bluuebunny/crossref_metadata_2025_split huggingface dataset:
Organic Cathode Electrolyte Interphase Achieving 4.8 V LiCoO2
Authors: Weng Chaocang , Qiu Meijia , Wang Bingfang , Yang Jiaqi , Mai Wenjie , Pan Likun , Huang Sumei , Li Jinliang 
Published: December 2024

AbstractDeveloping high‐voltage electrolytes to stabilize LiCoO2 (LCO) cycling remains a challenge in lithium‐ion batteries. Constructing a high‐quality cathode electrolyte interphase (CEI) is essential to mitigate adverse reactions at high voltages. However, conventional inorganic CEIs dominated by LiF have shown limited performance for high‐voltage LCO. Here, we propose an ionic liquid electrolyte (ILE) with a high donor number additive, enabling Li//LCO cells to achieve a high cut‐off voltage of 4.7 V/4.8 V and a high‐capacity retention of 86.9 %/74.2 % after 100 cycles at 0.5 C. During this process, a groundbreaking phenomenon was discovered: the construction of a stable organic CEI rich in C−F bonds by the high donor number additive under high voltage. These strong polar C−F bonds exhibit excellent electrochemical inertness and film‐forming properties, resulting in optimal passivation of the cathode. This organic C−F bond‐dominated CEI significantly suppresses phase transitions, cobalt dissolution, and gas evolution in LCO at high voltage. Additionally, the 4.8 V‐class Li//LiNi0.6Co0.2Mn0.2O2 and 4.95 V‐class Li//LiNi0.5Mn1.5O4 cells also demonstrate outstanding cycling stability. Even at 60 °C, the ILE‐constructed organic CEI maintains superior performance. Our findings highlight the potential of organic CEI to enhance high‐voltage cathode stability, paving the way for more efficient lithium‐ion batteries.
Enhancing System Capacity Through Joint Space‐Ground Multi‐Beam Coordination for LEO Satellite Systems
Authors: Liu Yuyang , Shi Tong , Wang Hua 
Published: December 2024

ABSTRACTDue to the long transmission distance of the constellation network represented by the low‐orbit satellite system, the satellite‐to‐ground link is subject to large path loss and limited communication performance. This paper uses multi‐satellite and multi‐beam joint transmission technology to form a virtual multiplex network with ground multi‐antenna terminals (Multiple‐Input Multiple‐Output [MIMO] system). However, due to the high‐speed movement of satellites, the topology of the MIMO system is unstable, which in turn affects the stability of the system throughput. This article proposes two inter‐satellite cooperation modes to improve the stability of MIMO system capacity. The first method is to optimize the channel capacity by rationally allocating the beam power of the gateway station so that the gateway station can achieve transparent forwarding through satellites. The second method rotates the angle of the user's receiving antenna to combat channel changes caused by changes in satellite position. Simulation results show that both methods can effectively improve the minimum channel capacity. Transparent forwarding can increase the capacity by about 22.7%, while the rotating antenna can still improve the performance gain by at least 36.3% even with a limited rotation angle. This research contributes to the development of stable and efficient communication systems in satellite‐ground cooperative networks.
Evaluating Machine Unlearning: Applications, Approaches, and Accuracy
Authors: Ali Zulfiqar , Muhammad Asif , Adnan Rubina , Alkhalifah Tamim , Aslam Sheraz 
Published: December 2024

ABSTRACTMachine learning (ML) enables computers to learn from experience by identifying patterns and trends. Despite ML's advancements in extracting valuable data, there are instances necessitating the removal or deletion of certain data, as ML models can inadvertently memorize training data. In many cases, ML models may memorize sensitive or personal data, raising concerns about data privacy and security. Machine unlearning (MU) techniques offer a solution to these concerns by selectively removing sensitive data from trained models without significantly compromising their performance. Similarly, we can analyze and evaluate whether MU can successfully achieve the “right to be forgotten.” In this paper, we investigate various MU approaches regarding their accuracy and potential applications. Experiments have shown that the data‐driven approach emerged as the most efficient method in terms of both time and accuracy, achieving a high level of precision with a minimal number of training epochs. When fine‐tuning, the full test error rises somewhat to 14.57% from the baseline model's 14.28%. One approach shows a high forget error of 99.90% with a full test error of 20.68%, while retraining yields a 100% forget error and a test error of 21.37%. While error‐minimizing noise preserves performance, the SCRUB technique results in a 21.08% test error and an 81.05% forget error, in contrast to the degradation brought on by error‐maximizing noise. On the other hand, the agnostic approach displayed sluggishness and generated less accurate results compared to the data‐driven approach. Furthermore, the choice of approach may depend on the unique requirements of the task and the available training resources.
Prophylactic Effects of Astragalus Polysaccharides on Depression‐Like Behaviors in Rats With Chronic Unpredictable Mild Stress: A Role of Gut‐Microbiota–Brain Axis
Authors: Liu Xiaojie , Xu Wenlu , Zhao Ziyu , Wu Xiaoling , Wang Senyan , Jian Chen , Li Mengyu , Li Ke , Wang Yulan , Qin Xuemei 
Published: December 2024

