bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigating the potential of graphene-doped nickel lanthanum ferrites for supercapacitor electrode material
Authors: Akbar Hassan , Akram Muhammad Salman , Ali Asghar , Subhan Javed Muhammad 
Published: October 2024

Abstract
Based on the demand for intensive research of supercapacitor electrode materials, graphene-doped nickel lanthanum ferrites (NiLaFe2O3) have been synthesized to explore their potential and unique properties of their electrochemical performance. The graphene is synthesized using the Hummers method and then doped into NiLaFe2O3 using a hydrothermal method. The graphene-doped NiLaFe2O3 is characterized by x-ray diffraction and scanning electron microscopy to analyze its structural and morphological properties. Fourier transform infrared spectroscopy and UV analysis are performed to explore the molecular structure and band gap of the material, respectively. Transmission electron microscopy analysis is performed to envision the ultrastructure of the composite at nanometer-scale resolution. Finally, the electrochemical performance of the graphene-doped NiLaFe2O3 is calculated by making electrodes. The slurry for the electrode material is prepared using polyvinylidene fluoride and activated carbon. The evaluation of electrochemical performance is carried out using cyclic voltammetry, electrochemical impedance spectroscopy and galvanostatic charge–discharge measurements.
Enhancing performance through friction welding of dissimilar aluminium 2014 and 7075 hybrid metal-matrix composite: insights into material characterization, crystallographic texture, and mechanical properties
Authors: Pandian Vasanthakumar , Kannan Sekar 
Published: October 2024

Abstract
Welding high-strength, age-hardenable aluminium alloys from the 2XXX and 7XXX series poses challenges when using fusion-based welding processes. Common issues such as hydrogen porosity, hot cracking, stress corrosion cracking, and solidification cracking can lead to a reduction in mechanical properties due to the loss of strengthening precipitates and alloying elements. Consequently, friction stir welding (FSW) has emerged as a promising solid-state welding technique for joining dissimilar aluminium alloys and composites, particularly in aerospace applications where a combination of strength, corrosion resistance, and other desirable properties is required. This study investigates the FSW of dissimilar aluminium alloys, specifically AA2014 and a hybrid metal-matrix composite of AA7075 reinforced with silicon carbide and graphite particles. The microstructural and mechanical properties of the welded joints were characterized, revealing an average grain size of 2.39 μm ± 1.2 in the stir zone (SZ). A high angle grain boundary volume fraction of 47.25% was observed in the SZ, compared to 2.01% in the AA7075 composite and 15.03% in the AA2014 base metal. The presence of shear textures and the distribution of cube, S, and H textures indicate a homogeneous mixing of the base materials and a high shear strain rate during welding. The hardness of the SZ increased by 13%, and the ultimate tensile strength, yield strength, and elongation of the joint were measured at 251 MPa, 183 MPa, and 6.44%, respectively. The flexural strength of the joints improved significantly, with the CW13 sample showing a 67% increase compared to CW1. The dissimilar joint CW13, welded at 12.5 mm min−1, achieved a maximum joint efficiency of 95%.
Micro water energy harvesting system based on tubular triboelectric nanogenerator
Authors: Tan Xiangyu , Na Zhimin , Zhuo Ran , Zhou Fangrong , Wang Dibo , Zhu Longchang , Wu Haoying 
Published: October 2024

Abstract
Constructing a micro-water energy-harvesting system for the power supply of micro-nano sensors in pipeline liquid transmission networks is of great significance. In this study, a micro water energy harvesting system based on a tubular triboelectric nanogenerator was designed, which achieves efficient energy harvesting and conversion by directly collecting the charge of the friction layer without the electrostatic induction effect. First, the working principle of the liquid–solid triboelectric nanogenerator is analyzed based on multi-physic coupling, and the potential distribution in the charge transfer process is analyzed. Second, the effects of liquid flow, pipe length, inner diameter, and material on the output characteristics of the triboelectric nanogenerator were investigated. Finally, the load power supply characteristics of the triboelectric nanogenerator were presented. The output characteristics of the liquid–solid triboelectric nanogenerator were proportional to the flow rate and inversely proportional to the inner diameter of the pipe. The output power of the liquid–solid triboelectric nanogenerator can be charged and stored by the capacitor through the rectifier bridge, and at least 30 LED lamp beads can be driven at a flow rate of 650 ml·min-1. This research has the potential to be applied to the construction of self-powered liquid-state monitoring intelligent sensors in pipeline networks.
Unsupervised end-to-end training with a self-defined target
Authors: Liu Dongshu , Laydevant Jérémie , Pontlevy Adrien , Querlioz Damien , Grollier Julie 
Published: October 2024

