bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of mechanical and electrical properties of photopolymer nanocomposites reinforced with carbon‐based nanoparticles produced by digital light processing 3D printing technique
Authors: Eren Oğulcan , Yüksel Nurullah , Şahin İsmail 
Published: November 2024

AbstractDigital Light Processing (DLP) techniques are being increasingly investigated to create advanced composite materials with improved properties by incorporating a variety of nanoparticles. In this study, the mechanical and electrical properties of photopolymer nanocomposite materials reinforced with carbon‐based nanoparticles produced by DLP were investigated. The nanocomposites were produced by incorporating varying proportions of Multi‐Walled Carbon Nanotubes (MWCNT), reduced Graphene Oxide (rGO), and combinations of Carbon Black and Carbon Nanotubes (CB/CNT) into the photopolymer matrix. The mechanical properties of the nanocomposites were assessed by tensile testing, while their electrical conductivity was determined using the four‐point probe technique. This study was the first to investigate the most effective concentrations of three distinct carbon‐based nanoparticles and the impact of their homogeneous distribution on the performance of composites with a holistic approach. The morphological analysis of the composites, conducted using optical microscopy and Scanning Electron Microscopy (SEM), revealed the critical role of nanoparticle distribution in determining composite properties. The findings indicate that the incorporation of nanoparticles at low proportions (up to 0.5 wt%) resulted in a significant improvement, with up to an 82% increase in the ultimate tensile strength of the photopolymer. Nevertheless, as the nanoparticle ratio increased, a rise in material brittleness and a decrease in mechanical strength were observed. On the other hand, electrical conductivity showed a significant increase when the percolation threshold was exceeded in the composites reinforced with MWCNT (0.5%wt) and CB/CNT (0.75%wt).Highlights
The properties of DLP composites with carbon nanoparticles are investigated.
SEM analysis shows nanoparticle dispersion's key role in composite performance.
0.5% rGO reinforcement boosts tensile strength by up to 82%.
Conductivity surges at 0.5% MWCNT, surpassing the percolation threshold.
High nanoparticle ratios increase composite brittleness.
Study on the mechanism of waterborne polyurethane modified ultrafine ground calcium carbonate and its properties in polypropylene plastics
Authors: Yang Xianrong , Shuai Huan , Du Gaoxiang , Wang Jiao , Shen Jie 
Published: November 2024

AbstractGround calcium carbonate (GCC) has the effect of reducing the incremental cost and improving the application performance as a plastic filler. In this study, waterborne polyurethane (WPU) was employed as a novel modifier for the wet modification of GCC. Polypropylene (PP)‐based composites incorporating GCC were then prepared for mechanical properties testing. The oil absorption value, wetting contact angle, and settling time in kerosene indicated that the modified GCC achieved an excellent modification effect with a WPU dosage of 2.0 wt%. The X‐ray Diffraction, Fourier Transform Infrared Spectroscopy, and X‐ray Photoelectron Spectroscopy results indicate that WPU was successfully coated on the surface of the GCC. SEM images revealed improved wettability and compatibility of GCC in the composites after modification. The mechanical tests showed that the GCC‐WPU/PP composites exhibited enhanced properties, including a flexural strength of 107 MPa, impact strength of 9.54 kJ/m2, tensile strength of 29.7 MPa, and an elongation at break of 30.9%.Highlights
WPU was innovatively used as a modifier of GCC.
An optimal modification effect was gained at the low dosage (2.0 wt%).
GCC has excellent compatibility and wettability in PP composites.
The obtained PP‐based composites have better mechanical properties.
The study has the potential to apply GCC in plastics and other industries.
A PDZ tandem repeat folds and unfolds via different pathways
Authors: Pennacchietti Valeria , di Matteo Sara , Pagano Livia , Toplek Fran Bačić , Stegani Bruno , Toto Angelo , Toso Julian , Puglisi Elena , Capelli Riccardo , Di Felice Mariana , Malagrinò Francesca , Camilloni Carlo , Gianni Stefano 
Published: November 2024

