bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diabetes, frailty and burden of comorbidities among older Malaysians with stroke
Authors: Wong W. J. , Tan K. M. , Harrison C. , Ng C. C. , Lim W. C. , Nguyen T. N. 
Published: August 2024

Abstract
Background
Stroke is a global health challenge. The increasing prevalence of diabetes and the ageing population further add to the complexities of stroke care.

Objective
This study aims to (1) describe the prevalence of diabetes in older patients with stroke and (2) compare the burden of comorbidities among patients with diabetes and frailty compared to those without these conditions.

Methods
This was a cross-sectional study in older patients aged ≥ 65 years with stroke. Comorbidities were assessed using the Charlson Comorbidity Index (CCI). Frailty assessments were done using the Clinical Frailty Scale. Participants were classified into four groups: Group 1, frail and diabetic; Group 2, non-frail and diabetic; Group 3, frail and non-diabetic; and Group 4, non-frail and non-diabetic.

Results
There were 384 participants (mean age 81.11 ± 6.37). Diabetes was present in 45.1%. The mean CCI was highest for the frail and diabetic group (6.97 ± 1.97), followed by non-frail and diabetic (6.00 ± 2.02), frail and non-diabetic (5.49 ± 1.79) and non-frail and non-diabetic (4.74 ± 1.68), p < 0.001. The non-frail and diabetic group had a significantly higher prevalence of hypertension (96.9%) and ischaemic heart disease (34.4%) compared to the other three groups.

Conclusions
There was a high prevalence of diabetes among older patients with stroke. While the frail and diabetic group had the highest overall burden of comorbidities, the non-frail and diabetic group had the most significant cardiovascular disease burden. These findings highlight the urgent need for integrated and personalized management approaches to enhance the overall well-being and quality of life for older stroke survivors with diabetes.
Fuel provisioning for pollen collection by solitary bee, Andrena taraxaci orienticola
Authors: Harano Ken-ichi , Sasaki Tetsuhiko 
Published: August 2024

AbstractFemale solitary bees collect pollen for their brood at the expense of using sugars in the nectar as fuel for flight. When flowers provide both pollen and nectar, solitary bees can refuel from the flowers to sustain pollen foraging. However, not all flowers provide both pollen and nectar. This study investigates how females of the solitary bee Andrena taraxaci orienticola secure fuel to sustain pollen foraging when flowers provide scarce nectar. By using DNA barcoding, we identified the Japanese dandelion Taraxacum platycarpum as their primary food source. This dandelion produces almost no nectar in the early morning when female bees collect almost no nectar but collect substantial amounts of pollen. We also found that these bees leave the nest with significantly more nectar at the first flight of the day than at later flights. When we restricted their fuel load by preventing nectar feeding, significantly more females failed to collect pollen on the first flight of the following day. These results suggest females hold back some part of the nectar collected at the end of a day’s foraging and use it the following morning as fuel to sustain pollen foraging from flowers providing little nectar.
Disseminated fusariosis after allogenic hematopoietic stem cell transplantation: case report
Authors: Gantner A. , Hagemann J. B. , Grüner B. , Walther G. , Neagoie A. , Wais V. , Döhner H. , Sala E. 
Published: August 2024

AbstractIn allogenic stem cell recipients, invasive fungal disease is a common yet dreaded complication with high mortality. Among these, fusariosis is especially complex to treat due to high intrinsic resistance and few antimycotic options, requiring close cooperation of all involved departments. We here report an instructive case of disseminated fusariosis after allogenic stem cell transplantation with fatal outcome despite maximum treatment.
A Qualitative Systematic Review and Meta-synthesis of Mothers’ Experiences of Parenting Autistic Women and Girls
Authors: Oliver Michelle , Poysden Zoe , Gillespie-Smith Karri 
Published: August 2024

