bluuebunny/crossref_metadata_2025 huggingface dataset:
S‐Modified Graphitic Carbon Nitride with Double Defect Sites For Efficient Photocatalytic Hydrogen Evolution
Authors: Quan Yongkang , Li Ruidong , Li Xingzhou , Chen Rongxing , Ng Yun Hau , Huang Jianying , Hu Jun , Lai Yuekun
Published: October 2024

Graphitic carbon nitride (gC3N4) is an attractive photocatalyst for solar energy conversion due to its unique electronic structure and chemical stability. However, gC3N4 generally suffers from insufficient light absorption and rapid compounding of photogenerated charges. The introduction of defects and atomic doping can optimize the electronic structure of gC3N4 and improve the light absorption and carrier separation efficiency. Herein, the high efficiency of carbon nitride photocatalysis for hydrogen evolution in visible light is achieved by an S‐modified double‐deficient site strategy. Defect engineering forms abundant unsaturated sites and cyano (─C≡N), which promotes strong interlayer C─N bonding interactions and accelerates charge transport in gC3N4. S doping tunes the electronic structure of the semiconductors, and the formation of C─S─C bonds optimizes the electron‐transfer paths of the C─N bonding, which enhances the absorption of visible light. Meanwhile,C≡N acts as an electron trap to capture photoexcited electrons, providing the active site for the reduction of H+ to hydrogen. The photocatalytic hydrogen evolution efficiency of SDCN (1613.5 µmol g−1 h−1) is 31.5 times higher than that of pristine MCN (51.2 µmol g−1 h−1). The charge separation situation and charge transfer mechanism of the photocatalysts are investigated in detail by a combination of experimental and theoretical calculations.
Recent Achievements in Heterogeneous Bimetallic Atomically Dispersed Catalysts for Zn–Air Batteries: A Minireview
Authors: Gao Sanshuang , Lian Kang , Wang Xinzhong , Liu Xijun , Abdukayum Abdukader , Kong Qingquan , Hu Guangzhi
Published: October 2024

Rechargeable Zn–air batteries (ZABs) hold promise as the next‐generation energy‐storage devices owing to their affordability, environmental friendliness, and safety. However, cathodic catalysts are easily inactivated in prolonged redox potential environments, resulting in inadequate energy efficiency and poor cycle stability. To address these challenges, anodic active sites require multiple‐atom combinations, that is, ensembles of metals. Heterogeneous bimetallic atomically dispersed catalysts (HBADCs), consisting of heterogeneous isolated single atoms and atomic pairs, are expected to synergistically boost the cyclic oxygen reduction and evolution reactions of ZABs owing to their tuneable microenvironments. This minireview revisits recent achievements in HBADCs for ZABs. Coordination environment engineering and catalytic substrate structure optimization strategies are summarized to predict the innovation direction for HBADCs in ZAB performance enhancement. These HBADCs are divided into ferrous and nonferrous dual sites with unique microenvironments, including synergistic effects, ion modulation, electronic coupling, and catalytic activity. Finally, conclusions and perspectives relating to future challenges and potential opportunities are provided to optimise the performance of ZABs.
Step‐Scheme SnO₂/Zn₃In₂S₆ Catalysts for Solar Production of Hydrogen Peroxide From Seawater
Authors: Ding Chunsheng , Ruan Xiaowen , Xu Minghua , Meng Depeng , Fang Guozhen , Jiao Dongxu , Zhang Wei , Leng Jing , Jiang Zhifeng , Ba Kaikai , Xie Tengfeng , Jin Shengye , Zheng Weijia , Ravi Sai Kishore , Cui Xiaoqiang
Published: October 2024

