bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synergistic Gas Therapy and Targeted Interventional Ablation With Size‐Controllable Arsenic Sulfide (As2S3) Nanoparticles for Effective Elimination of Localized Cancer Pain
Authors: Tang Yu , Zhang Jiyun , Yuan Yuan , Shen Kele , Luo Zhiyuan , Jia Luyu , Long Xiaofeng , Peng Chi , Xie Tian , Chen Xiaoyuan , Zhang Pengfei 
Published: October 2024

AbstractThe elimination of localized cancer pain remains a globally neglected challenge. A potential solution lies in combining gas therapy with targeted interventional ablation therapy. In this study, HA‐As2S3 nanoparticles with controlled sizes are synthesized using different molecular weights of sodium hyaluronate (HA) as a supramolecular scaffold. Initially, HA co‐assembles with arsenic ions (As3+) via coordinate bonds, forming HA‐As3+ scaffold intermediates. These intermediates, varying in size, then react with sulfur ions to produce size‐controlled HA‐As2S3 particles. This approach demonstrates that different molecular weights of HA enable precise control over the particle size of arsenic sulfide, offering a straightforward and environmentally friendly method for synthesizing metal sulfide particles. In an acidic environment, HA‐As2S3 nanoparticles release hydrogen sulfide(H2S) gas and As3+. The released As3+ directly damage tumor mitochondria, leading to substantial reactive oxygen species (ROS) production from mitochondria. Concurrently, the H2S gas inhibits the activity of catalase (CAT) and complex IV, preventing the beneficial decomposition of ROS and disrupting electron transfer in the mitochondrial respiratory chain. Consequently, it is found that H2S gas significantly enhances the mitochondrial damage induced by arsenic nanodrugs, effectively killing local tumors and ultimately eliminating cancer pain in mice.
Closed‐Loop Recycling of Wearable Electronic Textiles
Authors: Dulal Marzia , Afroj Shaila , Islam Md Rashedul , Zhang Minglonghai , Yang Yadie , Hu Hong , Novoselov Kostya S. , Karim Nazmul 
Published: October 2024

AbstractWearable electronic textiles (e‐textiles) are transforming personalized healthcare through innovative applications. However, integrating electronics into textiles for e‐textile manufacturing exacerbates the rapidly growing issues of electronic waste (e‐waste) and textile recycling due to the complicated recycling and disposal processes needed for mixed materials, including textile fibers, electronic materials, and components. Here, first closed‐loop recycling for wearable e‐textiles is reported by incorporating the thermal‐pyrolysis of graphene‐based e‐textiles to convert them into graphene‐like electrically conductive recycled powders. A scalable pad‐dry coating technique is then used to reproduce graphene‐based wearable e‐textiles and demonstrate their potential healthcare applications as wearable electrodes for capturing electrocardiogram (ECG) signals and temperature sensors. Additionally, recycled graphene‐based textile supercapacitor highlights their potential as sustainable energy storage devices, maintaining notable durability and retaining ≈94% capacitance after 1000 cycles with an areal capacitance of 4.92 mF cm⁻2. Such sustainable closed‐loop recycling of e‐textiles showcases the potential for their repurposing into multifunctional applications, promoting a circular approach that potentially prevents negative environmental impact and reduces landfill disposal.
Multifunctional Hydrogel Microneedle Patches Modulating Oxi‐inflamm‐aging for Diabetic Wound Healing
Authors: Tian Shen , Mei Jiawei , Zhang Lisha , Wang Senyan , Yuan Yuhui , Li Jia , Liu Hongjian , Zhu Wanbo , Xu Dongdong 
Published: October 2024

