bluuebunny/crossref_metadata_2025_split huggingface dataset:
SAM: Semi‐Active Mechanism for Extensible Continuum Manipulator and Real‐Time Hysteresis Compensation Control Algorithm
Authors: Park Junhyun , Jang Seonghyeok , Park Myeongbo , Park Hyojae , Yoon Jeonghyeon , Hwang Minho 
Published: December 2024

ABSTRACTBackgroundCable‐driven continuum manipulators (CDCMs) enable scar‐free procedures but face limitations in workspace and control accuracy due to hysteresis.MethodsWe introduce an extensible CDCM with a semi‐active mechanism (SAM) and develop a real‐time hysteresis compensation control algorithm using a temporal convolution network (TCN) based on data collected from fiducial markers and RGBD sensing.ResultsPerformance validation shows the proposed controller significantly reduces hysteresis by up to 69.5% in random trajectory tracking test and approximately 26% in the box pointing task.ConclusionThe SAM mechanism enables access to various lesions without damaging surrounding tissues. The proposed controller with TCN‐based compensation effectively predicts hysteresis behaviour and minimises position and joint angle errors in real‐time, which has the potential to enhance surgical task performance.
Optimal Tampering Attack Strategy for FIR System Identification With Multi‐Level Quantized Observations
Authors: Liu Wenke , Jing Fengwei , Wang Yinghui , Guo Jin 
Published: December 2024

ABSTRACTThis paper considers the optimal tampering attack strategy in system identification of Finite Impulse Response (FIR) systems with multi‐level quantized observations under data tampering attacks. First, the data tampering attack model based on a multi‐level quantization system is established in a conditional probability manner according to the features of the quantization system. Second, a multi‐parameter‐based system parameter estimation algorithm is designed and its convergence consistency is proved. Then, according to the convergence of the designed identification algorithm under a tampering attack, the infinite paradigm of the difference between the converged value and the actual parameter after the attack is used as the attack index, and the optimal tampering attack strategy is designed to destroy the consistency of the recognition algorithm so as to make the best attack effect achieved. Finally, numerical simulation experiments under different conditions are used to verify the result.
Complementary Filter‐Based Incremental Nonlinear Model Following Control Design for a Tilt‐Wing UAV
Authors: Autenrieb Johannes , Shin Hyo‐Sang 
Published: December 2024

ABSTRACTThis article presents an incremental nonlinear model following control (INMFC) strategy for a tilt‐wing vertical take‐off and landing (VTOL) unmanned aerial vehicle (UAV). To ensure a good and robust regulation performance, a two‐loop feedback controller, based on the incremental backstepping (IBS) methodology, is used to handle uncertainties and external disturbances robustly. In order to ensure a good mode following and to aid the tracking performance of the flight control system, the first and second‐time derivatives of the desired model response, computed by a model reference (MR) system, are either directly used as feedforward signals for the outer loop or are additionally transformed for the inner‐loop by using an incremental nonlinear dynamic inversion (INDI) grounded approach to transform the signals based on known systems kinematics. In order to uniformly handle the overactuated flight vehicle in both mission model and during the transition, an operation mode‐based weighted incremental linear control allocation approach is applied for safe operation. The performance of the suggested control approach is investigated by utilizing a high‐fidelity nonlinear flight dynamics model of the tilt‐wing system. The results presented in this paper demonstrate that the proposed control approach provides significant benefits for the robust control of the considered tilt‐wing UAV.
A Nonsingular Fixed‐Time Sliding Mode Controller for Robot Manipulators in the Presence of External Perturbations and Partially Known Model
Authors: Arteaga Marco A. , Moulay Emmanuel , Defoort Michael 
Published: December 2024

ABSTRACTThe current contribution introduces a nonsingular fixed‐time sliding mode control (SMC) scheme for position and velocity tracking of robot manipulators. The approach avoids singularities by introducing a new sliding surface with the special attribute that the exponent employed to achieve fixed time convergence depends on the tracking error and is smaller than one except when the error is exactly zero, whereas the exponent becomes one at zero, which makes the derivative at zero to be well defined. A new theoretical result has been introduced in the form of a lemma to prove this innovative property. Furthermore, model uncertainties are handled by means of a time‐varying gain given by a polynomial of the powers of the norms of the tracking and velocity errors. The fixed‐time convergence is proven employing Lyapunov theory, and the result holds globally. Simulation outcomes confirm the developed theory, and the advantages of the proposed scheme are shown qualitatively by comparing its performance with well‐known equivalent control schemes.
Event‐Triggered Based Differential Privacy Distributed Optimization
Authors: Wang Pinlin , Wang Zhenqian , Lü Jinhu 
Published: December 2024