Photocatalytic generation of H₂O₂, involving both oxygen reduction and water oxidation without sacrificial agents, necessitates maximized light absorption, suitable band structure, and efficient carrier transport. Leveraging the redox capacity this study designs and constructs a step‐scheme heterostructured SnO₂/Zn₃In₂S₆ catalyst for H₂O₂ production from seawater under ambient conditions for the first time. This photocatalyst demonstrates a remarkable H₂O₂ production rate of 43.5 µmol g⁻¹ min⁻¹ without sacrificial agents, which can be increased to 80.7 µmol g⁻¹ min⁻¹ with additional O₂ injection. Extensive in situ and ex situ characterizations, supported by theoretical calculations, reveal efficient carrier transport and robust redox ability, enabling complete photosynthesis of H₂O₂ at the oxidation and reduction sites in the S‐scheme SnO₂/Zn₃In₂S₆ heterojunction. Furthermore, it is hypothesized that substituting SnO₂ with other semiconductors such as TiO₂, WO₃, and BiVO₄ can all form S‐scheme and the results confirm the feasibility of such catalyst design. Additionally, it demonstrates the recycling and further utilization of the H₂O₂ produced. These findings offer new insights into the design of heterostructure catalyst architectures and present new opportunities for H₂O₂ production from seawater at ambient conditions without sacrificial agents.
High‐Energy‐Density All‐V2O5 Battery
Authors: Wang Guolong , Wang Jingqi , Song Jiale , Tai Yuxi , Ren Junwen , Liu Jiamei , Shi Xiaowei , Zhao Zehua , Li Lei
Published: October 2024

Symmetrical batteries hold great promise as cost‐effective and safe candidates for future battery technology. However, they realistically suffer low energy density due to the challenge in integrating high specific capacity with high voltage plateau from the limited choice of bipolar electrodes. Herein, a high‐voltage all‐V2O5 symmetrical battery with clear voltage plateau is conceptualized by decoupling the cathodic/anodic redox reactions based upon the episteme of V2O5 intercalation chemistry. As the proof‐of‐concept, a hierarchical V2O5‐carboncomposite (VO‐C) bipolar electrode with boosted electron/ion transport kinetics is fabricated, which shows high performance as both cathode and anode in their precisely clamped working potential windows. Accordingly, the symmetrical full‐battery exhibits a high capacity of 174 mAh g−1 along with peak voltage output of above 2.9 V at 0.5C, remarkable capacity retention of 81% from 0.5C to 10C, and good cycling stability of 70% capacity retention after 300 cycles at 5C. Notably, its energy density reaches 429 Wh kg−1 at 0.5C estimated by the cathode mass, which outperforms most of the existing Li/Na/K‐based symmetrical batteries. This study leaps forward the performance of symmetrical battery and provides guidance to extend the scope of future battery designs.
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

The 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

Wearable 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

Oxidative 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

Thermoelectric 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

The 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

Proton 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

Due 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

Autonomous 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

Due 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

This 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

mRNA‐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

To 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

This 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

As 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

Refinements 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

Path 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.
An Automated Lane-Change System Based on Probabilistic Trajectory Prediction Network
Authors: Ahn Yoonyong , Han Sangwon , Sung Jihoon , Choi Jaeho , Huh Kunsoo
Published: October 2024

In highway driving, understanding the intentions of surrounding vehicles is a crucial prerequisite to ensure collision-free lane changes. In this study, an automated lane change system framework is proposed for highway driving. A Long Short-Term Memory (LSTM)-based network is utilized to predict the paths of surrounding vehicles as probability distributions. When initiating a lane change, multiple candidate paths are generated, and the collision probability is then calculated by considering the generated paths of the host vehicle and the predicted paths of surrounding vehicles. Using the vehicle as a reference, the collision risk area is defined first related to the lane change. Secondly, the probability of the predicted distribution of the surrounding vehicles existing within this area is integrated to derive the collision probability. Subsequently, the collision-free optimal path is adopted, and Model Predictive Control (MPC) is employed for path tracking. The proposed framework was validated on a highway-like proving ground.
Development of Vehicle State Estimation Method for Dedicated Sensor-Less Semi-active Suspension Using AI Technology
Authors: Kawasaki Yoshifumi , Akihito Akai , Hirao Ryusuke
Published: October 2024

This paper presents a sensor-less vehicle state estimation method using a neural network for semi-active suspensions. This method surpasses conventional mathematical models in performance and reduces calibration effort. The developed system, logic, and learning method are designed to address AI-specific challenges such as increased processing load and learning techniques, and their performance is validated through simulations and real-world tests. The results show that this system performs on par with those using dedicated sensors.
Influence of the Front-Rear Torque Distribution on the Handling Characteristics and Stability Boundaries of an AWD-Vehicle
Authors: Eberhart Manuel , Arndt Martin , Edelmann Johannes , Plöchl Manfred
Published: October 2024

