bluuebunny/crossref_metadata_2025_split huggingface dataset:
An optimized explainable artificial intelligence approach for sustainable clean water
Authors: Ezzat Dalia , Soliman Mona , Ahmed Eman , Hassanien Aboul Ella 
Published: August 2023

AbstractWater, sanitation, and hygiene are essential components of the 2030 agenda for sustainable development. Goal 6 is dedicated to guarantee all societies have access to water and sanitation. Water quality (WQ) assessment is crucial to ensure the availability of clean water. This paper presents an approach called AHA–XDNN for predicting WQ. The proposed approach is based on three pillars to predict WQ with high accuracy and confidence, namely, deep neural networks (DNN), artificial hummingbird algorithm (AHA), and explainable artificial intelligence. The proposed approach involves five phases: data preprocessing, optimization, training, and evaluation. In the first phase, problems such as unwanted noise and imbalance are addressed. In the second phase, AHA is applied to optimize the DNN model’s hyper-parameters. In the third phase, the DNN model is trained on the dataset processed in the first phase. The performance of the optimized DNN model is evaluated using four measurements, and the results are explained and interpreted using SHapley additive exPlanations. The proposed approach achieved an accuracy, average precision, average recall, average F1-score of 91%, 91%, 91.5%, and 91% on the test set, respectively. By comparing the proposed approach with existing models based on artificial neural network (ANN), the proposed approach was able to outperform its counterparts in terms of average recall and average F1-score.
On the benefits of insurance and disaster risk management integration for improved climate-related natural catastrophe resilience
Authors: Sheehan Barry , Mullins Martin , Shannon Darren , McCullagh Orla 
Published: August 2023

AbstractInsurance serves modern society and commerce by pooling risk to reduce the economic impact of disasters. Concurrently, Disaster Risk Management (DRM) scientists, responders and policymakers are co-developingproactiveresilience and mitigation strategies with European citizens against accelerating climate-related natural catastrophes. The increasing frequency and severity of natural catastrophes exacerbates the insurance coverage gap by incurring even greater losses for (re)insurers, leading to higher premiums in exchange for cover or the withdrawal of services entirely. This paper presents a conceptual framework for cross-sectoral collaboration between the insurance and DRM communities towards open, transparent and optimised disaster risk management for all EU citizens and businesses. Furthermore, this research identifies key enabling technologies (satellite, drone, artificial intelligence, blockchain) and novel risk transfer mechanisms with the potential to accelerate societal resilience to climate disasters through effective risk management. The study emphasises the critical role of the insurance industry in effective DRM and highlights where insurers could take amoreactive role across the temporal plane of a natural disaster by engaging in ex-ante interventions to protect those vulnerable to climate change-related risk.
Advance of echocardiography in cardiac amyloidosis
Authors: Liang Shichu , Liu Zhiyue , Li Qian , He Wenfeng , Huang He 
Published: August 2023

AbstractCardiac amyloidosis (CA) occurs when the insoluble fibrils formed by misfolded precursor proteins deposit in cardiac tissues. The early clinical manifestations of CA are not evident, but it is easy to progress to refractory heart failure with an inferior prognosis. Echocardiography is the most commonly adopted non-invasive modality of imaging to visualize cardiac structures and functions, and the preferred modality in the evaluation of patients with cardiac symptoms and suspected CA, which plays a vital role in the diagnosis, prognosis, and long-term management of CA. The present review summarizes the echocardiographic manifestations of CA, new echocardiographic techniques, and the application of multi-parametric echocardiographic models in CA diagnosis.
Metaphyton contributes to open water phytoplankton diversity
Authors: Lukács Áron , Szabó Sándor , T-Krasznai Enikő , Görgényi Judit , Nemes-Kókai Zsuzsanna , B-Béres Viktória , Borics Gábor 
Published: August 2023