ABSTRACTDistributed optimization has emerged as a pivotal research area with widespread applications in machine learning and networked systems. While optimization algorithms efficiently collaborate to minimize a global objective function through information exchange among nodes, they are susceptible to privacy breaches, potentially leading to severe and unpredictable consequences. As differential privacy becomes the de facto standard for privacy preservation, recent studies have integrated differential privacy with distributed optimization. However, existing differential privacy distributed optimization algorithms typically require continuous communication and noise injection, which results in substantial communication overhead and degraded optimization performance. In this paper, we introduce a novel event‐triggered based differential privacy distributed optimization algorithm that leverages intermittent Laplace noise injection. Recognizing that event‐triggered timings may inadvertently reveal gradient information about the objective function, we introduce an enhanced ‐Differential Privacy definition specifically tailored for event‐triggered communication, accounting for both the transmitted state information and the event‐triggered timings. By intermittently injecting Laplace noise, our mechanism significantly reduces the total amount of noise required, thereby minimizing its negative impact on the algorithm's performance. We rigorously prove that, even with reduced noise, our algorithm ensures rigorous privacy preservation. Furthermore, our algorithm achieves accurate convergence and improved optimization performance in constrained optimization problems, while reducing communication overhead. Numerical simulations confirm the effectiveness of our proposed algorithm.
Generation and Application of Reactive Oxygen Radicals in Cancer Treatment
Authors: Patial Taniya , Sharma Niharika , Sharma Kunal , Mishra Vivek 
Published: December 2024

AbstractReactive oxygen species (ROS) play a dual role in cancer, influencing both tumor growth and regression. Their intricate involvement in cellular processes underscores the necessity of maintaining a delicate ROS balance for normal cellular function. Intriguingly, while ROS contribute to tumor progression, they also exhibit the potential to selectively kill cancer cells. Emerging therapeutic strategies focus on modulating ROS levels within cancer cells, considering the type of radicals generated, their site of formation, and concentration gradients. This review delves into recent advancements in understanding the impact of ROS on the tumor microenvironment and cancer treatment. By exploring the interplay between ROS dynamics and therapeutic outcomes, this study provides a comprehensive perspective on the pivotal role of oxygen‐related free radicals in cancer therapy and highlights the innovative approaches and insights shaping this rapidly evolving field.
Novel Antiviral Phytochemicals Against Dengue Virus 2 NS2B‐NS3 Protease: An In Silico Drug Development Approach
Authors: Bari Muhammad Abdul , Ahmed Sabbir , Perveen Faria Farzana , Akter Mahfuza , Ahmed Nasim , Hossain Jakaria , Nasrulla Md. , Akter Khadiza , Islam Md. Nurul 
Published: December 2024

AbstractDengue fever, a viral disease transmitted by mosquitoes, presents a major public health risk in tropical and subtropical regions globally. Currently, there is no treatment to fight against this disease. The dengue virus 2 (DENV2) NS2B‐NS3 protease is critical for viral replication, making it a promising target for drug discovery. This study aims to identify potential inhibitors against the DENV2 NS2B‐NS3 protease using in silico methods, including molecular docking, ADMET analysis, molecular dynamics simulations, MMGBSA, and DFT calculations. We screened 1138 phytochemicals from the NuBBE database against the NS2B‐NS3 protease (PDB ID: 2FOM) and compared their binding affinities to policresulen, reported as DENV2 NS2B‐NS3 protease inhibitor. Four novel phytochemicals: 3′,4′‐methylenedioxy‐7,8‐(2″,2″‐dimethylpyrano)‐flavone; limonianin; gnetin‐B; and 5,4′‐dihydroxy‐3′,5′‐dimethoxy‐6,7‐(2″,2″‐dimethylpyran)flavonen revealed binding affinities of −8.7, −8.0, −7.8, and −7.8 kcal/mol, respectively, surpassing the reference compound's affinity of −7.0 kcal. Additionally, MD simulations over 100 ns confirmed the stability of these compounds bound with the target protein. Moreover, ADMET analysis demonstrated favorable pharmacokinetic and toxicity profiles, whereas MMGBSA and DFT calculations supported their binding consistency and reactivity. In conclusion, this study discovered promising novel phytochemicals against DENV2 NS2B‐NS3 protease, which could serve as potential leads for developing effective antiviral therapies for the treatment of dengue fever.
Determination of Antioxidant, Antimicrobial and Anticancer Properties of Newly Synthesized 2‐methoxyphenyl Thiophene Derivatives
Authors: Çetin Doğan , Konuş Metin , Yılmaz Can , Arslan Şevki , Abdelsalam AmineHafis , Hutanu Elena Daniela , Kurt Kızıldoğan Aslıhan , Otur Çiğdem , Hama AzadKhalaf , Kivrak Arif 
Published: December 2024

