Synthesis,characterization, and voltammetric hydrogen peroxide sensing on novel monometallic (Ag,Co/MWCNT) and bimetallic (AgCo/MWCNT) alloy nanoparticles

Multiwall carbon nanotube supported (MWCNT) Ag, Co, and Ag-Co alloy nanocatalysts were synthesized at varying metal loadings by borohydride reduction methods without stabilizers to obtain enhanced hydrogen peroxide sensitivity. The resulting materials were characterized employing Scanning electron microscopy (SEM), Energy dispersive X-ray spectroscopy (EDX), and X-ray diffraction (XRD). For electrochemical measurements carried out cyclic voltammetry (CV) and differential pulse voltammetry (DPV), glassy carbon electrode (GCE) was modified with Ag/MWCNT, Co/MWCNT, and Ag-Co/MWCNT alloy nanoparticles. Ag-Co/MWCNT/GCE exhibited the highest performance toward electrochemical oxidation of H₂O₂ in 0.1 M phosphate buffered solution (PBS). Furthermore, the sensitivity and the limit of detection values for Ag-Co/MWCNT/GCE were obtained as 57.14 µA cm^?2 mM^?1and 0.74 µM, respectively. However, the sensitivity values for Ag/MWCNT/GCE, and Co/MWCNT/GCE are 41.66 and 13.88 µA cm^?2 mM^?1, respectively. The LOD values were predicted as 1.84 µM for Ag/MWCNT/GCE and 3.3 µM for Co/MWCNT/GCE.

In addition, the interference experiment indicated that the Ag-Co/MWCNT alloy nanoparticles have good selectivity toward H₂O₂.     

Intelligent DoS Attack Detection with Congestion Control Technique for VANETs

Vehicular Ad hoc Network (VANET) has become an integral part of Intelligent Transportation Systems (ITS) in today's life. VANET is a network that can be heavily scaled up with a number of vehicles and road side units that keep fluctuating in real world. VANET is susceptible to security issues, particularly DoS attacks, owing to maximum unpredictability in location. So, effective identification and the classification of attacks have become the major requirements for secure data transmission in VANET. At the same time, congestion control is also one of the key research problems in VANET which aims at minimizing the time expended on roads and calculating travel time as well as waiting time at intersections, for a traveler. With this motivation, the current research paper presents an intelligent DoS attack detection with Congestion Control (IDoS-CC) technique for VANET. The presented IDoS-CC technique involves two-stage processes namely, Teaching and Learning Based Optimization (TLBO)-based Congestion Control (TLBO-CC) and Gated Recurrent Unit (GRU)-based DoS detection (GRU-DoSD). The goal of IDoS-CC technique is to reduce the level of congestion and detect the attacks that exist in the network. TLBO algorithm is also involved in IDoS-CC technique for optimization of the routes taken by vehicles via traffic signals and to minimize the congestion on a particular route instantaneously so as to assure minimal fuel utilization. TLBO is applied to avoid congestion on roadways. Besides, GRU-DoSD model is employed as a classification model to effectively discriminate the compromised and genuine vehicles in the network. The outcomes from a series of simulation analyses highlight the supremacy of the proposed IDoS-CC technique as it reduced the congestion and successfully identified the DoS attacks in network.     

Compact Bat Algorithm with Deep Learning Model for Biomedical EEG EyeState Classification

Electroencephalography (EEG) eye state classification becomes an essential tool to identify the cognitive state of humans. It can be used in several fields such as motor imagery recognition, drug effect detection, emotion categorization, seizure detection, etc. With the latest advances in deep learning (DL) models, it is possible to design an accurate and prompt EEG EyeState classification problem. In this view, this study presents a novel compact bat algorithm with deep learning model for biomedical EEG EyeState classification (CBADL-BEESC) model. The major intention of the CBADL-BEESC technique aims to categorize the presence of EEG EyeState. The CBADL-BEESC model performs feature extraction using the ALexNet model which helps to produce useful feature vectors. In addition, extreme learning machine autoencoder (ELM-AE) model is applied to classify the EEG signals and the parameter tuning of the ELM-AE model is performed using CBA. The experimental result analysis of the CBADL-BEESC model is carried out on benchmark results and the comparative outcome reported the supremacy of the CBADL-BEESC model over the recent methods.     

