bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting Flush End‐Plate Connections Response Using Artificial Neural Networks
Authors: Georgiou Gregory , Elkady Ahmed 
Published: September 2023

AbstractPredicting the moment‐rotation response parameters of semi‐rigid steel connections can be challenging given the multitude of components that contribute to the connection's elastic and plastic deformations. This applies to the popular bolted flush end‐plate beam‐to‐column connections (FEPCs). The literature has highlighted the limitations of current analytical, mechanical, and empirical models in providing accurate predictions. Considering these limitations, the application of machine‐learning methods in structural engineering, such as artificial neural networks (ANN), have gained wide attention recently in addressing problems associated with complex structural deformation and damage phenomena. To that end, the superior nonlinearity of ANNs is employed herein in to predict the response characteristics of FEPCs. A dataset of more than 200 specimens, collected from past experimental programs, is utilized to train the ANN for predicting the elastic stiffness, plastic strength, and posy‐yield stiffness. The paper describes the deduction of response parameters from test data using data fitting, the determination of significant geometric and material features, the ANN architecture and algorithms, and the accuracy metrics of the new model.
Hybrid Coupled Walls with Replaceable Shear Links: Technical Solution and Seismic Performance of a 3D Multi‐Story Building
Authors: Vulcu Cristian , Hoffmeister Benno , Bimbli Dorina , Das Rajarshi , Degee Herve 
Published: September 2023

AbstractAs recent research findings evidenced a significant potential of the steel‐concrete hybrid coupled wall (HCW) systems, further research activities are still needed for addressing particular issues and for developing advancements in the analysis, design, and detailing. These aspects are currently being addressed within the ongoing European research project “HYCAD”, which also represents the research framework of the current study. This paper investigates through a set of nonlinear static and dynamic analyses the behavior and the seismic performance of a newly introduced steel‐concrete HCW system. In particular, a case‐study was carried out on a 3D multi‐story building structure with perimeter lateral load resisting frames, each composed of: (i) a HCW, i.e. a steel‐concrete composite wall coupled to steel columns through a set of replaceable steel shear links; (ii) a moment resisting frame (MRF). Beside a brief state of the art, a description of the research framework and the case‐study structural system, the current paper makes an overview of the following: (i) experimental program on components; (ii) proposed technical solution for connecting the replaceable dissipative shear links to the composite wall; (iii) experimental test set‐up; (iv) response of the shear links based on pretest FE investigations; (v) seismic demand in terms of rotation for the shear links.
Cold‐formed steel T‐joints with semi‐oval hollow section chord: Experimental insight and finite element modelling
Authors: Oeng Pouykang , Chen Man‐Tai , Young Ben 
Published: September 2023

AbstractExperimental study and finite element modelling of cold‐formed steel T‐joints with semi‐oval hollow section (SOHS) chord are presented. The rectangular or square hollow section (RHS/SHS) brace was welded to the flat flange of SOHS chord by robotic gas metal arc welding. Twelve SOHS T‐joints with brace‐to‐chord width ratio β from 0.29 to 0.89 were tested with the chord simply supported and the brace axially compressed. The joint strengths, failure modes and load‐deformation responses are discussed. The feasibility of the current design provisions in the CIDECT and Eurocode 3 initially developed for RHS T‐joints was examined. Generally, the predictions by these design methods are quite conservative for T‐joints with cold‐formed steel SOHS chord. In addition, a finite element model was developed to simulate the cold‐formed steel T‐joints with semi‐oval hollow section chord. Details of numerical model, including element type and mesh size as well as heat affected zone and cold‐working effect considerations, are described. The model was verified against the test results in terms of joint strength and load‐deformation response.
Initial Quenching Efficiency Determines Light‐Driven H2 Evolution of [Mo3S13]2− in Lipid Bilayers
Authors: Abbas Amir , Oswald Eva , Romer Jan , Lenzer Anja , Heiland Magdalena , Streb Carsten , Kranz Christine , Pannwitz Andrea 
Published: September 2023

