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Private transportation has become a daily need for most people nowadays. Because of the increased use of private transportation by modern society, road accidents have become a major issue. Vehicular communication is one of the methods to reduce the number of dangerous accidents. It is possible to communicate between two vehicles, Known as Vehicle to Vehicle Communication (V2V). Road Side Unit (RSU) is a communication with a specific fixed unit. If communication is established between the vehicle and nearby infrastructure (V2I), accidents can be avoided. Inter Vehicular communication is the term for this type of communication. It also lets vehicles share information such as post-accident investigation, safety information for accident prevention, traffic jams, and many more. Europe and North America are at the forefronts of research to conclude vehicular communication standards. It recognizes technical specification for enabling the communication between vehicles and the road infrastructure and between the various manufacturers. In the existing method, Cloud-based VANET helps to monitor the road condition. Through the connected Vehicular Ad-hoc Network (VANET) and cloud computing technologies, the entities in VANET were able to access the valuable storage and computing services made available by some cloud service provider. The benefits cannot be given away for free because their combination introduces various privacy and security requirements for VANET applications. The authority should monitor real-time road condition using a cloud server, so sound responses to emergencies can be made on time, according to the cloudbased Road Condition Monitoring (RCoM) scenario examined here. Vehicles on site should report information if any dangerous road condition is detected, such as geologic hazards or accidents. Three major issues are discussed in RCoM. An efficient RCoM method was suggested to address these three issues to analyze its efficiency theoretically and to demonstrate its practicality through experiments. They were generated using random numbers and help us in authorization process. So, the malicious vehicles easily identity it. To resolve the issues mentioned above, one Improved Road Condition monitoring system (IRCOM) was initiated. Using the random key generator, the first sub authority delegation is performed, and by using the RSA algorithm, the vehicle registration is attained by generating individual keys. The distribution of the token is based on the individual key and time stamp assigned to each vehicle. Cloud will categorize the received report using the key, token and time stamp. Finally, the route authority will decode the reports and, if necessary, will take the appropriate action.

Machine learning (ML) has been increasingly adopted due to its ability to model complex and non-linearities between river water temperature (RWT) and its predictors (e.g., Air Temperature, AT). Most of these ML approaches have been applied using average AT without any detailed sensitivity analysis of other forms of AT (e.g., maximum and minimum). The present study demonstrates how new ML approaches, such as ridge regression (RR), K-nearest neighbors (KNN) regressor, random forest (RF) regressor, and support vector regression (SVR), can be coupled with Sobol’ global sensitivity analysis (GSA) to predict accurate RWT estimates with the most appropriate form of AT. Furthermore, the proposed ML approaches have been combined with the Ensemble Kalman Filter (EnKF), a data assimilation (DA) technique to improve the predicted values based on the measured data. The proposed modelling framework's effectiveness is demonstrated with a tropical river system of India, Tunga-Bhadra River, as a case study. The SVR has been noted as the most robust ML model to predict RWT at a monthly time scale compared with daily and seasonal. The study demonstrates how ML methods can be coupled with a global sensitivity algorithm and DA techniques to generate accurate RWT predictions in river water quality modelling. HIGHLIGHTS Machine learning models coupled with global sensitivity analysis to predict RWT.; Ridge regression, KNN, random forest, SVR, along with Sobol’ sensitivity analysis were explored.; Maximum AT as the most sensitive variable in RWT prediction.; The SVR as the most robust ML model to predict RWT at monthly time scale.; Application on a tropical river system of India.;

The DC Microgrid sounds familiar in recent days for its independent grid operation and energizing small communities without relying on the central grid. The sudden change in energy demand in the microgrid can negatively impact its performance and operation. Energy management is the only optimal solution to the energy production of microgrids. This article -discusses an economically operated DC microgrid for rural electrification with a tri-port converter based on the radial basis function neural network (RBFNN)-based intelligent control strategy to provide enhanced performance to the microgrid. The advantage of the proposed system is that it provides optimal energy management solutions during dynamic loading conditions and enhances the operation of the microgrid. The outstanding aspect of the proposed system is that it boosts the conversion operation and effectively manages the battery energy storage system to supply energy to the domestic loads and supply power to the grid during excess power generation. In the assessment, the rural regions of Tamilnadu and Andhra Pradesh, India, have been considered to enhance the microgrid setup. The performance evaluation of the proposed system has been conducted and validated using an experimental setup. The assessment also discusses the economic and environmental analysis in using the proposed system. The results support the performance and efficiency of the proposed model.

