bluuebunny/crossref_metadata_2025_split huggingface dataset:
Subphenotypes of adult‐onset diabetes: Data‐driven clustering in the population‐based KORA cohort
Authors: Dong Qiuling , Xi Yue , Brandmaier Stefan , Fuchs Markéta , Huemer Marie‐Theres , Waldenberger Melanie , Niu Jiefei , Herder Christian , Rathmann Wolfgang , Roden Michael , Koenig Wolfgang , Bönhof Gidon J. , Gieger Christian , Thorand Barbara , Peters Annette , Rospleszcz Susanne , Grallert Harald 
Published: October 2024

AbstractAimsA data‐driven cluster analysis in a cohort of European individuals with type 2 diabetes (T2D) has previously identified four subgroups based on clinical characteristics. In the current study, we performed a comprehensive statistical assessment to (1) replicate the above‐mentioned original clusters; (2) derive de novo T2D subphenotypes in the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) cohort and (3) describe underlying genetic risk and diabetes complications.MethodsWe used data from n = 301 individuals with T2D from KORA FF4 study (Southern Germany). Original cluster replication was assessed forcing k = 4 clusters using three different hyperparameter combinations. De novo clusters were derived by open k‐means analysis. Stability of de novo clusters was assessed by assignment congruence over different variable sets and Jaccard indices. Distribution of polygenic risk scores and diabetes complications in the respective clusters were described as an indication of underlying heterogeneity.ResultsOriginal clusters did not replicate well, indicated by substantially different assignment frequencies and cluster characteristics between the original and current sample. De novo clustering using k = 3 clusters and including high sensitivity C‐reactive protein in the variable set showed high stability (all Jaccard indices >0.75). The three de novo clusters (n = 96, n = 172, n = 33, respectively) adequately captured heterogeneity within the sample and showed different distributions of polygenic risk scores and diabetes complications, that is, cluster 1 was characterized by insulin resistance with high neuropathy prevalence, cluster 2 was defined as age‐related diabetes and cluster 3 showed highest risk of genetic and obesity‐related diabetes.ConclusionT2D subphenotyping based on its sample's own clinical characteristics leads to stable categorization and adequately reflects T2D heterogeneity.
How the Rejection of Incompatible Speech Acts Transforms Human Cognition
Authors: Stovall Preston 
Published: October 2024

AbstractEngaging with the literature on transformative conceptions of rationality, I argue for the following position on the way reason transforms human cognition: when the capacity for knowing that one ought to do something is directed at one's own speech acts, an initially domain‐specific and practical grasp of genus/species relations – manifest in the ability to select among the various permitted ways to do as one judges one ought – becomes a mechanism through which the reflective study of genus/species relations hones the domain‐general classificatory abilities that accompany adult human language use. In this fashion, our instinctive behaviors may be transformed: we might cease to respond to events simply as (e.g.) fearful or enraging, recognize these motivations as cases of cowardice and recklessness, and begin to treat them as opportunities for courage and restraint.
Interpersonal Reasoning: A Philosophical Psychology of Testimonial Trust
Authors: Marušić Berislav 
Published: October 2024

AbstractAnscombe famously said, “It is an insult and it may be an injury not to be believed.” But what is it to believe someone? My aim is to show that understanding what it is to believe someone requires a conception of a distinctive kind of interpersonal reasoning. To do so, I develop an analogy between interpersonal reasoning and an Anscombean conception of practical reasoning. I suggest that the distinctive ‘form’ of interpersonal reasoning is recognition. I furthermore argue that this is to be understood as a primarily logical, rather than epistemological point. In concluding, I explain why a notion of interpersonal reasoning makes available an ethics of thought and, specifically, an account of testimonial injustice.
Planting native trees in degraded grassy woodland does not restore species composition
Authors: Nichols Peter W. B. , Morris E. Charles 
Published: October 2024

