bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing the Robustness of Hybrid Metal-Composite Connections Through 3D Printed Micro Penetrative Anchors
Authors: Raimondi Luca , Tomesani Luca , Zucchelli Andrea 
Published: April 2024

AbstractThis work proposes a novel solution for manufacturing hybrid metal-composite joints, in which different pin shapes are evaluated for their capability to penetrate long carbon fiber epoxy composites successfully and for the mechanical behavior determined by each configuration. On the metal side, pins are manufactured by Laser Powder Bed Fusion (LPBF), downsizing the currently adopted solutions and, at the same time, developing new blocking features aimed at enhancing the mechanical properties of the joint. The different configurations were evaluated in two distinct experiments: the first to evaluate the induced defects in the composite substrate and the second to characterize the mechanical behavior of the joint. It emerges that smaller pins produce much less damage and misalignments in the composite structure with respect to the conventional pin solution, whereas the new “blocking features” configurations consistently increase maximum pullout load and energy with respect to the conventional pin solution, with the same level of fiber damage.
Survey of automatic plankton image recognition: challenges, existing solutions and future perspectives
Authors: Eerola Tuomas , Batrakhanov Daniel , Barazandeh Nastaran Vatankhah , Kraft Kaisa , Haraguchi Lumi , Lensu Lasse , Suikkanen Sanna , Seppälä Jukka , Tamminen Timo , Kälviäinen Heikki 
Published: April 2024

AbstractPlanktonic organisms including phyto-, zoo-, and mixoplankton are key components of aquatic ecosystems and respond quickly to changes in the environment, therefore their monitoring is vital to follow and understand these changes. Advances in imaging technology have enabled novel possibilities to study plankton populations, but the manual classification of images is time consuming and expert-based, making such an approach unsuitable for large-scale application and urging for automatic solutions for the analysis, especially recognizing the plankton species from images. Despite the extensive research done on automatic plankton recognition, the latest cutting-edge methods have not been widely adopted for operational use. In this paper, a comprehensive survey on existing solutions for automatic plankton recognition is presented. First, we identify the most notable challenges that make the development of plankton recognition systems difficult and restrict the deployment of these systems for operational use. Then, we provide a detailed description of solutions found in plankton recognition literature. Finally, we propose a workflow to identify the specific challenges in new datasets and the recommended approaches to address them. Many important challenges remain unsolved including the following: (1) the domain shift between the datasets hindering the development of an imaging instrument independent plankton recognition system, (2) the difficulty to identify and process the images of previously unseen classes and non-plankton particles, and (3) the uncertainty in expert annotations that affects the training of the machine learning models. To build harmonized instrument and location agnostic methods for operational purposes these challenges should be addressed in future research.
Assessment of Laws of the Wall During Flame–Wall Interaction of Premixed Flames Within Turbulent Boundary Layers
Authors: Ahmed Umair , Ghai Sanjeev Kr. , Chakraborty Nilanjan 
Published: April 2024

AbstractThe validity of the usual laws of the wall for Favre mean values of the streamwise velocity component and temperature for non-reacting flows has been assessed for turbulent premixed flame-wall interaction using Direct Numerical Simulation (DNS) data. Two different DNS databases corresponding to friction velocity-based Reynolds number of 110 and 180 representing unsteady head-on quenching of statistically planar flames within turbulent boundary layers have been considered. The usual log-law based expressions for the Favre mean values of the streamwise velocity and temperature for the inertial layer have been found to be inadequate at capturing the corresponding variations obtained from DNS data. The underlying assumptions of constant shear stress and the equilibrium of production and dissipation of turbulent kinetic energy underpinning the derivation of the usual log-law for the mean streamwise velocity have been found to be rendered invalid within the usual inertial layer during flame-wall interaction for both cases considered here. The heat flux does not remain constant within the usual inertial layer, and the turbulent flux of temperature exhibits counter-gradient transport within the so-called inertial layer for the cases considered in this work. These render the assumptions behind the derivation of the usual log-law for temperature to be invalid for application to turbulent flame-wall interaction. It has been found that previously proposed empirical modifications to the existing laws of the wall, which account for density and kinematic viscosity variations with temperature, do not significantly improve the agreement with the corresponding DNS data in the inertial layer and the inaccurate approximations for the kinematic viscosity compensated wall normal distance and the density compensated streamwise velocity component contribute to this disagreement. The DNS data has been utilised here to propose new expressions for the kinematic viscosity compensated wall normal distance and the density compensated streamwise velocity component, which upon using in the empirically modified law of wall expressions have been demonstrated to provide reasonable agreement with DNS data.
Terahertz time-domain spectroscopy as a novel tool for crystallographic analysis in cellulose: tracking lattice changes following physical treatments
Authors: Wang Han , Aoki Dan , Teramoto Yoshikuni , Tsuchikawa Satoru , Inagaki Tetsuya 
Published: April 2024

