bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating the applicability of ivabradine in acute heart failure
Authors: Tsai Tzu‐Hsien , Tsai Ming‐Lung , Chen Dong‐Yi , Lin Yuan , Peng Jian‐Rong , Yang Ning‐I , Hung Ming‐Jui , Chen Tien‐Hsing 
Published: December 2023

AbstractBackgroundWhile ivabradine has demonstrated benefits in heart rate control and prognosis for chronic heart failure patients, its application in acute decompensated heart failure remains underexplored.HypothesisFor patients with acute decompensated heart failure with reduced ejection fraction (HFrEF) who are intolerant to β‐blockers or unable to further titrate their dosage, the use of ivabradine is hypothesized to be effective and safe is improving outcomes.MethodsThis retrospective, multicenter database analysis included patients with hospitalized decompensated heart failure with a left ventricular ejection fraction of ≤40% from June 1, 2015 to December 31, 2020. The exclusion criteria were a baseline heart rate of <70 bpm, previous use of ivabradine, mortality during admission, existing atrial fibrillation, or atrial flutter. The primary outcome was the composite of cardiovascular death and hospitalization for heart failure.ResultsOf the 4163 HFrEF patients analyzed, 684 (16.4%) were administered ivabradine during their index admission. After matching, there were 617 patients in either group. The results indicated that ivabradine use was not significantly associated with the risk of the primary composite outcome (hazard ratio: 1.10; 95% confidence interval: 0.94−1.29). Similarly, the risk of secondary outcomes and adverse renal events did not significantly differ between the ivabradine and non‐ivabradine cohorts (all p > .05).ConclusionFor hospitalized acute decompensated heart failure patients who are intolerant to β‐blockers or cannot further titrate them, ivabradine offers a consistent therapeutic effect. No significant disparities were noted between the ivabradine and non‐ivabradine groups in heart failure hospitalization and cardiovascular death.
Design of novel deformable mirror with large displacement
Authors: Li Jinchao , Tian Yuxuan , Wang Jindong , Yang Jinling , Zhu Yinfang , Cheng Xuemin , Hao Qun 
Published: December 2023

SummaryA stabilized zoom system with deformable mirrors (DMs) was designed for continuous optical zoom. In order to adjust the focal length and expand the field angle, the characteristic surface shapes of the DMs composed of the low‐order and high‐order Zernike polynomials were provided. The maximum peak‐to‐valley (PV) value at the center of the surface shape is 80 μm. This work presents a piezoelectrically‐actuated deformable mirror (PADM) with large displacement for a stabilized zoom system. The COMSOL simulation was conducted to obtain the desired design by matching and optimizing structural parameters. The maximum displacement of PADM was more than 80 μm. The fitting results by the steepest descent algorithm (SD) showed that the RMS values of the residual surface shapes were 1 of 7 to 1 of 4 of their PV values, and the PV values of the residual surface shapes were less than 1 of 10 of the PV values of the target surface shapes.
A feed forward deep neural network model using feature selection for cloud intrusion detection system
Authors: Sharma Hidangmayum Satyajeet , Singh Khundrakpam Johnson 
Published: December 2023

SummaryThe rapid advancement and growth of technology have rendered cloud computing services indispensable to our activities. Threats and intrusions have since multiplied exponentially across a range of industries. In such a scenario, the intrusion detection system, or simply the IDS, is deployed on the network to monitor and detect any attacks. The paper proposes a feed‐forward deep neural network (FFDNN) method based on deep learning methodology using a filter‐based feature selection model. The feature selection strategy aims to determine and select the most highly relevant subset of attributes from the feature importance score for training the deep learning model. Three benchmark data sets were used to assess the experiment: CIC‐IDS 2017, UNSW‐NB15, and NSL‐KDD. In order to justify the proposed technique, a comparison was done using other learning algorithms ranging from classical machine learning to ensemble learning methods that can detect various attacks. The experiments showed that the FFDNN model with reduced feature subsets gave the highest accuracy of 99.53% and 94.45% in the NSL‐KDD and UNSW‐NB15 data sets, while the ensemble‐based XGBoost model performed better in the CIC‐IDS 2017 data set. In addition, the results show that the overall accuracy, recall, and F1 score of the deep learning algorithm are generally better for all the data sets.
Influence of green human resource management on employee green behavior: The sequential mediating effect of perceived behavioral control and attitude toward corporate environmental policy
Authors: Fawehinmi Olawole , Yusliza Mohd Yusoff , Tanveer Muhammad Imran , Abdullahi Mohammed Sani 
Published: December 2023