Synthesis of β-myrcene-based macroporous nanocomposite foams: Altering the morphological and mechanical properties by using organo-modified nanoclay

Organo-modified nanoclay incorporated high internal phase emulsions (HIPEs) were successfully used for the preparation of macroporous nanocomposite foams. Due to the aim of obtaining mechanically improved foams, HIPEs were prepared by using a monomer mixture composed of β-myrcene and ethylene glycol dimethacrylate. Accordingly, two groups of macroporous nanocomposite foams were synthesized depending on the nanoclay type. The morphological analysis demonstrated that the pore openness of the resulting nanocomposites were significantly improved due to the decrease in the average cavity size and increase in the interconnected pore size. In terms of mechanical properties, it was found that filling 1 wt% of nanoclay which is surface modified by hydrogenated tallow lead to a 33% of increment in the compression modulus, as compared to the neat foam. However, loading 5 wt% of nanoclay having octadecylamine and aminopropyltriethoxysilane surface groups caused only 11% of increment in the compression modulus, as compared to the neat foam.     

Electrochemical,Structural and Magnetic Analysis of Electrodeposited CoCu/Cu Multilayers: Influence of Cu Layer Deposition Potential

The electrochemical, structural and magnetic properties of CoCu/Cu multilayers electrodeposited at different cathode potentials were investigated from a single bath. The Cu layer deposition potentials were selected as \(-\,0.3,\,\hbox {V}\) \(-\,0.4\,\,\hbox {V}\), and \(-\,0.5\,\hbox {V}\) with respect to saturated calomel electrode (SCE) while the Co layer deposition potential was constant at \(-\,1.5\,\hbox {V}\) versus SCE. For the electrochemical analysis, the current-time transients were obtained. The amount of noble non-magnetic (Cu) metal materials decreased with the increase of deposition potentials due to anomalous codeposition. Further, current-time transient curves for the Co layer deposition and capacitance were calculated. In the structural analysis, the multilayers were found to be polycrystalline with both Co and Cu layers adopting the face-centered cubic structure. The (111) peak shifts towards higher angle with the increase of the deposition potentials. Also, the lattice parameters of the multilayers decrease from 0.3669 nm to 0.3610 nm with the increase of the deposition potentials from \(-\,0.3\,\hbox {V}\) to \(-\,0.5\,\hbox {V}\), which corresponds to the bulk values of Cu and Co, respectively. The electrochemical and structural results demonstrate that the amount of Co atoms increased and the Cu atoms decreased in the layers with the increase of deposition potentials due to anomalous codeposition. For magnetic measurements, the saturation magnetizations, \(M_s\) obtained from the magnetic curves of the multilayers were obtained as 212 kA/m, 276 kA/m, and 366 kA/m with \(-\,0.3\,\hbox {V}\), \(-\,0.4\,\hbox {V}\), and \(-\,0.5\,\hbox {V}\) versus SCE, respectively. It is seen that the \(M_s\) values increased with the increase of the deposition potentials confirming the increase of the Co atoms and decrease of the Cu amount. The results of electrochemical and structural analysis show that the deposition potentials of non-magnetic layers plays important role on the amount of magnetic and non-magnetic materials in the layers and thus on the magnetic properties of the multilayers.     

Optimal Water Allocation from Subsurface Dams: A Risk-Based Optimization Approach

Subsurface dams, strongly advocated in the 1992 United Nations Agenda-21, have been widely studied to increase groundwater storage capacity. However, an optimal allocation of augmented water with the construction of the subsurface dams to compensate for the water shortage during dry periods has not so far been investigated. This study, therefore, presents a risk-based simulation–optimization framework to determine optimal water allocation with subsurface dams, which minimizes the risk of water shortage in different climatic conditions. The developed framework was evaluated in Al-Aswad falaj, an ancient water supply system in which a gently sloping underground channel was dug to convey water from an aquifer via the gravity force to the surface for irrigation of downstream agricultural zones. The groundwater dynamics were modeled using MODFLOW UnStructured-Grid. The data of boreholes were used to generate a three-dimensional stratigraphic model, which was used to define materials and elevations of five-layer grid cells. The validated groundwater model was employed to assess the effects of the subsurface dam on the discharge of the falaj. A Conditional Value-at-Risk optimization model was also developed to minimize the risk of water shortage for the augmented discharge on downstream agricultural zones. Results show that discharge of the falaj is significantly augmented with a long-term average increase of 46.51%. Moreover, it was found that the developed framework decreases the water shortage percentage in 5% of the worst cases from 87%, 75%, and 32% to 53%, 32%, and 0% under the current and augmented discharge in dry, normal, and wet periods, respectively.