AbstractThe authors’ series of studies aimed to explore the potential of terahertz time-domain spectroscopy (THz-TDS) in cellulose crystallographic studies, since THz radiation can detect most intermolecular vibrations and respond to lattice phonons. In this study, we tracked changes in four types of cellulose after ball milling. As the planetary ball milling time increases, it is observed through electron microscopy that the four types of cellulose particles are gradually destroyed into finer particles, while gel permeation chromatography can prove that the molecular weight gradually decreases after ball milling and the dispersity gradually approaches one, which indicates that the dispersion of the material was reduced. The most fascinating observation was made by THz-TDS, that is we have confirmed that after ball milling, the absorption characteristics of cellulose I and II in cellulose I treated with 10% NaOH (crystalline partial transition from cellulose I to II) exhibited an opposite trend. Specifically, the absorption of cellulose II at 2.40THz and 2.77THz increased, while the absorption of cellulose I at 2.11THz and 3.04THz decreased after ball milling, which suggests an increased conversion rate of cellulose I to cellulose II post-milling. Cellulose with different crystalline allomorphs shows different characteristic absorption in the THz region, and the peak position will not change even after the ball milling, only the absorption intensity changes. Although it can be observed through the most traditional X-ray diffraction method that the crystallinity index of all cellulose samples gradually decreases after ball milling. However, different from the THz results, the change after ball milling of cellulose I treated with 10% NaOH is only reflected in very subtle pattern changes, that is, the peak close to the 200 crystalline plane position is slightly shifted after ball milling.
Almost optimal manipulation of pairwise comparisons of alternatives
Authors: Szybowski Jacek , Kułakowski Konrad , Ernst Sebastian 
Published: April 2024

AbstractThe role of an expert in the decision-making process is crucial. If we ask an expert to help us to make a decision we assume their honesty. But what if the expert is dishonest? Then, the answer on how difficult it is for an expert to provide manipulated data in a given case of decision-making process becomes essential. In the presented work, we consider manipulation of a ranking obtained by the Geometric Mean Method applied to a pairwise comparisons matrix. More specifically, we propose an algorithm for finding an almost optimal way to swap the positions of two selected alternatives in a ranking. We also define a new index which measures how difficult such manipulation is in a given case.
Co-designing a Physical Activity Service for Refugees and Asylum Seekers Using an Experience-Based Co-design Framework
Authors: McKeon Grace , Curtis Jackie , Rostami Reza , Sroba Monika , Farello Anna , Morell Rachel , Steel Zachary , Harris Mark , Silove Derrick , Parmenter Belinda , Matthews Evan , Jamaluddin Juliana , Rosenbaum Simon 
Published: April 2024

