Bidirectional rotating direct-current triboelectric nanogenerator with self-adaptive mechanical switching for harvesting reciprocating motion

Amid the growing interest in triboelectric nanogenerators(TENGs)as novel energy-harvesting devices,several studies have focused on direct current(DC)TENGs to generate a stable DC output for operating electronic devices.However,owing to the working mechanisms of conventional DC TENGs,generating a stable DC output from reciprocating motion remains a challenge.Accordingly,we propose a bidirectional rotating DC TENG(BiR-TENG),which can generate DC outputs,regardless of the direction of rotation,from reciprocating motions.The distinct design of the BiR-TENG enables the mechanical rectification of the alternating current output into a rotational-direction-dependent DC output.Furthermore,it allows the conversion of the rotational-direction-dependent DC output into a unidirectional DC output by adapting the configurations depending on the rotational direction.Owing to these tailored design strategies and subsequent optimizations,the BiR-TENG could generate an effective unidirectional DC output.Applications of the BiR-TENG for the reciprocating motions of swinging doors and waves were demonstrated by harnessing this output.This study demonstrates the potential of the BiR-TENG design strategy as an effective and versatile solution for energy harvesting from reciprocating motions,highlighting the suitability of DC outputs as an energy source for electronic devices.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

The control of welding wire feed self-adaptive mechanism based on fuzzy PID

The welding wire feed mechanism is an important component of welding equipment, both reliability and stabilization are the premise that the welding quality can be ensured. The PID is currently adapted to control the welding wire feed mechanism, although the fuzzy PID has advantage of fast response and adaptation, the precision of fuzzy PID is lower. Accordingly, the fuzzy self-adaptive PID controller was proposed through changing fuzzy input variables and output variables based on variable universe, simple furwtion is adopted as scaling factor, the fuzzy PID controller parameters are adjusted to improve the precision and adjustment range. Simulation results show that control effects of fuzzy self-adaptive PID adopted by the welding wire feed mechanism have good adaptive ability and robustness based on variable universe, the welding experiments indicate that the welding quality met the requirements actually.

Effect of the Gut Microbiota on Obesity and Its Underlying Mechanisms: an Update

Obesity has become one of the most prevalent health issues of our time. According to a 2012 WHO report, around 3.4 million adults die each year as a result of being overweight or obese. Humans are in fact superorganisms composed of both human and microbial cells with 2 sets of genes, those encoded in our own genome and those encoded in our microbiota. All these cells and genes have the potential to influence our health.

Marchenko imaging based on self-adaptive traveltime updating

Marchenko imaging obtains the subsurface reflectors using one-way Green’s functions,which are retrieved by solving the Marchenko equation.This method generates an image that is free of spurious artifacts due to internal multiples.The Marchenko imaging method is a target-oriented technique;thus,it can image a user specified area.In the traditional Marchenko method,an accurate velocity model is critical for estimating direct waves from imaging points to the surface.An error in the velocity model results in the inaccurate estimation of direct waves.In turn,this leads to errors in computation of one-way Green’s functions,which then affects the final Marchenko images.To solve this problem,in this paper,we propose a self-adaptive traveltime updating technique based on the principle of equal traveltime to improve the Marchenko imaging method.The proposed method calculates the time shift of direct waves caused by the error in the velocity model,and corrects the wrong direct wave according to the time shift and reconstructs the correct Green’s functions.The proposed method improves the results of imaging using an inaccurate velocity model.By comparing the results from traditional Marchenko and the new method using synthetic data experiments,we demonstrated that the adaptive traveltime updating Marchenko imaging method could restore the image of geological structures to their true positions.

