bluuebunny/crossref_metadata_2025_split huggingface dataset:
Island biocultural diversity in the Mediterranean: the case study of Sardinia
Authors: Nazari Vazrick , Pungetti Gloria , Hong Sun-Kee , Belardinelli Sofia , Bisol Giovanni Destro , Pievani Dietelmo 
Published: September 2024

AbstractThe Mediterranean Basin is a hotspot for biological and cultural diversity, and this is particularly evident in its islands, even though little attention has been paid to their remarkable biocultural diversity. In order to elucidate this characteristic phenomenon, we present a review of the literature on biodiversity and cultural studies in Sardinia. From the review, it has emerged that the island can serve as an excellent case study and a model for the development of a methodology on the topic, which can be applied to the entire Mediterranean Basin. An Island Biocultural Diversity Initiative for the Mediterranean Region has therefore been set up to support the preservation of biocultural diversity and Traditional Ecological Knowledge (TEK) in Mediterranean islands, with Sardinia as its primary hotspot.
How preferences enslave attention: calling into question the endogenous/exogenous dichotomy from an active inference perspective
Authors: Parvizi-Wayne Darius 
Published: September 2024

AbstractIt is easy to think of attention as a purely sensorimotor, exogenous mechanism divorced from the influence of an agent’s preferences and needs. However, according to the active inference framework, such a strict reduction cannot be straightforwardly invoked, since all cognitive and behavioural processes can at least be described as maximising the evidence for a generative model entailed by the ongoing existence of that agent; that is, the minimisation of variational free energy. As such, active inference models could cast an (embodied) cognitive mechanism like attention, described in this paper as a relevance filter, as constrained (or enslaved) by these prior preferences for which an agent must seek evidence, whether or not such priors are having direct, real-time neurocognitive effects on the sensorimotor loops that couple the attending agent and her surrounding environment. This duality with respect to the role of priors corresponds to a wider, ongoing debate in the active inference community regarding the framework’s explanatory power. More specifically, the debate centres on whether the notion of a generative model and the priors embedded ubiqitously therein act as a purely useful instrumental tool for scientists aiming to model the behaviours of self-organising entities, or, rather, the brain (and body) is genuinely constituted by a predictive hierarchy within which higher-order dynamics constrain and contextualise activity unfolding at lower levels. With a focus on the second (ontologically realist) construal of active inference presented here, this paper argues that in cognitive systems endowed with attentional schema, higher-order preferences do, indeed, impose a demonstrable and powerful modulating effect on the way attention unfolds. Furthermore, these preferences in question transcend the contingent, task-relevant goals that have already been shown to bias attention. Rather, attention is powerfully tuned by the most-deep rooted priors the agent possesses, such that, when sensory evidence against these priors is observed and free energy spikes, the agent attentionally prioritises the homeostatic restoration of these preferred states over their shorter-term desires. This suggests that, at its core, attention is a goal-driven process, which calls into question the putative dichotomy that exists between endogenous (goal-directed) attention and exogenous (stimulus-driven) attention. What emerges in its place is a symbiotic relationship between attention and preferences, whereby the fulfilment of the latter rests on successful application of the former, and the former derives its function from the organismic need to find evidence for the latter.
Approximate Controllability of Fractional Evolution System on Non-Dense Domain
Authors: Singh Vikram , Chaudhary Renu , Kumar Umesh , Kumar Sandeep 
Published: September 2024

Abstract
This article explores the existence and approximate controllability of integral solutions for Hilfer fractional evolution equations in a non-dense domain. Leveraging the well-known generalized Banach contraction theorem, we establish both the existence and uniqueness of the integral solution. Furthermore, we adopt a sequential approach to derive results related to approximate controllability, without relying on the compactness of semigroups or the uniform boundedness of nonlinear functions. To validate our findings, we present and discuss an illustrative example.
Exploring the Facilitating Environment for Mindfulness Meditation: Establishing a Framework through Analysis of Means and Exploratory Factor Analysis
Authors: Chen Anran , Tang Yue 
Published: September 2024

Abstract
Objective
While mindfulness meditation is an established practice for improving well-being, the physical environment for this activity awaits further exploration. This research aimed to explore how the physical environment facilitates mindfulness meditation and to establish a framework through Analysis of Means (ANOM) and Exploratory Factor Analysis (EFA). The framework was intended to provide guidance for organisations and individuals to better design or modify physical space to support their mindfulness meditations.