AbstractOxidative stress, chronic inflammation, and immune senescence are important pathologic factors in diabetic wound nonhealing. This study loads taurine (Tau) into cerium dioxide (CeO2) to develop CeO2@Tau nanoparticles with excellent antioxidant, anti‐inflammatory, and anti‐aging properties. To enhance the drug penetration efficiency in wounds, CeO2@Tau is encapsulated in gelatin methacryloyl (GelMA) hydrogel to prepare CeO2@Tau@Hydrogel@Microneedle (CTH@MN) patch system. Microneedle technology achieves precise and efficient delivery of CeO2@Tau, ensuring their deep penetration into the wound tissue for optimal efficacy. Rigorous in vitro and in vivo tests have confirmed the satisfactory therapeutic effect of CTH@MN patch on diabetic wound healing. Mechanistically, CTH@MN attenuates oxidative damage and inflammatory responses in macrophages by inhibiting the ROS/NF‐κB signaling pathway. Meanwhile, CTH@MN activated autophagy‐mediated anti‐aging activity, creating a favorable immune microenvironment for tissue repair. Notably, in a diabetic mouse wound model, the multifunctional CTH@MN patch significantly promotes wound healing by systematically regulating the oxidation‐inflammation‐aging (oxi‐inflamm‐aging) pathological axis. In conclusion, the in‐depth exploration of the CTH@MN system in this study provides new strategies and perspectives for treating diabetic non‐healing wounds.
Exploring Pyrazine‐Based Organic Redox Couples for Enhanced Thermoelectric Performance in Wearable Energy Harvesters
Authors: Lee Chia‐Yu , Hsu Ching‐Chieh , Wang Chia‐Hsin , Jeng U‐Ser , Tung Shih‐Huang , Hu Chi‐Chang , Liu Cheng‐Liang 
Published: October 2024

AbstractThermoelectric generators (TEGs) based on thermogalvanic cells can convert low‐temperature waste heat into electricity. Organic redox couples are well‐suited for wearable devices due to their nontoxicity and the potential to enhance the ionic Seebeck coefficient through functional‐group modifications. Pyrazine‐based organic redox couples with different functional groups is comparatively analyzed through cyclic voltammetry under varying temperatures. The results reveal substantial differences in entropy changes with temperature and highlight 2,5‐pyrazinedicarboxylic acid dihydrate (PDCA) as the optimal candidate. How the functional groups of the pyrazine compounds impact the ionic Seebeck coefficient is examined, by calculating the electrostatic potential based on density functional theory. To evaluate the thermoelectric properties, PDCA is integrated in different concentrations into a double‐network hydrogel comprising poly(vinyl alcohol) and polyacrylamide. The resulting champion device exhibits an impressive ionic Seebeck coefficient (Si) of 2.99 mV K−1, with ionic and thermal conductivities of ≈67.6 µS cm−1 and ≈0.49 W m−1 K−1, respectively. Finally, a TEG is constructed by connecting 36 pieces of 20 × 10−3 m PDCA‐soaked hydrogel in series. It achieves a maximum power output of ≈0.28 µW under a temperature gradient of 28.3 °C and can power a small light‐emitting diode. These findings highlight the significant potential of TEGs for wearable devices.
Advancing Zinc Anodes: Strategies for Enhanced Performance in Aqueous Zinc‐Ion Batteries
Authors: Upreti Bharat Bhushan , Kamboj Navpreet , Dey Ramendra Sundar 
Published: October 2024

AbstractThe promising features of aqueous zinc ion batteries (AZIBs), including their inherent safety, environmental friendliness, abundant raw materials, cost‐effectiveness, and simple manufacturing process, position them as strong candidates for large‐scale energy storage. However, their practical application faces significant challenges, such as uncontrolled dendritic growth, undesirable side reactions, and hydrogen evolution reactions (HER), which undermine the efficiency and longevity of the system. To address these issues, extensive research has been conducted to improve these batteries' energy density and lifespan. This comprehensive review explores the fundamental mechanisms of zinc dendrite formation, its properties, and the interfacial chemistry between the electrode and electrolyte. It also delves into strategies for protecting the zinc anode, with a focus on the modulation of zinc ion deposition dynamics at the electrolyte interface. The discussion concludes with an evaluation of the current challenges and future prospects of AZIB, aiming to enhance their viability for grid‐scale energy storage solutions.
Benzotrithiophene‐sulfonate covalent‐organic frameworks: Supramolecular proton pumps for high‐rate aqueous zinc‐ion energy storage systems
Authors: Peng Haijun , Montes‐García Verónica , Jiang Kaiyue , Pakulski Dawid , Xu Shunqi , Bielejewski Michał , Richard Fanny , Zhuang Xiaodong , Samorì Paolo , Ciesielski Artur 
Published: October 2024