AbstractIn this study, antioxidants, anticancer, and antimicrobial properties of four newly synthesized thiophene derivatives were investigated. In addition, basic ADME properties were calculated in silico. According to the study's findings, tested compounds antioxidant activity was weaker than the standards in both the FRAP and ABTS assays. The MTT analysis revealed that the chemicals 3 and 4 were cytotoxic to every cancer cell line that was tested. 3 and 4 increased the rate of apoptosis in the tested cancer cells at levels close to that in the positive control group. The gene expression levels of apoptotic markers (BAX, Bcl‐2, Casp‐3, ‐8, and ‐9) detected at all cell lines after incubation with 3 and 4 were changed as expected for apoptotic agents, except Bcl‐2 of HT‐29. It was concluded that the addition of bromine to C2 of thiophene cycle of 3, resulted 4 with greater apoptotic potential probably because of a change in molecular conformation and ligand exchange kinetics. Compound 3 was found to have antifungal activity against Aspergillus niger, while 4 was found to have antibacterial activity on gram‐positive bacteria. In silico ADME/T analysis revealed that 3 and 4 were able to pass through the gastrointestinal tract lumen and blood‐brain barrier.
Large Language Model‐Assisted Genotoxic Metal‐Phenolic Nanoplatform for Osteosarcoma Therapy
Authors: Fan Qingxin , He Yunxiang , Liu Jialing , Liu Qinling , Wu Yue , Chen Yuxing , Dou Qingyu , Shi Jing , Kong Qingquan , Ou Yunsheng , Guo Junling 
Published: December 2024

AbstractOsteosarcoma, a leading primary bone malignancy in children and adolescents, is associated with a poor prognosis and a low global fertility rate. A large language model‐assisted phenolic network (LLMPN) platform is demonstrated that integrates the large language model (LLM) GPT‐4 into the design of multifunctional metal‐phenolic network materials. Fine‐tuned GPT‐4 identified gossypol as a phenolic compound with superior efficacy against osteosarcoma after evaluating across a library of 60 polyphenols based on the correlation between experimental anti‐osteosarcoma activity and multiplexed chemical properties of polyphenols. Subsequently, gossypol is then self‐assembled into Cu2+‐gossypol nanocomplexes with a hyaluronic acid surface modification (CuGOS NPs). CuGOS NPs has demonstrated the ability to induce genetic alterations and cell death in osteosarcoma cells, offering significant therapeutic benefits for primary osteosarcoma tumors and reducing metastasis without adverse effects on major organs or the genital system. This work presents an LLM‐driven approach for engineering metal‐organic nanoplatform and broadening applications by harnessing the capabilities of LLMs, thereby improving the feasibility and efficiency of research activities.
Banana Starch Nanoparticles Disrupt the Integrity of the Intestinal Barrier by Opening Tight Junctions in Mice
Authors: Jiang Bing , Peng Chenglu , Li Xiaoyang , Sun Cuixia , Lu Wei , Fang Yapeng 
Published: December 2024

