This paper demonstrates a single sensor based multispectral spectral imaging camera using a hybrid RGB colour mosaic made of plasmonic and 1D photonic crystal layers.

In this paper, we review the work we have done to improve the performance of users located at the cell boundary of a 60 GHz radio-over-fibre fronthaul using coordinated-multipoint (CoMP) together with non-orthogonal-multiple-access (NOMA).

This paper introduces a novel IoT-owned service for Global IoT Device Discovery and Integration (GIDDI) of existing IoT devices that are owned and managed by different parties who are the IoT devices providers. The GIDDI service promotes the sharing of existing IoT devices and the deployment of new devices via a revenue generating scheme for the IoT device providers. Unlike existing IoT device discovery and integration solutions that are currently owned and/or controlled by specific IoT platform or service providers, the GIDDI service has been specifically designed to manage all the metadata needed for IoT device discovery and integration in a specialized blockchain (we refer to this as GIDDI Blockchain) and via this blockchain-based solution be IoT-owned (i.e., not owned or controlled by any specific provider). In addition to the GIDDI Blockchain, the GIDDI service includes a distributed GIDDI Marketplace that provides the functionality of IoT device discovery, integration and payment. The paper describes a proof-of-concept implementation of the GIDDI blockchain. It also provides an experimental evaluation of the GIDDI blockchain in variety of IoT device registration and query workloads. An evaluation of the proposed GIDDI service concludes the paper.

The inherent centralized control architecture of radio-over-fiber (RoF) enables advanced coordination functionality to be implemented in a RoF-based mobile fronthaul to facility network management and coordination. This advanced coordination functionality enhances the performance of disadvantaged end users located further away from the remote radio head (RRH) or at the cell edges. In this paper, we review our work incorporating multi-level code based non-orthogonal multiple access (NOMA) to improve the performance of users located further away from the RRH with poor channel gain.

In this article, we propose a model-based characterization of energy consumption in a software-defined wireless sensor network (SD-WSN) architecture in an effort to examine the implications for network performance when making the WSN reprogrammable. The proposed model consists of breaking down all key functions involved in the correct functioning of an SD-WSN, namely; neighbor discovery, neighbor advertisement, network configuration, and data collection. The model is analyzed from a multihop network perspective. We consider two static SD-WSN scenarios to examine scalability, and one scenario to assess the performance implications in a pseudo-dynamic SD-WSN. Extensive simulation results are presented regarding the control overhead introduced, the percentage of alive nodes and remaining energy, and the impacts on network lifetime. We show that the accumulated control overhead is inversely proportional to the interaction period with the controller, whereas the remaining energy and the network lifetime are directly proportional to this parameter. Results show that the control overhead, for static SD-WSNs, can take up to 10%–29% of the total data flowing to the controller for the large SD-WSN and 6–19% for the small SD-WSN. For a pseudo-dynamic network, the control overhead can take up to two-thirds of the total data sent to the controller, and the network lifetime was reduced by up to 80% compared with the static scenarios.

Software-defined networking (SDN) offers potential pathways to overcome the management complexity of the Internet of Things (IoT). Previous studies have often been limited to software simulations or general proposals only. In this article, we design and evaluate an SDN-based management system for wireless sensor networks (WSNs) using IPv6 over low-power wireless personal area networks (6LoWPAN). The framework is described in detail covering different data-, control-, and application-plane implementations, and includes a novel addressing scheme and packet format. It also uses a centralized routing protocol, located at the SDN controller, based on the shortest path algorithm. We compare our approach with the routing protocol for low-power and lossy networks (RPL), which uses a distributed routing protocol. Hardware tests were carried out in a dynamic environment, with multiple sources of interference for different payload sizes to evaluate the impacts and practicality of SDN in WSNs. The performance comparison shows that the proposed SDN management system for IP-enabled WSNs using a centralized routing protocol outperforms the RPL protocol in terms of round-trip time, jitter, memory consumption, and packet loss rate (PLR), despite the control overhead introduced.

The software defined networking framework facilitates flexible and reliable internet of things networks by moving the network intelligence to a centralized location while enabling low power wireless network in the edge. In this paper, we present SD-WSN6Lo, a novel software-defined wireless management solution for 6LoWPAN networks that aims to reduce the management complexity in WSN's. As an example of the technique, a simulation of controlling the power consumption of sensor nodes is presented. The results demonstrate improved energy consumption of approximately 15% on average per node compared to the baseline condition.

In this paper, we propose an energy-aware routing algorithm and a control overhead reduction technique for prolonging the network lifetime of software-defined multihop wireless sensor networks (SDWSNs). This is an effort to optimize the energy consumption of WSNs that provide services to the Industrial Internet of Things (IIoT). A centralized controller grants a global view of the sensor network by introducing extra control overhead in the network, but this leads to extra energy costs. However, our new algorithm takes advantage of this global view and balances the network energy by selecting paths with the highest remaining energy level among multiple paths for each sensor node. We also identify key functions draining energy from the SDWSN and minimize their impact by implementing a data packet aggregation function, and minimizing the control overhead by keeping track of the sensor nodes’ routing tables using a simple checksum function. We show that the proposed approach prolongs the network lifetime of the WSN by 6.5% on average compared to the standard shortest-path algorithm, and that the control overhead is reduced by approximately 12% while still maintaining a very high packet delivery ratio.

