bluuebunny/crossref_metadata_2025_split huggingface dataset:
Based on Molecular Docking, Molecular Dynamics Simulation and MM/PB(GB)SA to Study Potential Inhibitors of PRRSV‐Nsp4
Authors: Shi Tianyu , Chang Wenzhou , Wei Xinyu , Kong Yiling , Wei Ying 
Published: October 2024

ABSTRACTPorcine reproductive and respiratory syndrome (PRRS) is one of the most serious infectious immunosuppressive diseases in the world. The nonstructural protein Nsp4 can be used as an ideal target for anti‐PRRSV replication inhibitors. However, little is known about potential inhibitors that target Nsp4 to affect PRRSV replication. The purpose of this study was to screen potential natural inhibitors that affect PRRSV replication by inhibiting Nsp4. Five compounds with strong binding affinity to Nsp4 were selected by structure‐based molecular docking method. The complexes of naringin dihydrochalcone (NDC), agathisflavone (AGT), and amentoflavone (AMF) with Nsp4 were stable throughout the molecular dynamics simulation. According to MM/PBSA analysis, the free energies of binding of NDC, AGT, and AMF to Nsp4 were less than—30 Kcal/mol. In conclusion, these three compounds are worthy of further investigation as novel inhibitors of PRRSV. This study provides a theoretical basis for the development of anti‐PRRSV natural drugs.
Classical and Bayesian inference of Cpc$\mathcal {C}_{pc}$ for Wilson–Hilferty distribution under progressively first‐failure type‐II censoring samples
Authors: Al‐Mosawi Riyadh R. , Dey Sanku 
Published: October 2024

AbstractThis study uses two frequentist approaches and the Bayesian method of estimation using progressively first‐failure type‐II censored data to estimate process capability index (PCI), , for the Wilson–Hilferty (WH) distribution. A competitive maximum product of spacing (MPS) method for estimation of is proposed in the frequentist method as an alternative to conventional likelihood (LK)‐based estimation. We have also taken into account the PS function in the Bayesian setup as an alternative to the conventional LK function, and both LK and PS‐based Bayesian estimates are given for . Further, the Bayes estimates are evaluated by applying Tierney–Kadane (TK) approximation method and Markov chain Monte Carlo (MCMC) method with the help of both LK and PS functions and Jeffrey's prior. Additionally, the approximate confidence intervals based on the suggested frequentist techniques as well as the Bayes highest posterior density (HPD) credible intervals are built for the index . In addition, two bootstrap confidence intervals are obtained. In the simulation exercise, the performance of the Bayes and traditional estimates of is assessed in terms of their mean squared errors, and the average width and coverage probabilities of the CIs and HPD intervals are compared. An actual data set from the electronic industries is reanalyzed in order to show the efficacy of the proposed index and estimation methodology.
Benchmarking Quantum Computational Advantages on Supercomputers
Authors: Wu Junjie , Liu Yong 
Published: October 2024

AbstractThe achievement of quantum computational advantage, also known as quantum supremacy, is a major milestone at which a quantum computer can solve a problem significantly faster than the world's most powerful classical computers. Two tasks, boson sampling and random quantum circuit sampling, have experimentally exhibited quantum advantages on photonic and superconducting platforms respectively. Classical benchmarking is essential, yet challenging, because these tasks are intractable for classical computers. This study reviews models, algorithms and large‐scale simulations of these two sampling tasks. These approaches continue to hold substantial significance for research in both current noisy intermediate‐scale quantum (NISQ) systems and future fault‐tolerant quantum computing.
Maximum Entropy Methods for Quantum State Compatibility Problems
Authors: Hou Shi‐Yao , Wu Zipeng , Zeng Jinfeng , Cao Ningping , Cao Chenfeng , Li Youning , Zeng Bei 
Published: October 2024

