bluuebunny/crossref_metadata_2025_split huggingface dataset:
Observation of momentum-induced broadening of width in narrow Feshbach resonances of ultracold 133Cs atoms
Authors: Liu 刘 Zhennan 震南 , Zhao 赵 Hongxing 宏星 , Wang 王 Yunfei 云飞 , Li 李 Yuqing 玉清 , Wu 武 Jizhou 寄洲 , Liu 刘 Wenliang 文良 , Li 李 Peng 鹏 , Fu 付 Yongming 永明 , Xiao 肖 Liantuan 连团 , Ma 马 Jie 杰 , Jia 贾 Suotang 锁堂 
Published: November 2024

Abstract
Interactions between atoms in ultracold quantum gases play an important role in the study of the quantum simulation of many-body physics. Feshbach resonance is a versatile tool to control atomic interactions, where the atom-loss spectra are widely used to characterize Feshbach resonances of various atomic species. Here, we report the experimental observation of momentum-induced broadening of widths in atom-loss spectra of narrow 133Cs Feshbach resonances. We drive Bragg excitation to kick the Bose–Einstein condensate of Cs atoms in a cigar-shaped optical trap, and measure the atom-loss spectra of narrow Feshbach resonances of moving ultracold atoms near the magnetic fields 19.84 G and 47.97 G. We show that the widths of the atom-loss spectra are broadened for the atoms with the momenta of 2ħk and 4ħk, and even observe splitting in the Feshbach resonance of the atoms with momentum 4ħk. Our work may open the way for exploring the interesting physical phenomena arising from the collective velocity of colliding atoms that have been ignored in general.
Group cohesion and passive dynamics of a pair of inertial swimmers with three-dimensional hydrodynamic interactions
Authors: Mabrouk Mohamed Niged , Floryan Daniel 
Published: November 2024

Abstract
When swimming animals form cohesive groups, they can reap several benefits. Our understanding of collective animal motion has traditionally been driven by models based on phenomenological behavioral rules, but more recent work has highlighted the critical importance of hydrodynamic interactions among a group of inertial swimmers. To study how hydrodynamic interactions affect group cohesion, we develop a three-dimensional, inviscid, far-field model of a swimmer. In a group of two model swimmers, we observe several dynamical phases, including following, divergence, collision, and cohesion. Our results illustrate when cohesive groups can passively form through hydrodynamic interactions alone, and when other action is needed to maintain cohesion. We find that misalignment between swimmers makes passive cohesion less likely; nevertheless, it is possible for a cohesive group to form through passive hydrodynamic interactions alone. We also find that the geometry of swimmers critically affects the group dynamics due to its role in how swimmers sample the velocity gradient of the flow.
A Bowen ratio-informed method for coordinating the estimates of air–sea turbulent heat fluxes
Authors: Wang Yizhe , Tang Ronglin , Huang Lingxiao , Liu Meng , Jiang Yazhen , Li Zhao-Liang 
Published: November 2024

Abstract
Accurate quantification of turbulent heat fluxes [THF, comprising sensible heat flux (SHF) and latent heat flux (LHF)] and Bowen ratio (β, ratio of SHF and LHF) is essential for understanding the air–sea interaction. However, the biased estimates of SHF and LHF by widely applied bulk aerodynamic models, and the separate estimates of SHF and LHF by data-driven models, both may result in unrealistic β estimates. This study for the first time innovatively proposes a Bowen ratio-informed data-driven model (BrTHF) for coordinating the estimations of THF and β using the multivariate random forest (RF) technique and a combination of eddy covariance flux observations and meteorological and oceanic observations collected from 53 historical cruises. The result shows that the BrTHF model could not only achieve high-accuracy SHF and LHF estimates, but also avoid the outliers of β estimates that were commonly found in un-synergistic RF and well-known Coupled Ocean Atmosphere Response Experiment 3.5 models.
Fabrication of superhydrophobic transparent coatings prepared by spraying dual-sized silica particles
Authors: Yang Yue-Xin , Wang Bing-Bing , Wang Xin , Liu Yu 
Published: November 2024

