bluuebunny/crossref_metadata_2025_split huggingface dataset:
GPT-4, an artificial intelligence large language model, exhibits high levels of accuracy on dermatology specialty certificate exam questions
Authors: Shetty Meghna , Ettlinger Michael , Lynch Magnus 
Published: July 2023

AbstractArtificial Intelligence (AI) has shown considerable potential within medical fields including dermatology. In recent years a new form of AI, large language models, has shown impressive performance in complex textual reasoning across a wide range of domains including standardised medical licensing exam questions. Here, we compare the performance of different models within the GPT family (GPT-3, GPT-3.5, and GPT-4) on 89 publicly available sample questions from the Dermatology specialty certificate examination. We find that despite no specific training on dermatological text, GPT-4, the most advanced large language model, exhibits remarkable accuracy - answering in excess of 85% of questions correctly, at a level that would likely be sufficient to pass the SCE exam.
Consequences of Heterogeneity in Aging: Parental Age at Death Predicts Midlife All-Cause Mortality and Hospitalization in a Swedish National Birth Cohort
Authors: Thalén Anna , Ledberg Anders 
Published: July 2023

BackgroundThe processes that underlie aging may advance at different rates in different individuals and an advanced biological age, relative to the chronological age, is associated with increased risk of disease and death. Here we set out to quantify the extent to which heterogeneous aging shapes health outcomes in midlife by following a Swedish birth-cohort and using parental age at death as a proxy for biological age in the offspring.MethodsWe followed a nationwide Swedish birth cohort (N= 89 688) between the ages of 39 to 66 with respect to hospitalizations and death. Cox regressions were used to estimate the association, in the offspring, between parental age at death and all-cause mortality, as well as hospitalization for conditions belonging to one of 10 different ICD-10 chapters.ResultsLonger parental lifespan was consistently associated with reduced risks of hospitalization and all-cause mortality. Differences in risk were mostly evident before the age of 50. Each additional decade of parental survival decreased the risk of offspring all-cause mortality by 22% and risks of hospitalizations by 9 to 20 percent across the ten diseases categories considered. The number of deaths and hospitalizations attributable to having parents not living until old age were 1500 (22%) and 11000 (11%) respectively.ConclusionsOur findings highlight that increased parental lifespan is consistently associated with health benefits in the offspring across multiple outcomes and suggests that heterogeneous aging processes have clinical implications already in midlife.
Position: a study protocol for the prevention of fall injuries in French Special Forces selection courses using a body-centered intervention
Authors: Obligi Loucas , Bertrand Mathieu , Boivent Mathieu , Corcostegui Simon-Pierre , Coz Pierre-Emmanuel , Derkenne Clément , Des Robert Vincent , Hurpin Victor , Hus Jauffrey , L’Hermitte Benoît , Lely Laurent , Patey Edouard , Romary Emeric , Saint-Jean Luc , Trente Alexandre , Turpin Marine , Vertu Nicolas , Verdonk Charles , Duffaud Anaïs M. 
Published: July 2023

IntroductionThe Military Physical and Sports Training program was developed by the French Army in order to train, optimize, and maintain individual readiness. Although the health benefits of sport practice do not need to be demonstrated, such activities can cause acute musculoskeletal injuries that need to be addressed. The prevalence of lower limb injury is rather high in the French military population and, in particular, ranges from 15 to 45% during Special Forces selection courses. Thus, this project aims to investigate the efficiency of a body-centered program designed to enhance body awareness. The program seeks to train the mind to actively pay attention to body information, while the latter is viewed as a protective factor against fall injuries. We assume: (i) that postural control can be improved by enhancing the level of body awareness; and (ii) that greater postural awareness could be beneficial in reducing the risk of fall injuries. The body-centered prevention program is based on the Optimization of the Resources of the Armed Forces (ORAF) intervention, which focuses on mental preparation and recovery, and has been deployed in the French Army for many yearsMethod and analysesThe study focuses on five French Special Forces selection courses (400 soldiers/ participants). It is divided into two stages (year 1, year 2). The first year is dedicated to data collection from the control group (200 participants), while in the second year the ORAF intervention will be deployed. The main objective is to evaluate the effectiveness of the ORAF intervention in reducing the rate of fall injuries during military selection, based on a multidisciplinary method that captures demographic, biological, biometric, clinical, and para clinical measures.Registration numberIDRCB number 2021-A02108-33, Clinical Trial: NCT 05451394
Pooled endogenous protein tagging and recruitment for scalable discovery of effectors for induced proximity therapeutics
Authors: Serebrenik Yevgeniy V. , Mani Deepak , Maujean Timothé , Burslem George M. , Shalem Ophir 
Published: July 2023

