Quality of Service Provisioning for Heterogeneous Services in Cognitive Radio-enabled Internet of Things

IEEE The Internet of Things (IoT) is a network of interconnected objects, in which every object in the world seeks to communicate and exchange information actively. This exponential growth of interconnected objects increases the demand for wireless spectrum. However, providing wireless channel access to every communicating object while ensuring its guaranteed quality of service (QoS) requirements is challenging and has not yet been explored, especially for IoT-enabled mission-critical applications and services. Meanwhile, Cognitive Radio-enabled Internet of Things (CR-IoT) is an emerging field that is considered the future of IoT. The combination of CR technology and IoT can better handle the increasing demands of various applications such as manufacturing, logistics, retail, environment, public safety, healthcare, food, and drugs. However, due to the limited and dynamic resource availability, CR-IoT cannot accommodate all types of users. In this paper, we first examine the availability of a licensed channel on the basis of its primary users' activities (e.g., traffic patterns). Second, we propose a priority-based secondary user (SU) call admission and channel allocation scheme, which is further based on a priority-based dynamic channel reservation scheme. The objective of our study is to reduce the blocking probability of higher-priority SU calls while maintaining a sufficient level of channel utilization. The arrival rates of SU calls of all priority classes are estimated using a Markov chain model, and further channels for each priority class are reserved based on this analysis. We compare the performance of the proposed scheme with the greedy non-priority and fair proportion schemes in terms of the SU call-blocking probability, SU call-dropping probability, channel utilization, and throughput. Numerical results show that the proposed priority scheme outperforms the greedy non-priority and fair proportion schemes

Efficient and Secured Swarm Pattern Multi-UAV Communication

Unmanned Aerial Vehicle (UAV) or drone, is an evolving technology in today's market with an enormous number of applications. Mini UAVs are developed in order to compensate the performance constraints imposed by larger UAVs during emergency situations. Multiple mini autonomous UAVs require communication and coordination for ubiquitous coverage and relaying during deployment. Multi-UAV coordination or swarm optimization is required for reliable connectivity among UAVs, due to its high mobility and dynamic topology. In this paper, a Secured UAV (S-UAV) model is proposed which takes the location of the UAVs as inputs to form a Wireless Mesh Network (WMN) among multiple drones with the help of a centralized controller. After WMN formation, efficient communication takes place using A∗ search, an intelligent algorithm that finds the shortest communication path among UAVs. Further, the S-UAV model utilizes cryptographic techniques such as Advanced Encryption Standard (AES) and Blowfish to overcome the security attacks efficiently. Simulation results show that the S-UAV model offers higher throughput, reduced power consumption and guaranteed message transmission with reduced encryption and decryption time

Interference Mitigation Based on Radio Aware Channel Assignment for Wireless Mesh Networks

© 2018, Springer Science+Business Media, LLC, part of Springer Nature. An intricate network deployment for high demand users leads to simultaneous transmission in wireless mesh networks. Multiple radios are adapted to individual nodes for improving network performance and Quality of Service (QoS). However, whenever multiple radios are assigned to the same channel, co-located radio interference occurs, which poses a major drawback. This paper proposes a Radio aware Channel Assignment (Ra-CA) mechanism based on a direct graphical model for mitigation of interference in multi-radio multi-channel networks. Initially, the co-located radio interference is identified by classifying non-interfering links for simultaneous transmission in the network. Proposed channel assignment mechanism helps in allocating the minimal number of channels to the network that mitigate co-located radio interference. Performance analysis of the proposed Ra-CA strategy is carried out compared with other existing techniques, like Breadth First Search-Channel Assignment (BFS-CA) and Maximal Independent Set Channel Assignment (MaIS-CA), in multi-radio networks. Simulation results demonstrate that the proposed channel assignment scheme is more efficient compared to the existing ones, in terms of QoS parameters like, packet drop rate, packet delivery ratio, transmission delay and throughput

Metric for Measuring the Effectiveness of Clustering of DNA Microarray Expression