Method
This study used methods to establish an initial research framework from the literature on mindfulness, architectural design, and environmental psychology. A survey of UK mindfulness practitioners was conducted in 2021–2022 to provide insights from a quantitative perspective. The data were analysed using ANOM and EFA to obtain a comprehensive framework based on the responses.

Results
Through a review of the literature and empirical study, nine physical factors with controllable elements were identified, ranked by their relative importance. Quietness, the use of supportive tools, and natural sounds were found to be the most important.

Conclusion
This research suggests the priority elements for groups and individuals to consider when adapting the physical environment for mindfulness meditation. The results revealed quietness as the most beneficial controllable element for its facilitation. Additionally, the use of supportive meditation tools was also important. Considering these top elements first could support practitioners' mindfulness meditation more effectively and efficiently.

Preregistration
This study was not preregistered.
A review of deep learning-based reconstruction methods for accelerated MRI using spatiotemporal and multi-contrast redundancies
Authors: Kim Seonghyuk , Park HyunWook , Park Sung-Hong 
Published: September 2024

AbstractAccelerated magnetic resonance imaging (MRI) has played an essential role in reducing data acquisition time for MRI. Acceleration can be achieved by acquiring fewer data points in k-space, which results in various artifacts in the image domain. Conventional reconstruction methods have resolved the artifacts by utilizing multi-coil information, but with limited robustness. Recently, numerous deep learning-based reconstruction methods have been developed, enabling outstanding reconstruction performances with higher acceleration. Advances in hardware and developments of specialized network architectures have produced such achievements. Besides, MRI signals contain various redundant information including multi-coil redundancy, multi-contrast redundancy, and spatiotemporal redundancy. Utilization of the redundant information combined with deep learning approaches allow not only higher acceleration, but also well-preserved details in the reconstructed images. Consequently, this review paper introduces the basic concepts of deep learning and conventional accelerated MRI reconstruction methods, followed by review of recent deep learning-based reconstruction methods that exploit various redundancies. Lastly, the paper concludes by discussing the challenges, limitations, and potential directions of future developments.
Nonlinear damping effects for the 2D Mindlin–Timoshenko system
Authors: Bchatnia Ahmed , Chebbi Sabrine , Hamouda Makram 
Published: September 2024

AbstractIn this article, we investigate the asymptotic behavior of the Mindlin–Timoshenko system under the influence of nonlinear dissipation affecting the rotation angle equations. Initially, we provide a concise review of the system’s solution existence. Subsequently, we demonstrate that the energy associated with the solution of the Mindlin–Timoshenko setup follows a dissipation. Furthermore, under the condition of equal wave speeds, we establish a comprehensive decay theorem for the energy, offering explicit insights into its general behavior.
Determination of the load acting on the probe by separating force and torque during FSW of AA 6060 T66
Authors: Sennewald Martin , Wüstefeld Ramon , Hasieber Michael , Löhn Torsten , Bergmann Jean Pierre 
Published: September 2024