AbstractThe banana‐derived starch nanoparticles have been extensively used in food and biomedicine industries, due to their unique physicochemical properties and functional benefits. With their pervasive presence in food, people are significantly exposed to these nanoparticles, raising concerns about their potential health risks and impact on intestinal health. However, there is still limited understanding of the direct interaction between native banana starch nanoparticles (BSNs) and the intestinal systems. Here, it is demonstrated that BSNs can cause tight junctions to loosen, increase intestinal permeability, and disrupt the intestinal barrier. This increased permeability is closely linked to the size of BSNs, with smaller BSNs (d = 60 nm) having a stronger effect on permeation. Furthermore, the disruption of the intestinal barrier integrity caused by BSNs is connected to a reduced amount of tight junction proteins. Mechanistically, BSNs disrupt tight junctions by affecting mitochondrial function and activating myosin light chain kinase (MLCK) signaling pathway. These findings indicate that BSNs have the potential to pose health risks by compromising the integrity of the intestinal barrier, reminding the safety of food biopolymer nanoparticles in living organisms needs to be re‐assessed.
Isomeric Cu(I) Azolate Frameworks Showing Contrasting Electrocatalytic CO2 Reduction Selectivities and Stabilities
Authors: Zheng Kai , Hu Ding‐Yi , Wang Chao , Liang Zi‐Jun , Zhang Xue‐Wen , Xiao Xian‐Xian , Wu Jun‐Xi , Zhuo Lin‐Ling , Lin Duo‐Yu , Zhou Dong‐Dong , Zhang Jie‐Peng 
Published: December 2024

AbstractMetal‒organic frameworks have attracted wide interest in the electrocatalytic CO2 reduction reaction (eCO2RR), but their differences of performances originated from chemical composition and stabilities are rarely concerned. Here, isomeric Cu(I) triazolate frameworks (MAF‐2Fa and MAF‐2Fb) with similar thermal/chemical stabilities but very different coordination modes are used for eCO2RR studies. MAF‐2Fa with monotypic planar dinuclear Cu(I) coordination mode achieves high selectivity for C2H4 (53%) and C2 products (70%), with almost unchanged over a wide potential window (‒1.1 to ‒1.5 V), making it among one of the best Cu‐complex electrocatalysts. In contrast, MAF‐2Fb with multiple Cu(I) coordination modes (including planar/bent dinuclear, linear mononuclear, and trigonal mononuclear ones) showed low C2/C1 products without significant differences. More interestingly, MAF‐2Fa can maintain its performance for at least 8 h, whereas MAF‐2Fb decomposed into inorganics with inferior performance after 1.5 h. The significant differences of eCO2RR selectivities and stabilities are elucidated by computational simulations and operando electrochemical tests.
Emergent Skyrmions in Cr0.85Te nanoflakes at Room Temperature
Authors: Ni Yan , Guo Yongxiang , Jiang Yuan‐Yuan , Huang Ting , Mu Qiuxuan , Hou Feiyan , Li Tiaoyang , Wang Shaohao , Zhang Zhen , Shao Dingfu , Ding Xiangdong , Min Tai , Li Tao 
Published: December 2024

AbstractChiral noncollinear magnetic nanostructures, such as skyrmions, are intriguing spin configurations with significant potential for magnetic memory technologies. However, the limited availability of 2D magnetic materials that host skyrmions with Curie temperatures above room temperature presents a major challenge for practical implementation. Chromium tellurides exhibit diverse spin configurations and remarkable stability under ambient conditions, making them a promising platform for fundamental spin physics research and the development of innovative 2D spintronic devices. Here, domain structures of Cr0.85Te nanoflakes synthesized via chemical vapor deposition are investigated, using magnetic force microscopy at room temperature. The results reveal that the domain width of the as‐grown nanoflakes scales with the square root of their thicknesses. Notably, the emergence and annihilation of skyrmions are observed, which can be reversibly controlled by external magnetic fields and thermal excitation in ambient air. Micromagnetic simulations suggest that the emergence of skyrmions in Cr0.85Te nanoflakes arises from inversion symmetry breaking due to compositional gradients across the sample thickness, rather than the interfacial Dzyaloshinskii–Moriya interaction. These findings provide new insights into the mechanisms underlying skyrmion formation in 2D ferromagnets and open exciting possibilities for manipulating domain structures at room temperature, offering practical pathways for developing next‐generation spintronic devices.
Evolving Emulsion Microcompartments via Enzyme‐Mimicking Amyloid‐Mediated Interfacial Catalysis
Authors: Song Peiyong , Chen Jing , Zhao Dan , Shi Ke , Xu Runze , Zhu Mengyue , Zhao Li , Pashuck E. Thomas , Ouyang Liliang , Jiao Fang , Lin Yiyang 
Published: December 2024

