Showing papers by "Heritage Institute of Technology published in 2020"

Machine learning techniques for sequence-based prediction of viral-host interactions between SARS-CoV-2 and human proteins.

Abstract: Background COVID-19 (Coronavirus Disease-19), a disease caused by the SARS-CoV-2 virus, has been declared as a pandemic by the World Health Organization on March 11, 2020. Over 15 million people have already been affected worldwide by COVID-19, resulting in more than 0.6 million deaths. Protein–protein interactions (PPIs) play a key role in the cellular process of SARS-CoV-2 virus infection in the human body. Recently a study has reported some SARS-CoV-2 proteins that interact with several human proteins while many potential interactions remain to be identified. Method In this article, various machine learning models are built to predict the PPIs between the virus and human proteins that are further validated using biological experiments. The classification models are prepared based on different sequence-based features of human proteins like amino acid composition, pseudo amino acid composition, and conjoint triad. Result We have built an ensemble voting classifier using SVMRadial, SVMPolynomial, and Random Forest technique that gives a greater accuracy, precision, specificity, recall, and F1 score compared to all other models used in the work. A total of 1326 potential human target proteins of SARS-CoV-2 have been predicted by the proposed ensemble model and validated using gene ontology and KEGG pathway enrichment analysis. Several repurposable drugs targeting the predicted interactions are also reported. Conclusion This study may encourage the identification of potential targets for more effective anti-COVID drug discovery.

Neutrosophic fuzzy set and its application in decision making

Abstract: Fuzzy set (FS) is used to tackle the uncertainty using the membership grade, whereas neutrosophic set (NS) is used to tackle uncertainty using the truth, indeterminacy and falsity membership grades which are considered as independent. In this paper, we introduce the notion of neutrosophic fuzzy set (NFS) by combining FS with NS, which gives rise to some new concepts. Since NFS finds some difficulties to deal with some real life problems due to the nonstandard interval of neutrosophic components, we introduce single valued NFS (SVNFS) which is considered as an instance of NFS. Some set theoretic operations of SVNFS are proposed and their properties are derived. We also propose the distance measures between two SVNFSs. Then a decision making approach is presented using similarity measures based on distance measures. Finally, we emonstrate the proposed approach using a numerical example.

Uncertain programming models for multi-objective shortest path problem with uncertain parameters

Abstract: The shortest path problem is considered as one of the essential problems in network optimization with a wide range of real-world applications. Modelling such real-world applications involves various indeterminate phenomena which can be estimated through human beliefs. The uncertainty theory proposed by Liu (Uncertain theory, 2nd edn., Springer, Berlin, 2007) is widely regarded as a legitimate tool to deal with such uncertainty. This paper presents an uncertain multi-objective shortest path problem (UMSPP) for a weighted connected directed graph (WCDG), where every edge weight is associated with two uncertain parameters: cost and time. These parameters are represented as uncertain variables. Here, we have formulated the expected value model and chance-constrained model of the proposed UMSPP, and the corresponding deterministic transformation of these models is also presented. Subsequently, the deterministic models are solved with a classical multi-objective solution method, namely the global criterion method. Furthermore, two multi-objective genetic algorithms (MOGAs): nondominated sorting genetic algorithm II (NSGA-II) and multi-objective cross-generational elitist selection, heterogeneous recombination and cataclysmic mutation (MOCHC), are employed to solve these models. A suitable example is provided to illustrate the proposed model. Finally, the performance of MOGAs is compared for five randomly generated instances of UMSPP.

Kinetic analysis and parametric optimization for bioaugmentation of oil from oily wastewater with hydrocarbonoclastic Rhodococcus pyridinivorans F5 strain

Abstract: Bioaugmentation is the most coveted bioremediation technology in present days that is being widely quested around the world for the treatment of wastewater. The present study thus investigates the bioaugmentation capability of the isolated hydrocarbonoclastic bacterium Rhodococcus pyridinivorans F5 in polymeric entrapment to degrade hydrocarbons from oily wastewater. The strain showed high hydrocarbon tolerance ability as high as 8% (v/v) hydrocarbon concentration. Optimization of the growth conditions was simulated using response surface methodology (RSM), which was found and validated at the temperature 37 °C with neutral pH for a wide range of salinity. Maximum percentage degradation of hydrocarbon was seen as 79( ± 0.03)% for the system comprising of both free and emulsified form of oil using the isolated strain in free bacterial suspension state. While the degradation percentage was increased to 86( ± 0.028)% with the cell entrapped alginate bead without the presence of activated carbon as the doped agent. After doping activated carbon with the alginate bead the percentage degradation was further increased to 95( ± 0.02)%. It was studied that with the entrapment technology the sustainability of the technology enhances because of the enhanced recyclability of the microbial cells in bioaugmenting the oil from oily wastewater. Statistical interpretation showed that the degree of hydrocarbon degradation was significantly sensitive to both the state of presence of oil in an oily-water system (F = 444.8 > F critical = 6 . 9 ) and the presence of bacterial form (either free bacterial suspension or immobilized state) (F = 168.1 > F critical = 6 . 9 ).