SummaryRestoration of degraded former Cumberland Plain Woodland by planting of native trees and shrubs was undertaken by Greening Australia (NSW) on the Cumberland Plain, west of Sydney, Australia, from the mid‐1990s. Our study examined the success of this restoration in stands of two ages using species composition as the criterion. The starting point (pasture) and the target (reference woodland) were sampled to document the extent of progress of species composition from pasture through young (3–5 years) and old (9–11 years) restoration stands to reference woodland across three sites at two surveys. Comparisons showed restored stands of both ages differed significantly from pasture, and from each other, showing decreasing similarity between the restoration stands and pasture at all sites. Despite this, species composition in restored stands at all three sites was still significantly different from reference sites, showing that none had achieved the target reference state after 11 years. The trajectory of restored sites between the two surveys was not towards the reference state. Restoration resulted in the establishment of 20 (71%) of the planted species. Recruits from five planted species were found. A further 40 unplanted native ground layer species were found in restoration. Structurally, tree cover increased with time since restoration and was higher in the restored sites. Ground cover, which was very high in pasture was lower in some restored sites. The majority of the unplanted native species were resprouters, and their presence in the above‐ground vegetation was most likely by vegetative resprouting from the bud‐and‐tuber bank as ground cover was lower with the increase in tree cover and shade. Tree and shrub planting by itself has not yet progressed the restored areas to the species composition of reference sites. Additional tools will be needed to assist restoration, specifically the addition of re‐seeder native plants not able to persist through vegetative resprouting after restoration. Measures to control the burden of weeds present in the pasture seed bank are also required.
Improving Teacher Training Through Emotion Recognition and Data Fusion
Authors: Albaladejo‐González Mariano , Gaspar‐Marco Rubén , Mármol Félix Gómez , Reich Justin , Ruipérez‐Valiente José A. 
Published: October 2024

ABSTRACTThe quality of education hinges on the proficiency and training of educators. Due to the importance of teacher training, the innovative platform Teacher Moments creates simulated classroom scenarios. In this scenario‐based learning, confusion is an important indicator to detect users who struggle with the simulations. Through Teacher Moments, we gathered 7975 audio recording responses from participants who self‐labelled their recordings according to whether they sounded confused. Our dataset stands out for its size, for not including actor‐generated audio, and for measuring confusion, a neglected emotion in artificial intelligence (AI). Our experiments tested unimodal approaches and feature‐level, model‐level and decision‐level fusion. Feature‐level fusion demonstrated superior performance to unimodal methods, achieving a balanced accuracy of 0.6607 on the test set. This outcome highlights the necessity for further investigation in the overlooked area of confusion detection, particularly employing realistic datasets like the one used in this study and exploring new methods. Beyond teacher training, the insights of this research also extend to other directions, such as other professionals making critical decisions, user interface design or adaptive learning systems.
General Industrial Process Optimization Method to Leverage Machine Learning Applied to Injection Moulding
Authors: Charest‐Finn Meaghan , Dubay Rickey 
Published: October 2024

ABSTRACTThe development of machine learning (ML) technologies is driving changes across many sectors. In industrial settings, this is called the fourth industrial revolution and encompasses several technologies pushing the boundaries of industrial automation. In this study, a general industrial process optimization (GIPO) methodology is formulated in the context of Industry 4.0 and tested on an industrial injection moulding machine (IMM). GIPO aims to encourage the practical inclusion of industrial artificial intelligence at all levels of the manufacturing process, while enabling industrial equipment to adapt to a changing processing environment. Special attention is given to the generality of the methodology so that it can be extended to other applications. In the example case study presented here, GIPO combines K‐nearest neighbours classification and nearest neighbours optimization methods to optimize an injection moulding process effectively. Practical implementation conducted on the IMM demonstrates a novel methodology to leverage data mining and ML methods in a real‐world setting to improve production quality, production time and energy cost.
Couples therapy and the challenges of building trust, fairness, and justice
Authors: Daneshpour Manijeh 
Published: October 2024

