Gene expression is a complex biochemical process, involving many specific processes such as transcription, translation, switching between promoter states, and regulation. All these biochemical processes inevitably lea...Gene expression is a complex biochemical process, involving many specific processes such as transcription, translation, switching between promoter states, and regulation. All these biochemical processes inevitably lead to fluctuations in mRNA and protein abundances. This noise has been identified as an important factor underlying the observed phenotypic variability of genetically identical cells in homogeneous environments. Quantifying the contributions of different sources of noise using stochastic models of gene expression is an important step towards understanding fundamental cellular processes and cell-to-cell variability in expression levels. In this paper, we review progresses in quantitative study of simple gene expression systems, including some results that we have not published. We analytically show how specific processes associated with gene expression affect expression levels. In particular, we derive the analytical decomposition of expression noise, which is important for understanding the roles of the factorial noise in controlling phenotypic variability. We also introduce a new index （called attribute factor） to quantify expression noise, which has more advantages than the commonly-used noise indices such as noise intensity and Fano factor.展开更多
Scattering of the electromagnetic waves by a randomly inhomogeneous electrically gyrotropic slab are studied using the perturbation method. Second order statistical moments of the ordinary and extraordinary waves scat...Scattering of the electromagnetic waves by a randomly inhomogeneous electrically gyrotropic slab are studied using the perturbation method. Second order statistical moments of the ordinary and extraordinary waves scattered by the magnetized plasma slab are obtained using the boundary conditions for an arbitrary correlation function of electron density fluctuations. Normalized correlation functions at quasi-longitudinal propagation along the external magnetic field are calculated for the carrier frequency 0.1 MHz and 40 MHz. Isolines of the normalized variance of Faraday angle are constructed for the anisotropic Gaussian correlation function at various anisotropy factors of irregularities. Obtained results are in a good agreement with the experimental data.展开更多
An essential part of any activity recognition system claiming be truly real-time is the ability to perform feature extraction in real-time. We present, in this paper, a quite simple and computationally tractable appro...An essential part of any activity recognition system claiming be truly real-time is the ability to perform feature extraction in real-time. We present, in this paper, a quite simple and computationally tractable approach for real-time human activity recognition that is based on simple statistical features. These features are simple and relatively small, accordingly they are easy and fast to be calculated, and further form a relatively low-dimensional feature space in which classification can be carried out robustly. On the Weizmann publicly benchmark dataset, promising results (i.e. 97.8%) have been achieved, showing the effectiveness of the proposed approach compared to the-state-of-the-art. Furthermore, the approach is quite fast and thus can provide timing guarantees to real-time applications.展开更多
Phosphoaspartate is one of the major components of eukaryotes and prokaryotic two-component signaling pathways,and it communicates the signal from the sensor of histidine kinase,through the response regulator,to the D...Phosphoaspartate is one of the major components of eukaryotes and prokaryotic two-component signaling pathways,and it communicates the signal from the sensor of histidine kinase,through the response regulator,to the DNA alongside transcription features and initiates the transcription of correct response genes.Thus,the prediction of phosphoaspartate sites is critical,and its experimental identification can be expensive,time-consuming,and tedious.For this purpose,we propose iPhosD-PseAAC,a new computational model for predicting phosphoaspartate sites in a particular protein sequence using Chou’s 5-steps rues:(1)Benchmark dataset.(2)The feature extraction techniques such as pseudo amino acid composition(PseAAC),statistical moments,and position relative features.(3)For the classification,artificial neural network AAN will be used.(4)In this step,10-fold cross-validation and self-consistency testing will be used for validation.For self-consistency testing,100%Acc is achieved,whereas,for 10-fold crossvalidation 95.14%Acc,95.58%Sn,94.70%Sp and 0.95 MCC are observed.(5).The final step is the development of a user-friendly web server for the ease of users.Thus,the iPhosD-PseAAC is the first and novel predictor for accurate and efficient identification of phosphoaspartate sites.展开更多