AbstractThe development of suitable welding processes is required to meet the ever-increasing demands on joining processes, particularly for lightweight construction and increasing environmental awareness. Friction stir welding (FSW) represents a promising alternative to conventional fusion welding processes, particularly for the joining of low-melting-point materials such as aluminium and magnesium alloys, which present a number of challenges, including the formation of pores and the occurrence of hot cracks. The central element of the process is the friction stir welding tool, which consists of a shoulder and a probe. The rotation and the simultaneous application of pressure during the joining process create a friction-based heat input through the tool. The excellent mechanical properties resulting from dynamic recrystallisation during the welding process are a major advantage of the process. As a result, strengths comparable to those of the base material can be achieved. However, FSW is subject to process-specific challenges, including high process forces, which result in the fabrication of complex and robust devices. Additionally, high dynamic loads on the friction stir welding tools must be considered. In many cases, the design of friction stir welding tools is based on empirical data. However, these empirical values are machine-, component- and material-specific, which often results in under- or overmatching of friction stir welding tools. Sudden probe failure, component scrap, and low process reliability are the direct consequences of undermatching. Overmatching results in enlarged tools with limited accessibility, high heat input, and high process forces, leading to component deformation. The aim of this study is to determine the load on the probe by separating the forces and torque of the shoulder and the probe in order to be able to make statements about the load acting on the probe and the resulting stress state. The knowledge of the stress state can be employed to design friction stir welding tools, both statically and dynamically, for a specific welding task. A strategy was devised to distribute the load exerted on the shoulder and probe. To this end, the length of the probe was gradually reduced between the welding tests. The investigations were carried out with a force-controlled robotized welding setup in which AA 6060 T66 sheets with a thickness of 5 mm were welded. A Kistler multicomponent dynamometer type 9139AA allows to measure the Cartesian forces to be recorded in the x-, y-, and z-directions with a sampling rate of 80 kHz. The weld seam properties were determined by visual and metallographic inspections as well as tensile and bending tests in accordance with DIN EN ISO 25239–5.
Excellent lubricating hydrogels with rapid photothermal sterilization for medical catheters coating
Authors: Sun Yue , Shang Zhenling , Li Chenghao , Guo Jinglun , Chen Zhuo , Zhao Nan , Liu Guoqiang , Zhou Feng , Liu Weimin 
Published: September 2024

AbstractBacterial infection and tissue damage caused by friction are two major threats to patients’ health in medical catheter implantation. Hydrogels with antibacterial and lubrication effects are competitive candidates for catheter coating materials. Photothermal therapy (PTT) is a highly efficient bactericidal method. Here, a composite hydrogel containing MXene nanosheets and hydrophilic 3-sulfopropyl methacrylate potassium salt (SPMK) is reported, which is synthesized through the one-pot method and heat-initiated polymerization. The hydrogel shows excellent antibacterial performance against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) in 3 min in the air or 20 min in the water environment under near-infrared light (NIR; 808 nm) irradiation. The friction coefficient of the hydrogel is about 0.11, which is 48% lower than that without SPMK. The rapid photothermal sterilization is attributed to the outstanding antibacterial ability and thermal effect of photoactivated MXene. The ultra-low friction is the result of the hydration lubrication mechanism. This study provides a potential strategy for the surface coatings of biomedical catheters, which enables rapid sterilization and extremely low interface resistance between catheters and biological tissues.
A robust low-friction triple network hydrogel based on multiple synergistic enhancement mechanisms
Authors: Zhang Xinyue , Chen Qin , Chen Kai , Feng Cunao , Feng Haiyan , Li Xiaowei , Zhang Dekun 
Published: September 2024

AbstractHydrogels exhibit promising applications, particularly due to their high water content and excellent biocompatibility. Despite notable progress in hydrogel technology, the concurrent enhancement of water content, mechanical strength, and low friction poses substantial challenges to practical utilization. In this study, employing molecular and network design guided based on multiple synergistic enhancement mechanisms, we have developed a robust polyvinyl alcohol (PVA)–polyacrylic acid (PAA)–polyacrylamide (PAAm) three-network (TN) hydrogel exhibiting high water content, enhanced strength, low friction, and fatigue resistance. The hydrogel manifests a water content of 63.7%, compression strength of 6.3 MPa, compression modulus of 2.68 MPa, tensile strength reaching 7.3 MPa, and a tensile modulus of 10.27 MPa. Remarkably, even after one million cycles of dynamic loading, the hydrogel exhibits no signs of fatigue failure, with a minimal strain difference of only 1.15%. Furthermore, it boasts a low sliding coefficient of friction (COF) of 0.043 and excellent biocompatibility. This advancement extends the applications of hydrogels in emerging fields within biomedicine and soft bio-devices, including load-bearing artificial tissues, artificial blood vessels, tissue scaffolds, robust hydrogel coatings for medical devices, and joint parts of soft robots.
An Extended Learning Analytics Framework Integrating Machine Learning and Pedagogical Approaches for Student Performance Prediction and Intervention
Authors: Alalawi Khalid , Athauda Rukshan , Chiong Raymond 
Published: September 2024

