bluuebunny/crossref_metadata_2025_split huggingface dataset:
Libertarian independent ideologies predict lower support for and participation in COVID‐19 safety precautions among Americans
Authors: Coberly Elise , Xu Xiaowen 
Published: September 2023

AbstractIn the US, higher conservatism has consistently been linked to lower receptiveness toward COVID‐19 safety precautions. The present studies extended these findings by examining how specific dimensions of conservatism contributed to this relationship. Three studies (total N = 1123) found that conservatives with higher Libertarian Independent attitudes reported less support for and participation in COVID‐19 safety precautions. These effects remained robust after controlling for demographics, general political orientation, COVID‐19 threat perception, and personality. These findings offer nuanced insight into how those with different conservative ideologies responded to COVID‐19 safety precautions.
Singularity Structure Optimization for Hexahedral Mesh Via Dual Operations
Authors: Shen Chun , Wang Rui 
Published: September 2023

Abstract
This paper presents an improved method for optimizing the singularity structure of hexahedral meshes using various dual operations. Our approach aims at reducing element distortion by decomposing complex singular nodes into singular curves using high-quality sheet insertion at proper locations. Then, singular curves that meet the topological parallel requirements are paired to perform the semantic column operation, which eliminates the singular curves. Finally, the topological structure is further optimized by collapsing sheets, resulting in a valid hex mesh with a simpler structure. Compared to existing hexahedral mesh simplification methods, our approach can generate higher quality meshes. Experimental results demonstrate the effectiveness of the proposed method.
Toward an Online Monitoring of Structural Performance Based on Physics-Informed Hybrid Modeling Method
Authors: He Xiwang , Li Kunpeng , Wang Shuo , Lai Xiaonan , Yang Liangliang , Kan Ziyun , Song Xueguan 
Published: September 2023

Abstract
To optimize structures and monitor their health, it is essential to build an accurate dynamic analysis model. However, traditional modeling methods based solely on physical information or data-driven techniques may not suffice for many engineering applications. While physical models can accurately simulate complex equipment, they may also incur high computational time. On the other hand, data-driven models may improve computational efficiency but are subject to significant deviations due to the influence of training data. To address these challenges, the Physics-Informed Neural Network (PINN) has gained popularity for imposing physical constraints during the training process, leading to better generalization capabilities with fewer data samples. This paper proposes a physics-informed hybrid modeling (PIHM) approach that combines a reduced-order model, kernel functions, and dynamic equations to predict dynamic output with limited training data and physical information. The method integrates prior physics information into function approximation by incorporating the reduced dynamic equation into a surrogate modeling framework. The loss function considers inertial and damping effects, ensuring physical plausibility. Unlike traditional PINN applications, the proposed modeling method is more explainable, as the trained model can be expressed in function form with engineering interpretation. The approach is verified with a real-world engineering example (telehandler boom) under complex load conditions, demonstrating accuracy, efficiency, and physical plausibility. Overall, the proposed method offers promising capabilities in solving problems where high-fidelity simulation is challenging.
The Fine-Tuning Approach for Training Monitoring
Authors: Boullosa Daniel , Claudino João Gustavo , Fernandez-Fernandez Jaime , Bok Daniel , Loturco Irineu , Stults-Kolehmainen Matthew , García-López Juan , Foster Carl 
Published: September 2023

Purpose: Monitoring is a fundamental part of the training process to guarantee that the programmed training loads are executed by athletes and result in the intended adaptations and enhanced performance. A number of monitoring tools have emerged during the last century in sport. These tools capture different facets (eg, psychophysiological, physical, biomechanical) of acute training bouts and chronic adaptations while presenting specific advantages and limitations. Therefore, there is a need to identify what tools are more efficient in each sport context for better monitoring of training process. Methods and Results: We present and discuss the fine-tuning approach for training monitoring, which consists of identifying and combining the best monitoring tools with experts’ knowledge in different sport settings, designed to improve (1) the control of actual training loads and (2) understanding of athletes’ training adaptations. Instead of using single-tool approaches or merely subjective decision making, the identification of the best combination of monitoring tools to assist experts’ decisions in each specific context (ie, triangulation) is necessary to better understand the link between acute and chronic adaptations and their impact on health and performance. Future studies should elaborate on the identification of the best combination of monitoring tools for each specific sport setting. Conclusion: The fine-tuning monitoring approach requires the simultaneous use of several valid and practical tools, instead of a single tool, to improve the effectiveness of monitoring practices when added to experts’ knowledge.
Birds of Different Feathers: Coaches’ Perspectives of Cultural Diversity and Team Dynamics in Professional Sport
Authors: Eluère Manon , Martin Luc J. , Godfrey Michael , Mallett Clifford J. , Heuzé Jean-Philippe 
Published: September 2023

