bluuebunny/crossref_metadata_2025_split huggingface dataset:
Approximate bregman proximal gradient algorithm for relatively smooth nonconvex optimization
Authors: Takahashi Shota , Takeda Akiko 
Published: November 2024

Abstract
In this paper, we propose the approximate Bregman proximal gradient algorithm (ABPG) for solving composite nonconvex optimization problems. ABPG employs a new distance that approximates the Bregman distance, making the subproblem of ABPG simpler to solve compared to existing Bregman-type algorithms. The subproblem of ABPG is often expressed in a closed form. Similarly to existing Bregman-type algorithms, ABPG does not require the global Lipschitz continuity for the gradient of the smooth part. Instead, assuming the smooth adaptable property, we establish the global subsequential convergence under standard assumptions. Additionally, assuming that the Kurdyka–Łojasiewicz property holds, we prove the global convergence for a special case. Our numerical experiments on the

$$\ell _p$$

ℓ
p

regularized least squares problem, the

$$\ell _p$$

ℓ
p

loss problem, and the nonnegative linear system show that ABPG outperforms existing algorithms especially when the gradient of the smooth part is not globally Lipschitz or even locally Lipschitz continuous.
Fast convergence of the primal-dual dynamical system and corresponding algorithms for a nonsmooth bilinearly coupled saddle point problem
Authors: Ding Ke-wei , Fliege Jörg , Vuong Phan Tu 
Published: November 2024

Abstract
This paper studies the convergence rate of a second-order dynamical system associated with a nonsmooth bilinearly coupled convex-concave saddle point problem, as well as the convergence rate of its corresponding discretizations. We derive the convergence rate of the primal-dual gap for the second-order dynamical system with asymptotically vanishing damping term. Based on an implicit discretization scheme, we propose a primal-dual algorithm and provide a non-ergodic convergence rate under a general setting for the inertial parameters when one objective function is continuously differentiable and convex and the other is a proper, convex and lower semicontinuous function. For this algorithm we derive a

$$O\left( 1/k^2 \right) $$

O

1
/

k
2

convergence rate under three classical rules proposed by Nesterov, Chambolle-Dossal and Attouch-Cabot without assuming strong convexity, which is compatible with the results of the continuous-time dynamic system. For the case when both objective functions are continuously differentiable and convex, we further present a primal-dual algorithm based on an explicit discretization. We provide a corresponding non-ergodic convergence rate for this algorithm and show that the sequence of iterates generated weakly converges to a primal-dual optimal solution. Finally, we present numerical experiments that indicate the superior numerical performance of both algorithms.
More than just fun: Investigating students’ perceptions towards the potential of leveraging esports for promoting the acquisition of 21st century skills
Authors: Zhong Yuchun , Guo Kai , Fryer Luke Kutszik , Chu Samuel Kai Wah , Deng Hao 
Published: November 2024

Abstract
Esports (electronic sports) or competitive video gaming has taken its place as a leading form of entertainment for young people worldwide. However, esports were generally studied as a popular form of entertainment, and rarely have studies examined esports from an educational perspective. This study aimed to investigate the perceived impact of various types of esports on the acquisition of the 4Cs skills (critical thinking, creativity, collaboration, and communication) through the lenses of higher education students. A sequential mixed methods research design was adopted, with a questionnaire survey involving 628 participants followed by semi-structured interviews with 46 participants. The quantitative findings showed that the players generally perceived that esports can cultivate the 4Cs skills and their perception was significantly related to gaming experience, gaming frequency, and time spent on each gameplay. The higher level of engagement in games was associated with higher 4Cs skills. No significant difference was found in scores of the 4Cs skills across nine esports genres. Apart from statistical inferences, natural language process (NLP) techniques combined with thematic analysis were used to identify various mechanisms and elements of different games associated with the 4Cs skills development. The quantitative and qualitative findings collectively shed light on the potential of integrating esports elements into innovative pedagogies for promoting learning and developing the 4Cs skills for both life and career.
Editorial on special issues: “regional nutrient management in the circular economy” & “nitrogen and carbon recycling: benefits from the stakeholders’ perspective”
Authors: Wichern Florian , García-González María Cruz , Moral Raúl , Papangelou Anastasia , Spiller Marc 
Published: November 2024

