Buurmorrison6778

Aiming at the problem that the performance of adaptive Kalman filter estimation will be affected when the statistical characteristics of the process and measurement of the noise matrices are inaccurate and time-varying in the linear Gaussian state-space model, an algorithm of multi-fading factor and an updated monitoring strategy adaptive Kalman filter-based variational Bayesian is proposed. Inverse Wishart distribution is selected as the measurement noise model and the system state vector and measurement noise covariance matrix are estimated with the variational Bayesian method. The process noise covariance matrix is estimated by the maximum a posteriori principle, and the updated monitoring strategy with adjustment factors is used to maintain the positive semi-definite of the updated matrix. The above optimal estimation results are introduced as time-varying parameters into the multiple fading factors to improve the estimation accuracy of the one-step state predicted covariance matrix. The application of the proposed algorithm in target tracking is simulated. The results show that compared with the current filters, the proposed filtering algorithm has better accuracy and convergence performance, and realizes the simultaneous estimation of inaccurate time-varying process and measurement noise covariance matrices.Bayesian methods have been rapidly developed due to the important role of explicable causality in practical problems. We develope geometric approaches to Bayesian inference of Pareto models, and give an application to the analysis of sea clutter. For Pareto two-parameter model, we show the non-existence of α-parallel prior in general, hence we adopt Jeffreys prior to deal with the Bayesian inference. Considering geodesic distance as the loss function, an estimation in the sense of minimal mean geodesic distance is obtained. Meanwhile, by involving Al-Bayyati's loss function we gain a new class of Bayesian estimations. In the simulation, for sea clutter, we adopt Pareto model to acquire various types of parameter estimations and the posterior prediction results. Simulation results show the advantages of the Bayesian estimations proposed and the posterior prediction.Floral organs have evolved from leaves for reproduction, and the morphological analyses help to understand the plant diversity and evolution. Habenaria radiata (syn. Pecteilis radiata) is a terrestrial orchid living in wetlands in Japan, Russia, South Korea, and China. GSK2110183 The habitats of this plant in Japan have been reduced because of environmental destruction and overexploitation, and thus it is on the Red List of Japan as a Near Threatened species. One of the three petals of the H. radiata flower is called a lip or labellum, which resembles a flying white bird, egret, or white heron, with its proposed function being to attract pollinators. To understand the diversity of H. radiata plants in different areas, we examined the lip morphology and phylogeny of populations from eight habitats in the Kinki area, Japan. The complex shapes of the lips were quantified and presented as a radar chart, enabling characterization of the morphological difference among populations. Phylogenetic analysis with microsatellite markers that we generated showed the variation of genetic diversity among populations, suggesting the different degrees of inbreeding, outbreeding, and vegetative propagation. Our approach offers a basic method to characterize the morphological and genetic diversity in natural populations.This paper addresses the Multi-Athlete Tracking (MAT) problem, which plays a crucial role in sports video analysis. There exist specific challenges in MAT, e.g., athletes share a high similarity in appearance and frequently occlude with each other, making existing approaches not applicable for this task. To address this problem, we propose a novel online multiple athlete tracking approach which make use of long-term temporal pose dynamics for better distinguishing different athletes. Firstly, we design a Pose-based Triple Stream Network (PTSN) based on Long Short-Term Memory (LSTM) networks, capable of modeling long-term temporal pose dynamics of athletes, including pose-based appearance, motion and athletes' interaction clues. Secondly, we propose a multi-state online matching algorithm based on bipartite graph matching and similarity scores produced by PTSN. It is robust to noisy detections and occlusions due to the reliable transitions of multiple detection states. We evaluate our method on the APIDIS, NCAA Basketball and VolleyTrack databases, and the experiment results demonstrate its effectiveness.The present study analyzed the methanol extract and tincture obtained from the spontaneous Romanian Cichorium intybus species, in order to evaluate polyphenols content and some biological properties. Chromatographic and spectrophotometric methods were used for the analysis of polyphenols and the antioxidant capacity was assessed in vitro with DPPH● (2,2-diphenyl-picrylhydrazil) and FRAP (ferric-reducing antioxidant power) tests. The cardio-protective effects of Cichoriiherba tincture on myocardial ischemia induced by isoprenaline and nephroprotection on renal failure induced by gentamicin were evaluated on rats. Also, aspartate aminotrasferase (AST), alanine aminotransferase (ALT), creatine kinase-MB (CK-MB) and creatinine clearance (CrCl) were measured. The antioxidant effect was evaluated by determining total oxidative stress (TOS), oxidative stress index (OSI, total antioxidant capacity (TAC), malondyaldehide (MDA), total thiols (SH) and total nitrites and nitrates (NOx). Cichoric acid was the main polyphenolic compound. The extracts had moderate in vitro antioxidant activity but the in vivo antioxidant and anti-inflammatory effects were significant and associated with myocardial and renal dysfunction improvement. The results were attributed to the content of polyphenols in the extracts, for which reason C. intybus may be considered an important raw material for pharmaceuticals formulations recommended in the prevention or treatment of heart or kidney diseases.

The combination of the unique properties of cancer cells makes it possible to find specific ligands that interact directly with the tumor, and to conduct targeted tumor therapy. Phage display is one of the most common methods for searching for specific ligands. Bacteriophages display peptides, and the peptides themselves can be used as targeting molecules for the delivery of diagnostic and therapeutic agents. Phage display can be performed both in vitro and in vivo. Moreover, it is possible to carry out the phage display on cells pre-enriched for a certain tumor marker, for example, CD44 and CD133.

For this work we used several methods, such as phage display, sequencing, cell sorting, immunocytochemistry, phage titration.

We performed phage display using different screening systems (in vitro and in vivo), different phage libraries (Ph.D-7, Ph.D-12, Ph.D-C7C) on CD44+/CD133+ and without enrichment U-87 MG cells. The binding efficiency of bacteriophages displayed tumor-targeting peptides on U-87 MG cells was compared in vitro.