Hybrid Chameleon Search and Remora Optimization Algorithm-based Dynamic Heterogeneous load balancing clustering protocol for extending the lifetime of wireless sensor networks

Clustering is an indispensable strategy that helps towards the extension of lifetime of each sensor nodes with energy stability in wireless sensor networks (WSNs). This clustering process aids in sustaining energy efficiency and extended network lifetime in sensitive and critical real-life applications that include landslide monitoring and military applications. The dynamic characteristics of WSNs and several cluster configurations introduce challenge in the process of searching an ideal network structure, a herculean challenge. In this paper, Hybrid Chameleon Search and Remora Optimization Algorithm-based Dynamic Clustering Method (HCSROA) is proposed for dynamic optimization of wireless sensor node clusters. It utilized the global searching process of Chameleon Search Algorithm for selecting potential cluster head (CH) selection with balanced trade-off between intensification and extensification. It determines an ideal dynamic network structure based on factors that include quantity of nodes in the neighborhood, distance to sink, predictable energy utilization rate, and residual energy into account during the formulation of fitness function. It specifically achieved sink node mobility through the integration of the local searching capability of Improved Remora Optimization Algorithm for determining the optimal points of deployment over which the packets can be forwarded from the CH of the cluster to the sink node. This proposed HCSROA scheme compared in contrast to standard methods is identified to greatly prolong network lifetime by 29.21% and maintain energy stability by 25.64% in contrast to baseline protocols taken for investigation.     

Language independent unsupervised learning of short message service dialect

Noise in textual data such as those introduced by multilinguality, misspellings, abbreviations, deletions, phonetic spellings, non-standard transliteration, etc. pose considerable problems for text-mining. Such corruptions are very common in instant messenger and short message service data and they adversely affect off-the-shelf text mining methods. Most techniques address this problem by supervised methods by making use of hand labeled corrections. But they require human generated labels and corrections that are very expensive and time consuming to obtain because of multilinguality and complexity of the corruptions. While we do not champion unsupervised methods over supervised when quality of results is the singular concern, we demonstrate that unsupervised methods can provide cost effective results without the need for expensive human intervention that is necessary to generate a parallel labeled corpora. A generative model based unsupervised technique is presented that maps non-standard words to their corresponding conventional frequent form. A hidden Markov model (HMM) over a “subsequencized” representation of words is used, where a word is represented as a bag of weighted subsequences. The approximate maximum likelihood inference algorithm used is such that the training phase involves clustering over vectors and not the customary and expensive dynamic programming (Baum–Welch algorithm) over sequences that is necessary for HMMs. A principled transformation of maximum likelihood based “central clustering” cost function of Baum–Welch into a “pairwise similarity” based clustering is proposed. This transformation makes it possible to apply “subsequence kernel” based methods that model delete and insert corruptions well. The novelty of this approach lies in that the expensive (Baum–Welch) iterations required for HMM, can be avoided through an approximation of the loglikelihood function and by establishing a connection between the loglikelihood and a pairwise distance. Anecdotal evidence of efficacy is provided on public and proprietary data.     

Study on ozone bleaching of cotton fabric – process optimisation, dyeing and finishing properties

In this work the role played by the presence of moisture and pH during ozone bleaching of grey cotton fabric and the design features of the ozone application chamber are reported. The results are explained with the help of a simplified model. The dyeing and resin finishing properties of ozone-bleached fabric are compared with those of hydrogen peroxide-bleached fabric.     

Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

Nanostructured, molecularly imprinted, and template-patterned polythiophenes for chiral sensing and differentiation

An innovation to thin-film molecular imprinting is presented for the sensitive detection and effective discrimination of chiral compounds using a portable quartz crystal microbalance transduction technique. The facile approach involves i) colloidal sphere layering of latex particles onto the surface via a Langmuir-Blodgett-like technique followed by ii) template molecular imprinting using electrodeposition of a single functional and cross-linking monomer.     

