bluuebunny/crossref_metadata_2025_split huggingface dataset:
Theoretical Calculation–Driven Metal–Organic Framework Nanozymes: Catalytic Mechanisms and Applications
Authors: Zhang Ziyu , Yuan Zhishuang , Zhang Ziyan , Guan Jing , Tan Weiqiang , Zhang Guangyao , Chai Huining 
Published: October 2024

ABSTRACTMetal–organic framework (MOF) nanozymes have garnered widespread attention in the field of biomimetic catalysis due to their highly controllable porous structure and surface functionalization, enabling them to mimic the catalytic activity and specificity of natural enzymes while offering greater stability and reusability. In recent years, significant progress has been made in the theoretical computation studies of MOF nanozymes' catalytic reactions, providing deep insights into their catalytic and analytical mechanisms. This review comprehensively gathers the latest research progress of theoretical calculation–driven MOF nanozymes on their catalytic mechanisms and applications. First, the methods that can be used for theoretical calculations of MOF nanozymes, especially density functional theory (DFT), are reviewed to help deeply analyze the active site distribution, electron transfer pathways, and adsorption and activation mechanisms of reactants of MOF nanozymes. Subsequently, this review deeply studies the contribution of these theoretical calculation methods to revealing the catalytic reaction mechanism of MOF nanozymes (such as active sites and enzyme‐like activity), especially the specific role of electron transfer and reaction energy changes in key reaction steps. Finally, this review looks forward to the challenges and opportunities in the theoretical computation for the future design and application of MOF nanozymes, especially in accurately predicting catalytic activities, understanding complex reaction mechanisms, and guiding the synthesis of new nanozyme materials. By integrating theoretical calculations with experimental research, the study of MOF nanozymes is expected to forge new avenues in biomimetic catalysis and provide effective strategies for addressing challenges in the fields of sensing, biomedicine, and environmental protection.
Industrial experimental study on combustion characteristics and NOx emission characteristics of a 600 MWe wall‐fired boiler under ultra‐low excess air coefficient conditions
Authors: Ti Shuguang , Deng Shanshan , Yang Zhi , Zheng Li , Zhu Youjian , Gao Ke , Gao Shang , Yang Jinhui , Wang Haopeng 
Published: October 2024

AbstractThis paper aims to explore the effects of ultra‐low excess air coefficients on the combustion performance and NOx emission characteristics of coal‐fired boilers through industrial experiments conducted on a 600 MWe wall‐fired boiler. The results indicate that the burners demonstrate good ignition performance under different ultra‐low excess air coefficient conditions. As the excess air coefficient increases, the temperature in the main combustion zone rises, and the ignition distance of pulverized coal shortens. Under ultra‐low excess air coefficient conditions (such as 1.04), the unburned carbon content in fly ash reaches 5.50%, which is 3.23% higher than under the condition of 1.11, indicating poor pulverized coal burnout. When the excess air coefficient is close to the theoretical design value (such as 1.11), the carbon content in slag and the unburned carbon content in fly ash is relatively low (1.40% and 2.28%, respectively), indicating more complete combustion of pulverized coal. Additionally, the flue gas temperature at the air preheater outlet under this condition is relatively low; compared to the condition of an excess air coefficient of 1.07, the flue gas temperature is reduced by 6°C, thus reducing flue gas loss. Although the NOx concentration under the condition of an excess air coefficient of 1.11 is slightly higher, the quantity of cooling water is less. Flow field tracking of the powder verifies the flow path and characteristics of the primary air of the burners, and the results show that the primary air flow path of the burners is relatively concentrated, avoiding impingement on the water‐cooled walls and effectively preventing slagging issues on the water‐cooled walls. The research findings are of great significance for improving the operational performance and environmental protection level of coal‐fired boilers.
Bayesian Sequential Learning and Decision Making in Bike‐Sharing Systems
Authors: Aktekin Tevfik , Kim Bumsoo , Novoa Luis J. , Zafari Babak 
Published: October 2024