AbstractPeople from refugee and asylum seeker backgrounds resettling in Australia often experience intersecting risks for poor mental and physical health. Physical activity can promote better health outcomes, however there are limited programs tailored for this population. Therefore, understanding how to support refugees and asylum seekers to engage in physical activity is crucial. This paper aims to describe how the experience-based co-design (EBCD) process was used to identify priorities for a new physical activity service for refugees and asylum seekers. Using an EBCD framework we conducted qualitative interviews and co-design workshops with service users (refugees and asylum seekers living in the community) and service providers at a community Centre in Sydney, Australia. Sixteen participants, including eight service users and eight service providers engaged in the EBCD process over 12-months. The interviews revealed common themes or ‘touchpoints’ including barriers and enablers to physical activity participation such as access, safety and competing stressors. Subsequent co-design focus groups resulted in the establishment of five fundamental priorities and actionable strategies; ensuring cultural and psychological safety, promoting accessibility, facilitating support to access basic needs, enhancing physical activity literacy and fostering social connection. Using EBCD methodology, this study used the insights and lived experiences of both service users and providers to co-design a physical activity service for refugees and asylum seekers which is safe, supportive, social and accessible. The results of the implementation and evaluation of the program are ongoing.
Making the Unseen Seen: The Role of Signaling and Novelty in Rating Metaphors
Authors: Ahrens Kathleen , Burgers Christian , Zhong Yin 
Published: April 2024

AbstractComprehension of metaphorical expressions differs with their degree of novelty. Conventional metaphors are typically comprehended as easily as literal sentences, while novel metaphors are responded to less quickly than their conventional counterparts. However, the influence of metaphor signals on the interpretability and acceptability of sentences with metaphors, especially their potential interaction with novelty, remains an open question. We conducted six online experiments among 1,694 native speakers of American English to examine how interpretability and acceptability ratings of individually presented sentences were affected by metaphor novelty and different types of metaphor signals. Across all six experiments, we consistently found that novel metaphors decreased the interpretability and acceptability of sentences compared to both conventional metaphors and literal controls. Signals, on the contrary, did not impact the interpretability or acceptability of the sentences. Moreover, only in experiment 3b did we find an interaction between metaphor type and signals. Specifically, when a metaphor was marked by double signals (i.e., both lexical signals and a typographical signal were added around the metaphorical keywords) vs. no signals, acceptability of novel metaphors increased, but acceptability of conventional metaphors decreased. We hypothesize that the double signaling of novel metaphors marks their novelty, making them more acceptable. By contrast, the double signaling of conventional metaphors may have been perceived as redundant, leading to a lower acceptability.
Exploring the determinants of disaster and climate resilience building in Zimbabwe’s rural communities
Authors: Nyahunda Louis , Nemakonde Livhuwani David , Khoza Sizwile 
Published: April 2024

AbstractWith the burgeoning threats from natural hazards and extreme weather events driven by climate change in every section and sector of society, building resilience against disasters and risks posed by climate change has become an unescapable discourse. The study’s main thrust is to establish the determinants of resilience building in Zimbabwe’s rural communities. The study adopted the qualitative constructivist grounded theory approach in conjunction with participatory action research to gain insights from community members and traditional leaders. A total of forty-six participants from Chimanimani District, Zimbabwe participated in the study. The findings revealed that the availability of natural and human resources, collective efficacy, government and development agency support systems, indigenous knowledge systems, and livelihood diversification were crucial determinants of resilience building for rural communities in Zimbabwe. The identified determinants for resilience building signal that these determinants need to be harnessed to inform policy and practice interventions. Furthermore, the availability of the identified determinants implies that rural communities can minimise, and prevent losses, reduce exposure to natural hazards, disasters and climate change risks and manage the impacts of natural hazards whenever they emerge. The study recommends that these determinants be complemented by access to technology, resilient community infrastructures, robust social protection systems, and hazard risk assessment participatory processes by rural communities. In addition, effective emergency and health services, among other contingent measures essential to improve community resilience.
Parsimonious consensus hierarchies, partitions and fuzzy partitioning of a set of hierarchies
Authors: Bombelli Ilaria , Vichi Maurizio 
Published: April 2024

