bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intensity Zones and Intensity Thresholds Used to Quantify External Load in Competitive Basketball: A Systematic Review
Authors: Tuttle Matthew C. , Power Cody J. , Dalbo Vincent J. , Scanlan Aaron T. 
Published: June 2024

Abstract
Background
Despite widespread use of intensity zones to quantify external load variables in basketball research, the consistency in identifying zones and accompanying intensity thresholds using predominant monitoring approaches in training and games remains unclear.

Objectives
The purpose of this work was to examine the external load intensity zones and thresholds adopted across basketball studies using video-based time-motion analysis (TMA), microsensors, and local positioning systems (LPS).

Methods
PubMed, MEDLINE, and SPORTDiscus databases were searched from inception until 31 January 2023 for studies using intensity zones to quantify external load during basketball training sessions or games. Studies were excluded if they examined players participating in recreational or wheelchair basketball, were reviews or meta-analyses, or utilized monitoring approaches other than video-based TMA, microsensors, or LPS.

Results
Following screening, 86 studies were included. Video-based TMA studies consistently classified jogging, running, sprinting, and jumping as intensity zones, but demonstrated considerable variation in classifying low-intensity (standing and walking) and basketball-specific activities. Microsensor studies mostly utilized a single, and rather consistent, threshold to identify only high-intensity activities (> 3.5 m·s−2 for accelerations, decelerations, and changes-in-direction or > 40 cm for jumps), not separately quantifying lower intensity zones. Similarly, LPS studies predominantly quantified only high-intensity activities in a relatively consistent manner for speed (> 18.0 m·s−1) and acceleration/deceleration zones (> 2.0 m·s−2); however, the thresholds adopted for various intensity zones differed greatly to those used in TMA and microsensor research.

Conclusions
Notable inconsistencies were mostly evident for low-intensity activities, basketball-specific activities, and between the different monitoring approaches. Accordingly, we recommend further research to inform the development of consensus guidelines outlining suitable approaches when setting external load intensity zones and accompanying thresholds in research and practice.
Osteosarcopenia increases the risk of mortality: a systematic review and meta-analysis of prospective observational studies
Authors: Veronese Nicola , Ragusa Francesco Saverio , Sabico Shaun , Dominguez Ligia J. , Barbagallo Mario , Duque Gustavo , Al-Daghri Nasser 
Published: June 2024

Abstract
Background & aims
Osteosarcopenia is a recently recognized geriatric syndrome. The association between osteosarcopenia and mortality risk is still largely underexplored. In this systematic review with meta-analysis of prospective cohort studies, we aimed to explore whether osteosarcopenia could be associated with a higher mortality risk.

Methods
Several databases were searched from the inception to 16th February 2024 for prospective cohort studies dealing with osteosarcopenia and mortality. We calculated the mortality risk in osteosarcopenia vs. controls using the most adjusted estimate available and summarized the data as risk ratios (RRs) with their 95% confidence intervals (CIs). A random-effect model was considered for all analyses.

Results
Among 231 studies initially considered, nine articles were included after exclusions for a total of 14,429 participants (mean age: 70 years; 64.5% females). The weighted prevalence of osteosarcopenia was 12.72%. Over a mean follow-up of 6.6 years and after adjusting for a mean of four covariates, osteosarcopenia was associated with approximately 53% increased risk of mortality (RR: 1.53; 95% CI: 1.28–1.78). After accounting for publication bias, the re-calculated RR was 1.48 (95%CI: 1.23–1.72). The quality of the studies was generally good, as determined by the Newcastle Ottawa Scale.