ABSTRACTIn this article, we introduce modeling strategies for sequentially learning various types of demand uncertainty in bike‐share networks and propose methods for optimal station inventory management. Our approach is motivated by a real bike‐share network in Seoul, South Korea, with 40,000 bikes over a network of 2500 stations covering 25 municipal districts. In doing so, we consider novel Bayesian state space models that are suitable for fast and efficient learning of dynamically evolving system parameters for both intra‐day and inter‐week planning horizons. Our proposed approach provides an overall solution for operation managers where sequential parameter updating, demand prediction, and inventory decision making are addressed simultaneously and is straightforward to implement for the end‐user. We illustrate how our approach can be applied to a large metropolitan area like Seoul and discuss practical implementation insights.
Target Fisher: A Consensus Structure‐Based Target Prediction Tool, and its Application in the Discovery of Selective MAO‐B Inhibitors
Authors: Fernández Julián F. , Martinez Heredia Leandro , Caracciolo Fernando , Esses Daniel , Suarez Rodrigo , Siless Gaston , Perez Concepcion , Isabel Rodríguez‐Franco María , Fernández Lucía R. , Palermo Jorge A. , Lavecchia Martín 
Published: October 2024

AbstractIn this work we introduce Target Fisher, a consensus structure‐based target prediction tool that integrates molecular docking and machine learning with the aim to aid in the identification of potential biological targets and the optimization of the use of bioassays. Target Fisher uses per‐residue energy decomposition profiles extracted from docking poses as fingerprints to train target‐specific machine learning models. It provides predictions for a curated set of 37 protein targets, covering a diverse range of biological entities, and offers a user‐friendly interface accessible via a web server (https://gqc.quimica.unlp.edu.ar/targetfisher/). In this sense, Target Fisher is a valuable tool to aid organic and medicinal chemistry groups in target identification, drug discovery and drug repurposing. As a case study, we demonstrate the efficacy of Target Fisher by screening a small library of assorted natural products for targets relevant to neurodegenerative diseases, which resulted in the identification and experimental validation of selective inhibitors of monoamine oxidase B (MAO−B).
Research on Resonant Wireless Power Transfer With Hybrid Array Composite Shielding for Small Electronic Equipment
Authors: Chen Weihua , Cao Heyi , Yan Xiaoheng , Liu Yuepeng , Huang Zhishi 
Published: October 2024

ABSTRACTIn order to reduce the damage and interference caused by electromagnetic leakage to human beings and equipment during wireless energy transmission, this paper proposes a resonant hybrid array composite shielding structure based on an LCC‐S compensation circuit at an operating frequency of 200 kHz. First, by analyzing the effects of the number of turns and turn spacing on the coil coupling coefficient, the optimal parameters of the circular main coil were determined and analysis of the effect of different inductance ratios on the transmission efficiency of the system using MATLAB. Second, the system transmission efficiency and magnetic field distribution of the system with an intermediate resonant coil and three different types of array coils are simulated, and the optimal location of the hybrid array is determined; nanocrystals are selected as the shielding material and integrated reactive and passive shielding methods to improve system transmission performance and reduce electromagnetic leakage. Finally, an experimental platform was set up to verify the system's transmission performance. The results showed that when the hybrid array was placed in the center of the transmission coil, the magnetic flux density decreased by 40.1% at 58 mm from the measurement center. At a transmission distance of 16 mm, the transmission efficiency reached 60.2%, which was 9.4% higher than the situation without shielding.
Big data research is everyone's research—Making epilepsy data science accessible to the global community: Report of the ILAE big data commission
Authors: Josephson Colin B. , Aronica Eleonora , Beniczky Sandor , Boyce Danielle , Cavalleri Gianpiero , Denaxas Spiros , French Jacqueline , Jehi Lara , Koh Hyunyong , Kwan Patrick , McDonald Carrie , Mitchell James W. , Rampp Stefan , Sadleir Lynette , Sisodiya Sanjay M. , Wang Irene , Wiebe Samuel , Yasuda Clarissa , Youngerman Brett ,   the ILAE Big Data Commission
Published: October 2024

