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The Internet of things (IoT) information system plays important roles in disposing of huge volumes of real-time service requests from heterogeneous devices, targeting for different complex application requirements. Load-dispatching control (LDC) is a key problem to be solved for devices accessing concurrently in cluster systems. Self-adaptive LDC optimizes the resource allocation to ensure no overloading node, thus, improving the performance of IoT systems. This paper focuses on adaptive dispatching control problem in IoT information system. First, a device data access platform is proposed for reducing the load imbalance and improving the efficiency of data processing. Then, we propose a processing capability prediction model to evaluate the system performance. On the basis of the model, we present a practical self-adaptive LDC framework with a self-adaptive control strategy and a load dispatching method. Finally, a case study is given to verify the framework and the control strategy. Experimental results show that the proposed strategy can meet the requirements of dynamic load balancing with the ability to avoid the load imbalance problem, and the LDC-based device access platform can process data accessing effectively and ubiquitously. [ABSTRACT FROM AUTHOR]

Acute respiratory tract infection is a major cause of morbidity and mortality worldwide, particularly in infants and young children. High-throughput, accurate, broad-range tools for etiologic diagnosis are critical for effective epidemic control. In this study, the diagnostic capacities of an Ibis platform based on the PCR/ESI-MS assay were evaluated using clinical samples. Nasopharyngeal aspirates (NPAs) were collected from 120 children ( <5 years old) who were hospitalized with lower respiratory tract infections between November 2010 and October 2011. The respiratory virus detection assay was performed using the PCR/ESI-MS assay and the DFA. The discordant PCR/ESI-MS and DFA results were resolved with RT-PCR plus sequencing. The overall agreement for PCR/ESI-MS and DFA was 98.3% (118/120). Compared with the results from DFA, the sensitivity and specificity of the PCR/ESI-MS assay were 100% and 97.5%, respectively. The PCR/ESI-MS assay also detected more multiple virus infections and revealed more detailed subtype information than DFA. Among the 12 original specimens with discordant results between PCR/ESI-MS and DFA, 11 had confirmed PCR/ESI-MS results. Thus, the PCR/ESI-MS assay is a high-throughput, sensitive, specific and promising method to detect and subtype conventional viruses in respiratory tract infections and allows rapid identification of mixed pathogens. J. Med. Virol. 87:1867-1871, 2015. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Ultrafast time‐stretch imaging technique recently attracts an increasing interest for applications in cell classification due to high throughput and high sensitivity. A novel imaging modality of time‐stretch imaging technique for edge detection is proposed. Edge detection based on the directional derivative is realized using differential detection. As the image processing is mainly implemented in the physical layer, the computation complexity of edge extraction is significantly reduced. An imaging system for edge detection with the scan rate of 77.76 MHz is experimentally demonstrated. Resolution target is first measured to verify the feasibility of the edge extraction. Furthermore, various cells, including red blood cells, lung cancer cells and breast cancer cells, are detected. The edges of cancerous cells present in a completely different form. The imaging system for edge detection would be a good candidate for high‐throughput cell classification. An ultrafast time‐stretch imaging technique for edge detection is demonstrated at the scan rate of 77.76 MHz for extracting the edges of various cells including red blood cells, lung cancer cells and breast cancer cells. As the edge detection is implemented in the physical layer, the computation complexity in the back‐end digital signal processing could be significantly reduced. The cells can be easily and rapidly identified by distinguishing the edges. [ABSTRACT FROM AUTHOR]

Abstract: Acanthamoeba spp. can be parasitic in certain situations and are responsible for serious human infections, including Acanthamoeba keratitis, granulomatous amoebic encephalitis, and cutaneous acanthamoebiasis. We analyzed the fatty acid composition of Acanthamoeba castellanii trophozoites and tested the inhibitory activity of the main fatty acids, oleic acid and arachidonic acid, in vitro. Oleic acid markedly inhibited the growth of A. castellanii, with trophozoite viability of 57.4% at a concentration of 200 μM. Caspase‐3 staining and annexin V assays showed that apoptotic death occurred in A. castellanii trophozoites. Quantitative PCR and dot blot analysis showed increased levels of metacaspase and interleukin‐1β converting enzyme, which is also an indication of apoptosis. In contrast, arachidonic acid showed negligible inhibition of growth of A. castellanii trophozoites. Stimulated expression of Atg3, Atg8 and LC3A/B genes and monodansylcadaverine labeling suggested that oleic acid induces apoptosis by triggering autophagy of trophozoites. [ABSTRACT FROM AUTHOR]