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Breeding for disease resistance in plants is an integral part of integrated disease management, which helps develop resistance against devastating plant diseases and reduces yield losses. The present study focuses on characterizing the Cercospora leaf spot (CLS) resistant genotypes through simple sequence repeats (SSR) markers linked to CLS resistance. Two hundred sixty-one mung bean genotypes were screened against CLS resistance from 2018 to 2020 under field conditions with a completely randomized block design. Further, six susceptible and six resistant genotypes were tested along with a susceptible check, artificially inoculated with the pathogen to induce disease, and screened through SSR markers to identify the CLS-resistant genotypes. Out of 10 reported CLS-linked SSR markers, seven markers i.e. CEDAAG002, CEDC050, CEDG037, CEDG084, CEDG150, VR108, and VR393, have been validated and confirmed to show polymorphism with different DNA banding patterns in resistant and susceptible genotypes. The extent of polymorphism analyzed, SSR markers such as CEDG084 (71.42%), CEDG150 (50%), VR108 (85.71%), and VR393 (50%) showed higher polymorphism than other markers, which may serve as promising markers for identification of CLS resistance source.

Directing Aβ42to adopt a conformation that is free from aggregation and cell toxicity is an attractive and viable strategy to design therapeutics for Alzheimer's disease. Over the years, extensive efforts have been made to disrupt the aggregation of Aβ42using various types of inhibitors but with limited success. Herein, we report the inhibition of aggregation of Aβ42and disintegration of matured fibrils of Aβ42into smaller assemblies by a 15-mer cationic amphiphilic peptide. The biophysical analysis comprising thioflavin T (ThT) mediated amyloid aggregation kinetic analysis, dynamic light scattering, ELISA, AFM, and TEM suggested that the peptide effectively disrupts Aβ42aggregation. The circular dichroism (CD) and 2D-NMR HSQC analysis reveal that upon interaction, the peptide induces a conformational change in Aβ42that is free from aggregation. Further, the cell assay experiments revealed that this peptide is non-toxic to cells and also rescues the cells from the toxicity of Aβ42. Peptides with a shorter length displayed either weak or no inhibitory effect on Aβ42aggregation and cytotoxicity. These results suggest that the 15-residue cationic amphiphilic peptide reported here may serve as a potential therapeutic candidate for Alzheimer's disease.

As diabetic retinopathy (DR) is considered as most common infectious diseases in humans, more researches have been already proposed under various aspects, yet the attainment of accurate DR detection seems to be an issue. This paper intends to develop an innovative contribution by introducing a novel DR detection model, and further the proposed model tells the severity of retinopathy from the given input fundus image. The proposed model comprises of stages such as Segmentation, Feature Extraction and Classification. Here, Active contour model is used for segmentation; also the GLCM and GLRM features are extracted during feature extraction process. Moreover, the classifier called neural network (NN) is used for classification purpose. As a main contribution, the extracted features (feature selection), and weight in NN model are optimally chosen by a new hybridised algorithm called whale with particle swarm optimisation (WP), which compares its performance over other conventional methods for analysis purpose.

The robot inverse kinematic controller does not give the shut frame arrangement. Henceforth Mechanical controller can accomplish end effectors position in more than one arrangement. To accomplish correct arrangement of the joint angle has been the fundamental worried in the research work. In this paper the analytical solution has been done using D-H method. The method gives 6 DOF industrial robot with D-H Parameter value, which will be the best uses for any inverse kinematics algorithm. Levenberg-Marquardt algorithm is used to solve inverse kinematic of 6-DOF industrial robot arm and the result has been simulated with different soft computing method like ANN and fuzzy logic. A comparison is taken between both the result obtain from different sources.

Diabetic retinopathy (DR) is a health issue which curtailed from diabetes for over long periods. When symptoms are rigorous, the patient might be blinded. The only way to avoid this problem is screening by an ophthalmologist. Anyhow, the automated detection utilises more time, and in addition, it includes several experts. Hence, this paper intends to propose a new diagnosis model of DR, which determines the severity of retinopathy. This model exploits three stages including segmentation, feature extraction, and classification. Here, density-based spatial clustering model (DBSCAN) is exploited for segmentation process, where it segments the abnormalities of retina. Coming to the feature extraction stage, this paper proceeds to extract the GLCM and GLRM features from the given input fundus image. Exclusively, it aims at a subjective contribution, i.e., the required features are optimally selected in this phase. Finally, for classification, this paper deploys a renowned neural network (NN) model. As the second contribution, the weight in NN model is optimally chosen. The optimal issues (selection of optimal features and weights) are successively solved by a new self-adaptive grey wolf optimisation (SA-GWO) approach. Moreover, the proposed method is evaluated with other conventional schemes, and the outcomes are obtained.

