bluuebunny/crossref_metadata_2025_split huggingface dataset:
QT interval in children with orthostatic dysregulation: Changes in standing load
Authors: Sakata Miho , Oyazato Yoshinobu , Nishiyama Atsushi 
Published: September 2024

AbstractBackgroundThe corrected QT interval (QTc) is affected by changes in autonomic sympathovagal modulation. The aim of this study was to determine whether children with orthostatic dysregulation (OD) have a longer QTc while standing than children without OD.MethodsWe retrospectively assessed patients who underwent the Schellong test and electrocardiography between November 2016 and November 2019. Patients who met the criteria of OD subtypes according to the Japanese clinical guidelines for juvenile OD (version 1) were classified as OD positive (the OD‐positive group), and patients who did not meet the criteria were classified as OD negative (the OD‐negative group).ResultsThere were 73 patients in the OD‐positive group and 52 patients in the OD‐negative group. Baseline heart rate, QT interval, and QTc were comparable between the OD‐positive and OD‐negative groups. Heart rate after standing was significantly higher in the OD‐positive group than in the OD‐negative group (median: 33 bpm vs. 21 bpm, p < 0.001). Further, shortening of QT interval after standing was greater in the OD‐positive group than in the OD‐negative group (median: 19 ms vs. 8 ms, p = 0.015). The QTc significantly increased from baseline to standing in both groups. Changes in the QT interval corrected by Bazett's formula were greater in the OD‐positive group than in the OD‐negative group (median: 73 ms vs. 42 ms, p < 0.001).ConclusionsThe QTc increased significantly from baseline to standing in the OD‐positive group. Thus, a high QTc while standing could be considered an auxiliary marker for OD diagnosis.
Auxin as a downstream signal positively participates in melatonin‐mediated chilling tolerance of cucumber
Authors: Yuan Xinru , Li Junqi , Zhang Xiaowei , Ai Xizhen , Bi Huangai 
Published: September 2024

AbstractHere, we elucidate the interaction between IAA and melatonin (MT) in response to chilling in cucumber. The results showed that chilling stress induced the increase of endogenous MT and IAA, and the application of MT promoted the synthesis of IAA, while IAA could not affect endogenous MT content under chilling stress. Moreover, MT and IAA application both remarkably increased the chilling tolerance of cucumber seedlings in terms of lower contents of MDA and ROS, higher mRNA abundance of cold response genes, net photosynthetic rate (Pn), maximum regeneration rate of ribulose‐1,5‐diphosphate (Jmax), Rubisco maximum carboxylation efficiency (Vcmax), the activities and gene expression of RCA and Rubisco, as well as the content of active P700 (I/I0) and photosynthetic electron transport, compared with the plants in H2O treatment. Further analysis revealed that the inhibition of IAA transportation significantly reduced the chilling tolerance induced by MT, whereas the inhibition of endogenous MT did not affect the chilling tolerance induced by IAA. Meanwhile, we found that overexpression of the MT biosynthesis gene CsASMT increased the chilling tolerance, which was blocked by inhibition of endogenous IAA, and the silence of IAA biosynthesis gene CsYUCCA10 decreased the chilling tolerance of cucumber, which could not be alleviated by MT. These data implied IAA acted as a downstream signal to participate in the MT‐induced chilling tolerance of cucumber seedlings. The study has implications for the production of greenhouse cucumber in winter seasons.
Transcriptomics Combined with Physiology and Metabolomics Reveals the Mechanism of Tolerance to Lead Toxicity in Maize Seedling
Authors: Zhang Xiaoxiang , Li Min , Ma Xingye , Jin Xining , Wu Xiangyuan , Zhang Huaisheng , Guan Zhongrong , Fu Zhiyuan , Chen Shilin , Wang Pingxi 
Published: September 2024

