On the improvement of detection characteristics of trans-stilbene crystals by improving crystal perfection

Organic molecular scintillating crystals are noted for their good timing and particle discrimination process. Trans-stilbene is one such candidate noted for its good particle detection characteristics for the past five decades. Progressive strengthening of detection characteristics of trans-stilbene has been attempted by improving crystal perfection. A series of timing resolution studies have been carried out for the Bridgman grown trans-stilbene crystals under different experimental conditions. The results were compared with the previously reported values. Pulse shape discrimination process has been carried out for ²⁴¹Am and ²⁵²Cf sources and good discrimination has been obtained for gamma-alpha and gamma-neutron sources from the grown organic phosphor crystal. Electronic Publication     

Studies on nucleation kinetics of InxGa1−xN/GaN heterostructures

Nucleation kinetics during the growth of In_xGa_1−xN on a GaN substrate have been studied. The behavior of nonequilibrium between the In_xGa_1−xN and the GaN substrate has been analyzed, and hence, the expression derived for the stress-induced supercooling/superheating has been numerically evaluated. The maximum amount of stress-induced supercooling is found to be 1.017 K at x=0.12. These values are incorporated in the classical heterogeneous nucleation theory. Using the regular solution model, the interfacial tension between the nucleus and substrate and, hence, the interfacial tension between nucleus and mother phase and thermodynamical potential of the compounds have been calculated. The amount of driving force available for the nucleation has been determined for different compositions and degrees of supercooling. It has been shown that the value of the interaction parameter of InN-GaN plays a dominant role in nucleation and growth kinetics of In_xGa_1−xN on a GaN substrate. These values have been used to evaluate the nucleation parameters. It is shown that the nucleation barrier for the formation of a In_xGa_1−xN nucleus on a GaN substrate is minimum in the range of x=0.12 to x=0.17, and it has been qualitatively proved that good quality In_xGa_1−xN on GaN can be grown only in the range 0<x≤0.2.     

Modeling electric field transfer of excitation at cell junctions

The electric field (EF) model was first developed on a "breadboard" using physical electric components (e.g., resistors, capacitors, batteries) and was then modeled mathematically by a series of differential equations and matrix equations and simulated on a large computer (CDC-6400). The results obtained by the two methods agreed very closely. However, these two methods of analysis are quite cumbersome. Therefore, in order to simplify the EF simulation, we wanted to model it on the PSpice program. In this article we discuss how we succeeded in demonstrating transmission of excitation from cell to cell in cardiac muscle and smooth muscle based on EF transmission at the cell junctions.     

Effect of alkyl chain length on the electrochemical perfluorination of n-alkane (C6–C10) carboxylic acid chlorides

Electrochemical perfluorination (ECPF) of n-hexanoyl, n-heptanoyl, n-octanoyl, n-nonanoyl and n-decanoyl chlorides was carried out under identical experimental conditions in liquid HF. The product distribution among perfluorinated carboxylic acids, perfluoro ethers, perfluoroalkanes, isomerised and fragmented products containing less number of carbon atoms was identified using ¹⁹F NMR. The selectivity of C₆–C₁₀ perfluoro carboxylic acid varied between 29 and 36%. The alkali insoluble perfluoro cyclic ether and perfluoro alkane fractions increased with increasing chain length. The increase of perfluoroalkane fractions is mainly due to decarboxylation. Cyclic ether fractions also decreased slightly with increase in chain length. Among the cyclic ethers α substituted oxolanes were the predominant products. Six membered cyclic ethers were always found to contain β substitution. The possible pathways for these products are also indicated. An erratum to this article can be found at     

HamleDT: Harmonized multi-language dependency treebank

We present HamleDT—a HArmonized Multi-LanguagE Dependency Treebank. HamleDT is a compilation of existing dependency treebanks (or dependency conversions of other treebanks), transformed so that they all conform to the same annotation style. In the present article, we provide a thorough investigation and discussion of a number of phenomena that are comparable across languages, though their annotation in treebanks often differs. We claim that transformation procedures can be designed to automatically identify most such phenomena and convert them to a unified annotation style. This unification is beneficial both to comparative corpus linguistics and to machine learning of syntactic parsing.     

Metallo-organic deposition of tungsten oxide films from alkylammonium tungstate solutions

This paper describes a simple and inexpensive metallo-organic deposition (MOD) process for forming electrochromic tungsten oxide (WO₃) films on glass. The thin films of WO₃ were made by air firing (500–700°C) films from xylene/2-propanol solutions of bis-(di-n-octylammonium) tetratungstate, [(n-C₈H₁₇)₂NH₂]₂[W₄O₁₃]. The process coats glass with undoped films ranging in colour from faint yellow to dark brown, and can be used to make gradients of these colours. The colour is determined by the firing parameters and results from residual carbon and tungsten suboxides in the film due to incomplete firing. Increased firing temperatures or longer firing times removes the carbon and produces films with higher crystallinity. Electrochemical doping with acid (H⁺) switches the colour gradient films to a uniformly blue colour.     

Optimized deep learning-based intrusion detection for wireless sensor networks

The technological innovations and wide use of Wireless Sensor Network (WSN) applications need to handle diverse data. These huge data possess network security issues as intrusions that cannot be neglected or ignored. An effective strategy to counteract security issues in WSN can be achieved through the Intrusion Detection System (IDS). IDS ensures network integrity, availability, and confidentiality by detecting different attacks. Regardless of efforts by various researchers, the domain is still open to obtain an IDS with improved detection accuracy with minimum false alarms to detect intrusions. Machine learning models are deployed as IDS, but their potential solutions need to be improved in terms of detection accuracy. The neural network performance depends on feature selection, and hence, it is essential to bring an efficient feature selection model for better performance. An optimized deep learning model has been presented to detect different types of attacks in WSN. Instead of the conventional parameter selection procedure for Convolutional Neural Network (CNN) architecture, a nature-inspired whale optimization algorithm is included to optimize the CNN parameters such as kernel size, feature map count, padding, and pooling type. These optimized features greatly improved the intrusion detection accuracy compared to Deep Neural network (DNN), Random Forest (RF), and Decision Tree (DT) models.     

An automatic query expansion based on hybrid CMO-COOT algorithm for optimized information retrieval

The World Wide Web(WWW) comprises a wide range of information, and it is mainly operated on the principles of keyword matching which often reduces accurate information retrieval. Automatic query expansion is one of the primary methods for information retrieval, and it handles the vocabulary mismatch problem often faced by the information retrieval systems to retrieve an appropriate document using the keywords. This paper proposed a novel approach of hybrid COOT-based Cat and Mouse Optimization (CMO) algorithm named as hybrid COOT-CMO for the appropriate selection of optimal candidate terms in the automatic query expansion process. To improve the accuracy of the Cat and Mouse Optimization (CMO) algorithm, the parameters are tuned with the help of the Coot algorithm. The best suitable expanded query is identified from the available expanded query sets also known as candidate query pools. All feasible combinations in this candidate query pool should be obtained from the top retrieved documents. Benchmark datasets such as the GOV2 Test Collection, the Cranfield Collections, and the NTCIR Test Collection are utilized to assess the performance of the proposed hybrid COOT-CMO method for automatic query expansion. This proposed method surpasses the existing state-of-the-art techniques using many performance measures such as F-score, precision, and mean average precision (MAP).