AbstractProtein folding and unfolding experiments are interpreted under the assumption of microscopic reversibility, that is, that at equilibrium one process is the reverse of the other. Single‐domain proteins illustrate the validity of such an interpretation, although reversibility does not necessarily hold under the different conditions typically used for folding and unfolding experiments. In fact, more complex proteins, which often exhibit irreversible unfolding, are generally considered not amenable to folding kinetics studies. Here, the X11 PDZ1‐PDZ2 tandem repeat allows us to reveal the different folding and unfolding pathways at play under different experimental conditions, thus reconciling the apparent contradiction between theory and experiment.
Event‐Based Formation Control for Multi‐UAV Systems Under DoS and Deception Attacks
Authors: Pan Kunpeng , Yang Feisheng , Lyu Yang , Ji Mingyue , Tan Zheng , Pan Quan 
Published: November 2024

ABSTRACTIntermittent random denial‐of‐service attacks (IRDoS) and deception attacks in multi‐UAV systems (MUAVs) can present significant security challenges. The intrusions of IRDoS attacks and deception attacks, respectively, can interrupt the network communication among followers and manipulate the received neighbor information with a certain probability, failing MUAVs to complete the formation task. A secure formation controller is developed for MUAVs in the presence of IRDoS and deception attacks, utilizing a distributed dynamic event‐triggered mechanism (DETM). Unlike the static event‐triggered mechanism, the triggering threshold of the DETM is adaptively adjustable, which can reduce data transmission and save network resources. The stability of the system is analyzed, and sufficient conditions are derived. Additionally, the duration and probability of successful attacks are examined. Ultimately, the simulation results showcase the efficacy and superiority of the suggested approach.
Statistical Inference for Box–Cox based Receiver Operating Characteristic Curves
Authors: Bantis Leonidas E. , Brewer Benjamin , Nakas Christos T. , Reiser Benjamin 
Published: November 2024

ABSTRACTReceiver operating characteristic (ROC) curve analysis is widely used in evaluating the effectiveness of a diagnostic test/biomarker or classifier score. A parametric approach for statistical inference on ROC curves based on a Box–Cox transformation to normality has frequently been discussed in the literature. Many investigators have highlighted the difficulty of taking into account the variability of the estimated transformation parameter when carrying out such an analysis. This variability is often ignored and inferences are made by considering the estimated transformation parameter as fixed and known. In this paper, we will review the literature discussing the use of the Box–Cox transformation for ROC curves and the methodology for accounting for the estimation of the Box–Cox transformation parameter in the context of ROC analysis, and detail its application to a number of problems. We present a general framework for inference on any functional of interest, including common measures such as the AUC, the Youden index, and the sensitivity at a given specificity (and vice versa). We further developed a new R package (named ‘rocbc’) that carries out all discussed approaches and is available in CRAN.
Simulating New Fusidic Acid Derivatives to Target Gram‐Positive Bacteria by Using Computational Methods
Authors: Hossain Md. Shamim , Sakib Mohiuddin , Rahman Shofiur , Al‐Gawati Mahmoud A. , Alodhayb Abdullah N. , Albrithen Hamad , Hossain Md. Mainul , Poirier Raymond A. , Uddin Kabir M. 
Published: November 2024

