CLOCIS:Cloud-based conformance testing framework for IoT devices in the future internet

In recent years, the Internet of Things (IoT) has not only become ubiquitous in daily life but has also emerged as a pivotal technology across various sectors, including smart factories and smart cities. Consequently, there is a pressing need to ensure the consistent and uninterrupted delivery of IoT services. Conformance testing has thus become an integral aspect of IoT technologies. However, traditional methods of IoT conformance testing fall short of addressing the evolving requirements put forth by both industry and academia. Historically, IoT testing has necessitated a visit to a testing laboratory, implying that both the testing systems and testers must be co-located. Furthermore, there is a notable absence of a comprehensive method for testing an array of IoT standards, especially given their inherent heterogeneity. With a surge in the development of diverse IoT standards, crafting an appropriate testing environment poses challenges. To address these concerns, this article introduces a method for remote IoT conformance testing, underpinned by a novel conceptual architecture termed CLOCIS. This architecture encompasses an extensible approach tailored for a myriad of IoT standards. Moreover, we elucidate the methods and procedures integral to testing IoT devices. CLOCIS, predicated on this conceptual framework, is actualized, and to attest to its viability, we undertake IoT conformance testing and present the results. When leveraging CLOCIS, small and medium-sized enterprises (SMEs) and entities in the throes of IoT service development stand to benefit from a reduced time to market and cost-efficient testing procedures. Additionally, this innovation holds promise for IoT standardization communities, enabling them to champion their standards with renewed vigor

Temperature change in pig rib bone during implant site preparation by low-speed drilling

OBJECTIVES: The purpose of this study was to evaluate the temperature change during low-speed drilling using infrared thermography. MATERIAL AND METHODS: Pig ribs were used to provide cortical bone of a similar quality to human mandible. Heat production by three implant drill systems (two conventional drilling systems and one low-speed drilling system) was evaluated by measuring the bone temperature using infrared thermography. Each system had two different bur sizes. The drill systems used were twist drill (2.0 mm/2.5 mm), which establishes the direction of the implant, and finally a 3.0 mm-pilot drill. Thermal images were recorded using the IRI1001 system (Infrared Integrated Systems Ltd.). Baseline temperature was 31±1ºC. Measurements were repeated 10 times, and a static load of 10 kg was applied while drilling. Data were analyzed using descriptive statistics. Statistical analysis was conducted with two-way ANOVA. RESULTS AND CONCLUSIONS: Mean values (n=10 drill sequences) for maximum recorded temperature (Max TºC), change in temperature (ΔTºC) from baseline were as follows. The changes in temperature (ΔTºC) were 1.57ºC and 2.46ºC for the lowest and the highest values, respectively. Drilling at 50 rpm without irrigation did not produce overheating. There was no significant difference in heat production between the 3 implant drill systems (p>;0.05). No implant drill system produced heat exceeding 47ºC, which is the critical temperature for bone necrosis during low-speed drilling. Low-speed drilling without irrigation could be used during implant site preparation

A peptide encoded by a highly conserved gene belonging to the genus Streptomyces shows antimicrobial activity against plant pathogens

The genus Streptomyces has been unceasingly highlighted for the versatility and diversity of the antimicrobial agents they produce. Moreover, it is a heavily sequenced taxon in the phylum Actinobacteria. In this study, 47 sequence profiles were identified as proteins highly conserved within the genus Streptomyces. Significant hits to the 38 profiles were found in more than 2000 Streptomyces genomes, 11 of which were further conserved in more than 90% of Actinobacterial genomes analyzed. Only a few genes corresponding to these sequence profiles were functionally characterized, which play regulatory roles in the morphology and biosynthesis of antibiotics. Here a highly conserved sequence, namely, SHC-AMP (Streptomyces highly conserved antimicrobial peptide), which exhibited antimicrobial activity against bacterial and fungal plant pathogens, was reported. In particular, Arabidopsis thaliana was effectively protected against infection with Pseudomonas syringae pv. tomato DC3000 by treatment with this peptide. Results indicated the potential application of this peptide as an antimicrobial agent for control of plant diseases. Our results suggest putative target genes for controlling Streptomyces spp., including the one exhibiting antimicrobial activity against a wide range of phytopathogens

A Context Retrieval Method for Context-awareness Using Ontology-Based Approach in Internet of Things Environments

A context-aware system is required for providing context-aware services to users in the Internet of things (IoT) environment. It consists of three primary tasks: gathering context data, abstracting the collected data, and providing services to users. In IoT environments, context data are generated by a large number of sensors, and this context data are part of the context-awareness services provided to the users. When the context-aware system provides context-aware services with their service descriptions, it is necessary to process the data gathered by abstracting and contextualizing them. Generally, the context-aware system encounters a problem in that the context representations between contextualized sensor data and their related service descriptions do not match well. We herein propose a context retrieval method that facilitates in obtaining context information for the context-aware system in IoT environments. The context-aware system communicates with an ontology module that handles input data described in a set of universal resource identifiers, as a triplet. The ontology module resolves each representation request from the context-aware system. The proposed method provides an ontology-based mapping procedure for the context representation problem described above

Design and synthesis of multigrain nanocrystals via geometric misfit strain.

The impact of topological defects associated with grain boundaries (GB defects) on the electrical, optical, magnetic, mechanical and chemical properties of nanocrystalline materials1,2 is well known. However, elucidating this influence experimentally is difficult because grains typically exhibit a large range of sizes, shapes and random relative orientations3-5. Here we demonstrate that precise control of the heteroepitaxy of colloidal polyhedral nanocrystals enables ordered grain growth and can thereby produce material samples with uniform GB defects. We illustrate our approach with a multigrain nanocrystal comprising a Co3O4 nanocube core that carries a Mn3O4 shell on each facet. The individual shells are symmetry-related interconnected grains6, and the large geometric misfit between adjacent tetragonal Mn3O4 grains results in tilt boundaries at the sharp edges of the Co3O4 nanocube core that join via disclinations. We identify four design principles that govern the production of these highly ordered multigrain nanostructures. First, the shape of the substrate nanocrystal must guide the crystallographic orientation of the overgrowth phase7. Second, the size of the substrate must be smaller than the characteristic distance between the dislocations. Third, the incompatible symmetry between the overgrowth phase and the substrate increases the geometric misfit strain between the grains. Fourth, for GB formation under near-equilibrium conditions, the surface energy of the shell needs to be balanced by the increasing elastic energy through ligand passivation8-10. With these principles, we can produce a range of multigrain nanocrystals containing distinct GB defects