AbstractThe intensification and specialization of global agriculture has led to a nutrient surplus resulting in regional environmental issues such as eutrophication and loss of biodiversity due to nutrient accumulation. Addressing these challenges requires a shift towards regional nutrient circularity, inspired by the principles of a circular economy, to create a more resource-efficient agricultural system. Circular agriculture, particularly in Europe, provides a model for sustainable nutrient management at various scales—local, regional, national and international. Existing technologies enable the production of fertilizers from secondary or waste streams and can improve nutrient use efficiency. The development of a market with transparency of supply and demand dynamics, standardized products, and reliable traceability is essential for the effective implementation of nutrient circularity. However, practical nutrient management takes place on a local level, with significant variability in environmental, economic, and social conditions at the farm and field levels due to differences in nutrient demand by crops or farm management, e.g. organic farming with often lower total nutrient intensity. Therefore, the successful development of a regional circular nutrient economy necessitates a stronger stakeholder perspective, emphasizing the importance of participatory research approaches. In addition to circularity, the efficiency of nutrient use from secondary fertilizers must be enhanced, and the broader food system must evolve towards more nutrient-efficient practices. This transformation will likely require adopting a planetary health diet that promotes both sufficiency and sustainability in nutrient use. Therefore, policy measures need to provide a clear regulatory framework at supranational (e.g. European Union) or national level, targeting environmental and societal goals, while at the same time supporting locally adaptable interventions through economic incentives and innovation support.
A brief review on Ce and Zr-based phase-separated metallic glasses
Authors: Singh Devinder , Singh Dharmendra , Tiwari Radhey Shyam , Ramasamy Parthiban , Eckert Jürgen 
Published: November 2024

AbstractPhase-separated metallic glasses (MGs) have attracted a lot of interest recently because they offer a unique opportunity to design composites or alloys with hierarchical microstructure at various length scales. Phase-separated MGs differ from other MGs in terms of their structure and physical properties. Though a lot of theoretical work has been done, there is still a lack of understanding regarding the mechanism underlying phase separation in MGs. In general, phase separation in many MG systems is explained on the basis of nucleation and growth or spinodal decomposition mechanisms. On the other hand, the phase separation in Ce-based MGs is examined based on changes in the electronic structure of Ce atoms. This opens up a new direction of research for delineating issues pertaining to phase separation in amorphous systems. The present brief review aims to provide a comprehensive overview of the phase separation phenomenon in Ce- and Zr-based MG systems. It is broadly divided into two sections: the first section gives a brief introduction into the phase separation in MG systems, mechanisms of phase separation, micro-structural and thermal characteristics, and advantages of phase separation. The second section discusses some of the recent work on Ce- and Zr-based phase-separated MGs with respect to their design and properties.
Graphical Abstract
Experience with Mandatory Reporting of Intimate Partner Violence: An Explorative Qualitative Study of Service Providers and Help-Seeking IPV Victims and IPV Perpetrators
Authors: Kristiansen Susanne Tilke Thon , Leer-Salvesen Kjartan , Dahl Silje Louise , Linge Anita Dyb , Vatnar Solveig Karin Bø 
Published: November 2024

Abstract
Purpose
This study explored service providers’ and help-seeking intimate partner violence (IPV) victims’ and IPV perpetrators’ experiences with mandatory reporting of intimate partner violence (MR-IPV) in Norway. We examined the following research questions: How do service providers experience work within the context of MR-IPV? How do help-seeking IPV victims and IPV perpetrators experience MR-IPV?

Methods
This qualitative study used reflexive thematic analysis to identify, analyze and report themes and patterns uncovered in semi-structured interviews with 42 service providers and 6 help-seeking IPV victims and IPV perpetrators, following Braun and Clark’s Qualitative Research in Psychology six phases of reflexive thematic analysis.

Results
The service providers in this study aimed to establish collaboration with help-seeking IPV victims and IPV perpetrators to avert IPV rather than immediately reporting IPV to the police, thus working within the discretionary space allowed in the Norwegian legislation. Stories concerning breaches of trust related to MR-IPV were prominent in the interviews with both groups of help-seekers. The IPV perpetrators expressed having experienced a breach of trust when the IPV was reported to the police, while most of the IPV victims expressed a breach of trust due to a lack of MR-IPV.

Conclusions
IPV victims expressed ambivalence linked to a desire for interventions and a fear of not receiving adequate help. These findings highlight the challenges of certain requirements placed on service providers when working within the MR-IPV context; distinguishing between situations in which collaboration is appropriate and situations in which immediate reporting to the police is required.
Solution existence for a class of nonsmooth robust optimization problems
Authors: Hung Nguyen Canh , Chuong Thai Doan , Le Hoang Anh Nguyen 
Published: November 2024