AbstractThis review systematically explores qualitative evidence of the lived experience of mothers’ parenting autistic women and girls. A SPIDER search strategy was conducted on five databases and in the grey literature. Backward, forward and relevant journal scanning was also carried out. Twenty-two qualitative or mixed-method studies were included and quality appraised using CASP, encompassing over 150 mothers. A thematic synthesis highlighted five super-ordinate themes; ‘The diagnosis process and getting support’, ‘Mother’s role as all consuming’, ‘Experiences of family wellbeing’, ‘Mother as an expert observer’ and ‘The hopes and fears of mothers’. The review highlights areas of motivation to socialise, masking and menstruation needs as key differences in the autistic female presentation from a mothers’ perspective. Implications for practice are discussed.
Effect of docosahexaenoic acid as an anti-inflammatory for Caco-2 cells and modulating agent for gut microbiota in children with obesity (the DAMOCLE study)
Authors: Lammi C. , Ottaviano E. , Fiore G. , Bollati C. , d’Adduzio L. , Fanzaga M. , Ceccarani C. , Vizzuso S. , Zuccotti G. , Borghi E. , Verduci E. 
Published: August 2024

Abstract

Purpose
Docosahexaenoic acid (DHA) is a long-chain omega‐3 polyunsaturated fatty acid. We investigated the dual health ability of DHA to modulate gut microbiota in children with obesity and to exert anti-inflammatory activity on human intestinal Caco-2 cells.

Methods
In a pilot study involving 18 obese children (8–14 years), participants received a daily DHA supplement (500 mg/day) and dietary intervention from baseline (T0) to 4 months (T1), followed by dietary intervention alone from 4 months (T1) to 8 months (T2). Fecal samples, anthropometry, biochemicals and dietary assessment were collected at each timepoint. At preclinical level, we evaluated DHA’s antioxidant and anti-inflammatory effects on Caco-2 cells stimulated with Hydrogen peroxide (H2O2) and Lipopolysaccharides (LPS), by measuring also Inducible nitric oxide synthase (iNOS) levels and cytokines, respectively.

Results
Ten children were included in final analysis. No major changes were observed for anthropometric and biochemical parameters, and participants showed a low dietary compliance at T1 and T2. DHA supplementation restored the Firmicutes/Bacteroidetes ratio that was conserved also after the DHA discontinuation at T2. DHA supplementation drove a depletion in Ruminococcaceae and Dialisteraceae, and enrichment in Bacteroidaceae, Oscillospiraceae, and Akkermansiaceae. At genus level, Allisonella was the most decreased by DHA supplementation. In Caco-2 cells, DHA decreased H2O2-induced reactive oxygen species (ROS) and nitric oxide (NO) production via iNOS pathway modulation. Additionally, DHA modulated proinflammatory (IL-1β, IL-6, IFN-γ, TNF-α) and anti-inflammatory (IL-10) cytokine production in LPS-stimulated Caco-2 cells.

Conclusion
An improvement in gut dysbiosis of children with obesity seems to be triggered by DHA and to continue after discontinuation. The ability to modulate gut microbiota, matches also with an anti-inflammatory effect of DHA on Caco-2 cells.

Graphical abstract
Verbreitung und Bedingungen von betrieblichen Maßnahmen zum Umgang mit Mobbing in Deutschland
Authors: Rauls J. , Buchallik F. , Zimmer A. , Kraft E. , Beck D. 
Published: August 2024

Zusammenfassung

Hintergrund
Mobbing im Betrieb stellt einen erheblichen Risikofaktor für die Gesundheit von betroffenen Beschäftigten dar. Durch das Arbeitsschutzgesetz ist der Arbeitgeber verpflichtet, Maßnahmen zur Gefährdungsvermeidung zu ergreifen. Wesentlich hierfür ist die Durchführung einer Gefährdungsbeurteilung. Im Beitrag wird untersucht, wie hoch der Anteil der Betriebe in Deutschland ist, die Verfahren zum Umgang mit möglichen Fällen von Mobbing ergriffen haben, und inwieweit hierfür die Umsetzung von Gefährdungsbeurteilungen prädiktiv ist.

Daten und Methoden
Die Analysen erfolgen auf Grundlage der Daten der deutschen Stichprobe des 2019 durchgeführten European Survey of Enterprises on New and Emerging Risks (ESENER‑3, n = 1234 Betriebe mit mind. 20 Beschäftigten). Neben deskriptiven Analysen werden logistische Regressionsanalysen zur Untersuchung der in Frage stehenden Zusammenhänge durchgeführt.

