Semi-parametric evaluation of rapid rate-of-change proportional intensity models for repairable systems with censoring.

Keywords. repairable systems reliability, right-censoring, recurrent events, proportional intensity models, log-linear intensity functionThis research investigates the robustness of four leading proportional intensity (PI) models: PWP-gap time (PWP-GT), PWP-total time (PWP-TT), Andersen-Gill (AG), and Wei-Lin-Weissfeld (WLW), for right-censored recurrent failure event data that follow a Non-homogeneous Poisson Process (NHPP) with log-linear constant or increasing intensity function. The results are beneficial to practitioners in anticipating the more favorable applications domains and selecting appropriate PI models for monitoring failure trends and for decisions in preventive maintenance, service parts inventory, and repair versus replacement. The experimental design has incorporated four levels of censoring severity, three levels of sample size, and seven levels of shape parameter to evaluate these four proposed PI models. The effect of failure event count is also studied. The models of choice are the PWP-GT (for increasing rate of occurrence of failures and low event count) and AG (for constant rate of occurrence of failures), evaluated in terms of three robustness metrics: bias, mean absolute deviation, and mean squared error of covariate regression coefficients. The more favorable engineering application ranges are recommended. Robustness of the PWP-GT for the case of an underlying log-linear increasing intensity function tends to be sensitive to the failure event count. For lower failure counts (N ≤ 4), the PWP-GT proves to perform well for moderate to severe right-censoring (40% to 80% of units censored), constant and moderately increasing rates of occurrence of failure (log-linear NHPP shape parameter in the range of 0 ≤ theta ≤ 0.01), and small to large sample size (60 ≤ U ≤ 180). The AG model proves to outperform the PWP-TT and WLW for stationary process (HPP) across a wide range of right censorship (0% to 100%) and for sample size of 60 or more. A highly automated SAS macro proved to be a valuable tool for the research infrastructure in this and future studies

Association Between Maternal Weight Gain in Different Periods of Pregnancy and the Risk of Venous Thromboembolism: A Retrospective Case–Control Study

BackgroundVenous thromboembolism (VTE) remains an important cause of maternal deaths. Little is known about the associations of specific periods of gestational weight gain (GWG) with the category of VTE, pulmonary embolism (PE), or deep venous thrombosis (DVT) with or without PE.MethodsIn a retrospective case–control study conducted in Shanghai First Maternity and Infant Hospital from January 1, 2017 to September 30, 2021, cases of VTE within pregnancy or the first 6 postnatal weeks were identified. Controls without VTE were randomly selected from women giving birth on the same day as the cases, with 10 controls matched to each case. Total GWG and rates of early, mid, and late GWG values were standardized into z-scores, stratified by pre-pregnant body mass index (BMI). The adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were estimated through multivariate logistic regression models.ResultsThere were 196 cases (14.4 per 10,000) of VTE within pregnancy or the first 6 postnatal weeks were identified. Higher total weight gain was associated with increased risks of PE (aOR, 13.22; 95% CI, 2.03–85.99) and VTE (OR, 10.49; 95% CI, 1.82–60.45) among women with underweight. In addition, higher total weight gain was associated with increased risk of PE (aOR, 2.06; 95% CI, 1.14–3.72) among women with healthy weight. Similarly, rate of higher early weight gain was associated with significantly increased risk for PE (aOR, 2.15; 95% CI, 1.05–4.42) among women with healthy BMI. The lower rate of late weight gain was associated with increased risks of PE (aOR, 7.30; 95% CI, 1.14–46.55) and VTE (OR, 7.54; 95% CI, 1.20–47.57) among women with underweight. No significant associations between maternal rate of mid GWG and increased risk for any category of VTE, PE, or DVT with or without PE were present, regardless of maternal pre-pregnant BMI.ConclusionThe GWG associations with the category of VTE, PE, or DVT with or without PE differ at different periods of pregnancy. In order to effectively improve maternal and child outcomes, intensive weight management that continues through pregnancy may be indispensable

On the detection and refinement of transcription factor binding sites using ChIP-Seq data

