bluuebunny/crossref_metadata_2025_split huggingface dataset:
Green supply chain management and firm sustainable performance: unlocking the role of transactional and transformational leadership in firm sustainable operations
Authors: Abbas Jawad 
Published: May 2024

AbstractCompanies are adopting innovative and environmentally friendly methods and technologies to mitigate the adverse effects of their products and services on the natural environment. Various internal and external factors influence a company’s ability to comply with such sustainability standards. This study specifically examines the connection between a company’s sustainable supply chain operations and a crucial internal factor, namely leadership. It focuses on comparing and contrasting the impacts of transformational and transactional leadership on green supply chain management (GSCM) and the overall sustainable performance of the company. Using a quantitative approach, the author conducted surveys among employees and managers and utilized structural equation modeling to analyze the model. The findings indicate that transformational leadership significantly impacts GSCM practices and sustainable organizational performance (OSP). However, the association between transactional leadership and GSCM is relatively weak. Additionally, it is observed that GSCM positively contributes to OSP. The results emphasize the importance of upper-level management involvement in green initiatives, particularly GSCM, to enhance the company’s environmental performance and ensure its long-term sustainability.
Phenomenology, Perspectivalism and (Quantum) Physics
Authors: French Steven 
Published: May 2024

AbstractIt has been claimed that Massimi’s recent perspectival approach to science sits in tension with a realist stance. I shall argue that this tension can be defused in the quantum context by recasting Massimi’s perspectivalism within a phenomenological framework. I shall begin by indicating how the different but complementary forms of the former are manifested in the distinction between certain so-called ‘-epistemic’ and ‘-ontic’ understandings of quantum mechanics, namely QBism and Relational Quantum Mechanics, respectively. A brief consideration of Dieks’ perspectivism will then lead to a consideration of the much-maligned and typically dismissed role of the observer in the measurement process. This opens the door to London and Bauer’s presentation of a form of ‘phenomenological quantum perspectivalism’ that brings together Massimi’s two forms and explicitly eschews the ‘naïve’ realism that creates the above tension. I shall conclude with some reflections on how intersubjectivity can still be established within this framework, focusing in particular on how Massimi’s idea of ‘interlacing’ scientific perspectives can be accommodated, using the example of a ‘new cosmopolitanism’ that gave rise to Bose-Einstein statistics.
Lipschitz Regularity for a Priori Bounded Minimizers of Integral Functionals with Nonstandard Growth
Authors: Eleuteri Michela , Passarelli di Napoli Antonia 
Published: May 2024

AbstractWe establish the Lipschitz regularity of the a priori bounded local minimizers of integral functionals with non autonomous energy densities satisfying non standard growth conditions under a bound on the gap between the growth and the ellipticity exponent that is reminiscent of the sharp bound already found in [16].
The Future of Obesity Management through Precision Nutrition: Putting the Individual at the Center
Authors: Ulusoy-Gezer Hande Gül , Rakıcıoğlu Neslişah 
Published: May 2024

Abstract
Purpose of Review
The prevalence of obesity continues to rise steadily. While obesity management typically relies on dietary and lifestyle modifications, individual responses to these interventions vary widely. Clinical guidelines for overweight and obesity stress the importance of personalized approaches to care. This review aims to underscore the role of precision nutrition in delivering tailored interventions for obesity management.

Recent Findings
Recent technological strides have expanded our ability to detect obesity-related genetic polymorphisms, with machine learning algorithms proving pivotal in analyzing intricate genomic data. Machine learning algorithms can also predict postprandial glucose, triglyceride, and insulin levels, facilitating customized dietary interventions and ultimately leading to successful weight loss. Additionally, given that adherence to dietary recommendations is one of the key predictors of weight loss success, employing more objective methods for dietary assessment and monitoring can enhance sustained long-term compliance.