The influence of the drive torque distribution of an AWD vehicle with individual motors at the front and rear axles on the handling and stability properties is investigated. By applying bifurcation analysis methods, different types of loss of stability at combined longitudinal and lateral acceleration are identified. The impact of the drive torque distribution on the stability boundaries in the GG diagram is examined, and the related stable acceleration envelope is compared to the envelope derived from applying optimisation methods. Representative corresponding handling characteristics are compared and discussed.
Prediction Based Cooperative Adaptive Cruise Control for Heterogeneous Platoons with Delays
Authors: de Haan Redmer , der Sande Tom van , Lefeber Erjen
Published: October 2024

We present a prediction based controller for heterogeneous platoons with actuation delay. By using a prediction of the ego vehicle’s acceleration and compensating the ego vehicle’s influence on the error dynamics, we obtain a controller that achieves input-to-state stability (ISS) with respect to the preceding vehicle’s acceleration. The result is a controller that does not require driveline information of the preceding vehicle, which enables platooning in a heterogeneous setting. An analysis is presented of the string stability properties of the system with both actuation and communication delays. The effectiveness of the controller is shown in simulation.
Iterative Learning Trajectory Tracking Control of an Autonomous Bicycle
Authors: Wang Yixiao , Bruzelius Fredrik , Sjöberg Jonas
Published: October 2024

An autonomous bicycle has been developed for repeatable active safety tests of Advanced Driver Assistance Systems (ADAS). For effective interaction with other test objects, precise bicycle trajectory tracking control is essential. The repetitive nature of these tests suggest an Iterative Learning Control (ILC) approach.

In this paper, we present a design of an ILC controller tailored for the trajectory tracking problem of an autonomous bicycle. To illustrate the performance of the controller, simulations have been conducted.
Temporal and Frequency Analysis with Empirical Mode Decomposition for Vehicle Vibration Signals
Authors: Masuda Makoto , Shiiba Taichi
Published: October 2024

This study presents the empirical mode decomposition method (EMD) for vehicle vibration and a correlation detection approach for input from road and vehicle body vibration using the Hilbert-Huang transform (HHT). Although the magnitude squared coherence is commonly used to examine the correlation of vehicle vibration with road input, it is not suitable for non-stationary vibration. On the other hand, the Hilbert-Huang transform (HHT) which consists of EMD and the Hilbert transform is proposed. This method is suitable for transient vibration analysis, while the drawbacks to intermittence signals are suggested. Vehicle vibration signals include intermittence signals in some cases. In this study, the masking EMD which adapts the mask signal to the amplitude of the target signal was applied to vehicle vibration to alleviate the drawbacks. By this method, the correlation analysis by HHT demonstrates higher temporal resolution compared to the continuous wavelet transform. Thus, it becomes possible to identify the components that caused vibrations at the moments when the passengers felt comfortable or uncomfortable, and to analyze the characteristics of the vibrations.
A Rule-Defined Adaptive MPC Based Motion Planner for Autonomous Driving Applications
Authors: Sathyamangalam Imran Mohammed Irshadh Ismaaeel , Awasthi Satyesh Shanker , Khayyat Michael , Arrigoni Stefano , Braghin Francesco
Published: October 2024

In autonomous driving systems, motion planning to reach a given destination while avoiding obstacles becomes a task entirely managed by the on-board unit. In this work, we present a rule-defined motion planning algorithm for autonomous driving applications based on an adaptive Model Predictive Controller (MPC) framework. The motion planning task is first formulated as an Optimal Control Problem (OCP) subject to time-varying Control Barrier Function (CBF) constraints. It is then integrated within an MPC framework with adaptive weights settings, enabling the algorithm to dynamically adjust the MPC weights according to the rule-defined driving scenarios. The developed motion planner generates optimized trajectories for a high-fidelity Autonomous Vehicle (AV) model within IPG CarMaker software. Simulations performed showed that the developed motion planner adeptly facilitates successful overtaking, following, and stopping of the AV behind the Obstacle Vehicle (OV) based on rule-defined scenarios perceived by the AV.
Investigating Reversing Motion of Truck-Semitrailer Along Clothoid Curve
Authors: Mihályi Levente , Takács Dénes
Published: October 2024