AbstractInferring a quantum system from incomplete information is a common problem in many aspects of quantum information science and applications, where the principle of maximum entropy (MaxEnt) plays an important role. The quantum state compatibility problem asks whether there exists a density matrix compatible with some given measurement results. Such a compatibility problem can be naturally formulated as a semidefinite programming (SDP), which searches directly for the existence of a . However, for large system dimensions, it is hard to represent directly, since it requires too many parameters. In this work, MaxEnt is applied to solve various quantum state compatibility problems, including the quantum marginal problem. An immediate advantage of the MaxEnt method is that it only needs to represent via a relatively small number of parameters, which is exactly the number of the operators measured. Furthermore, in case of incompatible measurement results, the method will further return a witness that is a supporting hyperplane of the compatible set. The method has a clear geometric meaning and can be computed effectively with hybrid quantum‐classical algorithms.
A Natural History Study of Hindlimb Physiology and Histopathology in a Heterozygous OPMD Mouse Model
Authors: Amaya Jorge Miguel , van Zanen‐Gerhardt Sofie , Suidgeest Ernst , de Greef Jessica C. , van der Weerd Louise , Cameron Donnie , Coenen de Roo Christina J. J. , van Putten Maaike , Raz Vered 
Published: October 2024

ABSTRACTBackgroundOculopharyngeal muscular dystrophy (OPMD) is an adult‐onset autosomal dominant myopathy. OPMD is caused by a short alanine expansion in the gene encoding for poly(A) binding protein nuclear 1 (PABPN1) forming insoluble nuclear aggregates. OPMD patients are predominantly heterozygous, and the knock‐in Pabpn1+/A17 mouse, which expresses one copy of the expanded Pabpn1 gene under the PABPN1 promoter genetically, mimics OPMD. Insights into the A17/+ mouse model are necessary to evaluate its preclinical value and test therapeutics for OPMD. Here, we performed a natural disease history study for the A17/+ model.MethodsWe combined muscle force measurements of the tibialis anterior with magnetic resonance imaging (MRI) measurements of the calf muscles made in 4‐, 8‐ and 12‐month‐old wild‐type and A17/+ mice. These measures were complemented by muscle histopathology staining and image quantification to detect PABPN1 aggregates and to assess muscle wasting. Statistical significance between genotypes over the three time points was assessed using ANOVA or Student's t test.ResultsPABPN1 nuclear aggregates were found in the 12‐month‐old A17/+ mice at similar quantities of ~2% across hindlimb muscles. We did not observe changes in muscle strength of the tibialis anterior in A17/+ mice. MRI analyses of hindlimb muscles revealed no metabolic difference, no fatty infiltration and limited muscle atrophy between A17/+ and +/+ mice. The plantaris muscle in A17/+ showed 30% atrophy at 12 months of age, which was corroborated by a 30% myofiber shift in the myosin heavy chain −2A to −2B ratio. Histopathologic staining did not reveal muscle wasting in the hindlimb muscles.ConclusionsDespite the presence of PABPN1 insoluble aggregates in hindlimb muscles, muscle involvement in the 12‐month‐old A17/+ mice was limited. Our results query the usefulness of A17/+ hindlimb muscles for preclinical studies.
Predefined‐time impedance control of free‐flying flexible‐joint space robots for force sensor‐less target capturing with prescribed performance
Authors: Gu Xiutao , Liu Liaoxue , Wang Lu , Mao Jianheng , Guo Yu 
Published: October 2024

AbstractAiming at safely capturing faulty satellites on orbit, a novel predefined‐time impedance controller is designed to address the control challenges of free‐flying flexible‐joint space robots (FFSR) considering output constraint. The FFSR system model is transformed into a singularly perturbed form consisting of both fast and slow subsystems. For the slow subsystem, an adaptive predefined‐time sliding mode observer is developed to obtain the contact torque between the end‐effector and the target. To mitigate overshooting and enhance tracking precision, a predefined‐time prescribed performance function is proposed, and the output constraint issue is reformulated as a coordinate transformation problem involving the trajectory tracking errors. Based on these, a predefined‐time impedance controller is designed to achieve the compliant capture of the target. For the fast subsystem, a new non‐singular fixed‐time controller is proposed to rapidly overcome the vibration of the flexible joints. Stability analysis proves predefined‐time stability of the FFSR system and the tracking errors can be maintained within a predefined region. Finally, numerical simulations indicate the feasibility and validity of the presented control strategy.
Four‐Wheeled Mobile Robot With Flexible Posture Control
Authors: Lan Tianxiang , Yang Guotian 
Published: October 2024