A Hand Prosthesis with an Under-Actuated and Self-Adaptive Finger Mechanism

One of the major problems faced by hand amputees is the unavailability of a lightweight and powered multi-functional hand prosthesis. Under-actuated finger designs play a key role to make the hand prosthesis lightweight. In this paper, a hand prosthesis with an under-actuated and self-adaptive finger mechanism is proposed. The proposed finger is capable to generate passively different flexion/extension angles for a proximal interphalangeal (PIP) joint and a distal interphalangeal (DIP) joint for each flexion angle of metacarpophalangeal (MCP) joint. In addition, DIP joint is capable to generate different angles for the same angle of PIP joint. Hand prosthesis is built on the proposed finger mechanism. The hand prosthesis enables user to grasp objects with various geometries by performing five grasping patterns. Thumb of the hand prosthesis includes opposition/apposition in addition to flexion/extension of MCP and interphalangeal (IP) joint. Kinematic analysis of the proposed finger has been carried out to verify the movable range of the joints. Simulations and experiments are carried out to verify the effectiveness of the proposed finger mechanism and the hand prosthesis.

Enhanced Chimp Optimization Algorithm Using Attack Defense Strategy and Golden Update Mechanism for Robust COVID-19 Medical Image Segmentation

Medical image segmentation is a powerful and evolving technology in medical diagnosis.In fact,it has been identified as a very effective tool to support and accompany doctors in their fight against the spread of the coronavirus(COVID-19).Various techniques have been utilized for COVID-19 image segmentation,including Multilevel Thresholding(MLT)-based meta-heuristics,which are considered crucial in addressing this issue.However,despite their importance,meta-heuristics have significant limitations.Specifically,the imbalance between exploration and exploitation,as well as premature convergence,can cause the optimization process to become stuck in local optima,resulting in unsatisfactory segmentation results.In this paper,an enhanced War Strategy Chimp Optimization Algorithm(WSChOA)is proposed to address MLT problems.Two strategies are incorporated into the traditional Chimp Optimization Algorithm.Golden update mechanism that provides diversity in the population.Additionally,the attack and defense strategies are incorporated to improve the search space leading to avoiding local optima.The experimental results were conducted by comparing WSChoA with recent and well-known algorithms using various evaluation metrics such as Feature Similarity Index(FSIM),Structural Similarity Index(SSIM),Peak signal-to-Noise Ratio(PSNR),Standard deviation(STD),Freidman Test(FT),and Wilcoxon Sign Rank Test(WSRT).The results obtained by WSChoA surpassed those of other optimization techniques in terms of robustness and accuracy,indicating that it is a powerful tool for image segmentation.

Mechanical Eye Trauma Epidemiology, Prognostic Factors, and Management Controversies—An Update

Purpose of Review: The management of eye injuries is both difficult and argumentative. This study attempts to highlight the management of ocular trauma using currently available information in the literature and author experience. This review presents a workable framework from the first presentation, epidemiology, classification, investigations, management principles, complications, prognostic factors, final visual outcome and management debates. Review Findings: Mechanical ocular trauma is a leading cause of monocular blindness and possible handicap worldwide. Among several classification systems, the most widely accepted is Birmingham Eye Trauma Terminology (BETT). Mechanical ocular trauma is a topic of unsolved controversy. Patching for corneal abrasion, paracentesis for hyphema, the timing of cataract surgery and intraocular lens implantation are all issues in anterior segment injuries. Regarding posterior segment controversies, the timing of vitrectomy, use of prophylactic cryotherapy, the necessity of intravitreal antibiotics in the absence of infection, the use of vitrectomy vs vitreous tap in traumatic endophthalmitis is the issues. The pediatric age group needs to be approached by a different protocol due to the risk of amblyopia, intraocular inflammation, and significant vitreoretinal adhesions. The various prognostic factors have a role in the final visual outcome. B scan is used to exclude R.D, Intraocular foreign body (IOFB), and vitreous haemorrhage in hazy media. Individual surgical strategies are used for every patient according to the classification and extent of the injuries. Conclusion: This article examines relevant evidence on the management challenges and controversies of mechanical trauma of the eye and offers treatment recommendations based on published research and the authors’ own experience.