AbstractMethodology is described for fitting a fuzzy partition and a parsimonious consensus hierarchy (ultrametric matrix) to a set of hierarchies of the same set of objects. A model defining a fuzzy partition of a set of hierarchical classifications, with every class of the partition synthesized by a parsimonious consensus hierarchy is described. Each consensus includes an optimal consensus hard partition of objects and all the hierarchical agglomerative aggregations among the clusters of the consensus partition. The performances of the methodology are illustrated by an extended simulation study and applications to real data. A discussion is provided on the new methodology and some interesting future developments are described.
Efficient processing of coverage centrality queries on road networks
Authors: Xu Yehong , Zhang Mengxuan , Wu Ruizhong , Li Lei , Zhou Xiaofang 
Published: April 2024

AbstractCoverage Centrality is an important metric to evaluate vertex importance in road networks. However, current solutions have to compute the coverage centrality of all the vertices together, which is resource-wasting, especially when only some vertices centrality is required. In addition, they have poor adaption to the dynamic scenario because of the computation inefficiency. In this paper, we focus on the coverage centrality query problem and propose a method that efficiently computes the centrality of single vertices without relying on the underlying graph being static by employing the intra-region pruning, inter-region pruning, and top-down search. We further propose the bottom-up search and mixed search to improve efficiency. Experiments validate the efficiency and effectiveness of our algorithms compared with the state-of-the-art method.
Arrhythmogenesis in Fabry Disease
Authors: Roy Ashwin , Cumberland Max J. , O’Shea Christopher , Holmes Andrew , Kalla Manish , Gehmlich Katja , Geberhiwot Tarekegn , Steeds Richard P. 
Published: April 2024

Abstract
Purpose of Review
Fabry Disease (FD) is a rare lysosomal storage disorder characterised by multiorgan accumulation of glycosphingolipid due to deficiency in the enzyme α-galactosidase A. Cardiac sphingolipid accumulation triggers various types of arrhythmias, predominantly ventricular arrhythmia, bradyarrhythmia, and atrial fibrillation. Arrhythmia is likely the primary contributor to FD mortality with sudden cardiac death, the most frequent cardiac mode of death. Traditionally FD was seen as a storage cardiomyopathy triggering left ventricular hypertrophy, diastolic dysfunction, and ultimately, systolic dysfunction in advanced disease. The purpose of this review is to outline the current evidence exploring novel mechanisms underlying the arrhythmia substrate.

Recent Findings
There is growing evidence that FD cardiomyopathy is a primary arrhythmic disease with each stage of cardiomyopathy (accumulation, hypertrophy, inflammation, and fibrosis) contributing to the arrhythmia substrate via various intracellular, extracellular, and environmental mechanisms. It is therefore important to understand how these mechanisms contribute to an individual’s risk of arrhythmia in FD.

Summary
In this review, we outline the epidemiology of arrhythmia, pathophysiology of arrhythmogenesis, risk stratification, and cardiac therapy in FD. We explore how advances in conventional cardiac investigations performed in FD patients including 12-lead electrocardiography, transthoracic echocardiography, and cardiac magnetic resonance imaging have enabled early detection of pro-arrhythmic substrate. This has allowed for appropriate risk stratification of FD patients. This paves the way for future work exploring the development of therapeutic initiatives and risk prediction models to reduce the burden of arrhythmia.
A pilot feasibility and acceptability trial of an internet indicated prevention program for perfectionism to reduce eating disorder symptoms in adolescents
Authors: O’Brien Amy , Anderson Rebecca , Mazzucchelli Trevor G. , Ure Sarah , Egan Sarah J. 
Published: April 2024

Abstract
Purpose
Perfectionism is a transdiagnostic risk factor for eating disorders. Treating perfectionism can reduce symptoms of eating disorders. No research has examined an indicated prevention trial using internet-based Cognitive-Behavioural Therapy for Perfectionism (ICBT-P) in adolescent girls at elevated risk for eating disorders. Our aim was to conduct a preliminary feasibility trial using a co-designed ICBT-P intervention. It was hypothesised that a higher proportion of participants in the ICBT-P condition would achieve reliable and clinically significant change on perfectionism, eating disorders, anxiety and depression, compared to waitlist control.

Methods
Twenty-one adolescent girls with elevated symptoms of eating disorders (M age = 16.14 years) were randomised to a 4-week online feasibility trial of a co-designed ICBT-P prevention program or waitlist control. Qualitative surveys were used to gain participant perspectives.

