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Traditional Data Field Hierarchical Clustering Algorithm (DFHCA) uses brute force method to compute the forces exert on each object. The computation complexity increases as O ( n 2 ). In this study, we improve the force computation efficiency of DFHCA to O ( n log  n ). We use the Barnes–Hut tree to reduce the number of force computation by approximating far away particles with their center of mass. And compared with traditional method, our method does not need to tune the parameters. In our implementation, we discuss two different merging strategies. Experimental results show that the proposed method could improve the computation efficiency under the same settings. We also find that DFHCA-M merging strategy converges faster than DFHCA-S merging strategy. Finally, we compare and analyze the time complexity and space complexity of our algorithm. [ABSTRACT FROM AUTHOR]

Coconut proteins have attracted increasing attention due to their nutritional and potential health benefits, but there have been few proteomic studies on coconuts. The aims of this study were to generate a proteomic map and identify common coconut proteins in different species. Two-dimensional electrophoresis (2-DE) was used to comprehensively analyze coconut proteins. Approximately 200 protein spots were detected on 2-DE maps of coconut samples from three different sources. The proteins were distributed in seven taxa (labeled a to g) according to their molecular mass. Taxa a, b, e and g contained common proteins, while taxa e and g were thermally stable and, therefore, may be considered characteristic of coconut products. Taxa a, b, d, e and g were subjected to MALDI-TOF/TOF-MS analysis. Taxa a, b and g were found to be homologous to 7S globulin. Taxon d was identified as glutelin, and taxon e was identified as a putative receptor-like protein kinase. [ABSTRACT FROM AUTHOR]

Ophiocordyceps sinensis (Berk.) Sacc. is one of the most well-known fungi in traditional Chinese medicine and is attracting attention because of its nutritious and medicinal properties. The present study aimed to produce a proteomic map to identify common O. sinensis proteins. The caterpillar body and stroma of O. sinensis collected from five locations and four fungal specimens of similar appearance were examined by two-dimensional electrophoresis (2-DE). Five proteins were identified using MALDI-TOF--TOF/MS, and the 2-DE identification pattern was provided. OCS_04585 and β-lactamase domain-containing protein, the two abundant and characteristic proteins, were separated and purified using liquid-phase isoelectric focusing. The products were high-quality materials that can be used for future protein-function studies and immunoassay development. [ABSTRACT FROM AUTHOR]

A highly specific competitive enzyme-linked immunosorbent assay (ELISA) protocol has been developed to identify and classify almond products based on differential proteomic analysis. We applied two-dimensional electrophoresis to compare the differences between almond and apricot kernels to search for almond-specific proteins. The amino acid of apricot Pru-1 was sequenced and aligned to almond Pru-1. One peptide, RQGRQQGRQQQEEGR, which exists in almond but not in apricot, was used as hapten to prepare monoclonal antibody against almond Pru-1. An optimized ELISA method was established using this antibody. The assay did not exhibit cross-reactivity with the tested apricot kernels and other edible plant seeds. The limit of detection (LOD) was 2.5–100 μg/g based on different food samples. The recoveries of fortified samples at levels of twofold and eightfold LOD ranged from 82% to 96%. The coefficients of variation were less than 13.0%. Using 7 M urea as extracting solution, the heat-treated protein loss ratios were 2%, 5% and 15% under pasteurization (65 °C for 30 min), baking (150 °C for 30 min) and autoclaved sterilization (120 °C for 15 min), respectively. [ABSTRACT FROM AUTHOR]

The article presents a sandwich enzyme linked immunosorbent assay (ELISA) for identification of edible bird's nest. The characteristic sialoglycoproteins were found by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and purified by liquid-phase isoelectric focusing (LIEF). According to the analysis, the molecular weight was 106–128 kDa and the isoelectric point was ≤pH 3.0. Two anti-characteristic sialoglycoprotein monoclonal antibodies were produced. The monoclonal antibodies were examined by western-blot assay. One of the monoclonal antibody was used as coating and the other as the enzyme-labeled antibody after being coupled to horseradish peroxidase (HRP). Based on the optimized ELISA condition, the method was established with IC50of 1.5 ng/mL, and low cross-reactivity with various fake materials (<0.01%). ELISA provided a suitable means for screening of a large number of samples. The coefficients of variation were between 2.9% and 5.8%. [ABSTRACT FROM AUTHOR]

Abstract: Programmable Logic Controllers (PLC) are widely used in industry. Reliable PLC systems are vital to many critical applications. The reliability analysis of PLC is special because the hardware component and embedded software are combined and operated in a specific manner. This paper presents a probabilistic modeling for PLC systems, which considers both the hardware and software components. Three analysis strategies are proposed for probabilistic evaluation of reliability characterization. The first method is an input-based analysis which considers the impact of errors from primary inputs. The second one is an action-based analysis. It extends the first method by considering the impact of software-based processing deviations on primary inputs. The third method is an action-traverse analysis. It computes the reliability characterization in a single topological traverse through the primary inputs during the software execution. Experimental results demonstrate the effectiveness of our approaches when compared to fault tree analysis. [Copyright &y& Elsevier]