AbstractThe field of induced proximity therapeutics is in its ascendancy but is limited by a lack of scalable tools to systematically explore effector-target protein pairs in an unbiased manner. Here, we combined Scalable POoled Targeting with a LIgandable Tag at Endogenous Sites (SPOTLITES) for the high-throughput tagging of endogenous proteins, with generic small molecule-based protein recruitment to screen for novel proximity-based effectors. We apply this methodology in two orthogonal screens for targeted protein degradation: the first using fluorescence to monitor target protein levels directly, and the second using a cellular growth phenotype that depends on the degradation of an essential protein. Our screens revealed a multitude of potential new effector proteins for degradation and converged on members of the CTLH complex which we demonstrate potently induce degradation. Altogether, we introduce a platform for pooled induction of endogenous protein-protein interactions that can be used to expand our toolset of effector proteins for targeted protein degradation and other forms of induced proximity.
Mimicking Kidney Flow Shear Efficiently Induces Aggregation of LECT2, a Protein Involved in Renal Amyloidosis
Authors: Ha Jeung-Hoi , Xu Yikang , Sekhon Harsimranjit , Wilkens Stephan , Ren Dacheng , Loh Stewart N. 
Published: July 2023

AbstractAggregation of leukocyte cell-derived chemotaxin 2 (LECT2) causes ALECT2, a systemic amyloidosis that affects the kidney and liver. Homozygosity of the I40V LECT2 mutation is believed to be necessary but not sufficient for the disease. Previous studies established that LECT2 fibrillogenesis is greatly accelerated by loss of its single bound zinc ion and stirring or shaking. These forms of agitation are often used to facilitate protein aggregation, but they create heterogeneous shear conditions, including air-liquid interfaces that denature proteins, that are not present in the body. Here, we determined the extent to which a more physiological form of mechanical stress—shear generated by fluid flow through a network of artery and capillary-sized channels—drives LECT2 fibrillogenesis. To mimic blood flow through the human kidney, where LECT2 and other proteins form amyloid deposits, we developed a microfluidic device consisting of progressively branched channels narrowing from 5 mm to 20 μm in width. Flow shear was particularly pronounced at the branch points and in the smallest capillaries, and this induced LECT2 aggregation much more efficiently than conventional shaking methods. EM images suggested the resulting fibril structures were different in the two conditions. Importantly, results from the microfluidic device showed the first evidence that the I40V mutation accelerated fibril formation and increased both size and density of the aggregates. These findings suggest that kidney-like flow shear, in combination with zinc loss, acts in combination with the I40V mutation to trigger LECT2 amyloidogenesis. These microfluidic devices may be of general use for uncovering the mechanisms by which blood flow induces misfolding and amyloidosis of circulating proteins.
Polyubiquitinated PCNA promotes alternative lengthening of telomeres by inducing break-induced replication
Authors: Kim Sangin , Kang Nalae , Ra Jae Sun , Park Su Hyung , Myung Kyungjae , Lee Kyoo-young 
Published: July 2023