The efficiency of a graph embedding problem when simulating one interconnection network in another interconnection network is characterized by the influential parameter of wirelength. Obtaining the minimum wirelength in an embedding problem determines the quality of that embedding. In this paper, we obtained the convex edge partition of 3-Ary n-Cubes and the minimized wirelength of the embeddings of both 3-Ary n-Cubes and circulant networks.

Abstract High quality silver (Ag) decorated CeO2 nanoparticles were prepared by a facile one-step chemical method. The samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), High resolution transmission electron microscopy (HR-TEM), fourier transform infrared spectrometer (FT-IR), electron paramagnetic resonance (EPR), X-ray photoelectron spectroscopy (XPS), UV–Visible absorption (UV–Vis), photoluminescence (PL) and thermogravimetric analysis. The decoration of Ag on CeO2 surface was confirmed by XRD, EPR and HR-TEM analysis. Harmful textile pollutant Rose Bengal dye was degraded under sunlight using the novel Ag decorated CeO2 catalyst. It was found that great enhancement of the degradation efficiency for Ag/CeO2 compared to pure CeO2, it can be ascribed mainly due to decrease in its band gap and charge carrier recombination rate. The Ag/CeO2 sample exhibited an efficient photocatalytic characteristic for degrading RB under visible light irradiation with a high degradation rate of 96% after 3 h. With the help of various characterizations, a possible degradation mechanism has been proposed which shows the effect of generation of oxygen vacancies owing to the decoration of Ag on the CeO2 surface.

Background & objectives: Malaria is a serious public health problem in Car Nicobar Island, Andaman & Nicobar Islands, India. Using larvivorous fishes has proved to be the cheapest method for vector management approach, with long suppression of mosquito population. This study aims to scale-up the diversity of larvivorous fishes and their potential larvivoracity to evolve an appropriate biological intervention strategy against the immature stages of malaria vectors. Methods: During 2003 (pre-tsunami) and 2014–2016 (post-tsunami), an ecological descriptive survey was carried out in the water bodies around Car Nicobar Island. Fishes were captured using fishing nets and cast nets; and placed in plastic jars and preserved in formalin solution. Fishes were identified and classified according to the available keys. Their abundance and data on the current conservation status was recorded and analyzed. Their potential larvivoracity was graded according to their feeding intensity. Results: Pre-tsunami, a total of 27 larvivorous fish species belonging to 11 orders, 23 families and 23 genera were identified. Order Perciformes and the family Cyprinidae were the most ascendant group constituting 51.9 and 11.1%, respectively. While, 80.8% of species were preferred to inhabit the freshwater region, only 37% of species were surface feeders (SF). According to the conservation, assessment and management plan (CAMP, 1998), 44.4% species were at lower risk least concern (LRlc), while 55.6% species were at least concerned (LC) as per the IUCN, 2017 categorization. However, after the tsunami, 17 fish species had gone extinct and 10 fish species were found to remain alive in the local water bodies. Interpretation & conclusion: Post-tsunami, the larvivoracity analysis indicated that Ophiocara aporos, Ophiocara procephala, Valamugil seheli, Channa punctata, Kuhlia rupestris, Khulia mugil, and Terapon jarbua possess high-level larvivorous potentiality in nature and are recommended for vector control in the study area. These fish species were facing several anthropogenic threats, such as human interference, loss of habitat, trade, overexploitation, and fishing. Therefore, it is important to protect the water bodies from external impact and implement the conservation strategies. Further, periodic fish fauna surveys, identification of breeding sites, scale-up of the larvivorous potentiality at the field level, creating public awareness through health education on establishment of larvivorous fish ponds and planning for mass rearing of the native fish species should be adopted as part of vector management approach in the endemic malarious region of Car Nicobar Island.