AbstractThe cornerstone of the contextual family therapy model is predicated on the belief that all family members benefit from trustworthy relationships, which result from (a) acknowledging the contributions of deserving family members, (b) engaging in responsible interactions, and (c) ensuring a fair distribution of relational burdens and benefits. Nonetheless, conflicts may arise when one partner asserts a claim to relational resources based on need, while the other believes they are entitled to such resources based on merit. Based on relational ethics and the development of trust, this paper focuses on the therapist's role in facilitating the conflict‐resolution process to assist couples in reestablishing individual responsibility and accountability within the systemic framework of couple therapy. It elucidates several clinical strategies, including (a) cultivating trust through fairness and focusing on the importance of reciprocity and equitable give‐and‐take, (b) detecting destructive entitlement, and (c) marital relationships and ethics of care. Several clinical examples are discussed, as well as common couple relational issues associated with horizontal and vertical relationships, partnership, and fusion, and the impact of gender and power dynamics and trustworthiness based on the feminist lens.
Study of Vibration‐Ultrasonic Combined Fatigue on 7075‐T6 Aluminum Alloy
Authors: Zhao Ziyu , Tang Sen , Chen Mingsan , Liu Yongjie , He Chao , Xu Bo , Wang Chong , Wang Qingyuan 
Published: October 2024

ABSTRACTComponents in aero‐engine are likely excited in multiple resonance models in dynamic loads. This paper proposes an accelerated fatigue testing method that combines the vibration test with ultrasonic loading to develop a feasible experimental system for combined cycle fatigue (CCF) and explore the CCF characteristics in the high cycle fatigue (HCF) associated with very high cycle fatigue (VHCF) conditions. A thin plate specimen of 7075‐T6 aluminum alloy with two natural frequencies of 2 and 20 kHz is designed for the experiment. The stress waveform and distribution during real‐time monitoring provide validation for the method. Finally, the influences of composite loads are demonstrated by exploring the characteristics of the S–N curves and fracture morphology. The results suggest that the increase in both axial and bending stress markedly diminishes fatigue life, while the difference in stress levels under combined loading is revealed through variations in fatigue striation morphology.
Utilizing Spatial Statistical Bounds on Residual Stress Fields From Cold Expansion: Effects on Fatigue Crack Growth Behavior
Authors: Andrew Dallen L. , Ribeiro Renan , Thomsen Mark , Ocampo Juan , Alaeddini Adel , Popelar Carl F. , Han Hai Chao 
Published: October 2024

ABSTRACTThis paper assesses the impact of utilizing statistically defined residual stress fields from cold expansion (Cx) in linear elastic, multi‐point fracture mechanics analyses using the spatial analysis of residual stress (SpARS) methodology. There is significant value and interest in leveraging the increased fatigue life afforded by Cx, but it is imperative to quantify the variability of the residual stress to understand the expected variability in benefit due to Cx. Comparisons of the predicted fatigue lives from SpARS‐produced statistical residual stress fields are made to fatigue test data. Results demonstrated that the less compressive 95% upper bound from the mean residual stress would be a reasonable strategy as it supplies a compromise between safety and inherent material and process variability while still producing a sizable improvement in predicted fatigue life. In this study, using SpARS to incorporate statistically representative residual stress fields in fatigue crack growth analyses demonstrates a methodology to aircraft structural engineers for improved fleet management and allow increased aircraft availability through fewer inspections.
The role of magnesium oxide addition in densification of AlON transparent ceramics by pressureless sintering
Authors: Zhang Chenyun , Sun Zehan , Shi Ying 
Published: October 2024

AbstractPressureless sintering processing was adopted to fabricate transparent aluminum oxynitride (AlON) ceramics by using magnesium oxide (MgO) as a sintering additive into synthetic single phased aluminum oxynitride powder. Under the condition of adding 0.6 wt% magnesium oxide, the relative density of aluminum oxynitride ceramics increased from 98.67% with no addition to 99.9% after being held at 1800°C for 24 h, coupled by a reducing of average grain size from 190 µm to 130 µm. The optical linear transmittance of the AlON ceramic sample (thickness 1.2 mm) reached 84.2% at the wavelength of 1100 nm. The microstructural characterizations by energy dispersive spectroscopy and atom probe tomography indicated that the doping Mg element was uniformly dispersed inside aluminum oxynitride grains of as‐sintered ceramics. It was demonstrated that magnesium oxide played a key role in inhibiting the movement of grain boundaries, eliminating pores, leading to the fully densification of aluminum oxynitride ceramics.
Clinical Risk Management in Mental Health Services: 10 Principles for Best Practice
Authors: Doyle Michael , Grundy Andrew , McGleenan Katherine , Nash Michael , Deering Kris 
Published: October 2024