Abstract
Designing algorithms for versatile AI hardware that can learn on the edge using both labeled and unlabeled data is challenging. Deep end-to-end training methods incorporating phases of self-supervised and supervised learning are accurate and adaptable to input data but self-supervised learning requires even more computational and memory resources than supervised learning, too high for current embedded hardware. Conversely, unsupervised layer-by-layer training, such as Hebbian learning, is more compatible with existing hardware but does not integrate well with supervised learning. To address this, we propose a method enabling networks or hardware designed for end-to-end supervised learning to also perform high-performance unsupervised learning by adding two simple elements to the output layer: winner-take-all selectivity and homeostasis regularization. These mechanisms introduce a ‘self-defined target’ for unlabeled data, allowing purely unsupervised training for both fully-connected and convolutional layers using backpropagation or equilibrium propagation on datasets like MNIST (up to 99.2%), Fashion-MNIST (up to 90.3%), and SVHN (up to 81.5%). We extend this method to semi-supervised learning, adjusting targets based on data type, achieving 96.6% accuracy with only 600 labeled MNIST samples in a multi-layer perceptron. Our results show that this approach can effectively enable networks and hardware initially dedicated to supervised learning to also perform unsupervised learning, adapting to varying availability of labeled data.
Associations between amyloid-β load and cognition in cerebrovascular disease beyond cerebral amyloid angiopathy: a systematic review and meta-analysis of positron emission tomography studies
Authors: Zhang Jie , Price Cathy J , Zhao Ke , Tang Yuanyuan , Zhong Shuchang , Lou Jingjing , Ye Xiangming , Liang Feng 
Published: October 2024

Abstract

Background
There is growing interest in the comorbidity of vascular and neurodegenerative pathologies in patients with cerebrovascular disease (CVD) beyond cerebral amyloid angiopathy (CAA). However, the relationship between amyloid-β and vascular cognitive impairment (VCI) remains debated.

Objective
To investigate the association between VCI and amyloid-β deposition in non-CAA CVD patients.

Methods
PubMed, Embase, Web of Science, PsycINFO and CENTRAL databases were systematically searched. Observational studies, including case–control and cohort studies, associating cognitive scores with amyloid load measured by positron emission tomography were selected. Meta-analyses were performed to assess the strength of amyloid–cognition associations across CVD subtypes and cognitive domains. A random-effects model using the inverse variance method was used, with heterogeneity evaluated by Q-statistics and I2 statistics. Meta-regression analyses were conducted to examine the influence of moderators, and publication bias was assessed using funnel plots and Egger’s test. All statistical analyses were performed using StataMP 18.

Results
Twenty-seven eligible studies encompassing 2894 participants were included. Among non-CAA CVD patients, global cognitive performance was significantly lower in those with higher amyloid-β deposition (standardized mean difference = −0.43, P &lt; 0.001). The correlation strength varied across cognitive domains (executive function: r = −0.41; language: r = −0.36; memory: r = −0.29; all P &lt; 0.001). The correlation was significant in patients with subcortical vascular disease (r = −0.43, P &lt; 0.001) but not post-stroke patients (r = −0.19, P &gt; 0.05).

Conclusions
Amyloid-β load is associated with cognitive decline in non-CAA CVD patients. This is more pronounced in patients with subcortical vascular disease than in post-stroke patients. Executive function is the most susceptible domain in VCI when the level of amyloid-β increases.
Evaluation of hand–arm vibration (HAV) exposure among groundskeepers in the southeastern United States
Authors: Chen Nathan , Yang Seunghyeon , Oh Jonghwa 
Published: October 2024

Abstract

Objective
The objectives of this study were to evaluate daily hand–arm vibration (HAV) exposure among groundskeepers, characterize power tools used, and estimate lifetime cumulative HAV exposure dose.