As the number of international transfers increases in professional sport teams, it is unclear how this diversity impacts team functioning, and also, whether coaches feel equipped to meet this new challenge. In this study, we explored professional coaches’ perceptions and experiences of cultural diversity (i.e., national and racioethnic diversity), with a specific emphasis on implications for team dynamics. Semistructured interviews were conducted with nine professional coaches from four interdependent team sports in France (i.e., basketball, football, handball, volleyball). The coaches had experience leading first or second division men’s and/or women’s teams (e.g., two highest national championships in France, Canada, or Italy) and national teams (e.g., France, Belgium, China). Based on a critical realist approach, results indicated that coaches purposefully considered cultural diversity within their teams, and discussed stereotypical differences based on nationalities pertaining to work ethic, communication, and motives for action. Coaches’ international experience and intercultural competence seemed to be key elements that influenced their willingness to consider the cultural diversity of their teams in their coaching/management strategies. Herein, we discuss the importance of purposefully considering a team’s context (e.g., sport, member composition, geographical location) and note that coach intercultural competence appears to be a concept warranting further investigation.
Exploring the Experiences of Community Sport Coaches: Stressors, Coping Strategies, and Mental Health
Authors: Hogan Kelsey , Vierimaa Matthew , Dithurbide Lori 
Published: September 2023

In recent years, athlete mental health has received increased attention from researchers; however, coaches also experience stressors that can impact their mental health. This study addressed a gap in the sport coaching literature by using a phenomenological approach to explore the experiences of community sport coaches in Canada—an understudied population that makes up a large portion of the coaching workforce. Nineteen coaches from Atlantic Canada discussed stressors, coping strategies, and mental health in one-on-one semistructured interviews. Interviews were transcribed verbatim and analyzed using reflexive thematic analysis. Results are presented in three higher order themes: mental health culture in sport, influences on coach mental health, and coping strategies and supports. Our findings suggest that community coaches experience a variety of stressors (e.g., interpersonal, personal, organizational) similar to elite coaches, but that the origin of stressors may be different in the community sport context. The impact of stressors can be mitigated by coaches’ coping strategies, access to training and resources, and aspects of the role that support their mental health (e.g., rewarding work). Finally, these results suggest that training should address gaps in mental health literacy for coaches to support their own mental health needs as well as their athletes’ needs.
Evidence for a prehistoric multifault rupture along the southern Calico fault system, Eastern California Shear Zone, USA
Authors: Vadman Michael J. , Garvue Max M. , Spotila James A. , Bemis Sean P. , Stamps D. Sarah , Owen Lewis A. , Figueiredo Paula M. 
Published: September 2023