ABSTRACTRadix Astragalus (RA) has been used in the treatment of depression. Astragalus polysaccharide (APS) is one of the effective components of RA. However, the antidepressant mechanism of APS is still unclear. This research utilized 16S rRNA analysis, microbial analysis, and metabolomics analysis to elucidate the antidepressant mechanism of APS at both micro and macro levels. Correlation analysis was performed on the perspective of “behavioral indicators‐intestinal bacteria‐immune factors‐differential metabolites” to show the relationships among various indicators. The results showed that APS could significantly regulate the depressive behaviors of depressed rats, alleviate the imbalance of Th17/Treg, increase the expression level of anti‐inflammatory factor IL‐10, while reduce the expression level of pro‐inflammatory factor IL‐22. APS significantly reduced the expression levels of lysine, alanine, and arginine of depressed rats, as well as the abundance of Aerococcus. Lysine and arginine were the most closely related to behaviors, immune factors, and gut bacteria. The current findings revealed the antidepressant mechanism of APS from the perspective of the “gut microbiome–immunity–metabolome” axis. This study provides a new strategy for proving the antidepressant effects of plant polysaccharides and lays a solid foundation for the discovery of new drugs from botanical drugs and the improvement of patients' quality of life.
Step by Step—A Quarterly Evaluation of EU Commission's GDP Forecasts
Authors: Heinisch Katja 
Published: December 2024

ABSTRACTThe European Commission's growth forecasts play a crucial role in shaping policies and provide a benchmark for many (national) forecasters. The annual forecasts are built on quarterly estimates, which do not receive much attention and are hardly known. Therefore, this paper provides a comprehensive analysis of multiperiod ahead quarterly GDP growth forecasts for the European Union (EU), euro area, and several EU member states with respect to first‐release and current‐release data. Forecast revisions and forecast errors are analyzed, and the results show that the forecasts are not systematically biased. However, GDP forecasts for several member states tend to be overestimated at short‐time horizons. Furthermore, the final forecast revision in the current quarter is generally downward biased for almost all countries. Overall, the differences in mean forecast errors are minor when using real‐time data or pseudo–real‐time data and these differences do not significantly impact the overall assessment of the forecasts' quality. Additionally, the forecast performance varies across countries, with smaller countries and Central and Eastern European countries (CEECs) experiencing larger forecast errors. The paper provides evidence that there is still potential for improvement in forecasting techniques both for nowcasts but also forecasts up to eight quarters ahead. In the latter case, the performance of the mean forecast tends to be superior for many countries.
Voice Analysis as a Method for Preoperatively Predicting a Difficult Airway Based on Machine Learning Algorithms: Original Research Report
Authors: Rodiera Claudia , Fortuny Helena , Valls Adaia , Borras Rosa , Ramírez Carlos , Ros Bibiana , Rodiera Josep , Santaliestra Jesús , Lanau Miquel , Rodríguez Nacho 
Published: December 2024

