bluuebunny/crossref_metadata_2025_split huggingface dataset:
In situ Tracking the Constrained Reconstruction of Cu3Pd@SiO2 Nanoparticles Driven by Redox Atmospheres
Authors: Xu Changcheng , Zhao Qiao , Han Shaobo , Liu Shuang , Liu Wei , Li Yong , Shen Wenjie 
Published: March 2024

AbstractEndowed with flexible surface coordination and synergetic electronic status, bimetallic particles serve as promising heterogeneous catalysts as their microstructures evolved sensitively to the treatment atmospheres, whereas knowledge of dynamic manners is less. Herein, utilizing environmental transmission electron microscopy (ETEM), the reconstructions of Cu3Pd particles in oxidization/reduction atmospheres were explored at atomic scale. Specifically, bare Cu3Pd particles went through a phase separation of CuOx and PdOx during in situ oxidation, and subsequent agglomeration after H2 reduction. While protected in a silica shell, the confined Cu3Pd particles were oxidized into Cu1.5Pd0.5O2 phase after air calcination and subsequently restructured into versatile configurations during H2 reduction. Specifically, hollow Cu3Pd alloy architecture with Pd enriched layer near surface as reduced at 200 °C. Further rising 400 to 600 °C, it yielded disordered Cu3Pd alloys with slightly Pd atoms enrichment at outmost surface. The dynamical behaviors of single Cu1.5Pd0.5O2 particle during in situ reduction have been visualized in ETEM, wherein a series of deformation, elongation and rotation is involved during the hollow architecture firstly formation, and then vanished into a Cu3Pd solid solution nanoparticle. The tunable microstructures of Cu3Pd@SiO2 driven by redox atmospheres demonstrate efficient approach for precisely regulating the chemical environments of constrained bimetallic nanocatalysts.
Optimizing air quality predictions: A discrete wavelet transform and long short‐term memory approach with wavelet‐type selection for hourly PM10 concentrations
Authors: Taşağıl Arslan Gökçe Nur , Kılıç Depren Serpil 
Published: March 2024

AbstractThe rapid advancement of industrialization and urbanization has led to the global problem of air pollution. Air quality can decrease due to pollutants in the air, including types of gases and particles that are carcinogenic, causing adverse health effects. Therefore, estimating the concentration of air pollutants is of great interest as it can provide accurate information about air quality with proper planning of future activities. In this manner, this study considers Istanbul, a province with a high concentration of industry, population, and vehicle traffic. Particulate matter (PM), one of the most basic air pollutants, is stated to contain microscopic solids or liquid droplets that are small enough to be inhaled and cause serious health problems. Thus, it is recommended to apply discrete wavelet transform (DWT) and deep learning method long short‐term memory (LSTM) as a hybrid model to predict the concentration of PM10. Using the mentioned methods, they can predict air pollution to have been developed within the scope of this study. Furthermore, the hybrid approach with LSTM by selecting the most appropriate discrete wavelet type emphasizes the difference of this study from the existing literature. The ability of these developed methods to make successful future predictions helps institutions and organizations that can take precautions on the subject to take action at the right time; in addition, the deep learning methods used contribute to the development of sustainable smart environmental systems. In today's environment when air pollution is increasing and threatening human health, any precaution that can be taken would improve the quality of life for all living things, reduce health issues and deaths caused by air pollution, and thus raise the degree of well‐being. These findings might offer a reliable scientific evidence for Istanbul City's air pollution management, which can serve as an example for other regions.
Profiling of Oxylipins as Markers of Oxidative Stress in Biological Samples
Authors: Yang Liping , Choi Jaewoo , Maier Claudia S. , Stevens Jan F. 
Published: March 2024