Multi-warehouse partial backlogging inventory system with inflation for non-instantaneous deteriorating multi-item under imprecise environment

Abstract: In this study, we explored a multi-item inventory model for non-instantaneous deteriorating items under inflation in fuzzy rough environment with multiple warehouse facilities, where one is an owned warehouse and others are rented warehouses with limited storage capacity. Due to a number of uncertainties in the environment, the various expenditures and coefficients are considered as a fuzzy rough type. The objective and constraints in fuzzy rough are made deterministic using Tr–Pos chance constrained technique. The demand of items is considered as stock dependent, and deterioration of items is assumed to be constant over time. The model allows shortages in owned warehouse subject to partial backlogging. The purpose of this study is to find the retailer’s optimal replenishment policies to maximize the total profit. To illustrate the proposed model and also test the validity of the same, a numerical example is solved using the Mathematica-8.0 software. Sensitivity analysis is also performed to study the impact of important parameters on system decision variables, and its implications are discussed.

A Utility Driven Post Disaster Emergency Resource Allocation System Using DTN

Abstract: Two of the most dominant challenges in post disaster emergency resource allocation are: 1) understanding the exact utility, i.e., exigency, of emergency resources and 2) collecting and transmitting the need for these resources to the control station from where resources are allocated. Measuring the utility of resources with precision becomes tricky in a dynamic post disaster scenario, where demands are constantly evolving and supplies trickle in at an uncertain rate. Moreover, collection and transmission of resource needs of far-flung areas are easier said than done owing to the post disaster disruption of communication infrastructure. These result in the ad-hoc allocation of emergency resources to the shelters. In this paper, we first derive a utility function for dynamically enumerating the shelter specific utility of each emergency resource. Subsequently, we propose an opportunistic knowledge sharing scheme for gathering and disseminating resource needs to the control station using a smartphone-based delay tolerant network. Finally, based on these opportunistically transmitted needs, we formulate a utility driven optimal resource allocation model which minimizes overall resource deficit and total resource deployment time. The proposed system optimally assigns constrained emergency resources to different shelters, so that high-utility resources are deployed fast. The effectiveness of the proposed system is evaluated using ONE simulator and LINGO optimization modeling tool. Exhaustive simulation is done to evaluate the comparative performance of our system with a number of competing schemes. Results show that our system outperforms all these schemes in a fully connected scenario. It is also observed that even in an intermittently connected environment, the performance of our system is almost at par with the competing schemes.

Electric field assisted membrane separation for oily wastewater with a novel and cost-effective electrocoagulation and electroflotation enhanced membrane module (ECEFMM)

Abstract: The present study discusses the simultaneous application of electric field during membrane separation of oil from oily wastewater on eliminating the fouling propensity over the membrane. A novel hybrid electrocoagulation and electroflotation enhanced membrane module (ECEFMM) was proposed here to expect the benefits of electrocoagulation and electroflotation with the membrane separation. The synergistic effect of applied voltage and membrane operation facilitates demulsification for emulsified oily wastewater along with substantial turbulence creation over the membrane surface through hydrogen bubbling. Such turbulence reduces the deposition over the membrane surface that eventually restricts the permeate flux decrease by 43–72 %. Voltage was applied both continuously and periodically, along with a gradual voltage increment in each mode. Further with both the mode of applied voltage, polyethersulfone (PES) and polysulfone (PSf) membrane were employed with each of the modes. It was observed that the permeation of the PES membrane is not substantially affected by the mode of the applied voltage. On the contrary, with relatively low hydrophilic PSf membrane, the permeation is highly dependent on the applied voltage and its mode of application. The minimum flux decline for PSf membrane can be achieved with periodical voltage application at 10 V with substantial oil rejection of 94–96 %.

