Wave-Atom and Cycle-Spinning-Based Noise Reduction in Mammography Images

Image denoising is crucial in medical image processing. Digital mammography depends significantly on de-noising for computer-aided-detection of malignant cells like Microcalcifications. In this work, we proposed an unique hybrid approach to reduce Gaussian noise in digital mammograms by combining the wave-atom translation and cycle spinning methods. Pictures denoised by thresholding of coefficients would produce pseudo-Gibbs events because wave atoms are not translationally invariant. Circular motion is applied to keep away the artefacts. Experimental results clearly establish that the method is effective at filtering out background noise while maintaining the integrity of edges and enhancing picture quality. Mini-Mias pictures with variable quantities of Gaussian Noise are used to evaluate and analyse the performance using peak signal-to-noise ratio and structural similarity index.  The provided technique outperforms several current filters in terms of evaluated results of peak signal-to-noise ratio and structural similarity index

Studies on biosorption of nickel using immobilized fungus, Rhizomucor tauricus

Rhizomucor tauricus, an industrial fungus, was immobilized in sodium alginate and used as adsorbent for the removal of nickel from aqueous solutions. The biosorption capacity of Ni(II) was found to be 394 mg/g of immobilized biomass. It was observed that an increase in pH from 3 to 6 increased the percent adsorption, and an increase in liquid-to-solid ratio from 2 to 10 increased the metal uptake. The percent adsorption was increased when increasing the initial metal concentration from 25 to 100 mg/L. The equilibrium biosorption data was evaluated by Langmuir, Freundlich, and Langmuir-Freundlich (L-R) isotherm models, and was best described by the Langmuir and Freundlich isotherms. FTIR analysis revealed that –NH (bending), C–H (stretching), C=O (stretching), and –OH functional groups were mainly responsible for Ni(II) biosorption. Thus, this study demonstrated that the immobilized Rhizomucor tauricus biomass could be used as an adsorbent for the treatment of Ni(II) from aqueous solution

Bio-inoculated Nutrient Management Influence on Soil Nutrient Availability Pattern and Growth of Hybrid Pigeonpea (ICPH 2740) under Establishment Methods and Crop Geometry

Background A two-year field study was conducted at the ICRISAT research farm during the rainy seasons of 2021 and 2022 to investigate the impact of crop geometry, crop establishment method and sustainable nutrient management practices on nutrient availability pattern and growth of hybrid pigeon pea. Methods The experiment followed a split-split plot design. The collected data was analysed using radar graph and heat maps for nutrient availability and dry matter respectively. Result Data revealing that transplanted plots registered higher nutrient availability and proportionate root and total dry matter production at various growth stages. Among plant geometry the root and total dry matter production was higher with 100×100 cm. when considering planting methods, transplanting with a square system of 100×100 cm, combined with an integrated nutrient management approach consisting of 150% (or) 100% soil test based NPK, vermicompost at a rate of 5 t ha-1, phosphate-solubilizing bacteria (PSB) and seed treatment with Rhizobium, resulted in average of 31.5% higher dry matter production over alone inorganic nutrient management practices. Thus, a square geometry of 100×100 cm, along with sustainable integrated nutrient management (100% soil test based NPK, vermicompost at a rate of 5 t ha-1, PSB and seed treatment with Rhizobium), resulted in higher nutrient availability and dry matter production. These findings highlight the importance of careful selection of planting methods, crop geometry and nutrient management practices for maximizing the nutrient mining for production of high dry matter production of hybrid pigeonpea

Securing IoT Devices from DDoS Attacks through Blockchain and Multi-Code Trust Framework

In an era where IoT devices are integral components of numerous systems, their security from prevalent DDoS attacks has become imperative. The traditional security protocols are unable to withstand the sophisticated nature of these attacks, presenting an escalating vulnerability issue in the network security ecosystem. This research proposes a revolutionary approach to address these challenges through a “Blockchain and Multi-Code Trust Framework” utilizing the “UNB IoT DDoS Data Set.” Leveraging the decentralized and immutable characteristics of blockchain technology, alongside a multi-code driven trust mechanism, this framework aims to create a secure, robust, and resilient environment for IoT devices. Our methodology capitalizes on blockchain's transparency to foster trust and validation in network transactions, significantly reducing the threat surface for DDoS attacks. Furthermore, the incorporation of a multi-code system intensifies the security measures, providing several layers of protection against potential breaches. Data sets used in this study encompass diverse real-world IoT network traffic, meticulously collected from the “UNB IoT DDoS Data Set,” to facilitate a comprehensive analysis of the system's performance under various attack scenarios. Our preliminary findings indicate a remarkable improvement in the security posture of IoT devices, exhibiting a substantial reduction in successful DDoS attacks, thereby achieving a new pinnacle in IoT security. This research not only proposes a robust solution to a pressing issue but also opens avenues for further innovations in IoT device security using blockchain technology

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Not AvailableTo assessthe determinants oftechnology adoption by sunflower farmers towards improved sunflower production technologies, a study was conducted in Akola district of Maharashtra. The assessment was done on a comparative basis between 60 each of farmers who participated in the frontline demonstrations (FLDs) organized by Crop Research Unit, Dr.Panjabrao Deshmukh Krishi Vidyapeeth (PDKV), Akola, Maharashtra (FLD farmers) and farmers who did not participate in the FLD programme but belong to the same villages wherein FLDs were organized (non-FLD farmers). The respondents were selected through multi-stage random sampling procedure. There was highly significant difference between FLD and non-FLD respondents with respect to their adoption behaviour and sunflower productivity. There was significant difference among non-FLD farmers with small, medium and large size of land holdings with respect to their adoption behaviour and sunflower productivity, while there was no such difference was observed among the FLD farmers. Most of the non-FLD farmers had low to medium level of sunflower productivity, while most of the FLD farmers had medium to high level of sunflower productivity. Overall, there was 11% mean seed yield increase obtained by the FLD farmers over that of non-FLD farmers with ` 2254/ha additional net returns. The personal, socio-economical, biotic and abiotic determinants of sunflower production and perceived information needs were assessed and the strategies for improving the sunflower production scenario in the study area were suggested.Not Availabl