ABSTRACTRisk assessment and management are a fundamental part of clinical practice globally within mental health services. In the United Kingdom (UK), the evidence to support the effectiveness of structured risk assessment and management remains limited, although the perception remains that structured management frameworks are effective in reducing risk in mental health care. Despite the importance of risk management within mental health services, the most recent UK wide guidance was published in 2009, while international guidance for the assessing and management of service user risks also appears sparse. This perspective paper reports on a consultation and co‐production project to provide up‐to‐date best practice principles in clinical risk management to enhance the consistency, quality and safety of mental health practice in the UK mental health services, and for mental health services in other English speaking countries. A three‐stage approach was used including literature review, referral to mental health experts for review and final evaluation and sign off by users of mental health services as experts by experience. Ten principles for best practice were confirmed as a benchmark for practice and are offered as a benchmark to improve the quality and safety of mental health practice.
Effectiveness of Digital Education on Human Papillomavirus Knowledge, Vaccination Intent and Completion Rates in Adolescents and Young Adults: A Meta‐Analysis
Authors: Sandi Yudisa Diaz Lutfi , Yang Li‐Yu , Andarini Esti , Maryam Dewi , Wu Li‐Min 
Published: October 2024

ABSTRACTAimsTo examine the effects of digital educational intervention on HPV knowledge, vaccination intent and completion rates among adolescents and young adults.DesignA systematic review and meta‐analysis.MethodsThe study followed PRISMA guidelines. Studies included randomised controlled trials assessing digital HPV educational interventions on individuals aged 9–26 years. Odds ratios (ORs), confidence intervals (CIs) and standardised mean differences (SMDs) were calculated and analysed with fixed‐ and random‐effects models, depending on the degree of heterogeneity.Data SourcesSeven databases (Medline, PubMed, CINAHL, Cochrane Library, Web of Science, EMBASE and ASC) were searched from inception through April 9, 2024.ResultsTwelve studies enrolled 4925 participants were included. Six studies demonstrated that the intervention group significantly had higher HPV knowledge compared to the control group. Five studies reported a significant improvement on vaccination intent and vaccine completion rate. Subgroup analysis of the completion rates indicated that male participants demonstrated significantly greater vaccine competed rates. A tailored educational intervention was likely to effectively enhance HPV vaccine completion rates.ConclusionOur findings confirmed that digital education was beneficial in enhancing adolescents and young adults' HPV knowledge, vaccination intention and vaccine completion rates. The tailored education might be considered prioritised in the design of interventions, while also considering the impact of gender on digital education.ImpactsDigital interventions for HPV vaccinations require at least 7 months of follow‐up, highlighting the vital role of tailored education for high‐risk groups in designing effective interventions. The efficacy of digital interventions for HPV vaccination may differ across genders.Patient or Public ContributionThere was no direct patient or public contribution, as this is a review of previous research.Trial Registration: CRD‐42023406919
Assistive Technology Uses and Barriers in the Home and Workplace for Adults With Intellectual and Developmental Disabilities
Authors: Randall Kristina N. , Drew Hannah , Gilman Elizabeth S. , Dixon Emma 
Published: October 2024

