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Nanocomposites hold the possible to reform the field of conventional composites together in conditions of recital and prospective applications. Polymer nanocomposites enclose enormous market future together as replacements for present composites and in the making of new markets during their great behaviour. It offer advanced technologies and enhances business opportunities to all industrial sectors. This review gives a broad resource for polymer nanocomposite, nanoparticles synthesis, fabrication and testing methods of polymer nanocomposites.

Oligo(ethylene glycol) methacrylates functionalized with anthrapyrazolone are reported as fluorescent polymeric thermometers with a broad linear temperature sensing regime.

The main purpose of this paper is to observe the effect PV variation of solar temperature and irradiance on different conditions and on the inverter output for a grid-connected system. Majorly temperature& solar irradiation effects the performance of a grid connected inverter, also on the photo-voltaic (PV) electric system. The simulation based study was carried out in order to evaluate the variation of inverter output with the variation of solar temperature and irradiance with the variation in climate. The analysis of Grid-connected inverter and their performance at various seasons and conditions is investigated. Solar power plant for a year. In solar power plant efficiency of inverter is also considered to calculate overall losses so, the inverter efficiency and plant performance are considered in this paper using MAT Lab software. In summer season the inverter performed efficiency is decreased because of peak temperature value and slightly increased with the increase in irradiance.

In present scenario, each and every activity in basic lifestyle of people is becoming smarter with the day-to-day flourishing development of technology such as Internet of Things, Artificial Intelligence, Machine Learning and Blockchain. Among the smart improvements, smart city holds the highest rank due to the initiatives provided by the administration. Smart city mission has influenced the citizen’s life with respect to the automation on fundamental needs. Energy resources are considered as one of the important requirements for the survival of people. With the advent of Internet of Things, smart grid systems are designed in order to meet the sustainable demands. It also provides information about the energy resources consumed and alert the consumers about the demand prevails on the resources. Technological improvement is more essential for a country, only if it can be considered and adaptable for sustainable development. Therefore these papers outline the Internet of Things based smart grid which helps in the energy conservation process to meet the future demands. Energy management processes has to be well-versed among the citizens as it helps in understanding the possible ways on storage of energy resources. However, when energy storage is concerned, security issues are the counterpart which has to be focused at higher level. Therefore, blockchain techniques applied for energy storage systems are also outlined along with the applications and future directions of smart grid.

In the present digital world, Information and Communication Technology along with Internet of Things are considered as backbone for the smart city evolution. IoT is concentrated more nowadays, due to the convergence of images on Information Technology and human behaviour known as Operation Technology. It is in the progressing stage with notion on cyber-physical world, where things are facilitated to satisfy feasible needs. Similarly, Internet of Medical Things is gaining attention due to the current COVID-19 situation. It has gifted numerous sensors and devices with the increased accuracy, productivity and reliability to the healthcare industry. Increasing the sensor devices in smart city, results in the handling of large amount of data. Therefore, big data is focused due to their characteristics such as volume, variety, velocity and veracity. Extraction of hidden correlations and insights from data is performed through big data analytics or big data value chain. Such concepts are integrated with Artificial Intelligence and Machine Learning technologies which are more important in collecting the real-time data collection and helps in gaining knowledge on how the smart cities and their applications in health sector evolves to adapt the conditions. The main advantage on Big Data Analytics is that it helps in commonality along with heterogeneity principles. Even though cities are digitalized, urban health is still limited to IoT devices which fetch sensor data, eliminating the inclusion of human anatomy and biological data. Integration of these two data forms will help in attaining the target of Big Data and leads to the contextualized, sustainable and resilient smart cities which renders more living factors. This chapter will focus on role of Big Data in smart health applications which plays a vital role in safeguarding the human lives.

