bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fuel starvation in automotive PEMFC stacks: stack current and bipolar plate resistance
Authors: Nissen Jens , Boye Jan-Peter , Schrievers Max , Schwämmlein Jan Nicolas , Hölzle Markus 
Published: December 2024

Abstract
Fuel cells are a viable option to reduce CO2 emissions of the heavy-duty transportation sector. However, under certain operation conditions, individual cells in the fuel cell stack may suffer from an undersupply of hydrogen, called fuel gross starvation (FGS). The voltage of affected cells is then reversed, enabling subsidiary reactions to gain the necessary current. These reactions are known to cause oxidation of the carbon in the anode catalyst layer, leading to performance degradation. This study demonstrates that FGS situations may furthermore cause a detrimental overheating behavior at high stack current. The behavior of two different 20-cell fuel cell stacks is investigated towards fuel starvation of one contained cell. One stack used carbon bipolar plates (BPs) with a comparatively high electric sheet resistance. The other stack used a modified BP which contained a copper-inlay, resulting in low electric sheet resistance. The behavior of the intentionally fuel starved cell was inspected in form of locally resolved current density, temperature and cell voltage. Additionally, the voltage of all other cells was simultaneously measured at the fuel inlet and outlet. At low stack currents, the fuel starved cell showed well comparable local behavior for both stack types. Significant differences occurred with increasing stack current. A spatially equal negative voltage was observed for the fuel starved cell when incorporated in the stack with a copper-inlay in the BP. A very high heat generation resulted from this condition, and detrimental effects of overheating were observed. In contrast, the fuel starved cell showed an intense variation of the local voltage when incorporated in the stack with only carbon-based BPs. The fuel outlet region of this cell hereby obtained a negative voltage, but the fuel inlet region maintained a positive voltage. This phenomenon allowed the fuel starved cell to counter-act an excessive heat production.
Latest advancements in smart grid technologies and their transformative role in shaping the power systems of tomorrow: an overview
Authors: Al-Shetwi Ali Q , Hannan M A , Al-Masri Hussein M K , Sujod Muhamad Zahim 
Published: December 2024

Abstract
Against the backdrop of a global shift towards renewable energy sources (RES) and the increasing complexity of modern power grids, smart grids (SGs) emerge as a critical solution for enhancing efficiency, reliability, and sustainability. This paper reviews a total of 177 key references published between 2014 and 2024, providing a comprehensive analysis of the most recent advancements in SG technologies and their pivotal role in shaping the future of power systems. The research explores the multifaceted components of SGs, encompassing intelligent sensing, communication technologies, home energy management systems, demand-side management, smart metering, smart electric vehicle charging, smart lighting, the Internet of Things, and the integration of big data, while investigating their role in enhancing the power grid in a smart and digitally integrated manner. The paper also discusses the SG features that have developed and improved the transmission and distribution networks, as well as the ancillary services on a grid-scale introduced through digitization. In addition, the status of the investment in SG is highlighted. The electrification of the global economy, driven by the urgent need to integrate RES, prompted an 8% increase in electricity grid investment in 2022. Additionally, digital technology investments for the grid constituted 19% of the total grid investment in the same year. SGs stand at the forefront of this transformation, playing a central role in facilitating the integration of variable RES, implementing digital technologies, smart devices, and optimizing power systems for diverse sectors. Despite substantial progress, some challenges persist that need further attention to ensure the seamless integration of SG technologies. The findings underscore the pivotal role of SGs in enhancing energy efficiency, effectively managing distributed energy resources, and strengthening the resilience of power systems. In conclusion, the recent advancements in SGs mark a transformative era for the power sector. However, to fully unlock their potential, it is essential to address the key challenges that hinder their seamless integration. Accordingly, these challenges are outlined to guide future research in developing innovative solutions that further optimize and advance the capabilities of SGs.
Supply-side challenges and research needs on the road to 100% zero-emissions vehicle sales
Authors: Jenn Alan , Chakraborty Amrita , Hardman Scott , Hoogland Kelly , Sugihara Claire , Tal Gil , Helveston John , Rich Jeppe , Jochem Patrick , Plötz Patrick , Sprei Frances , Williams Brett , Axsen Jonn , Figenbaum Erik , Pontes Jose , Refa Nazir 
Published: December 2024