Methods
Seventeen groundskeepers and ten office workers employed at two US southeasterrn institutions were recruited as a target exposure group and a reference group, respectively. A 6-d exposure assessment of HAV was scheduled, and vibration dosimeters were used to obtain daily vibration exposure value, A(8). Information on power tools used and corresponding operation duration was recorded to assign the real-time vibration data collected from the dosimeters for tool characterization in terms of vibration total value (ahv) and frequency. Lifetime cumulative exposure dose, ahv-lifetime, was determined using ahv for all tools used and lifetime exposure duration obtained through a questionnaire.

Results
The individual groundskeepers’ average A(8) ranged from 0.8 to 2.6 and from 1.0 to 2.6 m/s2 for the right hand and left hands, respectively. Among 11 power tools used by the groundskeepers, grass trimmers contributed the most to the vibration exposure. The average ahv of the individual tools ranged from 8.0 (chainsaws) to 1.9 m/s2 (seating mowers and handheld blowers) for the right hand and from 6.4 (push mowers) to 1.4 m/s2 (backpack blowers) for the left hand. The highest acceleration peak of grass trimmers, edgers, backpack blowers, pole saws, riding blowers, and hedgers was observed between 100 and 200 Hz while riding mowers, seating mowers, push mowers, and chainsaws showed the highest acceleration peak at lower frequencies (≤63.5 Hz). The groundskeepers’ average ahv-lifetime was 76,520.6 and 61,955.5 h m/s2 for the right and left hands, respectively. The average ahv-lifetime of office workers was 2,306.2 and 2,205.8 h m/s2 for the right and left hands, respectively, which was attributed to personal hobby activities.

Conclusion
Three groundskeepers’ average A(8) reached 2.5 m/s2, the Action Limit recommended by the American Conference of Governmental Industrial Hygienists (ACGIH). The highest contribution to the vibration exposure was observed during grass trimmer operations with a major acceleration peak at 100 Hz. The groundskeepers’ ahv-lifetime was 33 and 28 times higher for the right and left hands, respectively, than the office workers.
A consensus-based classification workflow to determine genetically inferred ancestry from comprehensive genomic profiling of patients with solid tumors
Authors: Wallen Zachary D , Nesline Mary K , Pabla Sarabjot , Gao Shuang , Vanroey Erik , Hastings Stephanie B , Ko Heidi , Strickland Kyle C , Previs Rebecca A , Zhang Shengle , Conroy Jeffrey M , Jensen Taylor J , George Elizabeth , Eisenberg Marcia , Caveney Brian , Sathyan Pratheesh , Ramkissoon Shakti , Severson Eric A 
Published: October 2024

Abstract
Disparities in cancer diagnosis, treatment, and outcomes based on self-identified race and ethnicity (SIRE) are well documented, yet these variables have historically been excluded from clinical research. Without SIRE, genetic ancestry can be inferred using single-nucleotide polymorphisms (SNPs) detected from tumor DNA using comprehensive genomic profiling (CGP). However, factors inherent to CGP of tumor DNA increase the difficulty of identifying ancestry-informative SNPs, and current workflows for inferring genetic ancestry from CGP need improvements in key areas of the ancestry inference process. This study used genomic data from 4274 diverse reference subjects and CGP data from 491 patients with solid tumors and SIRE to develop and validate a workflow to obtain accurate genetically inferred ancestry (GIA) from CGP sequencing results. We use consensus-based classification to derive confident ancestral inferences from an expanded reference dataset covering eight world populations (African, Admixed American, Central Asian/Siberian, European, East Asian, Middle Eastern, Oceania, South Asian). Our GIA calls were highly concordant with SIRE (95%) and aligned well with reference populations of inferred ancestries. Further, our workflow could expand on SIRE by (i) detecting the ancestry of patients that usually lack appropriate racial categories, (ii) determining what patients have mixed ancestry, and (iii) resolving ancestries of patients in heterogeneous racial categories and who had missing SIRE. Accurate GIA provides needed information to enable ancestry-aware biomarker research, ensure the inclusion of underrepresented groups in clinical research, and increase the diverse representation of patient populations eligible for precision medicine therapies and trials.
CompariPSSM: a PSSM–PSSM comparison tool for motif-binding determinant analysis
Authors: Tsitsa Ifigenia , Krystkowiak Izabella , Davey Norman E 
Published: October 2024

