A Trust-Based Group Key Management Protocol for Non-Networks

In this paper, a secure and trust-based group key management protocol (GKMP) is presented for non-networks such as MANET/VANET. The scheme provides secure communication for group members in a dynamic network environment and does not restrict the users (registered or non-registered), allowing for flexible group communication. The proposed scheme is designed to address the challenges of key distribution, secure grouping, and secure communication. For result evaluation, first of all formal and informal security analysis was done and then compared with existing protocols. The proposed trust-based GKMP protocol satisfies the authentication, confidentiality of messages, forward/backward security concurrently as well as shows robustness in terms of packet delivery ratio and throughput

Strong exciton-localized plasmon coupling in a-Ge24Se76/AuNP heterostructure

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A panel of blood-based circulatory miRNAs with diagnostic potential in patients with psoriasis

Psoriasis is a chronic inflammatory skin disease with keratinocyte hyperproliferation and T cells as key mediators of lesional and systemic inflammatory changes. To date, no suitable differential biomarkers are available for the disease diagnosis. More recently, microRNAs have been identified as critical regulators of lesional and systemic immune changes in psoriasis with diagnostic potential. We have performed expression profiling of T cell-specific miRNAs in 38 plasma samples from psoriasis vulgaris patients and an equal number of age- and gender-matched healthy subjects. Our findings have identified a panel of five blood-based circulatory miRNAs with a significant change in their expression levels, comprising miR-215, miR-148a, miR-125b-5p, miR-223, and miR-142-3p, which can differentiate psoriasis vulgaris patients from healthy individuals. The receiver operating characteristic (ROC) curves for all five miRNAs individually and in combination exhibited a significant disease discriminatory area under the curve with an AUC of 0.762 and a p < 0.0001 for all the miRNAs together. Statistically, all five miRNAs in combination depicted the best-fit model in relation to disease severity (PASI) compared with individual miRNAs, with the highest R2 value of 0.94 and the lowest AIC score of 131.8. Each of the miRNAs also exhibited a significant association with at least one of the other miRNAs in the panel. Importantly, the five miRNAs in the panel regulate one or more immune-inflammation pathways based on target prediction, pathway network analysis, and validated roles in the literature. The miRNA panel provides a rationalized combination of biomarkers that can be tested further on an expanded cohort of patients for their diagnostic value

Optimization of energy consumption in smart homes using firefly algorithm and deep neural networks

Electronic gadget advancements have increased the demand for IoT-based smart homes as the number of connected devices grows rapidly. The most prevalent connected electronic devices are smart environments in houses, grids, structures, and metropolises. Smart grid technology advancements have enabled smart structures to cover every nanosecond of energy use. The problem with smart, intelligent operations is that they use a lot more energy than traditional ones. Because of the growing growth of smart cities and houses, there is an increasing demand for efficient resource management. Energy is a valuable resource with a high unit cost. Consequently, authors are endeavoring to decrease energy usage, specifically in smart urban areas, while simultaneously ensuring a consistent terrain. The objective of this study is to enhance energy efficiency in intelligent buildings for both homes and businesses. For the comfort indicator ("thermal, visual, and air quality"), three parameters are used: temperature, illumination, and CO2. A hybrid rule-based Deep Neural Network (DNN) and Fire Fly (FF) algorithm are used to read the sensor parameters and to operate the comfort indication, as well as optimize energy consumption, respectively. The anticipated user attributes contributed to the system's enhanced performance in terms of the ease of use of the smart system and its energy usage. When compared to traditional approaches in expressions of Multi View with 98.23%, convolutional neural network (CNN) with 99.17%, and traffic automatic vehicle (AV) with 98.14%, the activities of the contributed approach are negligibly commanding

A Critical Study on Group Key Management Protocols and Security Aspects For Non-Networks

The rise in internet usage and advanced communication systems has led to an increase in security issues. The need for more robust and flexible secure communication has led to the introduction of mobile non-network multicast communication systems like MANET or VANET. Multicasting is increasingly being used for group-oriented applications such as video conferencing, interactive games, TV over Internet, e-learning, etc. To address the security concerns, this paper highlighted the confidentiality, authentication, and access control for non-network multicast communication systems like MANET or VANET.  For this, paper explores the group key management protocols. The paper concluded that centralized and asymmetric group key management protocol (GKMP) is most effective for designing secure, and efficient communication models for non-networks. The key findings of the paper are that in group key management protocols (GKMPs) for multicast communication systems adoption of asymmetric GKMPs provides better security, and reduces computational overhead. Therefore, this paper help to improve the robustness and security of multicast communication systems and meet the growing demands of group-oriented applications over the internet

Zn2+ dependent glyoxalase I plays the major role in methylglyoxal detoxification and salinity stress tolerance in plants.