BACKGROUND: The recent advancement of microarray technology with lower noise and better affordability makes it possible to determine expression of several thousand genes simultaneously. The differentially expressed genes are filtered first and then clustered based on the expression profiles of the genes. A large number of clustering algorithms and distance measuring matrices are proposed in the literature. The popular ones among them include hierarchal clustering and k-means clustering. These algorithms have often used the Euclidian distance or Pearson correlation distance. The biologists or the practitioners are often confused as to which algorithm to use since there is no clear winner among algorithms or among distance measuring metrics. Several validation indices have been proposed in the literature and these are based directly or indirectly on distances; hence a method that uses any of these indices does not relate to any biological features such as biological processes or molecular functions. RESULTS: In this paper we have proposed a metric to measure the effectiveness of clustering algorithms of genes by computing inter-cluster cohesiveness and as well as the intra-cluster separation with respect to biological features such as biological processes or molecular functions. We have applied this metric to the clusters on the data set that we have created as part of a larger study to determine the cancer suppressive mechanism of a class of chemicals called retinoids. We have considered hierarchal and k-means clustering with Euclidian and Pearson correlation distances. Our results show that genes of similar expression profiles are more likely to be closely related to biological processes than they are to molecular functions. The findings have been supported by many works in the area of gene clustering. CONCLUSION: The best clustering algorithm of genes must achieve cohesiveness within a cluster with respect to some biological features, and as well as maximum separation between clusters in terms of the distribution of genes of a behavioral group across clusters. We claim that our proposed metric is novel in this respect and that it provides a measure of both inter and intra cluster cohesiveness. Best of all, computation of the proposed metric is easy and it provides a single quantitative value, which makes comparison of different algorithms easier. The maximum cluster cohesiveness and the maximum intra-cluster separation are indicated by the metric when its value is 0. We have demonstrated the metric by applying it to a data set with gene behavioral groupings such as biological process and molecular functions. The metric can be easily extended to other features of a gene such as DNA binding sites and protein-protein interactions of the gene product, special features of the intron-exon structure, promoter characteristics, etc. The metric can also be used in other domains that use two different parametric spaces; one for clustering and the other one for measuring the effectiveness

Electron quantum metamaterials in van der Waals heterostructures

In recent decades, scientists have developed the means to engineer synthetic periodic arrays with feature sizes below the wavelength of light. When such features are appropriately structured, electromagnetic radiation can be manipulated in unusual ways, resulting in optical metamaterials whose function is directly controlled through nanoscale structure. Nature, too, has adopted such techniques -- for example in the unique coloring of butterfly wings -- to manipulate photons as they propagate through nanoscale periodic assemblies. In this Perspective, we highlight the intriguing potential of designer sub-electron wavelength (as well as wavelength-scale) structuring of electronic matter, which affords a new range of synthetic quantum metamaterials with unconventional responses. Driven by experimental developments in stacking atomically layered heterostructures -- e.g., mechanical pick-up/transfer assembly -- atomic scale registrations and structures can be readily tuned over distances smaller than characteristic electronic length-scales (such as electron wavelength, screening length, and electron mean free path). Yet electronic metamaterials promise far richer categories of behavior than those found in conventional optical metamaterial technologies. This is because unlike photons that scarcely interact with each other, electrons in subwavelength structured metamaterials are charged, and strongly interact. As a result, an enormous variety of emergent phenomena can be expected, and radically new classes of interacting quantum metamaterials designed

Population dynamics and identification of efficient strains of Azospirillum in maize ecosystems of Bihar (India)

Information on inoculum load and diversity of native microbial community is an important prerequisite for crop management of microbial origin. Azospirillum has a proven role in benefiting the maize (Zea mays) crop in terms of nutrient (nitrogen) supply as well as plant growth enhancement. Bihar state has highest average national maize productivity although fertilizer consumption is minimum, indicating richness of Azospirillum both in terms of population and diversity in soils. An experiment was planned to generate basic information on Azospirillum population variation in maize soils under different agricultural practices and soil types of Bihar, to identify suitable agricultural practices supporting the target microorganism and efficient Azospirillum strain(s). No tillage, growing traditional maize cultivar, land use history (diara soil having history of maize cultivation), soil organic carbon (>1%) and intercrop with oat supported prevalence of Azospirillum in maize rhizosphere. Native Azospirillum population varied from 1 million to 1 billion/g soil under diverse agricultural practices and soil types. Such richness, however, does not necessarily mean that artificial inoculation of Azospirillum is not required in Bihar soils as 92% of Azospirillum isolates (50 isolates) were poor in nitrogen-fixing ability and 88% were poor on IAA production. Efficient strains of Azospirillum based on growth (three), acetylene reduction assay (three), IAA production (three), broad range of pH (two) and temperature tolerance were identified. The findings suggested that maize crop in Bihar should be inoculated in universal mode rather than site-specific mode

