Exploring Molecular Contacts of MUC1 at CIN85 Binding Interface to Address Future Drug Design Efforts

The modulation of protein-protein interactions (PPIs) by small molecules represents a valuable strategy for pharmacological intervention in several human diseases. In this context, computer-aided drug discovery techniques offer useful resources to predict the network of interactions governing the recognition process between protein partners, thus furnishing relevant information for the design of novel PPI modulators. In this work, we focused our attention on the MUC1-CIN85 complex as a crucial PPI controlling cancer progression and metastasis. MUC1 is a transmembrane glycoprotein whose extracellular domain contains a variable number of tandem repeats (VNTRs) regions that are highly glycosylated in normal cells and under-glycosylated in cancer. The hypo-glycosylation fosters the exposure of the backbone to new interactions with other proteins, such as CIN85, that alter the intracellular signalling in tumour cells. Herein, different computational approaches were combined to investigate the molecular recognition pattern of MUC1-CIN85 PPI thus unveiling new structural information useful for the design of MUC1-CIN85 PPI inhibitors as potential anti-metastatic agents.     

激光在线测厚振动分析与精度优化

激光测厚具有安全可靠、测量精度高、测量范围大等优点,广泛应用于纸张、电池极片等薄膜类材料厚度的在线测量。带材宽幅方向扫描测厚时由于扫描架往复运动会产生机械振动,影响在线测厚精度。针对该问题,以锂离子电池极片厚度测量为例,使用双激光差动式测厚平台对电池极片和铜箔分别进行厚度测量,然后对测厚数据进行频谱分析,探究其振动规律的相似性,并基于频谱分析结果采用滑动带阻滤波方式对测厚数据进行处理,滤波后极片和铜箔的厚度极差分别降低了33.4%和73.8%,有效过滤了机械振动导致的测量误差,可满足极片和铜箔厚度测量的精度要求。     

Domain reversal and current transport property in BiFeO3 films

The electrical properties and domain reversal in BiFeO₃ ferroelectric films were studied using sandwiched heterostructures and piezoresponse force microscopy. A robust polarization state was observed, combined with a switchable domain pattern and a remanent polarization of approximately 100 μC cm^?2. In addition, domain reversal was explored using scanning probe microscopy. The results show that dipoles could be reversed along the direction of the electric field under a negative tip bias, leading to carrier gathering near the domain walls. The enhanced conductivity near the domain walls was owing to the discontinuous polarization boundary conditions. In addition, typical diode-like current transport properties are sensitive to various temperature conditions, which is attributed to the Schottky barriers at the contact interface. These findings extend the current understanding of domain texture reversal in ferroelectric films and shed light on their potential applications for future ferroelectric random-access memory operations over a wide temperature range.     

基于LP与小波包的复杂机电系统监测序列混沌降噪方法

针对流程工业生产系统监测数据存在强噪声和混沌性的特点,提出了一种局部投影方法(Local Projection Method)与小波包方法相结合的信号降噪方法。该方法先利用局部投影方法从动力学系统嵌入流形的角度进行多次迭代降噪,并根据关联维数来判定迭代终止;再利用小波包方法从频率的角度进行降噪,抑制高频噪声的干扰,取得了较好的降噪效果。用Lorenz时间序列进行仿真验证,对仿真时间序列加入不同程度的噪声,对比分析小波包、局部投影与该方法降噪后的相空间、SNR值和最大Lyapunov指数,证明了该方法对于中高强度噪声具有更好的降噪效果。并将该方法用于某压缩机组的实际监测数据降噪,评估三种方法的降噪效果,进一步验证了该方法的优越性。     

Polynomial filtering for nonlinear stochastic systems with state‐ and disturbance‐dependent noises

This article is concerned with the polynomial filtering problem for a class of nonlinear stochastic systems governed by the Itô differential equation. The system under investigation involves polynomial nonlinearities, unknown‐but‐bounded disturbances, and state‐ and disturbance‐dependent noises ((x,d)‐dependent noises for short). By expanding the polynomial nonlinear functions in Taylor series around the state estimate, a new polynomial filter design method is developed with hope to reduce the conservatism of the existing results. In virtue of stochastic analysis and inequality technique, sufficient conditions in terms of parameter‐dependent linear matrix inequalities (PDLMIs) are derived to guarantee that the estimation error system is input‐to‐state stable in probability. Moreover, the desired polynomial matrix can be obtained by solving the PDLMIs via the sum‐of‐squares approach. The effectiveness and applicability of the proposed method are illustrated by two numerical examples with one concerning the permanent magnet synchronous motor.     

Learning Association Rules and Tracking the Changing Concepts on Webpages: An Effective Pornographic Websites Filtering Approach

We applied the decision tree algorithm to learn association rules between webpage’s category (pornographic or normal) and the critical features. Based on these rules, we proposed an efficient method of filtering pornographic webpages with the following major advantages: 1) a weighted window-based technique was proposed to estimate for the condition of concept drift for the keywords found recently in pornographic webpages; 2) checking only contexts of webpages without scanning pictures; 3) an incremental learning mechanism was designed to incrementally update the pornographic keyword database.     

