bluuebunny/crossref_metadata_2025_split huggingface dataset:
The diagnostic efficiency of artificial intelligence based 2 hours Holter monitoring in premature ventricular and supraventricular contractions detection
Authors: Huang Qiong , Fan Yuansheng , Wang Jialin , Xu Zhiyang , Yang Linfeng , Wang Junhong , Zhan Yiyang , Kong Xiangqing , Zhou Ningtian 
Published: April 2024

AbstractBackgroundElectrocardiography (ECG) and 24 hours Holter monitoring (24 h‐Holter) provided valuable information for premature ventricular and supraventricular contractions (PVC and PSVC). Currently, artificial intelligence (AI) based 2 hours single‐lead Holter (2 h‐Holter) monitoring may provide an improved strategy for PSVC/PVC diagnosis.HypothesisAI combined with single‐lead Holter monitoring improves PSVC/PVC detection.MethodsIn total, 170 patients were enrolled between August 2022 and 2023. All patients wore both devices simultaneously; then, we compared diagnostic efficiency, including the sensitivity/specificity/positive predictive‐value (PPV) and negative predictive‐value (NPV) in detecting PSVC/PVC by 24 h‐Holter and 2 h‐Holter.ResultsThe PPV and NPV in patients underwent 2 h‐Holter were 76.00%/87.50% and 96.35%/98.55, respectively, and the sensitivity and specificity were 79.17%/91.30%, and 95.65%/97.84% in PSVC/PVC detection compared with 24 h‐Holter. The areas under the ROC curves (AUCs) for PSVC and PVC were 0.885 and 0.741, respectively (p < .0001).ConclusionsThe potential advantages of the 2 h‐Holter were shortened wearing period, improved convenience, and excellent consistency of diagnosis.
Hydrogen Peroxide‐Induced Overoxidation of Fe−N−C Catalysts: Implications for ORR Activity
Authors: Morankar Ankita , Atanassov Plamen , Greeley Jeffrey 
Published: April 2024

AbstractFe−N−C (iron‐nitrogen‐carbon) electrocatalysts have emerged as promising alternatives to precious metals for the oxygen reduction reaction (ORR), but they remain insufficiently stable for widespread adoption in fuel cell technologies. One plausible mechanism to explain this lack of stability, and the associated catalyst degradation, is oxidative attack on the catalyst surface by hydrogen peroxide, a non‐selective byproduct of the ORR. In this work, we perform a detailed analysis of this degradation mechanism, using a combination of periodic Density Functional Theory (DFT) calculations and ab‐initio molecular dynamics (AIMD) simulations to probe the thermodynamics and kinetics of hydrogen peroxide activation on a series of candidate active sites for the Fe−N−C catalyst. The results demonstrate that carbon atoms neighbouring FeN4 active sites can be strongly over‐oxidized via formation of hydroxyl or epoxy groups when hydrogen peroxide is present in the electrolyte. In most cases, the interaction between the over‐oxidizing groups and the ORR reaction intermediates reduces the ORR activity, and we further propose that the over‐oxidized sites are likely precursors to irreversible carbon corrosion and further catalyst deactivation.
The role of the Terminal Benzene Derivatives in Triphenylamine‐Based Oxime Esters for Free Radical Photopolymerization
Authors: Hsieh Jyun‐Bin , Chen Yung‐Chung 
Published: April 2024

AbstractIn this study, we investigate the effect of terminal benzene derivatives in triphenylamine‐based oxime esters on their photoreactivity. Five novel oxime esters (Miko series) that containing different benzene derivatives as terminal groups, were synthesized. The electronic properties of the substituents on the benzene ring range from electron‐donating to electron‐withdrawing. Specifically, a methoxy benzene for Miko‐MOB, tert‐butyl benezene for Miko‐t‐Bu, chloro benzene for Miko‐CB, trifluoromethyl benzene for Miko‐TFM, and nitro benzene for Miko‐NB. Additionally, a compound with benzene only as the terminal substituent (TP‐1) was selected for comparision. All the new compounds exhibited higher molar extinction coefficients than TP‐1. Additionally, the steady‐state photolysis and electron spin resonance (ESR) properties would decrease from the electron‐donating substitutes to electron‐withdrawing substitutes. Finally, these oxime esters are utilized in Type I photoinitiating systems for the free radical polymerization of trimethylolpropane triacrylate (TMPTA) under UV or LED@405 nm light irradiation conditions. Among all formulations, Miko‐MOB demonstrated the highest double bond conversion efficiency under both UV and LED@405 nm light irradiation. Thus, terminal benzene derivatives in oxime esters play an important role in tuning the optical and photochemical reaction performance, offering significant value for the design strategy of such photoinitiators.
Pressure‐Induced Effects on BaPbO3: A Prospectively Valuable Material for Piezoelectric Applications via DFT
Authors: Alathlawi Hussain J. , Tariq Saad , Al‐Dossari Mawaheb , Mubarak A. A. , Saleem Muhammad , Saad H‐E M. Musa , Ali Mohsin , Kanwal Bushra 
Published: April 2024