Abstract
Photovoltaic modules exposed to severe wind and sand conditions over extended periods often accumulate dust, significantly impacting their power generation efficiency. Superhydrophobic self-cleaning coatings present a promising solution to mitigate this issue. In this study, a SiO2/PU coating was applied to glass substrates using a combined sol–gel spraying technique. The sol system comprised a mixture of SiO2 particles with diameters of 20 nm and 200 nm, enabling the construction of a micro-nano structure that enhances surface hydrophobicity. The SiO2/PU coatings prepared with mixed particle sizes demonstrated significant improvements in contact angle, rolling angle, self-cleaning, and antifouling properties compared to those made with a single particle size, achieving a water contact angle of 164.52°. Furthermore, the prepared SiO2/PU coatings possess excellent stability and transmittance. It is anticipated that this superhydrophobic SiO2/PU coating will be a candidate for anti- dust applications in photovoltaic modules.
Evaluating machine learning-based elephant recognition in complex African landscapes using drone imagery
Authors: McCarthy Chris , Banda Lumbani Benedicto , Kachamba Daud Jones , Emmanuel Junior Zuza , Chisambi Cornelius , Kumanga Ndaona , Lawrence Luciano , Sternberg Troy 
Published: November 2024

Abstract
This paper evaluates a machine learning-based approach for identifying and analyzing African bush elephants within complex terrains using high-resolution drone imagery. With human-wildlife conflict posing a significant threat to elephants worldwide, accurate and efficient monitoring techniques are crucial, yet challenging in diverse landscapes. Our study utilizes approximately 3,180 drone-captured images from Kasungu National Park in Malawi, encompassing various terrains including dense forests and open bushlands. These images were systematically preprocessed and analyzed using three distinct ML algorithms: Faster R-CNN, RetinaNet, and Mask R-CNN, each fine-tuned for identification of elephants across different age groups. Comparative performance metrics revealed nuanced strengths and limitations: Faster R-CNN showed notable proficiency in detecting adult elephants, particularly in dense foliage. Mask R-CNN, while less precise overall, demonstrated increased effectiveness in identifying juveniles and infants. RetinaNet, optimized for larger images, showed particular adeptness with adult elephants but less so with younger ones. Despite these promising results, overall recognition rates were lower than ideal, highlighting the complexities of wildlife identification in natural settings. This study not only facilitates the identification and counting of individual elephants but also provides insights into the challenges of applying ML in complex ecological contexts. The derived insights can assist conservationists and park officials in making informed decisions related to wildlife protection and habitat preservation. Furthermore, the study offers a valuable blueprint for integrating AI and machine learning technology into wildlife conservation strategies, presenting a scalable model with potential applications for different species and geographic regions, while acknowledging the need for further refinement to enhance accuracy and reliability in diverse ecological settings.
Farm characteristics determine why a large share of organically produced wine is not labelled as organic
Authors: Zachmann Lucca , McCallum Chloe , Finger Robert 
Published: November 2024

Abstract
Organic agricultural production is increasing globally and is of high policy relevance, particularly in Europe. Various measures incentivize farmers to adopt organic practices, such as direct payments and labelling. We here address a rarely considered aspect of organic production, that not all organic producers in Europe opt for organic labelling for their products at the point of sale. We investigate the discrepancy between organic production and labelling in Swiss viticulture. Out of 115 grapevine growers who adhere to organic principles in production, 43.5% do not use organic labelling when marketing their wines. We find that especially farms using alternative labelling strategies (e.g. for fungus-resistant varieties), smaller farms and farms less specialized in viticulture to be more likely to forgo organic labelling. We draw conclusions for policy and science. For example, our findings show that there may be, for some crops, more organic products on shelves than indicated from sales statistics of organically labelled products. The use of statistics that indicate the share of sales of organic products for specific products and food sales at large may thus be misleading.
Enhancing regeneration and functionality of excitable tissues via integrating bioelectronics and bioengineered constructs
Authors: Meng Zijie , Gu Bingsong , Yao Cong , Li Jiaxin , Yu Kun , Ding Yi , He Pei , Jiang Nan , Li Dichen , He Jiankang 
Published: November 2024