Comparative Study of Variations in Gate Oxide Material of a Novel Underlap DG MOS-HEMT for Analog/RF and High Power Applications

Abstract: In this paper an Underlap Double Gate (U-DG) Symmetric Heterojunction AlGaN/GaN Metal Oxide Semiconductor High Electron Mobility Transistor (MOS-HEMT) with gate oxide materials of different dielectric constant has been studied using gate oxide materials such as Hafnium dioxide (HfO2), Silicon dioxide (SiO2) and a symmetric gate stack (GS) of HfO2-SiO2. In this work, the analog performance of the devices has been studied on the basis of parameters like transconductance (gm), transconductance generation factor (gm/ID) and intrinsic gain (gmR0). This paper depicts the effect of varying oxide materials on the analog and RF figure of merits (FOMs) such as the gate to drain capacitance (CGD), gate to source capacitance (CGS) and total gate capacitance (CGG), intrinsic resistances, cut-off frequency (fT) and maximum frequency of oscillation (fMAX) using non-quasi-static approach. Studies show that the introduction of a gate oxide layer in the MOS-HEMT device increases the gate controllability reducing gate leakage currents improving RF performance. U-DG AlGaN/GaN MOS-HEMT with HfO2 gate dielectric shows superior Power output efficiency (POE) of 55% compared to the HfO2-SiO2 composite structure and SiO2 with 26% and 20% respectively.

Modeling Dynamic Stability and Cutting Forces in Micro Milling of Ti6Al4V Using Intermittent Oblique Cutting Finite Element Method Simulation-Based Force Coefficients

Abstract: Tool breakage is a significant issue in micro milling owing to the less stiffness of the micro tool. To cope up with such limitation, precise predictions of dynamic stability, and cutting force have the utmost importance to monitor and optimize the process. In this article, dynamic stability and cutting force are predicted precisely for micro milling of Ti6Al4V by obtaining force coefficients from a novel 3D intermittent oblique cutting finite element method (FEM) simulation considering the influence of tool run out. First, the stability model is modified by incorporating the appropriate values of limiting angles obtained analytically accounting the trajectories of the flutes due to tool run out. This stability model is utilized to select chatter-free parametric combinations for micro milling tests. Next, an improved cutting force model is developed by incorporating the force coefficients obtained from oblique cutting simulation in the mechanistic model and differentiating the whole machining region into three distinct region considering size effect. The force model also considers the effect of increased edge radius of the worn tool, run out, elastic recovery, ploughing, minimum undeformed chip thickness (MUCT), and limiting angles, cumulatively. The proposed dynamic stability and cutting force models based on the oblique cutting simulation show their adequacy by predicting the stability limit and cutting force more precisely, respectively, as compared to those obtained by orthogonal cutting simulation. Besides, the proposed force model for the worn tool is found to be viable as it is closer to the experimental forces, whereas force model without the incorporation of tool wear underestimated the experimental forces.

Random selection based GA optimization in 2D-DCT domain color image steganography

Abstract: Steganography, the hiding technique used to secure sensitive data (i.e., images, audio ) while communication takes place. In this paper, the message is embedded in color image in frequency domain exploiting Genetic Algorithm (GA) which provides the robustness i.e., the algorithm can withstand against any rigorous testing and brutal attack except destruction of the stego image. The fragmentation of 8-bit binary stream of each color component to 4-bit and applying Genetic Algorithm (GA) to increase the robustness of the scheme. Random Multiple bits are chosen to embed secret message which increases security along with the payload. The use of transform domain, hash function based random pixel and bit selections for data hiding, secrete data encryption and more over use of Genetic Algorithm (GA) for optimization is the novelty of the proposed work. Perspective and meticulous statistical analysis has been done to immune the algorithm from any attack. The algorithm proposed here is tested with benchmark tools like StirMark 4.0, Confusion Matrix (Receiver Operating Curve Characteristic (ROC) curve) along with steganalysis and statistical tools. Visual disturbance and distortion in stego image is also very insignificant here.

Water dimer isomers: interaction energies and electronic structure.

