Collapse-free thermal bonding technique for large area microchambers in plastic lab-on-a-chip applications

Bonding is an essential step to form microchannels or microchambers in lab-on-a-chip applications. In this paper, we present a novel plastic thermal bonding technique to seal and form large area microchambers (planar characteristic width and length on the order of 1 mm and characteristic thickness on the order of 10–100 μm) without collapse by introducing a holed pressure equalizing plate (HPEP) that includes holes of the same size and shape as the microchambers. To demonstrate the proposed technique, two types of large area microchambers [(1) 20 × 10 mm and 40 μm thick and (2) 12 × 2.5 mm and 120 μm thick] with microchannels were designed and replicated on plastic substrates by means of hot embossing and injection molding processes with prepared two nickel mold inserts. The replicated large area microchambers as well as the microchannels in the plastic lab-on-a-chip were successfully sealed (i.e., no leakage) and formed without any collapse by the proposed thermal bonding technique with the help of the HPEP.     

Sliding Mode Control with Adaptive Fuzzy Dead-Zone Compensation of an Electro-hydraulic Servo-System

Electro-hydraulic servo-systems are widely employed in industrial applications such as robotic manipulators, active suspensions, precision machine tools and aerospace systems. They provide many advantages over electric motors, including high force to weight ratio, fast response time and compact size. However, precise control of electro-hydraulic systems, due to their inherent nonlinear characteristics, cannot be easily obtained with conventional linear controllers. Most flow control valves can also exhibit some hard nonlinearities such as dead-zone due to valve spool overlap. This work describes the development of an adaptive fuzzy sliding mode controller for an electro-hydraulic system with unknown dead-zone. The boundedness and convergence properties of the closed-loop signals are proven using Lyapunov stability theory and Barbalat’s lemma. Numerical results are presented in order to demonstrate the control system performance.     

蛇形益智魔方的三维路径求解算法

蛇形益智魔方是智力魔方的一种,由27个两两相连的小正方体组成。文章通过计算机图形学的概念建立空间三维坐标模型,对模型中关键点进行分析归类,对空间中每个方块体可能的坐标点进行了递归公式推导,最后利用三维空间坐标的遍历算法来寻找蛇形魔方所有可能的解,指出了模型的使用前景。     

Stress wave propagation in supporting bolts: A test for bolt support quality

A test method for the non-destructive determination of bolt length, anchoring length, and bolt body force is described. This addresses the problems of low accuracy, limited number of data, and untimely warning signs encountered with existing test methods. Numerical simulations of the bolt, resin, and rock system show that the length accuracy when using the velocity wave is lower than when using the acceleration wave. It is accepted practice to use the acceleration wave for length tests because of improved signal to noise ratios of the waveforms. Laboratory and in situ underground tests showed that the precision of the measurements meets field requirements. Using this method the anchor properties of each single bolt and, thus, the safety of the entire roadway support may be evaluated.     

Node trust evaluation in mobile ad hoc networks based on multi-dimensional fuzzy and Markov SCGM(1, 1) model

Due to the nature of distribution and self-organization, mobile ad hoc networks rely on cooperation between nodes to transfer information. One of the key factors to ensure high communication quality is an efficient assessment scheme for risks and trust of choosing next potential cooperative nodes. Trust model, an abstract psychological cognitive process, is one of the most complex concepts in social relationships, involving factors such as assumptions, expectations and behaviors. All of the above make it difficult to quantify and forecast trust accurately. In this paper, based on the theories of fuzzy recognition with feedback, SCGM(1, 1) model and Markov chain, we present a pattern of prediction making. The analysis and experimental computation show that this scheme is efficient in trust prediction for ad hoc networks.     

Parallel machine scheduling to minimize the sum of quadratic completion times

We consider the parallel machine scheduling problem of minimizing the sum of quadratic job completion times. We first prove that the problem is strongly NP-hard. We then demonstrate by probabilistic analysis that the shortest processing time rule solves the problem asymptotically. The relative error of the rule converges in probability to zero under the assumption that the job processing times are independent random variables uniformly distributed in (0, 1). We finally provide some computational results, which show that the rule is effective in solving the problem in practice.     

纳滤回收染料废水中染料的实验研究

以含盐染料废水为研究对象,应用商业化的卷式膜组件,研究了纳滤膜对染料和盐的截留特性．实验结果表明,纳滤膜对染料的截留率高达99％以上．当染料分子量高于膜截留分子量时,染料初始浓度和染料品种对染料截留率的影响甚小,盐浓度对染料截留也无明显影响,但对NaCl截留率影响显著．随料液中NaCl浓度的增加,盐截留率快速下降,当盐浓度达到3．5％时,NaCl的截留率低于25％．纳滤膜对染料的高截留率和对NaCl的低截留率,使得应用纳滤技术从含盐染料废水中回收染料具有较好的经济性和可行性．     

CSatDTA: Prediction of Drug–Target Binding Affinity Using Convolution Model with Self-Attention

Drug discovery, which aids to identify potential novel treatments, entails a broad range of fields of science, including chemistry, pharmacology, and biology. In the early stages of drug development, predicting drug–target affinity is crucial. The proposed model, the prediction of drug–target affinity using a convolution model with self-attention (CSatDTA), applies convolution-based self-attention mechanisms to the molecular drug and target sequences to predict drug–target affinity (DTA) effectively, unlike previous convolution methods, which exhibit significant limitations related to this aspect. The convolutional neural network (CNN) only works on a particular region of information, excluding comprehensive details. Self-attention, on the other hand, is a relatively recent technique for capturing long-range interactions that has been used primarily in sequence modeling tasks. The results of comparative experiments show that CSatDTA surpasses previous sequence-based or other approaches and has outstanding retention abilities.