Abstract
The inherent complexities of excitable cardiac, nervous, and skeletal muscle tissues pose great challenges in constructing artificial counterparts that closely resemble their natural bioelectrical, structural, and mechanical properties. Recent advances have increasingly revealed the beneficial impact of bioelectrical microenvironments on cellular behaviors, tissue regeneration, and therapeutic efficacy for excitable tissues. This review aims to unveil the mechanisms by which electrical microenvironments enhance the regeneration and functionality of excitable cells and tissues, considering both endogenous electrical cues from electroactive biomaterials and exogenous electrical stimuli from external electronic systems. We explore the synergistic effects of these electrical microenvironments, combined with structural and mechanical guidance, on the regeneration of excitable tissues using tissue engineering scaffolds. Additionally, the emergence of micro/nanoscale bioelectronics has significantly broadened this field, facilitating intimate interactions between implantable bioelectronics and excitable tissues across cellular, tissue, and organ levels. These interactions enable precise data acquisition and localized modulation of cell and tissue functionalities through intricately designed electronic components according to physiological needs. The integration of tissue engineering and bioelectronics promises optimal outcomes, highlighting a growing trend in developing living tissue construct-bioelectronic hybrids for restoring and monitoring damaged excitable tissues. Furthermore, we envision critical challenges in engineering the next-generation hybrids, focusing on integrated fabrication strategies, the development of ionic conductive biomaterials, and their convergence with biosensors.
Impact of data bias on machine learning for crystal compound synthesizability predictions
Authors: Davariashtiyani Ali , Wang Busheng , Hajinazar Samad , Zurek Eva , Kadkhodaei Sara 
Published: November 2024

Abstract
Machine learning models are susceptible to being misled by biases in training data that emphasize incidental correlations over the intended learning task. In this study, we demonstrate the impact of data bias on the performance of a machine learning model designed to predict the likelihood of synthesizability of crystal compounds. The model performs a binary classification on labeled crystal samples. Despite using the same architecture for the machine learning model, we showcase how the model’s learning and prediction behavior differs once trained on distinct data. We use two data sets for illustration: a mixed-source data set that integrates experimental and computational crystal samples and a single-source data set consisting of data exclusively from one computational database. We present simple procedures to detect data bias and to evaluate its effect on the model’s performance and generalization. This study reveals how inconsistent, unbalanced data can propagate bias, undermining real-world applicability even for advanced machine learning techniques.
An efficient Wasserstein-distance approach for reconstructing jump-diffusion processes using parameterized neural networks
Authors: Xia Mingtao , Li Xiangting , Shen Qijing , Chou Tom 
Published: November 2024

Abstract
We analyze the Wasserstein distance (W-distance) between two probability distributions associated with two multidimensional jump-diffusion processes. Specifically, we analyze a temporally decoupled squared W
2-distance, which provides both upper and lower bounds associated with the discrepancies in the drift, diffusion, and jump amplitude functions between the two jump-diffusion processes. Then, we propose a temporally decoupled squared W
2-distance method for efficiently reconstructing unknown jump-diffusion processes from data using parameterized neural networks. We further show its performance can be enhanced by utilizing prior information on the drift function of the jump-diffusion process. The effectiveness of our proposed reconstruction method is demonstrated across several examples and applications.
The paradox of safe milk supply by small-scale dairy farmers in Sub-Saharan Africa: insights based on current practices in Malawi
Authors: Njombwa Chunala A , Chisambi Cornellius , Chris McCarthy 
Published: November 2024

Abstract
This research paper aimed to assess milking and milk handling practices among small-scale dairy farmers and to determine the presence of Escherichia coli (E. coli) in raw and processed liquid milk in Malawi. A total of 113 dairy farmers were interviewed across three agroecological zones of Malawi. Eighty-seven (87) processed and raw milk samples were collected from selected food stores and dairy farms and tested for E. coli. Ninety-five percent of small-scale dairy farmers had at most 2 milking cows, with a daily average milk production of less than 10 l. Sixty-nine percent cleaned milking utensils using untreated water, and the farmers had no refrigerators. Eighty-eight percent held raw milk for over 6 h at room temperature. E. coli was found to be widely distributed in raw milk (76%) and pasteurized milk (75%), averaging 5.38 ± 1.82 and 2.47 ± 1.02 log cfu ml−1, respectively. In conclusion, this study demonstrates that Malawian small-scale dairy farmers employ poor milking and post-milking practices, which compromise the socioeconomic environment of small-scale dairy farmers.
Source-specific acute cardio-respiratory effects of ambient coarse particulate matter exposure in California’s Salton Sea region
Authors: Miao Yaning , Porter William C , Benmarhnia Tarik , Lowe Catherine , Lyons Timothy W , Hung Caroline , Diamond Charles 
Published: November 2024