ABSTRACTBackgroundAssistive technology (AT) has been successfully used by researchers and practitioners to increase task completion and independence in work and home environments for individuals with intellectual and developmental disabilities. While prior research has shown increased outcomes of incorporating AT into daily tasks, research has also indicated that actual use of AT in these settings is much lower.MethodThe current qualitative study used semi‐structured interviews with a sample of 25 adults (22 individuals with intellectual and developmental disabilities and three job coaches) to examine the perceived use and implementation of AT into home and work environments, along with potential challenges and barriers. Interviews were analyzed using a thematic analysis approach.ResultsThree themes were identified: (1) technologies used to support daily living skills, (2) technologies used to support employment and (3) challenges and barriers to using technologies.ConclusionsFindings indicate that while individuals with intellectual and developmental disabilities are using a variety of AT in their homes both successfully and independently, they have extremely limited use in their workplaces. Implications for practice and future research are discussed.
Chest x‐ray images: transfer learning model in COVID‐19 detection
Authors: Mao Siqi , Kulbayeva Saltanat , Osadchuk Mikhail 
Published: October 2024

AbstractRationale, Aims and ObjectivesThis research aims to develop an effective algorithm for diagnosing COVID‐19 in chest X‐rays using the transfer learning method and support vector machines.MethodIn total, data was collected from 10 clinics, including both large city hospitals and smaller medical institutions. This ensured a diverse range of geographical and demographic information in the sample. An extensive data set was collected, including 10,000 chest X‐ray images. 5000 images represent normal cases, 3993 images represent pneumonia cases, and 1007 images represent COVID‐19 cases. Machine learning methods were applied to develop a classification model, and the results were compared with seven state‐of‐the‐art models and a lightweight CNN architecture.ResultsThe results showed that the proposed method achieves high accuracy values (Accuracy): 0.95 for COVID‐19, 0.89 for pneumonia, and 0.92 for normal images (p < 0.05). Comparison with other models demonstrates statistically significant superiority of our method in accuracy across all three classes. The EfficientNet‐B0 model surpasses our method only in accuracy for normal images with p < 0.01, confirming the advantages of our method. Our method demonstrates high sensitivity values (Sensitivity): 0.96 for COVID‐19, 0.88 for pneumonia, and 0.93 for normal images (p < 0.05), outperforming most of the compared models. Correlation analysis showed Pearson coefficients of 0.92, 0.89, and 0.94 for COVID‐19, pneumonia, and normal images, respectively, confirming a high degree of consistency between predicted and true class labels. In addition, the model was validated on external datasets to assess its generalizability. This validation confirmed its high level of effectiveness in a variety of clinical settings.ConclusionThis study confirms the importance of applying machine learning methods in medical applications and opens new perspectives for early diagnosis of infectious diseases. The practical application of the obtained results can enhance the efficiency of diagnosis and control the spread of COVID‐19, as well as contribute to the development of innovative methods in medical practice.
Submissions of diagnostic samples of two critically endangered species of handfish (Branchionichthys hirsutus and Thymichthys politus) from a public aquarium from 2018 to 2024
Authors: Nowak Barbara F. , Knowles Graeme , Handlinger Judith , Hawkins Rachelle , Jantawongsri Khattapan , Dang Mai , Thompson Andrew , van Gelderen Rebecca , Bott Nathan J. 
Published: October 2024

AbstractHandfish (Family Brachionichthyidae) is the most threatened marine teleost fish family, however, there is little information on handfish health. We reviewed the results of submissions of mortalities from captive and captive bred spotted handfish (Branchionichthys hirsutus (Lacepède, 1804)) and red handfish (Thymichthys politus (Richardson, 1844)) from a public aquarium from January 2018 to February 2024. Seventeen cases for spotted handfish (comprising 33 individuals) and five cases for red handfish (one individual each) were submitted for mortality investigation. In 2018–2019, six of seven cases were diagnosed with scuticociliatosis. Other conditions included epitheliocystis (1 of 17), infections with metazoan parasites (2 of 17 for spotted handfish and 2 of 5 for red handfish) and hepatic lipidosis (4 of 17). Most submissions were fixed samples for histology with only one fish suitable for microbiology. We recommend development of a coordinated health program for all captive breeders and aquaria, which should include sampling protocols, collection, and preservation in a range of fixatives of all the dying or dead handfish and adapting sublethal sampling, including tank water to assess presence of pathogens and other microorganisms. Risk factors for handfish health in captivity should be assessed. Handfish health database should be established to avoid loss of corporate knowledge in this area.