AbstractEmploying density functional theory within the Wien2k code, first‐principle calculations are conducted to explore the impact of applied pressure up to 80 GPa on the structural, mechanical, thermal, and electronic characteristics of BaPbO3. Demonstrating metallic behavior with ductile attributes, BaPbO3 exhibits a decreasing anisotropic nature under escalating pressure. Evaluation of cubic elastic constants, optimization curves, and enthalpy of formation indicates the compound's mechanical and thermodynamic stability under high pressure conditions. Calculated values of C11 and C44 reflect heightened resistance to unidirectional compression and increased stiffness under pressure. These mechanical properties position BaPbO3 as a promising candidate for diverse industrial applications across varying pressure ranges, including utilization in piezoelectric materials (0–20 GPa) and high‐pressure sensors. Additionally, charge density contours suggest a combination of ionic (Ba─Pb) and covalent bonding (Pb─O) within the compound's constituent atoms. The material can exhibit potential applications as a piezoelectric sensor at 0–20 GPa, high‐pressure actuators ≈20 GPa, and as a high melting temperature resistive substrate for laser welding and cutting materials.
Mist Chemical Vapor Deposition Using Poorly Soluble Particles as Raw Material
Authors: Yamazaki Yuki , Nakamura Tsubasa , Kato Kodai , Hara Kazuhiko , Kouno Tetsuya 
Published: April 2024

AbstractMist chemical vapor deposition (mist‐CVD) is expected to be a potentially low‐environment‐impact and low‐cost crystal growth technique. With mist‐CVD, soluble materials are usually selected as raw materials, and mist is usually generated from an aqueous solution including raw materials. However, any substances to be included in the mist can be potentially supplied as raw materials. Namely, there is no need for the substances to be dissolved in some solvent. Therefore, as a trial, it is demonstrated that mist including poorly soluble particles are used as raw materials for mist‐CVD crystal growth.
Higher levels of virulence to multiple resistance genes were detected in Hessian fly (Mayetiola destructor) populations from Texas
Authors: Melson Ellen E. , Chen Ming‐Shun , Ibrahim Amir M. H. , Drake David, R. , Liu Shuyu , Sutton Russell , Zhu‐Salzman Keyan , Mays D. Tyler 
Published: April 2024

AbstractHessian fly is an important pest of wheat worldwide and is of particular importance in Texas and the southeastern United States. Texas is the highest wheat‐producing state that is severely impacted by this insect. The most effective control in these areas is an integrated pest management program, including resistant varieties of wheat. Hessian fly populations are genetically diverse and can rapidly become virulent to specific resistance genes once they are widely deployed in a region. Knowing the current virulence status of regional fly populations is important for wheat breeders and producers. In this study, a virulence analysis was conducted on populations sampled in the northeastern and central Texas regions. This analysis showed that resistance genes H12, H13, H20, H22, H25, H26, H28, H29, H32, H33, H34, and Hdic are still highly effective in these regions. However, it is also evident that Texas fly populations have become more virulent to existing genes in the past 10 years, with very high levels of virulence to resistance genes H3, H5, vH6, H7/H8, H9, H10, H14, H15, H23, H24, H31, and H35/H36.
2D TiO2 Nanosheets Decorated Via Sphere‐Like BiVO4: A Promising Non‐Toxic Material for Liquid Phase Photocatalysis and Bacterial Eradication
Authors: Hanif Muhammad Bilal , Bacova Jana , Berezenko Viktoriia , Zeng Yilan , Paluch Emil , Seniuk Alicja , Khan Muhammad Zubair , Rauf Sajid , Hussain Iftikhar , Motlochova Monika , Plesch Gustav , Monfort Olivier , Capek Jan , Dworniczek Ewa , Rousar Tomas , Motola Martin 
Published: April 2024