Abstract
Windblown dust is an ongoing air quality and public health concern among residents living around California’s Salton Sea, a region characterized by critical socioeconomic and health outcome disparities. Dropping water levels and unique biogeochemistry at the Salton Sea have raised concerns regarding the human health impacts of drying sediments exposed on shrinking shorelines, as well as potential lake spray emissions from the water surface itself. As particles emitted from different surface types can differ greatly in terms of composition, size distribution, and other properties, variability in the resulting health impacts of windblown particulates reaching communities in the region may likewise be source dependent. However, these potential effects remain understudied. Here we use observed coarse particulate matter (PMc) concentrations and modeled atmospheric back trajectories along with land surface data to estimate individual source region contributions to particulates observed at long term surface air quality monitoring sites in the Salton Sea region. We then apply these data products to an analysis of source-specific acute cardio-respiratory impacts using a time-stratified case crossover design with conditional logistic regression based on 171 465 hospitalizations cases recorded from 2008 to 2019. To assess source-specific health impacts, we quantify and compare the acute health effects of dust arriving from different directions and from over different source surfaces on daily respiratory and cardiovascular hospitalizations. Using a remote sensing chlorophyll-a data product, we further investigate the possible influence of periodic bloom events—a result of ongoing nutrient loading into the Salton Sea—on those hospitalizations. Results suggest that a 10 μg m−3 increase in coarse PM coming from over the Salton Sea is associated with an 8.6% (Risk Ratio, RR = 1.086, 95% CI: 1.028–1.147) increased risk of respiratory hospital admissions; increases that are greater than those for dust likely originating from other surface types. Furthermore, we find even higher RR values for dust associated with Salton Sea back trajectories during bloom events: a 24.9% (RR = 1.249 95% CI: 1.031–1.514) increased risk in respiratory hospitalization. Our findings suggest that exposure to dust and aerosols potentially originating from the Salton Sea or surrounding surfaces is associated with increased respiratory hospitalizations, especially during observed bloom events. Further research is needed to determine the underlying mechanisms responsible for these health impacts, as well as possible primary or secondary preventive strategies.
Natural assets, changes, and variations of the socioeconomic-environmental systems along the Asian drylands belt
Authors: Chen Jiquan , John Ranjeet , Kolluru Venkatesh , Mack Elizabeth A , Fan Peilei , Yuan Jing , Ouyang Zutao , Chen Jingyan , Groisman Pavel , Shao Changliang , Amartuvshin Amarjargal , Gutman Garik 
Published: November 2024

Abstract
The amount of and changes in a country’s natural assets are crucial for developing national strategic plans and policies due to their foundational role in determining the resilience of social-environmental systems (SES), especially under a changing climate. Many integrated metrics on natural assets have been proposed based on individual measures to provide insights into the state of national natural resources. This is particularly true for countries experiencing extreme environmental stresses. Drawing on longitudinal data spanning from 1980 to 2020, the objective of this study is to analyze nuanced distinctions across 23 political entities (PEs) in the dryland regions of mid-latitudinal Asia, investigating their interannual variabilities over the four-decade study period and discerning potential driving forces. We examined three key integrated measures of the SES: ecosystem water use efficiency, human appropriation of net primary production, and human appropriation of water resources. We found increased variability as well as spikes in extreme values in each of these three measures of SES function among the 23 PEs over the study period. Water stress played an increasing and more important role than temperature in influencing the magnitude and variations of the three measures. Our results also indicate that human interventions may help increase the efficiency of water use in this dryland region of the world.
Portraits of Religious Conversions
Authors: John Aruthuckal Varughese 
Published: November 2024