Biomarker selection for detection of occult tumour cells in lymph nodes of colorectal cancer patients using real-time quantitative RT–PCR

Accurate identification of lymph node involvement is critical for successful treatment of patients with colorectal carcinoma (CRC). Real-time quantitative RT–PCR with a specific probe and RNA copy standard for biomarker mRNA has proven very powerful for detection of disseminated tumour cells. Which properties of biomarker mRNAs are important for identification of disseminated CRC cells? Seven biomarker candidates, CEA, CEACAM1-S/L, CEACAM6, CEACAM7-1/2, MUC2, MMP7 and CK20, were compared in a test-set of lymph nodes from 51 CRC patients (Dukes' A–D) and 10 controls. Normal colon epithelial cells, primary tumours, and different immune cells were also analysed. The biomarkers were ranked according to: (1) detection of haematoxylin/eosin positive nodes, (2) detection of Dukes' A and B patients, who developed metastases during a 54 months follow-up period and (3) identification of patients with Dukes' C and D tumours using the highest value of control nodes as cutoff. The following properties appear to be of importance; (a) no expression in immune cells, (b) relatively high and constant expression in tumour tissue irrespective of Dukes' stage and (c) no or weak downregulation in tumours compared to normal tissue. CEA fulfilled these criteria best, followed by CK20 and MUC2

Rising burden of Hepatitis C Virus in hemodialysis patients

<p>Abstract</p> <p>Aim</p> <p>High prevalence of Hepatitis C virus (HCV) has been reported among the dialysis patients throughout the world. No serious efforts were taken to investigate HCV in patients undergoing hemodialysis (HD) treatment who are at great increased risk to HCV. HCV genotypes are important in the study of epidemiology, pathogenesis and reaction to antiviral therapy. This study was performed to investigate the prevalence of active HCV infection, HCV genotypes and to assess risk factors associated with HCV genotype infection in HD patients of Khyber Pakhtunkhwa as well as comparing this prevalence data with past studies in Pakistan.</p> <p>Methods</p> <p>Polymerase chain reaction was performed for HCV RNA detection and genotyping in 384 HD patients. The data obtained was compared with available past studies from Pakistan.</p> <p>Results</p> <p>Anti HCV antibodies were observed in 112 (29.2%), of whom 90 (80.4%) were HCV RNA positive. In rest of the anti HCV negative patients, HCV RNA was detected in 16 (5.9%) patients. The dominant HCV genotypes in HCV infected HD patients were found to be 3a (n = 36), 3b (n = 20), 1a (n = 16), 2a (n = 10), 2b (n = 2), 1b (n = 4), 4a (n = 2), untypeable (n = 10) and mixed (n = 12) genotype.</p> <p>Conclusion</p> <p>This study suggesting that i) the prevalence of HCV does not differentiate between past and present infection and continued to be elevated ii) HD patients may be a risk for HCV due to the involvement of multiple routes of infections especially poor blood screening of transfused blood and low standard of dialysis procedures in Pakistan and iii) need to apply infection control practice.</p

STROCSS 2021: Strengthening the reporting of cohort, cross-sectional and case-control studies in surgery

Introduction: Strengthening The Reporting Of Cohort Studies in Surgery (STROCSS) guidelines were developed in 2017 in order to improve the reporting quality of observational studies in surgery and updated in 2019. In order to maintain relevance and continue upholding good reporting quality among observational studies in surgery, we aimed to update STROCSS 2019 guidelines. / Methods: A STROCSS 2021 steering group was formed to come up with proposals to update STROCSS 2019 guidelines. An expert panel of researchers assessed these proposals and judged whether they should become part of STROCSS 2021 guidelines or not, through a Delphi consensus exercise. / Results: 42 people (89%) completed the DELPHI survey and hence participated in the development of STROCSS 2021 guidelines. All items received a score between 7 and 9 by greater than 70% of the participants, indicating a high level of agreement among the DELPHI group members with the proposed changes to all the items. / Conclusion: We present updated STROCSS 2021 guidelines to ensure ongoing good reporting quality among observational studies in surgery