AbstractThe main purpose of this paper is to investigate the existence of global optimal solutions for nonsmooth and nonconvex robust optimization problems. To do this, we first introduce a concept called extended tangency variety and show how a robust optimization problem can be transformed into a minimizing problem of the corresponding tangency variety. We utilize this concept together with a constraint qualification condition and the boundedness of the objective function to provide relationships among the concepts of robust properness, robust M-tamesness and robust Palais-Smale condition related to the considered problem. The obtained results are also employed to derive necessary and sufficient conditions for the existence of global optimal solutions to the underlying robust optimization problem.
A High-Order Eulerian–Lagrangian Runge–Kutta Finite Volume (EL–RK–FV) Method for Scalar Nonlinear Conservation Laws
Authors: Chen Jiajie , Nakao Joseph , Qiu Jing-Mei , Yang Yang 
Published: November 2024

Abstract
We present a class of high-order Eulerian–Lagrangian Runge–Kutta finite volume methods that can numerically solve Burgers’ equation with shock formations, which could be extended to general scalar conservation laws. Eulerian–Lagrangian (EL) and semi-Lagrangian (SL) methods have recently seen increased development and have become a staple for allowing large time-stepping sizes. Yet, maintaining relatively large time-stepping sizes post shock formation remains quite challenging. Our proposed scheme integrates the partial differential equation on a space-time region partitioned by linear approximations to the characteristics determined by the Rankine–Hugoniot jump condition. We trace the characteristics forward in time and present a merging procedure for the mesh cells to handle intersecting characteristics due to shocks. Following this partitioning, we write the equation in a time-differential form and evolve with Runge–Kutta methods in a method-of-lines fashion. High-resolution methods such as ENO and WENO-AO schemes are used for spatial reconstruction. Extension to higher dimensions is done via dimensional splitting. Numerical experiments demonstrate our scheme’s high-order accuracy and ability to sharply capture post-shock solutions with large time-stepping sizes.
Parametric Machine Learning-Based Adaptive Sampling Algorithm for Efficient IoT Data Collection in Environmental Monitoring
Authors: Algabroun Hatem , Håkansson Lars 
Published: November 2024

Abstract
With the IoT trend, wireless sensors are gaining growing interest. This is due to the possibility of installing them in locations inaccessible to wired sensors. Although great success has already been achieved in this area, energy limitation remains a major obstacle for further advances. As such, it is important to optimize sampling to a sufficient rate to catch important information without excessive energy consumption. One way to achieve sufficient sampling is by using an algorithm for adaptive sampling named dynamic sampling rate algorithm (DSRA); however, this algorithm requires an expert to set and tune its parameters, which might not always be readily available. This study aims to further develop this algorithm to be machine learning based to tune these parameters. To achieve this goal, the algorithm was modified and an optimization strategy that considers a predetermined error threshold was developed. Then the algorithm was implemented using simulated and real data with a set of predetermined errors thresholds to observe its performance. The results showed that the developed algorithm exhibited adaptive sampling behavior, and it could collect data efficiently depending on the predetermined error threshold. Based on the results, it is possible to conclude that the developed algorithm endows sensors with adaptive sampling capabilities based on the signal rate of change.
Are They Ready to Teach? Generative AI as a Means to Uncover Pre-Service Science Teachers’ PCK and Enhance Their Preparation Program
Authors: Blonder Ron , Feldman-Maggor Yael , Rap Shelley 
Published: November 2024

AbstractIntegrating generative artificial intelligence (GenAI) in pre-service teachers’ education programs offers a transformative opportunity to enhance the pedagogical development of future science educators. This conceptual paper suggests applying the GenAI tool to evaluate pedagogical content knowledge (PCK) among pre-service science teachers. By holding interactive dialogues with GenAI, pre-service teachers engage in lesson planning in a way that reveals their understanding of content, pedagogy, and PCK while facilitating the practical application of theoretical knowledge. Interpretation of these interactions provides insights into teachers-to-be knowledge and skills, enabling personalized learning experiences and targeted program adjustments. The paper underscores the need to equip pre-service teachers with the necessary competencies to utilize GenAI effectively in their future teaching practices. It contributes to the ongoing discourse on technology’s role in teacher preparation programs, highlighting the potential of addressing existing challenges in evaluating and developing teacher knowledge via GenAI. The suggested future research directions aim to further investigate the GenAI usage implications in educational contexts.
Lateritic Ni–Co Prospectivity Modeling in Eastern Australia Using an Enhanced Generative Adversarial Network and Positive-Unlabeled Bagging
Authors: Wake Nathan , Farahbakhsh Ehsan , Müller R. Dietmar 
Published: November 2024