Coupling chromatin immunoprecipitation (ChIP) with recently developed massively parallel sequencing technologies has enabled genome-wide detection of protein–DNA interactions with unprecedented sensitivity and specificity. This new technology, ChIP-Seq, presents opportunities for in-depth analysis of transcription regulation. In this study, we explore the value of using ChIP-Seq data to better detect and refine transcription factor binding sites (TFBS). We introduce a novel computational algorithm named Hybrid Motif Sampler (HMS), specifically designed for TFBS motif discovery in ChIP-Seq data. We propose a Bayesian model that incorporates sequencing depth information to aid motif identification. Our model also allows intra-motif dependency to describe more accurately the underlying motif pattern. Our algorithm combines stochastic sampling and deterministic ‘greedy’ search steps into a novel hybrid iterative scheme. This combination accelerates the computation process. Simulation studies demonstrate favorable performance of HMS compared to other existing methods. When applying HMS to real ChIP-Seq datasets, we find that (i) the accuracy of existing TFBS motif patterns can be significantly improved; and (ii) there is significant intra-motif dependency inside all the TFBS motifs we tested; modeling these dependencies further improves the accuracy of these TFBS motif patterns. These findings may offer new biological insights into the mechanisms of transcription factor regulation

The Effect of Iron Oxide Magnetic Nanoparticles on Smooth Muscle Cells

Recently, magnetic nanoparticles of iron oxide (Fe3O4, γ-Fe2O3) have shown an increasing number of applications in the field of biomedicine, but some questions have been raised about the potential impact of these nanoparticles on the environment and human health. In this work, the three types of magnetic nanoparticles (DMSA-Fe2O3, APTS-Fe2O3, and GLU-Fe2O3) with the same crystal structure, magnetic properties, and size distribution was designed, prepared, and characterized by transmission electronic microscopy, powder X-ray diffraction, zeta potential analyzer, vibrating sample magnetometer, and Fourier transform Infrared spectroscopy. Then, we have investigated the effect of the three types of magnetic nanoparticles (DMSA-Fe2O3, APTS-Fe2O3, and GLU-Fe2O3) on smooth muscle cells (SMCs). Cellular uptake of nanoparticles by SMC displays the dose, the incubation time and surface property dependent patterns. Through the thin section TEM images, we observe that DMSA-Fe2O3is incorporated into the lysosome of SMCs. The magnetic nanoparticles have no inflammation impact, but decrease the viability of SMCs. The other questions about metabolism and other impacts will be the next subject of further studies

Biometric Recognition Systems Employing Novel Shape-based Features

With the increased security requirements in a variety of applications and advances in sensor technology, emerging biometric technologies, including using some lesser known biometrics, have become important research topics. This is due to the potential benefits they may provide as independent biometric markers or as compliments to existing biometric systems. In this work, our aim is to explore new biometric technologies for person identification. We consider three different biometrics, namely, Three Dimensional (3D) and Two Dimensional (2D) ear biometrics, 3D face recognition, and human identification based on dental X-Ray images. For the ear biometrics component, we propose a novel 3D shape descriptor, termed Histogram of Categorized Shape (HCS), to robustly encode range images within a 3D object detection framework. For the 3D ear detection task, this feature, employed in conjunction with a linear SVM classifier and sliding window technique, produces a robust and efficient 3D ear detection system. Afterwards, we extend the HCS descriptor to an object-centered 3D surface feature descriptor, termed Surface Patch Histogram of Indexed Shape (SPHIS), for local surface patch representation. The SPHIS feature descriptor is evaluated for its effectiveness in real world scenarios where a database may contain ears of highly similar shape. The ear surface is also voxelized to construct a holistic representation. Based on the novel SPHIS feature and the voxelization representation, a unified approach incorporating local and holistic surface features is proposed to improve both the robustness and efficiency of the 3D ear shape matching subsystem, while simultaneously improving the performance of the recognition system. In the 2D domain, a complete, automatic ear biometric system based on 2D images is developed. The color Scale Invariant Feature Transform (SIFT) descriptor is exploited as the feature representation, which in conjunction with a feature fusion method, maximizes the robustness of the recognition system. For the 3D face recognition component, we propose a method using AdaBoost to determine the geodesic distances between anatomical point pairs that are most discriminative for 3D face recognition. Through a method that establishes a dense set of correspondences between face surfaces, the discriminating potential of geodesic distances between anatomical points is investigated. For the dental biometrics component, we present a content-based image archiving and retrieval system for assisting in human identification using dental radiographs. The system includes processes for dental image classification, automatic segmentation of bitewing dental X-Ray images, and teeth shape matching

A content-based system for human identification based on bitewing dental X-ray images

This paper presents a system for assisting in human identification using dental radiographs. The goal of the system is to archive antemortem (AM) dental images and enable content-based retrieval of AM images that have similar teeth shapes to a given postmortem (PM) dental image. During archiving, the system classifies the dental images to bitewing, periapical, and panoramic views. It then segments the teeth and the bones in the bitewing images, separates each tooth into the crown and the root, and stores the contours of the teeth in the database. During retrieval, the proposed system retrieves from the AM database the images with the most similar teeth to the PM image based on Hausdorff distance measure between the teeth contours. Experiments on a small database show that our method is effective for dental image classification and teeth segmentation, provides good results for separating each tooth into crown and root, and provides a good tool for human identification