开洞刚性墙后土体破坏模式运动单元上限分析

超载作用下开洞地下刚性连续墙后土体稳定性问题具有广泛的工程应用背景。考虑墙体矩形开洞宽度足够大,且刚性墙与土体完全光滑接触等条件,参考构造刚性多块体上限法思路,预设墙后土体极简破坏机构并转化为初始三角网格,提出交替循环式新增节点、单元缩减、对角互换及成层加密等网格更新措施,同步开展基于刚体平动运动单元上限方法的刚性墙后土体破坏分析,通过多层级非线性规划运算获得高精度临界超载系数σ_(s)/c上限解,界定墙后土体滑移线网破坏模式及其定量范围与扩展边界。进一步依前述流程计算获得多参数影响下的临界超载系数σ_(s)/c上限解图表,结果表明:1)刚性墙后土体典型破坏特征表现为土体上方和开洞处的整体下沉刚性区域,开洞前方核心区域以密集滑移线网区隔的刚性滑块群,以及外围主要滑动面;2)临界超载系数σ_(s)/c随土体内摩擦角ϕ增大而增大,且后续增幅显著增加;3)σ_(s)/c随开洞深度比C/D的增大呈现出近似线性增大的趋势;4)相较于ϕ和C/D,土体重度参数γD/c的变化对于σ_(s)/c的影响不甚明显,σ_(s)/c随γD/c增大呈现近似线性减小的趋势;5)σ_(s)/c受剪胀角参数ψ/ϕ的影响与ϕ的增大程度密切相关。本研究结果可为开洞地下刚性连续墙后土体失稳破坏模式定量分析、破坏机理研究及工程措施制定等工作提供有力的数据支持。

基于城市更新动力类型评价的更新模式研究——以丹江口市老城区为例

随着中国城镇化率超过60%,城市发展开始由过去大规模的增量建设向存量提质改造和增量结构优化并重转变,城市更新在这个过程中发挥着重要作用。城市更新从一种技术手段,向综合的政策转变。在当前实践中,城市更新的模式选择仍缺乏一定的客观性,呈现粗放化的态势。通过对城市更新动力的分解,发现更新模式的选择与主导力量之间存在直接关联。本文以研究区域内地块所受的主要动力作为更新类型的评判标准,构建评价指标体系。以丹江口市老城区为例开展实证研究,依据评价结果对更新单元进行类型划分,并根据不同的类型提出针对性的更新模式选择建议。研究表明,基于动力差异评价得到的单元更新类型,是客观选择更新模式的重要依据,对城市更新的精细化发展、促进更新规划的科学实施具有重要意义。

基于改进蜘蛛蜂算法的无人机三维路径规划

为了提高无人机路径规划在复杂环境中的收敛速度和收敛精度,避免陷入局部最优,提出了一种基于改进蜘蛛蜂算法的无人机三维路径规划方法。本文在传统SWO算法中引入自适应t分布扰动变异和Cubic映射策略更新搜索阶段位置,避免局部早熟收敛;然后,引入周期性随机振幅动态调整追逐和逃逸阶段搜索方向,帮助算法跳出局部最优,并结合螺旋更新机制和Levy飞行策略增强算法全局寻优能力,提高算法收敛精度;最后,将ISWO算法在8个测试函数中进行性能验证并实验仿真,结果表明,复杂地形环境中ISWO算法执行时间相比传统SWO算法减少了26.86%,并且较CPO、COA、GOOSE、PSO、GWO算法执行时间减少了13.80%~28.27%不等。同时,ISWO算法最小适应度值较传统SWO算法减小49.76%,较其他算法至少减小27.73%。由此得出,本文所提改进算法能够在复杂地形环境中快速得到一条更短且更安全的路径。

