The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
As a passive blood drop impacts a hard surface, it is observed to collapse and spread laterally, then retract and settle. During the spreading phase, the edge of the drop may rise forming a crown extending into spines and breaking up into secondary drops. When a similar drop falls onto a textile surface these same processes may occur, but the process of blood wicking into the fabric complicates stain...
Background Integrative analysis of multi-omics data is becoming increasingly important to unravel functional mechanisms of complex diseases. However, the currently available multi-omics datasets inevitably suffer from missing values due to technical limitations and various constrains in experiments. These missing values severely hinder integrative analysis of multi-omics data. Current imputation methods...
Multicolor Fluorescence In-Situ Hybridization (M-FISH) is an imaging technique for rapid detection of chromosomal abnormalities, where the segmentation of chromosomes has been a challenge. Multi-channel information of M-FISH images can be used in a segmentation algorithm to exploit the correlated information across channels for better image segmentation. In addition, the neighboring pixels share similar...
Recently, more evidence of polygenicity and pleiotropy has been found in genome-wide association (GWA) studies of complex psychiatric diseases (e.g., schizophrenia), where multiple interacting genetic variants may affect multiple phenotypic traits simultaneously. In this work, we propose a new sparse collaborative group-ridge low-rank regression model (sCGRLR) to study the pleiotropic effects of a...
We developed a new sparse multivariate regression method, collaborative sparse reduced rank regression(C-sRRR) for detecting genetic networks associated with brain functional networks in schizophrenia (SZ). Our study: 1) introduced both genetic and brain network structure to group single nucleotide polymorphism (SNP) and voxels simultaneously for utilizing the interacting effects implied in both features;...
In this paper we propose a structure based sparse model with different constrains by extending the general sparse model to the multiple pixels case, where each pixel together with its neighboring pixels are used simultaneously in the sparse representation of chromosome classes. We use the model to classify multicolor fluorescence in-situ hybridization (M-FISH) images. Both the simulation and real...
We investigate the correspondence between genetic variations with single nucleotide polymorphism (SNP) and brain activity measured by functional magnetic resonance imaging (fMRI). A group sparse canonical correlation analysis method (group sparse CCA) was proposed to explore the correlation between these two types of data, which are high dimensional with small number of samples. It can exploit the...
We developed a structure based sparse representation model for classifying chromosomes in M-FISH images. The sparse representation based classification model used in our previous work only considered one pixel without incorporating any structural information. The new proposed model extends the previous one to multiple pixels case, where each target pixel together with its neighboring pixels will be...
This paper presents a hybrid algorithm, based on ant colony algorithm, developed to address the dual-resource constrained job shop scheduling problem with heterogeneous workers. The algorithm establishes a dynamic candidate solution set, based on the technology constraint, for each ant to improve the calculating efficiency of the algorithm. Meanwhile, the algorithm utilizes the simulated annealing...
A hybrid ant colony algorithm with self-adaptive parameters has been researched in this paper. Two schemes of adjusting parameters have been put forward according to the simulation analysis on different affect of different parameter sets of TACOSA algorithm when solving the dual resource constrained job shop scheduling problem with heterogeneous workers which based on decreasing production cost. Based...
The paper proposes a predictive maintenance model for the deteriorating system with semi-Markov process, and presents a method to determine the best inspection and maintenance policy together. Furthermore, the phase-type (PH) algorithm is put forward to measure the transition probability matrix analytical tractability. The results of numerical simulation show that the model and algorithm are effective...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.