Summary
Biomarkers of food intake hold promise for a more objective dietary assessment. Acknowledging the multifaceted nature of obesity, precision nutrition stands poised to transform obesity management by tailoring dietary interventions to individuals' genetic backgrounds, gut microbiota, metabolic profiles, and behavioral patterns. However, there is insufficient evidence demonstrating the superiority of precision nutrition over traditional dietary recommendations. The integration of precision nutrition into routine clinical practice requires further validation through randomized controlled trials and the accumulation of a larger body of evidence to strengthen its foundation.
DIAR: a blockchain-based system for generation and verification of academic diplomas
Authors: Rustemi Avni , Dalipi Fisnik , Atanasovski Vladimir , Risteski Aleksandar 
Published: May 2024

AbstractNowadays, the centralized systems used in higher education institutions are sophisticated and have high security mechanisms, offering secure data transfer and real-time encryption. Despite the prevalent usage of centralized systems in many institutions, particularly those within the realm of higher education, some unresolved concerns persist pertaining to privacy, potential abuse, transparency, and the limited capacity to digitize numerous services. Blockchain systems are considered as a potential solution for addressing these constraints. This study begins by highlighting the significance of implementing blockchain systems in higher education institutions, while also outlining the obstacles encountered by researchers in this domain. Centralized systems and blockchain systems are distinguished, with a description of the challenges related to data transfer and adaptation to different platforms. A thorough explanation of the proposed blockchain system begins with a presentation of the conceptual model, followed by a detailed architecture of the processes that would be executed by the system, with particular emphasis on the generation and authentication of academic credentials. Additionally, an analysis is provided on the significance of smart contracts in the programming of blockchain systems. This includes a detailed explanation of the main smart contract architecture used in the proposed blockchain system. This article aims to explore the development of a proposed blockchain system and its practical implementation for testing purposes using specific scenarios and data in the foreseeable future.
Modeling rehabilitation dataset to implement effective AI assistive systems
Authors: Mennella Ciro , Maniscalco Umberto , Pietro Giuseppe De , Esposito Massimo 
Published: May 2024

AbstractThe demand for automated systems monitoring and supporting patients in their home-based recovery programs is substantial. While emerging technologies have been proposed as potential solutions to enhance at-home patient care, limited systems are in place due to their challenges in offering real-time monitoring and corrective feedback. Most proposed methodologies provide an overall measure or score for the executed movement. The proposed work involves the adaptation of an existing published dataset to cater to the needs of a system capable of remotely assisting patients, effectively acting as a virtual physical therapist able to provide corrective feedback. A dataset containing a set of three simple exercises for shoulder rehabilitation was processed. Each movement was meticulously annotated for temporal and categorical motion domains to monitor exercise execution in terms of the range of motion completeness and to evaluate compensatory movement patterns. This work carries substantial significance by offering a standardized and easily accessible model for human movement data, thus fostering the advancement of digital assistive systems designed to support home-based rehabilitation programs.
Evaluating Adaptation Pathways in a Complex Multi‐Risk System
Authors: Schlumberger Julius , Haasnoot Marjolijn , Aerts Jeroen C. J. H. , Bril Veerle , van der Weide Lars , de Ruiter Marleen 
Published: May 2024

AbstractDisaster Risk Management (DRM) is complex due to interacting climate risks from interacting hazards and sectors. We develop a synthetic multi‐risk test case to explore the effects of these interactions on decision‐making under deep uncertainty. The test case accounts for changes in hazard impacts and occurrence frequency due to interactions between floods and droughts. Interactions between the shipping, housing and agricultural sectors are considered as well. We use this test case to explore the utility of the Dynamic Adaptive Policy Pathways for Multi‐Risk (DAPP‐MR) framework. DAPP‐MR has been introduced to assess DRM policies' effectiveness under deep uncertainties and to develop integrated adaptive strategies considering interactions across hazards, sectors and time. With the test case, we show that the stage‐wise approach of DAPP‐MR, which gradually increases the complexity of the analysis, can facilitate the evaluation process. Earlier stages of the analysis can be used to establish the direct cause‐effect relations, later stages allow us to identify whether additional interacting factors have a significant effect on the direct cause‐effect relations. As a result, decision‐makers can gain insights into dependencies and their relevance for developing short‐to long‐term strategies under deep uncertainty. We show that multi‐risk interactions can lead to non‐linear effects that influence the outcome of the policy analysis, for example, the indirect influence of a decision in one sector on another. Future work could investigate further improving the operationalization of this staged approach as well as extending the set of uncertainties, dynamics and decision‐rules accounted for in the multi‐risk test case.
The Distribution Pattern of Ground Movement and Co‐Seismic Landslides: A Case Study of the 5 September 2022 Luding Earthquake, China
Authors: Li W. P. , Wu Y. M. , Gao X. , Wang W. M. , Yang Z. H. , Liu H. J. 
Published: May 2024