AbstractIn contrast to pelagic and benthic realms of the aquatic ecosystems, studies on the metaphytic habitats remain underrepresented in the literature. However, this realm may have a potential impact on composition and diversity of the open water assemblages through metacommunity processes (source-sink dynamics, mass-effect) especially in small ponds with extended littoral zone. Using a limnocorral experiment we studied how metaphyton affects diversity and composition of open water phytoplankton in a small eutrophic pond in the vegetation period. The three habitats (metaphyton, isolated and non-isolated open water) showed considerable differences in their taxa and functional group composition. Abundance-based diversity measures did not reveal remarkable differences among the assemblages of the three habitats. However, taxonomic and functional richness of the metaphyton and the non-isolated part of the pelagial significantly exceeded that of the limnocorral. Incidence-based similarity index values also showed closer resemblance of the metaphyton and plankton samples compared to that of the limnocorral. In the case of several functional groups, their functional redundancy in the metaphyton exceeded that in the open water areas. These results suggest that the metaphyton provides a refuge for several euplanktic elements that survive in the littoral and occasionally enrich the phytoplankton of the open water areas, representing that a within–lake metacommunity processes shape the composition and functioning of the open water areas in standing waters.
Analyzing the Patterns of Questioning Chains and Their Intervention on Student Learning in Science Teacher Preparation
Authors: Wang Jianlan , Wang Yuanhua , Moore Yanhong , Sneed Stacey , Thacker Beth , Hart Stephanie 
Published: August 2023

AbstractQuestioning is a critical instructional strategy for teachers to support students’ knowledge construction in inquiry-oriented science teaching. Existing literature has delineated the characteristics and functions of effective questioning strategies. However, attention has been primarily cast on the format of questioning like open-ended questions in prompting student interactions or class discourses, but not much on science content embedded in questions and how they guide students toward learning objectives. Insufficient attention has been cast on the connection between a chain of questions used by a teacher in the attempt to scaffold student conceptual understanding, especially when students encounter difficulties. Furthermore, existing methods of question analysis from massive information of class discourses are unwieldy for large-scale analysis. Science teacher education needs an instrument to assess a large sample of Pre-service Teachers’ (PST) competencies of not only asking open-ended questions to solicit students’ thoughts but also analyzing the information collected from students’ responses and determining the logical of consecutive responses. This study presented such an instrument for analyzing patterns of 60 PST’s questioning chains from when they taught a science lesson during a methods course and another lesson during student teaching. Cohen’s Kappa was conducted to examine the inter-rater reliability of the coders. The PST’s orientations from the two videos were determined and the correlation between them was compared to test the validity of this instrument. Consideration of the data from this instrument identified patterns of the PSTs’ science teaching, discussed the importance of guiding questions in inquiry teaching, and suggested quantitative studies with this instrument.
Synthesize and characterization of Ag-CuO/rGO nanoparticles as a filler of the PVDF polymer to improve its polar β phase and electrical conductivity for polymer batteries applications
Authors: El-Masry Mai M. 
Published: August 2023

AbstractThis article presents the synthesis and characterization of Ag-CuO/rGO nanoparticles, which serve as a filler for the PVDF polymer to enhance its polar β phase and electrical conductivity for possible use in polymer batteries. The Ag-CuO/rGO nanoparticles were prepared through a straightforward hydrothermal method and incorporated into a PVDF matrix using a solution casting technique. Various techniques were employed to examine the structure, crystallinity, dielectric, and electrical properties of the PVDF/Ag-CuO/rGO nanocomposites. The results revealed that the Ag-CuO/rGO nanoparticles incorporated within the PVDF matrix, promoting the formation of the polar β phase of PVDF. The PVDF/Ag-CuO/rGO nanocomposites displayed a higher dielectric constant and lower dielectric loss compared to pure PVDF. As the Ag-CuO/rGO content increased, so did the electrical conductivity of the nanocomposites, reaching a value of 1.23 × 10− 3 S/cm at 2.5 Wt% Ag-CuO/rGO loading. The enhanced electrical conductivity was attributed to the conductive networks formed by both the Ag-CuO/rGO nanoparticles and the polar β phase of PVDF. These findings indicate that PVDF/Ag-CuO/rGO nanocomposites hold promise for different applications such as polymer batteries.
Motion-aware and data-independent model based multi-view 3D pose refinement for volleyball spike analysis
Authors: Liu Yanchao , Cheng Xina , Ikenaga Takeshi 
Published: August 2023