The modeling and development of the boost DC to DC converter with Partial Swarm Optimization with Distinctive Feed Forward Propagation (PSO-DFFP) controller for hybrid power systems including solar panels. The static and dynamic investigation of the developed PSO DEEP controller is presented. The PSO-DFFP controller has been designed to improve the operating efficiency and reduces the input converter current ripple. The PSO DFFP controller is developed and performance is compared with ANFIS and FLC. The developed system reduces the switching losses and voltage drops in switching modes. The designed system is demonstrated and developed with 200W, 100kHz model. The investigation results is exposed that the developed PSO DEEP system is an acceptable for SOLAR applications.

Treatment of wounds, which is being a difcult to treat because of chronic nature in many patients in day-to-day practice. There are so many topical treatments which are being used. In our study we are going to compare the efcacy two different type of dressing to Select and make rapid decisions . Phenytoin and hypochlorous acid are widely used in the management of chronic ulcers, their efcacy in terms of time taken for granulation tissue formation, duration of hospital stay, time taken for complete healing of ulcer and cost effectiveness remains unclear. Hence this study was conducted to compare the outcome of phenytoin or neutral pH hypochlorous acid solution dressings in the management of diabetic and chronic ulcers.

The present investigation entitled “Effect of Different Biofertilizers and Organic Manures on Growth, Yield and Quality of Strawberry (Fragaria×ananassa Duch.) cv. Chandler.” An experiment was conducted at the research field, Department of Horticulture, Allahabad School of Agriculture, Sam Higgibottom Institute of Agriculture, Technology & Sciences, Allahabad during the year 2015-2016, the experiment was laid out in a Randomized Block Design having 12 treatments three replications of bio-fertilizers and organic manure at different levels. The result revealed that treatment T12 (Phosphobacter 5kg/ha + Azatobacter 5 kg/ha + FYM 6 ton/ha + Vermicompost 3 ton/ha + Poultry Manure 3 ton/ha) was found to be best in terms of maximum plant height (19.67 cm), plant spread (26.43cm), number of leaves (18.13), petiole length (4.96 cm), day to first flowering (67.33), number of flowers per plant (16.80), fruit yield per plant (75.94 g), fruit yield per plot (683.46gm), fruit yield per hectare(6.83 t), TSS (8.54 0 B), acidity (0.46%), pH of juice (4.40). Similarly the maximum gross return (1079250 rupees), net return (696022.95 rupees) and benefit cost ratio (2.77:1) for cultivation of strawberry under Allahabad agro- climatic condition. However, since these findings are based on a one-year experiment, additional trials may be required to support them.

The objective of this work was to determine the biological parameters and thermal requirements of Trichogramma chilonis strain reared on Corcyra cephalonica and Plutella xylostella eggs at College of Agriculture, CAU, Imphal, Manipur. The optimum temperature for the parasitism and emergence of T. chilonis was 25°C and the utmost longevity was found at the same temperature. Maximum parasitism was observed 84.14 and 82.71 per cent at 25°C, while minimum parasitism was 76.57 and 69.14 per cent at 20°C on C. cephalonica and P. xylostella eggs, respectively. The results indicate that temperature has a significant effect on the biological parameters of T. chilonis and with increasing temperature developmental duration decreased in laboratory condition of Manipur. On the basis of the present results Corcyra cephalonica eggs was more suitable for mass production of T. chilonis than P. xylostella under controlled conditions.

Salivary duct carcinoma is an aggressive subtype of primary salivary gland carcinoma with advanced stage at presentation, high rates of metastasis and recurrence. It is most commonly seen in parotid gland of older men with microscopic resemblance to high-grade breast ductal carcinoma. Salivary duct carcinoma mainly affects men over 50 years of age and accounts for 5% to 10% of all salivary gland malignancies. Characteristic histomorphology and immunohistochemical expression of Androgen Receptor (AR) aids the diagnosis of salivary duct carcinoma. Fine-needle aspiration typically reveals cytologic features of high-grade carcinoma. Heterologous alterations have been recognized in oncogenes and tumor suppressor genes such as TP53, HRAS, PIK3CA, PTEN, and BRAF as well as AR and HER2. Targeted therapy against these genes may help in broadening treatment options for salivary duct carcinoma. Salivary Duct Carcinoma is one of the most aggressive salivary malignancies with 33% local recurrence and 45% metastasis. We report a case of a 75 years old female patient, who presented with a swelling obliterating the retromandibular groove. FNAC & histopathology confirmed the diagnosis of salivary duct carcinoma.