Abstract: The energetic and electronic structure of various water dimer isomers has been explored through DFT methodology. Six different possible water dimers come in two broad categories, planar and non-planar. In each of the categories, three distinct topologies (i) linear, (ii) ring and (iii) bifurcated, have been obtained. The linear dimer has the highest interaction energy, followed by the ring dimer and then comes the bifurcated dimer. For each of these type, a planar dimer having all six atoms organized in a single plane come very close to, but has a slightly higher energy than the corresponding non-planar counterpart. Bader’s atoms in molecules (AIM) theory, reduced density gradient (RDG) method and non-covalent interaction (NCI) analysis reveal that the electron density distribution among the interacting water molecules correlates exactly in the sequence of interaction energies of different isomers of water dimer.

A multi-objective multi-item solid transportation problem with vehicle cost, volume and weight capacity under fuzzy environment

Abstract: Generally, in transportation problem, full vehicles (e.g., light commercial vehicles, medium duty and heavy duty trucks, etc.) are to be booked, and transportation cost of a vehicle has to be paid irrespective of the fulfilment of the capacity of the vehicle. Besides the transportation cost, total time that includes travel time of a vehicle, loading and unloading times of products is also an important issue. Also, instead of a single item, different types of items may need to be transported from some sources to destinations through different types of conveyances. The optimal transportation policy may be affected by many other issues like volume and weight of per unit of product, unavailability of sufficient number of certain types of vehicles, etc. In this paper, we formulate a multi-objective multi-item solid transportation problem by addressing all these issues. The problem is formulated with the transportation cost and time parameters as fuzzy variables. Using credibility theory of fuzzy variables, a chance-constraint programming model is formulated, and is then transformed into the corresponding deterministic form. Finally numerical example is provided to illustrate the problem.

GAN-Based Novel Approach for Data Augmentation with Improved Disease Classification

Abstract: Deep learning, via Convolutional Neural Network (CNN) models, has had significant breakthroughs and achievements in image classification tasks where there is a sufficient amount of annotated data. Generally, medical image datasets are highly imbalanced, and training a convolutional neural network model to classify diseases across classes does not give the desired performance. To combat this, data augmentation is required, and in this chapter, we propose a new strategy to improve the generalization performance of CNN model using a novel online data augmentation strategy with Deep Convolutional Generative Adversarial Network (DCGAN). This helps in regularizing the training and gives better performance across classes, as it prevents the model from overfitting to the majority class. We performed our experiment on NIH chest X-ray image dataset, available openly, considering three classes: Infiltration, Atelectasis and No Findings. The test accuracy of the CNN model is 60.3% compared to the 65.3% test accuracy of the online GAN-augmented CNN model.

Exergy and Cost Optimization of a Two-Stage Refrigeration System Using Refrigerant R32 and R410A

Abstract: An attempt has been made to investigate numerically a two-stage refrigeration system with flash intercooler of 50 kW cooling capacity using refrigerant R410A and its possible alternative R32. Development of the simulation model for the analysis of the system has been carried out in engineering equation solver considering the energetic, exergetic, economic, and environmental aspects. Evaporator and condenser temperatures have been varied from −50 °C to −25 °C and 40 °C to 55 °C, respectively, to carry out the simulation work. Co-efficient of performance (COP), exergetic efficiency, and plant cost rate are the three performance parameters computed in this present work. Results show that the performances of the system using R32 are comparable with those of the system using R410A. It is also observed that R32 shows slightly better thermo-economic performances at higher condenser temperature. Multi-objective optimization has also been carried out using the toolbox available for optimization in matlab to obtain the optimum performance and optimum operating conditions for both the refrigerants. Optimization results also show better thermo-economic performances of R32 over R410A though compressor discharge temperature is higher in case of R32.

Improvement in Threshold Switching Performance Using Al₂O₃ Interfacial Layer in Ag/Al₂O₃/SiOₓ/W Cross-Point Platform

Abstract: An Al2O3/SiOx bi-layer cross-point selector was proposed and experimentally demonstrated in this work to mitigate the sneak path leakage issue in the high density passive crossbar array. A 2 nm Al2O3 interfacial layer confines filament dissolution gap caused by Ag diffusion into the SiOx layer, enabling significant improvement in uniformity and other electrical performances as compared to the monolayer SiOx selector (without Al2O3 layer). Devices with Al2O3 interfacial layer exhibit I-V characteristics with large selectivity of $> 5\times 10^{{7}}$ , high rectifying ratio ( RR ) of $> 5\times 10^{{7}}$ , high ON state current density of $> 10^{{3}}~\text{A}\cdot $ cm $^{\text {-2}}$ , steep slope subthreshold swing ( SS ) of $> 10~^{{4}}$ seconds were also demonstrated.