AbstractOxylipins are oxidized metabolites of polyunsaturated fatty acids (PUFAs). They represent a class of risk markers and/or therapeutic targets for diseases associated with inflammation, including cardiovascular disease and brain disorders. Because the biological activities of free PUFAs and oxylipins depend on their chemical structures and concentrations, monitoring PUFAs and oxylipin levels in biological systems is critical for understanding their roles in health and disease. Traditionally, accurate quantification of free PUFAs and oxylipins in biological samples was performed separately, as PUFAs are often 1000‐fold more abundant than the derived oxidized fatty acids (oxylipins). This article describes a liquid chromatography multiple reaction monitoring tandem mass spectrometry method for the quantitative analysis of five free PUFAs and 88 oxylipins in various biological fluids, including plasma, platelet supernatants, and tissues. The same approach can also be used in conjunction with an alkaline hydrolysis step to quantify total oxylipins in fish oils. We observed that in some samples, linoleic acid levels in plasma and eicosapentaenoic acid and arachidonic acid levels in brain tissue were above the upper limit of quantification. To address this issue, we developed a data analysis method to obtain PUFA and oxylipin concentrations in these samples without additional sample preparation, thus significantly saving time and labor. © 2024 Wiley Periodicals LLC.Basic Protocol: Quantification of polyunsaturated fatty acids (PUFAs) and oxylipins using liquid chromatography multiple reaction monitoring tandem mass spectrometrySupport Protocol 1: Preparation of internal standard mixed working solutionSupport Protocol 2: Preparation of standard mixed stock solutionSupport Protocol 3: Preparation of standard mixed working solutionAlternate Protocol 1: Extraction and quantitation of free PUFAs and oxylipins from mouse brain tissueAlternate Protocol 2: Extraction and quantitation of total PUFAs and oxylipins from fish oil
Assessing habitat connectivity of rare species to inform urban conservation planning
Authors: McCluskey Eric M. , Kuzma Faith C. , Enander Helen D. , Cole‐Wick Ashley , Coury Michela , Cuthrell David L. , Johnson Caley , Kelso Marianne , Lee Yu Man , Methner Diana , Rowe Logan , Swinehart Alyssa , Moore Jennifer A. 
Published: March 2024

AbstractUrbanization is commonly associated with biodiversity loss and habitat fragmentation. However, urban environments often have greenspaces that can support wildlife populations, including rare species. The challenge for conservation planners working in these systems is identifying priority habitats and corridors for protection before they are lost. In a rapidly changing urban environment, this requires prompt decisions informed by accurate spatial information. Here, we combine several approaches to map habitat and assess connectivity for a diverse set of rare species in seven urban study areas across southern Michigan, USA. We incorporated multiple connectivity tools for a comprehensive appraisal of species‐habitat patterns across these urban landscapes. We observed distinct differences in connectivity by taxonomic group and site. The three turtle species (Blanding's, Eastern Box, and Spotted) consistently had more habitat predicted to be suitable per site than other evaluated species. This is promising for this at‐risk taxonomic group and allows conservation efforts to focus on mitigating threats such as road mortality. Grassland and prairie‐associated species (American Bumble Bee, Black and Gold Bumble Bee, and Henslow's Sparrow) had the least amount of habitat on a site‐by‐site basis. Kalamazoo and the northern Detroit sites had the highest levels of multi‐species connectivity across the entire study area based on the least cost paths. These connectivity results have direct applications in urban planning. Kalamazoo, one of the focal urban regions, has implemented a Natural Features Protection (NFP) plan to bolster natural area protections within the city. We compared our connectivity results to the NFP area and show where this plan will have an immediate positive impact and additional areas for potential consideration in future expansions of the protection network. Our results show that conservation opportunities exist within each of the assessed urban areas for maintaining rare species, a key benefit of this multi‐species and multi‐site approach.
Mental fatigue impairs the number of repetitions to muscular failure in the half back‐squat exercise for low‐ and mid‐ but not high‐intensity resistance exercise
Authors: de Lima‐Junior Dalton , Gantois Petrus , Nakamura Fabio Yuzo , Marcora Samuele Maria , Batista Gilmário Ricarte , Bartolomei Sandro , Ferreira Maria Elisa Caputo , de Sousa Fortes Leonardo 
Published: March 2024