AbstractNature uses reactive components embedded in biological membranes to perform light‐driven photosynthesis. Here, a model artificial photosynthetic system for light‐driven hydrogen (H2) evolution is reported. The system is based on liposomes where amphiphilic ruthenium trisbipyridine based photosensitizer (RuC9) and the H2 evolution reaction (HER) catalyst [Mo3S13]2− are embedded in biomimetic phospholipid membranes. When DMPC was used as the main lipid of these light‐active liposomes, increased catalytic activity (TONCAT ~200) was observed compared to purely aqueous conditions. Although all tested lipid matrixes, including DMPC, DOPG, DPPC and DOPG liposomes provided similar liposomal structures according to TEM analysis, only DMPC yielded high H2 amounts. In situ scanning electrochemical microscopy (SECM) measurements using Pd microsensors revealed an induction period of around 26 minutes prior to H2 evolution, indicating an activation mechanism which might be induced by the fluid‐gel phase transition of DMPC at room temperature. Stern‐Volmer‐type quenching studies revealed that electron transfer dynamics from the excited state photosensitizer are most efficient in the DMPC lipid environment giving insight for design of artificial photosynthetic systems using lipid bilayer membranes.
Synergistic Effect of Nitrogen/Phosphorus Co‐Doping and Molybdenum Carbide Induced Electron Redistribution of Carbon Layer to Boost Hydrogen Evolution Reaction†
Authors: Xiao Jiamin , Li Peng , Sun Yanyan , Liu Heng , Khan Javid , Zhang Handong , Zhou Han , Su Yaqiong , Wang Shuangyin , Han Lei 
Published: September 2023

Comprehensive SummaryThe development of highly efficient non‐precious‐metal‐based electrocatalysts for the hydrogen evolution reaction is imperative for promoting the large‐scale application of electrochemical water splitting. Herein, nitrogen/phosphorus co‐doped carbon nanorods encapsulated Mo2C nanoparticles (Mo2C@PNC) have been prepared by pre‐phosphating treatment in combination of the coordination with polydopamine and the subsequent pyrolysis. The phosphating temperature has a significant effect on the content of phosphorus within the resultant Mo2C@PNC, and the optimal catalyst delivers superior HER activity with the low overpotential of 104 mV at a current density of 10 mA·cm–2 and good stability for 8 h, which has been theoretically demonstrated to originate from the synergistic effect between P doping and Mo2C induced electron redistribution of nitrogen‐doped carbon layer.
Personalized lifetime prediction of survival and treatment benefit in patients with heart failure with reduced ejection fraction: The LIFE‐HF model
Authors: Burger Pascal M. , Savarese Gianluigi , Tromp Jasper , Adamson Carly , Jhund Pardeep S. , Benson Lina , Hage Camilla , Tay Wan Ting , Solomon Scott D. , Packer Milton , Rossello Xavier , McEvoy John W. , De Bacquer Dirk , Timmis Adam , Vardas Panos , Graham Ian M. , Di Angelantonio Emanuele , Visseren Frank L.J. , McMurray John J.V. , Lam Carolyn S.P. , Lund Lars H. , Koudstaal Stefan , Dorresteijn Jannick A.N. , Mosterd Arend ,   in collaboration with the European Society of Cardiology's Cardiovascular Risk Collaboration (ESC CRC)
Published: September 2023

AimsAlthough trials have proven the group‐level effectiveness of various therapies for heart failure with reduced ejection fraction (HFrEF), important differences in absolute effectiveness exist between individuals. We developed and validated the LIFEtime‐perspective for Heart Failure (LIFE‐HF) model for the prediction of individual (lifetime) risk and treatment benefit in patients with HFrEF.Methods and resultsCox proportional hazards functions with age as the time scale were developed in the PARADIGM‐HF and ATMOSPHERE trials (n = 15 415). Outcomes were cardiovascular death, heart failure (HF) hospitalization or cardiovascular death, and non‐cardiovascular mortality. Predictors were age, sex, New York Heart Association class, prior HF hospitalization, diabetes mellitus, extracardiac vascular disease, systolic blood pressure, left ventricular ejection fraction, N‐terminal pro‐B‐type natriuretic peptide, and glomerular filtration rate. The functions were combined in life‐tables to predict individual overall and HF hospitalization‐free survival. External validation was performed in the SwedeHF registry, ASIAN‐HF registry, and DAPA‐HF trial (n = 51 286). Calibration of 2‐ to 10‐year risk was adequate, and c‐statistics were 0.65–0.74. An interactive tool was developed combining the model with hazard ratios from trials to allow estimation of an individual's (lifetime) risk and treatment benefit in clinical practice. Applying the tool to the development cohort, combined treatment with a mineralocorticoid receptor antagonist, sodium–glucose cotransporter 2 inhibitor, and angiotensin receptor–neprilysin inhibitor was estimated to afford a median of 2.5 (interquartile range [IQR] 1.7–3.7) and 3.7 (IQR 2.4–5.5) additional years of overall and HF hospitalization‐free survival, respectively.ConclusionThe LIFE‐HF model enables estimation of lifelong overall and HF hospitalization‐free survival, and (lifetime) treatment benefit for individual patients with HFrEF. It could serve as a tool to improve the management of HFrEF by facilitating personalized medicine and shared decision‐making.
Exploration of Metal‐Metal Charge Transfer (MMCT) and its Effect in Generating New Colored Compounds in Mixed Metal Oxides
Authors: Shanmugapriya Indrani. G. , Mukherjee Supratik , Muñoz Alfonso , Vaitheeswaran Ganapathy , Natarajan Srinivasan 
Published: September 2023