Abstract
Geomorphic mapping and paleoseismologic data reveal evidence for a late Holocene multifault surface rupture along the Calico-Hidalgo fault system of the southern Eastern California Shear Zone (ECSZ). We have identified ~18 km of continuous surface rupture along the combined Calico and Hidalgo faults in the vicinity of Hidalgo Mountain in the southern Mojave Desert. Based on the freshness of geomorphic fault features and continuity of surface expression, we interpret this feature to reflect a simultaneous paleorupture of both faults. Displacement along the paleorupture is defined by 39 field measurements to be generally pure right-slip with a mean offset of 2.3 m. Scaling relationships for this offset amount imply that the original surface rupture length may have been ~82 km (corresponding to a M7.4 earthquake) and that much of the rupture trace was erased by subsequent erosion of sandy and unconsolidated valley alluvium. Eight luminescence ages from a paleoseismic trench across the paleorupture on the Hidalgo fault bracket the timing of the most recent rupture to 0.9–1.7 ka and a possible penultimate event at 5.5–6.6 ka. This timing is generally consistent with the known earthquake clusters in the southern ECSZ based on previous paleoseismic investigations. The ages of these earthquakes also overlap with the age brackets of the most recent events on the Calico fault 42 km to the north and the Mesquite Lake fault 40 km to the south from earlier work. Based on these age constraints and the expected surface rupture length, we propose that the Calico fault system experienced a major, multifault rupture that spanned the entire length of the fault system between the historical Landers and Hector Mine ruptures but preceded these events by ~1–2 k.y. Coulomb stress change modeling shows that the Calico paleorupture may have delayed the occurrence of the Landers-Hector Mine cluster by placing their respective faults in stress shadows and may have also prevented a triggered event from occurring on the Calico fault following the historic events. This work implies that closely spaced ruptures in complex shear zones may repel each other and thereby stretch out the duration of major earthquake clusters. These results also suggest that complex multifault ruptures in the ECSZ may not follow simple, repeatable patterns.
Geochemistry (TE, REE, Oxygen) of Zircon from Leucogranites of the Belokurikhinsky Massif, Gorny Altai, as Indicator of Formation Conditions
Authors: Levashova E. V. , Mamykina M. E. , Skublov S. G. , Galankina O. L. , Li Q.-L. , Li X.-H. 
Published: September 2023

Abstract
The present contribution deals with the isotopic-geochemical study (by Electron Probe Microanalysis (EPMA) and Method of Secondary Ion Mass Spectroscopy (SIMS) of zircons from Belokurikhinsky massif leucogranites, which resulted in the determination of two morphological varieties of zircons (zonal and porous). Zonal zircons exhibit low content of trace elements, a “magmatic” type of REE distribution spectra, and geochemical indices consistent with those of magmatic zircons. Anomalously high REE (up to 38 800 ppm), Y (up to 50 700 ppm) and U (up to 24 700 ppm) contents, as well as elevated Hf, P, F, Cl, and water contents (up to 3.5 wt %) were found in porous zircons. They display gently flattened REE distribution spectra with no Ce-anomaly and the persistence of negative Eu-anomaly, as well as geochemical parameters that differ from typical zircons of magmatic origin. The obtained geochemical characteristics of porous zircons reflect the process of enrichment of the magmatic melt with rare and rare earth elements, and indicate a high fluid saturation of the melt. The δ18О determined value for porous zircons is in the range of 9.22 to 12.54‰, which significantly exceeds a mantle value and seems to be caused by influence of external fluids interacting with sedimentary rocks surrounding leucogranites. The detailed isotopic-geochemical study of zircon samples suggests that their crystallization from leucogranites of a third (final) phase in the evolution of the Belokurikhinsky massif took place from fluid-saturated melt with elevated incompatible element concentrations.
Nesting-tree preferences of the black woodpecker—the biggest cavity excavator in a conifer-dominated forests in Poland
Authors: Zawadzki Grzegorz 
Published: September 2023

The black woodpecker Dryocopus martius is an ecologically disproportionately important forest species owing to its abundance. Its large cavities provide breeding sites and shelter for many species—large birds, mammals, and social insects. I evaluated the nest tree preferences of black woodpeckers in the Augustów Forest, northeast Poland. Approximately 400 black woodpecker cavities were observed. The Scots pine, Pinus sylvestris, was the most commonly selected tree species, accounting for 90%. The cavity trees were 55–225 years old. All trees younger than 90 years were broadleaved tree species. The trees used to excavate the cavities had a larger diameter at the breast height (DBH) than the average of the stand. The trees selected by black woodpeckers were significantly shorter than the average height of the stands. Over 60% of the cavities were excavated 10–16 m above ground level. I found that the DBH and the first branch height were critical factors affecting the cavity entrance height. In pine-dominated forests, black woodpeckers preferred dead trees. Approximately 44% of new cavities were excavated from dead trees. Leaving dead or dying large trees in commercial forests benefits black woodpeckers and large secondary cavity nesters that depend on it and promotes biodiversity conservation. Birds excavate new cavities at a high rate yearly, in contrast with beech-dominated forests.
ZPP: A Dynamic Technique to Eliminate Cache Pollution in NoC based MPSoCs
Authors: Deb Dipika , Jose John 
Published: September 2023