AbstractIn the volleyball game, estimating the 3D pose of the spiker is very valuable for training and analysis, because the spiker’s technique level determines the scoring or not of a round. The development of computer vision provides the possibility for the acquisition of the 3D pose. Most conventional pose estimation works are data-dependent methods, which mainly focus on reaching a high level on the dataset with the controllable scene, but fail to get good results in the wild real volleyball competition scene because of the lack of large labelled data, abnormal pose, occlusion and overlap. To refine the inaccurate estimated pose, this paper proposes a motion-aware and data-independent method based on a calibrated multi-camera system for a real volleyball competition scene. The proposed methods consist of three key components: 1) By utilizing the relationship of multi-views, an irrelevant projection based potential joint restore approach is proposed, which refines the wrong pose of one view with the other three views projected information to reduce the influence of occlusion and overlap. 2) Instead of training with a large amount labelled data, the proposed motion-aware method utilizes the similarity of specific motion in sports to achieve construct a spike model. Based on the spike model, joint and trajectory matching is proposed for coarse refinement. 3) To finely refine, a point distribution based posterior decision network is proposed. While expanding the receptive field, the pose estimation task is decomposed into a classification decision problem, which greatly avoids the dependence on a large amount of labelled data. The experimental dataset videos with four synchronous camera views are from a real game, the Game of 2014 Japan Inter High School of Men Volleyball. The experiment result achieves 76.25%, 81.89%, and 86.13% success rate at the 30mm, 50mm, and 70mm error range, respectively. Since the proposed refinement framework is based on a real volleyball competition, it is expected to be applied in the volleyball analysis.
Compound Dihuang Granule Changes Gut Microbiota of MPTP-Induced Parkinson’s Disease Mice via Inhibiting TLR4/NF-κB Signaling
Authors: He Zhu-qing , Huan Peng-fei , Wang Li , He Jian-cheng 
Published: August 2023

AbstractIntestinal microbiota was connected to Parkinson’s Disease (PD) pathology. The ancient Chinese medication for PD is Compound Dihuang Granule (CDG), and we found a neuroprotective function in treating the constipation of PD patients. Nevertheless, the mechanism of action still needs to be clarified. We predicted the probable targets of CDG against PD through Traditional Chinese medicine (TCM) network pharmacology and verified the analysis through animal experiments in vivo. The protein–protein interaction (PPI) network analysis screened PD-related genes, including Toll-like receptor 4(TLR4), TANK-binding kinase 1(TBK1), Nuclear Factor- Kappa B (NF-κB), and Tumor necrosis factor (TNF). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses proved that the NF-κB and toll-like receptor signaling pathways serve a key function in CDG therapy of PD. Molecular docking analysis demonstrated that CDG strongly connected to TLR4/NF-κB. Experiments findings indicated that CDG improved the damage of dopaminergic neurons and gut microbial dysbiosis, ameliorated motor impairments, and suppressed the PD-associated inflammation and oxidative stress in mice induced by 1-methyl-4-phenyl-1,2,3,6-tetrahy dropyridine (MPTP). CDG suppressed the inflammatory proteins in the colon and protected the intestinal barrier. Overall, CDG improved gut microbial in PD by blocking the pathway of TLR4/NF-κB.
The explanatory nature of constraints: Law-based, mathematical, and causal
Authors: Ross Lauren N. 
Published: August 2023

AbstractThis paper provides an analysis of explanatory constraints and their role in scientific explanation. This analysis clarifies main characteristics of explanatory constraints, ways in which they differ from “standard” explanatory factors, and the unique roles they play in scientific explanation. While current philosophical work appreciates two main types of explanatory constraints, this paper suggests a new taxonomy: law-based constraints, mathematical constraints, and causal constraints. This classification helps capture unique features of constraint types, the different roles they play in explanation, and it includes causal constraints, which are often overlooked in this literature.
Incorporating (variational) free energy models into mechanisms: the case of predictive processing under the free energy principle
Authors: Piekarski Michał 
Published: August 2023