AbstractEpilepsy care generates multiple sources of high‐dimensional data, including clinical, imaging, electroencephalographic, genomic, and neuropsychological information, that are collected routinely to establish the diagnosis and guide management. Thanks to high‐performance computing, sophisticated graphics processing units, and advanced analytics, we are now on the cusp of being able to use these data to significantly improve individualized care for people with epilepsy. Despite this, many clinicians, health care providers, and people with epilepsy are apprehensive about implementing Big Data and accompanying technologies such as artificial intelligence (AI). Practical, ethical, privacy, and climate issues represent real and enduring concerns that have yet to be completely resolved. Similarly, Big Data and AI‐related biases have the potential to exacerbate local and global disparities. These are highly germane concerns to the field of epilepsy, given its high burden in developing nations and areas of socioeconomic deprivation. This educational paper from the International League Against Epilepsy's (ILAE) Big Data Commission aims to help clinicians caring for people with epilepsy become familiar with how Big Data is collected and processed, how they are applied to studies using AI, and outline the immense potential positive impact Big Data can have on diagnosis and management.
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Authors: Zhu Bing‐Xuan , Zhu Cheng‐Yi , Qin Jing‐Kai , He Wen , Yue Lin‐Qing , Huang Pei‐Yu , Li Dong , Sun Ruo‐Yao , Ye Sheng , Du Yu , Sui Jie‐He , Li Ming‐Yu , Mao Jun , Zhen Liang , Xu Cheng‐Yan 
Published: October 2024

A dual‐gate photothermoelectric detector with 2D SnP2Se6 channel demonstrates wide spectral photoresponse, high responsivity and detectivity in telecommunication bands.
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Evaluation of empathy levels of dentistry students in pediatric dentistry clinical practice education process
Authors: Arslan Gözde , Hazar Bodrumlu Ebru 
Published: October 2024

AbstractPurpose/objectivesThe objective of this study was to assess the empathy levels of dental students during their clinical practice training in pediatric dentistry and to evaluate various factors that influence changes in these empathy levels.MethodsThe study evaluated the empathy levels of a total of 350 students (70 third‐year, 140 fourth‐year, and 140 fifth‐year dental students) who received pediatric dentistry clinical practice training and/or observation between October 2022 and December 2023. The Jefferson Scale of Physician Empathy‐Student Version was used to assess empathy levels before and after the training. The data were subjected to statistical analysis using the Mann‐Whitney U test, Kruskal‐Wallis test, Wilcoxon test, and Dunn Test (p < 0.05).ResultsThe response rate of the participants was 92.10%. The highest empathy level was observed in third‐year students, while the lowest empathy level was observed in fifth‐year students. A statistically significant relationship was found between these two variables (p < 0.001). Additionally, the empathy level of female students was statistically significantly higher than that of male students (p < 0.001). Following the completion of the pediatric dentistry training, a statistically significant increase was observed in the empathy levels of the students in comparison to the baseline (p < 0.001).ConclusionEmpathy levels in students are found to be correlated with academic year, sibling count, and gender. It is of paramount importance to enhance empathy skills through training in order to foster the development of human‐oriented physicians capable of effective patient communication.
A benthic mesocosm system for long‐term multi‐factorial experiments applying predicted warming and realistic microplastic pollution scenarios
Authors: Mackay‐Roberts Nicholas , Bock Christian , Lannig Gisela , Lucassen Magnus , Paul Nina , Schaum Elisa , Pogoda Bernadette , Gerdts Gunnar 
Published: October 2024

AbstractPredicting anthropogenic impacts on benthic marine ecosystems is of great importance for conservation. Climate change models have indicated that increasing seawater temperatures will drive shifts in the distribution of benthic organisms due to species‐specific thermal tolerances. When combined with other stressors such as pollutants, interactive effects may lead to even greater impacts. Microplastics (MP), as a marine pollutant, have been shown to elicit responses in organisms but often at concentrations far greater than experienced in the environment and with short‐term exposure times. Assessing long‐term interactive effects of MP pollution and ocean warming on benthic marine organisms has not been previously addressed. A unique mesocosm facility was constructed on the island of Helgoland, in the southern North Sea, to explore the combined impacts of these two factors. The multi‐factorial experimental system is composed of 16 independent benthic mesocosms, utilizing novel features and methods for the continuous generation of climate change and MP exposure scenarios, while retaining natural conditions for other environmental parameters. We provide a description of the system design and methods, followed by an operational performance assessment during a 10‐month exposure experiment with European flat oysters (Ostrea edulis), evaluated on the accuracy of exposure scenario control and the degree of realism achieved. We demonstrate the novel application of kinetic modeling for generating environmentally relevant MP exposure conditions (+ 25 MP L−1), and highlight the mesocosm systems suitability for studying chronic effects of MP pollution and ocean warming on benthic marine ecosystems through its real‐world application.
Structural Evolution of Microgels During Precipitation Polymerization Revealed by Light Scattering and Electrophoresis
Authors: Sato Yuji , Namioka Ryuji , Nishizawa Yuichiro , Suzuki Daisuke 
Published: October 2024