AbstractGram‐positive bacteria represent a significant threat due to their resistance to conventional antibiotics. This study employs computational methods to investigate fusidic acid (FA) derivatives (1–24) as potential antibiotics against Gram‐positive bacteria. Techniques such as density functional theory calculations, molecular docking, and molecular dynamics simulations were utilized to evaluate ligand interactions with target proteins Staphylococcus aureus (S. aureus) elongation factor G (fusA) (2XEX), fusidic acid resistance protein (fusB) (4ADN), and fusidic acid resistance protein (fusC) (2YB5), comparing them to established antibiotics (ceftobiprole, linezolid, vancomycin). Notably, ligand 16 demonstrated a remarkable binding affinity to the S. aureus elongation factor G protein (−8.7 kcal mol⁻¹), closely aligning with both in vitro and in vivo results and outperforming fusidic acid and reference drugs. In silico methods (SwissADME, AdmetSAR, Molinspiration, Molsoft) were used to assess pharmacokinetics and drug‐likeness. Molecular dynamics (MD) simulations confirmed superior S. aureus elongation factor G stability for ligands fusidic acid 1, (Z)‐2‐((3R,4S,8S,9R,10S,11R,13S,14S,16S)‐16‐acetoxy‐3,11‐dihydroxy‐4,8,10,14‐tetramethylhexadecahydro‐17H‐cyclopenta[a]phenanthren‐17‐ylidene)‐5‐cyclohexylidene‐ pentanoic acid (14), (Z)‐2‐((3R,4S,8S,9R,10S,11R,13S, 14S,16S)‐16‐acetoxy‐3,11‐dihydroxy‐4,8,10,14‐tetramethylhexadecahydro‐17H‐cyclopenta[a]phenanthren‐17‐ylidene)‐5cyclohexylidenepentanoic acid (16), and (Z)‐2‐((3R,4S,8S,9R,10S,11R,13S,14S,16S)‐16‐acetoxy‐3,11‐dihydroxy‐4,8,10,14‐tetramethylhexadecahydro‐17H‐cyclopenta[a]phenanthren‐17‐ylidene)‐5‐cyclopentylidenepentanoic acid (17), with ligand 16 exhibiting exceptional stability across various temperatures, especially at human body temperature (310 K). Further molecular dynamics simulations of ligand 16 validated its robust stability and potential to disrupt S. aureus elongation factor G, supporting the docking results and showing strong consistency with in vitro and in vivo findings. Consequently, ligand 16 emerges as a promising candidate for further development as an anti‐Gram‐positive bacterial drug, pending validation through rigorous clinical trials.
Plausible Colloidal Methods to Synthesize Semiconductor Nanowires: Deep Study From ZnSe Nanorods
Authors: Yu Chunyu , Li Yibo , Qin Yue , Wang Yinghui , Ning Jiajia 
Published: November 2024

AbstractWhen the diameter of semiconductor nanowires is below the Bohr radius, confined excitons in the radial direction can freely move along the elongated axis direction, highlighting their potential for applications in quantum information and optoelectronic devices. Controlled anisotropic growth and oriented attachment are viable strategies for producing ultra‐long semiconductor nanowires with precisely controlled lengths and diameters. Anisotropic ZnSe nanorods are used as the initial seeds for the controlled anisotropic growth and oriented attachment methods. ZnSe nanorods/nanowires with limiting lengths of tens to hundreds of nanometers are produced. The advantages and limitations of semiconductor nanowires via controlled anisotropic growth and oriented attachment are summarized. The perspective for the promotion of controlled anisotropic growth and oriented attachment is discussed, which allows to promotion of the precise synthesis of semiconductor ultra‐long nanowires to develop the fundamental research and applications of ultra‐long semiconductor nanowires.
Governance in the time of COVID‐19: Systemic implications for governing in an Anthropocene world based on experiences from Australia and Brazil
Authors: Ison Ray L. , Schlindwein Sandro L. 
Published: November 2024

AbstractThe disruption of the COVID‐19 pandemic reveals that contemporary governance systems are not fit for purpose as we progress our living in a human‐induced Anthropocene world. Governance failings of a cybersystemic nature are highlighted through a comparative case study undertaken as a systemic co‐inquiry of acts of governing in relation to pandemic effects in Australia and Brazil. Drawing on recent governance scholarship, key praxis failures in governing were revealed. The systemic implications were explored using a narrative analysis plus use of a simple diagnosis and design heuristic based on 14 cybersystemic conceptual elements. Arguments and evidence for the pressing need to institutionalise cybersystemic governance practices are presented, highlighting how they are critical to systemic design of effective governance systems. Considering that the human‐induced Anthropocene world and climate emergency will have similar patterns to the pandemic, the proposed design heuristic within a rapidly assembled systemic co‐inquiry process has the potential to facilitate dialogue and design for imagining and enacting new alternative governance systems.
Use of Dependency‐Annotated Learner Corpora in Measuring Syntactic Complexity for Granularity, Accuracy, Consistency, and Transparency: Implications for Research and Teaching
Authors: Zhang Yujie , Zhang Lawrence Jun 
Published: November 2024