提出了一种针对JPEG图像隐写术的检测方案。针对现今比较流行的F5、model based steganography(MB1)、MB2、OutGuess等隐写算法进行了检测。利用基于图像像素间相关性的空域预测算法、剪裁算法、二维统计直方图等方法,结合马尔可夫转移...提出了一种针对JPEG图像隐写术的检测方案。针对现今比较流行的F5、model based steganography(MB1)、MB2、OutGuess等隐写算法进行了检测。利用基于图像像素间相关性的空域预测算法、剪裁算法、二维统计直方图等方法,结合马尔可夫转移概率矩阵,对JPEG图像进行特征提取,进而利用Liblinear分类器作线性分类。实验结果表明:新方法对上述4种隐写术具有较强的分辨能力,并且比其他算法快速、简便。展开更多
文摘Gene expression is a complex biochemical process, involving many specific processes such as transcription, translation, switching between promoter states, and regulation. All these biochemical processes inevitably lead to fluctuations in mRNA and protein abundances. This noise has been identified as an important factor underlying the observed phenotypic variability of genetically identical cells in homogeneous environments. Quantifying the contributions of different sources of noise using stochastic models of gene expression is an important step towards understanding fundamental cellular processes and cell-to-cell variability in expression levels. In this paper, we review progresses in quantitative study of simple gene expression systems, including some results that we have not published. We analytically show how specific processes associated with gene expression affect expression levels. In particular, we derive the analytical decomposition of expression noise, which is important for understanding the roles of the factorial noise in controlling phenotypic variability. We also introduce a new index （called attribute factor） to quantify expression noise, which has more advantages than the commonly-used noise indices such as noise intensity and Fano factor.
文摘Scattering of the electromagnetic waves by a randomly inhomogeneous electrically gyrotropic slab are studied using the perturbation method. Second order statistical moments of the ordinary and extraordinary waves scattered by the magnetized plasma slab are obtained using the boundary conditions for an arbitrary correlation function of electron density fluctuations. Normalized correlation functions at quasi-longitudinal propagation along the external magnetic field are calculated for the carrier frequency 0.1 MHz and 40 MHz. Isolines of the normalized variance of Faraday angle are constructed for the anisotropic Gaussian correlation function at various anisotropy factors of irregularities. Obtained results are in a good agreement with the experimental data.
文摘An essential part of any activity recognition system claiming be truly real-time is the ability to perform feature extraction in real-time. We present, in this paper, a quite simple and computationally tractable approach for real-time human activity recognition that is based on simple statistical features. These features are simple and relatively small, accordingly they are easy and fast to be calculated, and further form a relatively low-dimensional feature space in which classification can be carried out robustly. On the Weizmann publicly benchmark dataset, promising results (i.e. 97.8%) have been achieved, showing the effectiveness of the proposed approach compared to the-state-of-the-art. Furthermore, the approach is quite fast and thus can provide timing guarantees to real-time applications.
基金the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,https://dsr.kau.edu.sa/Default-305-EN under Grant No.G:136-611-1441.
文摘Phosphoaspartate is one of the major components of eukaryotes and prokaryotic two-component signaling pathways,and it communicates the signal from the sensor of histidine kinase,through the response regulator,to the DNA alongside transcription features and initiates the transcription of correct response genes.Thus,the prediction of phosphoaspartate sites is critical,and its experimental identification can be expensive,time-consuming,and tedious.For this purpose,we propose iPhosD-PseAAC,a new computational model for predicting phosphoaspartate sites in a particular protein sequence using Chou’s 5-steps rues:(1)Benchmark dataset.(2)The feature extraction techniques such as pseudo amino acid composition(PseAAC),statistical moments,and position relative features.(3)For the classification,artificial neural network AAN will be used.(4)In this step,10-fold cross-validation and self-consistency testing will be used for validation.For self-consistency testing,100%Acc is achieved,whereas,for 10-fold crossvalidation 95.14%Acc,95.58%Sn,94.70%Sp and 0.95 MCC are observed.(5).The final step is the development of a user-friendly web server for the ease of users.Thus,the iPhosD-PseAAC is the first and novel predictor for accurate and efficient identification of phosphoaspartate sites.
文摘提出了一种针对JPEG图像隐写术的检测方案。针对现今比较流行的F5、model based steganography(MB1)、MB2、OutGuess等隐写算法进行了检测。利用基于图像像素间相关性的空域预测算法、剪裁算法、二维统计直方图等方法,结合马尔可夫转移概率矩阵,对JPEG图像进行特征提取,进而利用Liblinear分类器作线性分类。实验结果表明:新方法对上述4种隐写术具有较强的分辨能力,并且比其他算法快速、简便。