A novel hotspot and rare somatic mutation p.A138V, at TP53 is associated with poor survival of pancreatic ductal and periampullary adenocarcinoma patients.

Abstract: Pancreatic Ductal Adenocarcinoma (PDAC) is a cancer of the exocrine pancreas and 5-year survival rates remain constant at 7%. Along with PDAC, Periampullary Adenocarcinoma (PAC) accounts for 0.5–2% of all gastrointestinal malignancies. Genomic observations were well concluded for PDAC and PACs in western countries but no reports are available from India till now. Targeted Next Generation Sequencing were performed in 8 (5 PDAC and 3 PAC) tumour normal pairs, using a panel of 412 cancer related genes. Primary findings were replicated in 85 tumour samples (31 PDAC and 54 PAC) using the Sanger sequencing. Mutations were also validated by ASPCR, RFLP, and Ion Torrent sequencing. IHC along with molecular dynamics and docking studies were performed for the p.A138V mutant of TP53. Key polymorphisms at TP53 and its associated genes were genotyped by PCR-RFLP method and association with somatic mutations were evaluated. All survival analysis was done using the Kaplan-Meier survival method which revealed that the survival rates varied significantly depending on the somatic mutations the patients harboured. Among the total 114 detected somatic mutations, TP53 was the most frequently mutated (41%) gene, followed by KRAS, SMAD4, CTNNB1, and ERBB3. We identified a novel hotspot TP53 mutation (p.A138V, in 17% of all patients). Low frequency of KRAS mutation (33%) was detected in these samples compared to patients from Western counties. Molecular Dynamics (MD) simulation and DNA-protein docking analysis predicted p.A138V to have oncogenic characteristics. Patients with p.A138V mutation showed poorer overall survival (p = 0.01). So, our finding highlights elevated prevalence of the p53p.A138V somatic mutation in PDAC and pancreatobiliary PAC patients. Detection of p.A138V somatic variant in TP53 might serve as a prognostic marker to classify patients. It might also have a role in determining treatment regimes. In addition, low frequency of KRAS hotspot mutation mostly in Indian PDAC patient cohort indicates presence of other early drivers in malignant transformation.

Resistive Analysis of Scattering-Dependent Electrical Transport in Single-Wall Carbon-Nanotube Networks

Abstract: With the development of separation and sorting techniques, highly enriched semiconducting single-walled carbon nanotubes (SWNTs) have become widely accessible, which has led to the rapid growth of high-performance solution-processed SWNT-based thin-film field-effect transistors (TFTs) showing capabilities comparable to the ideal single-SWNT FETs. With such improvements, theoretical studies and detailed analyses of these networks have become necessary. In this work, a model justifying the near-ideal electrical transport in SWNT networks is presented. The field-dependent resistive properties of the networks are calculated using a numerical solver based on the derived individual resistances of SWNTs and the intertube couplings. The model is capable of simulating mixed SWNT networks consisting of both metallic and semiconducting nanotubes of varying chiralities. Our analysis reveals that the high electrical currents in networks could be largely attributed to the suppression of phonon scattering and strong intertube couplings in highly dense SWNT networks (>30–40 SWNTs $/{\mu m}^{2}$ ). Comparisons between the simu- lated and experimental results indicate good agreement thereby demonstrating the accuracy of the proposed model.

Two-dimensional modeling of the underlap graded-channel FinFET

Abstract: The graded n-channel underlap fin-shaped field-effect transistor (FinFET) provides ample scope for future investigation. This device and the effects of the underlap, gate length, and doping concentration of the short channel are analyzed herein using two-dimensional (2-D) modeling. The proposed structure includes four regions, in each of which a potential function is developed by applying boundary conditions on Poisson’s equation. The parabolic potential profiles in the graded channel region and the underlap regions are found to depend on the bias at the gate/drain terminals, the doping profile, the channel length, and the underlap length, ensuring the reliability of the device for low-power circuit applications. The results of this analysis are validated against numerical solutions obtained using a 2-D device simulator, revealing an exact match.