AbstractSyntactic complexity has long been used to gauge language learners' performance, proficiency, and development, offering language teachers valid recommendations for syllabus design and materials development. Progress in syntactic complexity research foreshadows the imperative of measuring syntactic features at a high level of granularity, which remains, however, inadequately represented in the current operationalization of syntactic complexity. Beyond this misalignment, researchers also caution against the issues of consistency and accuracy in its measurement. We thus advocate for a methodological synergy by combining automatized dependency annotation and self‐built learner corpora, arguing that this can effectively address the aforementioned concerns and promote the initiative for transparency and openness in applied linguistics. Next, we concisely showcase how to manage this method step by step, which can be done easily with tools, and some practical considerations, so researchers and teachers can compile their do‐it‐yourself corpora. We conclude by discussing the implications of adopting this method for research and teaching. How this method can figure into potential areas of inquiry is identified with examples, including task‐based language teaching, writing assessment, and additional language syntactic acquisition. Pedagogically, we illustrate how this method can help language teachers identify gaps in learners' language production, raise their language awareness, and inform learner‐centered instruction.
Global Financial Market Spillovers to the Dhaka Stock Exchange: Strategic Insights From Trade‐Friendly Nations
Authors: Borman Tanmay , Nahiduzzaman Md. , Kuri Bapon Chandra , Dhar Bablu Kumar , Sarker Sanjoy Kumar 
Published: November 2024

ABSTRACTThis study explores the strategic implications of global financial market spillovers on the Dhaka Stock Exchange (DSE), with a particular emphasis on the financial markets of Bangladesh's key trade partners. Leveraging daily price data, the analysis focuses on major equity indices from Bangladesh, the USA, China, Japan, Russia, and India, in addition to global green and commodity indices. The study employs advanced methodologies, including value at risk (VaR), conditional value at risk (CVaR), continuous wavelet transforms (CWT), wavelet coherence (WC), and time‐varying parameter vector autoregression (TVP‐VAR). The findings reveal that while the DSE demonstrates lower downside risk relative to global indices, certain global assets, such as WTICO, exhibit heightened tail risk. The wavelet analyses underscore significant volatility and co‐movements among key assets, particularly during periods of global crises, such as the COVID‐19 pandemic and the Russia–Ukraine conflict, highlighting the profound interconnectedness between global and regional markets and the DSE. Notably, global green and commodity assets provide potential safe haven benefits for Bangladeshi investors during times of crisis. The TVP‐VAR model further highlights the dynamic nature of volatility spillovers, identifying global green indices as key volatility transmitters, while the DSE retains robust internal market dynamics with reciprocal spillovers between DSE30 and DSEB. These insights suggest that Bangladesh should strategically integrate green and commodity assets into its financial markets to bolster market stability and protect investors amidst global uncertainties.
Embedded Many‐Body Green's Function Methods for Electronic Excitations in Complex Molecular Systems
Authors: Tirimbó Gianluca , Sundaram Vivek , Baumeier Björn 
Published: November 2024

ABSTRACTMany‐body Green's function theory in the GW approximation with the Bethe–Salpeter equation (BSE) provides a powerful framework for the first‐principles calculations of single‐particle and electron–hole excitations in perfect crystals and molecules alike. Application to complex molecular systems, for example, solvated dyes, molecular aggregates, thin films, interfaces, or macromolecules, is particularly challenging as they contain a prohibitively large number of atoms. Exploiting the often localized nature of excitation in such disordered systems, several methods have recently been developed in which GW‐BSE is applied to a smaller, tractable region of interest that is embedded into an environment described with a lower‐level method. Here, we review the various strategies proposed for such embedded many‐body Green's functions approaches, including quantum–quantum and quantum–classical embeddings, and focus in particular on how they include environment screening effects either intrinsically in the screened Coulomb interaction in the GW and BSE steps or via extrinsic electrostatic couplings.
Geometric Theory of Perturbation Dynamics Around Non-equilibrium Fluid Flows
Authors: Holm Darryl D. , Hu Ruiao , Street Oliver D. 
Published: November 2024