AbstractThe current existential global threat brought about by excessive carbon emissions caused by employee activity in the workplace calls for actions of corporate environmental policy. Thus, this study investigated the sequential mediating effects of perceived behavioral control (PBC) and attitude between green human resource management (GHRM) and employee green behavior (EGB) on the basis of ability–motivation–opportunity (AMO) theory and the theory of planned behavior (TPB). Data were purposely collected using a quantitative approach from a cross‐sectional study of 425 lecturers in Malaysian public universities. Smart PLS‐SEM was utilized to investigate the relationship between variables. Findings confirmed the relationship between GHRM and PBC. Furthermore, results demonstrated a strong positive relationship between PBC and both attitude and EGB. In addition, the link between attitude and EGB was found to be significantly related. However, no significant relationship was found between GHRM and both employee attitude and EGB. For the mediating effect, findings showed that PBC significantly mediates the link between GHRM and EGB and the relationship between GHRM and attitude. Further, the sequential mediating effect of PBC and attitude between GHRM and EGB was supported. Results also shed some light on the importance of the underlying mechanism of employees' PBC and attitude between GHRM and EGB, thereby providing implications regarding the role of AMO theory on TPB. Future directions are also discussed.
The role of fathers in child development from preconception to postnatal influences: Opportunities for the National Institutes of Health Environmental influences on Child Health Outcomes (ECHO) program
Authors: Jansen Elena , Marceau Kristine , Sellers Ruth , Chen Tong , Garfield Craig F. , Leve Leslie D. , Neiderhiser Jenae M. , Spotts Erica L. , Roary Mary ,   program collaborators for Environmental influences on Child Health Outcomes
Published: December 2023

AbstractA growing body of literature highlights the important role of paternal health and socioemotional characteristics in child development, from preconception through adolescence. Much of this research addresses the indirect effects of fathers, for instance, their influence on maternal behaviors during the prenatal period or via the relationship with their partner. However, emerging evidence also recognizes the direct role of paternal health and behavior for child health and adjustment across development. This critical review presents evidence of biological and sociocultural influences of fathers on preconception, prenatal, and postnatal contributions to child development. The National Institutes of Health Environmental influences on Child Health Outcomes (ECHO) program incorporates in its central conceptualization the impact of fathers on family and child outcomes. This critical synthesis of the literature focuses on three specific child outcomes in the ECHO program: health outcomes (e.g., obesity), neurodevelopmental outcomes (e.g., emotional, behavioral, psychopathological development), and positive health. We highlight the unique insights gained from the literature to date and provide next steps for future studies on paternal influences.
Some Improvements on Wettability and Internal Resistance of Modified Micro‐porous Layer for Direct Methanol Fuel Cell
Authors: Zhao Zhengang , Jin Dian , Zhang Dacheng 
Published: December 2023

Micro‐porous layer (MPL) is an essential component of the membrane electrode assembly in a direct methanol fuel cell (DMFC). It enables proton transport and maintains the stability of gas diffusion layers. The wettability and internal resistance of MPL directly affect the cell output power density. Herein, a hydrophilic MPL is developed on the anode side of DMFC by depositing Ag‐modified carbon nano‐fiber powder (CNFP). The modification improves the diffusion of methanol–water solution into the anode catalytic layer, leading to an increased catalytic reaction rate and output power density. Moreover, thanks to the lower electrical resistance of CNFP/Ag, the cell's charge transfer and mass transfer resistances can be reduced, which leverage the power densities at different concentrations. The experimental results show that the peak power density of the modified MPL is increased by 42.2% from to . The charge transfer resistance is reduced by 34.8% from to and a reduction of 43.1% from to for the mass transfer resistance.
Study of electric and hybrid vehicles in the form of alternative transport in Kazakhstan
Authors: Arystanov Zhanat , Togizbayeva Baglan , Kenesbek Anuar , Mambetov Dulat , Kinzhebayeva Aizhan 
Published: December 2023

AbstractThe global energy crisis and the conditions it has created are becoming important factors for the development of energy efficiency. The aim of the research is to study electric vehicles, as well as hybrid cars as alternative fuels in Kazakhstan and in the world. A wide range of methodological tools was used to conduct the research, in particular, the method of analysis and generalization of information, comparative, as well as induction and deduction. In addition, the method of analysis of scientific literature was applied, which partially reveals the problematic issues of this topic. A review of the literature concluded that alternative and transitional fuels were the most popular among transport users in the city. The information analyzed from the literature also allows concluding that in recent years some studies have presented new scientific, technical and political strategies to improve the use of alternative and transitional fuel resources. The practical value of the research is the possibility to use its results to study and analyze information on electric and hybrid vehicles. The information provided in the study could form the basis for the study of alternative fuels for cars.
Coal pillar destabilization prediction and mining method in residual mining areas under remining disturbances
Authors: Wen Guang , Gong Peilin , Zhu Yanhui , Yi Kang , Li Peng , Kang Hui , Tian Ye 
Published: December 2023