AbstractCompounds belonging to the palmierite structure, (Zn3−xMx)A2O8 (M=Co, Ni, Cu and A=V, P) have been prepared employing solid state methods. The transition metal substituted compounds of Zn3V2O8 exhibits colors that are unique varying from mint green to forest green for Co2+ ions. The observed colors were understood based on the allowed d‐d transitions and metal to metal charge transfer (MMCT) transitions. The MMCT transitions involve partially filled d‐orbitals of Co2+ (3d7), Ni2+ (3d8), and Cu2+ (3d9) ions and the V5+ ions (3d0). The spinel compounds, Zn2−xCoxMO4 (M=Ti, Sn) were also prepared to understand the MMCT transitions in the compounds. Band structure calculations were carried out to understand the participating orbitals near the Fermi level and the band gap. The calculations support the idea that the substitution of transition elements in the palmierite structure reduces the overall band gap from 3.18 eV for Zn3V2O8 to 2.61 eV Zn2.5Co0.5V2O8 compound. This indicates the substitution of transition elements provide a tool towards band gap engineering.
Cross‐Electrophile Coupling between Two Different Tosylates Enabled by Nickel/Palladium Cooperative Catalysis
Authors: Qu Ruiling , Zhang Jinyu , Lian Zhong 
Published: September 2023

AbstractCross‐electrophile coupling reactions are efficient for the construction of carbon‐carbon bonds under relatively mild conditions, and hence widely used for making new molecules. Among various electrophiles, the cross‐electrophile coupling reaction between two different tosylates has been rarely studied. Herein, we present a cross‐electrophile coupling of gem‐difluoroalkenyl tosylate (C(sp2)−OTs) and α‐CF3 benzyl tosylate (C(sp3)−OTs) by nickel/palladium cooperative catalysis. Mechanistic investigation indicated that the activation of C(sp2)−OTs bond and C(sp3)−OTs bond was facilitated by nickel and palladium respectively.
Effect of CTMABr/SiO2 molar ratio in synthesis of micro‐mesoporous ZSM‐5 composite and its application in 5‐EMF (biofuel additive) formation
Authors: Manal Prajakta N. , Niphadkar Prashant S. , Nandanwar Sachin U. , Bokade Vijay V. 
Published: September 2023

AbstractSynthesis of micro‐mesoporous zeolite composite with optimum micro and mesoporosity is an emerging research area due to its wide applications, especially in bulk chemical or biomass transformations. It offers advantages in preserving zeolite crystallinity, creating mesoporosity and converting bulky molecules into valuable products. This work presents the process of preparing bimodal micro‐mesoporous ZSM‐5 using dual templates (CTMABr and TPABr). XRD, N2 adsorption–desorption, SEM, TEM, 29Si, and 27Al NMR were used to analyze the two‐dimensional micro‐mesoporous ZSM‐5. One‐step synthesis of bimodal micro‐mesoporous ZSM‐5 features dual micro/mesoporosity by a marginal decrease in the crystallinity (71%). Micro‐mesoporous ZSM‐5 composite was found to be dependent on the optimum CTMABr/SiO2 molar ratio of 0.04 to 0.06. The micro‐mesoporous ZSM‐5 zeolite composite was evaluated for cascade synthesis of 5‐EMF (methoxymethyl furfural‐ biofuel additive) from fructose and exhibited a five fold increase in 5‐EMF yield to 24.2% as compared with parent ZSM‐5 (4.6%).
Evolution trend analysis of carbon emissions in light industrial parks: A system dynamics approach
Authors: Zhang Weiguo , Lin Huijie , Zhu Qing , Gan Haiqing , Ren Yucheng , Yang Ziyue 
Published: September 2023