A New Scheme for Determination of Respiration Rate in Human Being using MEMS Based Capacitive Pressure Sensor: Simulation Study

Abstract: In this paper, a MEMS based capacitive nasal sensor system for measuring Respiration Rate (RR) of human being is developed. At first two identical diaphragm based MEMS capacitive nasal sensors are designed and virtually fabricated. A proposed schematic of the system consists of signal conditioning circuitry alongwith the sensors is described here. In order to measure the respiration rate the sensors are mounted below Right Nostril (RN) and Left Nostril (LN), in such a way that the nasal airflow during inspiration and expiration impinge on the sensor diaphragms. Due to nasal airflow, the designed square diaphragm of the sensor is being deflected and thus induces a corresponding change in the original capacitance value. This change in capacitance value is to be detected by a correlated- double-sampling (CDS) capacitance-to-voltage converter is designed for a precision interface with a MEMS capacitive pressure sensor, followed by an amplifier and a differential cyclic ADC to digitize the pressure information. The designed MEMS based capacitive nasal sensors is capable of identifying normal RR (18.5±1.5 bpm) of human being. The design of sensors and its characteristics analysis are performed in a FEA/BEA based virtual simulation platform. Index Terms— MEMS capacitive nasal sensor, diaphragm deflection, respiration rate (RR), oscillator, sensitivity, Finite Element Analysis, Boundary Element Analysis.

E-waste Inventorisation for Sustainable Smart Cities in India: A Cloud-based Framework

Abstract: The expansion of the electronics market, increased demand, short cycles of innovation, cunning marketing gimmick and buying capacity of consumers; the lifespan of electronic items are reducing. End-of-Life (EoL), popularly known as e-waste has become a big environmental menace worldwide. Global e-waste generation reached 53.6 million metric tons in 2019 from 41.8 million metric tons in 2014. India generated about 3.28 million metric tons of e-waste in 2019. However, the generation data might not be the same in reality in a country like India. The e-waste data is calculated from the electronics sales data. In India, the sales data is not properly obtained as no proper record is maintained and hence rough estimations are carried out. With the rise of the e-commerce sector nearly 26 percent electronic items are sold online in India. While offline electronics sales can be estimated from the associated Goods and Sales Tax (GST) data. E-waste management in India has geared up in the last 5 years and it is an important aspect for sustainable smart cities. With India promoting a smart city mission and targeting to reach the SDGs, it important to develop a system that can record the online as well as offline sales data and contribute in creating an e-waste inventory. An e-waste inventory for any country will be beneficial for further analysis. In this study, we propose a cloud-based framework for keeping record of electronics item sales data primarily from the e-commerce sector as well as from offline sales. The developed framework will be helpful to the researcher and it is expected to be a prima-facie for developing national e-waste inventory for any country.

Studies on Security Threats in Waste Mobile Phone Recycling Supply Chain in India

Abstract: The presence of different metals and rare earth elements in the smart phones have made waste mobile phone recycling economically suitable. In order to maintain the equilibrium of resource exploitation and enhance resource efficiency, it is important to recycle mobile sustainably. Increasing environmental and data loss threats have enforced several policies to increase the recycling rate. Despite all, a small fraction of waste mobile phones are recycled properly and a significant amount mobile phones are refurbished and repaired which enters the second-hand market. The secondhand market is a critical node in the supply chain of waste mobile phone. The data security issues arise from this area and it varies with the amount of time it spends in the repairing zone. A lot of valuable and sensitive data are saved in storage units of a mobile phone. Improper disposal of waste mobile phone can lead to potential threat of exposing personal information from the devices, including logged in profile details of social networking sites, emails, personal messages, photos etc. This can lead to cyber risks including identity theft, data tampering, information disclosure etc. which may have higher social impact. General issues with data security from ewaste have been reported. Studies focusing on threats from used, lost or improperly discarded mobile phones are scant. In this study, we identify such issues pertaining in the supply chain of waste mobile phones. Possible solutions have been proposed to address these issues. A supply-chain based framework has been proposed which can serve as a prima facie towards development of a detailed solution architecture.