AbstractProton chemistry is becoming a focal point in the development of zinc‐ion energy storage devices due to its swift H+ insertion/extraction kinetics. This characteristic feature confers to electrodes a remarkable power density, rate capability, and prolonged cycling durability. However, the storage mechanism of H+ in electrodes based on covalent‐organic frameworks (COFs) has not been thoroughly investigated. In this work, we introduce an unprecedented concept involving a supramolecular approach based on the design of a benzotrithiophene‐sulfonate COF (COF‐BTT‐SO3H) with remarkable storage capacity for simultaneous insertion and extraction of H+ and Zn2+. The ad hoc positioning of the ‐SO3H groups within the COF‐BTT‐SO3H structure facilitates the formation of a robust H‐bonded network. Through density functional theory calculations and employing in situ and ex situ analyses, we demonstrate that this network functions as a spontaneous proton ion pump leading to enhanced ion‐diffusion kinetics and exceptional rate performance in zinc‐ion energy storage devices. COF‐BTT‐SO3H reveals a high capacity of 294.7 mA h/g (0.1 A/g), a remarkable maximum energy density of 182.5 W h/kg, and power density of 14.8 kW/kg, which are superior to most of the reported COF‐based electrodes or other organic and inorganic electrode materials in Zn2+ energy storage devices.
Disodium Malate Electrolyte Additive Facilitates Dendrite‐Free Zinc Anode: Deposition Kinetics and Interface Regulation
Authors: Liu Jiayi , Shen Zhongrong , Lu Can‐Zhong 
Published: October 2024

AbstractDue to the presence of H2O within the solvated sheath of [Zn(H2O)6]2+ as well as reactive free water in the electrolyte bulk phase, the extended cycling of aqueous zinc‐ion batteries (AZIBs) is significantly affected by detrimental side reactions and the growth of Zn dendrites. This study significantly enhances the long‐term cycling stability of AZIBs by introducing a small amount of disodium malate (DM) into a 2 m ZnSO4 electrolyte solution. DM involvement in the solvation sheath of Zn2+ reduces the desolvation energy of Zn2+, thereby mitigating the corrosion and hydrogen evolution reaction (HER) of the negative electrode surface by [Zn(H2O)6]2+ ions. Additionally, DM adsorption on the zinc surface retards the reduction kinetics of Zn2+ at anode, promoting uniform distribution and predominant deposition on the flat (002) crystal plane, thus reducing dendrite formation. The assembled Zn||Zn symmetric cell exhibits stable cycling for over 500 h at 10 mA cm−2 and 5 mAh cm−2. The Zn||VO2 full cells with DM additive exhibits an ultralong cycling lifespan without capacity loss.
Mutation‐Guided Metamorphic Testing of Optimality in AI Planning
Authors: Mazouni Quentin , Gotlieb Arnaud , Spieker Helge , Acher Mathieu , Combemale Benoit 
Published: October 2024

ABSTRACTAutonomous systems such as space‐ or underwater‐exploration robots or elderly people assistance robots often include an artificial intelligence (AI) planner as a component. Starting from the initial state of a system, an AI planner automatically generates sequential plans to reach final states that satisfy user‐specified goals. Generating plans having a minimum number of intermediate steps or taking the least time to execute is usually strongly desired, as these plans exhibit minimal costs. Unfortunately, testing if an AI planner generates optimal plans is almost impossible because the expected cost of these plans is usually unknown. Based on mutation adequacy test suite selection, this article proposes a novel metamorphic testing framework for detecting the lack of optimality in AI planners. The general idea is to perform a systematic but non‐exhaustive state space exploration from the initial state and to select mutant‐adequate states to instantiate new planning tasks as follow‐up test cases. We then check a metamorphic relation between the automatically generated solutions of the AI planner for these new test cases and the cost of the initial plan. We implemented this metamorphic testing framework in a tool called MorphinPlan. Our experimental evaluation shows that MorphinPlan can detect non‐optimal behaviour in both mutated AI planners and off‐the‐shelf, configurable planners. It also shows that our proposed mutation adequacy test selection strategy outperforms three alternative test generation and selection strategies, including both random state selection and random walks through the state space in terms of mutation scores.
Antimicrobial activity of isoxazole derivatives: A brief overview
Authors: Vashisht Ketan , Sethi Pooja , Bansal Anshul , Bansal Poonam 
Published: October 2024