Abstract
In this review paper, we delve into the supply-side challenges and considerations for transitioning to 100% zero-emission vehicles (ZEVs), weaving together an analysis of batteries, vehicle production, charging infrastructure, and relevant supply-side policies. We begin by examining the innovations and environmental impacts of lithium mining and recycling, highlighting the need for robust frameworks to ensure sustainable battery production. Our exploration of vehicle production reveals important issues regarding labor dynamics and global competitiveness. Our investigation into charging infrastructure reveals complexities in deployment models and access, reflecting broader societal and economic considerations. Lastly, a critical evaluation of policies across various jurisdictions provides insights into the effectiveness and potential improvements needed to support the ZEV transition. We emphasize the need for coordinated efforts and further research, particularly in areas such as end-of-life considerations for batteries and the alignment of international production standards. Our findings contribute to a comprehensive understanding of the supply-side landscape for ZEVs and underscore the essential research directions to ensure a responsible and successful electrification of the transportation system.
Accurate path tracing of a tracked robot: a modified PID approach with slip compensation
Authors: Deshmukh Deepak , Kumutham Anand Ronald , Pratihar Dilip Kumar , Deb Alok Kanti 
Published: December 2024

Abstract
The tracked robot functioning in unstructured and dynamic off-road environments poses significant challenges, necessitating sophisticated mathematical modeling. This paper explores the precise path-tracking capabilities of tracked robots in the presence of external disturbances. This study presents a model-based control method for tracked robots, using a modified PID controller. Genetic algorithms optimizes the control parameters to enhance tracking performance. The dynamic model of the robot has been implemented with kinematic backstepping to ensure velocity and position control. Considering the importance of accurately representing real-world scenarios, the mathematical model includes the robot dynamics, factoring in the influence of external disturbances and slippage, which increases the accuracy of the proposed control system. The output of the proposed controller was compared with the classical PID control technique on the basis of various performance indicators such as Integral Absolute Error (IAE), Integral Square Error (ISE), and sensitivity to disturbances. Simulation studies using MATLAB Simulink demonstrated the effectiveness of the proposed approach by enabling tracked robots to follow a desired path in complex terrain accurately. The developed controller was deployed on the experimental setup, and the trajectory tracking test was performed in indoor laboratory conditions. Experimental results show the robust performance and reliability of the modified PID controller, which provides precise path tracking while maintaining the reference robot's velocities.
Are queries and keys always relevant? A case study on transformer wave functions
Authors: Rende Riccardo , Loris Viteritti Luciano 
Published: December 2024

Abstract
The dot product attention mechanism, originally designed for natural language processing tasks, is a cornerstone of modern Transformers. It adeptly captures semantic relationships between word pairs in sentences by computing a similarity overlap between queries and keys. In this work, we explore the suitability of Transformers, focusing on their attention mechanisms, in the specific domain of the parametrization of variational wave functions to approximate ground states of quantum many-body spin Hamiltonians. Specifically, we perform numerical simulations on the two-dimensional J
1–J
2 Heisenberg model, a common benchmark in the field of quantum many-body systems on lattice. By comparing the performance of standard attention mechanisms with a simplified version that excludes queries and keys, relying solely on positions, we achieve competitive results while reducing computational cost and parameter usage. Furthermore, through the analysis of the attention maps generated by standard attention mechanisms, we show that the attention weights become effectively input-independent at the end of the optimization. We support the numerical results with analytical calculations, providing physical insights of why queries and keys should be, in principle, omitted from the attention mechanism when studying large systems.
Toward a process-oriented understanding of water in the climate system: recent insights from stable isotopes
Authors: Bailey Adriana , Noone David , Dee Sylvia , Nusbaumer Jesse , Conroy Jessica , Stevenson Samantha , Atwood Alyssa 
Published: December 2024

