Dynamic Inference Approach Based on Rules Engine in Intelligent Edge Computing for Building Environment Control.

Computation offloading enables intensive computational tasks in edge computing to be separated into multiple computing resources of the server to overcome hardware limitations. Deep learning derives the inference approach based on the learning approach with a volume of data using a sufficient computing resource. However, deploying the domain-specific inference approaches to edge computing provides intelligent services close to the edge of the networks. In this paper, we propose intelligent edge computing by providing a dynamic inference approach for building environment control. The dynamic inference approach is provided based on the rules engine that is deployed on the edge gateway to select an inference function by the triggered rule. The edge gateway is deployed in the entry of a network edge and provides comprehensive functions, including device management, device proxy, client service, intelligent service and rules engine. The functions are provided by microservices provider modules that enable flexibility, extensibility and light weight for offloading domain-specific solutions to the edge gateway. Additionally, the intelligent services can be updated through offloading the microservices provider module with the inference models. Then, using the rules engine, the edge gateway operates an intelligent scenario based on the deployed rule profile by requesting the inference model of the intelligent service provider. The inference models are derived by training the building user data with the deep learning model using the edge server, which provides a high-performance computing resource. The intelligent service provider includes inference models and provides intelligent functions in the edge gateway using a constrained hardware resource based on microservices. Moreover, for bridging the Internet of Things (IoT) device network to the Internet, the gateway provides device management and proxy to enable device access to web clients.

Towards Network Lifetime Enhancement of Resource Constrained IoT Devices in Heterogeneous Wireless Sensor Networks.

The participating nodes in Wireless Sensor Networks (WSNs) are usually resource-constrained in terms of energy consumption, storage capacity, computational capability, and communication range. Energy is one of the major constraints which requires an efficient mechanism that takes into account the energy consumption of nodes to prolong the network lifetime. Particularly in the large scale heterogeneous WSNs, this challenge becomes more critical due to high data collection rate and increased number of transmissions. To this end, clustering is one of the most popular mechanisms which is being used to minimize the energy consumption of nodes and prolong the lifetime of the network. In this paper, therefore, we propose a robust clustering mechanism for energy optimization in heterogeneous WSNs. In the proposed scheme, nodes declare themselves as cluster head (CH) based on available resources such as residual energy, available storage and computational capability. The proposed scheme employs the multi criteria decision making technique named as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) which allows the child nodes to select the optimal CH among several potential CH candidates. Moreover, we also propose mechanisms such as CH-acquaintanceship and CH-friendship in order to prolong the network lifetime. Simulation results show that our proposed scheme minimizes the control overhead, reduces the power consumption and enhances overall lifetime of the network by comparing with the most recent and relevant proposed protocol for WSNs.

A novel small-molecule PPI inhibitor targeting integrin αvß3-osteopontin interface blocks bone resorption in vitro and prevents bone loss in mice.

Small molecule-inhibition targeting protein-protein interaction (PPI) is now recognized as an emerging and challenging area in drug design. We developed a novel interactive drug discovery methodology known as Protein Chip technology (ProteoChip) as a cutting-edge PPI assay system applicable for unique PPI-targeting therapeutics integrated with computer-aided drug design (CADD). Here, we describe a novel small molecular PPI inhibitor, IPS-02001, which the blocks integrin αvß3-osteopontin interface a novel PPI inhibitor identified by the interactive methodology of both ProteoChip- and CADD-based PPI assay. IPS-02001 (6,7-Dichloro-2,3,5,8-tetrahydroxy-1,4-naphthoquinone) was screened from different compound libraries (InterBioScreen, Commercial libraries) using an in silico structure-based molecular docking simulation method and a protein chip-based protein-protein interaction assay system. Additionally, integrin αvß3, an adhesion receptor expressed in osteoclasts (OCs), was implicated in the regulation of OC function via regulation of the cytoskeletal organization of OCs. IPS-02001 blocked OC maturation from murine bone marrow-derived macrophages, as well as the resorptive function of OCs. Moreover, treatment with IPS-02001 impaired downstream signaling of integrin αvß3 linked to Pyk2, c-Src, PLCγ2, and Vav3 and disrupted the actin cytoskeleton in mature OCs. Furthermore, IPS-02001 blocked RANKL-induced bone destruction by reducing the number of OCs and protected against ovariectomy-induced bone loss in mice. Thus, IPS-02001 may represent a promising new class of anti-resorptive drugs for treatment of bone diseases associated with increased OC function.

