SSR marker based DNA fingerprinting and diversity study in rice (Oryza sativa. L)

The genetic diversity and DNA fingerprinting of 15 elite rice genotypes using 30 SSR primers on chromosome numbers 7-12 was investigated. The results revealed that all the primers showed distinct polymorphism among the cultivars studied indicating the robust nature of microsatellites in revealing polymorphism. Cluster analysis grouped the rice genotypes into 10 classes in which japonica types DH-1 (Azucena) and Moroborekan clustered separately from indica types. Principal component analysis was done to visualize genetic relationships among the elite breeding lines. The results were similar toUPGMA results. Based on this study, the larger range of similarity values for related cultivars using microsatellites provides greater confidence for the assessment of genetic diversity and relationships. The information obtained from the DNA fingerprinting studies helps to distinctly identify andcharacterize 9 varieties using 18 different RM primers. This information can be used in background selections during backcross breeding program

Unravelling Seasonal Shifts: Exploring Carbon and Nitrogen Stable Isotope Signatures in Zooplankton of Kakinada Bay, Andhra Pradesh, India.

The present study focused on the seasonal variability of carbon and nitrogen stable isotopic signatures in zooplankton collected from Kakinada Bay. Physiochemical parameters of the bay, such as temperature, salinity, nitrates, nitrites, dissolved nutrients, phosphates, and chlorophyll a, were evaluated. The isotopic ratios of carbon and nitrogen in zooplankton and POM were determined using an isotope-ratio mass spectrophotometer. The δ13C values of zooplankton and POM were higher in Kakinada Bay, indicating enrichment of δ13C in primary production. The δ15N values of zooplankton ranged from 8.17 to 9.58, with the highest values observed during the monsoon season. The study provides insights into the trophic structure and anthropogenic influences on the marine ecosystem in Kakinada Ba

Congestion Management Using an Optimized Deep Convolution Neural Network in Deregulated Environment

The technical issue of congestion, which is predominantly found in deregulated power systems, is caused by the failure of transmission networks to satisfy load power demands. This failure is primarily caused due to an increase in loads or loss of transmission lines or generators in modern restructured power networks. This work introduces a CM approach using Deep Convolution Neural Network (DCNN) for minimizing congestion and supporting Independent System Operators (ISOs). The purpose of the work is to generate enhanced prediction outputs for congestion management with reduced error values. These objectives were achieved through the actual power rescheduling of generators. The proposed work adopts DCNN which is optimized using an Improved Lion Algorithm (LA) and aids in providing significant outcomes for congestion management with reduced error. By implementing customized IEEE 57-bus, IEEE 30-bus, and IEEE 118-bus test systems, the suggested approach has been successfully verified for its performance on test systems of varied sizes. This analysis incorporates restrictions such as line loads, bus voltage influence, generator, line limits, etc. The most important results for the test system indicating convergence profile, congestion cost, and change in real-power and voltage magnitude are obtained by the simulation in MATLAB, and on the basis of the obtained simulation outcomes, it is evident that the proposed Improved Lion Algorithm optimized Deep Convolution Neural Network displays phenomenal computation performance in minimizing congestion losses at minimum congestion costs. When compared to several contemporary optimization techniques, the suggested technique performs better in terms of congestion cost and losses by generating improved prediction outputs with reduced errors

Bflier's: A Novel Butterfly Inspired Multi-robotic Model in Search of Signal Sources

The diversified ecology in nature had various forms of swarm behaviors in many species. The butterfly species is one of the prominent and a bit insightful in their random flights and converting that into an artificial metaphor would lead to enormous possibilities. This paper considers one such metaphor known as Butterfly Mating Optimization (BMO). In BMO, the Bfly follows the patrolling mating phenomena and simultaneously captures all the local optima of multimodal functions. To imitate this algorithm, a mobile robot (Bflybot) was designed to meet the features of the Bfly in the BMO algorithm. Also, the multi-Bflybot swarm is designed to act like butterflies in nature and follow the algorithm's rules. The real-time experiments were performed on the BMO algorithm in the multi-robotic arena and considered the signal source as the light source. The experimental results show that the BMO algorithm is applicable to detect multiple signal sources with significant variations in their movements i.e., static and dynamic. In the case of static signal sources, with varying initial locations of Bflybots, the convergence is affected in terms of time and smoothness. Whereas the experiments with varying step-size leads to their variation in the execution time and speed of the bots. In this work, experiments were performed in a dynamic environment where the movement of the signal source in both maneuvering and non-maneuvering scenarios. The Bflybot swarm is able to detect the single and multi-signal sources, moving linearly in between two fixed points, in circular, up and down movements.To evaluate the BMO phenomenon, various ongoing and prospective works such as mid-sea ship detection, aerial search applications, and earthquake prediction were discussed.Comment: 12 pages, 17 figure

