Kelimpahan Dan Keanekaragaman Plankton Di Perairan Laguna Desa Tolongano Kecamatan Banawa Selatan

Penelitian bertujuan untuk mengetahui kelimpahan dan keanekaragaman plankton yang ada di Perairan Laguna, Desa Tolongano, Kecamatan Banawa Selatan. Penelitian dilaksanakan pada bulan Juni – Juli 2009. Pengambilan sampel plankton bertempat di Perairan Laguna, Desa Tolongano, Kecamatan Banawa Selatan, Kabupaten Donggala. Identifikasi sampel dilakukan di Laboratorium Budidaya Perairan, Fakultas Pertanian, Universitas Tadulako. Metode penelitian yang digunakan adalah purpossive sampling method (penempatan titik sampel dengan sengaja). Stasiun pengambilan sampel terdiri atas 5 stasiun, dilakukan sebanyak 3 kali yaitu pada pukul 07.00, 12.00, dan 17.00 WITA. Hasil penelitian menunjukkan, bahwa kelimpahan fitoplankton dari kelas Bacillariophyceae berkisar antara 8.925 – 16.135 ind/l dan kelimpahan zooplankton dari kelas Crustacea berkisar antara 35 – 70 ind/l, indeks keanekaragaman fitoplankton dari kelas Bacillariophyceae berkisar antara 2,010 – 2,504 dan indeks keanekaragaman zooplankton dari kelas Crustacea berkisar antara 0 – 0,6931, indeks dominansi dari kelas Bacillariophyceae berkisar antara 1,1995 – 1,2326 menunjukkan ada jenis plankton yang mendominasi, yaitu Nitzchia sp

Systematic identification of an integrative network module during senescence from time-series gene expression

Background: Cellular senescence irreversibly arrests growth of human diploid cells. In addition, recent studies have indicated that senescence is a multi-step evolving process related to important complex biological processes. Most studies analyzed only the genes and their functions representing each senescence phase without considering gene-level interactions and continuously perturbed genes. It is necessary to reveal the genotypic mechanism inferred by affected genes and their interaction underlying the senescence process. Results: We suggested a novel computational approach to identify an integrative network which profiles an underlying genotypic signature from time-series gene expression data. The relatively perturbed genes were selected for each time point based on the proposed scoring measure denominated as perturbation scores. Then, the selected genes were integrated with protein-protein interactions to construct time point specific network. From these constructed networks, the conserved edges across time point were extracted for the common network and statistical test was performed to demonstrate that the network could explain the phenotypic alteration. As a result, it was confirmed that the difference of average perturbation scores of common networks at both two time points could explain the phenotypic alteration. We also performed functional enrichment on the common network and identified high association with phenotypic alteration. Remarkably, we observed that the identified cell cycle specific common network played an important role in replicative senescence as a key regulator. Conclusions: Heretofore, the network analysis from time series gene expression data has been focused on what topological structure was changed over time point. Conversely, we focused on the conserved structure but its context was changed in course of time and showed it was available to explain the phenotypic changes. We expect that the proposed method will help to elucidate the biological mechanism unrevealed by the existing approaches.1

Production Scheduling with Queue-time Constraints: Alternative Formulations

Abstract In manufacturing, queue-time constraints occur when a set of consecutive process steps must be completed within a fixed time window. Such constraints are common in semiconductor manufacturing, particularly in the diffusion area. Violations of queue-time constraints can lead to rework, scrap and longer cycle times. These constraints add significant complexity to the already difficult problem of scheduling in a semiconductor fab. In this paper, we consider the gate-keeping decision. Given a job arriving at a queue-time zone, the decision to be made is whether and when the job should be allowed to enter the zone. To make this decision, we propose a mixed integer linear programming model of the local scheduling problem within the queue-time zone. Because the gate-keeping decision is made at a higher level than detailed scheduling, our local scheduling model is simplified, i.e., it does not incorporate issues such as batching. This simplification allows us to consider a larger set of arriving jobs when making the gate-keeping decision. We propose two alternative model formulations, time-and slot-based, for the local scheduling problem. We compare the performance of these two formulations using a set of numerical experiments generated based on process flow information from an actual semiconductor fab

A Multi-Sample Based Method for Identifying Common CNVs in Normal Human Genomic Structure Using High-Resolution aCGH Data