AbstractMajor earthquakes can cause extensive landsliding that poses a major threat to both property and human lives. In addition to co‐seismically triggered ground failure, the earthquake‐affected region remains vulnerable to landslides due to loosened and unstable materials and structures. Many researchers have studied landslide distributions and their controlling factors after earthquakes, but the function of ground motion is unclear. To investigate the connection in a strike‐slip earthquake, we analyzed the 5 September 2022 Luding earthquake (Mw 6.6) in Sichuan Province, China. We interpreted remote‐sensing images to obtain the landslide distribution before and after the earthquake, calculated surface deformation from D‐InSAR data (pre‐ and post‐earthquake), utilized a point‐source model for the focal mechanism inversion, and then constructed a finite fault model for the rupture slip. There are clear differences in the landslide distributions on the two sides of the fault before and after the earthquake. The density of co‐seismic landslides on the west side of the fault exceeded that on the east side. The patterns of surface deformation and ground motion indicated that the areas with larger deformation and motion were associated with more landslides. Furthermore, the landslide size decreased with distance from the fault. A new finding is that co‐seismic landslides induced by strike‐slip earthquakes result in high landslide concentration on both sides of the fault, while previous studies find that co‐seismic landslides triggered by thrust earthquakes present a hanging wall concentrated distribution pattern. These findings contribute to a more comprehensive understanding of the connection between ground movement patterns and landslide distributions.
Chasmophyte associated stress tolerant bacteria confer drought resilience to chickpea through efficient nutrient mining and modulation of stress response
Authors: Das Sudipta , Chakdar Hillol , Kumar Adarsh , Singh Rajni , Saxena Anil Kumar 
Published: May 2024

AbstractIn the present study, ten (10) selected bacteria isolated from chasmophytic wild Chenopodium were evaluated for alleviation of drought stress in chickpea. All the bacterial cultures were potential P, K and Zn solubilizer. About 50% of the bacteria could produce Indole-3-acetic acid (IAA) and 1-aminocyclopropane-1-carboxylate (ACC) deaminase. The bacteria showed wide range of tolerance towards pH, salinity, temperature and osmotic stress. Bacillus paralicheniformis L38, Pseudomonas sp. LN75, Enterobacter hormachei subsp. xiangfengensis LJ89, B. paramycoides L17 and Micrococcus luteus LA9 significantly improved growth and nutrient (N, P, K, Fe and Zn) content in chickpea under water stress during a green house experiment conducted following a completely randomized design (CRD). Application of Microbacterium imperiale LJ10, B. stercoris LN74, Pseudomonas sp. LN75, B. paralicheniformis L38 and E. hormachei subsp. xiangfengensis LJ89 reduced the antioxidant enzymes under water stress. During field experiments conducted following randomized block design (RBD), all the bacterial inoculations improved chickpea yield under water stress. Highest yield (1363 kg ha−1) was obtained in plants inoculated with Pseudomonas sp. LN75. Pseudomonas sp. LN75, B. paralicheniformis L38 and E. hormachei subsp. xiangfengensis LJ89 have potential as microbial stimulants to alleviate the water stress in chickpea. To the best of our knowledge this is the first report of using chasmophyte associated bacteria for alleviation of water stress in a crop plant.
A comprehensive analysis of COVID-19 nonlinear mathematical model by incorporating the environment and social distancing
Authors: Riaz Muhammad , Shah Kamal , Abdeljawad Thabet , Amacha Inas , Al-Jaser Asma , Alqudah Manar 
Published: May 2024