AbstractLiving organisms take in matter and energy from their surroundings, transforming these inputs into forms that cells can use to sustain metabolism and power various functions. A significant advancement in the development of protocells and life‐like materials has been the creation of cell‐like microcompartments capable of evolving into higher‐order structures characterized by hierarchy and complexity. In this study, a smart emulsion system is designed to digests chemical substrates and generates organic or inorganic products, driving the self‐organization and structuration of microcompartments. Central to this system is a lipase‐derived peptide that undergoes amyloid fibrillation, exhibiting hydrolase‐like activity and stabilizing Pickering emulsions. Through catalytic hydrolysis or silicatein‐inspired mineralization, these emulsion microcompartments generate self‐organized surfactant layers from organic substrates or silica scaffolds from inorganic substrates at the oil–water interface, respectively, helping to prevent coalescence. This process further facilitates a structural evolution into high‐internal phase emulsion gels that are suitable for direct‐ink‐writing 3D printing. The findings underscore the potential for designing self‐evolving soft materials that replicate the structures and functions of living organisms.
Cellular Interactions and Biological Effects of Silk Fibroin: Implications for Tissue Engineering and Regenerative Medicine
Authors: Zhu Jialin , Du Yan , Backman Ludvig J. , Chen Jialin , Ouyang Hongwei , Zhang Wei 
Published: December 2024

AbstractSilk fibroin (SF), the core structural protein derived from Bombyx mori silk, is extensively employed in tissue engineering and regenerative medicine due to its exceptional mechanical properties, favorable biocompatibility, tunable biodegradability, and versatile processing capabilities. Despite these advantages, current research predominantly focuses on SF biomaterials as structural scaffolds or drug carriers, often overlooking their potential role in modulating cellular behavior and tissue regeneration. This review aims to present a comprehensive overview of the inherent biological effects of SF biomaterials, independent of any exogenous biomolecules, and their implications for various tissue regeneration. It will cover in vitro cellular interactions of SF with various cell types, including stem cells and functional tissue cells such as osteoblasts, chondrocytes, keratinocytes, endothelial cells, fibroblasts, and epithelial cells. Moreover, it will summarize in vivo immune responses, cellular responses, and tissue regeneration following SF implantation, specifically focusing on vascular, bone, skin, cartilage, ocular, and tendon/ligament regeneration. Furthermore, it will address current limitations and future perspectives in the design of bioactive SF biomaterials. A comprehensive understanding of these cellular interactions and the biological effects of SF is crucial for predicting regenerative outcomes with precision and for designing SF‐based biomaterials tailored to specific properties, enabling broader applications in regenerative medicine.
2D Polyamides Enable Self‐Healing and Recyclable Elastomers with High Robustness, Toughness, and Crack Resistance via Supramolecular Interactions
Authors: Xing Yuedong , Li Jiongchao , Cheng Jie , Lu Liwei , Xue Tao , Xu Jianben , Xu Xiang , Zhang Faai 
Published: December 2024

AbstractHigh‐performance elastomers with exceptional mechanical properties and self‐healing capabilities have garnered significant attention due to their wide range of potential applications. However, designing elastomers that strike a balance between self‐healing capabilities and mechanical properties remains a considerable challenge. Inspired by biological cartilage, a highly robust, tough, and crack‐resistant self‐healing elastomer is presented by incorporating hydrogen‐bond‐rich 2D polyamide (2DPA) into a poly(urethane‐urea) matrix. This integration enhances supramolecular interactions driven by multiple hydrogen bonds. The resulting elastomer exhibits impressive strength (54.6 MPa), remarkable elongation at break (705.4%), exceptional toughness (116.7 MJ m−3), outstanding crack resistance (fracture energy up to 187.2 kJ m−2), high self‐healing efficiency (98.9% at 50 °C for 9 h, 97.9% at room temperature for 48 h), and excellent recyclability, capable of lifting ≈40 000 times its own weight. Furthermore, a damage‐tolerant, fatigue‐resistant anticorrosive coating from this elastomer, showcasing its potential for protective skin applications in underwater robotics is developed. The underlying enhancement mechanism is validated through testing of various elastomers and molecular dynamics simulations, confirming the potential of engineering 2DPA for high‐performance elastomers by leveraging supramolecular interactions.