ABSTRACTThis paper presents a novel wheeled robot with adaptive suspensions to maintain a stable body posture when driving uneven roads. Each robot suspension is driven by a brushless geared motor, eliminating the traditional mechanical shock absorber. We design a virtual spring‐damping system using force control to solve the problem of uneven support and high‐frequency oscillation on four wheels. Subsequently, we incorporated a flexible posture control that uses the chassis posture as feedback and linearized the control to improve the dynamic response. Finally, the prototype is experimented on a simulated road and verified that the prototype and the proposed control algorithm can realize the expected requirements.
Leveraging Industry 4.0 technologies for sustainable value chains: Raising awareness on digital transformation and responsible operations management
Authors: Strazzullo Serena , Cricelli Livio , Troise Ciro , Camilleri Mark Anthony 
Published: October 2024

AbstractPractitioners, policy makers as well as scholars are increasingly focusing their attention on the promotion of sustainable practices that reduce the businesses' impacts on the environment. In many cases, they are well aware that manufacturers and their suppliers are resorting to lean management processes and Industry 4.0 (I4.0) technologies such as big data, internet of things (IoT), and artificial intelligence (AI), among others, to implement sustainable production models in their operational processes. This research utilizes an inductive approach to better understand how I4.0 technologies could result in increased organizational performance in terms of resource efficiencies, quality assurance as well as in environmentally sustainable outcomes, in the context of the automotive industry. The findings shed light on the relationship between I4.0 technologies, sustainable and lean practices of automakers of combustion engines, hybrid models and/or electric vehicles (EVs). In conclusion, this contribution puts forward an original conceptual framework that clearly explains how practitioners can avail themselves of disruptive technologies to foster continuous improvements in their value chain.
Earth‐Abundant CuWO4 as a Versatile Platform for Photoelectrochemical Valorization of Soluble Biomass Under Benign Conditions
Authors: Chuang Ping‐Chang , Lin Chin‐Yuan , Ye Si‐Ting , Lai Yi‐Hsuan 
Published: October 2024

AbstractHere, a nanosheet‐structured CuWO4 (nanoCuWO4) is demonstrated as a selective and stable photoanode for biomass valorization in neutral and near‐neutral solutions. nanoCuWO4 can be readily prepared by a solid phase reaction using nanosheet‐structured WO3 as the template. Several substrates, including glucose, fructose and glycerol, are investigated to reveal the wide applicability of nanoCuWO4. The activity and product distribution trends in biomass valorization are investigated at different pH by taking advantage of the promising stability of nanoCuWO4 in a wide pH range. Product analyses confirm that formate production with a Faradaic efficiency (FE) of 76 ± 5% and glycolate production with an FE of 61 ± 8% can be achieved by glucose and fructose valorization at pH 10.2, respectively. On the other hand, glyceraldehyde and dihydroxyacetone (DHA) are the main products in the glycerol valorization, accounting for an FE of over 85% at pH 7. Notably, nanoCuWO4 has the highest FE of DHA in photoelectrochemical (PEC) glycerol valorization compared to WO3 and BiVO4 at neutral pH. The oxidation routes and mechanism of glycerol valorization on nanoCuWO4 are also under investigation. The co‐production of H2 and value‐added chemicals is finally demonstrated using a photovoltaic cell connected to a nanoCuWO4‐based PEC glycerol valorization system.
Thermoelectric Materials and Devices for Advanced Biomedical Applications
Authors: Jia Shiyu , Ma Huangshui , Gao Shaojingya , Yang Lei , Sun Qiang 
Published: October 2024