This article presents the modeling and development of a DC-DC converter with Partial Swarm Optimization with Distinctive Feed Forward Propagation (PSO-DFFP) controller for hybrid power systems, including photovoltaic panels. The transient and dynamic analysis of the proposed controller has been presented. The PSO-DFFP controller has been designed to improve the operating efficiency and reduces the input converter current ripple. The ANFIS and PSO DFFP controllers are developed, and the performance of the system is compared. The proposed system reduces the switching losses and voltage drops in switching modes. The proposed system is demonstrated and developed with a 200W, 100kHz model. From the experimental results, it can be exposed that the proposed system is acceptable for PV applications.

Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) is a Special Scheme launched by Government of India to reach the unreached segment of the population. As Poverty and Unemployment forms a Vicious circle, this becomes impossible to break. The Indian Government’s commitment to meet this issue and break the Vicious circle of Poverty, was headed by Introducing MGNREGA is highly appreciated world-wide. This Paper is an Empirical Study of various levels in Transformation of MGNREGA in Tamil Nadu among the Beneficiaries. The study is based on the secondary data analysis for last 7 years – 2015 to 2022 in specific relation to Socio economic parameters and Fund allocation with Pre Covid19 years and During Covid19 year’s segmentation. This Study reveals that there is a positive transformation, that it has an increase in fund allocation during COVID19 years to provide job to the migrant workers returning to the villages from cities.

Due to the growth of Big Data (BD) storage and access in cloud computing infrastructure, the detection of anomalies for Cloud Servers (CSs) is essential to ensure data confidentiality. Over the past decades, different security systems have been designed based on various methods like encryption, Access Policy (AP) control schemes, signcryption and so on. Among many security systems, a new Improved NTRU (INTRU) decryption based on the AP strategy has been suggested to secure the BD processed by the CSs. Also, the shared secret data was authenticated to defend the clients from anomalies in the cloud. But, the AP upgrade must not degrade the confidentiality of storing information, reveal trust in the CS or cause any different security challenges. It is not considered that such security challenges occur when the data owner shares its data with many CSs. Hence in this article, an INTRU with Detecting Anomalous in CS (INTRU-DACS) system is proposed that employs a deep learning-based Anomaly Detection System (ADS) to handle and secure the BD stored in the CSs. The main goal of this method is to effectively identify the abnormalities in the real world by the conduct utilization, i.e., the System Call Identifier Sequences (SCISs) created from CSs in which these conducts are associated with BD. Initially, effective data summarization is constructed via different feature states to analyze the SCISs of specific durations. After that, an anomaly identification algorithm is proposed to train and test the streaming of raw SC sequences. This observable SCs execution task of CSs is gathered from log files. The variations of such SCISs having a specified duration are random for usual and unusual sequences. So, the fact of current normal and abnormal services is recognized regarding their SCISs. Such normal and abnormal behavioral states are learned from Convolutional Neural Network-Hidden Markov Model (CNNHMM) classifier to identify the anomalies in CSs. But, it is still a challenging process because of the patterns of usual and unusual events. The performance is not effective since it models only the conduct of a huge number of SCISs created from a single CS. As a result, a Secure Access Control Scheme with DACS (SACS-DACS) system is proposed in which a Multidimensional Feature Misbehavior Server Detection method (MFMSD) is introduced for detecting anomalies in multiple CSs. In this method, large-scale SCISs of multiple CSs are extracted, including different features such as network traffic sequence features, CPU energy usage and memory usage from host logs. These extracted multidimensional features are fed to the CNNHMM that identifies the anomalies and maximizes the detection accuracy. At last, the simulation results demonstrate the effectiveness of the SACS-DACS and INTRU-DACS as compared to the INTRU.