AbstractTo address the problem of pillar instability in residual mining areas under repeated mining disturbances, the prediction of pillar instability time and mining technology is studied by using numerical simulations, theoretical examinations, and practical experimentation techniques utilizing the remaining facade of the Shenghua Coal Industry 3103. On the basis of the findings, employing a fully mechanized mining technique exerts greater pressure on the coal pillar, increasing the likelihood of plastic failure. However, adopting the segmental filling mining approach can effectively disperse this pressure, consequently mitigating potential damage to the coal pillar. Initially, the coal pillar undergoes a progressive yielding or collapsing process at its periphery, leading to instability once the area of the projectile core of the coal pillar decreases beyond a specific threshold. The dimensions of both the affected roadway and the coal pillar play a pivotal role in determining the coal pillar's load‐bearing capacity. A prediction model for pillar instability is established. If the area of the projectile core is less than 34% during remining, the mining method should be changed or pillar reinforcement should be implemented. The accurate prediction and adaptation of the model's mining approach ensure the secure extraction of coal pillars within the remaining mining region, with successful validation of the model's performance.
Research on how acidification affects the coal's microscopic pore structure in the Guizhou mining region
Authors: He Yuhuan , Li Xijian , Xue Feng , Sui Hao , Xie Honggao , Xu Chao , Li Xianxian 
Published: December 2023

AbstractBy eliminating their minerals, acidification technology makes coal seams more permeable. Acidification technology were conducted in the Farr and Qinglong mining areas using a mixed acid solution to study the impact of acidification technology on increasing the permeability of primary structural coals in the Guizhou region, China. The microphysical and chemical structure of the coal samples before and after acidification transformation was compared using X‐ray diffraction, scanning electron microscope, mercury intrusion porosimetry, and Fourier transform infrared spectrometry experiments. The results show that after acidification, the volatile matter content is reduced by 4.2% and 16.25%, the carbon content is increased, the degree of coalification is deepened, the gas content of the coal seam is elevated, and the gas source is more abundant. The minerals on the surface are dissolved to different degrees, and the pores and cracks are dredged, so that the surface of the coal samples shows better connectivity, which is conducive to the diffusion and transport of coalbed methane. The volume and pore diameter of the macropore and mesopore in the Farr coal samples were improved after acidification, and the fractal structure was more prominent, the pore connectivity was good, and the pore diameter of the Qinglong coal samples was greatly increased. The content of oxygen‐containing functional groups increased by 11.2% and 2.1%, respectively, which is conducive to the desorption of coalbed methane after acidification, and with the increasing degree of metamorphism of the coal samples, the higher the content of oxygen‐containing functional groups was and the less pronounced the effect of acidification. Acidification technology can effectively remove the minerals in the coal body and has a good effect on penetration enhancement, and the results of the study can provide certain theoretical references for the penetration enhancement of coal seams in Guizhou mining areas.
Automated detecting, segmenting and measuring of grains in images of fluvial sediments: The potential for large and precise data from specialist deep learning models and transfer learning
Authors: Mair David , Witz Guillaume , Do Prado Ariel Henrique , Garefalakis Philippos , Schlunegger Fritz 
Published: December 2023

AbstractThe size of sedimentary particles in rivers bears information on the sediment entrainment or deposition mechanisms and the hydraulic conditions controlling them. However, collecting such data from coarse‐grained sediments is work intensive, both in the field and remotely. Therefore, attention has turned to machine learning models to improve the data acquisition. Despite their success, current methods need large quantities of data and yield results limited to a few percentile values of grain size datasets, often additionally affected by a systematic bias. In most cases, the root of these limitations is the challenge of accurately segmenting grains. Here, we present a new approach to improve the segmentation of individual grains based on the capacity of transfer learning in convolutional neural networks. Specifically, we re‐train a state‐of‐the‐art model for cell segmentation in biomedical images to find and segment coarse‐grained particles in images of fluvial sediments. Our results show that the performance in the segmentation tasks can be directly transferred to images of fluvial sediments and that our re‐trained models outperform existing methods. We document that our results are achievable with only 10%–20% of the data needed for training other deep learning models designed to measure the size of fluvial sediments. Moreover, we find that traits in our data control the segmentation performance. This enables data‐driven approaches to create specialist segmentation models. Additionally, comparing our automatically obtained datasets with the results retrieved from image and field‐based surveys confirms that improvements in segmentation are directly leading to more precise and more accurate grain size data even if data collection occurs in images taken at different conditions. Finally, we release a software package, the trained models and our data. The goal is to offer a tool to efficiently segment and measure grains in sediment images in an automated way, which can be adapted to different settings.
Effect of fenugreek and flaxseed polysaccharide‐based edible coatings on the quality attributes and shelf life of apple fruit during storage
Authors: Rashid Farhat , Ahmed Zaheer , Ferheen Ifra , Mehmood Tahir , Liaqat Saba , Ghoneim Mohammed M. , Rahman Afzal 
Published: December 2023