AbstractThermoelectrics (TEs), enabling the direct conversion between heat and electrical energy, have demonstrated extensive application potential in biomedical fields. Herein, the mechanism of the TE effect, recent developments in TE materials, and the biocompatibility assessment of TE materials are provided. In addition to the fundamentals of TEs, a timely and comprehensive review of the recent progress of advanced TE materials and their applications is presented, including wearable power generation, personal thermal management, and biosensing. In addition, the new‐emerged medical applications of TE materials in wound healing, disease treatment, antimicrobial therapy, and anti‐cancer therapy are thoroughly reviewed. Finally, the main challenges and future possibilities are outlined for TEs in biomedical fields, as well as their material selection criteria for specific application scenarios. Together, these advancements can provide innovative insights into the development of TEs for broader applications in biomedical fields.
A Two‐Step Dry Etching Model for Non‐Uniform Etching Profile in Gate‐All‐Around Field‐Effect Transistor Manufacturing
Authors: Hu Ziyi , Li Junjie , Chen Rui , Shang Dashan , Wei Yayi , Wang Zhongrui , Li Ling , Filipovic Lado 
Published: October 2024

AbstractThe Gate‐All‐Around Field‐Effect Transistor (GAAFET) is proposed as a successor to Fin Field‐Effect Transistor (FinFET) technology to increase channel length and improve the device performance. The GAAFET features a complex multilayer structure, which complicates the manufacturing process. One of the most critical steps in GAAFET fabrication is the selective lateral etching of the SiGe layers, essential for forming the inner‐spacer. Industry commonly encounters a non‐uniform etching profile during this step. In this paper, a continuous two‐step dry etching model is proposed to investigate the mechanism behind the formation of the non‐uniform profiles. The model consists of four modules: anisotropic etching simulation, Ge atom diffusion simulation, Si/SiGe etch selectivity calculation and SiGe selective etching simulation. By calibrating and verifying this model with experimental data, the edge rounding and gradient etching rates along the sidewall surface are successfully simulated. Based on further examination of the influence of chamber pressure on the profile using this model, the inner‐spacer shape is improved experimentally by appropriately reducing the chamber pressure. This work aims to provide valuable insights for etching process recipes in advanced GAAFETs manufacturing.
Dislocation Evolution in Cyclic‐Loaded Cu Nanopillars with Different Configurations
Authors: Li Xiyao , Zhao Zhiyu , Zhang Zhenghao , Shao Xiaohong , An Xianghai , Wei Siyuan , Zhou Haofei , Song Kexing , Wang Jiangwei 
Published: October 2024

AbstractSmall‐sized metals generally exhibit unusual deformation responses subjected to cyclic loading, since their limited volume cannot effectively accommodate micro‐sized dislocation patterns typically found in their bulk counterparts. Here, the cyclic behaviors in Cu nanopillars with different configurations are investigated using in situ transmission electron microscopy fatigue test. Dislocation tangles formed in single‐ and twinned‐crystal nanopillars as a result of cycling‐induced operations of multiple slip systems and further unpinning and absorption of pinned dislocations. While, nanopillars configured with low‐angle grain boundary (LAGB) underwent the degradation and eventual decomposition of the LAGB due to the cycling‐induced emission of grain boundary dislocations, which resulted in high‐density mobile dislocations to withstand the cyclic loading. These findings contribute to a systematic and comprehensive understanding of the micro‐mechanics of dislocation‐related phenomena in the cyclic response of nanoscale metals.
Soft‐Rigid Construction of Mechanically Robust, Thermally Stable, and Self‐Healing Polyimine Networks with Strongly Recyclable Adhesion
Authors: Jia Zichen , Wang Haiyue , Yu Ping , He Hongfei , Huang Qirui , Hong Wei , Liu Cai , Shi Yanji , Wang Jue , Xin Yumeng , Jia Xuemeng , Ma Juanjuan , Yu Bin 
Published: October 2024