AbstractThis research conducts a detailed analysis of a nonlinear mathematical model representing COVID-19, incorporating both environmental factors and social distancing measures. It thoroughly analyzes the model’s equilibrium points, computes the basic reproductive rate, and evaluates the stability of the model at disease-free and endemic equilibrium states, both locally and globally. Additionally, sensitivity analysis is carried out. The study develops a sophisticated stability theory, primarily focusing on the characteristics of the Volterra–Lyapunov (V–L) matrices method. To understand the dynamic behavior of COVID-19, numerical simulations are essential. For this purpose, the study employs a robust numerical technique known as the non-standard finite difference (NSFD) method, introduced by Mickens. Various results are visually presented through graphical representations across different parameter values to illustrate the impact of environmental factors and social distancing measures.
Harnessing the runoff reduction potential of urban bioswales as an adaptation response to climate change
Authors: Lu Lingwen , Johnson Matthew , Zhu Fangfang , Xu Yaoyang , Ruan Tian , Chan Faith Ka Shun 
Published: May 2024

AbstractNature-based solutions (NbS), including China's Sponge City Program (SCP), can address the challenges urban communities face due to surface runoff and flooding. The current capacity of SCP facilities in urban environments falls short of meeting the demands placed on communities by climate change. Bioswales are a form of SCP facility that plays an important role in reducing surface runoff by promoting infiltration. This study assesses the potential of SCP facilities to reduce runoff in urban communities under climate change using the storm water management model. The study site in Ningbo, China, was used to evaluate the potential role of bioswales in reducing runoff risks from climate change. We found that bioswales were most effective in scenarios when rainfall peaks occurred early and were less effective in right-skewed rainfall events. The overall performance of SCP facilities was similar across all climate scenarios. To maintain the current protection level of SCP facilities, bioswales would need to cover at least 4% of the catchment area. These findings from Ningbo provide a useful method for assessing NbS in other regions and indicative values for the increase in the bioswale coverage needed to adapt to climate change.
Polyetheretherketone bioactivity induced by farringtonite
Authors: Martínková Martina , Zárybnická Lucie , Viani Alberto , Killinger Michael , Mácová Petra , Sedláček Tomáš , Oralová Veronika , Klepárník Karel , Humpolíček Petr 
Published: May 2024

AbstractPolyetheretherketone (PEEK) is considered as an excellent biomaterial for bone grafting and connective tissue replacement. The clinical potential is, however, limited by its bioinertness, poor osteoconduction, and weak antibacterial activity. These disadvantages can be overcome by introducing suitable additives to produce mineral-polymer composites or coatings. In this work, a PEEK-based bioactive composite has been obtained by blending the polymer with magnesium phosphate (Mg3(PO4)2) particles in amounts ranging from 1 to 10 wt.% using the hot press technique. The obtained composite exhibited improved mechanical and physical properties, above the lower limits set for bone engineering applications. The tested grafts were found to not induce cytotoxicity. The presence of magnesium phosphate induced the mineralisation process with no adverse effects on the expression of the marker crucial for osteoblastic differentiation. The most promising results were observed in the grafts containing 1 wt.% of magnesium phosphate embedded within the PEEK matrix. The improved bioactivity of grafts, together with suitable physical–chemical and mechanical properties, indicate this composite as a promising orthopaedic implant material.
Auditory rhythm facilitates perception and action in children at risk for developmental coordination disorder
Authors: Carrillo Chantal , Chang Andrew , Armstrong Hannah , Cairney John , McAuley J. Devin , Trainor Laurel J. 
Published: May 2024

