Evaluation of Seed Quality in Naturally Aged Seed Lots of Coriander

Three seed lots of fifteen genotypes of coriander were subjected to study the effect of natural ageing on different seed quality parameters. Results revealed that all the genotypes showed the germination percentage above the Minimum Seed Certification Standards (65%) in Lot-1 (freshly harvested seed) and Lot-2 (1 year old seed). Standard germination (%), seedling length (cm), seedling dry weight (mg), seedling vigor index-I & II and accelerated ageing test (%) revealed that quality of seeds declined with faster rate inLot-3 (2 years old seed). Among all the genotypes, maximum germination was retained by genotype DH-339 (75.5%) followed by Hisar Surbhi (74.5%) and maximum loss of germination was observed in genotype DH 352-1 (61.2%). Hence, the genotypes DH-339 and Hisar Surbhi were found superior in terms of viability, vigor and storability whereas genotype DH 352-1 was found poor under ambient conditions

Temperature based rapid SAW humidity sensor

This paper investigates the effect of temperature on the sensitivity of a thin-film Polyvinyl alcohol (PVA) based SAW humidity sensor. A PVA coated 433.92 MHz SAW resonator-based humidity sensor was fabricated and tested with different levels of humidity (0.5 to 95% RH) at different operating temperatures (10°C to 70°C). The sensor response was recorded through in-house developed data acquisition software and it was observed that PVA thin film coated SAW sensor shows the maximum sensitivity for trace level moisture detection at a lower temperature (≤10 °C). The sensor sensitivity has been recorded >400Hz/% RH for trace level detection (0.5–30% RH). It has been observed that sensor sensitivity deteriorates when temperature increased to 40 °C from 10 °C. The sensor has a fast response (~1s) and recovery time (<3s) for trace level humidity detection. The proposed sensor can be used in many applications, including fabrication of electronic devices, IC fabrication, pharmaceutical, textile industries, food processing, semiconductor device fabrication, and packaging

In-silico molecular docking analysis of some plant derived molecules for anti-inflammatory inhibitory activity

Herbs are essential resources for drug discovery. However, numerous challenges stand in front of the scientific community to discover novel drugs from herbs. To explore the validation behind the precious knowledge of traditional medicine, we focused on achieving virtual screening to detect the potential medicines from the herbs.  Five bioactive compounds from known anti-inflammatory medicinal plants were examined through molecular docking against  cyclooxygenase-2 (COX-2) and inducible Nitric Oxide Synthase (iNOS), using AutoDock 4.2. The docking of selected ligands with COX-2 showed the binding energy varying from -6.15 Kcal/mol to ‑11.24 Kcal/mol. The docking energies of identified ligands with iNOS were generated ranges from -3.85kcal/mol to -6.99 kcal/mol.  Among the tested ligands, it was noted that 6 urs-12-en-24-oic acid showed the best binding energy than other compounds with the lowest binding energy and highest binding affinity with both anti-inflammatory target proteins COX-2 and iNOS. The in silico study validates the potential phytochemical compound of the medicinal herb that contribute to anti-inflammatory activity with low toxicity and minimal side effects

Seed Production of \u3cem\u3eBrachiaria ruziziensis\u3c/em\u3e in India--Seed Collection Methods and Feed Opportunities

Brachiaria ruziziensis is an important fodder crop suitable for high rainfall areas and soils with low nutrient supply. Though the area under B. ruziziensis cultivation in India is not properly documented, it is widely grown in Kerala (Stür et al. 1996) and in parts of Karnataka and Goa. By virtue of its shade tolerance and adaptability, B. ruziziensis have wide scope for adoption in other parts of India. In India, Brachiaria is mainly planted through root slips as availability of good quality filled seeds is very less. It is known that the proportion of filled to unfilled seeds depends on method of harvest and seed collection method (Hare et al., 2007). Appropriate method of harvest depends on growth habit, synchrony of crop development, standing seeds, fallen seeds, availability of labour and on previous experience. Hence a study was conducted for first time in India to standardise harvesting and seed collection method in B.ruziziensis