AbstractThe study aimed to analyze the acute effect of mental fatigue on the maximum number of repetitions in a resistance exercise session with different intensities in resistance‐trained adults. Eighteen young men aged between 18 and 25 years old (age, 22.1 ± 2.0 years; body weight, 82.5 ± 6.6 kg; height, 177.4 ± 5.2 cm; half‐back squat 1‐RM, 106.7 ± 21.9 kg) were recruited for the study. Each participant performed two trials (i.e., control and mental fatigue) in a random and balanced order for 30‐min. The participants performed three sets of half back‐squat exercise to failure, with intensities of 50%, 70%, and 90% of 1RM with a passive recovery interval of 5‐min between sets. The intensity was randomized and counterbalanced, and the order was maintained in both conditions for the same subject. We assessed resistance training using the number of repetitions to failure and perceived effort and checked the mental fatigue subjectively and objectively. The participants in the mental fatigue condition presented a significantly increased perception of mental fatigue (p < 0.05) and reduced pupil diameter (p < 0.05). The number of repetitions were significantly lower for the 50 (p < 0.05) and 75% 1RM (p < 0.05) in the mental fatigue condition, but the 90% 1RM remained similar (p > 0.05). Also, the perceived effort showed significantly higher results for the 50 (p < 0.05) and 75% 1RM (p < 0.05) in the mental fatigue condition, but the 90% 1RM remained similar (p > 0.05). Then, this study showed that mental fatigue reduced resistance exercise performance for low‐ and mid‐intensity but not for high‐intensity.
Predicting performance of elite kickboxers using the multi‐states theory framework
Authors: Morrone Marco , Ventura Lucia , Roggio Irene , Di Blasio Andrea , Ruiz Montse , Deriu Franca , Cugusi Lucia , Manca Andrea , Robazza Claudio 
Published: March 2024

AbstractUsing the multi‐states (MuSt) theory framework, this study examined the interplay between self‐confidence, emotional arousal control, worry, concentration disruption, challenge and threat appraisals, psychobiosocial experiences, and self‐evaluated performance of medalist kickboxers involved in the WAKO World Kickboxing Championship 2021. Participants were 103 gold, silver, or bronze medalists (58 women and 45 men), aged 18–39 (M = 25.16 ± 4.54 years), who were contacted via email and social media and asked to fill an online survey 3 months after the event. According to the MuSt theory predictions, self‐confidence and emotional arousal control were positively related to challenge appraisal, functional psychobiosocial experiences, and self‐evaluated performance. Worry and concentration disruption were positively associated with threat appraisal, and negatively related to functional psychobiosocial experiences; concentration disruption was also negatively related to self‐evaluated performance. Results from path analysis revealed a positive indirect link from self‐confidence to self‐evaluated performance via challenge appraisal and psychobiosocial experiences. Negative indirect links from worry and concentration disruption to self‐evaluated performance through threat appraisal and psychobiosocial experiences were significant. A positive indirect effect from emotional arousal control to self‐evaluated performance via psychobiosocial experiences was also shown. The findings are discussed in light of the MuSt theory.
Effect of eggshell powder on polyvinyl ester composite: A statistical correlation on mechanical strength
Authors: Babu Kumba Anand , Paramasivam Baranitharan , Vijayananth Kavimani , Seenivasan Venkatesh , Raju Sasikumar 
Published: March 2024

AbstractThe present study focuses on day‐by‐day litter discarded cigarette filter fiber (CFF) reinforced polyvinyl ester (VE) composites developed by a compression molding process. Chicken eggshell powder (ESP) is used as a filler material in the matrix phase with different weight percentages (0%, 3%, and 5%). Multi‐criteria decision‐making (MCDM) using Criteria Importance through Inter criteria Correlation (CRITIC) integrated TOmada de Decisao Interativa Multicriterio (TODIM) methodology was used to find the optimal condition for mechanical properties. CFF (50–60 wt%), fiber length (10–20 mm), and filler (0–5 wt%) are selected as process control factors with different levels. The CRITIC‐TODIM optimization results reveal that ESP filler has acted as the dominant parameter in fabricated composites in amplifying the tensile, impact, and flexural properties. The integrated approach reveals that CFF 60 wt%, fiber length 20 mm with ESP 3 wt% combination have the optimal mechanical characteristics. Thermo‐gravimetric analysis indicates that composite developed at optimal conditions exhibits better thermal stability when compared with null ESP filler composite.
A deep learning‐based financial hedging approach for the effective management of commodity risks
Authors: Hu Yan , Ni Jian 
Published: March 2024