Abstract

Motivation
Short linear motifs (SLiMs) are compact functional modules that mediate low-affinity protein–protein interactions. SLiMs direct the function of many dynamic signalling and regulatory complexes playing a central role in most biological processes of the cell. Motif-binding determinants describe the contribution of each residue in a motif-containing peptide to the affinity and specificity of binding to the motif-binding partner. Motif-binding determinants are generally defined as a motif consensus pattern or a position-specific scoring matrix (PSSM) encoding quantitative preferences. Motif-binding determinant comparison is an important motif analysis task and can be applied to motif annotation, classification, clustering, discovery and benchmarking. Currently, binding determinant comparison is generally performed by analysing consensus similarity; however, this ignores important quantitative information in both the consensus and non-consensus positions.

Results
We have created a new tool, CompariPSSM, that quantifies the similarity between motif-binding determinants using sliding window PSSM–PSSM comparison and scores PSSM similarity using a randomisation-based probabilistic framework. The tool has been benchmarked on curated data from the eukaryotic linear motif database and experimental data from proteomic peptidephage display. CompariPSSM can be used for peptide classification to validate motif classes, peptide clustering to group functionally related conserved disordered regions, and benchmarking experimental motif discovery methods.

Availability and implementation
CompariPSSM is available at https://slim.icr.ac.uk/projects/comparipssm.
Value of projectional imaging relative to cross-sectional imaging to assess catheter tip position in the superior vena cava: evaluation of reader variability
Authors: Gullo Giuseppe , Rotzinger David Christian , Frossard Pierre , Colin Anaïs , Saliou Guillaume , Qanadli Salah Dine 
Published: October 2024

Abstract

Objectives
The cavo-atrial junction (CAJ) is the most appropriate central venous catheters CVC tip location to reduce complications. Among chest X-ray (CXR) landmarks for tips assessment, only the pericardial reflection lies in the same plane as the vascular structures. We aimed to evaluate the observer variability to determine tip positioning on CXR, using CT as a gold standard.

Methods
We retrospectively analyzed 107 CT scans of patients with port catheters (January–December 2021). The tip to CAJ distance (DCAJ) was measured on both projectional (PJ) and cross-sectional (CS) CT images by 2 × 2 observers (within and between evaluations). Observational statistics included paired t-tests, repeatability coefficients (RC), and intraclass correlation coefficients (ICC), with data visualized using Bland-Altman plots.

Results
All ICC were &gt;0.9, indicating excellent reliability. The mean difference between observers comparing CS and PJ was 0.13 ± 0.80 cm (P = .10) with outer 95% confidence limits of 1.92 cm and −2.17 cm and an RC of 1.79 cm.

Conclusion
CXR provides a reliable method for CVC tip localization, though assessment variability is ±2 cm.

Advances in knowledge
CXR assessment of CVC tips shows both intra- and inter-individual variability, due to challenges in identifying the CAJ and catheter tip . While considering the 3 cm anatomical zone around the CAJ acceptable, operators should be aware of the 2 cm variability resulting from CXR assessment. To account for this variability and avoid the risk of positioning the tip beyond 3 cm from the CAJ, operators should reduce the CXR-based acceptable zone to 1 cm around the CAJ, impacting approximately 30% of procedures.
Classifying histopathological growth patterns for resected colorectal liver metastasis with a deep learning analysis
Authors: Höppener Diederik J , Aswolinskiy Witali , Qian Zhen , Tellez David , Nierop Pieter M H , Starmans Martijn , Nagtegaal Iris D , Doukas Michail , de Wilt Johannes H W , Grünhagen Dirk J , van der Laak Jeroen A W M , Vermeulen Peter , Ciompi Francesco , Verhoef Cornelis 
Published: October 2024

Abstract

Background
Histopathological growth patterns are one of the strongest prognostic factors in patients with resected colorectal liver metastases. Development of an efficient, objective and ideally automated histopathological growth pattern scoring method can substantially help the implementation of histopathological growth pattern assessment in daily practice and research. This study aimed to develop and validate a deep-learning algorithm, namely neural image compression, to distinguish desmoplastic from non-desmoplastic histopathological growth patterns of colorectal liver metastases based on digital haematoxylin and eosin-stained slides.