The virulence factors of dermatophytes play a vital role in the etio-pathogenesis and emergence of drug resistance. Regular surveillance is essential for constant monitoring of association of virulence factors in the emergence of drug resistant isolates and to guide proper therapeutic strategies to combat infections due to drug resistant isolates of dermatophytes. The aim of this study is to isolate and identify various enzymatic and non-enzymatic virulence factors of dermatophytes isolated from clinically suspected cases of dermatophytosis attending the dermatology outpatient clinic. From 30 clinical samples received from department of Dermatology to the department of Microbiology during the study period July to December 2019, KOH mount and fungal culture was done and only the isolates which grew dermatophytes were used for detecting virulence factors using standard methods. Among 30 affected patients, 13 were male (43.3%) and 17 were female (56.7%) with age range of 13 to 60 years. Skin sample yielded positive growth in 96.6% of the cases. Out of 30 samples, 6 samples were positive for Trichophyton mentagrophytes. Tinea corporis was the common manifestation which yielded positive growth. Female predominance was seen. Male predominance was seen in younger age group while females were more commonly affected in older age group. Adolescents were commonly affected age group (40%). Then people between age 41-50 (middle age group) were mostly affected. The six Trichophyton mentagrophytes were found to have enzymatic and non- enzymatic virulence factors. All the virulence factors included in the study were present in Trichophyton mentagrophytes.

The effect of reinforcing natural fiber in the form of woven fabric on dynamic mechanical and thermogravimetric analysis was investigated. Further the influence of water molecule interaction on dynamic mechanical analysis of natural fiber composite were studied. Results revealed that basket type and intra-ply hybridized composites enhances the dynamic mechanical properties of the composites due to the enhancement in modulus by the reinforcement, whereas herringbone composites enhance the loss factor of the composites. It was noticed that, irrespective of the weaving architecture and intra-ply hybridization, composite samples immersed in the water for 45 days affects the storage and loss modulus of the composite and to enhance the loss factor. Thermogravimetric analysis carried out on composites revealed that, compared to weaving architecture, the presence of cellulose and hemicellulose in the fiber cell wall influences the thermal properties of the composites.

A high yielding and early maturing prosomillet culture TNPm 230 was developed at the Centre of excellence, Athiyandal, Tamil Nadu Agricultural University and released TNPm 230 as ATL1at national level. It is a derivative of the cross involving TNAU 164 x IPM 19. It yields on average grain yield of 2152 kg/ha and straw yield of 5970 kg/haunder rainfed condition. This variety has registered 12 and 15 per cent increased grain yield over the checks TNAU145 and GPUP 21 respectively in All India Coordinated trials. Proposed variety has given Eight and 11 per cent increased grain yield over the qualifying varieties TNPm 228 and DHPrMV 2721 respectively. TNPm 230has semi-compact panicle, bold seeds and exhibited better grain quality than the checks; on par for a response to agronomic practices, susceptible to banded blight in AP only. Therefore, the entry TNPm 230 as ATL1 is recommended for the national level release except in Andhra Pradesh.

In the current work, the authors aim to present an insight on the role of cobalt (Co) doping for the structural, morphological, and linear and nonlinear optical (NLO) properties of CdO thin films. The films were prepared using the spray pyrolysis (SP) technique, and the weight % of Co (x) was varied from 0–10. The structural properties of the films were confirmed by the powder X-ray diffraction (P-XRD) studies and are polycrystalline with a cubic structure and a lattice parameter of 0.4658 nm. As Co content in CdO films increases, cluster grain size and porosity decrease significantly, as seen in surface topographic and nanostructural analysis. Through the Burstein–Moss shift, the optical band gap “Eg” in Co: CdO film decreases from 2.52 to 2.05 eV with the increase in Co-doping. To study the NLO parameters, open aperture (OA) and closed aperture (CA) Z-scan measurements were performed using the diode-pumped solid-state continuous wave laser excitation (532 nm), and with the increased Co-content, the NLO parameters—nonlinear absorption coefficient (β∼10−3 cm/W), nonlinear refractive index n2 ∼10−8 cm2/W), and the 3rd-order NLO susceptibility χ3∼10−7 to 10−6 e.s.u.) values were determined and found to be enhanced. The maximum NLO parameters achieved in the present study with increasing Co concentration on CdO nanostructures prepared by the SP method are found to be the highest among the reported values and suggest that processed films are a capable material for optoelectronic sensor applications.

The current exploration work focuses on the fabrication of aluminum 7075 matrix composites built up with different weight levels of titanium carbide particles by a traditional stir casting process. In particular, the combination of high hardness and flexible modulus, low density, great wettability, and low synthetic reactivity with aluminum melt makes TiC particle an attractive material. From 0% to 6 wt.% of reinforcement is introduced in steps of 3 wt.%. Aluminum matrix composites are studied in depth to learn more about their microstructures and mechanical properties. TiC particles were uniformly dispersed in the aluminum lattice, as shown by scanning electron micrographs of the material’s microstructure. As the weight of the TiC particles in the aluminum lattice increases, so does the density of the composites. The X-ray diffraction technique has also been used to detect the phase of TiC particles. As the amount of TiC particles in the aluminum matrix increases, the material’s mechanical properties, such as ultimate tensile strength and hardness, increase at the expense of ductility. The preorganized composites have also undergone fractography testing.