Data prefetching efficiently reduces the memory access latency in NUCA architectures as the Last Level Cache (LLC) is shared and distributed across multiple cores. But cache pollution generated by prefetcher reduces its efficiency by causing contention for shared resources such as LLC and the underlying network. The paper proposes Zero Pollution Prefetcher (ZPP) that eliminates cache pollution for NUCA architecture. For this purpose, ZPP uses L1 prefetcher and places the prefetched blocks in the data locations of LLC where modified blocks are stored. Since modified blocks in LLC are stale and request for such blocks are served from the exclusively owned private cache, their space unnecessary consumes power to maintain such stale data in the cache. The benefits of ZPP are (a) Eliminates cache pollution in L1 and LLC by storing prefetched blocks in LLC locations where stale blocks are stored. (b) Insufficient cache space is solved by placing prefetched blocks in LLC as LLCs are larger in size than L1 cache. This helps in prefetching more cache blocks, thereby increasing prefetch aggressiveness. (c) Increasing prefetch aggressiveness increases its coverage. (d) It also maintains an equivalent lookup latency to L1 cache for prefetched blocks. Experimentally it has been found that ZPP increases weighted speedup by 2.19x as compared to a system with no prefetching while prefetch coverage and prefetch accuracy increases by 50%, and 12%, respectively compared to the baseline.

1
CRIMP:

C

ompact &

R

eliable DNN Inference on

I

n-

M

emory

P

rocessing via Crossbar-Aligned Compression and Non-ideality Adaptation
Authors: Huai Shuo , Kong Hao , Luo Xiangzhong , Li Shiqing , Subramaniam Ravi , Makaya Christian , Lin Qian , Liu Weichen 
Published: September 2023

Crossbar-based In-Memory Processing (IMP) accelerators have been widely adopted to achieve high-speed and low-power computing, especially for deep neural network (DNN) models with numerous weights and high computational complexity. However, the floating-point (FP) arithmetic is not compatible with crossbar architectures. Also, redundant weights of current DNN models occupy too many crossbars, limiting the efficiency of crossbar accelerators. Meanwhile, due to the inherent non-ideal behavior of crossbar devices, like write variations, pre-trained DNN models suffer from accuracy degradation when it is deployed on a crossbar-based IMP accelerator for inference. Although some approaches are proposed to address these issues, they often fail to consider the interaction among these issues, and introduce significant hardware overhead for solving each issue. To deploy complex models on IMP accelerators, we should compact the model and mitigate the influence of device non-ideal behaviors without introducing significant overhead from each technique.
In this paper, we first propose to reuse bit-shift units in crossbars for approximately multiplying scaling factors in our quantization scheme to avoid using FP processors. Second, we propose to apply kernel-group pruning and crossbar pruning to eliminate the hardware units for data aligning. We also design a zerorize-recover training process for our pruning method to achieve higher accuracy. Third, we adopt the runtime-aware non-ideality adaptation with a self-compensation scheme to relieve the impact of non-ideality by exploiting the feature of crossbars. Finally, we integrate these three optimization procedures into one training process to form a comprehensive learning framework for co-optimization, which can achieve higher accuracy. The experimental results indicate that our comprehensive learning framework can obtain significant improvements over the original model when inferring on the crossbar-based IMP accelerator, with an average reduction of computing power and computing area by 100.02× and 17.37×, respectively. Furthermore, we can obtain totally integer-only, pruned, and reliable VGG-16 and ResNet-56 models for the Cifar-10 dataset on IMP accelerators, with accuracy drops of only 2.19% and 1.26%, respectively, without any hardware overhead.
Sound Mixed Fixed-Point Quantization of Neural Networks
Authors: Lohar Debasmita , Jeangoudoux Clothilde , Volkova Anastasia , Darulova Eva 
Published: September 2023