Ergebnisse
Verfahren für den Umgang mit Mobbing oder Belästigung sind in 38 % der Betriebe in Deutschland vorhanden; seltener in kleinen Betrieben (31 %) und überdurchschnittlich häufig in großen Unternehmen (69 %) sowie in Einrichtungen des Gesundheits- und Sozialwesens (54 %). Zwar sind Verfahren zum Umgang mit Mobbing in Betrieben, in denen Gefährdungsbeurteilungen vorliegen, häufiger vorhanden als in Betrieben, in denen dies nicht der Fall ist. Unter statistischer Kontrolle der Einflüsse von Betriebsgröße und Wirtschaftszweig sowie weiterer Aspekte der Arbeitsschutzorganisation zeigen sich diesbezüglich allerdings keine signifikanten Zusammenhänge. Dagegen ist die Chance für das Vorhandensein von Verfahren zum Umgang mit Mobbing signifikant erhöht in Betrieben, in denen ein Betriebs- bzw. Personalrat vorhanden ist (OR = 2,04 [KI 1,53–2,71]) und in denen Beratung durch einen Psychologen bzw. eine Psychologin in Anspruch genommen wird (OR = 3,38 [KI 2,47–4,63]).

Schlussfolgerung
Maßnahmen zur Vermeidung von Gefährdungen durch Mobbing am Arbeitsplatz fehlen vielerorts und scheinen bislang noch keine systematische Berücksichtigung in Gefährdungsbeurteilungen zu finden. Die Ergebnisse zeigen, dass ein Teil der Betriebe bereits Verfahren im Umgang mit Mobbing etabliert hat, aber noch weitergehende Anstrengungen nötig sind, um eine systematische Berücksichtigung von Mobbing im Arbeitsschutz zu gewährleisten.
Fresh Concrete Properties from Stereoscopic Image Sequences
Authors: Meyer Max , Langer Amadeus , Mehltretter Max , Beyer Dries , Coenen Max , Schack Tobias , Haist Michael , Heipke Christian 
Published: August 2024

AbstractIncreasing the degree of digitization and automation in concrete production can make a decisive contribution to reducing the associated $$\text{CO}_{2}$$

CO
2

emissions. This paper presents a method which predicts the properties of fresh concrete during the mixing process on the basis of stereoscopic image sequences of the moving concrete and mix design information or a variation of these. A Convolutional Neural Network (CNN) is used for the prediction, which receives the images supported by information about the mix design as input. In addition, the network receives temporal information in the form of the time difference between image acquisition and the point in time for which the concrete properties are to be predicted. During training, the times at which the reference values were captured are used for the latter. With this temporal information, the network implicitly learns the time-dependent behavior of the concrete properties. The network predicts the slump flow diameter, the yield stress and the plastic viscosity. The time-dependent prediction opens up the possibility of forecasting the temporal development of the fresh concrete properties during mixing. This is a significant advantage for the concrete industry, as countermeasures can then be taken in a timely manner, if the properties deviate from the desired ones. In various experiments it is shown that both the stereoscopic observations and the mix design information contain valuable information for the time-dependent prediction of the fresh concrete properties.
Empirical model for the effect of air humidity during manufacturing on the glass transition temperature of carbon fiber reinforced hot curing epoxy – a case study
Authors: Krolitzki Benjamin , Clausen Tim , Andresen Elisa , Boskovic Lazar 
Published: August 2024

AbstractCarbon fiber-epoxy laminates are used in aerospace manufacturing, e.g. as substrates for solar cells of satellites. Commonly, fibers or fibermats are impregnated with epoxy resin and placed in the required orientation. During subsequent curing, the resin molecules are crosslinked. Cured parts are characterized by their glass transition temperature (Tg). It has been observed that Tg of epoxy matrix resin vary with recorded absolute air humidity during wet fiber placement manufacturing. Based on the production data of a series production of 203 carbon fiber laminates for space application, an empirical linear relationship between the absolute air humidity at the beginning of each production day and the observed glass transition temperature of the fully cured laminate is formulated and validated. The empirical equation describes a linear decrease of achievable glass transition temperature with increasing absolute air humidity. The quantitative nature of the results encourages straightforward practical application to determine the maximum achievable Tg for given production conditions.
The psycho-social impact of video games on K12 Spanish students
Authors: Vázquez-Cano Esteban , Quero-Gervilla Mercedes , Quicios-García María-Pilar , López-Meneses Eloy 
Published: August 2024