融合蚁群算法框架下区域资源的动态调度模型

针对目前电力作业人力资源调度主要依赖于人工经验的现状,文中提出了基于改进蚁群算法的区域资源动态调度模型。该模型以花费总时间与总成本最小为优化目标,考虑了任务的资源需求、先后顺序等方面的约束条件。同时,结合区域资源动态调度模型的特性,对传统蚁群算法进行了改进设计,提出了优化的编码解码方法、蚁群动态更新机制及2-opt局部搜索方法等策略。算例分析结果表明,所提改进蚁群算法相比于传统蚁群算法具有更快的收敛速度和更高的计算准确度。在实际电力作业调度中,对比传统蚁群算法,所设计模型能够减少总时间约12%,降低总成本约10%。

小样本积木式可靠性评估与更新方法

针对工程上只能进行极少甚至无法进行整机寿命试验,导致可靠性评估精度不高的情况,提出一种小样本积木式可靠性评估与更新方法。首先建立了能够根据机电产品子系统当前试验、以往试验和以往服役寿命数据,对其整机高置信度、高可靠度的可靠寿命进行评估的方法,从而解决了机电产品无法进行整机寿命试验时的可靠性评估难题,为其外场使用提供了科学依据。然后给出了能够根据该机电产品整机试验寿命数据和外场服役寿命数据对上述可靠寿命评估结果进行更新的方法,从而增大了信息量,显著提高其可靠性评估精度。文中针对工程上常用的指数分布、Weibull分布和对数正态分布情况进行了详细讨论,给出了相应的整机高置信度、高可靠度的可靠寿命评估与更新公式。

去中心化分布式控制系统设计研究

针对上万个被控对象,传统的分布式控制系统无法实现控制器与服务器去中心化,导致效率低且故障率高,设计了一种去中心化分布式控制系统。该系统中的控制器、被控对象、传感器及执行器、服务器通过控制网络进行通信传输,利用冗余备份机制进行控制器动态切换,从而实现控制器去中心化,利用映射表动态更新机制使服务器对相应的被控对象进行数据运算,从而实现服务器去中心化;利用工具箱Truetime2.0及MATLAB/Simulink搭建去中心化分布式电机控制系统仿真平台,以电机为被控对象,研究冗余备份机制对去中心化分布式控制系统的性能影响以及去中心化分布式控制系统的网状网架构能否支持大规模电机正常运行。仿真结果表明,冗余备份机制有效地提高了系统运行的平稳性,系统的网状网架构足以支持上万个电机运行。

机理约束下钻井机械钻速智能预测泛化方法

钻井机械钻速的准确预测可辅助油气井钻井前科学配置资源,对制订更加合理的钻井作业方案以及钻井提效、降本增效具有重要现实意义。智能化预测钻井机械钻速已成为行业研究热点,为解决常规智能模型在不同井间迁移能力较差的问题,在对综合录井数据进行降噪、补全等预处理的基础上,利用钻井专业知识构造约束条件,引入了域对抗神经网络(DANN),建立了机械钻速模型在不同井间的迁移机制,结合滑动窗口、增量更新与实时录井数据,形成了机械钻速模型随井下工况的实时更新方法。研究结果表明:(1)数据层约束和网络层约束均可提高智能模型的精度与稳定性,且双机理约束下的BP模型相比于普通BP模型预测精度明显提高;(2)基于域对抗神经网络的机械钻速预测模型可有效地将邻井(源域)数据知识迁移到测试井(目标域);(3)基于增量学习算法建立的双滑动窗口数据更新机制,使模型实时适应地下钻进环境变化,预测精度和泛化能力进一步提升;(4)机理约束、迁移训练与实时更新对模型泛化性能的强化作用具有叠加效应,新井机械钻速预测平均相对误差降低至20.2%。结论认为,建立的机械钻速预测模型及迁移方法相较于传统钻速预测模型,具有更好的迁移性和更高的准确度,减少了迁移过程中重复训练时间,为机械钻速智能预测提供了新的思路和方向。

