Amorphous carbon materials with sophisticated morphologies, variable carbon layer structures, abundant defects, and tunable porosities are favorable as anodes for potassium-ion batteries (PIBs). Synthesizing amorphous carbon materials typically involves the pyrolysis of carbonaceous precursors. Nonetheless, there is still a lack of studies focused on achieving multifaceted structural optimizations of amorphous carbon through precursor formulation. Herein, nitrogen-doped amorphous carbon nanotubes (NACNTs) are derived from a novel composite precursor of cobalt-based metal-organic framework (CMOF) and graphitic carbon nitride (g-CN). The addition of g-CN in the precursor optimizes the structure of amorphous carbon such as morphology, interlayer spacing, nitrogen doping, and porosity. As a result, NACNTs demonstrate significantly improved electrochemical performance. The specific capacities of NACNTs after cycling at current densities of 100 mA/g and 1000 mA/g increased by 194 % and 230 %, reaching 346.6 mAh/g and 211.8 mAh/g, respectively. Furthermore, the NACNTs anode is matched with an organic cathode for full-cell evaluation. The full-cell attains a high specific capacity of 106 mAh/gcathode at a current density of 100 mA/g, retaining 90.5 % of the specific capacity of the cathode half-cell. This study provides a valuable reference for multifaceted structural optimization of amorphous carbon to improve potassium-ion storage capability.

To amplify the displacement of the radiation shell, a double-shell type-IV curved hydroacoustic transducer was proposed. Through Ansys finite element simulation, the vibration modes of the transducer in different stages and the harmonic response characteristics in air and water were studied, and the bandwidth emission of the hydroacoustic transducer was achieved. By optimizing the size of each component, the resonant frequency of the transducer is 740 Hz, the maximum conductivity was 0.66 mS, and the maximum transmitting voltage response was 130 dB. According to the optimized parameters, a longitudinal acoustic transducer prototype was manufactured, and a physical test was conducted in an anechoic pool. The obtained resonant frequency was 750 Hz, the maximum conductivity was 0.44 mS, the maximum transmitting voltage response was 129.25 dB, and the maximum linear dimension was 250 mm, which match the simulated value of the virtual prototype and meet the expected requirements.

The acoustically actuated nanomechanical magnetoelectric (ME) antennas represent a promising new technology that can significantly reduce antenna size by 1-2 orders of magnitude compared to traditional antennas. However, current ME antennas face challenges such as low antenna gain and narrow operating bandwidth, limiting their engineering applications. In this paper, we enhance the bandwidth and radiation performance of ME antennas through structural optimization, leveraging theoretical analysis and numerical simulations. Our findings indicate that optimizing the inner diameter of the ring-shaped ME antenna can elevate the average stress of the magnetic layer, leading to improved radiation performance and bandwidth compared to circular ME antennas. We establish an optimization model for the radiation performance of the ME antenna and conduct shape optimization simulations using COMSOL Multiphysics. The results of the Multiphysics field optimization align with the stress concentration theory, demonstrating a strong correlation between the radiation performance and bandwidth of the ME antenna with the average stress of the magnetic film. The resonant frequency in the thickness vibration mode is determined to be 170 MHz. Furthermore, shape optimization can enhance the bandwidth by up to 104% compared to circular ME antenna structures of the same size.

Considering the high strength and excellent biocompatibility of low-nickel stainless steel, this paper focused on optimizing the design of a vascular stent made from this material using finite element analysis (FEA) combined with the response surface methodology (RSM). The aim is to achieve the desired compressive resistance for the stent while maintaining a thin stent wall thickness. The parameters of the stent\'s support unit width (H), strut width (W), and thickness (T) were selected as input parameters, while the output parameters obtained from FEA included the compressive load, the equivalent plastic strain (PEEQ), axial shortening rate, radial recoil rate, and metal coverage rate. The mathematical models of input parameters and output parameters were established by using the Box Behnken design (BBD) of RSM. The model equations were solved under constrained conditions, and the optimal structural parameters, namely H, W, and T, were finally determined as 0.770 mm, 0.100 mm, and 0.075 mm respectively. In this situation, the compression load of the stent reached the target value of 0.38 N/mm; the PEEQ resulting from the stent expansion was small; the axial shortening, radial recoil, and metal coverage index were all minimized within the required range.

Necroptosis is a form of regulated necrotic cell death and has been confirmed to play pivotal roles in the pathogenesis of multiple autoimmune diseases such as rheumatoid arthritis (RA) and psoriasis. The development of necroptosis inhibitors may offer a promising therapeutic strategy for the treatment of these autoimmune diseases. Herein, starting from the in-house hit compound 1, we systematically performed structural optimization to discover potent necroptosis inhibitors with good pharmacokinetic profiles. The resulting compound 33 was a potent necroptosis inhibitor for both human I2.1 cells (IC50 < 0.2 nM) and murine Hepa1-6 cells (IC50 < 5 nM). Further target identification revealed that compound 33 was an inhibitor of receptor interacting protein kinase 1 (RIPK1) with favorable selectivity. In addition, compound 33 also exhibited favorable pharmacokinetic profiles (T1/2 = 1.32 h, AUC = 1157 ng·h/mL) in Sprague-Dawley rats. Molecular docking and molecular dynamics simulations confirmed that compound 33 could bind to RIPK1 with high affinity. In silico ADMET analysis demonstrated that compound 33 possesses good drug-likeness profiles. Collectively, compound 33 is a promising candidate for antinecroptotic drug discovery.