AbstractThe present study was designed to explore the potential of fenugreek and flaxseed polysaccharide‐based edible coatings to enhance the postharvest storage life of apple fruit. The experimental plan involved the preparation of five different coating formulations, which were subsequently applied to the fruit. The coated fruit was then stored at a temperature of 25 ± 2°C for a duration of 35 days. The effects of these coatings on physicochemical and biochemical attributes (weight loss, firmness, acidity, pH, sugar content, antioxidant activity, microbial growth, and sensory properties) of coated and uncoated samples were evaluated at regular intervals: 0, 7, 14, 21, 28, and 35 days of storage. The experimental results revealed a significant difference (p ≤ .05) in the physicochemical parameters of uncoated and coated apple at different storage times. The coated apple fruits showed significantly (p ≤ .05) lower weight loss, pH, total sugars, total soluble solids, and maximum retention of ascorbic acid, firmness, acidity, and antioxidant contents, leading to enhanced organoleptic properties. The application of edible coatings extended the shelf‐life of the apples by inhibiting microbiological spoilage without substantial impact on sensory and nutritional properties. Based on these results, it is concluded that the edible coating formulation labeled T1 (containing 2.5 g fenugreek polysaccharide and 1.5 g flax polysaccharide) effectively preserved the valuable physicochemical and organoleptic characteristics of the apple fruit throughout the storage period.
Financial incentives and prescribing behavior in primary care
Authors: Bodnar Olivia , Gravelle Hugh , Gutacker Nils , Herr Annika 
Published: December 2023

AbstractMany healthcare systems prohibit primary care physicians from dispensing the drugs they prescribe due to concerns that this encourages excessive, ineffective or unnecessarily costly prescribing. Using data from the English National Health Service for 2011–2018, we estimate the impact of physician dispensing rights on prescribing behavior at the extensive margin (comparing practices that dispense and those that do not) and the intensive margin (comparing practices with different proportions of patients to whom they dispense). We control for practices selecting into dispensing based on observable (OLS, entropy balancing) and unobservable practice characteristics (2SLS). We find that physician dispensing increases drug costs per patient by 3.1%, due to more, and more expensive, drugs being prescribed. Reimbursement is partly based on a fixed fee per package dispensed and we find that dispensing practices prescribe smaller packages. As the proportion of the practice population for whom they can dispense increases, dispensing practices behave more like non‐dispensing practices.
Short‐term dynamics of drainage density based on a combination of channel flow state surveys and water level measurements
Authors: Bujak‐Ozga Izabela , van Meerveld H.J. (Ilja) , Rinaldo Andrea , von Freyberg Jana 
Published: December 2023

AbstractHeadwater streams often experience intermittent flow. Consequently, the flowing drainage network expands and contracts and the flowing drainage density (DD) varies over time. Monitoring the DD dynamics is essential to understand the processes controlling it. However, our knowledge of the event‐scale DD dynamics is limited because high spatial and temporal resolution data on the DD remain sparse. Therefore, our team monitored the DD dynamics and hydrologic variables in two 5‐ha headwater catchments in the Swiss pre‐Alps in the summer of 2021, through mapping surveys of the flow state and a wireless streamwater level sensor network. We combined the two data sources to calculate the DD at the event‐time scale. Our so‐called CEASE method assumes that flow in a channel reach occurs above a set of water level thresholds, and it determined the DDs with accuracies >94%. DD responses to events differed for the two catchments, despite their proximity and similar size. DD ranged from 2.7 to 32.2 km km−2 in the flatter catchment (average slope: 15°). For this catchment, the discharge‐DD relationship became steeper when DD exceeded 20 km km−2 and DD increased substantially with relatively small increases in discharge. For rainfall events during dry conditions, the discharge‐DD relationship showed counterclockwise hysteresis, likely due to initially high groundwater discharge from the area near the catchment outlet; once rainfall stopped, DD remained high during the streamflow recession due to rising groundwater levels throughout the catchment. For events during wet conditions, the discharge and DD responded synchronously. In the steeper catchment (average slope: 24°), the DD varied only from 7.8 to 14.6 km km−2 and there was no hysteresis or threshold behaviour in the discharge‐DD relationship, likely because multiple groundwater springs maintained streamflow throughout the network during the monitoring period. These results highlight the high variability in DD and its dynamics across small headwater catchments.