AbstractLead (Pb) exposure can induce molecular changes in plants, disrupt metabolites, and impact plant growth. Therefore, it is essential to comprehend the molecular mechanisms involved in Pb tolerance in plants to evaluate the long‐term environmental consequences of Pb exposure. This research focused on maize as the test subject to study variations in biomass, root traits, genes, and metabolites under hydroponic conditions under Pb conditions. The findings indicate that high Pb stress significantly disrupts plant growth and development, leading to a reduction in catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD) activities by 17.12, 5.78, and 19.38%, respectively. Conversely, Pb stress led to increase malondialdehyde (MDA) contents, ultimately impacting the growth of maize. The non‐targeted metabolomics analysis identified 393 metabolites categorized into 12 groups, primarily consisting of organic acids and derivatives, organ heterocyclic compounds, lipids and lipid‐like molecules and benzenoids. Further analysis indicated that Pb stress induced an accumulation of 174 metabolites mainly enriched in seven metabolic pathways, for example phenylpropanoid biosynthesis and flavonoid biosynthesis. Transcriptome analysis revealed 1933 shared differentially expressed genes (DEGs), with 1356 upregulated and 577 downregulated genes across all Pb treatments. Additionally, an integrated analysis identified several DEGs and differentially accumulated metabolites (DAMs), including peroxidase, alpha‐trehalose, and D‐glucose 6‐phosphate, which were linked to cell wall biosynthesis. These findings imply the significance of this pathway in Pb detoxification. This comprehensive investigation, employing multiple methodologies, provides a detailed molecular‐level insight into maize's response to Pb stress.
Standards‐based evaluation inform ecological restoration outcomes for a major mining activity in a global biodiversity hotspot
Authors: Campbell Tristan , Dixon Kingsley W. , Bradshaw Sidney D. , Gann George D. , Hartley William , Lambers Hans , Wardell‐Johnson Grant 
Published: September 2024

The International Principles and Standards for the Ecological Restoration and Recovery of Mine Sites were used to assess the restoration quality of one of the world's largest mines, located in the world's most biodiverse temperate forest. Quantitative analysis of longitudinal data spanning 35 years scored restoration quality at 2‐stars against a 5‐star forest ecosystem restoration target, with little indication of improvements from adaptive management. Two‐thirds of indicator plants were significantly under‐represented in early‐stage restoration and declined with age. Most plant species were effectively absent, including key structural species. Invasive plants and native legumes were persistently overabundant. Time required for the maturation of tree species will prevent the production of fundamental ecosystem features for well over a century (e.g. hollows and fallen logs), inhibiting functional fauna return (reptiles, bats, and conservation priority cockatoos in particular). The significantly different outcome compared with previous assessments is due to the age of restoration assessed and previous assumptions that early‐stage success indicate that restoration is on the correct, prolonged trajectory toward full ecological restoration. However, previous assessment methods did not consider many key metrics of the standards, nor accurately predict future restoration trajectory. In particluar, initial plant species richness (the only measure of biodiversity in the company's restoration completion criteria) did not reflect future restoration quality. These substandard restoration outcomes may result from removing the deep, multi‐layered bauxitic substrate on which the ecosystem evolved and establishing restoration on shallow topsoil over a more homogenized, impervious substrate. This study demonstrates the value of a robust, adaptable multi‐factor framework and methodology to evaluate restoration outcomes.
Risk early warning for unmanned aerial vehicle operators’ unsafe acts: A prediction model using Human Factors Analysis and Classification System and random forest
Authors: Xiao Qin , Li Yapeng , Luo Fan 
Published: September 2024

AbstractThe prediction of unmanned aerial vehicle (UAV) operators’ unsafe acts is critical for preventing UAV incidents. However, there is a lack of research specifically focusing on UAV operators’ unsafe acts, and existing approaches in related areas often lack precision and effectiveness. To address this, we propose a hybrid approach that combines the Human Factors Analysis and Classification System (HFACS) with random forest (RF) to predict and warn against UAV operators’ unsafe acts. Initially, we introduce an improved HFACS framework to identify risk factors influencing the unsafe acts. Subsequently, we utilize the adaptive synthetic sampling algorithm (ADASYN) to rectify the imbalance in the dataset. The RF model is then used to construct a risk prediction and early warning model, as well as to identify critical risk factors associated with the unsafe acts. The results obtained through the improved HFACS framework reveal 33 risk factors, encompassing environmental influences, industry influences, unsafe supervision, and operators’ states, contributing to the unsafe acts. The RF model demonstrates a significant improvement in prediction performance after applying ADASYN. The critical risk factors associated with the unsafe acts are identified as weak safety awareness, allowing unauthorized flight activities, lack of legal awareness, lack of supervision system, and obstacles. The findings of this study can assist policymakers in formulating effective measures to mitigate incidents resulting from UAV operators’ unsafe acts.
Comparative analysis of forecasting models in the nonlife insurance: Insights from the SARIMA and ETS approaches
Authors: Peovski Filip , Ivanovski Igor 
Published: September 2024