AbstractThe use of educational data mining and machine learning to analyse large data sets collected by educational institutions has the potential to discover valuable insights for decision-making. One such area that has gained attention is to predict student performance by analysing large educational data sets. In the relevant literature, many studies have focused on developing prediction models on student performance but comparatively less work exists on actions taken based on predicted at-risk students and evaluating their impact. Learning Analytics Intervention (LAI) studies have emerged as an approach that aims to address this gap. In LAI studies, student risk levels are predicted and disseminated to relevant stakeholders (academics, administrators and students) using learning analytics (LA) tools for targeted interventions. The interventions themselves are mainly left under the discretion of the academics and/or administrators, who are aware of the learning context and have the authority to make decisions, with LA tools facilitating this process. LAI studies have shown success in improving outcomes (e.g. improve pass rates, retention, grades), but their uptake has been slow. The main impediment to piloting LAIs by academics has been the lack of access to LAI infrastructure, which requires institutional investments to develop predictive models collecting data from diverse IT systems. Another challenge in LAIs is the development of effective interventions. This paper presents an extended LAI framework, termed Student Performance Prediction and Action (SPPA), which provides access to LAI infrastructure for academics to pilot LAIs in their courses without the need for institution-wide efforts. SPPA and its features are seamlessly accessed via a web browser and academics can develop course-specific predictive models based on historical course assessment data. Furthermore, SPPA integrates sound pedagogical approaches and provides relevant information (such as students’ knowledge gaps, personalised study plans) to assist academics in providing effective interventions. SPPA was evaluated by a number of academics piloting LAIs in their courses. Quantitative and qualitative data was collected and analysed. Academics were able to provide effective interventions using SPPA and also had a positive outlook on using SPPA and its features. SPPA is also provided as an open-source project for further development and can be a catalyst for widescale uptake in LAIs. Furthermore, a model for continuous improvement in LAIs is outlined along with a number of areas for future research and development.
Serum microRNA-146a-5p and microRNA-221-3p as potential clinical biomarkers for papillary thyroid carcinoma
Authors: Verrienti Antonella , Pecce Valeria , Grani Giorgio , Del Gatto Valeria , Barp Samuele , Maranghi Marianna , Giacomelli Laura , Di Gioia Cira , Biffoni Marco , Filetti Sebastiano , Durante Cosimo , Sponziello Marialuisa 
Published: September 2024

Abstract
Purpose
Papillary thyroid carcinoma (PTC) is the most common malignant thyroid neoplasm, accounting for approximately 85% of all follicular cell-derived thyroid nodules. This study aimed to assess the diagnostic potential of circulating microRNA-146a-5p and microRNA-221-3p as biomarkers for PTC and their usefulness in monitoring disease progression during patient follow-up.

Methods
An observational study was conducted on two cohorts of PTC patients and healthy controls (HCs) using digital PCR. We collected patients’ clinical, biochemical, and imaging data during the post-surgery surveillance. We analyzed the levels of circulating miRNAs in serum samples of patients before surgery and during the follow-up, including those with indeterminate/biochemical incomplete response (IndR/BIR) and residual thyroid tissues (Thy Residue).

Results
Both miR-146a-5p and miR-221-3p were confirmed as effective biomarkers for PTC diagnosis. They enabled differentiation between pre-surgery PTC patients and HCs with an area under the curve (AUC) of 92% and 87.3%, respectively, using a threshold level of 768,545 copies/uL for miR-146a-5p and 389,331 copies/uL for miR-221-3p. It was found that miRNA fold change levels, rather than absolute levels, can be useful during patient follow-up. In particular, we found that a fold change of 2 for miR-146a-5p and 2.2 for miR-221-3p can identify a progressive disease, regardless of the presence of TgAbs or remnant thyroid.