AbstractThe issue of the relationship between predictive processing (PP) and the free energy principle (FEP) remains a subject of debate and controversy within the research community. Many researchers have expressed doubts regarding the actual integration of PP with the FEP, questioning whether the FEP can truly contribute significantly to the mechanistic understanding of PP or even undermine such integration altogether. In this paper, I present an alternative perspective. I argue that, from the viewpoint of the constraint-based mechanisms approach, the FEP imposes an important constraint, namely variational free energy, on the mechanistic architecture proposed by PP. According to the constraint-based mechanisms approach, high-level cognitive mechanisms are integral parts of extensive heterarchical networks that govern the physiology and behavior of agents. Consequently, mechanistic explanations of cognitive phenomena should incorporate constraints and flows of free energy as relevant components, given that the implemented constraints operate as long as free energy is available. Within this framework, I contend that the FEP provides a relevant constraint for explaining at least some biological cognitive mechanisms described in terms of Bayesian generative models that minimize prediction errors.
Polystyrene and low-density polyethylene pellets are less effective in arsenic adsorption than uncontaminated river sediment
Authors: Nguyen Thanh Kien , Li Xiaowei , Ren Lei , Huang Yuhan , Zhou John L. 
Published: August 2023

AbstractThe adsorption process of inorganic arsenic (As) plays an important role in its mobility, bioavailability, and toxicity in the river environment. In this work, the adsorption of dissolved arsenite (As(III)) and arsenate (As(V)) by microplastics (MPs) pellets (polystyrene (PS) and low-density polyethylene (LDPE)), river sediment, and their mixture were investigated to assess the adsorption affinities and mechanism. The adsorption kinetics showed slow and mild rising zones from the natural behavior of the chemical adsorption. The results indicated that both MP characteristics and water properties played a significant role in the adsorption behavior of inorganic As species. The As adsorption equilibrium was modeled well by both Langmuir and Freundlich isotherms and partly fitted with the Sips model suggesting that both mono-layer and multi-layer adsorption occurred during adsorption The spontaneous adsorption process for both As(III) and As(V) was evidenced by the adsorption thermodynamics. The maximum adsorption capacities of As(III) and As(V) reached 143.3 mg/kg and 109.8 mg/kg on PS in deionized water, which were higher than those on sediment-PS mixture (119.3 mg/kg, 99.2 mg/kg), which were all lower than on sediment alone (263.3 mg/kg, 398.7 mg/kg). The Fourier transform infrared spectroscopy analysis identified that As(III) and As(V) interaction with sediment surface functional groups was the main adsorption mechanism from surface complexation and coordination. Two functional groups of polystyrene (-NH2, -OH) were mainly involved in the adsorption of inorganic As species on PS, while -COO- and -OH functional groups contributed to the adsorption mechanism of inorganic As species on LDPE. The findings provide valuable insight on the adsorption behavior and mechanisms of As(III) and As(V) in river systems in the presence of MPs particles. Both PS and LDPE were shown to be less effective than river sediment in the adsorption of As species from water, which provides a different perspective in understanding the scale of MPs impact in pollutant transport in the aquatic environment.
Graphical Abstract
Connecting Through Caregiving: Reappraising Intergeneration Relationship in Dementia Caregiving
Authors: Au Alma , Lai Daniel W. L. , Chow Amy Y. M. , Lai Simon , Cheng Sheung-Tak 
Published: August 2023

Abstract
Purpose
Dementia caregiving presents a challenge in life transition wherein the adult child is caring for his or her parents. The study examined the effects of a telephone-administered perspective-taking intervention for adult child caregivers of persons with Alzheimer’s Disease and Dementia to reduce levels of depressive symptoms as well as presence and reaction to behavioral problems and also to enhance social support. The mediation effect of perspective-taking on depressive symptoms was also examined.

Method
A two-arm cluster randomized controlled trial was conducted for 176 participants with 24 clusters for the 12-week Connecting Through Caregiving (CTC) intervention and Basic Skill Training (BSB). The CTC intervention integrated perspective taking with basic skill training. The primary outcome was depressive symptoms. The first secondary outcome was the presence and reaction to behavioral problems in the care-recipients. The second secondary outcome was social support. The trial also examined whether intervention effects were mediated by perspective-taking. Measures were obtained at baseline Week 1 (pre-intervention), Week 12 (post-intervention) and Week 24 (three-month follow up).