AbstractTo ensure competitiveness and sustainability, insurance companies need accurate predictions. The paper analyzes nonlife insurance gross written premiums, technical premiums, claims, and the number of contracts through a multi‐model univariate approach comparing Seasonal Autoregressive Integrated Moving Average (SARIMA) with Exponential Smoothing models. The hypothesis suggests that SARIMA's superior handling of complex seasonal patterns enhances predictive accuracy. Data from 2012M01 to 2023M06 provides a comprehensive sector‐wide view, essential for decision‐making. The results show that SARIMA models outperform exponential smoothing in almost all major accuracy metrics over the training period. Over the test period, the exponential smoothing models show more accurate performances. However, the optimal exponential smoothing models fail in mitigating autocorrelation and non‐normality in residuals, which is successfully tackled by the weighted ensemble models. In all cases except for the number of contracts concluded, the rolling one‐step ahead forecast approach generates superior accuracy over the classic training‐test split. This research confirms that using SARIMA, exponential smoothing, weighted ensemble, and rolling window models can significantly improve forecasting accuracy and are better solutions than the seasonal naive benchmark. It provides important insights into insurance forecasting and risk management, which are often overlooked in existing literature, and can greatly benefit corporate governance and policymaking.
Model‐assisted analysis of covariance estimators for stepped wedge cluster randomized experiments
Authors: Chen Xinyuan , Li Fan 
Published: September 2024

AbstractStepped wedge cluster randomized experiments (SW‐CREs) represent a class of unidirectional crossover designs. Although SW‐CREs have become popular, definitions of estimands and robust methods to target estimands under the potential outcomes framework remain insufficient. To address this gap, we describe a class of estimands that explicitly acknowledge the multilevel data structure in SW‐CREs and highlight three typical members of the estimand class that are interpretable. We then introduce four analysis of covariance (ANCOVA) working models to achieve estimand‐aligned analyses with covariate adjustment. Each ANCOVA estimator is model‐assisted, as its point estimator is consistent even when the working model is misspecified. Under the stepped wedge randomization scheme, we establish the finite population Central Limit Theorem for each estimator. We study the finite‐sample operating characteristics of the ANCOVA estimators in simulations and illustrate their application by analyzing the Washington State Expedited Partner Therapy study.
Choosing who to hate? The Extreme and Radical Right's Foreign Policy between Anti‐Semitism, Islamophobia, and Russophilia
Authors: Wondreys Jakub , Zulianello Mattia 
Published: September 2024

AbstractAlthough extensive research has been conducted on the extreme right (ER) and radical right (RR), their foreign policy remains understudied. Hence, we provide a comparative analysis of 42 ER and RR parties in Europe to identify their stances on two key issues of contemporary international politics: the Israeli‐Palestinian and the Russia‐Ukraine conflicts. The results suggest that ER and RR parties do not choose who to like but who to hate more: either Israel (Jews) or Palestine (Muslims); either Russia or the West (and Ukraine as its proxy). However, ER and RR parties are substantially different in their positions towards both conflicts, and a stance in one conflict corresponds to a specific position in the other: the ER tends to be supportive of Palestine and Russia, while the RR supportive of Israel and Ukraine. We argue that these profound differences are due to a combination of ideological and competitive incentives.
Differential contributions of double‐strand break repair pathways to DNA rearrangements following the irradiation of Arabidopsis seeds and seedlings with ion beams
Authors: Kitamura Satoshi , Satoh Katsuya , Hase Yoshihiro , Yoshihara Ryouhei , Oono Yutaka , Shikazono Naoya 
Published: September 2024

