Spread Spectrum based QoS aware Energy Efficient Clustering Algorithm for Wireless Sensor Networks

Wireless sensor networks (WSNs) are composed of small, resource-constrained sensor nodes that form self-organizing, infrastructure-less, and ad-hoc networks. Many energy-efficient protocols have been developed in the network layer to extend the lifetime and scalability of these networks, but they often do not consider the Quality of Service (QoS) requirements of the data flow, such as delay, data rate, reliability, and throughput. In clustering, the probabilistic and randomized approach for cluster head selection can lead to varying numbers of cluster heads in different rounds of data gathering. This paper presents a new algorithm called "Spread Spectrum based QoS aware Energy Efficient Clustering for Wireless sensor Networks" that uses spread spectrum to limit the formation of clusters and optimize the number of cluster heads in WSNs, improving energy efficiency and QoS for diverse data flows. Simulation results show that the proposed algorithm outperforms classical algorithms in terms of energy efficiency and QoS

Multivariate Analysis to Study Genetic Diversity for Yield and its Attributing Traits in Rice (Oryza sativa L.)

The present investigation was carried out with 72 germplasm lines and three checks of rice (Oryza sativa L.) were grown at Crop Research Station, Masodha conducted in the GPB farm, Acharya Narendra Deva University of Agriculture and Technology, Kumarganj, Ayodhya (U.P.) during Kharif June 2022- February 2023. Data on 10 characters, including grain yield per plant focused on diversity and PCA analysis. This investigation involved the analysis of 72 rice germplasm lines alongside three checks, showcasing extensive variation in agronomic and morphological traits. The study utilized Non-hierarchical Euclidean cluster analysis to assess genetic diversity. The pseudo F-test determined the optimal grouping of 75 genotypes into six distinct clusters. Cluster distribution revealed varying genotype compositions, with Cluster V comprising the highest entries (20), followed by Clusters I, VI, and II. Intra- and inter-cluster distances illustrated significant variability among clusters, emphasizing genetic diversity. Examining agronomic traits across these clusters revealed noteworthy variations in days to 50% flowering, days to maturity, plant height, and productive tillers. Panicle length, flag leaf area, biological yield, harvest index, 1000-grain weight, and grain yield per plant also exhibited cluster-specific variations. These findings provide valuable insights for rice breeding programs, facilitating targeted enhancements of specific agronomic traits within the rice population, thus contributing to the development of more resilient and productive rice varieties

Molecular docking and dynamics identify potential drugs to be repurposed as SARS-CoV-2 inhibitors

The novel coronavirus disease 19 (COVID-19) has resulted in an estimated 20 million excess deaths and the recent resurgence of COVID-19 in China is predicted to result in up to 1 million deaths over the next few months. With vaccines being ineffective in the case of immunocompromised patients, it is important to continue our quest for safe, effective and affordable drugs that will be available to all countries. Drug repurposing is one of the strategies being explored in this context. Recently, out of the 7817 drugs approved worldwide, 214 candidates were systematically down-selected using a combination of 11 filters including FDA/TGA approval status, assay data against SARS-CoV-2, pharmacokinetic, pharmacodynamic and toxicity profiles. These down-selected drugs were subjected in this study to virtual screening against various SARS-CoV-2 targets followed by molecular dynamics studies of the best scoring ligands against each target. The chosen molecular targets were spike receptor binding domain, nucleocapsid protein RNA binding domain and key nonstructural proteins 3, 5 and 12–14. Four drugs approved for other indications — alendronate, cromolyn, natamycin and treprostinil — look sufficiently promising from our in-silico studies to warrant further in-vitro and in-vivo investigations as appropriate to ascertain their extent of antiviral activities

Soil Nutrient Based Mobile App for Crop-wise Fertilizer Recommendation: A “SoilNutro” Application

Agriculture is the most important occupation for most Indian families in India. A relatively larger Indian population lives in rural areas. The majority of rural people depend on agriculture for their livelihood. Therefore, it is the responsibility of the government and information technology to provide relevant information related to agricultural technologies for better crop production so that farmers can feed India's growing population. Soil fertility refers to the ability of soil to sustain agricultural plant growth. The farmer needs to know the soil fertility of soil of their farm holding that soil is either capable of better crop production or not. Therefore, it is very necessary to know soil health for increasing crop production and reduce the cost of production. The available nutrient content is an important parameter to determine soil health. Nitrogen (N), Phosphorus (P), and Potassium (k) are major nutrients that are needed in the crop field with large amounts in the form of fertilizers. In the technology front, we all are aware that the mobile phones have become one of the major sources of communication technologies in developed and developing countries in the last few decades. With the realization of this fact about the use of smartphones, the development of a mobile application called ‘SoilNutro’ has been done. SoilNutro app has been developed to achieve the nutrient status of a specific location of users. It also recommends the combination of fertilizer doses required for crops based on current nutrient status for efficient use of various fertilizers. ‘SoilNutro’ app has been developed using minimum SDK version of API 24: Android 7 on the android platform. The developed Android application 'SoilNutro' will be of great use to provide farmers with a specific location of nutrients and recommend crop-wise fertilizer based on the available nutrient