Abstract
Describing the processes that regulate the flows and exchanges of water within the atmosphere and between the atmosphere and Earth’s surface is critical for understanding environmental change and predicting Earth’s future accurately. The heavy-to-light hydrogen and oxygen isotope ratios of water provide a useful lens through which to evaluate these processes due to their innate sensitivity to evaporation, condensation, and mixing. In this review, we examine how isotopic information advances our understanding about the origin and transport history of moisture in the atmosphere and about convective processes—including cloud mixing and detrainment, precipitation formation, and rain evaporation. Moreover, we discuss how isotopic data can be used to benchmark numerical simulations across a range of scales and improve predictive skill through data assimilation techniques. This synthesis of work illustrates that, when paired with air mass thermodynamic properties that are commonly measured and modeled (such as specific humidity and temperature), water’s isotope ratios help shed light on moist processes that help set the climate state.
Evaluation of historical precipitation interannual variability in CMIP6 over the United States
Authors: Harp Ryan D , Taguela Thierry N , Akinsanola Akintomide A , Horton Daniel E 
Published: December 2024

Abstract
Interannual precipitation variability profoundly influences society via its effects on agriculture, water resources, infrastructure, and disaster risks. In this study, we use daily in situ precipitation observations from the global historical climatology network-daily (GHCN-D) to assess the ability of 21 Coupled Model Intercomparison Project Phase 6 (CMIP6) models, including the 50-member fifth-generation Canadian Earth System Model single model initial-condition large ensemble (CanESM5_SMILE), to realistically simulate historical interannual precipitation variability trends within 17 regions of the contiguous United States (CONUS). We assess how accurately the CMIP6 simulations align with observational data across annual, summer, and winter periods, focusing on four key hydrometeorological metrics, including interannual precipitation variability, relative interannual precipitation variability (coefficient of variation), annual mean precipitation, and annual wet day frequency. Our findings reveal that CMIP6 ensemble members generally reproduce the spatial patterns of observed trends in annual mean precipitation. In most regions, models agree well with the signs of observed changes in annual mean precipitation, though discrepancies in trend magnitude are evident. Further, observed trends in winter mean precipitation broadly exhibit a spatial pattern similar to that of the observed annual mean. However, analysis of the CanESM5_SMILE shows that trends in precipitation variability may primarily be the result of model-simulated internal variability, suggesting caution in interpreting multi-model single-realization ensemble results. Challenges in accurately simulating interannual precipitation variability underscore the need for ongoing model refinement and validation to enhance climate projections, especially in regions vulnerable to extreme precipitation events.
Decarbonization and technology cost drivers: considerations for potential future thermoelectric water use in the power sector
Authors: Cohen Stuart , Valdez Raquel , Tidwell Vincent , Khanal Saroj , Gunda Thushara 
Published: December 2024

Abstract
The power sector is currently undergoing significant changes, driven by a combination of factors, including decarbonization and technology innovation. This study aims to assess implications of these drivers on U.S. power sector technology futures and the associated water and environmental implications for cooling thermoelectric power plants. Specifically, we evaluate four decarbonization scenarios for the contiguous United States that vary in assumptions concerning demand growth and technology costs, with technology costs driving alternative outcomes that prioritize either technologies that require low amounts of water (such as wind, solar, and battery) or high amounts of water (such as nuclear and carbon capture and storage). These scenarios are executed in a power sector capacity expansion model and compared to two reference scenarios that assume status quo with policy and cost drivers. Our analysis indicates that future U.S. thermoelectric water withdrawals could decrease by 25%–60%, but water consumption could more than triple in some scenarios. These changes are driven by a combination of retirement of some power facilities, shifts in cooling technologies, and new technology deployment. The water use patterns vary across the United States, with the eastern regions demonstrating a lot more variability in water consumption across scenarios than western regions. However, local concerns can influence these possible investments, since increased water consumption can exacerbate water scarcity, leading to conflicts among competing users and affecting regional social, environmental, and economic dynamics. Future work should consider possible costs associated with alternate water sources, as well as improve the representation of water constraints within simulations. Inclusion of extreme events and alternate modeling platforms (e.g. production cost modeling and resource adequacy) may also be warranted to further stress test the robustness of these possible technology futures. Such assessments will be critical for ensuring decarbonization and other infrastructure-oriented investments lead to a reliable and resilient power grid.
Ligand identification in CryoEM and X-ray maps using deep learning
Authors: Karolczak Jacek , Przybyłowska Anna , Szewczyk Konrad , Taisner Witold , Heumann John M , Stowell Michael H B , Nowicki Michał , Brzezinski Dariusz 
Published: December 2024