ABSTRACTBackground and AimsAn unanticipated difficult airway is one of the greatest challenges for anesthesiologists. Proper preoperative airway assessment is crucial to reducing complications. However, current screening tests based on anthropometric features are of uncertain benefit. Therefore, our study explores using voice analysis with machine learning algorithms to predict a difficult airway.MethodsObservational, multicenter study with N = 438 patients initially enrolled at Centro Medico Teknon and Institut Universitari Dexeus (2019–2022) for the research study. After excluding 125 patients, N = 313 were included. Ethics committee approval was obtained. Adults ASA I‐III scheduled for elective procedures under general anesthesia with endotracheal intubation were selected. Patient clinical features and traditional predictive tests were collected. Vowels “A, E, I, O, U” were recorded in normal, flexion, and extension positions. Cormack grade was assessed, and data were analyzed using KNIME, resulting in multiple models based on demographics and voice data. ROC curves and other metrics were evaluated for each model.ResultsAmong multiple models evaluated, two yielded the best performance to predict a difficult airway both exclusively analyzing Cormack I and IV cases which showed the most distinct differences. The variables included in each model were the following: Model 1; included demographic data, vowel “A” in all positions and harmonics of the voice achieving an AUC of 0.91. Model 2; Included demographic data, vowel “O” in normal positions and voice parameters (Shimmer, Jitter, HNR); achieving in an AUC of 0.90. In contrast, models which focused on analyzing all Cormack grades (I, II, III, IV) cases performed less effectively.ConclusionsAcoustic parameters of the voice together with the demographic data of the patients, when introduced into classification algorithms based on machine learning showed promising signs of predicting a difficult airway.
Prediction of Multisite Pain Incidence in Adolescence Using a Machine Learning Approach: A 2‐Year Longitudinal Study
Authors: Joensuu Laura , Rautiainen Ilkka , Hautala Arto J. , Siekkinen Kirsti , Pirnes Katariina , Tammelin Tuija H. 
Published: December 2024

ABSTRACTBackground and AimsMultisite pain is a prevalent and significant issue among adolescents, often associated with adverse physical, psychological, and social outcomes. We aimed to (1) predict multisite pain incidence in the whole body and in the musculoskeletal sites in adolescents, and (2) explore the sex‐specific predictors of multisite pain incidence using a novel machine learning (ML) approach (random forest, AdaBoost, and support vector classifier).MethodsA 2‐year longitudinal observational study (2013–2015) was conducted in a population‐based sample of Finnish adolescents (N = 410, 57% girls, 12.5 years (SD = 1.2) at baseline). Three different data sets were used. First data included 48 pre‐selected variables relevant for adolescents' health and wellbeing. The second data included nine physical fitness variables related to the Finnish national ‘Move!’ monitoring system for health‐related fitness. The third data set included all available baseline data (392 variables). Multisite pain was self‐reported weekly pain during the past 3 months manifesting in at least three sites and not related to any known disease or injury. Musculoskeletal pain sites included the neck/shoulder, upper extremities, chest, upper back, low back, buttocks, and lower extremities. Whole body pain sites also included the head and abdominal areas.ResultsOverall, 16% of boys and 28% of girls developed multisite pain in the whole body and 10% and 15% in the musculoskeletal area during the 2‐year follow‐up. The prediction ability of ML reached area under the receiver operating characteristic curve 0.78 at highest but remained mainly < 0.7 for the majority of the methods. With ML, a broad variety of predictors were identified, with up to 33 variables showing predictive power in girls and 13 in boys.ConclusionThe results highlight that rather than any isolated variable, a variety of factors contribute to future multisite pain.
Performance study on a hybrid solid desiccant‐vapor compression air‐conditioning system for hot‐humid ambient conditions
Authors: Venkatesh R. , Ganesh Madhu , Rudramoorthy R. 
Published: December 2024