Study of Cypermethrin Cytogenesis effects on Human Lymphocytes Using In-Vitro Techniques

The Cytogenetic effects of Cypermethrin a synthetic pyrithroid insecticide was investigated on human lymphocytes cultured in-vitro. Utilizing the trypan blue dye exclusion technique assay the LC50 of cypermethrin was found to be 36 uM. Based on LC50 value, cypermethrin was found to be low toxic to lymphocyte culture. Cypermethrin showed an increase in the frequency of chromosomal aberrations and found to be significant. Karyotype analysis revealed more satellite associations and chromosomal breaks in cypermethrin treated samples. Low-doses of the pesticide also induced singlestrand breaks in the DNA as assessed by comet assay. The pesticide caused increase in the comet tail length with increase in pesticide concentration, implicating genotoxicity in somatic cells. It is concluded that In vitro assays could give important information of the mechanism of toxicity at low dosages and impact on genetic material of human origin

Floral biology studies in wild melon [Cucumis melo L. ssp. agrestis (Naudin) Pangalo var. agrestis Naudin]

Studies on floral morphology, phenology and biology of wild melon revealed that the ratio of staminate and pistillate flowers was 3.40:1. The longevity of the male flowers were between 5 and 6 days, whereas, female flowers between 6 and 7 days. Anthesis was observed from 4.00 am to 10.00 am, while, the anther dehiscence started from 5.00 am which was continued to 7.00 am. The peak anthesis was observed from 8.00 am to 9.00 am and anther dehiscence from 6.00 am to 6.30 am. Freshly opened flowers showed pollen viability up to 98.35%, decreased upon closure and crashed to 17.48% in 3 days. Pollen germination was occurred after 15 minutes of incubation and continued up to 24 h of incubation. The stigma receptivity lasts from one to two days of anthesis. Major pollinator of wild melons observed was honey bee, mostly visited between 9:00 am to 6:00 pm

Antihypertensive treatment decreases arterial stiffness at night but not during the day. Results from the Hypertension in the Very Elderly Trial

The main Hypertension in the Very Elderly Trial (HYVET) demonstrated a very marked reduction in cardiovascular events by treating hypertensive participants 80 years or older with a low dose, sustained release prescription of indapamide (indapamide SR, 1.5 mg) to which was added a low dose of an angiotensin converting enzyme inhibitor in two-thirds of cases (perindopril 2–4 mg). This report from the ambulatory blood pressure sub-study investigates whether changes in arterial stiffness and ambulatory blood pressure (BP) could both explain the benefits observed in the main trial. A total of 139 participants were randomized to placebo [67] and to active treatment [72] and had both day and night observations of BP and arterial stiffness as determined from the Q wave Korotkoff diastolic (QKD) interval. The QKD interval was 5.6 ms longer (p = 0.017) in the actively treated group at night than in the placebo group. This was not true for the more numerous daytime readings so that 24-h results were similar in the two groups. The QKD interval remained longer at night in the actively treated group even when adjusted for systolic pressure, heart rate and height. The reduced arterial stiffness at night may partly explain the marked benefits observed in the main trial

Gesture Recognition for Enhancing Human Computer Interaction

Gesture recognition is critical in human-computer communication. As observed, a plethora of current technological developments are in the works, including biometric authentication, which we see all the time in our smartphones. Hand gesture focus, a frequent human-computer interface in which we manage our devices by presenting our hands in front of a webcam, can benefit people of different backgrounds. Some of the efforts in human-computer interface include voice assistance and virtual mouse implementation with voice commands, fingertip recognition and hand motion tracking based on an image in a live video. Human Computer Interaction (HCI), particularly vision-based gesture and object recognition, is becoming increasingly important. Hence, we focused to design and develop a system for monitoring fingers using extreme learning-based hand gesture recognition techniques. Extreme learning helps in quickly interpreting the hand gestures with improved accuracy which would be a highly useful in the domains like healthcare, financial transactions and global busines