A high yielding and early maturing Samai TNPsu 177 was developed at the Centre of Excellence In Millets, Tamil Nadu Agricultural University, Athiyandal and released as ATL 1. It is a derivative of CO(Samai) 4 x TNAU 141 with 1587 kg/ha grain yield and 3109 Kg/ha of straw yield in 85-90 days under rainfed condition. Being a short duration variety, this variety fits well in the existing double cropping rainfed condition of North, North western and western zones of Tamil Nadu. Samai is grown in June- July as a preceding crop to horsegram in more than 80,000 ha. It has yield advantage of 11.2 and13.7 percent for grain yield while11.8 - 14.4 percent for straw yield over the check varieties viz.,CO(Samai) 4 and Paiyur 2. Samai line TNPsu 177 has strong and sturdy culm with long, semi-compact panicles and drought tolerance. The plant has 6- 8 productive tillers and non-shattering grains. It has special attributes like easy threshability, synchronous maturity and nonlodging growth habit. The grains are bold with attractive golden yellow colour. In view of stable yield performance across seasons and locations, special attributes and drought tolerance, Samai TNPsu 177 is proposed for release as ATL 1 to fulfill the long felt need of the drylands, hilly and tribal areas in Dharmapuri, Thiruvannamalai, Vellore, Salem and Krishnagiri districts of Tamil Nadu where samai is predominantly grown under rainfed condition

The trend of using e-learning as a teaching tool is now rapidly expanding into education. Although e-learning environments are becoming popular there is minimal research on the impact of e-learning on the teachers. The purpose of this study is to develop a tool to measure the impact of e-learning on the teachers' of higher education in the Indian scenario. Initially the tool was constructed with 53 statements and administered to 300 teachers of Higher Education. Out of these 53 statements 17 statements focused on personal effectiveness, 21 statements focused on teaching skills and 15 statements focused on research and academic work. In order to standardize the tool the researcher applied Kolmogorov-Smirnov test, Cronbach Alpha test, Correlation and 't' test. After the item analysis 30 statements were selected with the dimensions personal effectiveness (10), Teaching skills (13) and Research and Academic work (7).

Background: Pakur district of Jharkhand state is highly malaria-endemic areas in eastern India, mainly inhabited by Sauria Paharia, a primitive and vulnerable tribal group. Methods: An epidemiological, entomological and malaria-related community-based education; and evaluation of the operational strategies for malaria interventions were performed in eight vulnerable forests-fringed tribal villages in the Pakur district of Jharkhand, India. Results: Of the 217 confirmed malaria infections, P. falciparum (92.2%), P. vivax (7.8%), and mixed-species infections (6.9%) were found. The SPR, SFR and Pf% ranged from 23.8 to 68.2, 23.8–64.8 and 84.2–100.0, respectively. An. culicifacies, An. annularis, An. fluviatilis and An. minimus became the primary vectors of malaria. Insecticidal susceptibility status indicates An. culicifacies and An. annularis resistance to DDT (4%); and An. culicifacies, An. annularis and An. fluviatilis susceptible to malathion (5%) and deltamethrin (0.05%). Most residents, including health staff, had excellent knowledge of malaria but did not adopt appropriate prevention steps. Many accredited social health activist workers have not trained to diagnose and treat malaria cases, nor have rapid diagnostic test kits and antimalarial drugs been available, resulting in the tribal community adopting traditional treatments and native remedies. Conclusion: High vector abundance, presence of parasite load, deficiency of prevention practices; and lack of early detection and prompt treatment and vector control strategies indicate that the population living in these provinces is more vulnerable to malaria. Therefore, periodic surveillance, monitoring, and evaluation are also needed to enhance the implementation of malaria interventions in this region.

The article focuses on the extraction and validation of Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) over Samastipur district of Bihar, India, using in situ measurements and remote sensing techniques. Topics include the significance of LST in surface energy budget assessment, the application of Global Land Data Assimilation System (GLDAS) LST product in agricultural studies, and the development of a satellite-derived LST and in situ measurements.