The focus of the research is on the most common transport vehicle, the truck-semitrailer combination. A single-track kinematic model is used, supplemented by the dynamics of the steering system, to design a linear state feedback controller for the low-speed path-following problem in reverse. Despite the significant time delay considered in our study, the linear stability of the system is ensured, even for complicated maneuvers. The advantages of the adaptive gain tuning method are presented based on simulations of the commonly used 90-degree alley dock.
Nipple–Areola Complex Reconstruction Using FixNip NRI Implant after Mastectomy: An Innovative Technique
Authors: Iacovelli Serena , De Palma Giuseppe , De Santis Valerio , Cutrignelli Daniela Anna , Armenio Andrea , Bove Samantha , Comes Maria Colomba , Fanizzi Annarita , Vitale Elsa , Massafra Raffaella , Ressa Cosmo Maurizio
Published: October 2024

Background

Nipple–areolar complex reconstruction is the final stage of breast reconstruction, and it improves quality of life in patients with post-mastectomy breast cancer. We present a case of a patient with breast cancer underwent breast reconstruction and subsequent nipple–areolar complex reconstruction with an innovative biocompatible smooth silicone implant specially designed for a long-lasting restoration of the nipple–areola complex called FixNip NRI. However, to our knowledge, nipple–areolar complex reconstruction with FixNip was not previously reported.

Innovative Technique

We present an emerging technique applied on a patient with breast cancer treated with skin-sparing mastectomy and with immediate breast reconstruction using an expander and then exchanged expander to breast implant. FixNip nipple reconstruction implant is implanted for the reconstruction of the areola–nipple complex with local–regional anaesthesia. She did not develop any postoperatively short-term or long-term complications, and her nipple slowly underwent to a gradual and better definition of its profile.

Conclusion

This new approach regarding the reconstruction of the nipple–areola complex seems to be very promising in relation to both the degree of aesthetic satisfaction of patients and the ease of use by surgeons.

Level of Evidence V

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.
Appendicitis in children: correlation between the surgical and histological diagnosis
Authors: Fadgyas Balazs , Monostori Georgina , Ori Dorottya , Vajda Peter
Published: October 2024

Purpose

Study was designed in order to evaluate the discrepancies between surgical and histological diagnosis in pediatric acute appendicitis (AA) and to compare the outcomes of laparoscopic (LA) and open appendectomies (OA).

Methods

In a retrospective observational cohort, AA patients were included under 18 years of age, operated between 2011 and 2020. Surgical diagnosis was defined by the operating surgeon. The histological findings were classified as uncomplicated and complicated AA. The LOS and complications were also statistically analyzed.

Results

Altogether, 1444 patients were included. Significant strong correlation and a moderate to substantial agreement were found between the surgeon’s and the histopathological findings in all appendectomy cases (weighted kappa value in OA: 0.633, LA: 0.639, total sample: 0.637). If the surgeon’s diagnosis was less severe than the pathologist’s, the LOS was 4 (3;7) days, whereas if the surgical diagnosis was correct, the LOS was 3 (3;5) days (p < 0.0001).

Conclusions

In contrary to the literature, our study revealed a strong correlation and moderate agreement between the intraoperative and histopathological findings regarding the severity of AA. Complicated cases are distinctly recognizable during the surgery. In case the surgeon underestimates the severity of AA, the chance of complications is higher.

Level of evidence: II
The prevalence of abnormal semen parameters in male partners of women with anovulatory polycystic ovarian syndrome: a retrospective case–control study
Authors: Aschauer Judith , Ott Johannes , Selzer Clara , Ghobrial Stefan , Fitz Victoria , Hager Marlene
Published: October 2024

Purpose

Polycystic ovary syndrome (PCOS) is the leading cause of anovulatory infertility, often requiring ovarian stimulation in affected women attempting to conceive. Male partner semen quality and shared lifestyle factors can significantly impact reproductive outcomes. However, current international guidelines lack evidence-based recommendations on the necessity and timing of semen analysis for the fertility management of anovulatory PCOS women.

Methods

In a retrospective case–control study, semen analysis results of male partners of 187 anovulatory PCOS women scheduled for ovarian stimulation were analyzed and compared to a control group of 76 male partners of women with bilateral tubal occlusion.

Results

The prevalence of semen analysis results with at least one parameter classified as “borderline” and “pathological” among male partners of women with PCOS eligible to undergo ovarian stimulation was 51.3% and 22.5%, compared to 44.7% and 13.2% in the control group, respectively (p = 0.027). In the PCOS group, male body mass index (odds ratio, OR 1.478, p < 0.001), and smoking status (OR 6.228, p < 0.001) were significant predictors of pathological sperm test results, while no association was observed with any female characteristics (p > 0.05).