Lanthanide Doped Near Infrared Active Upconversion Nanophosphors: Fundamental Concepts,Synthesis Strategies,and Technological Applications

Near infrared (NIR) light utilization in a range of current technologies has gained huge significance due to its abundance in nature and nondestructive properties. NIR active lanthanide (Ln) doped upconversion nanomaterials synthesized in controlled shape, size, and surface functionality can be combined with various pertinent materials for extensive applications in diverse fields. Upconversion nanophosphors (UCNP) possess unique abilities, such as deep tissue penetration, enhanced photostability, low toxicity, sharp emission peaks, long anti‐Stokes shift, etc., which have bestowed them with prodigious advantages over other conventional luminescent materials. As new generation fluorophores, UCNP have found a wide range of applications in various fields. In this Review, a comprehensive overview of lanthanide doped NIR active UCNP is provided by discussing the fundamental concepts including the different mechanisms proposed for explaining the upconversion processes, followed by the different strategies employed for the synthesis of these materials, and finally the technological applications of UCNP, mainly in the fields of bioimaging, drug delivery, sensing, and photocatalysis by highlighting the recent works in these areas. In addition, a brief note on the applications of UCNP in other fields is also provided along with the summary and future perspectives of these materials.     

Degradation of chlorpyrifos contaminated soil by bioslurry reactor operated in sequencing batch mode: bioprocess monitoring

Bioslurry reactor (SS-SBR) was studied for the degradation of chlorpyrifos contaminated soil using native mixed microflora, by adopting sequencing batch mode (anoxic-aerobic-anoxic) operation. Reactor operation was monitored for a total cycle period of 72 h consisting of 3 h of FILL, 64 h REACT, 2 h of SETTLE, and 3 h of DECANT with chlorpyrifos concentrations of 3000 micrpg/g, 6000 microg/g and 12000 microg/g. At 3000 microg/g of chlorpyrifos concentration, 91% was degraded after 72 h of the cycle period, whereas in the case of 6000 microg/g of chlorpyrifos, 82.5% was degraded. However, for 12000 microg/g of chlorpyrifos, only 14.5% degradation was observed. The degradation rate was rapid at lower substrate concentration and 12000 microg/g of substrate concentration was found to be inhibitory. Chlorpyrifos removal rate was slow during the initial phase of the sequence operation. Half-life of chlorpyrifos degradation (t0.5) was estimated to be 6.3 h for 3000 microg/g of substrate, 17.5 h for 6000 microg/g and 732.2 h for 12000 microg/g. Process performance was assessed by monitoring chlorpyrifos concentration and biochemical process parameters viz., pH, oxidation and reduction potential (ORP), dissolved oxygen (DO), oxygen consumption rate (OCR) and microbial count (CFU) during sequence operation. From the experimental data obtained it can be concluded that the rate-limiting step with the bioslurry phase reactor in the process of chlorpyrifos degradation may be attributed to the concentration of substrate present in either soil or liquid phase. Periodic operations (SBR) by varying individual components of substrate with time in each process step place micro-organisms under nutritional changes from feast to famine and maintains a wide distribution in the population of micro-organisms resulting in high uptake of the substrate in the bioslurry reactor.     

Bias voltage dependence properties of cadmium oxide films deposited by d.c. reactive magnetron sputtering

Cadmium oxide films were grown on glass substrates using d.c. reactive magnetron sputtering technique by sputtering from a metallic cadmium target in an oxygen partial pressure of 1×10^–3 mbar under various substrate bias voltages. The substrate bias voltage significantly influences the crystallographic structure of the deposited films. The influence of substrate bias voltage on the electrical and optical properties of the films was systematically studied. The films formed at a substrate temperature of 473 K and bias voltage of –80 V showed an electrical resistivity of 1×10^–3 cm, optical transmittance of 86%, optical band gap of 2.47 eV and a figure of merit of 7×10^{–3 –1}.