Interleukin-1β Modulation of the Mechanobiology of Primary Human Pulmonary Fibroblasts: Potential Implications in Lung Repair

Pro-inflammatory cytokines like interleukin-1β (IL-1β) are upregulated during early responses to tissue damage and are expected to transiently compromise the mechanical microenvironment. Fibroblasts are key regulators of tissue mechanics in the lungs and other organs. However, the effects of IL-1β on fibroblast mechanics and functions remain unclear. Here we treated human pulmonary fibroblasts from control donors with IL-1β and used Atomic Force Microscopy to unveil that IL-1β significantly reduces the stiffness of fibroblasts concomitantly with a downregulation of filamentous actin (F-actin) and alpha-smooth muscle (α-SMA). Likewise, COL1A1 mRNA was reduced, whereas that of collagenases MMP1 and MMP2 were upregulated, favoring a reduction of type-I collagen. These mechanobiology changes were functionally associated with reduced proliferation and enhanced migration upon IL-1β stimulation, which could facilitate lung repair by drawing fibroblasts to sites of tissue damage. Our observations reveal that IL-1β may reduce local tissue rigidity by acting both intracellularly and extracellularly through the downregulation of fibroblast contractility and type I collagen deposition, respectively. These IL-1β-dependent mechanical effects may enhance lung repair further by locally increasing pulmonary tissue compliance to preserve normal lung distension and function. Moreover, our results support that IL-1β provides innate anti-fibrotic protection that may be relevant during the early stages of lung repair.     

大数据环境下基于K中心点优化算法的Web服务组合

在当前Web服务海量增加、现有Web服务选择算法低效、用户匹配度差的基础上，针对K中心点算法存在的质点偏移、准确率低和容易发生畸变等问题，提出一种大数据环境下基于K中心点优化算法的Web服务组合方法。该方法是在大数据环境下，根据不同用户需求满意度及Web服务QoS参数，对基于优化初始聚类中心的K中心点算法的Web服务选择及最优Web服务组合进行研究。同时针对不同的选择方法对服务动态选择及组合的准确度、迭代更新次数、候选集选择时间及选择总时间进行实验分析，验证了本文研究方法的有效性和可靠性。     

粮仓环境监测系统设计

随着科学技术的发展,粮食行业信息化发展得到了强有力的科技支撑。为满足粮库整体信息化建设的要求,打破"信息孤岛"现状,实现资源整合、数据共享,为大数据分析和数据应用提供数据基础,设计一款能够实时采集粮仓内温湿度、氧气、二氧化碳气体浓度、粮堆高度的数据集成系统。系统采用分层分布式结构,由数据集中器和多种传感器模块组成,数据集中器与各传感器模块间通过RS485总线进行数据通讯,并由数据集中器通过网络专线传输汇总的环境监测数据,通过专用软件进行数据处理和挖掘,从而实现粮仓环境监测和预警等功能。     

适用于无线体域网的动态口令认证协议

无线体域网中传输的是与生命高度相关的敏感数据，身份认证是信息安全保护的第一道防线。现有的基于人体生物信息的身份认证方案存在信息难提取、偶然性大和误差性大的问题，基于传统密码学的认证方案需较大计算资源和能量消耗，并不适用于无线体域网环境。为此，在动态口令和非对称加密机制基础上，提出一种适用于无线体域网的动态口令双向认证轻量协议，并对其进行形式化分析。通过理论证明、SVO逻辑推理及SPIN模型检测得出：该协议满足双向认证，且能够抵御重放攻击、伪装攻击、拒绝服务器攻击和口令离线攻击，具有较高安全性。     

面向连续查询的敏感语义位置隐私保护方案

针对连续查询位置服务中构造匿名区域未考虑语义位置信息导致敏感隐私泄露问题，通过设计[(K,θ)]-隐私模型，提出一种路网环境下面向连续查询的敏感语义位置隐私保护方案。该方案利用Voronoi图将城市路网预先划分为独立的Voronoi单元，依据用户的移动路径和移动速度，选择具有相似特性的其他[K-1]个用户，构建匿名用户集；利用匿名用户集用户设定的敏感语义位置类型和语义安全阈值，以及用户所处语义位置的Voronoi单元，构建满足[(K,θ)]-隐私模型的语义安全匿名区域，可以同时防止连续查询追踪攻击和语义推断攻击。实验结果表明，与SCPA算法相比，该方案在隐私保护程度上提升约15%，系统开销上降低约20%。     