AbstractThe development of deep learning technique has granted firms with new opportunities to substantially improve their risk management strategies for sustainable growth. This paper introduces a novel deep learning‐based financial hedging (DL‐HE) strategy to leverage the salient ability of deep learning in extracting nonlinear features from complex high dimensional data, thus boosting the management of inventory risks arising from erratic commodity prices. Using real‐world data, we find that the average annualized economic benefit of the proposed strategy is at least 1.21 million CNY for a typical aluminum firm carrying an average level of inventory in China, as compared with those of the traditional hedging strategies. Further analysis reveals that such an economic benefit can largely be explained by the efficacy of the proposed DL‐HE strategy in terms of significantly improving return while still effectively controlling risk. Moreover, the superior of this strategy remains robust when extending to copper and zinc.
The utility of fetal heart rate deceleration's descending slope in searching for a non‐National Institute of Child Health and Human Development parameter for the detection of fetal acidosis
Authors: Castán Larraz Berta , Esteban Luis Mariano , Castán Mateo Sergio , Chóliz Ezquerro Marta , Calvo Torres Javier , Esteban‐Escaño Javier , Rodríguez Solanilla Belén , Cisneros Gimeno Ana , Savirón‐Cornudella Ricardo 
Published: March 2024

AbstractObjectiveTo identify new parameters predicting fetal acidemia.MethodsA retrospective case–control study in a cohort of deliveries from a tertiary referral hospital‐based cohort deliveries in Zaragoza, Spain between 2018 and 2021 was performed. To predict fetal acidemia, the NICHD categorizations and non‐NICHD parameters were analyzed in the electronic fetal monitoring (EFM). Those included total reperfusion time, total deceleration area and the slope of the descending limb of the fetal heart rate of the last deceleration curve. The accuracy of the parameters was evaluated using the specificity for (80%, 85%, 90%, 95%) sensitivity and the area under the receiver operating characteristic curve (AUC).ResultsA total of 10 362 deliveries were reviewed, with 224 cases and 278 controls included in the study. The NICHD categorizations showed reasonable discriminatory ability (AUC = 0.727). The non‐NICHD parameters measured during the 30‐min fetal monitoring, total deceleration area (AUC = 0.807, 95% CI: 0.770, 0.845) and total reperfusion time (AUC = 0.750, 95% CI: 0.707, 0.792), exhibited higher discriminatory ability. The slope of the descending limb of the fetal heart rate of the last deceleration curve had the best AUC value (0.853, 95% CI: 0.816, 0.889). The combination of total deceleration area or total reperfusion time with the slope demonstrated high discriminatory ability (AUC = 0.908, 95% CI: 0.882, 0.933; specificities of 71.6% and 72.7% for a sensitivity of 90%).ConclusionsThe slope of the descending limb of the fetal heart rate of the last deceleration curve is the strongest predictor of fetal acidosis, but its combination with the total reperfusion time shows better clinical utility.
Label‐free surface‐enhanced Raman spectroscopy coupled with machine learning algorithms in pathogenic microbial identification: Current trends, challenges, and perspectives
Authors: Tang Jia‐Wei , Yuan Quan , Wen Xin‐Ru , Usman Muhammad , Tay Alfred Chin Yen , Wang Liang 
Published: March 2024

AbstractInfectious diseases caused by microbial pathogens remain a primary contributor to global health burdens. Prompt control and effective prevention of these pathogens are critical for public health and medical diagnostics. Conventional microbial detection methods suffer from high complexity, low sensitivity, and poor selectivity. Therefore, developing rapid and reliable methods for microbial pathogen detection has become imperative. Surface‐enhanced Raman Spectroscopy (SERS), as an innovative non‐invasive diagnostic technique, holds significant promise in pathogenic microorganism detection due to its rapid, reliable, and cost‐effective advantages. This review comprehensively outlines the fundamental theories of Raman Spectroscopy (RS) with a focus on label‐free SERS strategy, reporting on the latest advancements of SERS technique in detecting bacteria, viruses, and fungi in clinical settings. Furthermore, we emphasize the application of machine learning algorithms in SERS spectral analysis. Finally, challenges faced by SERS application are probed, and the prospective development is discussed.
Model‐Based Framework for Data and Knowledge‐Driven Systems Architecting Demonstrated on a Hydrogen‐Powered Concept Aircraft
Authors: Kuelper Nils , Bielsky Thimo , Broehan Jasmin , Thielecke Frank 
Published: March 2024