AbstractThe industrial sector is China's major element of energy consumption and carbon emissions, and carbon emissions reduction in industrial parks has become an important foothold in carbon reduction work. Predicting the future evolution trend of carbon emissions in industrial parks under different policy orientations is of great significance for China to achieve the carbon emissions peaking and carbon neutrality goals. Based on the current status of electricity consumption and carbon emissions in industrial parks, this paper takes a light industrial park as the research object, analyzes the source of carbon emissions in this park, combines the characteristics of resource endowment and industrial structure, and considers the factors influencing society, load curve, energy supply and carbon sink, thus constructing a system dynamics model of carbon emission evolution for this park. Different influencing factors are selected to set multiple target scenarios, and the GDP, carbon emissions, carbon emissions reduction and near‐zero carbon evaluation coefficient of light industrial parks are used as characterization indicators for simulation analysis. The analysis results revealed that the comprehensive scenario set by increasing the maximum installed capacity of renewable energy units and raising the proportions of environmental and science and technology inputs while adjusting the industrial growth rate of the park performed best. In this scenario, the economic development of the park and the process of carbon emissions reduction are considered.
Improved deep learning based multi‐index comprehensive evaluation system for the research on accuracy and real‐time performance of coal gangue particles recognition
Authors: Zhang Yao , Yang Yang , Zeng Qingliang 
Published: September 2023

AbstractThe problems of insufficient recognition accuracy, poor real‐time performance and lack of consideration of actual working conditions in the process of intelligent construction of coal mines make this technology still in the research stage and not applied in practical engineering. The purpose of this paper is to establish an accurate and real‐time recognition model, which can quickly distinguish the vibration acceleration signals of coal and gangue under the influence of external factors such as impact position, velocity, and direction by using the different physical properties of coal and gangue particles. Therefore, the accuracy and real‐time of coal gangue recognition model established by different convolutional neural networks (CNN) structures and different position signal input are studied. First, to meet the real‐time requirements, an original CNN recognition model composed of single convolution layer and single pooling layer is established, and the data collected by seven sensors are input in the form of two‐dimensional matrix. However, the stability of the training and test results is insufficient. To solve this problem, once improved CNN (OI‐CNN) recognition model with multiconvolution layers and multipooling layers is built by deepening the network. The experimental results show that the stability and accuracy are improved, but the real‐time performance is poor. Furthermore, through parameter adjustment, the OI‐CNN is changed to the twice improved CNN (TI‐CNN), and the sensor data at different positions are input in the form of one‐dimensional vectors. The results show that the accuracy and real‐time performance of the TI‐CNN coal gangue recognition model are further improved. Finally, according to the research purpose of this paper, the weights of CNN indexes are given, and a multi‐index comprehensive evaluation system (MICES) is established. With the original CNN recognition model as the control, the OI‐CNN recognition model and the TI‐CNN recognition model at different positions are quantitatively compared to obtain the comprehensive evaluation scores of each model. The results show that the MICES of the coal gangue recognition model established based on the TI‐CNN structure and the data input of a single position sensor is the highest, while the sensor position has little effect on the recognition results.
The expression of lncRNAs CASC2, NEAT1, LINC00299 in breast cancer tissues and their relationship with the XBP1 splicing rate in Iranian patients during 2014–2019: A cross‐sectional study
Authors: Orak Ghazal , Rezaei Hossein Babaahmadi , Ameli Fereshteh , Maghsoodi Fatemeh , Cheraghzade Maryam , Adelipour Maryam 
Published: September 2023