UNASSIGNED: To address the application requirements of soft actuators in rehabilitation training gloves, and in combination with ergonomic requirements, we designed a segmented soft actuator with bending and elongation modules. This actuator can achieve independent or coupled movements of the finger joints.
UNASSIGNED: A finite element model of the joint actuator was established to compare the driving performance of actuators with different structural forms. Numerical calculations were used to analyze the effects of structural size parameters on the bending characteristics and end output force of the actuator. The design was then refined based on these analyses.
UNASSIGNED: The joint actuator designed in this study demonstrated a 71% increase in bending angle compared to the standard fast pneumatic network structure. Key factors affecting the driving performance include the thickness of the constraint layer, the inner wall thickness of the chamber, chamber height, chamber width, chamber spacing, chamber length, and the number of chambers. After improvements, the bending angle of the joint actuator increased by 60.6%, and the output force increased by 145.9%, indicating significant improvement.
UNASSIGNED: This study designed and improved a soft actuator for hand rehabilitation training, achieving independent and coupled joint movements. The bending angle, bending shape, and joint driving force of the soft actuator meet the requirements for finger rehabilitation training.

The clinical performance of biodegradable polymer stents implanted in blood vessels is affected by uneven degradation. Stress distribution plays an important role in polymer degradation, and local stress concentration leads to the premature fracture of stents. Numerical simulations combined with in vitro experimental validation can accurately describe the degradation process and perform structural optimization. Compared with traditional design techniques, optimization based on surrogate models is more scientifically effective. Three stent structures were designed and optimized, with the effective working time during degradation as the optimization goal. The finite element method was employed to simulate the degradation process of the stent. Surrogate models were employed to establish the functional relationship between the design parameters and the degradation performance. The proposed function models accurately predicted the degradation performance of various stents. The optimized stent structures demonstrated improved degradation performance, with the kriging model showing a better optimization effect. This study provided a novel approach for optimizing the structural design of biodegradable polymer stents to enhance degradation performance.

Celangulin V is a novel botanical insecticide with significant bioactivity and a unique molecular target, but its complex polyol ester structure hinders its broader application in agriculture. To discover new analogues of celangulin V with a simpler structure and enhanced biological activities, we initiated a research project aimed at simplifying its structure and assessing insecticidal efficacy. In this study, a series of novel 1-tetralone derivatives were designed via a structure-based rational design approach and synthesized by a facile method. The biological activities of the target compounds were determined against Mythimna separata (M. separata), Plutella xylostella, and Rhopalosiphum padi. The results revealed that most of the synthesized compounds exhibited superior activities compared to celangulin V. Remarkably, the insecticidal activity of compound 6.16 demonstrated 102-fold greater stomach toxicity than celangulin V against M. separata. In addition, certain compounds showed significant contact toxicity against M. separata, a finding not reported previously in the structural optimization studies of celangulin V. Molecular docking analysis illustrated that the binding pocket of compound 6.16 with the H subunit of V-ATPase was the same as celangulin V. This study presents novel insights into the structural optimization of botanical pesticides.

This paper discusses the influence of the digital economy (DE) on carbon emissions based on evidence at the global level. Specifically, based on the panel data from 80 countries from 2010 to 2020, this paper creates a DE measurement index and uses the System-GMM model to assess the influence of DE on carbon emissions. The results show that: (1) The development of DE significantly promotes carbon emissions reduction. (2) The development of DE significantly promotes carbon emissions reduction through technological advancement, structural optimization, and educational enhancement; (3) Regulatory quality and financial development play a positively moderating role in DE\'s promoting effect on carbon emissions reduction; (4) DE of European and North American nations have stronger promoting effect on carbon emissions reduction than DE of other countries. Compared to DE of developing countries, DE of developed countries has a stronger promoting effect on carbon emissions reduction. Additionally, this paper also finds that institutional differences can impact the carbon emission reduction effects of DE. Based on the results, this paper suggests that governments globally should promote the development of DE and foster international cooperation to enhance DE\'s driving role in promoting carbon emissions reduction.

Land use changes have profoundly influenced global environmental dynamics. The Yellow River (YR), as the world\'s fifth-longest river, significantly contributes to regional social and economic growth due to its extensive drainage area, making it a key global player. To ensure ecological stability and coordinate land use demand, modeling the future land allocation patterns of the Yellow River Basin (YRB) will assist in striking a balance between land use functions and the optimization of its spatial design, particularly in water and sand management. In this research, we used a multi-objective genetic algorithm (MOGA) with the PLUS model to simulate several different futures for the YRB\'s land use between 1990 and 2020 and predict its spatial pattern in 2030. An analysis of the spatiotemporal evolution of land use changes in the YRB indicated that construction land expansion is the primary driver of landscape pattern and structure changes and ecological degradation, with climate change also contributing to the expansion of the watershed area. On the other hand, the multi-scenario simulation, constrained by specific targets, revealed that economic development was mainly reflected in land expansion for construction. At the same time, grassland and woodland were essential pillars to support the region\'s ecological health, and increasing the development of unused land emerged as a potential pathway towards sustainable development in the region. This study could be used as a template for the long-term growth of other large river basins by elucidating the impacts of human activities on land use and rationalizing land resource allocation under various policy constraints.