CQA platforms is likely to get improved by further mining network features using advanced techniques, such as graph neural networks. One broader implication is that it is always important to include multi-dimensional features for expert recommendation and conduct systematic investigation to identify the most important features for finding directions for improvement.

Originality/value
This work proposes three-dimensional features given that existing works mostly focus on one or two-dimensional features and demonstrate the effectiveness of the newly proposed features.
Development of a personalized mask design method using three-dimensional scan data
Authors: Kang Yeonghoon , Jung Gyungin , Kim Sungmin 
Published: August 2024

Purpose This study aims to develop a novel design method to make personalized masks for the effective prevention of pandemic respiratory infectious disease.Design/methodology/approachThe changes in facial shape during speaking were analyzed using a three-dimensional (3D) scanning technique. In total, 13 anthropometric items were measured, and mask patterns were generated using a parametric pattern design method. Three sizing methods were proposed to reflect not only static but also dynamic body dimensions on the mask patterns.FindingsA significant increase or decrease was observed in 10 out of 13 measurement items. Based on this, four items were selected to be used in the mask pattern design. The nose and cheek areas of a mask were fixed to protect the respiratory tract against viruses. The lower jaw area was deformed to improve the fit.Social implicationsThis study is expected to provide fundamental data to understand the changes in facial shape during movement. In addition, it is expected that the development of individualized personal protective equipment with movement adaptability will facilitate an effective response to various pandemic respiratory diseases.Originality/valueIn order to develop a personal protective equipment (PPE) that has a good fit and can protect against pandemic respiratory infectious diseases, morphological analysis was attempted using 3D facial data. It would be possible to design various products and equipment to be worn on the face by using the method proposed in this study.
Impacts of institutional pressures and internal abilities on green performance of transport and logistics companies
Authors: Layaoen Haerold Dean , Abareshi Ahmad , Abdulrahman Muhammad Dan-Asabe , Abbasi Babak 
Published: August 2024

PurposeTransport and logistics companies (TLCs) have adopted green practices to reduce their emission and waste in support of environmental protection requirements. However, not all green practices of TLCs have resulted in green performance (GP) because of inherent variations in internal abilities and external factors affecting firms in different operational environments. Using institutional (INT) and resource-based view (RBV) theories we develop a model that shows how institutional pressures and internal abilities impact TLCs’ GP.Design/methodology/approach Underpinned by INT and RBV theories, this study utilised structural equation modelling on a cross-sectional survey of 222 TLC firms operating in the Philippines.Findings The study reveals that TLCs’ regulatory compliance, social obligations and competitor pressures have significant direct effects on TLCs’ GP while supplier integration and resource capabilities serially mediate the relationships. The findings indicate that institutional pressures and internal abilities that shape firms’ environmental policies and procedures explain TLCs’ GP.Research limitations/implications As a result of the cross-sectional nature of our data, findings may be time, population and prevailing situation dependent. The long-term validity of the research can be improved if longitudinal design is employed. We collected data from a single respondent considered as the best respondent. However, with time and resource availability, a jury of executives for each company would have been a better alternative respondent.Practical implications The findings of this research provide TLC managers, policymakers and other stakeholders with much-needed guidance for crafting policies and strategies for handling the challenges of caring for the planet and maintaining sustainable operations.Social implications Improving green practices of TLCs to enable waste and emission reductions is critical to the health and well-being of people and the planet. An environment free of pollution will result in fewer health challenges, fewer medical/insurance-related expenses, and, above all, enable a higher quality of life and a more productive workforce.Originality/value Studies have extensively explored the green practices of TLCs as well as the influences of both institutional pressures and internal abilities of TLCs on their green practices. This study identifies critical factors that significantly affect the GP of TLCs and provides a conceptual framework for a better understanding of the dynamics of strategic, tactical and operational issues that TCLs may face in their effort at greening the sector.
Feedback, training, goal-setting, planning and performance: understanding the pathway to improved organizational outcomes
Authors: Chowhan James , Mann Sara , Budworth Marie-Hélène 
Published: August 2024

PurposeAs competitive pressures persist and global economic influences continue to present new challenges, businesses need to be able to respond to emerging circumstances. Goal-setting and planning are key mechanisms contributing to organizational competitive success, yet organizations underappreciate the role of competency and capacity building factors that contribute to successful planning. This paper integrates three theoretical models enabling an investigation into the positive relationships between managerial activities generating information feedback, training in planning and skills and organizational performance outcomes, while exploring the positive mediating roles of goal-setting and planning.Design/methodology/approachA unique organizational sample of agribusiness producers (n = 499) in Canada is examined. A structural equation path analysis model is used to evaluate the main relationships.FindingsThe results suggest that organizations are finding that managerial and training activities should not be considered in isolation, but rather as supports for goal-setting, planning and performance outcomes. Thus, the implications are that managers can find organizational value enhanced through the building of human resource competency (e.g. management activities and training) with these emerging capacities aiding goal setting and planning activities.Originality/valueThis study makes three main contributions: first, by adopting a rational-design perspective and integrating theoretical frameworks focusing on (a) planning-performance and (b) goal-setting-planning. This extended model goes beyond previous studies by including managerial activities, training, goals, planning and performance outcomes. Second, this study uniquely accounts for a more comprehensive set of key confounding factors such as operational activities, organizational strategy and organizational size in the integrated framework. Finally, as far as the authors are aware, there has not been a survey study at the organizational level that has explored the role of managerial activities and training in planning within a similarly comprehensive model.
Weight gain and social support networks in Canadian federal correctional facilities
Authors: Johnson Claire , Dupuis Jérémie B. , Robichaudb Wendjie , Pone Edwige Kamwa , LeBlanc Caroline P. 
Published: August 2024

Purpose
This study aims to examine whether inmate’s social support network is related to changes in anthropometric data among individuals in Canadian correctional facilities.

Design/methodology/approach
Methods: A total of 754 participants in federal correctional facilities who had been incarcerated for at least six months responded to the questionnaire by interview regarding their social support network. Chi-square tests and non-parametric tests for median comparison were used to measure changes in anthropometric data [weight and body mass index (BMI)] between the date of admission into custody and the date of the interview. Subsequently, a multivariate regression analysis for BMI change was conducted to adjust for covariates such as sex, age and ethnicity.

Findings
Results: Participants who received more than two visits per month had significantly lower weight gain (2.6 kg) than those who received less than one visit per month (7.1 kg, p = 0.02). Similar results were observed for the average change in BMI (p = 0.01). The influence of an external social support network on BMI change remained significant after adjusting for covariates. Conclusions: An individual's external social support network (outside the prison environment) may protect against weight gain in correctional facilities. Given how social support will vary based on the prison context by country and jurisdiction, individual and organizational strategies should be considered to maintain a healthy social support network and increase the number of visits (at every stage of incarceration) to counteract this weight gain and its adverse health consequences.

Originality/value
The social support network outside the prison environment may protect against weight gain in correctional facilities. Strategies should be considered to maintain a healthy social support network and increase the number of visits to counteract this weight gain and its adverse health consequences.