AbstractThe present work investigates the evolution of linear perturbations of time-dependent ideal fluid flows with advected quantities, expressed in terms of the second order variations of the action corresponding to a Lagrangian defined on a semidirect product space. This approach is related to Jacobi fields along geodesics and several examples are given explicitly to elucidate our approach. Numerical simulations of the perturbation dynamics are also presented.
On Forward–Backward SDE Approaches to Conditional Estimation
Authors: Kim Jin Won , Reich Sebastian 
Published: November 2024

AbstractIn this chapter, we investigate the representation of conditional expectation values for partially observed diffusion processes in terms of appropriate estimators. The work of Kalman and Bucy has established a duality between filtering and estimation in the context of time-continuous linear systems. This duality has recently been extended to time-continuous nonlinear systems in terms of an optimization problem constrained by a backward stochastic partial differential equation. Here we revisit this problem from the perspective of appropriate forward-backward stochastic differential equations. Our approach sheds new light on the conditional estimation problem and provides a unifying perspective. It is also demonstrated that certain formulations of the estimation problem lead to deterministic formulations similar to the linear Gaussian case as originally investigated by Kalman and Bucy. Finally, we discuss an application of the proposed formulation to optimal control problem on partially observed diffusion processes.
Data Assimilation for the Stochastic Camassa-Holm Equation Using Particle Filtering: A Numerical Investigation
Authors: Cotter Colin J. , Crisan Dan , Singh Maneesh Kumar 
Published: November 2024

AbstractIn this study, we explore data assimilation for the Stochastic Camassa-Holm equation through the application of the particle filtering framework. Specifically, our approach integrates adaptive tempering, jittering, and nudging techniques to construct an advanced particle filtering system. All filtering processes are executed utilizing ensemble parallelism. We conduct extensive numerical experiments across various scenarios of the Stochastic Camassa-Holm model with transport noise and viscosity to examine the impact of different filtering procedures on the performance of the data assimilation process. Our analysis focuses on how observational data and the data assimilation step influence the stability of the obtained results.
A Central Limit Theorem for Random Disc-Polygons in Smooth Convex Discs
Authors: Fodor Ferenc , Papvári Dániel I. 
Published: November 2024

AbstractIn this paper we prove a quantitative central limit theorem for the area of uniform random disc-polygons in smooth convex discs whose boundary is $$C^2_+$$

C
+
2

. We use Stein’s method and the asymptotic lower bound for the variance of the area proved by Fodor, Grünfelder and Vígh (Doc Math 27: 1015-1029, 2022).
An efficient claim management assurance system using EPC contract based on improved monarch butterfly optimization models
Authors: Mukilan K. , Rameshbabu C. , Baranitharan B. , Muthusamy Suresh , Ramamoorthi Ponarun , Sadasivuni Kishor Kumar , Oflaz Kamil , Khan Anish 
Published: November 2024

Abstract
The Engineering Procurement Construction (EPC) contract systems are widely employed in the construction industry. Among the prevalent issues in this sector, cash flow problems frequently lead to decreased productivity and efficiency. To address these challenges, a claim management system is developed based on the Improved Monarch Butterfly Optimization Algorithm (IMBOA) and the principles of EPC. Conventional construction models typically optimize only a single objective, such as time, cost, or delay, which may not effectively enhance overall performance. This study aims to develop a claim management system based on IMBOA and EPC principles to optimize multiple objectives, focusing on minimizing project costs and time delays while ensuring high-quality results. The basic methodology of this research involves integrating EPC and claim management principles with the IMBOA algorithm to create an efficient, high-quality system. This process starts with a comprehensive literature review on EPC, claims, MBOA, and related algorithms. Common disputes and claims in the construction industry are examined, and critical factors influencing these claims are identified. The Monarch Butterfly Optimization Algorithm (MBOA) and its improved version (IMBOA) are explored for their application in optimizing project performance. A case study in China's coal mining industry evaluates the effectiveness of the EPC approach, demonstrating that it minimizes time delays and costs. The IMBOA approach proposed in this study has the potential to mitigate 23% of risks and avoid 32% of risks associated with the action plan of China's coal mining industry. Furthermore, comparative analysis with other optimization models indicates that the developed IMBOA model yields superior results, reducing overall project time by 15% and cost by 18%.