AbstractReversible and recyclable thermosets have garnered increasing attention for their smart functionality and sustainability. However, they still face challenges in balancing comprehensive performance and dynamic features. Herein, silicon (Si)─oxygen (O) and imidazole units covalent bonds are coupled to generate a new class of bio‐polyimines (Bio‐Si‐PABZs), to endow them with high performance and excellent reprocessing capability and acid‐degradability. By tailoring the molar content of diamines, this Bio‐Si‐PABZs displayed both a markedly high glass transition temperature (162 °C) and a high char yield at 800 °C in an oxygen atmosphere (73.1%). These Bio‐Si‐PABZs with their favorable properties outperformed various previously reported polyimines and competed effectively with commercial fossil‐based polycarbonate. Moreover, the scratch (≈10 µm) on the surface of samples can be self‐healing within only 2 min, and an effective “Bird Nest”‐to‐“Torch” recycling can also be achieved through free amines solution. Most importantly, a bio‐based siloxane adhesive derived from the intermediate Bio‐Si‐PABZ‐1 by acidic degradation demonstrated broad and robust adhesion in various substrates, with values reaching up to ≈3.5 MPa. For the first time, this study lays the scientific groundwork for designing robust and recyclable polyimine thermosets with Si─O and imidazole units, as well as converting plastic wastes into thermal‐reversibility and renewable adhesives.
A review on renewable energy: Conversion and utilization of biomass
Authors: Yang Xinping , Zhang Yongjia , Sun Peiliang , Peng Chong 
Published: October 2024

AbstractThe significant increase in demand for fuels and chemicals driven by global economic expansion has exacerbated concerns over fossil fuel consumption and environmental pollution. To achieve sustainable production of fuels and chemicals, biomass resources provide a rich repository for carbon‐neutral, green renewable energy, and organic carbon. This paper reviews the transformation and utilization of lignocellulosic biomass and its derivatives, emphasizing their valorization into high‐quality chemicals and biofuels. The advantages and disadvantages of various pretreatment methods are discussed based on the composition of lignocellulose. Furthermore, the methods and pathways for the valorization and conversion of cellulose, hemicellulose, and lignin are detailed according to the unique functional groups of different lignocellulosic platform molecules. However, the complex and resilient structure of biomass presents challenges for the disassembly and utilization of single components, and achieving high yields and selectivity for target products remains difficult. In conclusion, this paper comprehensively reviews the various types and pretreatment technologies of lignocellulose, focusing on the methods and pathways for the valorization of lignocellulosic biomass and its derivatives, thereby providing clear guidance and insights for optimizing lignocellulose utilization in the future.
Bayesian updating of relationships between crack width and corrosion level in reinforced concrete based on a large set of experimental data
Authors: Martens Constantijn , Botte Wouter , Caspeele Robby , Verstrynge Els 
Published: October 2024

AbstractThe evaluation of rebar corrosion in reinforced concrete (RC) structures presents a significant challenge for structural engineers, with on‐site visual inspections and crack width measurements playing a key role in the preliminary assessment. A general approach is to use corrosion models to predict the corrosion level of existing structures, and subsequently update these predictions by means of on‐site data. In this process, empirical models are often applied that relate the observed damage, such as corrosion‐induced cracks, to the corrosion level. However, these models have large uncertainties and are often not applicable to conditions that deviate from the test setups used to derive the empirical relations. This research aims to expand the applicability of these practical, existing empirical models for on‐site corrosion assessment through Bayesian updating techniques. To this aim, a Bayesian framework is developed to update crack width–corrosion models. The Bayesian updating methodology is illustrated for a simple regression model, and for a more complex relation that accounts for additional variables. A novel online database (KUL‐edCCRC) is used that is published accompanying this paper. The obtained results illustrate that the updated models have better agreement with the experimental results, and it is found that the confidence intervals of the regression parameters decrease for an increasing number of observations, even for a small number of additional datapoints. The results hence prove the efficiency of the approach to integrate information from new observations with prior information to adjust the crack width–corrosion model for specific conditions or cases, resulting in a more relevant model as more information becomes available.