Conclusions
Osteosarcopenia was significantly linked with an increased risk of mortality in older people, indicating the need to consider the presence of osteoporosis in patients with sarcopenia, and vice versa, since the combination of these two conditions typical of older people may lead to further complications, such as mortality.
The readiness of Jordanian-listed firms toward CAATTs application in the post Covid-19 epidemic period
Authors: Alnatour Abdulrahman , Al-Mawali Hamzah , Zaidan Hala , Meqbel Rasmi , Kawuq Shatha 
Published: June 2024

AbstractThis study examines the readiness of Jordanian-listed firms toward the application of Computer Assisted Audit Tools and Techniques (CAATTs) during the post-Covid-19 epidemic period. In particular, this study investigates the auditee perspective regarding the factors impacting the adoption of CAATTs based on the Organizational Readiness for Change (ORC) and the Technology Readiness Index (TRI) models. A cross-sectional survey was developed and distributed to 138 employees working in the accounting departments of Jordanian-listed firms. Partial least square structural equation modeling (PLS-SEM) was employed as the statistical analysis method to examine the study hypotheses. The results show a significant direct relationship of motivation for change, staff attributes, institutional resources, organizational climate and discomfort on readiness for change. Moreover, the results reveal that perceived fear of Covid-19 has a moderating effect on the direct relationship between motivation for change and readiness for change. However, the proposed relationships between optimism, innovativeness, and insecurity with readiness for change were not significant. This paper highlights the readiness toward CAATTs application from the auditee perspective rather than the external auditors. Moreover, this paper considers the changes in the work environment resulting from the Covid-19 pandemic on the motivation for change toward CAATTs. Lastly, the paper reveals the moderating role of perceived fear of Covid-19 on the influence of motivation for change on readiness to change. Hence, this paper set the basis for policymakers and practitioners toward evaluating the readiness of Jordanian-listed firms for CAATTs application.
From catch to consumer: enhancing seafood processing management with Industry 4.0 innovations
Authors: Subash Abhirami , Ramanathan Hareesh N. , Šostar Marko 
Published: June 2024

AbstractThe incorporation of Industry 4.0 technologies into the seafood processing sector presents a transformative potential for improving efficiency, sustainability, and transparency throughout the supply chain. This study aims to examine the impact of such technological advancements, including automation, robotics, blockchain, computer vision, AI, and IoT, on the seafood industry's operations, ranging from sorting, cleaning, and packing to quality assessment and product preservation. Conducted through a Systematic Literature Review (SLR) of Web of Science-indexed papers, this research assesses the synergy between innovation and business 4.0 technologies in seafood processing. Our findings suggest that these technologies not only promise enhanced operational efficiency and product quality but also offer sustainable practices through energy-efficient methods, waste management techniques, and innovative packaging solutions. Additionally, the study addresses the workforce implications, underscoring the shift in job roles towards more specialized and value-added positions rather than outright displacement. The primary data collected and analyzed herein underscores the critical role of Industry 4.0 in promoting sustainable resource management, optimizing processes, and ensuring ecological responsibility within the seafood sector, thereby contributing to the broader goals of food security and environmental sustainability.
Collective action in fishery resource management and its challenges in Ethiopia: a review
Authors: Zenbaba Oliyad Sori 
Published: June 2024

AbstractNatural resources such as fish are vital for improving human livelihood and serving as sources of food, income and employment opportunities in Ethiopia. But, its degradation and overexploitation lead to anxiety about the living standards of human beings and other living things. The degradation of these resources, which is caused by the less common participation of all stakeholders in protecting the resources, is the most challenging issue in the country. The objective of this paper is to review fishery production and management and their challenges, the extent of the overexploitation of natural resources, the contributions of collective action in fishery production and management, and fishery collective action challenges in Ethiopia. The review paper identified that the existence of a lack of strong coordination among different actors like local communities, the government, development agents, research centers and donor organizations whose concern are with the fishery sector caused the degradation of water bodies and fishery resources in Ethiopia. These issues resulted in challenges in fishery resource production and management, mismanagement in solving social differences among local communities, and low cooperation among communities in protecting fish resources. Besides, these challenges also caused a limited expansion of fishery collective action, overexploitation of fishery resources, and less concern for the protection of fish diversity species in the country. Therefore, essential policy implications forwarded are creating and improving joint collaboration between fish users, local communities, government institutions and development agents; organizing and empowering the local communities in collective action to involve them in the fishery sector to contribute to practical improvements in the protection, production, management and sustainability of fish resources.
MoonIndex, an Open‐Source Tool to Generate Spectral Indexes for the Moon From M3 Data
Authors: Suárez‐Valencia Javier Eduardo , Rossi Angelo Pio , Zambon Francesca , Carli Cristian , Nodjoumi Giacomo 
Published: June 2024