Abstract
Chapter 4 analyses the interreligious strife that has become common in India, focusing on the issue of religious conversion. The chapter argues that the conflicts related to conversion are manifestations of the cross-pressures within the condition of secularity in India. In particular, opposition to religious conversions reveals the way Christianity and the secular are seen as allies, even conflated, by many Hindus, based in part on the association of Christian missions with colonialism. In addition, though, religious conversions, which assume individual volition and threaten social hierarchy, can be perceived by orthodox Hindus as a betrayal of culture and a danger to a social fabric infused with the sacred.
Religious Freedom, Truth-Predicates, and the Ghent School
Authors: John Aruthuckal Varughese 
Published: November 2024

Abstract
Chapter 5 examines one prominent attempt to relieve the cross-pressures surrounding religious freedom: the Ghent School’s challenge to the classical notion of religious freedom as freedom to convert. S. N. Balagangadhara, Jakob De Roover, and some others have argued that the Indian Constitution’s definition of freedom of religion results from Judaeo-Christian religious doctrine rather than from the Hindu tradition. Underlying this argument is the assumption that conceptions of religious freedom function as subsets of religious doctrine. This, in their view, entails a conflict, in which the Constitution’s conception of religious freedom conflicts with the Hindu conception of religious freedom. However, the central assumption of the Ghent School’s argument, that truth-predicates are unique to Semitic religious beliefs and therefore alien to Hinduism, is false. By using Śivapurāṇa as a case in point, this chapter illustrates that Hinduism has a robust idea of truth. It also argues that all human beliefs, religious or otherwise, possess truth-predicates. If truth-predicates are tied to religious beliefs, contrary to the Ghent School’s claim, then the secularism of India’s Constitution cannot be dismissed as alien to Indian culture on these grounds. Religious freedom grounded in the equality of individuals rather than the equality of religious beliefs does not entail a privileging of Semitic religions over Hinduism.
Clinical biomarker–based biological ageing and the risk of adverse outcomes in patients with chronic kidney disease
Authors: Xiang Hao , Huang Yu , Zhang Yuanyuan , He Panpan , Ye Ziliang , Yang Sisi , Zhang Yanjun , Gan Xiaoqin , Hou Fan Fan , Qin Xianhui 
Published: November 2024

Abstract

Objective
Patients with chronic kidney disease (CKD) show features of premature ageing. We aimed to evaluate the association between biological ageing and adverse outcomes, including end-stage kidney disease (ESKD), cardiovascular diseases (CVD) and all-cause mortality, in patients with CKD.

Methods
23 435 participants with CKD and free of related adverse outcomes at baseline from the UK Biobank were included. Leukocyte telomere length (LTL) was measured by quantitative polymerase chain reaction assay. Clinical biomarker–based biological ages were quantified using Klemera–Doubal method biological age (KDM-BA) and PhenoAge algorithms.

Results
During a median follow-up of 12 years, 3417 incident CVD, 383 incident ESKD and 3195 all-cause mortality were recorded. Per SD increment of KDM-BA acceleration was associated with a 56% [95% confidence interval (CI): 41%–73%], 26% (95% CI: 21%–31%) and 39% (95% CI: 34%–44%) increase in the risk of incident ESKD, incident CVD and all-cause mortality, respectively. Similar results were found for PhenoAge acceleration. LTL (per SD increment) was inversely associated with the risk of incident CVD [hazard ratio (HR): 0.96, 95% CI: 0.92–0.99] and all-cause mortality (HR: 0.94, 95% CI: 0.91–0.98) and was not significantly associated with the risk of incident ESKD (HR: 0.96, 95% CI: 0.86–1.06). Adding KDM-BA acceleration or PhenoAge acceleration, but not LTL, to the traditional validated clinical prediction models significantly improved the predictive performance for incident ESKD, all-cause mortality and CVD.

Conclusion
In patients with CKD, both KDM-BA acceleration and PhenoAge acceleration were associated with an increased risk of ESKD, CVD and all-cause mortality, and KDM-BA or PhenoAge may be a better predictor on adverse outcomes than LTL.