SUMMARYDNA rearrangements, including inversions, translocations, and large insertions/deletions (indels), are crucial for crop evolution, domestication, and improvement. The rearrangements are frequently induced by ion beams via the mis‐repair of DNA double‐strand breaks (DSBs). Unfortunately, how ion beam‐induced DSBs are repaired has not been comprehensively analyzed and the mechanisms underlying DNA rearrangements remain unclear. In this study, clonal sectors originating from single mutated cells in carbon ion‐irradiated plants were used for whole‐genome sequencing analyses after Arabidopsis seeds and seedlings were irradiated. Comparative analyses of the induced mutations (e.g., size and frequency of indels and microhomology at the junctions of the rearrangements) in the irradiated materials suggested that the broken/rejoined DSB ends were more extensively processed in seedlings than in seeds. A mutation to canonical non‐homologous end‐joining (c‐NHEJ), which is a DSB repair pathway with minimal processing of DSB ends, increased the sensitivity to ion beams more in the seeds than in the seedlings, which was consistent with the junction analysis results, indicative of the minor contribution of c‐NHEJ to the carbon ion‐induced DSB repair in seedlings. Considering the characteristics of the large templated insertions in irradiated seedlings, ion‐beam‐induced DSBs in seedlings are likely repaired primarily by a polymerase theta‐mediated pathway. Polymerase theta‐deficient seedlings were more sensitive to ion beams than the c‐NHEJ‐deficient seedlings, consistent with this hypothesis. This study revealed the key characteristics of ion beam‐induced DSBs and the associated repair mechanisms related to the physiological status of the irradiated materials, with implications for elucidating the occurrence and induction of rearrangements.
Linkage and translation for tensor products of representations of simple algebraic groups and quantum groups
Authors: Gruber Jonathan 
Published: September 2024

AbstractLet be either a simple linear algebraic group over an algebraically closed field of characteristic or a quantum group at an ‐th root of unity. We define a tensor ideal of singular ‐modules in the category of finite‐dimensional ‐modules and study the associated quotient category , called the regular quotient. For , the Coxeter number of , we establish a ‘linkage principle’ and a ‘translation principle’ for tensor products: Let be the essential image in of the principal block of . We first show that is closed under tensor products in . Then we prove that the monoidal structure of is governed to a large extent by the monoidal structure of . These results can be combined to give an external tensor product decomposition , where denotes the Verlinde category of .
Numerical Simulation and Experimental Research on the Effect of Flow Regimes for Refrigeration Performance of Wave Rotor
Authors: Ma Jian-wei , Wang Yan-qiang , Zhou Zi-qi , Liu Zhi-chao , Sun Yu-wen 
Published: September 2024

Abstract
Wave rotors exchange energy through the interaction of fluids with different pressures to produce a cooling effect without the application of mechanical parts, which makes them suitable for the complex flow field environments. But the flow situation inside the wave rotor is complex, and research on the impact of various flow regimes for the refrigeration efficiency is currently incomplete. This study deals with the numerical simulation and the experimental verification of a four-port fixed rotor gas wave refrigerator. Various typical flow regimes within the wave rotor were obtained through simulation to analyze their impact on the refrigeration efficiency. To further demonstrate the effectiveness of the simulation results, experimental verification was conducted. The simulation results indicate that separation bubbles and vortices will be respectively generated on the upper and lower walls of the wave rotor tube during the gradual opening stage. Vortex affects the airflow flow and causes detachment of separation bubbles as the airflow moves, which results in the loss of pressure energy and kinetic energy of the incident gas. As a result, the loss caused by the gradual opening process leads to a decrease in the self-expansion ability of high-pressure gas during the gradual closing stage, thereby affecting the refrigeration effect. Therefore, reducing the influence of vortices plays an important role in improving the cooling efficiency of wave rotors. Finally, this study analyzes the main factors that affect the cooling effect within the wave rotor through flow regime and provides new insights for improving refrigeration efficiency.
Experimental and Numerical Investigation for Optimization of a Hybrid Battery Thermal Management System Based on Phase Change Material and Air Convection
Authors: Swamy Kundrapu Ayyappa , Verma Saket 
Published: September 2024