AbstractBackground and AimsBreast cancer is a leading cause of incidence and mortality in women globally. Identifying new molecular markers can aid in cancer diagnosis, targeted therapy, and treatment monitoring. This study aimed to measure the expression of the X‐box binding protein 1 (XBP1) gene, an index of the unfolded protein response (UPR), and long noncoding RNAs (lncRNAs), including Nuclear Enriched Abundant Transcript 1 (NEAT1), Cancer Susceptibility Candidate 2 (CASC2), and Long Intergenic Nonprotein Coding RNA 299 (LINC00299), as possible regulators of the UPR pathway.MethodsTotal RNA was extracted from 40 samples of breast tumor tissues and their respective controls. The expression level of lncRNAs CASC2, NEAT1, and LINC00299 was quantified using reverse transcription‐polymerase chain reaction (RT‐PCR). The ratio of the spliced form of XBP1 to its unspliced form (XBP1u) was determined by PCR and electrophoresis.ResultsThe results showed a 2.8‐fold increase in the ratio of XBP1s/u in breast cancer tissues compared to adjacent nonmalignant samples (p < 0.05). Additionally, the level of lncRNAs NEAT1, CASC2, and LINC00299 in breast tumor tissues increased significantly by twofold, 1.5‐fold, and 2.3‐fold, respectively, compared to adjacent nonmalignant samples (p < 0.05).ConclusionsBased on the association between the expression of lncRNAs CASC2, LINC00299, and NEAT1 and the XBP1s/u ratio, these lncRNAs could be potential regulators of the UPR pathway. Also, CASC2 and NEAT1 genes could be suggested as suitable biomarkers to distinguish cancerous tissue from noncancerous breast tissue due to their significant increase in expression in cancerous samples compared to adjacent noncancerous.
Molecular network mechanism of Shexiang Huayu Xingnao granules in treating intracerebral hemorrhage
Authors: Liu Ke‐Qian , Bai Xue , Chen Ji‐Lin , Chen Guo‐Jiao , Ameen Jamal Muhammad , He Yu‐Qi 
Published: September 2023

AbstractWe aim to explore the pharmacological efficacy and molecular network mechanism of Shexiang Huayu Xingnao granules (SX granules) in the treatment of intracerebral hemorrhage (ICH) based on experiments and network pharmacology. After the ICH model establishment, the behavioral functions of rats were assessed by the modified neurological severity score (mNSS), the wire suspension test, and the rotarod test. Brain histomorphological changes were observed using 2,3,5‐triphenyl tetrazolium chloride (TTC), hematoxylin–eosin (HE), Nissl, and TdT‐mediated dUTP nick end labeling (TUNEL) combined with neuronal nuclear (NEUN) immunofluorescence staining. The cross‐targets of SX granules and ICH were obtained using network pharmacology, gene ontology (GO) enrichment analysis, and Kyoto encyclopedia of genes and genomes (KEGG) signaling pathway analysis were performed. Then, the obtained Hub genes were verified using real‐time quantitative polymerase chain reaction (RT‐qPCR). The mNSS score was reduced and the duration to remain wire suspended increased in the SX group. In the morphological experiment, SX granules reduced brain tissue damage, neuronal apoptosis, and the number of astrocytes in the ICH rats. Moreover, 607 targets of drug–disease intersection were obtained by network pharmacology, and 10 Hub genes were found. SX granules regulated the expression of HRAS, MAPK3, and STAT3 in ICH condition. In conclusion, SX granules improved behavioral dysfunction, abnormal alterations in brain tissue, and cell morphology in ICH rats, and potential molecular mechanism was linked with the expression of multiple genes.
Limited Sampling Strategies for Estimating Busulfan Area Under the Concentration–Time Curve: Based on Peak and Trough Concentrations in Saliva
Authors: Xu Baohua , Zhou Jianxing , Zheng You , Xu Ruichao , Liu Qingxia , Li Dandan , Liu Maobai , Wu Xuemei 
Published: September 2023

AbstractTherapeutic drug monitoring for busulfan is currently performed by multiple plasma sampling. Saliva is considered a noninvasive therapeutic drug monitoring matrix. This study aimed to investigate intravenous busulfan pharmacokinetics (PK) in plasma and saliva, and establish a limited sampling strategy (LSS) for predicting the area under the concentration–time curve from time zero to infinity in plasma (AUC0‐∞,p) by using saliva samples. Therefore, the PK of busulfan was studied in 37 Chinese patients. Pearson correlation analysis was used to evaluate the correlation between the AUC of busulfan in plasma and saliva. LSS models were established by the multiple linear regression analysis. The prediction error, the mean prediction error, and the root mean square error were used to evaluate the predictive accuracy. The agreement between the predicted and observed AUC0‐∞ in saliva was investigated by the intraclass correlation coefficient and Bland–Altman analysis. The accuracy and robustness of the models were evaluated by using the bootstrap procedure. The result of PK analysis 62.2% of patients (23/37) was within the target range of AUC0‐∞,p. A good correlation between saliva and plasma busulfan AUC0‐∞ was observed (r = 0.63, p < .01). The bias and precision of the models 7 and 13 were less than 15%. The intraclass correlation coefficient exceeded 0.9, and the limits of agreement were within ±15%. The 2‐point LSS model in saliva is a convenient and desirable approach to predict the AUC0‐∞ of 4 times daily intravenous busulfan in plasma, which can be used to design personalized dosing for busulfan.