Sodium chloride tolerant organogenic callus lines of Nicotiana tabacumwere developed in vitroon Murashige and Skoog [16] medium supplemented with BA, IAA and different concentration of NaCl. The maximum shoot bud regeneration was achieved from both tolerant and non-tolerant calluses on MS medium supplemented with 1.0 mg/1 BA, 0.1 mg/1 IAA with or without NaCl within 4 weeks of culture. Standard growth parameters such as fresh weight and dry weight of organogenic callus, growth tolerant index and enzyme activity (peroxidase and catalase) were used as indicators of salt tolerance. The growth tolerance index in the 4-week after the beginning of treatments yielded significant differences among the non-tolerant and tolerant organogenic callus lines. The regenerated shoots were rooted on half-strength MS basal salts supplemented with 2% sucrose but devoid of growth regulator. The regenerated plants from tolerant callus lines were capable of growing in vitro in presence of 175 niM NaCl. SDS-PAGE profile showed that the progenies derived from tolerant sources were tolerant to salt. This investigation may help in the selection and characterization of salt tolerance in plant improvement programme.

The effect of fiber orientation, concentration and L/D ratio on the mechanical properties of short polyester fiber-natural rubber composites have been studied. High anisotropy in the mechanical properties were observed with respect to fiber orientation. Tensile strength, tear resistance and compression set were higher in the longitudinal direction than in the transverse direction. Hardness and abrasion resistance increased and resilience decreased on increasing fiber concentration. However increasing fiber length to diameter ratio (L/D), decreased the anisotropy in tensile and tear properties at 30 phr fiber loading.

The study undertaken corroborates two important aspects of the short nylon-6 fibre reinforced natural rubber composites. Effect of fibre loading on the tear, hardness and abrasion resistance is positive in the sense that it enhances these properties where as tensile strength increases only in the longitudinal orientation of fibres. The hysteresis properties and ultimate elongation are adversely affected. Secondly, an increase in the size of the fibres has mixed effect on the mechanical properties like tensile, abrasion, set and heat build up, where as tear strength improves in longitudinal orientation of the fibres. There exists a critical loading of fibres beyond which the mechanical properties of the composites decrease because of ineffective bonding of fibres with the rubber matrix.

In continuation of our endeavor to develop synthetic resins of improved properties and performance, we report here the synthesis of mixed copolymer resins by the condensation of resorcinol, aniline, and formaldehyde with ortho-, meta-, and para-phenylenediamine separately. The resins were characterized by infrared (IR) and thermogravimetric analysis (TGA). The mixed copolymer resins were found to have superior thermal stability over conventional phenol–CH2O and resorcinol–CH2O resins. The solubility behavior of the resins showed that they are resistant to common solvents. However, they are soluble in concentrated H2SO4 and HNO3, but insoluble in concentrated HCl. © 1998 John Wiley & Sons, Inc. J Appl Polm Sci 68: 2183–2187, 1998

In this article, we report the transesterification of coir with n-Butyl acrylate (BA) and methyl acrylate (MA) under appropriate reaction conditions using NaOH and/or pyridine (Py) as catalyst. The modified vinylog coir was subsequently cured with benzoylperoxide (BPO) in acetone at 50–60°C. The modified fibers were characterized by Fourier transform infrared (FTIR) spectroscopy. Transesterification and curing of transesterified coir lowered the percentage of moisture regain and imparted improved tensile strength and resistance to common chemical reagents. © 1997 John Wiley & Sons, Inc. J Appl Polym Sci 64: 2283–2291, 1997

Rapid growth of Diabetes mellitus in people causes damage to posterior part of eye vessel structures. Diabetic retinopathy (DR) is an important hurdle in diabetic people and it causes lesion formation in retina due to retinal vessel structures damage. Bright lesions (BLs) or exudates are initial clinical signs of DR. Early BLs detection can help avoiding vision loss. The severity can be recognized based on number of BLs formed in the color fundus image. Manually diagnosing a large amount of images is time consuming. So a computerized DR grading and BLs detection system is proposed. In this paper for BLs detection, curvelet fusion enhancement is done initially because bright objects maps to largest coefficients in an image by utilizing the curvelet transform, so that BLs can be recognized in the retina easily. Then optic disk (OD) appearance is similar to BLs and vessel structures are barriers for lesion exact detection and moreover OD falsely classified as BLs and that increases false positives in classification. So these structures are segmented and eliminated by thresholding techniques. Various features were obtained from detected BLs. Publicly available databases are used for DR severity testing. 260 fundus images were used for the performance evaluation of proposed work. The support vector machine classifier (SVM) used to separate fundus images in various levels of DR based on feature set extracted. The proposed system that obtained the statistical measures were sensitivity 100%, specificity 95.4% and accuracy 97.74%. Compared to existing state-of-art techniques, the proposed work obtained better results in terms of sensitivity, specificity and accuracy.