Bacterial Genome Reengineering

The web application PrimerPair at ecogene.org generates large sets of paired DNA sequences surrounding­ all protein and RNA genes of Escherichia coli K-12. Many DNA fragments, which these primers amplify, can be used to implement a genome reengineering strategy using complementary in vitro cloning and in vivo recombineering. The integration of a primer design tool with a model organism database increases the level of quality control. Computer-assisted design of gene primer pairs relies upon having highly accurate genomic DNA sequence information that exactly matches the DNA of the cells being used in the laboratory to ensure predictable DNA hybridizations. It is equally crucial to have confidence that the predicted start codons define the locations of genes accurately. Annotations in the EcoGene database are queried by PrimerPair to eliminate pseudogenes, IS elements, and other problematic genes before the design process starts. These projects progressively familiarize users with the EcoGene content, scope, and application interfaces that are useful for genome reengineering projects. The first protocol leads to the design of a pair of primer sequences that were used to clone and express a single gene. The N-terminal protein sequence was experimentally verified and the protein was detected in the periplasm. This is followed by instructions to design PCR primer pairs for cloning gene fragments encoding 50 periplasmic proteins without their signal peptides. The design process begins with the user simply designating one pair of forward and reverse primer endpoint positions relative to all start and stop codon positions. The gene name, genomic coordinates, and primer DNA sequences are reported to the user. When making chromosomal deletions, the integrity of the provisional primer design is checked to see whether it will generate any unwanted double deletions with adjacent genes. The bad designs are recalculated and replacement primers are provided alongside the requested primers. A list of all genes with overlaps includes those expressed from the translational coupling motifs 5′-UGAUG-3′ and 5′-AUGA-3′. Rigid alignments of the 893 ribosome binding sites (RBSs) linked to the AUG codons of this coupled subset are assessed for information content using WebLogo 3.0. These specialized logos are missing the G at the prominent information peak position normally seen in the rigid alignment of all genes. This novel GHOLE motif was apparently masked by the normal RBSs in two previously published rigid alignments. We propose a model constraining the distance between the ATG and the RBS, obviating­ the need for a flexible linker model to reveal a Shine–Dalgarno-like sequence

<title>Automatic human identification based on dental x-ray images</title>

This paper presents an automated system for human identification using dental radiographs. The goal of the system is to automatically archive dental images and enable identification based on shapes of the teeth in bitewing images. During archiving, the system builds the antemortem (AM) database, where it segments the teeth and the bones, separates each tooth into crown and root, and stores the contours of the teeth in the database. During retrieval, given a dental image of a postmortem (PM), the proposed system identifies the person from the AM database by automatically matching extracted teeth contours from the PM image to the teeth contours in the AM database. Experiments on a small database show that our method is effective for teeth segmentation, separation of teeth into crowns and roots, and matching

EcoGene 3.0

EcoGene ( http://ecogene.org ) is a database and website devoted to continuously improving the structural and functional annotation of Escherichia coli K-12, one of the most well understood model organisms, represented by the MG1655(Seq) genome sequence and annotations. Major improvements to EcoGene in the past decade include (i) graphic presentations of genome map features; (ii) ability to design Boolean queries and Venn diagrams from EcoArray, EcoTopics or user-provided GeneSets; (iii) the genome-wide clone and deletion primer design tool, PrimerPairs; (iv) sequence searches using a customized EcoBLAST; (v) a Cross Reference table of synonymous gene and protein identifiers; (vi) proteome-wide indexing with GO terms; (vii) EcoTools access to >2000 complete bacterial genomes in EcoGene-RefSeq; (viii) establishment of a MySql relational database; and (ix) use of web content management systems. The biomedical literature is surveyed daily to provide citation and gene function updates. As of September 2012, the review of 37 397 abstracts and articles led to creation of 98 425 PubMed-Gene links and 5415 PubMed-Topic links. Annotation updates to Genbank U00096 are transmitted from EcoGene to NCBI. Experimental verifications include confirmation of a CTG start codon, pseudogene restoration and quality assurance of the Keio strain collection

Human Ear Recognition from Face Profile Images

In this paper, we present a novel system for ear identification from profile images of the face. The system has two steps. In the first step, the ear is automatically detected from the profile image of the face. In the second step, the ear image is transformed to a force field, then feature points are extracted and the best match is found from a database. We propose a method based on differential geometry to extract ear feature points. We use a transformation of the ear image to make it suitable for extracting the feature points using differential geometry. During recognition, the feature points obtained from a query image are aligned and compared with those in the database using Hausdorff distance. The experimental results show that our method is effective