AbstractDevelopmental Coordination Disorder (DCD) is a common neurodevelopmental disorder featuring deficits in motor coordination and motor timing among children. Deficits in rhythmic tracking, including perceptually tracking and synchronizing action with auditory rhythms, have been studied in a wide range of motor disorders, providing a foundation for developing rehabilitation programs incorporating auditory rhythms. We tested whether DCD also features these auditory-motor deficits among 7–10 year-old children. In a speech recognition task with no overt motor component, modulating the speech rhythm interfered more with the performance of children at risk for DCD than typically developing (TD) children. A set of auditory-motor tapping tasks further showed that, although children at risk for DCD performed worse than TD children in general, the presence of an auditory rhythmic cue (isochronous metronome or music) facilitated the temporal consistency of tapping. Finally, accuracy in the recognition of rhythmically modulated speech and tapping consistency correlated with performance on the standardized motor assessment. Together, the results show auditory rhythmic regularity benefits auditory perception and auditory-motor coordination in children at risk for DCD. This provides a foundation for future clinical studies to develop evidence-based interventions involving auditory-motor rhythmic coordination for children with DCD.
Multi-omics analysis of macrophage-associated receptor and ligand reveals a strong prognostic signature and subtypes in hepatocellular carcinoma
Authors: Zhao Yulou , Chen Cong , Chen Kang , Sun Yanjun , He Ning , Zhang Xiubing , Xu Jian , Shen Aiguo , Zhao Suming 
Published: May 2024

AbstractHepatocellular carcinoma (HCC) is a significant contributor to morbidity and mortality worldwide. The interaction between receptors and ligands is the primary mode of intercellular signaling and plays a vital role in the progression of HCC. This study aimed to identify the macrophage-related receptor ligand marker genes associated with HCC and further explored the molecular immune mechanisms attributed to altered biomarkers. Single-cell RNA sequencing data containing primary and recurrent samples were downloaded from the China National GeneBank. Cell types were first identified to explore differences between immune cells from different sample sources. CellChat analysis was used to infer and analyze intercellular communication networks quantitatively. Three molecular subtypes were constructed based on the screened twenty macrophage-associated receptor ligand genes. Bulk RNA-Seq data were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. After the screening, the minor absolute shrinkage and selection operator (LASSO) regression model was employed to identify key markers. After collecting peripheral blood and clinical information from patients, an enzyme-linked immunosorbent assay (ELISA) was used to detect the correlation between key markers and IL-10, one of the macrophage markers. After developing a new HCC risk adjustment model and conducting analysis, it was found that there were significant differences in immune status and gene mutations between the high-risk and low-risk groups of patients based on macrophage-associated receptor and ligand genes. This study identified SPP1, ANGPT2, and NCL as key biological targets for HCC. The drug-gene interaction network analysis identified wortmannin, ribavirin, and tarnafloxin as potential therapeutic drugs for the three key markers. In a clinical cohort study, patients with immune checkpoint inhibitor (ICI) resistance had significantly higher expression levels of OPN, ANGPT2, NCL, and IL-10 than patients with ICI-responsiveness. These three key markers were positively correlated with the expression level of IL-10. The signature based on macrophage-associated receptor and ligand genes can accurately predict the prognosis of patients with HCC and the sensitivity to immunotherapy. These results may help guide the development of targeted prevention and personalized treatment of HCC.
Functional fixedness in chimpanzees
Authors: Ebel Sonja J. , Völter Christoph J. , Sánchez-Amaro Alejandro , Helming Katharina A. , Herrmann Esther , Call Josep 
Published: May 2024

AbstractDifferences in the tool use of non-human primates and humans are subject of ongoing debate. In humans, representations of object functions underpin efficient tool use. Yet, representations of object functions can lead to functional fixedness, which describes the fixation on a familiar tool function leading to less efficient problem solving when the problem requires using the tool for a new function. In the current study, we examined whether chimpanzees exhibit functional fixedness. After solving a problem with a tool, chimpanzees were less efficient in solving another problem which required using the same tool with a different function compared to a control group. This fixation effect was still apparent after a period of nine months and when chimpanzees had learned about the function of a tool by observation of a conspecific. These results suggest that functional fixedness in our closest living relatives likely exists and cast doubt on the notion that stable function representations are uniquely human.