面向噪声丢包感知的无线网络拥塞算法

针对无线网络链路干扰大、误码率高等特点，以及TCP Westwood算法（TCPW）存在估算带宽时过度依赖包的反馈，缺乏区分传输过程中丢包类型的缺点等问题，提出一种TCPW拥塞控制优化算法--TCPW-F。该算法利用发送速率等构建拥塞因子[F]作为判断丢包类型的依据，同时对判定发生噪声丢包时的拥塞窗口进一步调整，避免噪声丢包引起的窗口下降，提高该情况下窗口的发送效率。仿真结果表明，TCPW-F算法在时延性能方面表现更优，单位时间抖动趋于稳定的速度更快。在同一信道带宽下增大包生成速率，改进算法的实时吞吐量明显高于原算法，具备一定的噪声丢包感知能力，无线网络的TCP传输质量获得较大改善。     

基于双声表面波器件的引信加速度传感器

In view of the shortcomings of silicon micro acceleration sensor based on piezoresistive effect and capacitance principle, such as temperature drift, low resolution and poor anti-interference ability, a fuze acceleration sensor based on dual SAW devices is proposed. The sensor adopts a dual saw device structure, one is coated with a sensitive film for measurement, the other is an uncoat- ed reference channel for compensation of environmental temperature, pressure, humidity and other factors. The experimental results show that the maximum linear error is only 1.6%, the sensitivity is 54.3Hz/g, and the maximum hysteresis error is less than 1%. Compared with piezoresistive accelerometer and capacitive accelerometer, the linear error of the accelerometer is small, the sensitivi- ty is high, and it has strong anti-interference ability.     

Passive target detection and tracking from electromagnetic field measurements

This paper presents a novel approach to the localization of moving targets in a complex environment based on the measurement of the perturbations induced by the target presence on an independently‐generated time‐varying electromagnetic field. Field perturbations are measured via a set of sensors deployed over the domain of interest and used to detect and track a possible target by resorting to a particle Bernoulli filter (PBF). To comply with real‐time operation, the PBF works along with an artificial neural network (ANN) model of the environment trained offline via finite elements (FEs). The performance of the proposed algorithm is assessed via simulation experiments.     

Smart work packaging-enabled constraint-free path re-planning for tower crane in prefabricated products assembly process

Lack of constraint-free crane path planning is one of the critical concerns in the dynamic on-site assembly process of prefabrication housing production (PHP). For decades, researchers and practitioners have endeavored to improve both the efficiency and safety of crane path planning from either static environment or re-planning the path when colliding with constraints or periodically updating the path in the dynamic environment. However, there is a lack of approach related to the in-depth exploration of the nature of dynamic constraints so as to assist the crane operators in making adaptive path re-planning decisions by categorizing and prioritizing constraints. To address this issue, this study develops the smart work packaging (SWP)-enabled constraints optimization service. This service embraces the core characteristics of SWP, including adaptivity, sociability, and autonomy to achieve autonomous initial path planning, networked constraints classification, and adaptive decisions on path re-planning. This service is simulated and verified in the BIM environment, and it is found that SWP-enabled constraints optimization service can generate the constraint-free path when it is necessary.     

Zone model predictive control for pressure management of water distribution network

In the water distribution network (WDN), although the water demand of the node is changing constantly, the water quantity and water pressure of the node need to be met at each moment. To realize energy saving and consumption reduction, it is proposed to control the nodal water head of WDN in an appropriate narrow range. The frequent large fluctuation of the water demand, which may lead the water pressure exceed the expected range, increases the difficulty of the zone control. To realize optimized WND control, a novel zone predictive control is proposed, where two switching cases are considered. The switching condition is whether there are feasible solutions to keep the pressure within the expected region over the prediction horizon. When the condition is satisfied, the controller minimizes the variation of inputs with constraints of pressure range for ensuring the tank level staying within the expected zone and obtaining optimal economic cost. When the current pressure is out of the expected region or the condition is not satisfied due to the large variation of water demand, a reference trajectory of outputs is introduced, which is combined with the inputs as an optimization variable, and the constraints of expected zone are moved from the output to the introduced reference trajectory. Through minimizing the distance between reference trajectory and output, the controller will keep the tank level from deviating too far from the expected zone and will drive the tank level rapidly into the expected zone once the tank level exceeds the expected range. An application of the proposed zone MPC to WDN in Shinan District of Shanghai is given to illustrate its effectiveness.