AbstractReplication stresses are the major source of break-induced replication (BIR). Here, we show that in alternative lengthening of telomeres (ALT) cells, replication stress-induced polyubiquitinated PCNA (polyUb-PCNA) triggers BIR at telomeres and the common fragile site (CFS). Consistently, depleting RAD18, a PCNA ubiquitinating enzyme, reduces the occurrence of ALT-associated PML bodies (APBs) and mitotic DNA synthesis at telomeres and CFS, both of which are mediated by BIR. In contrast, inhibiting USP1, an Ub-PCNA deubiquitinating enzyme, results in an increase in the above phenotypes in a RAD18- and UBC13 (the PCNA polyubiquitinating enzyme)-dependent manner. Furthermore, deficiency of ATAD5, which facilitates USP1 activity and unloads PCNAs, augments recombination-associated phenotypes. Mechanistically, telomeric polyUb-PCNA accumulates SLX4, a nuclease scaffold, at telomeres through its ubiquitin-binding domain and increases telomere damage. Consistently, APB increase induced by Ub-PCNA depends on SLX4 and SLX4-associated nucleases. Taken together, our results identified the polyUb-PCNA-SLX4 axis as a trigger for directing BIR.
How effective are UK-based support interventions and services targeted at adults who have experienced domestic and sexual violence and abuse at improving their safety and wellbeing? A systematic review protocol
Authors: Carlisle Sophie , Bunce Annie , Prina Matthew , McManus Sally , Barbosa Estela , Feder Gene , Lewis Natalia 
Published: July 2023

AbstractBackgroundDomestic and sexual violence and abuse (DSVA) is prevalent in the UK, with wide-ranging impacts both on individuals and society. However, to date, there has been no systematic synthesis of the evidence for the effectiveness of UK-based support interventions and services for victim-survivors of DSVA. This review will aim to systematically collate, synthesise and quality assess the evidence regarding the effectiveness of UK support interventions and services targeted at those who have experienced DSVA. The review will use findings of a preliminary scoping review, as well as input from stakeholders representing domestic and sexual violence third sector organisations to identify and prioritise the most relevant outcomes to focus on.MethodsWe will undertake a systematic search for peer-reviewed literature in MEDLINE, EMBASE, PsycINFO, Social Policy and Practice, Applied Social Sciences Index and Abstracts (ASSIA), International Bibliography of the Social Sciences (IBSS), Sociological abstracts and SSCI. Grey literature will be identified by searching grey literature databases, circulating a call for evidence to local and national DSVA charities and organisations, and targeted website searching. Two reviewers will independently perform study selection and quality appraisal, with data extraction undertaken by one reviewer and checked for accuracy by a second reviewer. Narrative synthesis will be conducted, with meta-analysis if possible.DiscussionExisting individual studies and evaluations have reported positive impacts of support interventions and services for those who have experienced DSVA. Thus, it is expected that this review and synthesis will provide robust and conclusive evidence of these effects. It will also allow comparisons to be made between different types of support interventions and services, to inform policy makers and funders regarding the most effective ways of reducing domestic and sexual violence and abuse and its impacts.
Satisfaction with information services among individuals in China’s urban communities during the COVID-19 pandemic
Authors: Shen Wang , Wang Junyao , Feng Xin , He Yuming 
Published: July 2023

Purpose
This paper aims to study individuals’ information service satisfaction during the COVID-19 pandemic lockdown in China’s urban communities.

Design/methodology/approach
The researchers analyse people’s uncertainties during the pandemic and argue that uncertainties caused by the lockdown can negatively affect people. By reducing people’s uncertainty during the pandemic, community staff members can improve individuals’ information service satisfaction and social order. This study constructs a conceptual model that includes key transparency and self-disclosure constructs and their relationships that can contribute to the trust and satisfaction of the community information service phenomenon. The researchers collected 489 responses to test their hypothesis from an online survey of Chinese residents in areas where the strict lockdown policy was implemented.

Findings
The empirical results show that policy and goods information transparency significantly affect information service satisfaction in a positive way, with goods information transparency having the highest impact. Second, self-disclosure of community staff members is also an effective way to increase information service satisfaction. Finally, trust plays a mediating role in the influence of information transparency and self-disclosure on information service satisfaction.