AbstractThis research aims to study the psycho-social impact of video games on K12 students. For this, a probabilistic topic modelling analysis method based on text mining approach has been performed. This process is based on nodes’ connectivity and it has been developed through K Means approach; by launching the Jenks-Breaks algorithm. The sex differences are calculated according to a nonlinear dynamics approach based on Hurst exponent and multifractal function and the influence of time with the application of the Sobel test. The results show which are the most used video games by K12 and their psycho-social impact on students based on four categories: (1) boredom and sadness, (2) happiness and socialization, (3) immersion, and (4) families' conflicts. There are significant differences between boys and girls depending on the games they use, a factor that increases when playing more than two hours a day. For boys, games like FIFA and Fortnite produce higher levels of immersion and family conflict, while for girls, games are perceived as sources of greater happiness and a means to reinforce friendship and camaraderie, particularly with games like Brawl Stars, Rocket League, and PKXD.
Reliability of Machine Learning in functional assessment in cardiac magnetic resonance imaging
Authors: Boccetti Danilo , Lamja Stefania , Palumbo Pierpaolo , Barile Antonio , Di Cesare Ernesto 
Published: August 2024

Abstract
Purpose
Our study aims at evaluating Machine Learning’s reliability to calculate ventricular volumes and functions in cardiac magnetic resonance imaging (CMR).

Material and methods
Eighty-five patients underwent CMR: forty healthy subjects, fifteen affected by myocarditis, seventeen dilated cardiomyopathy patients (DCM), and thirteen hypertrophic cardiomyopathy patients (HCM). Left ventricle (LV) and right ventricle (RV) analyses were performed both manually by operators and using Cvi42 software, which automates the identification of telesystolic and telediastolic phases. Statistical analysis assessed the concordance between measurements obtained manually and through the software, considering the following parameters: end-diastolic volume (EDV-BSA), end-systolic volume (ESV-BSA), stroke volume (SV), ejection fraction (EF), and detection of telesystolic and telediastolic phases.

Results
Intraclass correlation coefficient (ICC) analysis for LV volumes showed high concordance between manual and automatic measurements (ESV-BSA 0.97, EDV-BSA 0.98, SV 0.87, EF 0.93). ICC analysis for RV volumes presented high concordance between ESV-BSA and EDV-BSA measurements as well (ICC 0.90 and 0.91, respectively), whereas SV and EF measurements showed lower values (0.65 and 0.67, respectively). Statistical analysis also exhibited good concordance between manual and automated methods in the detection of telesystolic and telediastolic phases (ICC 0.80 and 0.84, respectively).

Conclusion
The LV and RV analyses conducted using the automated tool provide non-inferior performance to manual analyses, in particular for LV volumes.
Correction of thermal airflow distortion in warpage measurements of microelectronic packaging structures via deep learning-based digital image correlation
Authors: Gao Yuhan , Chen Yuxin , Yu Ziniu , Xiong Chuanguo , Lei Xin , Lv Weishan , Liu Sheng , Zhu Fulong 
Published: August 2024