Abstract
This work presents the design and optimization of a phase change material (PCM)-based hybrid battery thermal management system (HBTMS). In the first stage, experiments are performed to measure the battery cell temperatures under various charge rates with and without the usage of PCM. Thereafter, a numerical model is developed to conduct a parametric study on the effect of the thickness of PCM layer around the battery cell. The results show that with the PCM thicknesses of 6–12 mm, the maximum cell temperature (36.35 °C) and thermal nonuniformity are within the safe range. In the second stage, a parametric study is conducted in the 6S1P battery module to optimize the spacing between the cells at constant inlet velocity. The result shows that an increase in cell spacing decreases the maximum temperature within the cells. The maximum temperature is within the optimal range when the cell spacing is 10 mm. At the constant cell spacing of 10 mm, an increase in inlet velocities from 0.25 m/s to 2.5 m/s gradually improves the thermal uniformity. The maximum temperature and thermal nonuniformity for the 6S1P battery module are found to be 42.07 °C and 1.17 °C respectively. In the third stage, the 6S1P battery module is optimized for PCM thickness, cell spacing, and inlet air velocity. It is found that effective thermal management is possible with PCM-based HBTMS at a low airflow rate of up to 1.5 m/s. The optimized PCM-based HBTMS shows 53.95% and 40% reductions in PCM mass and air flowrate, respectively.
Prediction and optimization of wet bulb efficiency in solar energy-based novel evaporative cooling system: Response Surface Method Approach
Authors: Tripathi Ram Ji , Kumar Devesh 
Published: September 2024

Abstract
The wet bulb efficiency is an essential parameter in performance of Indirect evaporative cooling systems, as it impacts efficiently cool air while minimizing energy usage. This paper focuses on model and optimize multi tubular type wet channel for indirect evaporative cooler system. The optimized wet bulb efficiency based on Box-Behnken experimental design model and response surface method. The methodology included predicting and optimizing input process and working flow parameters of indirect evaporative cooling system to maximize wet bulb efficiency. A quadratic model of response surface method was used to evaluate influence of each factor on wet bulb efficiency, which was validated through analysis of variance results. The study found a maximum WBE of 89.65% under specific conditions, with a relative error of 3.25% between predicted and experimental result. This optimization process, governed by RSM, determined essential parameters for enhancing efficiency of system. These parameters include inlet process temperature of 28°C, working air velocity of 3.5 m/s, relative humidity of 45%, and inlet working air temperature of 24°C. These results demonstrate practical significance of current research, providing useful insights for optimal design and optimization of indirect evaporative cooling systems to fulfil cooling requirements while minimising energy consumption.
Assessment of Additive Manufactured Micro-Channel Characteristics: Impact of Hydraulic Diameter Evaluation
Authors: Bacci Tommaso , Picchi Alessio , Castelli Niccolò , Facchini Bruno , Morante Francesco , Innocenti Luca 
Published: September 2024

Abstract
Among internal cooling techniques for gas turbines components, skin cooling is recognized as one of the most promising, especially thanks to the spread of additive manufacturing techniques. In this regard, several studies have tried to characterize heat transfer and pressure loss performance of additive manufactured micro-channels, as well as the impact of AM characteristic parameters, mainly in the form of building angle, and resulting surface roughness and channel shape. The open literature offers several correlations in terms of friction and heat transfer coefficient using a representative hydraulic diameter. Despite that, little attention is given on the importance of such characteristic length definition which may lead to under/over estimation of the cooling rates when correlations are used in the design In this work, coupons featuring circular micro-channelswith diameters of 0.5 and 1 mm and different building angles have been tested, to retrieve pressure losses and an average heat transfer coefficient through a lumped approach. The coupons were additive manufactured using the Laser Powder Bed Fusion (L-PBF) technique. Exploiting the experimental survey, the impact of the considered hydraulic diameter was investigated, by comparing different approaches based on a direct measurement. An additional and new approach, aimed at the identification of an “effective” diameter, based on fluid-dynamic considerations, was also considered. The data correlation and the comparison with available correlations from different authors showed the newly proposed approach to provide superior scaling capabilities and, in turn, allowing for the development of more accurate prediction methods