Glyoxalase pathway is the major pathway of methylglyoxal detoxification and is ubiquitously present in all organisms ranging from prokaryotes to eukaryotes. Glyoxalase I (GLYI) and Glyoxalase II (GLYII), the two core enzymes of this pathway work together to neutralize methylglyoxal (MG), a dicarbonyl molecule with detrimental cytotoxicity at higher concentrations. The first step towards the detoxification of MG is catalyzed by GLYI, a metalloenzyme that requires divalent metal ions (either Zn2+ as seen in eukaryotes or Ni2+ as in prokaryotes). However, both Zn2+ and Ni2+ dependent GLYIs have been shown to co-exist in a higher eukaryote i.e. Arabidopsis thaliana. In the present study, we determine the role of both Zn2+ dependent (AtGLYI2) and Ni2+ dependent (AtGLYI3, AtGLYI6) GLYIs from Arabidopsis in salinity stress tolerance. AtGLYI2 overexpressing Arabidopsis plants showed better growth rate while maintaining lower levels of MG under high saline conditions. They were taller with more number of silique formation with respect to their Ni2+ dependent counterparts. Further, lack in germination of Arabidopsis AtGLYI2 mutants in presence of exogenous MG indicates the direct involvement of Zn2+ dependent GLYI in MG detoxification, suggesting Zn2+ dependent GLYI as the main enzyme responsible for MG detoxification and salinity stress tolerance

Kinetic parameters of purified AtGLYI proteins.

<p>(A) Upper panel shows graphs depicting effect of change in pH on the activity of (i) AtGLYI2, (ii) AtGLYI3 and (iii) AtGLYI6 proteins. A range of pH conditions analyzed and the corresponding absorbance indicative of protein activity is shown on X-axis and Y-axis, respectively. All the three proteins were purified using Ni-NTA affinity chromatography. The activity of purified proteins was checked over a wide range of pH in different buffers (pH 5.5–6.75: MES buffer, pH 6.5–8.0: MOPS buffer, pH 7.40–9.0: tris buffer). The optimal pH for AtGLYI2 is 7.0; AtGLYI3 is 7.5 and AtGLYI6 is 7.5. (B) Lower panel shows graphs depicting kinetic parameters for (i) AtGLYI2, (ii) AtGLYI3 and (iii) AtGLYI6. These parameters were calculated using Lineweaver Burk’s plot. GLYI assay was performed with purified proteins with varying concentration of GSH and increase in absorbance (240 nm) with time was monitored. From the data obtained, Lineweaver Burk’s plot was made and various kinetic parameters were calculated.</p

Comparison of the specific activity of the GLYI proteins of Arabidopsis with GLYI proteins from other plant species.

<p>Comparison of the specific activity of the GLYI proteins of Arabidopsis with GLYI proteins from other plant species.</p

Stress tolerance assay of <i>E</i>. <i>coli</i> expressing <i>AtGLYI</i> genes.

<p>The <i>E</i>. <i>coli</i> cells transformed with <i>AtGLYI2</i> (shown in red color), <i>AtGLYI3</i> (shown in green color) and <i>AtGLYI6</i> (shown in purple color) genes were grown in presence of (A) salinity stress (200 mM NaCl), (B) oxidative stress (5 mM H₂O₂), (C) Cytotoxic methylglyoxal stress (0.5 mM), (D) Cytotoxic methylglyoxal stress (1 mM), (E) Osmotic stress (100 mM mannitol), (F) Heat stress (42°C) and the growth was monitored over time. Cells containing empty vector construct (pET28a without any gene) were used as control (shown in blue color).</p