AbstractThe projected speckle-based three-dimensional digital image correlation method (3D-DIC) is being increasingly used in the reliability measurement of microelectronic packaging structures because of its noninvasive nature, high precision, and low cost. However, during the measurement of the thermal reliability of packaging structures, the thermal airflow generated by heating introduces distortions in the images captured by the DIC measurement system, impacting the accuracy and reliability of noncontact measurements. To address this challenge, a thermal airflow distortion correction model based on the transformer attention mechanism is proposed specifically for the measurement of thermal warpage in microelectronic packaging structures. This model avoids the oversmoothing issue associated with convolutional neural networks and the lack of physical constraints in generative adversarial networks, ensuring the precision of grayscale gradient changes in speckle patterns and minimizing adverse effects on DIC calculation accuracy. By inputting the distorted images captured by the DIC measurement system into the network, corrected images are obtained for 3D-DIC calculations, thus allowing the thermal warpage measurement results of the sample to be acquired. Through experiments measuring topography with customized step block specimens, the effectiveness of the proposed method in improving warpage measurement accuracy is confirmed; this is particularly true when captured images are affected by thermal airflow at 140 °C and 160 °C, temperatures commonly encountered in thermal reliability testing of packaging structures. The method successfully reduces the standard deviation from 9.829 to 5.943 µm and from 12.318 to 6.418 µm, respectively. The results demonstrate the substantial practical value of this method for measuring thermal warpage in microelectronic packaging structures.
Genetic associations between non-cognitive skills and academic achievement over development
Authors: Malanchini Margherita , Allegrini Andrea G. , Nivard Michel G. , Biroli Pietro , Rimfeld Kaili , Cheesman Rosa , von Stumm Sophie , Demange Perline A. , van Bergen Elsje , Grotzinger Andrew D. , Raffington Laurel , De la Fuente Javier , Pingault Jean-Baptiste , Tucker-Drob Elliot M. , Harden K. Paige , Plomin Robert 
Published: August 2024

AbstractNon-cognitive skills, such as motivation and self-regulation, are partly heritable and predict academic achievement beyond cognitive skills. However, how the relationship between non-cognitive skills and academic achievement changes over development is unclear. The current study examined how cognitive and non-cognitive skills are associated with academic achievement from ages 7 to 16 years in a sample of over 10,000 children from England and Wales. The results showed that the association between non-cognitive skills and academic achievement increased across development. Twin and polygenic scores analyses found that the links between non-cognitive genetics and academic achievement became stronger over the school years. The results from within-family analyses indicated that non-cognitive genetic effects on academic achievement could not simply be attributed to confounding by environmental differences between nuclear families, consistent with a possible role for evocative/active gene–environment correlations. By studying genetic associations through a developmental lens, we provide further insights into the role of non-cognitive skills in academic development.
Modeling routing problems in QUBO with application to ride-hailing
Authors: Cattelan Michele , Yarkoni Sheir 
Published: August 2024

AbstractMany emerging commercial services are based on the sharing or pooling of resources for common use with the aim of reducing costs. Businesses such as delivery-, mobility-, or transport-as-a-service have become standard in many parts of the world, fulfilling on-demand requests for customers in live settings. However, it is known that many of these problems are NP-hard, and therefore both modeling and solving them accurately is a challenge. Here we focus on one such routing problem, the Ride Pooling Problem (RPP), where multiple customers can request on-demand pickups and drop-offs from shared vehicles within a fleet. The combinatorial optimization task is to optimally pool customer requests using the limited set of vehicles, akin to a small-scale flexible bus route. In this work, we propose a quadratic unconstrained binary optimization (QUBO) program and introduce efficient formulation methods for the RPP to be solved using metaheuristics, and specifically emerging quantum optimization algorithms.
A smart look at monitoring while drilling (MWD) and optimizing using acoustic emission technique (AET)
Authors: Khoshouei Mehrbod , Bagherpour Raheb , Yari Mojtaba 
Published: August 2024

AbstractMonitoring while drilling (MWD) is a crucial task in mining operations. Accurately measuring drill and rock-related operating parameters can significantly reduce the cost of drilling operations. This study explores the potential of monitoring drilling specific energy (SE) and optimizing drilling operations by processing vibroacoustic signals generated while drilling. For this purpose, 30 samples of different rocks, are used for drilling tests. During the drilling process, the acoustic and vibration signals are recorded and analyzed in the time, frequency, and time–frequency domains., and parameters related to the resulting spectra are extracted. After obtaining the vibroacoustic parameters for drilling, the relationship between them and the drilling SE was investigated. There is evidence that the progression of SE contributes to the magnitude of rock drilling vibroacoustic features, which could be employed to indicate energy conditions during drilling. Results obtained in this study have the potential to be used as the basis for an industrial monitoring system that can detect excessive energy consumption and advise the user of the end of the bit's useful life. This method can be an intelligent technique for measuring the behavior of real-time drilling operations based on the SE simply by installing vibroacoustic sensors on the drilling machines.