一种属性变化局部变精度邻域粗糙集动态算法

传统的邻域粗糙集模型对混合型数据的抗噪能力和计算效率低下,基于矩阵理论建立了一种属性动态变化的局部变精度邻域粗糙集模型。在局部对角矩阵和中间矩阵的更新规律的基础上,构建了混合信息系统局部变精度邻域粗糙集下近似的动态更新机制,提出了一种新的属性变化的局部变精度邻域粗糙集动态算法。通过实验分析可知:所提出的动态算法具有较高的计算效率和良好的稳健性。

结合空间注意力机制的实时鲁棒视觉跟踪

为提高全卷积孪生网络(SiamFC)跟踪器在复杂场景下的跟踪能力,缓解跟踪器在跟踪过程中出现的目标漂移问题,提出一种结合空间注意力机制的实时目标跟踪算法。在SiamFC框架基础上,将改进的视觉几何组(VGG)网络作为主干网络,增强跟踪器对于目标深度特征的建模能力。对自注意力机制进行优化,提出一种即插即用的轻量级单卷积注意力模块(SCAM),将空间注意力分解为2个并行的一维特征编码过程,减少空间注意力的计算复杂度。保留跟踪过程中的初始目标模板作为第1模板,通过分析连通域在跟踪结果响应图的变化动态选择第2模板,融合2个模板后对目标进行定位。实验结果表明:在OTB100、LaSOT和UAV123数据集上,所提算法相比于SiamFC跟踪成功率分别提高了0.082、0.045和0.045,跟踪精度分别提高了0.118、0.051和0.062;在VOT2018数据集上,所提算法相比于SiamFC在跟踪准确率、鲁棒性和期望平均重叠率上分别提高了0.029、0.276和0.134;跟踪速度达到了70帧/s,能够满足实时跟踪的需求。

考虑重力的液压重载机械臂模型修正应用研究

液压重载机械臂工作时由重力引起的预应力刚化对于整体结构的仿真分析具有显著的影响,针对此问题,提出了一种考虑预应力刚化的计算模态分析方法和基于径向基函数代理模型的有限元模型修正方法。以某型液压重载机械臂为研究对象,建立整体复杂结构的有限元模型及其预应力刚化模态频率的代理模型,以多个工况试验模态分析结果为目标,基于全局优化算法实现了整体结构的模型修正。对试验修正后的模型开展了应变响应预测,验证了模型的预测能力。研究结果表明,所提方法不仅提高了模型复现修正响应的能力,而且能够准确预测未修正的响应,从而验证了方法的可行性,为重载机械臂的自动控制和优化设计提供了精确动力学模型。

基于带权单链表多元哈希树的云数据审计方案

针对传统Merkle哈希树节点利用率低以及动态更新效率低的问题,提出一种支持批量更新的基于带权单链表的多元哈希树(WSLL-MHT)数据结构,在该结构中,将多元哈希树的叶子节点替换成单链表结构以存储更多数据块,增加其节点利用率。在动态更新过程中,引入树的平衡机制确保链表长度的平衡,提高动态更新的效率。采用BLS-HVA签名技术实现批量审计和隐私保护,结合随机掩蔽技术确保第三方审计员不能从返回的证据中获取用户隐私信息。实验结果表明,所提方案能安全高效实现云端数据的批量审计和全动态更新。

面向动态交通流多步预测的时空图模型

为更好表征交通路网中节点之间的动态隐式关系,提出一种基于时空数据嵌入的动态图卷积交通流预测模型。基于路网中节点之间的共现关系,利用深度游走算法将时空数据映射到嵌入空间中学习节点的向量表示;引入时隙嵌入特征与二维空间嵌入特征共同构建三维嵌入邻接张量,用于捕获时空依赖关系;在图卷积网络中添加自适应更新机制,利用循环组件演化图卷积网络的参数,以捕获图序列的动态性。将所提模型应用于基于真实交通数据集的交通流预测,结果验证了其有效性和提取路网隐式关系的准确性。