Neural networks are increasingly being used as components in safety-critical applications, for instance, as controllers in embedded systems. Their formal safety verification has made significant progress but typically considers only idealized real-valued networks. For practical applications, such neural networks have to be quantized, i.e., implemented in finite-precision arithmetic, which inevitably introduces roundoff errors. Choosing a suitable precision that is both guaranteed to satisfy a roundoff error bound to ensure safety and that is as small as possible to not waste resources is highly nontrivial to do manually. This task is especially challenging when quantizing a neural network in fixed-point arithmetic, where one can choose among a large number of precisions and has to ensure overflow-freedom explicitly.
This paper presents the first sound and fully automated mixed-precision quantization approach that specifically targets deep feed-forward neural networks. Our quantization is based on mixed-integer linear programming (MILP) and leverages the unique structure of neural networks and effective over-approximations to make MILP optimization feasible. Our approach efficiently optimizes the number of bits needed to implement a network while guaranteeing a provided error bound. Our evaluation on existing embedded neural controller benchmarks shows that our optimization translates into precision assignments that mostly use fewer machine cycles when compiled to an FPGA with a commercial HLS compiler than code generated by (sound) state-of-the-art. Furthermore, our approach handles significantly more benchmarks substantially faster, especially for larger networks.
Probabilistic Reaction Time Analysis
Authors: Günzel Mario , Ueter Niklas , Chen Kuan-Hsun , von der Brüggen Georg , Chen Jian-Jia 
Published: September 2023

In many embedded systems, for instance, in the automotive, avionic, or robotics domain, critical functionalities are implemented via chains of communicating recurrent tasks. To ensure safety and correctness of such systems, guarantees on the reaction time, that is, the delay between a cause (e.g., an external activity or reading of a sensor) and the corresponding effect, must be provided.
Current approaches focus on the maximum reaction time, considering the worst-case system behavior. However, in many scenarios, probabilistic guarantees on the reaction time are sufficient. That is, it is sufficient to provide a guarantee that the reaction does not exceed a certain threshold with (at least) a certain probability.
This work provides such probabilistic guarantees on the reaction time, considering two types of randomness: response time randomness and failure probabilities. To the best of our knowledge, this is the first work that defines and analyzes probabilistic reaction time for cause-effect chains based on sporadic tasks.
A Still Small Voice: Psalms and Correlation as Media of Communication in Hermann Cohen’s Philosophy
Authors: Alon-Altman Talya 
Published: September 2023

Abstract
This article examines communication between a human being and God in the Jewish philosophy of Hermann Cohen (1842–1918). The article focuses on two distinct forms of biblical communication: lyrical psalms and a godly revelation in a still small voice. It investigates Cohen’s Jewish philosophy in light of communication theories to deepen the philosophical and theoretical discussion. The article examines previously unexplored ideas in Cohen’s writings, analyzes his religious perceptions in terms of communication, and at the same time expands the concept of communication. This new perspective sheds new light on Cohen’s Jewish philosophy and offers a new philosophic perception of divine-human communication.
The Myth of Zero-Sum Responsibility: Towards Scaffolded Responsibility for Health
Authors: Levy Neil , Savulescu Julian 
Published: September 2023

Abstract
Some people argue that the distribution of medical resources should be sensitive to agents’ responsibility for their ill-health. In contrast, others point to the social determinants of health to argue that the collective agents that control the conditions in which agents act should bear responsibility. To a large degree, this is a debate in which those who hold individuals responsible currently have the upper hand: warranted appeals to individual responsibility effectively block allocation of any significant degree of responsibility to collective agents. We suggest that a different understanding of individual responsibility might lead to a fairer allocation of blame. Scaffolded agency is individual agency exercised in a context in which opportunities and affordances are structured by others. Appeals to scaffolded agency at once recognize the role of the individual and of the collective agents who have put the scaffolds in place.