AbstractSpectral indexes are tools widely used to analyze the composition of planetary surfaces. Many indexes have been formulated over the years to map the lunar surface, but there is no unified database for them. In this work we describe an Open‐Source Python package called MoonIndex, that recreates 38 indexes compiled from the literature, using data from the Moon Mineralogy Mapper (M3). The processing started with the filtering of the data cubes to reduce the noise, the continuum of the spectrum was then removed using a convex hull or a second‐and‐first‐order fit method. Later, the indexes were calculated, following as possible the original formulations. The results on spectral indexes calculated before the continuum removal were similar to those of the original formulations. Conversely, the results obtained for spectral indexes calculated after the continual removal were not always coherent. Some indexes, like the band depth, are especially sensitive to the removal method, as well as the derived band areas and asymmetries. We also recreated RGB composite maps, our results highlight the compositional patterns in a similar way as the ones in the literature, even if the color ramps can differ. The products of MoonIndex are open, ready for interpretation, versatile, consistent, and cross‐comparable.
Disentangling the Advective Brewer‐Dobson Circulation Change
Authors: Šácha P. , Zajíček R. , Kuchař A. , Eichinger R. , Pišoft P. , Rieder H. E. 
Published: June 2024

AbstractClimate models robustly project acceleration of the Brewer‐Dobson circulation (BDC) in response to climate change. However, the BDC trends simulated by comprehensive models are poorly constrained by observations, which cannot even determine the sign of potential trends. Additionally, the changing structure of the troposphere and stratosphere has received increasing attention in recent years. The extent to which vertical shifts of the circulation are driving the acceleration is under debate. In this study, we present a novel method that enables the attribution of advective BDC changes to structural changes of the circulation and of the stratosphere itself. Using this method allows studying the advective BDC trends in unprecedented detail and sheds new light into discrepancies between different data sets (reanalyses and models) at the tropopause and in the lower stratosphere. Our findings provide insights into the reliability of model projections of BDC changes and offer new possibilities for observational constraints.
WeatherBench 2: A Benchmark for the Next Generation of Data‐Driven Global Weather Models
Authors: Rasp Stephan , Hoyer Stephan , Merose Alexander , Langmore Ian , Battaglia Peter , Russell Tyler , Sanchez‐Gonzalez Alvaro , Yang Vivian , Carver Rob , Agrawal Shreya , Chantry Matthew , Ben Bouallegue Zied , Dueben Peter , Bromberg Carla , Sisk Jared , Barrington Luke , Bell Aaron , Sha Fei 
Published: June 2024

AbstractWeatherBench 2 is an update to the global, medium‐range (1–14 days) weather forecasting benchmark proposed by (Rasp et al., 2020, https://doi.org/10.1029/2020ms002203), designed with the aim to accelerate progress in data‐driven weather modeling. WeatherBench 2 consists of an open‐source evaluation framework, publicly available training, ground truth and baseline data as well as a continuously updated website with the latest metrics and state‐of‐the‐art models: https://sites.research.google/weatherbench. This paper describes the design principles of the evaluation framework and presents results for current state‐of‐the‐art physical and data‐driven weather models. The metrics are based on established practices for evaluating weather forecasts at leading operational weather centers. We define a set of headline scores to provide an overview of model performance. In addition, we also discuss caveats in the current evaluation setup and challenges for the future of data‐driven weather forecasting.
Anomaly Detection Using Machine Learning in Hydrochemical Data From Hot Springs: Implications for Earthquake Prediction
Authors: Zhu Ruijie , Yang Fengtian , Zhou Xiaocheng , Tian Jiao , Zhang Yongxian , He Miao , Li Jingchao , Dong Jinyuan , Li Ying 
Published: June 2024