AbstractAn in‐depth investigation was conducted on a promising composite material (BiVO4/TiO2), focusing on its potential toxicity, photoinduced catalytic properties, as well as its antibiofilm and antimicrobial functionalities. The preparation process involved the synthesis of 2D TiO2 using the lyophilization method, which was subsequently functionalized with sphere‐like BiVO4 through wet impregnation. Finally, we developed BiVO4/TiO2 S‐scheme heterojunctions which can greatly promote the separation of electron‐hole pairs to achieve high photocatalytic performance. The evaluation of concentration‐ and time‐dependent viability inhibition was performed on human lung carcinoma epithelial A549 cells. This assessment included the estimation of glutathione levels and mitochondrial dehydrogenase activity. Significantly, the BiVO4/TiO2 composite demonstrated minimal toxicity towards A549 cells. Impressively, the BiVO4/TiO2 composite exhibited notable photocatalytic performance in the degradation of rhodamine B (k=0.135 min−1) and phenol (k=0.016 min−1). In terms of photoinduced antimicrobial performance, the composite effectively inactivated both gram‐negative E. coli and gram‐positive E. faecalis bacteria upon 60 minutes of UV‐A light exposure, resulting in a significant log 6 (log 10 CFU/mL) reduction in bacterial count. In addition, a 49 % reduction of E. faecalis biofilm was observed. These promising results can be attributed to the unique 2D morphology of TiO2 modified by sphere‐like BiVO4, leading to an increased generation of (intracellular) hydroxyl radicals, which plays a crucial role in the treatments of both organic pollutants and bacteria. This research has significant potential for various applications, particularly in addressing environmental contamination and microbial infections.
Small amplitude solitary electron acoustic wave for hot electrons taking regularized kappa distribution
Authors: Liu Yong , Wang Meng–Lei 
Published: April 2024

AbstractThe properties of small‐amplitude solitary electron acoustic waves in a plasma where the hot electrons take regularized kappa distribution are investigated via the reductive perturbation method. It is found there only exists the sup‐electron‐acoustic rarefactive soliton, the electron acoustic velocity is modified by the regularized kappa distribution. The amplitude and width of the electron acoustic soliton decrease monotonously with the increase of the exponential cutoff parameter of hot electrons. But they vary with respect to the spectral index non‐monotonously. As to the observed parameters in the Earth's inner magnetosphere, the speed, electric field strength, and the width of solitary electron acoustic wave are comparable with the observations.
RETRACTED: Efficient machine learning‐based hybrid resource allocation for device‐to‐device underlay communication in 5G wireless networks
Authors: Gopal Malle , T Velmurugan 
Published: April 2024

SummaryDevices in close proximity can directly communicate with each other through device‐to‐device (D2D) communication, bypassing the need for base stations. To minimize the delay for D2D active clients, we use a sequential approach to reuse cellular‐type resources. Unlike conventional methods that focus solely on uplink or downlink resource distribution, our study introduces a novel optimization technique to maximize network throughput. Our proposal incorporates a hybrid approach that combines both downlink and uplink techniques for resource allocation. We utilize random forest and game theory algorithms to ensure smooth D2D communication while reducing interference between cellular and D2D pairings. Our hybrid structure effectively addresses challenges arising from intra‐ and inter‐cell interferences resulting from spectrum reusability and deployment. This approach also improves power control and quality of service. Traditionally, NP‐hard optimization solutions are proposed for mixed‐integer nonlinear problems. In our study, the critical stages include channel assignment and energy allocation. The objective problem in resource allocation considers parameters such as the transmission power of D2D active clients, cellular users, connection distance, base stations, and quality of service constraints. Our proposed hybrid method aims to enhance overall spectrum efficiency and network throughput. Simulated results demonstrate the superiority of our modified hybrid technique compared to existing joint resource allocation methods. This comprehensive approach represents a significant advancement in addressing the complexities associated with D2D communication, offering improved efficiency and performance in contemporary network environments.
Analytical identification of dynamic structural models: Mass matrix of an isospectral lumped mass model
Authors: Sivori Daniele , Lepidi Marco , Cattari Serena 
Published: April 2024