AbstractThe paper focuses on the simulation and testing of a hybrid solid desiccant‐vapor compression air‐conditioning system under different hot‐humid climates. The simulation is carried out by a BLUEJ programming framework. Air at the lowest achievable temperatures from a solid desiccant cooling system is supplied to a standard vapor compression air‐conditioning system (VCAS). The cooling capacities of the hybrid system under three modes 1, 2, and 3, indicating different supply air conditions to the cabin, are reported in the paper. This paper expresses the trade‐off between having comfort conditions and reasonable comfort conditions inside the cooling space with energy efficiency as the inflection point. The more the study is moved towards the point of energy efficiency, the higher the reduction in the cooling capacities of the vapor compression air conditioner. This is demonstrated by the cooling capacity savings when the system is operated in three modes namely 1, 2, and 3. The substantial energy savings provided by Mode 1, Mode 2, and Mode 3 are 71%, 57%, and 37%, respectively. If the system is made to provide substantial cooling and focuses deeply on cooling capacity savings, then the system could save up to 77% in the cooling capacity of the vapor compression air‐conditioning system. If the system is made to operate solely with the milestone of comfort cooling for the occupants with any substantial savings in the cooling capacity of the vapor compression air‐conditioning system, then Mode 3 would deliver the milestone and give savings in the cooling capacities from 32% to 41% which is a significant savings. From the results of the performance study, it is inferred that the hybrid system provides significant energy savings compared to a standard air conditioner, especially in hot‐humid ambient conditions. The solid desiccant cooling system thus establishes itself as an effective pre‐cooler unit for a VCAS. The hybrid solid desiccant air‐conditioning in the paper is analyzed from the aspects of savings in cooling capacities of an existing vapor compression air‐conditioning system and comfort cooling. This is a newer operational approach, especially for using this hybrid solid desiccant cooling system for ambient humidity ratios greater than 15 kg−1 d.a.
An Overview of Monkeypox Virus Detection in Different Clinical Samples and Analysis of Temporal Viral Load Dynamics
Authors: Cordeiro Rita , Pelerito Ana , de Carvalho Isabel Lopes , Lopo Sílvia , Neves Raquel , Rocha Raquel , Palminha Paula , Verdasca Nuno , Palhinhas Cláudia , Borrego Maria José , Manita Carla , Ferreira Idalina , Bettencourt Célia , Vieira Patrícia , Silva Sónia , Água‐Doce Ivone , Roque Carla , Cordeiro Dora , Brondani Greice , Santos João Almeida , Martins Susana , Rodrigues Irene , Ribeiro Carlos , Núncio Maria Sofia , Gomes João Paulo , Batista Fernando da Conceição 
Published: December 2024

ABSTRACTMpox is a zoonotic disease caused by the Monkeypox virus (MPXV), and since May 2022, tens of thousands of cases have been reported in non‐endemic countries. We aimed to evaluate the suitability of different sample types for mpox diagnostic and assess the temporal dynamics of viral load. We evaluated 1914 samples from 953 laboratory‐confirmed cases. The positivity rate was higher for lesion (91.3%) and rectal swabs (86.1%) when compared with oropharyngeal swabs (69.5%) and urines (41.2%), indicating higher viral loads for the former. Supporting this, lesion and rectal swabs showed lower median PCR Ct values (Ct = 23 and Ct = 24), compared to oropharyngeal swabs and urines (Ct = 31). Stable MPXV loads were observed in swabs from lesions up to 30 days after symptoms onset, contrasting with a considerable decrease in viral load in rectal and oropharyngeal swabs. Overall, these results point to lesion swabs as the most suitable samples for detecting MPXV in the 2022–2023 multicountry outbreak and show comparable accuracy to rectal swabs up to 8 days after symptoms onset. These findings, together with the observation that about 5% of patients were diagnosed through oropharyngeal swabs while having negative lesions, suggest that multisite testing should be performed to increase diagnostic sensitivity.
Effects of γ‐polyglutamic acid on the rheological, microstructural and sensory properties of low‐fat yogurt
Authors: Zhang Bobo , Zhu Hongshuai , Liang Dan , Chen Kai , Xie Xinhua , Yan Shuang , Gao Yulong 
Published: December 2024

AbstractBACKGROUNDWhile low‐fat yogurt offers numerous health benefits, its texture and sensory qualities are poor. This study aimed to investigate the effects of γ‐polyglutamic acid (γ‐PGA) on the rheological, microstructural and sensory properties of low‐fat yogurt using rheological tests, scanning electron microscopy (SEM) and sensory evaluation.RESULTSThe results showed that the syneresis of low‐fat yogurt added with 0.15% γ‐PGA was significantly (P < 0.05) reduced to 23.03%, compared to that of low‐fat yogurt without γ‐PGA (42.87%). An improvement in storage and loss moduli (G', G") and apparent viscosity was also observed. The power law model fitted to rheological data indicated that γ‐PGA enhanced the viscoelasticity and strength of the gel network though interaction with casein gel, which might lead to changes in the moduli of yogurts. Microstructural observation via SEM confirmed the enhanced crosslinking between casein micelles and the filling effect of γ‐PGA. Sensory liking scores were strongly correlated with rheological properties and apparent viscosity. The results of principal component analysis (PCA) confirmed the positive effects of γ‐PGA on quality and rheological attributes of low‐fat yogurt.CONCLUSIONThe results of this study provided valuable references for the potential use of γ‐PGA as a fat replacer to stabilize the sensory quality of low‐fat yogurt. © 2024 Society of Chemical Industry.
Structural and Optical Anomalies in Thin Films Grown in a Magnetic Field by Electron‐Assisted Vacuum Deposition of PTFE
Authors: Ksianzou Viachaslau , Villringer Claus , Grytsenko Kostyantyn , Pekur Demyd , Lytvyn Petro , Sopinskyy Mykola , Lebedyeva Iryna , Niemczyk Agata , Baranowska Jolanta 
Published: December 2024