MRI Kidney Tumor Image Classification with SMOTE Preprocessing and SIFT-tSNE Features using CNN

Kidney tumor detection is a challenging task due to the complexity of tumor characteristics and variability in imaging modalities. In this paper, we propose a deep learning-based approach for detecting kidney tumors with 98.5% accuracy. Our method addresses the issue of an imbalanced dataset by applying the Synthetic Minority Over-sampling Technique (SMOTE) to balance the distribution of images. SMOTE generates synthetic samples of the minority class to increase the number of samples, thus providing a balanced dataset. We utilize a convolutional neural network (CNN) architecture that is trained on this balanced dataset of kidney tumor images. The CNN can learn and extract relevant features from the images, resulting in precise tumor classification. We evaluated our approach on a separate dataset and compared it with state-of-the-art methods. The results demonstrate that our method not only outperforms other methods but also shows robustness in detecting kidney tumors with a high degree of accuracy. By enabling early detection and diagnosis of kidney tumors, our proposed method can potentially improve patient outcomes. Additionally, addressing the imbalance in the dataset using SMOTE demonstrates the usefulness of this technique in improving the performance of deep learning-based image classification systems

Real-time Thermal Error Compensation Module for Intelligent Ultra Precision Turning Machine (iUPTM)

AbstractAccuracy & precision are 1he main requirements for ultra precision machine tools. Many factors affect 1he performance of 1he system 1hat in turns affect 1he product quality. Among all sources of errors, the thermo mechanical deformation errors are the main contributor for 1he overall geometrical errors. This paper mainly aims at establislunent of methodology to compensate thermal deformation errors in real-time for ultra precision machine tools. The real-time thermal error compensation module has been developed and integrated to intelligent Ultra Precision Turning machine. The module includes temperatures as inputs, neural network algorithm for computing the thermal deformations errors, ‘C’ programming for real-time calculations and integration with open architecture CNC controller. The module runs in silent mode which avoids human intervention for correction of thermal deformation errors

Frequency of polymorphic variants in corticotropin releasing hormone receptor 1, glucocorticoid induced 1 and Fc fragment of IgE receptor II genes in healthy and asthmatic Tamilian population

Background: Asthma is a chronic airway inflammatory disease characterized by increased hyper-responsiveness and recurrent episodes of reversible obstructions. Asthma pharmacogenomic studies report significant association of single nucleotide polymorphisms (SNPs) in genes corticotropin releasing hormone receptor 1 (CRHR1), Fc fragment of IgE receptor II (FCER2) and glucocorticoid induced 1 (GLCCI1) with inhaled corticosteroid (ICS) response. The present study was aimed to establish the allelic and genotypic frequencies of polymorphisms rs242941, rs28364072 & rs37972 in CRHR1, FCER2 and GLCCI1 genes, respectively in Tamilian healthy population and asthma patients and to compare with established frequencies of global populations.Methods: The study groups consisted of healthy volunteers and persistent asthma patients who were drug naïve or without ICS treatment in the last ≥2 months, attending JIPMER hospital (n=111 and 78, respectively). SNP genotyping was done using PCR-RFLP (polymerase chain reaction-restriction fragment length polymorphism) and real time-PCR methods.Results: Allelic and genotypic frequencies for all the studied variants found to be in hardy-weinberg equilibrium with minor allele frequencies (MAF) of rs 242941, rs 28364072 and rs 37972 at 0.51, 0.33 and 0.38, respectively, in healthy population. No significant difference in gene frequencies was obtained between healthy control and asthma patient groups. Significant difference in allele frequencies was observed between Tamilian healthy and specific global populations. West African frequency was found to be significantly different for all 3 SNPs (p<0.0001).Conclusions: MAF of rs 242941, rs 28364072 and rs 37972 were 0.51, 0.33 and 0.38, respectively in Tamilian population which were significantly different from various global populations. The frequency distribution found helps to further with ICS response association studies in larger cohorts of asthma patients