Mobile Ad Hoc Networks (MANETs) versatility and portability have made them well known across a wide range of uses. Security conventions for protecting steering and device details have been established to ensure these systems. Those conventions, however, simply secure courses or correspondence, not both. To offer complete protection, both stable steering and communication safety conventions need to be performed. Using communication security conventions which were originally developed for, and Wi-Fi systems, may also place an enormous weight on a MANET's restricted network property. A new protected system (SUPERMAN) is proposed to disclose these problems. The framework is designed to allow present system and steering conventions to play out their capabilities while providing confirmation, control, and security components for correspondence. This paper shows SUPERMAN, a new protection system for MANETs. Results of replication contrasting SUPERMAN and IPsec, SAODV, and SOLSR are provided to demonstrate reasonableness of both the proposed structures for remote correspondence security.

The control system will measure the renewable energy generation power, and if the generated power is equal to the grid power, the generation sources are directly connected to the load system. When the power generation is not at sustaining level, the controller will optimize the source using the DC-DC converter and Battery based Energy management system. The operation of the battery system depends upon the power generation availability of renewable energy resources. During the high power RES, the battery is charging condition. When the RES is low power means the battery is in discharged condition. Also, the fuel cell-based energy compensation will take place when the battery power is low. The Energy router will monitor all the above generation plants based on the threshold values of each power plant, substantial Transformative Energy Management (STEM) Strategy and Resilient Power Flow Control (RPFC) controller takes necessary action like which power plant is connected to the grid power system. The simulation is performed on Mat lab / Simulink simulation platforms, and the results show the effectiveness and reliability of the control strategy for micro-grid interconnection and flexible energy flow correspondence.

This study attempts to analyze the microstructure and interface behavior of aluminum 6061 (Al 6061)-V-grooved stainless steel (SS304) explosive cladding by numerical and experimental methods. Numerical simulation was performed by Smoothed Particle Hydrodynamics (SPH) technique, in ANSYS AUTODYN, and the results are correlated with experimental outcome. The machining of V-grooves on the base plate transform the melted layer formed in conventional cladding (without grooves on the base plate) into a smooth undulating interface, for a similar experimental condition. The flyer plate and collision velocities, observed in numerical simulation, are in good agreement to the analytical expectations. The pressure developed in the flyer plate is higher than the base plate and the maximum pressure is witnessed at the collision point irrespective of grooved base plate or otherwise. The temperature developed in the collision point of conventional explosive cladding exceeds the melting point of both the participant metals, whereas, it exceeds the melting point of aluminum alone, in case of V-grooved base plate cladding. The shear and impact strengths of the V-grooved base plate clads are higher than the conventional clads and the fracture surfaces exhibit mixed modes of fracture.

This article discusses a transformer-free, high-efficiency DC-DC converter besides renewable energy applications. The traditional buck-boost, classic Zeta, Sepic, and Cuk converter does have the benefits of a simple design, low cost, as well as the capacity to execute voltage step-up and step-down. Conversely, because of the detrimental consequences of the parasitic constraints of the device, the voltage conversion gain of the traditional DC-DC converter is much more restricted and the efficiency is also significantly smaller, whereas this proposed converter does have a higher voltage gain and efficiency because it is used in a single power switch, resulting in reduced switching losses and voltage stress. The said converter's design is very simple, which simplifies the operation control and reduces switching and conduction losses, leading to an efficiency of 97.4 percent. This converter seems to have the same capabilities as the Zeta converter, including continuous desired output current and desired buck-boost operation. Such an article offers the operation principle and steady evaluation, as well as a comparison with other existing high step-up configurations. The proposed converter employs a fuzzy logic controller, which improves the voltage level as well as reduces the time taken to set the voltage output of a conventional PI and ANN controller, especially in comparison to the FLC controller. For deployment, Experimental Result and MATLAB/Simulink has been used, and the modeling results indicate that the proposed controller performance has improved