AbstractWhile precipitation polymerization allows the synthesis of microgels with controlled functional‐group distributions, the structural development of these microgels during the polymerization process still remains unclear. In this study, microgels with different reactivity ratios between the monomer and charged co‐monomer are prepared by precipitation polymerization, and the evolution of their size, thermoresponsive behavior, and surface properties during polymerization are evaluated. In particular, the surface properties of the microgels are analyzed quantitatively using the softness parameter and the surface charge density is calculated using Ohshima's equation. The results allowed describing the structural changes of microgels during precipitation polymerization well and provided design guidelines for functional microgels with controlled functional group distributions.
Eco‐efficient recycling of carbon fibers from CFRP waste: A two‐step strategy by nanosecond pulsed laser
Authors: Li Zihao , Yang Yikai , Teng Zhan , Zhang Chenyang , Yang Wenfeng , Cao Yu , Li Shaolong 
Published: October 2024

AbstractThe accumulation of CFRP waste poses significant environmental challenges, necessitating the development of green and efficient recycling technologies. This study employs a nanosecond pulse laser (λ = 1064 nm) to develop a two‐step laser recycling method (LRM) for CFRP. By setting stepped process parameters, the method sequentially completes the separation and cleaning of the CFRP layers, recovering carbon fibers that retain their original weave structure in just 147 s. The study delves into the characteristics of the products from the rapid laser pyrolysis of the epoxy resin matrix and unveils the interaction mechanisms between the pyrolysis products and recycled carbon fiber (rCF). The study utilized MATLAB to simulate the effects of defocusing on the distribution of laser energy and proposed an optimization strategy that balances product quality with efficiency. The results indicate that laser‐induced thermal decomposition leads to unique microscopic damage patterns in rCF, including microcracks, etching, and delamination. Cleanliness and resin removal rate serve as crucial indicators for quantitatively optimizing the process. The optimized LRM increased efficiency by 110.20% and achieved a resin removal rate of 97.92%, while maintaining rCF tensile strength and modulus retention rates at 93.38% and 105.77%, respectively. The energy consumption was only 13.77% of that required to produce virgin carbon fibers. The LRM operates under mild conditions without the need for harsh reaction conditions, enabling ultra‐fast on‐site recycling and offering a promising solution to the challenges of CFRP waste recycling.Highlights
Using lasers for rapid delamination and cleaning of CFRP carbon fiber layers.
The type and quantity of pyrolysis products significantly affect recovery quality.
Laser‐induced resin pyrolysis oxidation damages carbon fibers.
Laser energy compensation and defocusing strategies balance efficiency and quality.
Quality Evaluation of Kidney Tea Granules From Different Origins Based on TLC, HPLC Fingerprinting, and Quantitative Analysis Combined With Chemical Pattern Recognition
Authors: Li Yangling , Su Ying , Liang Yongjuan , Li Fangchan , Lin Ning , Jiang Lin , Lin Qinghua , Chen Qing 
Published: October 2024