AbstractCombining the accurate physical description of high‐fidelity mechanical formulations with the practical versatility of low‐order discrete models is a fundamental and open‐ended topic in structural dynamics. Finding a well‐balanced compromise between the opposite requirements of representativeness and synthesis is a delicate and challenging task. The paper systematizes a consistent methodological strategy to identify a physics‐based reduced‐order model (ROM) preserving the physical accuracy of large‐sized models with distributed parameters (REM), without resorting to classical techniques of dimensionality reduction. The leading idea is, first, to select a limited configurational set of representative degrees of freedom contributing significantly to the dynamic response (model reduction) and, second, to address an inverse indeterminate eigenproblem to identify the matrices governing the linear equations of undamped motion (structural identification). The physical representativeness of the identified model is guaranteed by imposing the exact coincidence of a selectable subset of natural frequencies and modes (partial isospectrality). The inverse eigenproblem is solved analytically and parametrically, since its indeterminacy can be circumvented by selecting the lumped mass matrix as the primary unknown and the stiffness matrix as a parameter (or vice versa). Therefore, explicit formulas are provided for the mass matrix of the ROM having the desired low dimension and possessing the selected partial isospectrality with the REM. Minor adjustments are also outlined to remove a posteriori unphysical effects, such as defects in the matrix symmetry, which are intrinsic consequences of the algebraic identification procedure. The direct and inverse eigenproblem solutions are explored through parametric analyses concerning a multistory frame, by adopting a high‐fidelity Finite Element model as REM and an Equivalent Frame model as ROM. Before mass matrix identification, modal analysis results indicate a general tendency of ROM to underestimate natural frequencies, with the underestimation strongly depending on the actual mass distribution of the structure. After the identification of the mass matrix and the elimination of unphysical defects, isospectrality is successfully achieved. Finally, extensions to prototypical highly massive masonry buildings are presented. The qualitative and quantitative discussion of the results under variation of the significant mechanical parameters provides useful insights to recognize the validity limits of the approximations affecting low‐order models with lumped parameters.
BlockSD‐5GNet: Enhancing security of 5G network through blockchain‐SDN with ML‐based bandwidth prediction
Authors: Rahman Anichur , Khan Md. Saikat Islam , Montieri Antonio , Islam Md. Jahidul , Karim Md. Razaul , Hasan Mahedi , Kundu Dipanjali , Nasir Mostofa Kamal , Pescapè Antonio 
Published: April 2024

AbstractThe fifth generation (5G) of mobile communications is the most exciting emerging technology for researchers and scientists to get the full benefit of a network system. However, 5G networks confront massive threats and vulnerabilities including protection, privacy, and secrecy. To face these challenges in the increasingly interconnected Internet of Things (IoT) scenario, we aim to leverage state‐of‐the‐art technologies as software defined networking (SDN) in conjunction with network function virtualization (NFV), blockchain, and machine learning (ML). Indeed, these technologies convey a robust and secure setting in the networking platform enabling to manage several criticalities related to security, privacy, flexibility, and performance. In light of these considerations, in this article, we propose the “BlockSD‐5GNet” architecture to efficiently improve the security of a 5G network and to exploit the combined advantages of Blockchain, SDN, NFV, and ML. In the proposed architecture, the SDN helps to manage the network by dividing it into data plane and control plane, while the Blockchain guarantees improved security and confidentiality. Therefore, the “BlockSD‐5GNet” architecture can both secure sensitive data and attain reliable data transfer within and between the 5G network‐infrastructure planes. Additionally, an ML module is integrated into the SDN controller to estimate network bandwidth and assist the administrator in taking effective decisions and satisfying high‐bandwidth demand. We assess the performance of the “BlockSD‐5GNet” architecture via an experimental evaluation performed in a simulation environment, and show the effectiveness of the proposed solution in comparison with baseline schemes. Finally, we also demonstrate the capability of different ML models in bandwidth prediction.
Research and mentorship in behavior analysis from a lens of cultural responsiveness and antiracism
Authors: Jimenez‐Gomez Corina 
Published: April 2024