Results
Data was collected from 2018 to 2021. Ninety-one participants completed the intervention for CTC and eighty-five completed BSB. In terms of the primary outcome, as compared to the BSB group, the CTC group reported significantly greater reductions in depressive symptoms. For the secondary outcomes, the CTC group also reported reduced perceived presence and reaction to behavioral and memory problems of the care recipient as well as increased social support. Perspective-taking was found to mediate between intervention and reduction of depressive symptoms of the caregiver. No moderation effect on the intervention was found for the presence of COVID-19.

Conclusion
The results provided support for the efficacy of the CTC telephone intervention. Findings have implications for enhancing sustainable care for non-digitalized older adults in the wider society.

Trial Registration
ClinicalTrial.gov NCT03030027
Ist-Analysen, Theorien und Effekte in evaluierten Interventionen der betrieblichen Gesundheitsförderung (BGF)
Authors: Blumentritt Sebastian , Luig Teresa , Schoch Nora , Enklaar Arnold , Englert Heike 
Published: August 2023

Zusammenfassung
Hintergrund
Zur qualitätsbasierten Weiterentwicklung effizienter und bedarfsorientierter Maßnahmen der betrieblichen Gesundheitsförderung (BGF) ist es von Interesse, einen Einblick in Ihren Aufbau, die Ausgestaltung und den Ablauf der Maßnahmen der letzten zwei Jahrzehnte zu erlangen.

Zielsetzung
Auf Basis der arbeitsschutzorientierten Leitlinien des GKV-Spitzenverbands wird untersucht, ob vor der Umsetzung von BGF-Maßnahmen Bedarfserhebungen mittels Ist-Analysen durchgeführt wurden. Zusätzlich wird betrachtet, ob die Analysen „weiche“ Faktoren wie Kultur, Führung und Beziehungsklima beinhalten. Weiter wird analysiert, welche wissenschaftlichen Theorien und Modelle den Maßnahmen zugrunde liegen. Zudem führt die Untersuchung eine Wirksamkeitsbetrachtung durch, um zu ermitteln, welche Effekte die Maßnahmen erzielten.

Methode
Das vorliegende Literatur-Review untersucht wissenschaftlich evaluierte BGF-Maßnahmen aus den Jahren 2000–2020. Hierzu wurde eine systematische Literaturrecherche in den zwei elektronischen Datenbanken Scopus und Web of Science für den benannten Publikationszeitraum durchgeführt.

Ergebnisse
Die Einschlusskriterien erfüllten 41 Artikel. Nur 4 der Studien führten eine Ist-Analyse zur Bedarfsbestimmung von BGF-Maßnahmen durch. 25 Studien führten Ist-Analysen im Rahmen der Maßnahmen durch, alle waren arbeitsschutzorientiert. Vier Studien inkludierten in ihrer Erhebung zu Beginn Teilaspekte von weichen Faktoren. In 12 Studien wurden den evaluierten Interventionen unterschiedliche wissenschaftliche Theorien und Modelle zugrunde gelegt. Alle Studien berichteten mindestens für einzelne Untersuchungsparameter von positiven Effekten.

Schlussfolgerung
Vor dem Hintergrund des Strukturwandels der Wirtschaft und der beständig zunehmenden Humanisierung der Arbeit spielen wissenschaftsbasierte Analyseinstrumente zur Bedarfsbestimmung eine große Rolle. Zukünftige Analyseinstrumente sollten von der Wissenschaft konzipiert und erprobt werden und zusätzlich zur Arbeitsschutzorientierung die immateriellen, weichen Faktoren Kultur, Führung und Beziehungsklima beinhalten. Trotz der Empfehlungen, Maßnahmen auf Grundlage von Theorien und Modellen zu konzipieren, wurde dieses Potenzial von nur wenigen wissenschaftlich evaluierten Studien genutzt. Die Wirksamkeitsbetrachtung zeigt, dass alle Studien mindestens für Teile Ihrer Evaluation von positiven Effekten berichten. Dieses Untersuchungsergebnis des Reviews weist auf ein Publikationsbias hin.