Erkitinib, a novel EGFR tyrosine kinase inhibitor screened using a ProteoChip system from a phytochemical library.

Receptor tyrosine kinases (PTKs) play key roles in the pathogenesis of numerous human diseases, including cancer. Therefore PTK inhibitors are currently under intensive investigation as potential drug candidates. Herein, we report on a ProteoChip-based screening of an epidermal growth factor receptor (EGFR) tyrosine kinase (TK) inhibitor, Erkitinibs, from phytochemical libraries. PLC-gamma-1 was used as a substrate immobilized on a ProteoChip and incubated with an EGFR kinase to phosphorylate tyrosine residues of the substrate, followed by a fluorescence detection of the substrate recognized by a phospho-specific monoclonal antibody. Erkitinibs inhibited HeLa cell proliferation in a dose-dependent manner. In conclusion, these data suggest that Erkitinibs can be a specific inhibitor of an EGFR kinase and can be further developed as a potent anti-tumor agent.

Knoellia aerolata sp. nov., isolated from an air sample in Korea.

An aerobic, Gram-positive, non-motile, non-spore-forming, rod-coccus-shaped bacterium, strain 5317S-21(T), was isolated from an air sample from Suwon city, Republic of Korea. The isolate was able to grow within a pH range of 5.0-9.0 and a temperature range of 5-35 degrees C and it tolerated up to 2 % (w/v) NaCl. The cell-wall peptidoglycan contained meso-diaminopimelic acid as diagnostic diamino acid. The predominant isoprenoid quinone was MK-8(H(4)). The major polar lipids were phosphatidylinositol, phosphatidylethanolamine and diphosphatidylglycerol; phosphatidylglycerol and several unknown phospholipids were also detected. Mycolic acids were absent. The only whole-cell sugar was glucose. The major cellular fatty acids were iso-C(16 : 0), C(17 : 1)omega8c and iso-C(15 : 0). 16S rRNA gene sequence analysis indicated that strain 5317S-21(T) was related phylogenetically to members of the genus Knoellia, with 97.4 % sequence similarity to the type strains of Knoellia sinensis and Knoellia subterranea. The G+C content of the genomic DNA of strain 5317S-21(T) was 73 mol%. Levels of DNA-DNA relatedness between strain 5317S-21(T) and the type strains of Knoellia sinensis and Knoellia subterranea were 37 and 41 %, respectively. It was concluded that strain 5317S-21(T) represents a novel species of the genus Knoellia, for which the name Knoellia aerolata sp. nov. is proposed. The type strain is 5317S-21(T) (=KACC 20583(T) =DSM 18566(T)).

Endoscopic grading of atrophic gastritis is inversely associated with gastroesophageal reflux and gastropharyngeal reflux.

BACKGROUND: Reflux esophagitis is inversely associated with the presence of atrophic gastritis, and endoscopic grading of atrophic gastritis correlates with histological evaluation. The aim of this study was to investigate the association of the endoscopic grade of atrophic gastritis with gastroesophageal and gastropharyngeal reflux. METHODS: A total of 627 patients, who underwent endoscopy and ambulatory 24-hour dual-probe pH monitoring, were included in this study. The grade of atrophic gastritis was endoscopically classified into 2 types with the atrophic pattern system: the closed-type (C-type) and the open-type (O-type). We compared the findings from endoscopy and ambulatory pH monitoring for these 2 types. RESULTS: The O-type was significantly associated with a lower prevalence of reflux esophagitis (p = 0.001). All variables showing gastroesophageal reflux in the distal probe were significantly lower in the O-type than in the C-type (p < 0.05). Similarly for the proximal probe, all variables, except the supine time of pH < 4, were significantly lower in the O-type than in the C-type (p < 0.05). The frequency of gastroesophageal reflux disease and gastropharyngeal reflux disease was in significantly lower in the O-type than in the C-type (p < 0.001, p = 0.012, respectively). CONCLUSIONS: Endoscopic grading of atrophic gastritis is easy and is inversely associated with gastroesophageal and gastropharyngeal reflux.