AbstractThe surging demand for Ni and Co, driven by the acceleration of clean energy transitions, has sparked interest in the Lachlan Orogen of New South Wales for its potential lateritic Ni–Co resources. Despite recent discoveries, a substantial knowledge gap exists in understanding the full scope of these critical metals in this geological province. This study employed a machine learning-based framework, integrating multidimensional datasets to create prospectivity maps for lateritic Ni–Co deposits within a specific Lachlan Orogen segment. The framework generated a variety of data-driven models incorporating geological (rock units, metamorphic facies), structural, and geophysical (magnetics, gravity, radiometrics, and remote sensing spectroscopy) data layers. These models ranged from comprehensive models that use all available data layers to fine-tuned models restricted to high-ranking features. Additionally, two hybrid (knowledge-data-driven) models distinguished between hypogene and supergene components of the lateritic Ni–Co mineral systems. The study implemented data augmentation methods and tackled imbalances in training samples using the SMOTE–GAN method, addressing common machine learning challenges with sparse training data. The study overcame difficulties in defining negative training samples by translating geological and geophysical data into training proxy layers and employing a positive and unlabeled bagging technique. The prospectivity maps revealed a robust spatial correlation between high probabilities and known mineral occurrences, projecting extensions from these sites and identifying potential greenfield areas for future exploration in the Lachlan Orogen. The high-accuracy models developed in this study utilizing the Random Forest classifier enhanced the understanding of mineralization processes and exploration potential in this promising region.
Withhold by default: a difference between epistemic and practical rationality
Authors: Tucker Chris 
Published: November 2024

AbstractIn practical rationality, if two reasons for alternative actions are tied, then either action is *permissible*. In epistemic rationality, we get the Epistemic Ties Datum: if the reasons for belief and disbelief are tied, then withholding judgment is *required*. I argue that this difference is explained by a difference in default biases. Practical rationality is biased toward permissibility. An action is permissible unless the specific features of the situation (e.g., the costs and benefits that apply) make it prohibited. In contrast, epistemic rationality is biased toward withholding judgment. Withholding judgment is required unless the specific features of the situation (e.g., the evidence) makes belief or disbelief permissible. This difference explains the Epistemic Ties Datum. When the reasons for belief and disbelief are equally weighty, they cancel each other out. But then the only remaining reason is the default reason, or default bias, to withhold judgment. Since it is the only remaining reason, it requires us to withhold judgment.
The spontaneous provision of criminal law
Authors: Benzecry Gabriel F. , Thompson Henry A. 
Published: November 2024

AbstractFor decades, non-state actors have supplied criminal law in Brazil’s favelas. This paper offers a humanomics account of the private provision of an impure public good. Our analysis reaches three conclusions. First, criminal law can be provided without either public intervention or reliance on the price system. Informal norms may be sufficient, indicating that Adam Smith’s invisible hand logic extends beyond legal markets grounded in private property rights and governed by well-defined prices. Second, a common sense of propriety, a key aspect of the humanomics approach, may not always be context-free. One’s environment may shape the precise objects of propriety. Third, spontaneous legal orders can be robust to agent type.
COVID-19 in California Community Colleges: College Responses, College Resources, and Student Outcomes
Authors: Hart Cassandra M.D. , Xu Di , Alonso Emily , Hill Michael 
Published: November 2024

Abstract
In Spring 2020, colleges across the nation swiftly transitioned their operations—including both classes and student support services—to remote delivery on an emergency basis in response to the crisis posed by the COVID-19 pandemic. While prior research has documented that the transition was associated with decrements in student outcomes, there remains limited understanding of the organizational factors that might have mitigated these negative associations during the pandemic. Drawing on administrative data from the California Community College system, along with a novel survey conducted among distance education leaders, our study reveals that the degree of declines in course completion and course passing rates varied based on pre-COVID online education resources (such as the ratio of distance education personnel to students and the availability of pre-COVID professional development programs in online learning): Colleges with greater pre-COVID online resources experienced more modest declines in student performance. To a lesser extent, we also found that declines in student performance during the onset of the pandemic varied depending on the responses implemented in reaction to the pandemic, such as the extent of technology delivery to students. The implications of our findings extend to the realm of planning for the continuity of operations in potential future crises.
Institutional Complexity and Social Innovation: The Case of Chinese Social Enterprises
Authors: Fu Jiawei Sophia , Yan Shipeng 
Published: November 2024

AbstractSocial enterprises (SEs) have emerged throughout the world to address societal challenges through market-based activities and innovation. Research has focused on how SEs manage the tensions arising from the combination of social-welfare and market logics, neglecting the institutional complexity that arises in authoritarian regimes where the state plays a dominant role. Based on the institutional logics perspective and interview data of 42 SE leaders in China, we find that key tensions arise from the state and social-welfare logics and that state logic (re)configures the social–market relationships to be compatible. Chinese SEs employed depoliticization and localization to adapt to this unique form of institutional complexity in their social innovation efforts. This study advances research on SEs, institutional complexity, and hybrid organizing.