Interconnect congestion estimation plays an important role in the physical design of integrated circuits. Fast congestion analysis prior to global routing enhances the placement quality and improves the routability for the subsequent routing phases. This article presents a novel congestion estimation method for a wire layout with bounded detours and bends. Experimental results on benchmarks demonstrate the efficiency and accuracy of our approach. [ABSTRACT FROM AUTHOR]

With the increase of the complexity of circuits, fast estimation can provide some vital information for optimal layout decisions. Fast congestion prediction plays an important role in the physical layout of VLSI design. In this paper, we present a probabilistic estimation approach with via minimization constraints. Our model is more realistic than previous models. It has more flexibility for wires to have more usage area to bypass congested regions and blockages. The experiment on routing benchmarks demonstrates the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

Abstract: Congestion estimation plays an important role in the physical layout of VLSI design. This paper presents a new probabilistic estimation model that improves the previous estimators by relaxing the constraint on detours in a route. The model is more general and realistic for it gives the flexibility for the wires to have wider usage area to bypass the congestion regions and blockages. Given a routing grid and a set of nets to be routed, the model predicts the routing density on each edge of the grid. The routing density provides direct congestion estimation. We compare our estimation results to the actual routing results. Experimental results show the effectiveness of our estimator. [Copyright &y& Elsevier]

Interconnect planning is an important issue in VLSI designs. Routing congestion is an important problem during placement. This paper presents a novel approach to estimating the routing congestion on the hexagonal model with bounded-length detours. It is the first probabilistic estimation work on hexagonal topologies. A combinatorial estimation algorithm is presented. The experimental results demonstrate the effectiveness of the method. [ABSTRACT FROM AUTHOR]

We propose a semi-supervised approach towards anomaly detection in multivariate categorical data. Our goal is to learn a model that can distinguish the anomalous data, given a small set of training data from the normal class. To this end, our approach learns the probability distribution of normal instances with the assumption that the categorical data are generated from a continuous latent space. Gaussian process is adopted to construct the generative model. As a non-parametric Bayesian model, Gaussian process can adapt its model complexity according to the data size. Hence, our approach can be effective when the training dataset is small. Comprehensive experiments over different benchmarks clearly demonstrate the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

Foodborne illnesses associated with foodborne pathogens Listeria monocytogenes and Staphylococcus aureus occur at high frequencies. In this study, species‐specific primers and probes sets for the detection of L. monocytogenes and S. aureus were designed based on the nucleotide sequences of the actin‐assembly inducing protein precursor (actA) and clumping factor A (clfA) genes, respectively. We established a duplex RPA assay that is capable of simultaneously detecting L. monocytogenes and S. aureus within 15 min. With the plasmid standard, the sensitivity of the double RPA to L. monocytogenes and S. aureus can reach 102 copies/μL. The method also detected DNA extracted from samples inoculated with L. monocytogenes and S. aureus. After 4 hr of incubation, the sensitivity of the food model to L. monocytogenes and S. aureus reached 230 and 270 cfu/reaction, respectively. The assay was highly specific and had no cross‐reaction between closely related bacteria. Further assessment of this method on strains isolated within the lab collection showed that the duplex RPA provided the same testing results as microbiological methods. Therefore, the assay is effective for the rapid detection and preliminary screening of L. monocytogenes and S. aureus. Practical applications: Listeria monocytogenes and Staphylococcus aureus are two major foodborne pathogens and have been found in a wide range of foods. We developed a duplex RPA specific targeting actA and clfA genes with high‐amplification efficiency. We evaluated the performance of duplex RPA by building a food model. The detection results by the duplex RPA were compared with PCR and no significant differences were found. This study provides the information of the developed duplex RPA for detecting two specific foodborne pathogens, which will be helpful for further studies about simultaneous detection of several targets using duplex RPA. [ABSTRACT FROM AUTHOR]

Recombinase polymerase amplification (RPA) is an isothermal amplification technique. Because of its short detection cycle and high specificity, it has been applied in various fields. However, the design of probe on the efficiency of RPA is not well understood and the effect of sequence mismatches of oligonucleotides on the performance of RPA is rarely discussed. In this study, we found that different primers with the same probe have a slight effect on the efficiency of fluorescent RPA, and different probes with the same amplified region have a great influence on the efficiency of fluorescent RPA. We summarized the design rules of probes suitable for fluorescent RPA by analyzing the experimental data. The rule is that the best distance between fluorescent groups in the probe is 1–2 bases, and the G content should be reduced as far as possible. In addition, we verified this rule by designing a series of probes. Furthermore, we found the base mismatches of the probe had a significant effect on RPA, which can lead to false positives and can change the amplification efficiency. However, 1–3 mismatches covering the center of the primer sequence only affect the amplification efficiency of RPA, not its specificity. And with an increase in the number of primer mismatches, the efficiency of RPA will decrease accordingly. This study suggests that the efficiency of fluorescent RPA is closely related to the probe. We recommend that when designing a fluorescent probe, one must consider the presence of closely related non-targets and specific bases. [ABSTRACT FROM AUTHOR]