ABSTRACTAircraft development is a protracted process over many years. Novel concept aircraft with new energy sources and disruptive systems technologies are investigated during the aircraft conceptual design phase with the goal to achieve sustainable aviation. Current development cycles need to be accelerated to reduce time to market and development costs of novel aircraft, while still handling complexity and uncertainty of systems technologies. Therefore, a holistic framework for knowledgebased systems architecting using a model‐based systems engineering approach is presented. This framework has the purpose to conserve and provide knowledge, that is, information, data, and experiences about existing systems architectures, to the engineer. The developed framework consists of a database concept, a method for model‐based systems architecting, and an interface to the overall systems design software toolGeneSys. Based on evaluating different modeling languages and tools,MathWorks System Composeris selected as most suitable tool for knowledge‐based systems architecting. The developed framework is then demonstrated by conserving and reusing formalized knowledge for the design of a novel hydrogen‐powered concept aircraft. On‐board systems architecture models are saved in a database and automatically recreated reducing development time. The complete graphical representation could not yet be stored in a formalized manner partly reducing the advantage of a clear representation of model‐based systems architecting. However, this did not reduce automatic recreation and evaluation capabilities.
Applying a System of Systems Perspective to Hyundai‐Kia's Virtual Tire Development
Authors: Yun Sunkil , Alai Shashank , Kim Yongdae , Kim Tae Kook , Jo Jaehun , Lee Dahyeon , Gorantla Lokesh , Baloh Michael 
Published: March 2024

ABSTRACTSystems engineering has become important in almost every complex product manufacturing industry, especially automotive. Emerging trends like vehicle electrification and autonomous driving now pose a system of systems (SoS) engineering challenge to automotive OEMs. This paper presents a proof‐of‐concept (PoC) that applies a top‐down SoS perspective to Hyundai‐Kia Motor Corporation's (HKMC) virtual product development process to develop a performance‐critical component of the vehicle, the tire. The PoC demonstrates using the Arcadia MBSE method to develop a consistent, layered, vehicle architecture model starting from the SoS operational context down to the lowest level of system decomposition in the physical architecture thereby capturing top‐down knowledge traceability Using the concept of functional chains, several vehicle performance views are captured that serve as the basis for architecture verification orchestration across engineering domains using a cross‐domain orchestration platform thereby validating key vehicle/tire performance metrics that influence the tire design parameters. Preliminary results of the study show that applying a method‐based modeling approach could provide several benefits to HKMC's current product development approach such as reduced time to model, SoS knowledge capture and reusability, parameter/requirement traceability, early performance verification, and effective systems engineering collaboration between the OEM, tire design supplier, and tire manufacturers.
Nanoparticles for the synthesis of bio‐based chemical 5‐Hydroxymethyl furfural from agricultural waste and biomass‐derived carbohydrates‐A review
Authors: Anjali  , Veluturla Sravanthi , Saranya R , Vijaya Lakshmi S , Hemanth K M 
Published: March 2024

AbstractThe need for 5‐Hydroxymethylfurfural (HMF) has garnered significant attention owing to its versatile applications in the chemical industry as a precursor for biofuels, pharmaceuticals and fine chemicals. This abstract summarizes a complete review on the synthesis of HMF using heterogeneous catalyst from agriculture waste and various biomass‐derived carbohydrates, focusing on their efficiency, selectivity and industrial feasibility. This review systematically outlines the diverse classes of heterogeneous catalyst employed in HMF production, including titanium dioxide (TiO2), zirconium dioxide (ZrO2), silicon dioxide (SiO2) and aluminium oxide (Al2O3), where the discussion highlights their catalytic mechanisms and intrinsic properties that influence HMF yield, selectivity, stability and reusability. In addition, the impact of reaction parameters such as temperature, pressure, solvent, feedstock composition and catalyst morphology on HMF synthesis has been assessed. This review consolidates the current state‐of‐the‐art methodologies in the synthesis of HMF using various heterogeneous nanoparticle catalysts. © 2024 Society of Chemical Industry (SCI).
Marc van Regenmortel, personal recollections on a forward‐thinking editor
Authors: Pellequer Jean‐Luc , Westhof Eric 
Published: March 2024

AbstractMarc van Regenmortel was the Editor‐in‐Chief of the Journal of Molecular Recognition for the last 25 years. Without attempting to summarize Marc's exceptional career and achievements, we would like to tell the story of the tortuous and contingent path to the unravelling of a key molecular recognition process in antigenicity. Life is indeed full of contingencies and scientific life, full of meetings and random encounters, is prone to contingencies, a key element in discovery and innovation.