ABSTRACTIntroductionKidney tea is an essential herbal medicine. It is widely used to treat conditions such as urinary stones, gallstones, and rheumatoid arthritis. There is currently no standardized or widely accepted research strategy for evaluating the quality of kidney tea granules (KTGs) after granulation.ObjectivesIn this study, we aim to establish a comprehensive strategy for evaluating the quality of KTGs produced from different sources of kidney tea.MethodsA TLC combined with HPLC method was established to identify the chemical components in KTGs, and HPLC method was used to determine the contents of rosmarinic acid of KTGs. In order to distinguish samples and identify differential components, similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS‐DA) were conducted.ResultsTLC and HPLC detection confirmed three chemical components of KTGs, which are rosmarinic acid, caffeic acid, and lithospermic acid. HPLC fingerprint analysis revealed a total of seven common peaks in 15 batches of KTGs. Similarity analysis showed that the similarity of all 15 batches of KTGs was greater than 0.969. The peak areas of the seven common peaks were identified by chemical pattern recognition, and the results showed that most of the KTGs from different origins were clustered together, with small differences between them. The PCA and OPLS‐DA results showed that two principal components can represent 82.638% of the common peaks of KTGs, among which peak 5 represents rosmarinic acid, which is the main differential biomarker of KTGs from different regions. Quantitative analysis of rosmarinic acid in KTG samples was performed using HPLC fingerprint conditions and the content of rosmarinic acid in 15 batches of KTGs samples was measured to be between 8.01–14.61 mg/g.ConclusionThis study combines TLC, HPLC, and chemometrics to establish a stable and reliable method that can quickly and effectively identify the components of KTGs, accurately quantify known components in KTGs, and provide reference for the quality evaluation of KTGs.
Synergistic effect of polymer‐modified rejuvenator and fresh asphalt on road performance of hot in‐place recycling styrene–butadiene–styrene‐modified asphalt mixtures
Authors: Xia Xu , Tang Dong , Wang Pengfei , Zhao Yongli 
Published: October 2024

AbstractTo enhance the road performance of hot in‐place recycling (HIR) styrene–butadiene–styrene (SBS)‐modified asphalt mixtures, this paper investigates the recycling effects of polymer‐modified rejuvenator (PMRA) and fresh SBS‐modified asphalt under synergistic conditions, comparing them with a conventional commercial rejuvenator. The rheological properties of the recycled asphalt binder were assessed using a dynamic shear rheometer and bending beam rheometer. Microscopic characteristics were examined through fluorescence microscopy, Fourier transform infrared spectroscopy and gel permeation chromatography. Road performance was evaluated at the mixture level using rutting tests, low‐temperature bending beam tests and semi‐circular bending tests. The results indicate that 6% PMRA not only enhances the low‐temperature performance and fatigue resistance of recycled asphalt binder but also maintains excellent high‐temperature performance with low stress sensitivity. Furthermore, PMRA recycled mixtures can reduce rutting depth and significantly improve maximum bending strain and fracture energy, compensating for the low‐temperature crack resistance deficiency of HIR mixtures. Despite being a form of physical regeneration, PMRA incorporates aromatic oil and softeners to replenish volatile light components and provides a swelling environment. The supplemental SBS helps reconstruct the damaged polymer network. However, adding fresh asphalt may dilute the recycling effect and reduce the degree of fusion between aged and new asphalt, ultimately decreasing fatigue life. Therefore, this paper recommends 20% fresh asphalt content and 6% PMRA. © 2024 Society of Chemical Industry.
Revealing the Hygroscopic Behavior of Ultrahigh Nitrogen Content Cyclo‐Pentazolate Salts
Authors: Shi Lei , Wang Pengfei , Jiang Jun , Gao Chao , Zhang Chong , Du Yang , Sun Chengguo , Hu Bingcheng 
Published: October 2024

AbstractThree representative cyclo‐pentazolate salts including N2H5+N5−, NH3OH+N5− and NH4+N5−, are highly favored for their ultrahigh nitrogen content (80–96%). However, their ambiguous nature has severely restricted the application exploration. Herein, the relationships between humidity and moisture content of salt were established by quantitative analysis. Among the three salts, the hygroscopic ability has the following order: NH3OH+N5−>NH4+N5−>N2H5+N5−. Especially in the range of 40% RH −60% RH, the NH3OH+N5− has a high sensitivity to water, and the absorbed moisture content can be as high as 20.8% at 60% RH. When the relative humidity exceeds 60% RH, the hygroscopic rate of NH3OH+N5− rises sharply, at 80% RH, NH3OH+N5− will absorb excess moisture and turns into liquid form. After treating NH3OH+N5− at 40% RH, the very sensitive friction sensitivity (FS) and impact sensitivity (IS) of dried NH3OH+N5− (FS=20 N, IS=2 J) will change into insensitive salt (FS>360 N, IS>40 J). The higher moisture content in NH3OH+N5−, the lower the thermal stability, its thermal decomposition temperature (103.22°C) is 3.24°C lower than that of dry salt (106.46°C) at 75% RH (moisture content is 30.2%). The other two salts N2H5+N5− and NH4+N5− have the similar properties. Molecular dynamics simulation was further applied to explain the strong hygroscopicity of salts.