AbstractThis study explores the potential of machine learning algorithms for earthquake prediction, utilizing fluid chemical anomaly data from hot springs. Six hot springs, located within an active fault zone along the southeastern coast of China, were carefully chosen as hydrochemical monitoring sites for an extended period of two and a half years. Using this data, a prediction model integrating six algorithms was developed to forecastM ≥ 5 earthquakes in Taiwan. The model's performance was validated against recorded earthquake events, and the factors influencing its predictive capability were analyzed. Our comprehensive analysis conclusively demonstrates the superiority of machine learning algorithms over traditional statistical methods for earthquake prediction. Additionally, including sampling time in the data sets significantly improves the model's predictive performance. However, it is important to note that the model's predictive performance varies across different hot spring and indicators type, highlighting the importance of identifying optimal indicators for specific scenarios. The model parameters, including the anomaly detection rate (P) and earthquake response time threshold (M), significantly impact the model's predictive capabilities. Therefore, adjustments are needed to optimize the model's performance for practical use. Despite limitations such as the inability to differentiate pre‐earthquake anomalies from post‐earthquake anomalies and pinpoint the precise location of earthquakes, this study successfully showcases the potential of machine learning algorithms in earthquake prediction, paving the way for further research and improved prediction methods.
A Global Assessment of Groundwater Recharge Response to Infiltration Variability at Monthly to Decadal Timescales
Authors: Moeck Christian , Collenteur Raoul A. , Berghuijs Wouter R. , Luijendijk Elco , Gurdak Jason J. 
Published: June 2024

AbstractPredictions of groundwater fluctuations in space and time are important for sustainable water resource management. Infiltration variability on monthly to decadal timescales leads to fluctuations in the water tables and thus groundwater resources. However, connections between global‐scale climate variability and infiltration patterns and groundwater are often poorly understood because the relationships between groundwater conditions and infiltration tend to be highly nonlinear. In addition, understanding is further hampered because many groundwater records are incomplete and groundwater tables are often anthropogenically influenced, which makes identifying the effects of infiltration variability difficult. Previous studies that have evaluated how infiltration variability controls groundwater are based on a limited number of point measurements. Here, we present a global assessment of how infiltration variability is expected to affect groundwater tables. We use an analytical solution derived from Richards' equation to model water level responses to idealized periodic infiltration variability with periods that range from months to decades, to approximate both the effects of short‐term and long‐term climate variability and thus infiltration patterns. Our global‐scale assessment reveals why infiltration variability would lead to periodicity in groundwater recharge in particular regions. The vadose zone strongly dampens short‐term (seasonal and shorter) variations in infiltration fluxes throughout most of Earth's land surface, while infiltration cycles exceeding 1 year would yield transient recharge, except in more arid regions. Our results may help forecasting long‐term groundwater tables and could support improving groundwater resource management.
Optimizing Drought Assessment for Soil Moisture Deficits
Authors: Hoylman Zachary H. , Holden Zachary , Bocinsky R. Kyle , Ketchum David , Swanson Alan , Jencso Kelsey 
Published: June 2024

AbstractAccurate drought assessments are critical for mitigating the deleterious impacts of water scarcity on communities across the world. In many regions, deficits in soil moisture represent a key driver of drought conditions. However, relationships between soil moisture and widely used drought indicators have not been thoroughly evaluated. In addition, there has not been an in‐depth assessment of the accuracy of operational soil moisture models used for drought monitoring. Here, we used 2,405 observed time series of soil moisture from 637 long‐term monitoring stations across the conterminous United States to test the ability of meteorological drought indices and soil moisture models to accurately characterize soil moisture drought. The optimal timescales for meteorological drought indices varied substantially by depth, but were ∼30 days for depth averaged conditions; progressively longer timescales (∼10–80 days) represent progressively deeper soil moisture (2–36 in.). However, soil moisture models (including Short‐term Prediction Research and Transition Center, Soil Moisture Active Passive L4, and Topofire) significantly outperformed the meteorological drought indices for predicting standardized soil moisture anomalies and drought conditions. Additionally, soil moisture models represent near instantaneous conditions, implicitly aggregating antecedent data thereby eliminating the need for timescales, providing a more effective and convenient method for soil moisture drought monitoring. We conclude that soil moisture models provide a straightforward and favorable alternative to meteorological drought indices that better characterize soil moisture drought.
Effects of Freezing Temperature Parameterization on Simulated Sea‐Ice Thickness Validated by MOSAiC Observations
Authors: Gu Fengguan , Kauker Frank , Yang Qinghua , Han Bo , Fang Yongjie , Liu Changwei 
Published: June 2024