AbstractAlthough scientific endeavors strive to be objective, they are the work of individuals whose unique perspectives and experiences influence their research and interpretations of the world and data. Much has been said and written lately about the need to embed cultural responsiveness in behavior analysis and the need to enhance diversity in the field. In fact, similar conversations are taking place in many areas of science. Despite the current buzz, many behavioral researchers may be left wondering what they can do or whether it is incumbent on them to act. For the field of behavior analysis to move toward adopting the values of diversity, equity, inclusion, and access, members of the scientific community must actively engage in behaviors that foster inclusive and safe learning environments for students, engage in collaborative work, and incorporate culturally responsive research and mentorship practices. This article will describe some current practices, showcase exemplars of culturally responsive research and mentorship, and provide resources for researchers and mentors.
Triglicerydes/high‐density lipoprotein ratio as a risk factor of post‐Covid‐19 sinus tachycardia: A retrospective study
Authors: Kuryłowicz Alina , Babicki Mateusz , Wąsowski Michał , Jankowski Piotr , Kapusta Joanna , Chudzik Michał 
Published: April 2024

AbstractInappropriate sinus tachycardia (IST) is one of the manifestations of the post‐COVID‐19 syndrome (PCS), which pathogenesis remains largely unknown. This study aimed to identify potential risk factors for IST in individuals with PCS. The 1349 patients with PCS were included into the study. Clinical examination, 24H Holter ECG, 24H ambulatory blood pressure monitoring and biochemical tests were performed 12–16 weeks after the COVID‐19 in all participants. IST was found in 69 (3.5%) individuals. In the clinical assessment IST patients were characterized by a higher age (p < 0.001) and lower prevalence of the diagnosed hypertension (p = 0.012), compared to remaining patients. Biochemical testing showed higher serum triglycerides (1.66 vs. 1.31 pmol/L, p = 0.007) and higher prevalence of a low high‐density lipoprotein (HDL) cholesterol (24.6% vs. 15.2%, p = 0.035) in the IST group. Subsequently, the triglicerydes (TG)/HDL ratio, an indicator of insulin resistance, was significantly higher in the IST individuals (3.2 vs. 2.4, p = 0.005). 24H monitoring revealed a significantly higher minimum diastolic, maximum systolic and mean arterial blood pressure values in the IST group (p < 0.001 for all), suggesting a high prevalence of undiagnosed hypertension. A multivariate analysis confirmed the predictive value TG/HDL ratio >3 (OR 2.67, p < 0.001) as predictors of IST development. A receiver operating characteristic curve analysis of the relationship between the TG/HDL ratio and the IST risk showed that the predictive cut‐off point for this parameter was 2.46 (area under the ROC curve = 0.600, p = 0.004). Based on these findings, one can conclude that insulin resistance seems to be a risk factor of IST, a common component of PCS.
Impact of cannabidiol on brain glucose metabolism of C57Bl/6 male mice previously exposed to cocaine
Authors: Spelta Lidia Emmanuela Wiazowski , Real Caroline Cristiano , Bruno Vitor , Buchpiguel Carlos Alberto , Garcia Raphael Caio Tamborelli , Torres Larissa Helena , de Paula Faria Daniele , Marcourakis Tania 
Published: April 2024

AbstractDespite evidence of the beneficial effects of cannabidiol (CBD) in animal models of cocaine use disorder (CUD), CBD neuronal mechanisms remain poorly understood. This study investigated the effects of CBD treatment on brain glucose metabolism, in a CUD animal model, using [18F]FDG positron emission tomography (PET). Male C57Bl/6 mice were injected with cocaine (20 mg/kg, i.p.) every other day for 9 days, followed by 8 days of CBD administration (30 mg/kg, i.p.). After 48 h, animals were challenged with cocaine. Control animals received saline/vehicle. [18F]FDG PET was performed at four time points: baseline, last day of sensitization, last day of withdrawal/CBD treatment, and challenge. Subsequently, the animals were euthanized and immunohistochemistry was performed on the hippocampus and amygdala to assess the CB1 receptors, neuronal nuclear protein, microglia (Iba1), and astrocytes (GFAP). Results showed that cocaine administration increased [18F]FDG uptake following sensitization. CBD treatment also increased [18F]FDG uptake in both saline and cocaine groups. However, animals that were sensitized and challenged with cocaine, and those receiving only an acute cocaine injection during the challenge phase, did not exhibit increased [18F]FDG uptake when treated with CBD. Furthermore, CBD induced modifications in the integrated density of NeuN, Iba, GFAP, and CB1R in the hippocampus and amygdala. This is the first study addressing the impact of CBD on brain glucose metabolism in a preclinical model of CUD using PET. Our findings suggest that CBD disrupts cocaine‐induced changes in brain energy consumption and activity, which might be correlated with alterations in neuronal and glial function.