AbstractPolytetrafluoroethylene (PTFE) films are deposited in parallel and perpendicular magnetic fields (MF) by electron‐enhanced vacuum deposition (EVD) and EVD + low‐temperature plasma (LTP) methods. The structure, morphology, and nanomechanical properties of the films are studied by infrared spectroscopy (IRS), atomic force microscopy (AFM), and spectroscopic ellipsometry. The structure of the thicker films is closer to that of bulk PTFE than that of thin films. The films' crystallinity and surface roughness are higher than those deposited without MF. The birefringence of the refractive index (n) of the films deposited in the MF is inverse to the anisotropy of the n of the films deposited without MF. The hardness of the films is close to that of bulk PTFE.
Co‐Simulation Interface Model Reduction for Large‐Scale Coupled Simulations
Authors: Peeters Jari , Vermaut Martijn , Vanpaemel Simon , Naets Frank 
Published: December 2024

ABSTRACTThe paper presents a novel approach for reducing the co‐simulation interface representation between multiple large‐scale models. The methodology leverages model order reduction through component mode synthesis in some specific small deformation flexible multibody formulations that yield a constant transformation matrix between Cartesian coordinates and general multibody coordinates, such as the flexible natural coordinates formulation or the generalized component mode synthesis. The constant transformation matrix stemming from these techniques is further modified using modified Gram–Schmidt orthonormalization and the effective independence methodology to create a constant interface model reduction matrix. This matrix effectively connects a minimal set of interface nodes to the entire nodal domain, while simultaneously projecting the forces acting on the entire nodal domain onto the interface nodes. Notably, the proposed methodology scales the size of the required co‐simulation interface representation with the considered set of mode shapes rather than the size of the numerical finite element mesh. This co‐simulation interface model reduction strategy not only renders large distributed load models compatible with the Functional Mock‐Up Interface but also extends its applicability to any structural model beyond the flexible multibody scope, provided that deformations remain relatively small. Numerical validation with a simply supported beam, connected to springs at each node, demonstrates that the interface model reduction error is significantly smaller than the co‐simulation error. This suggests that substantial interface model reduction can be achieved without compromising accuracy. Moreover, additional numerical validation performed with a rotor‐drum model showcases the versatility and scalability of the proposed approach, particularly in addressing dynamic structural systems.
Process Optimization for Fermentative Production of Black Rice Vinegar
Authors: Kaur Harmandeep , Kocher Gurvinder Singh 
Published: December 2024

ABSTRACTBlack rice (Oryza sativa) also known as forbidden rice, restricted only in northeast Asia, is now being cultivated in some Indian states and has a huge potential for producing vinegar being rich in health‐promoting characteristics. In the current study, enzymatic saccharification of black rice carried out using commercial amylases was optimized by response surface methodology (RSM) at 45°C with 5.5 pH. The optimized saccharified starch showed a Brix of 13.5°B with 10.937 g/100 mL and 8.602 g/100 mL of total sugars and reducing sugars, respectively. The saccharification validation of 2L showed a maximum of 14°B, 13.1 g/100 mL total sugars and 10.89 g/100 mL reducing sugars. The ethanolic fermentation of hydrolyzed starch was carried out using Saccharomyces cerevisiae KY069279, which led to 6.532% (v/v) ethanol at a fermentation efficiency of 93.11% and 0.47 g/g of ethanol productivity. The acetic acid fermentation was carried out post‐ethanol production using indigenous acetic acid bacteria, Acetobacter aceti AC1. The fermented vinegar showed 4.15% (w/v) volatile acidity at 64.7% fermentation efficiency and 0.38 g/g acetic acid productivity. The produced rice vinegar was found to be rich in antioxidants with a 77.8% DPPH scavenging activity at 50.93 µM concentration. The vinegar was found to be of standard quality with a mean sensory score of 7.92 ± 0.8 by a panel of 10 semitrained judges.