Abstract

Motivation
Accurately identifying ligands plays a crucial role in the process of structure-guided drug design. Based on density maps from X-ray diffraction or cryogenic-sample electron microscopy (cryoEM), scientists verify whether small-molecule ligands bind to active sites of interest. However, the interpretation of density maps is challenging, and cognitive bias can sometimes mislead investigators into modeling fictitious compounds. Ligand identification can be aided by automatic methods, but existing approaches are available only for X-ray diffraction and are based on iterative fitting or feature-engineered machine learning rather than end-to-end deep learning.

Results
Here, we propose to identify ligands using a deep-learning approach that treats density maps as 3D point clouds. We show that the proposed model is on par with existing machine learning methods for X-ray crystallography while also being applicable to cryoEM density maps. Our study demonstrates that electron density map fragments can aid the training of models that can later be applied to cryoEM structures but also highlights challenges associated with the standardization of electron microscopy maps and the quality assessment of cryoEM ligands.

Availability and implementation
Code and model weights are available on GitHub at https://github.com/jkarolczak/ligands-classification. An accompanying ChimeraX bundle is available at https://github.com/wtaisner/chimerax-ligand-recognizer.
A deficiency screen identifies genomic regions critical for sperm head–tail connection
Authors: Galletta Brian J , Konstantinidou Parthena , Haase Astrid D , Rusan Nasser M 
Published: December 2024

Abstract
The Sperm Neck provides a stable connection between the sperm head and tail, which is critical for fertility in species with flagellated sperm. Within the Sperm Neck, the Head–Tail Coupling Apparatus serves as the critical link between the nucleus (head) and the axoneme (tail) via the centriole. To identify regions of the Drosophila melanogaster genome that contain genetic elements that influence Head–Tail Coupling Apparatus formation, we undertook a 2 part screen using the Drosophila Deficiency kit. For this screen, we utilized a sensitized genetic background that overexpresses the pericentriolar material regulatory protein Pericentrin-Like Protein. We had previously shown that Pericentrin-Like Protein overexpression disrupts the head–tail connection in some spermatids, but not to a degree sufficient to reduce fertility. In the first step of the screen, we tested for deficiencies that in combination with Pericentrin-Like Protein overexpression causes a reduction in fertility. We ultimately identified 11 regions of the genome that resulted in an enhanced fertility defect when combined with Pericentrin-Like Protein overexpression. In the second step of the screen, we tested these deficiencies for their ability to enhance the head–tail connection defect caused by Pericentrin-Like Protein overexpression, finding 6 genomic regions. We then tested smaller deficiencies to narrow the region of the genome that contained these enhancers and examined the expression patterns of the genes within these deficiencies using publicly available datasets of Drosophila tissue RNAseq and Drosophila testes snRNAseq. In total, our analysis suggests that some deficiencies may contain single genes that influence Head–Tail Coupling Apparatus formation or fertility, while other deficiencies appear to be genomic regions rich in testis-expressed genes that might affect the Head–Tail Coupling Apparatus through complex, multigene interactions.
Examining the relationship between weekend catch-up sleep and phenotypic age acceleration: Insights from a cross-sectional study
Authors: Liu Dongmei , Wang Chen , Huang Ben , Qiu Jun , Zhang Zheng 
Published: December 2024

Abstract

Background
Phenotypic age acceleration (PhenoAgeAccel) is a potential aging biomarker. While weekend catch-up sleep (WCS) is commonly practiced to compensate for weekday sleep deficits, its relationship with PhenoAgeAccel remains unclear.