AbstractDue to their extensive range of biological actions, isoxazole and its analogues stand out among other heterocyclic compounds as a very important class of heterocycles. Over recent years, there has been a growing demand for these heterocyclic nuclei as crucial synthetic intermediates, contributing significantly to the advancement of newly formed chemical entities in the fields of pharmaceutical and medicinal chemistry. Furthermore, the significance of N and O‐containing heterocycles from medicinal perspective arises from their inherent ability to readily bind with biological systems, including various enzymes and receptors, through many non‐covalent interactions. The antimicrobial potential of isoxazole compounds has been extensively studied against broad range of microorganisms, including bacteria, fungi, etc. From a research perspective, isoxazoles exhibit antimicrobial, anticancer, antioxidant, analgesic, anti‐inflammatory, and central nervous system activities. It also exhibits inhibitory, glutamate transporter, and anti‐hypertensive properties, which are similar to GABA (γ‐aminobutyric acid). The current review explores the antimicrobial properties and structure‐activity relationship of different isoxazole derivatives relative to their antimicrobial efficacy. Furthermore, it seeks to highlight the potential applications and future directions in the development of isoxazole‐based antimicrobial agents.
Perceptions of informed Afghans on the Taliban's Islamic Emirate and the former Afghan government
Authors: Omarkhail Ihsanullah 
Published: October 2024

AbstractThis article examines many of the Taliban's prominent positions and dynamics in the Afghan state. The Taliban has had few explicit political goals. Instead, its policies have focused on reshaping Afghan society and re‐establishing the Islamic Emirate of Afghanistan. The Taliban conflicted with the Afghan Republic (2001−2021) and faced repeated administrative problems and opposition in realizing their minor political goals. They have re‐emerged in Afghanistan following the U.S. withdrawal. This article compares factors such as corruption, ethnicity, dictatorship, and politics between the Taliban and the Republic. It uses the fragile state framework to explain the continuation of the conflict in Afghanistan, analyzing historical discourse. This article primarily relies on survey data, focusing on the views of Afghan people concerning the Republic and the Taliban.
Insights into the formulation of lipid nanoparticles for the optimization of mRNA therapeutics
Authors: Jiao Xiangyu , He Xi , Qin Shugang , Yin Xiaoling , Song Tingting , Duan Xing , Shi Haixing , Jiang Shanhui , Zhang Yupei , Song Xiangrong 
Published: October 2024

AbstractmRNA‐based therapeutics increasingly demonstrate significant potential in treating various diseases, including infectious diseases, cancers, and genetic disorders. Effective delivery systems are crucial for advancing mRNA therapeutics. Lipid nanoparticles (LNPs) serve as an excellent carrier, widely validated for their safety and tolerability in commercially available mRNA vaccines. Standard LNPs typically consist of four components: ionizable lipids (ILs), helper lipids, cholesterol, and polyethylene glycol‐lipids (PEG‐lipids), with the structural design of ILs gradually becoming a focal point of research interest. The chemical structures and formulations of the other components also significantly affect the delivery efficiency, targeting specificity, and stability of LNPs. The complex formulations of LNPs may hinder the clinical transformation of mRNA therapeutics and have raised widespread concerns about their safety. This review aims to summarize the progress of LNPs‐based mRNA therapeutics in clinical trials, focusing on adverse effects that occurred during these trials. It also discusses representative innovations in LNP components, highlighting challenges and potential ways in this research field. We firmly believe this review will promote further improvements and designs of LNP compositions to optimize mRNA therapeutics.This article is categorized under:
Nanotechnology Approaches to Biology > Nanoscale Systems in Biology
Biology‐Inspired Nanomaterials > Lipid‐Based Structures
Numerical simulation of bio‐convection radiative heat transport flow of MHD Carreau nanofluid
Authors: Irfan Muhammad , Muhammad Taseer 
Published: October 2024

AbstractTo report the challenges and advance of heat transport performance, we aim to scrutinize the motile microbe's phenomenon in mixed convection Carreau nanofluid considering the properties of Soret and Dufour, non‐uniform heat sink/source, radiation and magnetohydrodynamic (MHD). The new mass flux and convective phenomenon are also considered. The inclusion of motile microbe phenomenon in conjunction with Soret and Dufour effects, non‐uniform heat sink/source, radiation, and MHD presents a multifaceted approach to studying heat transport in Carreau nanofluids. By integrating these factors, we gain insights into the complex interplay between thermal conductivity variations, convective heat transfer, and fluid flow behavior. This comprehensive analysis allows for a deeper understanding of how various mechanisms influence heat transport performance, offering valuable insights for optimizing nanofluid‐based heat transfer systems and enhancing their efficiency. The highly nonlinear and coupled partial differential equations (PDE) are transformed using similarity conversion and attained required ordinary differential equations (ODE). The bvp4c algorithm works to derive the solutions subjected to appropriate norms and physical boundary conditions. Furthermore, an assessment made with the obtainable works shows worthy outcomes. The controlling variables influence on the microorganisms, concentration, temperature, and velocity fields are scrutinized graphically for shear thinning and thickening phenomena. Skin frictions, motile density number, and Nusselt numbers of tables are prepared. Additionally, the cases of shear thinning/thickening are discussed in tables. The radiation and Biot factors exaggerate the temperature field; however, Brownian factor decay the fluid concentration. The bioconvection Rayleigh factor decreases and mixed convection factor increases the velocity field. Furthermore, the bioconvection Lewis factor declines the motile microbe's field. The graphs of controlling factors for followings values are plotted for accurate convergence that is, , , , , , , , ,
Stokes' second problem exact solution for hybrid nanofluid flow along an exponentially accelerating vertical surface
Authors: Arulmozhi S. , Sukkiramathi K. , Santra S. S. , Nandi S. , Vajravelu K. , Kumbhakar B. , Hussain S. M. 
Published: October 2024

