The Pharmacology and Therapeutic Utility of Sodium Hydroselenide

Metabolically active gasotransmitters (nitric oxide, carbon monoxide and hydrogen sulfide) are important signalling molecules that show therapeutic utility in oxidative pathologies. The reduced form of selenium, hydrogen selenide (HSe⁻/H₂Se), shares some characteristics with these molecules. The simple selenide salt, sodium hydroselenide (NaHSe) showed significant metabolic activity, dose-dependently decreasing ex vivo O₂ consumption (rat soleus muscle, liver) and transiently inhibiting mitochondrial cytochrome C oxidase (liver, heart). Pharmacological manipulation of selenoprotein expression in HepG2 human hepatocytes revealed that the oxidation status of selenium impacts on protein expression; reduced selenide (NaHSe) increased, whereas (oxidized) sodium selenite decreased the abundance of two ubiquitous selenoproteins. An inhibitor of endogenous sulfide production (DL-propargylglycine; PAG) also reduced selenoprotein expression; this was reversed by exogenous NaHSe, but not sodium hydrosulfide (NaHS). NaHSe also conferred cytoprotection against an oxidative challenge (H₂O₂), and this was associated with an increase in mitochondrial membrane potential. Anesthetized Wistar rats receiving intravenous NaHSe exhibited significant bradycardia, metabolic acidosis and hyperlactataemia. In summary, NaHSe modulates metabolism by inhibition of cytochrome C oxidase. Modification of selenoprotein expression revealed the importance of oxidation status of selenium therapies, with implications for current clinical practice. The utility of NaHSe as a research tool and putative therapeutic is discussed.     

Structural Basis for The Recognition of Deaminated Nucleobases by An Archaeal DNA Polymerase

With increasing temperature, nucleobases in DNA become increasingly damaged by hydrolysis of exocyclic amines. The most prominent damage includes the conversion of cytosine to uracil and adenine to hypoxanthine. These damages are mutagenic and put the integrity of the genome at risk if not repaired appropriately. Several archaea live at elevated temperatures and thus, are exposed to a higher risk of deamination. Earlier studies have shown that DNA polymerases of archaea have the property of sensing deaminated nucleobases in the DNA template and thereby stalling the DNA synthesis during DNA replication providing another layer of DNA damage recognition and repair. However, the structural basis of uracil and hypoxanthine sensing by archaeal B-family DNA polymerases is sparse. Here we report on three new crystal structures of the archaeal B-family DNA polymerase from Thermococcus kodakarensis (KOD) DNA polymerase in complex with primer and template strands that have extended single stranded DNA template 5’-overhangs. These overhangs contain either the canonical nucleobases as well as uracil or hypoxanthine, respectively, and provide unprecedented structural insights into their recognition by archaeal B-family DNA polymerases.     

Synchronous receiver initiated MAC protocol for long-lived sensor networks

In this paper, we discuss the design of a new Medium Access Control (MAC) protocol, SRI-MAC (Synchronous Receiver Initiated MAC), for wireless sensor networks whose goal is to extend the lifetime of the network by avoiding major energy waste causes, such as collisions, overhearing and idle listening.     

Analysis of impersonation attacks on systems using RF fingerprinting and low-end receivers

Recently, physical layer security commonly known as Radio Frequency (RF) fingerprinting has been proposed to provide an additional layer of security for wireless devices. A unique RF fingerprint can be used to establish the identity of a specific wireless device in order to prevent masquerading/impersonation attacks. In the literature, the performance of RF fingerprinting techniques is typically assessed using high-end (expensive) receiver hardware. However, in most practical situations receivers will not be high-end and will suffer from device specific impairments which affect the RF fingerprinting process. This paper evaluates the accuracy of RF fingerprinting employing low-end receivers. The vulnerability to an impersonation attack is assessed for a modulation-based RF fingerprinting system employing low-end commodity hardware (by legitimate and malicious users alike). Our results suggest that receiver impairment effectively decreases the success rate of impersonation attack on RF fingerprinting. In addition, the success rate of impersonation attack is receiver dependent.     

A secure and improved multi server authentication protocol using fuzzy commitment

Multimedia Tools and Applications - The advancement in communication and computation technologies has paved a way for connecting large number of heterogeneous devices to offer specified services....     

Interactive Evolutionary Multi-Objective Optimization Algorithm Using Cone Dominance

As the number of objectives increases, the performance of the Pareto dominance-based Evolutionary Multi-objective Optimization (EMO) algorithms such as NSGA-II, SPEA2 severely deteriorates due to the drastic increase in the Pareto-incomparable solutions. We propose a sorting method which classifies these incomparable solutions into several ordered classes by using the decision maker's (DM) preference information. This is accomplished by designing an interactive evolutionary algorithm and constructing convex cones. This method allows the DMs to drive the search process toward a preferred region of the Pareto optimal front. The performance of the proposed algorithm is assessed for two, three, and four-objective knapsack problems. The results demonstrate the algorithm's ability to converge to the most preferred point. The evaluation and comparison of the results indicate that the proposed approach gives better solutions than that of NSGA-II. In addition, the approach is more efficient compared to NSGA-II in terms of the number of generations required to reach the preferred point.     

Home Automation Using Augmented Reality (HAAR)

Wireless Personal Communications - The development of Smart Home Controllers has seen rapid growth in recent years, especially for smart devices, that can utilize the Internet of Things (IoT)....     

In situ trapped high-density single metal atoms within graphene: Iron-containing hybrids as representatives for efficient oxygen reduction

Nano Research - Atomically dispersed catalysts have attracted attention in energy conversion applications because their efficiency and chemoselectivity for special catalysis are superior to those...     

A Framework of Deep Optimal Features Selection for Apple Leaf Diseases Recognition

Identifying fruit disease manually is time-consuming, expert-required, and expensive; thus, a computer-based automated system is widely required. Fruit diseases affect not only the quality but also the quantity. As a result, it is possible to detect the disease early on and cure the fruits using computer-based techniques. However, computer-based methods face several challenges, including low contrast, a lack of dataset for training a model, and inappropriate feature extraction for final classification. In this paper, we proposed an automated framework for detecting apple fruit leaf diseases using CNN and a hybrid optimization algorithm. Data augmentation is performed initially to balance the selected apple dataset. After that, two pre-trained deep models are fine-tuning and trained using transfer learning. Then, a fusion technique is proposed named Parallel Correlation Threshold (PCT). The fused feature vector is optimized in the next step using a hybrid optimization algorithm. The selected features are finally classified using machine learning algorithms. Four different experiments have been carried out on the augmented Plant Village dataset and yielded the best accuracy of 99.8%. The accuracy of the proposed framework is also compared to that of several neural nets, and it outperforms them all.