Stabilization of cyclic water tetramers and dimers in the crystal host of 2D coordination networks: electrical conductivity and dielectric studies

Abstract: Water plays a pivotal role in many biological and chemical processes in a living body. Therefore, it is a challenging task to predict a suitable host for confinement of aqua molecules. Here, two new isostructural two-dimensional coordination polymers (2D CPs) {[Zn(fum)(4-nvp)2]·2H2O}n (1) and {[Zn(mes)(4-nvp)2]·H2O}n (2) (H2fum = fumaric acid and 4-nvp = 4-(1-naphthylvinyl)pyridine and H2mes = mesaconic acid) have been synthesized and structurally characterized by single crystal X-ray crystallography (SCXRD). The SCXRD reveals the presence of carboxylate bound cyclic water tetramers and water dimers in compounds 1 and 2 respectively, within rectangular grids of 2D coordination layers. Binding energies of the cavity bound tetramer as well as the dimer have been estimated computationally. The PXRD study of both the compounds shows reversible water desorption and re-absorption upon heating and cooling. The π⋯π and C–H⋯π interactions among the axially bound 4-nvp ligands are responsible for interdigitation of successive 2D coordination layers into a 3D supramolecular architecture. In addition, the impedance study shows that compounds 1 and 2 exhibit interesting temperature dependent dielectric properties.

Palladium-Catalyzed Cascade Reactions for Annulative π -Extension of Indoles to Carbazoles through C–H Bond Activation

Abstract: The annulative π-extension (APEX) reactions through C-H bond activation has tremendous potential to access fused aromatic systems from relatively simple aromatic compounds in a single step. This state-of-the-art technique has the ability to streamline the synthesis of functionalized materials useful in material science, biomedical research, agroand pharmaceutical industries. Furthermore, C-H activation strategy does not require prefunctionalization steps, which allows for the late-stage modification of the functional molecule with requisite molecular properties. Owing to their unique photophysical properties, carbazoles are widely used in photovoltaic cells, biomedical imaging, fluorescent polymer, etc. It is also ubiquitously found in many natural products, agrochemicals and privileged medicinal scaffolds. Hence, direct conversion of easily accessible indole to carbazole remains an active research area. In the last decades, significant advancement has been made to access carbazole moiety directly from indole through cascade C-H activation. The underlying mechanism behind this cascade π-extension strategy is the facile electrophilic metalation at the C-3 position of the indole moiety, 1,2- migration and electro cyclization. In this review, we will discuss recent literature reports for the palladium-catalyzed π-extension of indole to carbazole moiety through C-H bond activation.

Hybrid advanced player selection strategy based population search for global optimization

Abstract: Motivation: Finding the optimum solution of real world complex optimization problem needs efficient solver system. Meta-heuristic like swarm, evolutionary or physics based methods essentially form an expert system which may strive for the search of optimum solution. However, these methods have their own merits and demerits. To supersede the performance of existing systems in context of real time and advanced problems and to propose new intelligent method having an optimal balance between exploration and exploitation phase have become a center of focus of the expert system design. Therefore, being inspired from such a scenario, a hybrid advanced player selection strategy based population search (HAPS-PS) technique is proposed and evaluated in this paper in context of modern applications. Methods: Sport is a multi-functional activity where different learning methods like cooperative, competitive and self-learning variants along with interactive environmental features help to improve the performance of the players. The properties of playing activity and the thematic learning process of sports, along with some features like, chaotic map based initialization, pool based topological structure selection, integration of blended laplacian operator etc. contributes in the design of HAPS-PS. Also a novel mechanism of team reformation through elimination of comparatively poor players and recruitment of new talents is employed. It provides diversification and regulates the search agents in a promising direction. Results: We have comprehensively evaluated the performance of the HAPS-PS by applying it on standard benchmark problems and on various shifted rotated, hybrid and composite problems of CEC2013 and CEC2014. Also some of the competitive problems of CEC 2017 are tested using the proposed method and they are also compared with other state-of-the-art algorithm to validate the efficacy of the system. Further, tests are carried out on some real-world problems from CEC2011 which includes applications related to parameter optimization of frequency-modulated (FM) sound wave, minimization of molecular potential energy of Lennard-Jones cluster, controlling the chemical reactors, and evaluation of the inter atomic tersoff potentials for covalent systems of silicon. The proposed method is also applied on spread spectrum radar polyphase code design problem as a part of real world application. The comparative results validate the effectiveness and efficiency of HAPS-PS.

Hybrid Cryptography Algorithm For Secure And Low Cost Communication

Abstract: In a client-server architecture or open networks such as the internet, transmission of data may lead to leak of confidential information. The objective of encryption is to secure or protect data from unauthorized access or modifications. In this paper a hybrid cryptography algorithm is proposed in order to achieve confidentiality and increase security in the communications taking place over the internet. The paper also focuses on the time taken for the encryption and decryption process so that the algorithm is not CPU exhaustive.