AbstractFreezing temperature parameterization significantly impacts the heat balance at sea‐ice bottom and, consequently, the simulated sea‐ice thickness. Here, the single‐column model ICEPACK was used to investigate the impact of the freezing temperature parameterization on the simulated sea‐ice thermodynamic growth during the MOSAiC expedition from October 2019 to September 2020. It is shown that large model errors exist with the standard parameterization and that different formulations for calculating the freezing temperature impact the simulated sea‐ice thickness significantly. Considering the winter mixed layer temperature, a modified parameterization of the freezing point temperature based on Mushy scheme was developed. The mean absolute error (ratio) of simulating sea‐ice thickness for all buoys reduces from 7.4 cm (4.9%) with the “Millero” scheme, which performs the best among the existing schemes in the ICEPACK model, to 4.2 cm (2.9%) with the new developed scheme.
Two Effective Degrees of Freedom Can Represent the Dominant Features of Global Rayleigh Wave Dispersion Maps
Authors: Zhang Han , Ni Sidao , Liu Lijun , Schmandt Brandon 
Published: June 2024

AbstractObjectively exploring global variations in crust and upper mantle structure helps constrain fundamental aspects of Earth's plate tectonic and convective processes. Here we adopted a Variational Auto‐Encoder to explore the degrees of freedom of global Rayleigh wave dispersion maps at 4–40 mHz. We found that two latent variables sufficiently represent the global variations, suggesting inherent coupling between crustal and mantle seismic properties. We propose that the two extracted latent variables mostly correspond with crustal thickness and upper mantle thermal structure. The first variable shows low values for continental mountain belts and ocean spreading ridges, contrasted by high values for abyssal plains. The second variable shows low values for most oceanic lithosphere and Phanerozoic continental areas, contrasted by high values for Archean cratons. Latent space correlations indicate that continental lithosphere has more strongly coupled depth features than beneath the oceans, which might be a consequence of its longevity.
Aerosol‐Cloud Interactions Near Cloud Base Deteriorating the Haze Pollution in East China
Authors: Qi Ximeng , Zhu Caijun , Chen Liangduo , Chi Xuguang , Wang Jiaping , Niu Guangdong , Lai Shiyi , Nie Wei , Zhu Yannian , Huang Xin , Kokkonen Tom V. , Petäjä Tuukka , Kerminen Veli‐Matti , Kulmala Markku , Ding Aijun 
Published: June 2024

AbstractAtmospheric aerosols not only cause severe haze pollution, but also affect climate through changes in cloud properties. However, during the haze pollution, aerosol‐cloud interactions are not well understood due to a lack of in situ observations. In this study, we conducted simultaneous observations of cloud droplet and particle number size distribution, together with supporting atmospheric parameters, from ground to cloud base in East China using a high‐payload tethered airship. We found that high concentrations of aerosols and cloud condensation nuclei were constrained below cloud, leading to the pronounced “Twomey effect” near the cloud base. The cloud inhibited the pollutants dispersion by reducing surface heat flux and thus deteriorated the near‐surface haze pollution. Satellite retrievals matched well with the in situ observations for low stratus clouds, while were insufficient to quantify aerosol‐cloud interactions for other cases. Our results highlight the importance to combine in situ vertical and satellite observations to quantify the aerosol‐cloud interactions.