Calving Interval Sapi Perah Laktasi Di Balai Besar Pembibitan Ternak Unggul Dan Hijauan Pakan Ternak (Bbptu-hpt) Baturraden Purwokerto Jawa Tengah

The aim of this research are to know calving interval and factor´s at lactation dairy cattle in BBPTU-HPT Baturraden Purwokerto Central Java. This research was conducted on April 29 th -- May 13 th 2014 to on 151 heads lactating dairy cattle. This research used sensus method, data obtained was real data that present and accuread in BBPTU-HPT Baturraden. Analysis data used regression analysis with SPSS (Statistik Packet for Social Science). The result showed that the calving interval at lactating dairy cattle in BBPTU-HPT Baturraden is 14.80 ± 3.36 months. Factor that effect calving interval at lactating dairy cattle in BBPTU-HPT Baturraden from the herds man level are the number of cattle that maintain positively associated with factor value 0.177 and the distance between the cow shed with office that negatively assosiated with factor value 0.243. factor that efect calving interval on dairy cattle at the level of cattle are the age dairy cattle that positively associated with factor value 0,247;, periode lactation that negatively assosiated with factor value 0,287;, mating partus that positively associated with factor value 0,057;, lactating period that positively associated with factor value 0,904;, and dry priod that positively associated with factor value 0,961

Dynamics of Stock Market Correlations

We present a novel approach to the study the dynamics of stock market correlations. This is achieved through an innovative visualization tool that allows an investigation of the structure and dynamics of the market, through the study of correlations. This is based on the Stock Market Holography (SMH) method recently introduced. This qualitative measure is complemented by the use of the eigenvalue entropy measure, to quantify how the information in the market changes in time. Using this innovative approach, we analyzed data from the New York Stock Exchange (NYSE), and the Tel Aviv Stock Exchange (TASE), for daily trading data for the time period of 2000–2009. This paper covers these new concepts for the study of financial markets in terms of structure and information as reflected by the changes in correlations over time.Correlation, Stock Market Holography, eigenvalue entropy, sliding window

EUS-guided vascular interventions

Endoscopic ultrasound (EUS) has numerous advanced applications as a diagnostic and therapeutic modality in contemporary medicine. Through intraluminal placement, EUS offers a real-time Doppler-guided endoscopic visualization and access to intra-abdominal vasculature, which were previously inaccessible using historical methods. We aim to provide a comprehensive review of key studies on both current and future EUS-guided vascular applications. This review details EUS-based vascular diagnostic techniques of portal pressure measurements in the prognostication of liver disease and portal venous sampling for obtaining circulating tumor cells in the diagnosis of cancer. From an interventional perspective, we describe effective EUS-guided treatments via coiling and cyanoacrylate injections of gastric varices and visceral artery pseudoaneurysms. Specific attention is given to clinical studies on efficacy and procedural techniques described by investigators for each EUS-based application. We explore novel and future emerging EUS-based interventions, such as liver tumor ablation and intrahepatic portosystemic shunt placement

A Fatal Case of Brucine Poisoning

In some parts of India people follow a religious ritual of drinking an herbal preparation made from the bark of Alstonia scholaris tree (Blackboard tree) on the day of new moon in the month of July. This tree could be easily confused with Strychnos nux vomica tree. Brucine is the predominant alkaloid present in the bark of the tree Strychnos nux vomica. Toxicological property of Brucine is similar to strychnine. Brucine is a neurotoxin. A 29-year-old male presented with a history of consumption of a herbal preparation made from the bark of the Strychnos nux vomica tree confusing it for Alstonia scholaris. Soon after, he developed convulsions and later he died in the hospital on the same day. The main aim of this case report is to highlight the fact that people must be cautious when they follow religious rituals

Quantum central limit theorem for continuous-time quantum walks on odd graphs in quantum probability theory

The method of the quantum probability theory only requires simple structural data of graph and allows us to avoid a heavy combinational argument often necessary to obtain full description of spectrum of the adjacency matrix. In the present paper, by using the idea of calculation of the probability amplitudes for continuous-time quantum walk in terms of the quantum probability theory, we investigate quantum central limit theorem for continuous-time quantum walks on odd graphs.Comment: 19 page, 1 figure

An algorithm for network-based gene prioritization that encodes knowledge both in nodes and in links

Background: Candidate gene prioritization aims to identify promising new genes associated with a disease or a biological process from a larger set of candidate genes. In recent years, network-based methods - which utilize a knowledge network derived from biological knowledge - have been utilized for gene prioritization. Biological knowledge can be encoded either through the network's links or nodes. Current network-based methods can only encode knowledge through links. This paper describes a new network-based method that can encode knowledge in links as well as in nodes. Results: We developed a new network inference algorithm called the Knowledge Network Gene Prioritization (KNGP) algorithm which can incorporate both link and node knowledge. The performance of the KNGP algorithm was evaluated on both synthetic networks and on networks incorporating biological knowledge. The results showed that the combination of link knowledge and node knowledge provided a significant benefit across 19 experimental diseases over using link knowledge alone or node knowledge alone. Conclusions: The KNGP algorithm provides an advance over current network-based algorithms, because the algorithm can encode both link and node knowledge. We hope the algorithm will aid researchers with gene prioritization. © 2013 Kimmel, Visweswaran

Network Theory Analysis of Antibody-Antigen Reactivity Data: The Immune Trees at Birth and Adulthood

Motivation: New antigen microarray technology enables parallel recording of antibody reactivities with hundreds of antigens. Such data affords system level analysis of the immune system’s organization using methods and approaches from network theory. Here we measured the reactivity of 290 antigens (for both the IgG and IgM isotypes) of 10 healthy mothers and their term newborns. We constructed antigen correlation networks (or immune networks) whose nodes are the antigens and the edges are the antigen-antigen reactivity correlations, and we also computed their corresponding minimum spanning trees (MST) – maximal information reduced sub-graphs. We quantify the network organization (topology) in terms of the network theory divergence rate measure and rank the antigen importance in the full antigen correlation networks by the eigen-value centrality measure. This analysis makes possible the characterization and comparison of the IgG and IgM immune networks at birth (newborns) and adulthood (mothers) in terms of topology and node importance. Results: Comparison of the immune network topology at birth and adulthood revealed partial conservation of the IgG immune network topology, and significant reorganization of the IgM immune networks. Inspection of the antigen importance revealed some dominant (in terms of high centrality) antigens in the IgG and IgM networks at birth, which retain their importance at adulthood

Statistical Inference for Valued-Edge Networks: Generalized Exponential Random Graph Models

Across the sciences, the statistical analysis of networks is central to the production of knowledge on relational phenomena. Because of their ability to model the structural generation of networks, exponential random graph models are a ubiquitous means of analysis. However, they are limited by an inability to model networks with valued edges. We solve this problem by introducing a class of generalized exponential random graph models capable of modeling networks whose edges are valued, thus greatly expanding the scope of networks applied researchers can subject to statistical analysis