Conclusion
MiRNA-146a-5p and miRNA-221-3p, particularly the former, could be valuable diagnostic biomarkers for PTCs. They also seem to be effective in monitoring disease progression during patient follow-up by evaluating their fold change, even when thyroglobulin is uninformative.
IPSE: An Individualized Digital Environment for Strategic Planning at the University Level
Authors: Albano Giovannina , Telloni Agnese Ilaria 
Published: September 2024

AbstractThis study focuses on the design and the implementation of a digital environment aimed at fostering strategic planning competence in problem-solving through individualization features: the Individualized Planned Strategy Environment (IPSE). Within IPSE, students are engaged in a sequence of oriented activities, guiding them in constructing and following a theoretically justified plan for solving a mathematical problem, thus promoting a gradual integration between conceptual and procedural knowledge. IPSE envisages also meta-level activities, aimed at fostering the handling of multiple representations toward a unifying and structural view of the subject at stake. We discuss the results of a case study conducted with engineering freshmen at the University of Salerno, involved in problem-solving activities devoted to peer assessment. This led us to identify certain student profiles both theory- and data-driven, according to the students’ progress in using the components of Habermas’ rationality when solving a problem. We highlighted that some students show a full realization of the dynamic nature of Habermas’ model of rationality, where knowing, acting and communicating interact and intertwine.
Ecological environment quality assessment of coal mining cities based on GEE platform: A case study of Shuozhou, China
Authors: Duo Linghua , Wang Junqi , Zhong Yongping , Jiang Chengqing , Chen Yaoyao , Guo Xiaofei 
Published: September 2024

AbstractShuozhou is a typical coal mining city, and the Pingshuo Antaibao open-pit coal mine in its area is one of the largest open-pit coal mines in China. The mining of coal resources is an important part of ensuring national energy security, and at the same time, it inevitably has a certain impact on the ecology, such as coal dust generated by open-pit mining will affect air quality, soil, water and vegetation. It is of great significance to explore the temporal and spatial variation of ecological environment quality in coal mining cities for ecological protection and sustainable social and economic development. Based on the Google Earth Engine (GEE) platform, this paper combines the index-based coal dust index (ICDI) and Remote Sensing Ecological Index (RSEI) models to construct an improved RSEI (IRSEI) that can reflect coal mining cities. This paper explores the spatial–temporal evolution characteristics and spatial correlation of ecological environment quality in Shuozhou from 2000 to 2020. The results showed that the average value of IRSEI in Shuozhou was between 0.262 and 0.418, and the overall change showed an upward trend. The growth areas of ecological environment quality are mainly located in the eastern and southwestern areas with good vegetation growth, and these regions have vigorously implemented the Northern Shelter Forest Project, afforestation and greening projects, implemented the forest resource management and protection responsibility system, promoted the construction of ecological civilization, and significantly improved the ecological environment. While the declining areas are mainly located in the central and southern regions where mining activities and human activities are more intensive. The IRSEI in the study area showed a significant spatial positive correlation, and the agglomeration types of the spatial pattern were mainly high-high and low-low agglomeration types, with the high-high agglomeration types mainly distributed in the eastern and southwestern regions, and the low-low agglomeration types distributed in the northern and south-central regions of the study area. The trend of low and low agglomeration has decreased, which further proves that the ecological restoration measures taken by the government, such as returning farmland to forests, integrating protection and restoration of mountains, waters, forests, fields, lakes, grasslands, and sands, controlling soil erosion, and stage wise reclamation of coal mining subsidence areas, have improved the ecological environment quality of Shuozhou. This study provides a reference for understanding the spatiotemporal changes of the ecological environment of coal mining cities, and is conducive to formulating appropriate ecological protection strategies.