Conclusion

The high frequency of pathological sperm analysis results provides lacking epidemiological data on semen quality in this population, emphasizing the critical need for early male fertility evaluation prior to ovarian stimulation in PCOS women. Moreover, our findings indicate that the risk prediction for abnormal semen quality cannot be based on the female’s data.
The effect of head orientation on vestibular signal-based modulation of paraspinal muscle activity during walking
Authors: Li Yiyuan C. , Lemaire Koen K. , Bruijn Sjoerd M. , Brumagne Simon , van Dieën Jaap H.
Published: October 2024

Background

Vestibulospinal reflexes play a role in maintaining the upright posture of the trunk. Head orientation has been shown to modify the vestibulospinal reflexes during standing. This study investigated how vestibular signals affect paraspinal muscle activity during walking, and whether head orientation changes these effects.

Methods

Sixteen participants were instructed to walk on a treadmill for 8 min at 78 steps/min and 2.8 km/h in four conditions defined by the presence of electrical vestibular stimulation (EVS) and by head orientation (facing forward and facing leftward), while bipolar electromyography (EMG) was recorded bilaterally from the paraspinal muscles from cervical to lumbar levels.

Results

In both head orientations, significant phasic EVS-EMG coherence in the paraspinal muscles was observed at ipsilateral and/or contralateral heel strikes. Compared to walking with the head forward, a significant decrease was found in EVS-evoked responses (i.e., EVS-EMG coherence and gain) when participants walked with the leftward head orientation, with which EVS induced disturbance in the sagittal plane. This overall decrease can be explained by less need of feedback control for walking stabilization in the sagittal plane compared to in the frontal plane. The decrease in coherence was only significant at the left lower vertebral levels and at the right upper vertebral levels around left heel strikes.

Conclusion

These findings confirm the contribution of the vestibular afferent signals to the control of paraspinal muscle activity during walking and indicate that this control is changed in response to different head orientations.

Graphical abstract
MGMT methylation and its prognostic significance in inoperable IDH-wildtype glioblastoma: the MGMT-GBM study
Authors: Ghimire Prajwal , Kamaludin Ahmad , Palau Berta F. , Lavrador Jose P. , Gullan Richard , Vergani Francesco , Bhangoo Ranjeev , Ashkan Keyoumars
Published: October 2024

Introduction

The methylation of the O6-Methylguanine-DNA Methyltransferase (MGMT) promoter is a valid biomarker for predicting response to therapy with alkylating agents and, independently, prognosis in IDH-wildtype(IDH-w) glioblastoma. We aim to study the impact of its methylation in overall survival of the unresectable IDH-w glioblastoma undergoing biopsy and systemic treatment.

Methods

We collected six-year retrospective (2017–2023) data at a quaternary neurosurgery center for patients undergoing biopsy as the only surgical procedure for an unresectable IDH wildtype glioblastoma. Data was collected from patient records including neuro-oncology multidisciplinary team meeting (MDT) documentation. Patients were grouped into categories according to different types of treatment received after biopsy (no treatment, chemotherapy (CT), radiotherapy (RT), chemoradiotherapy (CRT), chemoradiotherapy with adjuvant temozolomide (CRT with adjuvant TMZ), EORTC-NCIC protocol followed by second line treatment) and according to methylation status (unmethylated (< 5%), borderline methylated (5–15%) and strongly methylated (> 15%)). Survival analysis was performed.

Results

166 glioblastoma IDH wildtype patients were included in the study with mean age of 62.5 years (M: F = 1.5: 1). 70 (49.3%) patients had unmethylated MGMT status (< 5%), 29 (20.4%) patients had borderline methylated MGMT status (5–15%) and 43 (30.2%) patients had methylated MGMT status (> 15%). 36 (25.3%) patients did not receive any treatment post biopsy, 13 (9.1%) received CT only, 27 (19%) RT only, 12 (8.4%) CRT, 33 (23.2%) CRT with adjuvant TMZ, whereas 21 (14.7%) received EORTC-NCIC protocol along with second line treatment.

In biopsy only group, there was no notable difference in survival outcomes among the different methylation statuses. For biopsy and any-other-form-of-treatment methylated groups showed a distinct trend of better survival compared to the borderline or unmethylated groups. Overall, methylated patients had better survival as compared to unmethylated or borderline groups.

Conclusion

Methylated MGMT status are predictors for better overall survival in unresectable IDH wildtype glioblastoma patients undergoing biopsy and treatment regardless of the treatment modality.