Results
The ICBT-P condition had a higher proportion of participants achieve reliable change and classified as recovered on perfectionism and symptoms of eating disorders and anxiety, compared to waitlist control. Qualitative findings indicated that 100% of participants found the program helpful.

Conclusion
The results indicate ICBT-P is a feasible and acceptable program for adolescent girls with elevated eating disorder symptoms. Future research is required to examine outcomes in a randomised controlled trial.

Level of evidence
Level III: Evidence obtained from well-designed cohort or case–control analytic studies.

Trial registration number

This trial was prospectively registered with Australian and New Zealand Clinical Trials Registry (ACTRN12620000951954P) on 23/09/2020.
Optimization of nitrogen management reduce nitrogen stress and enhance productivity of super-seeder sown wheat under rice residue incorporation
Authors: Longshang Peace Raising , Singh Virendra Pratap , Chandra Subhash , Shukla Anil , Singh V. K. , Pareek Navneet , Zhiipao R. Rustum , Reddy Kadapa Sreenivas , Duo Hriipulou , Dorjee Lham , Rayapati Karthik 
Published: April 2024

AbstractThe in-situ management of rice straw incorporation has become an essential practice in the rice–wheat cropping system with the growing adoption of super-seeder among farmers. While this equipment facilitates straw incorporation, nutrient immobilization from organic residues during decomposition poses a challenge to production. This study investigates the effect of bio-decomposer, nitrogen (N) level, and N scheduling on on various parameters in super-seeder sown wheat over two consecutive years (2020–21 and 2021–22). The experiment was laid in split-split-plot design without (B0) and with (B1) bio-decomposer, two nitrogen levels 150 (N1) and 180 (N2) kg ha−1 and three N splits (%) viz., 50: 25:25 (S1), 40: 30: 30 (S2), and 30:35:35 (S3) and replicated thrice. Results indicate significantly higher N concentration and uptake at pre- and post-anthesis with N2 and S1 compared to N1, S2, and S3. Post-anthesis N accumulation (post-NA) and remobilization (NR) were notably higher with N2. Dry matter accumulation (DMA) at anthesis and harvest significantly increased with N2 and S1 compared to N1 and S3, leading to significantly improved grain yield by 8.3% and 10.9% (two years mean). Soil urease activity (UA) significantly increased with bio-decomposer, N2, and S1 compared to B0, N1, and S3 at 30 and 60 DAS. Moreover, bio-decomposer enhanced soil microbial biomass carbon (SMBC). These findings underscore the importance of higher N levels with a greater basal N proportion in mitigating N stress and promoting sustainable wheat productivity. It also highlight the significance of effectively utilizing and conserving rice residue in the rice–wheat system.
Data-driven rolling eco-speed optimization for autonomous vehicles
Authors: Yang Ying , Gao Kun , Cui Shaohua , Xue Yongjie , Najafi Arsalan , Andric Jelena 
Published: April 2024

AbstractIn urban settings, fluctuating traffic conditions and closely spaced signalized intersections lead to frequent emergency acceleration, deceleration, and idling in vehicles. These maneuvers contribute to elevated energy use and emissions. Advances in vehicle-to-vehicle and vehicle-to-infrastructure communication technologies allow autonomous vehicles (AVs) to perceive signals over long distances and coordinate with other vehicles, thereby mitigating environmentally harmful maneuvers. This paper introduces a data-driven algorithm for rolling eco-speed optimization in AVs aimed at enhancing vehicle operation. The algorithm integrates a deep belief network with a back propagation neural network to formulate a traffic state perception mechanism for predicting feasible speed ranges. Fuel consumption data from the Argonne National Laboratory in the United States serves as the basis for establishing the quantitative correlation between the fuel consumption rate and speed. A spatiotemporal network is subsequently developed to achieve eco-speed optimization for AVs within the projected speed limits. The proposed algorithm results in a 12.2% reduction in energy consumption relative to standard driving practices, without a significant extension in travel time.