Methods
The algorithm was developed using digitalized whole-slide images obtained in a single-centre (Erasmus MC Cancer Institute, the Netherlands) cohort of patients who underwent first curative intent resection for colorectal liver metastases between January 2000 and February 2019. External validation was performed on whole-slide images of patients resected between October 2004 and December 2017 in another institution (Radboud University Medical Center, the Netherlands). The outcomes of interest were the automated classification of dichotomous hepatic growth patterns, distinguishing between desmoplastic hepatic growth pattern and non-desmoplatic growth pattern by a deep-learning model; secondary outcome was the correlation of these classifications with overall survival in the histopathology manual–assessed histopathological growth pattern and those assessed using neural image compression.

Results
Nine hundred and thirty-two patients, corresponding to 3.641 whole-slide images, were reviewed to develop the algorithm and 870 whole-slide images were used for external validation. Median follow-up for the development and the validation cohorts was 43 and 29 months respectively. The neural image compression approach achieved significant discriminatory power to classify 100% desmoplastic histopathological growth pattern with an area under the curve of 0.93 in the development cohort and 0.95 upon external validation. Both the histopathology manual–scored histopathological growth pattern and neural image compression-classified histopathological growth pattern achieved a similar multivariable hazard ratio for desmoplastic versus non-desmoplastic growth pattern in the development cohort (histopathology manual score: 0.63 versus neural image compression: 0.64) and in the validation cohort (histopathology manual score: 0.40 versus neural image compression: 0.48).

Conclusions
The neural image compression approach is suitable for pathology-based classification tasks of colorectal liver metastases.
Partisan Politics in Finland
Authors: Wass Hanna , Tukiainen Janne , Ylisalo Juha , Nieminen Jeremias , Hirvonen Salomo , Isotalo Veikko 
Published: October 2024

Abstract
Traditionally, the Finnish party system has involved a high level of fragmentation yet remarkable stability, consensual decision-making, ideologically broad government coalitions, and mostly modest levels of polarization between parties or voters. These features suggest a limited effect of the party composition of government on economic policy. However, based on studies on close local elections, parliamentary speech, and party manifestos, we argue that the link between party politics and policy outcomes likely plays a role in Finland. Most analyses have examined the extent to which the characteristics of local politicians within the parties affect policy outcomes. These studies show that occupation, education, experience, competence, and residential location of local politicians strongly affect local policies, indicating that, in general, politics matters for policy. We also discuss how consensual national politics may have contributed to the recent success of the populist challenger Finns Party. As a new major player, the party has emphasized the role of sociocultural issues and especially affective polarization, which represents a considerable paradigm shift from the catch-all party policies typical of Finland for many decades. It is thus possible that the link between politics and policy will become more pronounced in the future, motivating further research.
Demographic ageing: an opportunity to rethink economy, society and regions
Authors: Warner Mildred E , Zhang Xue , Guillemot Jonathan 
Published: October 2024

Abstract
Ageing is often depicted negatively, but we challenge passive views, suggesting that an “active ageing” agenda requires rethinking economy, urban form and societal responses. We present demographic trends in ageing, migration and urbanization across global regions. Building from psychological theories of ageing regarding disengagement and continuity, we argue for an adjustment response at the societal level to address needed structural changes in economy, social policy and regional planning. These adjustments should prioritize well-being and purpose over economic growth; social policy that links household, informal and formal care and new approaches to urban and regional planning that remake cities for all ages. Ageing requires new paradigms. These societal adjustments will permit new approaches that could build a more inclusive world.