AbstractThis study explored magnetohydrodynamic (MHD) radiative unsteady free convective hybrid nanofluid flow over an exponentially accelerated vertical plate under the impact of transverse magnetic force with first‐order chemical reaction. The term “hybrid” or “composite” nanofluid refers to a mixture of water‐containing nanoparticles (NPs) of and that have been dissolved in the base fluid to create the hybrid nanofluid. The crux of the investigation is the attention to two different cases of magnetic force, one being stationary relative to the plate and the other close to the fluid. The Dimensional equations are transformed into dimensionless forms using non‐dimensional quantities. The Laplace Transform technique is used to obtain the closed‐form solutions. Based on those outcomes, the velocity, the temperature, and the concentration distributions of the hybrid nanofluid are evaluated for several sets of values of the physical parameters related to MHD, NP's volume fraction, radiation, porosity, and plate accelerating parameters have been studied through graphs. Furthermore, it is discovered that when the magnetic force is applied to the fluid , the velocity drops with increasing magnetic parameters; nevertheless, the opposite trends occur when the magnetic force is applied to the plate .
Safe Control Allocation of Articulated Heavy Vehicles Using Machine Learning
Authors: van Dam Sander , Wisell Lukas , Shingade Kartik , Kieu Mikael , Erdinc Umur , Kati Maliheh Sadeghi , Gelso Esteban , Parthasarathy Dhasarathy 
Published: October 2024

AbstractAs articulated heavy vehicles are over-actuated, achieving a safe control allocation is crucial to ensure stability. This study introduces a machine learning model developed to identify unsafe behaviours and modes, such as jack-knifing and trailer swing, enabling the control scheme to prioritize stability. High-fidelity simulations, focusing on high-risk scenarios, generate data for training the machine learning model. This model is integrated into the control scheme to predict safe braking allocations and prevent unsafe vehicle modes during real-time driving scenarios. Initial tests showed promising results regarding prediction accuracy and a safety margin that can be implemented to further ensure that safe vehicle motion is achieved.
State Estimation and Sensorimotor Noise in a Driver Steering Model with a Gaussian Process Internal Model
Authors: Fieldhouse Harry , Cole David 
Published: October 2024

AbstractRefinements to a mathematical model of human drivers’ steering control incorporating driver learning are reported. State estimation and realistic sensorimotor noise sources are introduced to the driver model to better represent neural processes. It is found that the driver model exhibits the expected learning behaviour in terms of estimation and control performance. Further work is planned to validate the model experimentally.
Nonlinear Model Predictive Control for Enhanced Path Tracking and Autonomous Drifting Through Direct Yaw Moment Control and Rear-Wheel-Steering
Authors: Tavolo Gaetano , Stano Pietro , Tavernini Davide , Montanaro Umberto , Tufo Manuela , Fiengo Giovanni , Perlo Pietro , Sorniotti Aldo 
Published: October 2024

AbstractPath tracking (PT) controllers capable of replicating race driving techniques, such as drifting beyond the limits of handling, have the potential of enhancing active safety in critical conditions. This paper presents a nonlinear model predictive control (NMPC) approach that integrates multiple actuation methods, namely four-wheel-steering, longitudinal tyre force distribution, and direct yaw moment control, to execute drifting when this is beneficial for PT in emergency scenarios. Simulation results of challenging manoeuvres, based on an experimentally validated vehicle model, highlight the substantial PT performance improvements brought by: i) vehicle operation outside the envelope enforced by the current generation of stability controllers; and ii) the integrated control of multiple actuators.