Methods
In this cross-sectional study, we analyzed data from 7,683 participants in the National Health and Nutrition Examination Survey (NHANES). WCS duration was calculated as weekend sleep duration minus weekday sleep duration, and WCS was further defined as WCS duration &gt;0 h. Multivariable logistic regression adjusted for confounders and subgroup analyses by weekday sleep duration were employed to examine the relationship of WCS with PhenoAgeAccel.

Results
WCS is associated with a modulated risk of PhenoAgeAccel, contingent on the amount of WCS and regular weekday sleep. Specifically, engaging in 0–1 hour of WCS was associated with significantly lower odds of PhenoAgeAccel (Odds Ratio [OR] = 0.80, 95% Confidence Interval [CI]: 0.68, 0.94, p = 0.007) compared to no WCS, particularly among individuals who averaged 7–8 hours of sleep on weekdays (OR = 0.67, 95% CI: 0.49, 0.93, p = 0.016). Conversely, those sleeping less than 6 hours on weekdays benefited from extending WCS beyond 2 hours (OR = 0.65, 95% CI: 0.44, 0.97, p = 0.036). No benefits were observed for those with more than 8 hours of weekday sleep.

Conclusions
WCS is associated with a reduced likelihood of PhenoAgeAccel among individuals with inadequate weekday sleep, particularly those sleeping less than 6 hours or between 7 to 8 hours on weekdays.
Promoting Digital Citizenship in Social Work: Training Students for Inclusive and Accessible Tech-Health Practices
Authors: Funk Kristin , Wilkerson David 
Published: December 2024

Abstract
This article details a pedagogical approach to training graduate social work students in tech-health equity, emphasizing technology access as a fundamental human right. A tech-health training taxonomy was developed for a new social work course, aiming to equip students with macro-level skills to support equitable client access to telehealth. The training program was designed to illuminate and cultivate digital citizenship, an essential competency for advancing health equity and inclusivity among disadvantaged populations. To achieve this, the authors outline four pedagogical strategies to enhance students’ understanding and application of digital citizenship, digital self-efficacy, and the empowerment of underserved communities in navigating telehealth. Additionally, the article proposes a research framework to assess the effectiveness of these strategies in supporting students’ mastery of digital citizenship competencies and self-efficacy, including both reactive self-efficacy and generative self-efficacy. This novel approach seeks to prepare future social workers to address the digital divide in healthcare services and promote inclusivity.
Measuring the effectiveness of fisheries management to sustainably produce food
Authors: Hilborn Ray , Hively Daniel , Melnychuk Michael C 
Published: December 2024

Abstract
The objectives of fisheries management are diverse and include production of food, employment, and profit while protecting marine species and the environment. Most evaluations of fisheries outcomes focus on the status of fish stocks, rather than on fisheries’ performance in producing benefits such as food. We develop an index based on calculating the long-term food production for individual stocks as a function of fishing pressure, and comparing that to the estimated maximum sustainable yield. We calculate this index for 19 data-rich countries and 5 regional fisheries management organizations and estimate what fraction of the potential wild-caught fishery yield would be obtained under current management. Across all countries, 77% of the combined maximum sustainable yield is predicted to be caught in the long term. Of the remaining quantity foregone, 86% of foregone food production was attributed to low fishing pressure compared to only 14% foregone resulting from overfishing. The international fisheries had 4% of yield lost to overfishing, and 12% lost due to low fishing pressure. This means that most of the potential for increasing fisheries yield from assessed stocks would come from increased fishing pressure on stocks that are currently underexploited, but this may not be consistent with other national objectives.