Location Related Signals with Satellite Image Fusion Method Using Visual Image Integration Method

Investigations were performed on a group utilizing (General Purpose Unit) GPU and executions were evaluated for the utilization of the created parallel usages to process satellite pictures from satellite Landsat7.The usage on a realistic group gives execution change from 2 to 18 times. The nature of the considered techniques was assessed by relative dimensionless global error in synthesis (ERGAS) and Quality Without Reference (QNR) measurements. The outcomes demonstrate execution picks ups and holding of value with the bunch of GPU contrasted with the outcomes and different analysts for a CPU and single GPU. The errand of upgrading the view of a scene by combining data caught from various picture sensors is usually known as multisensor picture combination. This paper displays a territory based picture combination calculation to consolidate SAR (Synthetic Aperture Radar) and optical pictures. The co-enlistment of the two images is first led utilizing the proposed enrollment method prior to picture combination. The paper displays a parallel execution of existing picture combination techniques on a graphical group. Parallel executions of techniques in view of discrete wavelet changes are created. Division into dynamic and motionless regions is then executed on the SAR surface picture for particular injection of the SAR picture into panchromatic (PAN) picture. An integrated image in view of these two pictures is produced by the novel region based combination plot, which forces diverse combination rules for each fragmented region. At long last, this picture is melded into a multispectral(MS) picture through the half breed skillet honing technique proposed in past research. Exploratory outcomes exhibit that the proposed strategy demonstrates preferred execution over different fusion algorithms and can possibly be connected to the multisensory combination of SAR and optical pictures.     

New version of continuous–discrete cubature Kalman filtering for nonlinear continuous–discrete systems

For nonlinear continuous–discrete systems, this paper elaborates a new accurate implementation of continuous–discrete cubature Kalman filter (CD-CKF). As the main contribution of this work, the new Kalman prediction stage begins by integrating the nonlinear continuous model for all the cubature sample vectors; the prior estimate state and covariance prediction are based on the weighted statistics of these integrated cubature sample vectors and the Gauss–Legendre approximation scheme. The new square root form CD-CKF is also derived and accurately implemented by combining with the modified variable stepsize NIRK. As the advantages of proposed approach, the complicated and error-prone processes of solving covariance differential equation or calculating derivatives are avoided, while the positive semi-definiteness of prior error covariance are numerically guaranteed. Simulations of traffic control scenarios further confirm the new approach’s superior filtering performance in both reliability and accuracy.     

Comparison of joint angle,velocity and acceleration estimators for hydraulically actuated manipulators to a novel dynamical approach

Excavators are used for a wide range of applications like earthworks and material handling. Assistance systems are becoming more common to support the operator. For monitoring and control based assistance functions the angular position, velocity and acceleration of the joints from the working implement are required. Commercial systems often use inertial measurement units, consisting of triaxial accelerometers and gyroscopes, to accomplish an estimation of those states. A novel joint angle, velocity and acceleration estimation for hydraulic manipulators is proposed and compared to state of the art methods. A decentralized kinematic filter using no information about the underlying system and a centralized kinematic filter taking the system kinematics into account are implemented as state of the art approaches. Both filters only use inertial measurement units to obtain information about the current state of the system. The novel centralized dynamic filter uses the same information as the centralized kinematic filter and extends it by a dynamic model containing additional information about the angular acceleration due to pressure readings of the hydraulic cylinders. Kalman filtering is used to combine the derived system and measurement models with the sensor information. The methods are evaluated on a material handling excavator for single and coupled movements of the working implement. The novel centralized dynamic filter enables improvements for the angular acceleration estimation compared to the decentralized and centralized kinematic filter. Less noise of the acceleration estimation and a better tracking of the actual acceleration are shown.     

Multi-objective iterative optimization algorithm based optimal wavelet filter selection for multi-fault diagnosis of rolling element bearings

Rolling element bearings (REBs) play an essential role in modern machinery and their condition monitoring is significant in predictive maintenance. Due to the harsh operating conditions, multi-fault may co-exist in one bearing and vibration signal always exhibits low signal-to-noise ratio (SNR), which causes difficulties in detecting fault. In the previous studies, maximum correlated kurtosis deconvolution (MCKD) has been validated as an efficient method to extract fault feature in the fault signals. Nonetheless, there are still some challenges when MCKD is applied to fault detection owing to the rigorous requirements of multiple input parameters. To overcome limitation, a multi-objective iterative optimization algorithm (MOIOA) for multi-fault diagnosis is proposed. In this method, correlated kurtosis (CK) is taken as a criterion to select optimal Morlet wavelet filter using the whale optimization algorithm (WOA). Meanwhile, to further eliminate the effect of the inaccurate period on CK, the update process of period is incorporated. After that, the simulated and experimental signals are utilized to testify the validity and superiority of the MOIOA for multiple faults detection by the comparison with MCKD. The results indicate that MOIOA is efficient to extract weak fault features even with heavy noise and harmonic interferences.