Frequency dependent dielectric properties are important for understanding the structure and dynamics of biological materials. These properties can be used to study underlying biological processes such as changes in the concentration of biological materials, and the formation of chemical species. Computer simulations can be used to determine dielectric properties and atomic details inaccessible via experimental methods. In this paper, a unified theory utilizing molecular dynamics and density functional theory is presented that is able to determine the frequency dependent dielectric properties of biological materials in an aqueous solution from their molecular structure alone. The proposed method, which uses reaction field approximations, does not require a prior knowledge of the static dielectric constant of the material. The dielectric properties obtained from our method agree well with experimental values presented in the literature.

Mycoplasma synoviae strain MS-H, developed by chemical mutagenesis of the Australian field strain 86079/7NS, is a live temperature-sensitive (ts (+)) vaccine used for control of M. synoviae infection in poultry worldwide. Genetic basis of temperature sensitivity and attenuation of MS-H has not been revealed thus far. Comparison of the complete genome sequence of MS-H, its parent strain 86079/7NS and two non-temperature sensitive (ts (-)) reisolates of MS-H revealed a mutation in a highly conserved domain of GTP binding protein Obg of MS-H, with reversion in ts (-) MS-H reisolates. Nucleotide change from G to A at position 369 of the obg gene resulted in an alteration of glycine to arginine at position 123 in Obg fold. Further analysis of the complete obg gene sequence in several MS-H reisolates revealed that a Gly123Arg substitution was associated with alteration in temperature sensitivity phenotype of MS-H. A second mutation, C to T at position 629, in obg gene was found in some of the MS-H reisolates and appeared to suppress the effects of the Gly123Arg substitution. In silico analysis of point mutations revealed that Gly123Arg has highly destabilizing effect on the MS-H Obg structure that can potentially abolish its biological functions in vivo especially at non-permissive temperature. Findings of this study implicate Obg alteration (Gly123Arg) as one of the possible causes of MS-H attenuation/temperature sensitivity and warrant further investigations into exploring the role of Obg-like proteins, an evolutionarily conserved protein from human to bacteria, in the biology of mycoplasmas.

Autism spectrum disorder (ASD) depends on a clinical interview with no biomarkers to aid diagnosis. The current investigation interrogated single-nucleotide polymorphisms (SNPs) of individuals with ASD from the Autism Genetic Resource Exchange (AGRE) database. SNPs were mapped to Kyoto Encyclopedia of Genes and Genomes (KEGG)-derived pathways to identify affected cellular processes and develop a diagnostic test. This test was then applied to two independent samples from the Simons Foundation Autism Research Initiative (SFARI) and Wellcome Trust 1958 normal birth cohort (WTBC) for validation. Using AGRE SNP data from a Central European (CEU) cohort, we created a genetic diagnostic classifier consisting of 237 SNPs in 146 genes that correctly predicted ASD diagnosis in 85.6% of CEU cases. This classifier also predicted 84.3% of cases in an ethnically related Tuscan cohort; however, prediction was less accurate (56.4%) in a genetically dissimilar Han Chinese cohort (HAN). Eight SNPs in three genes (KCNMB4, GNAO1, GRM5) had the largest effect in the classifier with some acting as vulnerability SNPs, whereas others were protective. Prediction accuracy diminished as the number of SNPs analyzed in the model was decreased. Our diagnostic classifier correctly predicted ASD diagnosis with an accuracy of 71.7% in CEU individuals from the SFARI (ASD) and WTBC (controls) validation data sets. In conclusion, we have developed an accurate diagnostic test for a genetically homogeneous group to aid in early detection of ASD. While SNPs differ across ethnic groups, our pathway approach identified cellular processes common to ASD across ethnicities. Our results have wide implications for detection, intervention and prevention of ASD.

In contrast to the RNA viruses, the genome of large DNA viruses such as herpesviruses have been considered to be relatively stable. Intra-specific recombination has been proposed as an important, but underestimated, driving force in herpesvirus evolution. Recently, two distinct field strains of infectious laryngotracheitis virus (ILTV) have been shown to have arisen from independent recombination events between different commercial ILTV vaccines. In this study we sequenced the genomes of additional ILTV strains and also utilized other recently updated complete genome sequences of ILTV to confirm the existence of a number of ILTV recombinants in nature. Multiple recombination events were detected in the unique long and repeat regions of the genome, but not in the unique short region. Most recombinants contained a pair of crossover points between two distinct lineages of ILTV, corresponding to the European origin and the Australian origin vaccine strains of ILTV. These results suggest that there are two distinct genotypic lineages of ILTV and that these commonly recombine in the field.