BACKGROUND: It is difficult to identify copy number variations (CNV) in normal human genomic data due to noise and non-linear relationships between different genomic regions and signal intensity. A high-resolution array comparative genomic hybridization (aCGH) containing 42 million probes, which is very large compared to previous arrays, was recently published. Most existing CNV detection algorithms do not work well because of noise associated with the large amount of input data and because most of the current methods were not designed to analyze normal human samples. Normal human genome analysis often requires a joint approach across multiple samples. However, the majority of existing methods can only identify CNVs from a single sample. METHODOLOGY AND PRINCIPAL FINDINGS: We developed a multi-sample-based genomic variations detector (MGVD) that uses segmentation to identify common breakpoints across multiple samples and a k-means-based clustering strategy. Unlike previous methods, MGVD simultaneously considers multiple samples with different genomic intensities and identifies CNVs and CNV zones (CNVZs); CNVZ is a more precise measure of the location of a genomic variant than the CNV region (CNVR). CONCLUSIONS AND SIGNIFICANCE: We designed a specialized algorithm to detect common CNVs from extremely high-resolution multi-sample aCGH data. MGVD showed high sensitivity and a low false discovery rate for a simulated data set, and outperformed most current methods when real, high-resolution HapMap datasets were analyzed. MGVD also had the fastest runtime compared to the other algorithms evaluated when actual, high-resolution aCGH data were analyzed. The CNVZs identified by MGVD can be used in association studies for revealing relationships between phenotypes and genomic aberrations. Our algorithm was developed with standard C++ and is available in Linux and MS Windows format in the STL library. It is freely available at: http://embio.yonsei.ac.kr/~Park/mgvd.php

Rapid Consensus Structure: Continuous Common Knowledge in Asynchronous Distributed Systems

A distributed system guarantees the acceptance of Byzantine fault tolerance (BFT) for information transmission. Practical BFT (pBFT) and asynchronous BFT (aBFT) are among the various available forms of BFT. Distributed systems generally share information with all participating nodes. After information is shared, the systems reshare it. Thus, ensuring BFT consumes a considerable amount of time. Herein, we propose Decision search protocols that apply the gossip protocol, denoted by DecisionBFT, for distributed networks with guaranteed BFT. Each protocol in DecisionBFT is completely asynchronous and leaderless; it has an eventual consensus but no round-robin or proof-of-work. The core concept of the proposed technology is the consensus structure, which is based on the directed acyclic graph (DAG) and gossip protocol. In the most general form, each node in the algorithm has a set of k neighbors of most preference. When receiving transactions, a node creates and connects an event block with all its neighbors. Each event block is signed by the hashes of the creating node and its k peers. The consensus structure of the event blocks utilizes a DAG, which guarantees aBFT. The proposed framework uses Lamport timestamps and concurrent common knowledge. Further, an example of a Decision search algorithm, based on the gossip protocol DecisionBFT, is presented. The proposed DecisionBFT protocol can reach a consensus when 2/3 of all participants agree to an event block without any additional communication overhead. The DecisionBFT protocol relies on a cost function to identify the k peers and generate the DAG-based consensus structure. By creating a dynamic flag table that stores connection information between blocks, the gossip protocol achieves a consensus in fewer steps than that in the case of the existing aBFT protocol

Comparison of the performance of various algorithms for dataset 1, 2, and 3.

<p>The proposed method showed the best performance for all three datasets.</p

Predicting performance comparison of the proposed method with four existing methods using PPI data to identify informative genes.

<p>For each experiment, the optimal combination of two thresholds was obtained using the approach mentioned above and was applied to an independent test using unlabeled samples. Bold font indicates the superior performer.</p><p>TSVM: <i>P</i> (the ratio of two class labels).</p><p>SVM: PolyKernel –C 250007–E 1.0, The complexity parameter C (1.0), epsilon (1.0E−12), filterType (Normalized training data).</p><p>Naïve Bayesian: No parameters.</p><p>Random Forest: numTrees (10), seed (1).</p

Innocuous, Highly Conductive, and Affordable Thermal Interface Material with Copper-Based Multi-Dimensional Filler Design

Thermal interface materials (TIMs), typically composed of a polymer matrix with good wetting properties and thermally conductive fillers, are applied to the interfaces of mating components to reduce the interfacial thermal resistance. As a filler material, silver has been extensively studied because of its high intrinsic thermal conductivity. However, the high cost of silver and its toxicity has hindered the wide application of silver-based TIMs. Copper is an earth-abundant element and essential micronutrient for humans. In this paper, we present a copper-based multi-dimensional filler composed of three-dimensional microscale copper flakes, one-dimensional multi-walled carbon nanotubes (MWCNTs), and zero-dimensional copper nanoparticles (Cu NPs) to create a safe and low-cost TIM with a high thermal conductivity. Cu NPs synthesized by microwave irradiation of a precursor solution were bound to MWCNTs and mixed with copper flakes and polyimide matrix to obtain a TIM paste, which was stable even in a high-temperature environment. The cross-plane thermal conductivity of the copper-based TIM was 36 W/m/K. Owing to its high thermal conductivity and low cost, the copper-based TIM could be an industrially useful heat-dissipating material in the future