     

Role of pulses to modulate the nutritive,bioactive and technological functionality of cereal-based extruded snacks: a review

Pulses hold excellent nutritive potential owing to high-quality protein content, dietary fibre, minerals, vitamins, oligosaccharides, polyphenols, tannins, phytosterols and several other bioactive constituents. These bio-functional compounds impart significant health benefits by reducing the risk of several chronic complications such as hypertension, cancers, cardiovascular diseases and neurological concerns mainly through anti-oxidative and radical scavenging mechanisms. These high protein ingredients when added to cereal-based extruded snacks not only enhance the nutritive and bioactive profile of the resultant snacks but also modulate the techno-functional attributes of the extrudates. Protein interactions with cereal-based starch and other constituents result in structural variation at the macromolecular level consequently varying the physical, mechanical and techno-functional properties including expansion ratio, bulk density, hydration properties, pasting characteristics and texture. The present review aimed at elaborating the nutritive and bio-functional potential of pulses enriched cereal-based expanded snacks. Further, significant emphasis has been given to the impact of pulse flour incorporation on functional, structural and mechanical properties of the cereal-based extrudates.     

An Optimized Algorithm for CR-MIMO Wireless Networks

With the rapid development of wireless communication technology, the spectrum resources are increasingly strained which needs optimal solutions. Cognitive radio (CR) is one of the key technologies to solve this problem. Spectrum sensing not only includes the precise detection of the communication signal of the primary user (PU), but also the precise identification of its modulation type, which can then determine the a priori information such as the PU’ service category, so as to use this information to make the cognitive user (CU) aware to discover and use the idle spectrum more effectively, and improve the spectrum utilization. Spectrum sensing is the primary feature and core part of CR. Classical sensing algorithms includes energy detection, cyclostationary feature detection, matched filter detection, and so on. The energy detection algorithm has a simple structure and does not require prior knowledge of the PU transmitter signal, but it is easily affected by noise and the threshold is not easy to determine. The combination of multiple-input multiple-output (MIMO) with CR improves the spectral efficiency and multi-path fading utilization. To best utilize the PU spectrum while minimizing the overall transmit power, an iterative technique based on semidefinite programming (SDP) and minimum mean squared error (MMSE) is proposed. Also, this article proposed a new method for max-min fairness beamforming. When compared to existing algorithms, the simulation results show that the proposed algorithms perform better in terms of total transmitted power and signal-to-interference plus noise ratio (SINR). Furthermore, the proposed algorithm effectively improved the system performance in terms of number of iterations, interference temperature threshold and balance SINR level which makes it superior over the conventional schemes.     

Characterization of molecular markers indicative of cervical cancer progression

Cervical cancer originates with human papillomavirus (HPV) infection and progresses via histologically defined premalignant stages. Here we compare normal cervical epithelium and patient‐matched high‐grade squamous intraepithelial lesions (HSIL) with cervical carcinoma tissue from the same patient population (n = 10 per group). Specimens were analyzed by combined laser capture microdissection and 2‐D DIGE. Significant expression changes were seen with 53 spots resulting in identification of 23 unique proteins at the molecular level. These include eight that uniquely distinguish normal epithelium and HSIL and four that uniquely distinguish HSIL and carcinoma. In addition, one protein, cornulin, distinguishes all three states. Other identified proteins included differentiation markers, oncogene DJ‐1, serpins, stress and interferon‐responsive proteins, detoxifying enzymes, and serum transporters. A literature review, performed for all identified proteins, allowed most changes to be assigned to one of three causes: direct or indirect HPV oncoprotein interactions, growth selection during latency, or interactions in the lesion microenvironment. Selected findings were confirmed by immunohistochemistry using either frozen sections from the same cohort or formalin fixed paraffin embedded samples from a tissue microarray. Novel markers described here have potential applications for increasing the predictive value of current screening methods.