Originality/value
This paper innovatively uses uncertainty reduction theory to examine the effects of information transparency and self-disclosure on satisfaction with community information services. It expands the research in the field of information service satisfaction and extends the scope of the research subjects of self-disclosure.
Interval multi-objective grey wolf optimization algorithm based on fuzzy system
Authors: Lin Youping 
Published: July 2023

PurposeThe interval multi-objective optimization problems (IMOPs) are universal and vital uncertain optimization problems. In this study, an interval multi-objective grey wolf optimization algorithm (GWO) based on fuzzy system is proposed to solve IMOPs effectively.Design/methodology/approachFirst, the classical genetic operators are embedded into the interval multi-objective GWO as local search strategies, which effectively balanced the global search ability and local development ability. Second, by constructing a fuzzy system, an effective local search activation mechanism is proposed to save computing resources as much as possible while ensuring the performance of the algorithm. The fuzzy system takes hypervolume, imprecision and number of iterations as inputs and outputs the activation index, local population size and maximum number of iterations. Then, the fuzzy inference rules are defined. It uses the activation index to determine whether to activate the local search process and sets the population size and the maximum number of iterations in the process.FindingsThe experimental results show that the proposed algorithm achieves optimal hypervolume results on 9 of the 10 benchmark test problems. The imprecision achieved on 8 test problems is significantly better than other algorithms. This means that the proposed algorithm has better performance than the commonly used interval multi-objective evolutionary algorithms. Moreover, through experiments show that the local search activation mechanism based on fuzzy system proposed in this study can effectively ensure that the local search is activated reasonably in the whole algorithm process, and reasonably allocate computing resources by adaptively setting the population size and maximum number of iterations in the local search process.Originality/valueThis study proposes an Interval multi-objective GWO, which could effectively balance the global search ability and local development ability. Then an effective local search activation mechanism is developed by using fuzzy inference system. It closely combines global optimization with local search, which improves the performance of the algorithm and saves computing resources.
Implementing Lean Six Sigma in financial services: the effect of motivations, selected methods and challenges on LSS program- and organizational performance
Authors: Vashishth Abhishek , Lameijer Bart Alex , Chakraborty Ayon , Antony Jiju , Moormann Jürgen 
Published: July 2023

PurposeThe purpose of this paper is to contribute to the limited body of empirical knowledge on the impact of Lean Six Sigma (LSS) program implementations on organizational performance in financial services by investigating how antecedents of Lean Six Sigma program success (motivations, selected LSS methods and challenges) affect organizational performance enhancement via LSS program performance.Design/methodology/approachA sample of 198 LSS professionals from 7 countries are surveyed. Structural equation modeling (SEM) is performed to test the questioned relations.FindingsThis study’s findings comprise: (1) LSS program performance partially mediates the relationship between motivations for LSS implementation and organizational performance, (2) selected LSS method applications has a fully (mediated) indirect impact on organizational performance, (3) LSS implementation challenges also have an indirect (mediated) impact on organizational performance and (4) LSS program performance has a positive impact on organizational performance.Originality/valueThe findings of this research predominantly provide nuances and details about LSS implementation antecedents and effects, useful for managers in advising their business leaders about the prerequisites and potential operational and financial benefits of LSS implementation. Furthermore, the paper provides evidence and details about the relationship between important antecedents for LSS implementation identified in existing literature and their impact on organizational performance in services. Thereby, this research is the first in providing empirical, cross-sectional, evidence for the antecedents and effects of LSS program implementations in financial services.
The orchestration of a sustainable development agenda in the European Higher Education Area
Authors: Kushnir Iryna , Eta Elizabeth Agbor , Mbah Marcellus Forh , Kennedy Charlotte-Rose 
Published: July 2023

Purpose
This paper aims to ask how the European Higher Education Area (EHEA) has orchestrated a sustainable development (SD) agenda in its international policy since 2020.

Design/methodology/approach
By drawing on theoretical ideas around policy orchestration as a key UN governing strategy and applying them to the analysis of the progression of the SD agenda in the EHEA, the paper conducts a thematic analysis of six recent key EHEA international policy documents and 19 interviews with key Bologna stakeholders in France, Germany and Italy.

Findings
The resultant analysis uncovers three overarching key themes that show the EHEA has the capacity to mitigate pitfalls in the UN’s SD agenda; some weaknesses of the UN’s orchestration of SD are translated into weaknesses in the EHEA’s formulation of its SD agenda; and the further development of an SD agenda as an essential direction of EHEA’s work. The paper then goes on to discuss how EHEA policies only mention SD discourse, omit concrete plans for its implementation and keep the very meaning of SD ambiguous throughout international policy documents.

Originality/value
The authors offer three original recommendations that the EHEA should adopt in an attempt to mitigate the issues raised in the run-up to its 2030 deadline for implementing its policies: the EHEA should develop an explicit definition of SD; recognise the Euro-centredness of EHEA policies and open them up to other voices; and cite academic research when developing policy documents.
A step toward understanding the association between depressive symptoms and workplace support: documenting the mediating roles of unproductivity and self-disclosure
Authors: Reynolds Samantha , Manata Brian 
Published: July 2023

PurposeIn this manuscript, the authors argue that those suffering from depressive symptoms are prone to experiencing bouts of unproductivity. The authors argue further that such conditions promote instances of self-disclosure regarding related symptoms in the interest of procuring workplace support, i.e. the effect of depressive symptomology on workplace support is mediated by both unproductivity and self-disclosure, in turn.Design/methodology/approachTwo different online investigations were implemented to assess the accuracy of this prediction. Moreover, two different samples of organizational employees from numerous organizations were procured, such that one sample contained diagnosed individuals, whereas the other contained undiagnosed individuals (total N = 756). In general, the main analyses consisted of confirmatory factor analysis and path analysis.FindingsSubstantial statistical support was obtained for the authors' four-variable path model. Specifically, across two different investigations, a model was found in which those with depressive symptoms were unproductive, which prompted self-disclosure and thus subsequent manifestations of workplace support. Moreover, this was generally true for both diagnosed and undiagnosed individuals. Correlation coefficients and model fit indices are reported in the manuscript.Originality/valueThis work contributes substantially to the understanding of how depressive symptomology, self-disclosure and workplace support are interrelated within organizations. In addition, having examined these relationships using a sample of undiagnosed individuals, new insights were gained regarding a subset of the population that remains vastly understudied.
BesNet: binocular ferrographic image recognition model based on deep learning technology
Authors: Xie Fei , Wei Haijun 
Published: July 2023

Purpose
Using computer technology to realize ferrographic intelligent fault diagnosis technology is fundamental research to inspect the operation of mechanical equipment. This study aims to effectively improve the technology of deep learning technology in the field of ferrographic image recognition.

Design/methodology/approach
This paper proposes a binocular image classification model to solve ferrographic image classification problems.

Findings
This paper creatively proposes a binocular model (BesNet model). The model presents a more extreme situation. On the one hand, the model is almost unable to identify cutting wear particles. On the other hand, the model can achieve 100% accuracy in identifying Chunky and Nonferrous wear particles. The BesNet model is a bionic model of the human eye, and the used training image is a specially processed parallax image. After combining the MCECNN model, it is changed to BMECNN model, and its classification accuracy has reached the highest level in the industry.

Originality/value
The work presented in this thesis is original, except as acknowledged in the text. The material has not been submitted, either in whole or in part, for a degree at this or any other university. The BesNet model developed in this article is a brand new system for ferrographic image recognition. The BesNet model adopts a method of imitating the eyes to view ferrography images, and its image processing method is also unique. After combining the MCECNN model, it is changed to BMECNN model, and its classification accuracy has reached the highest level in the industry.

Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0150/