Enhancement and Detection of Objects in Underwater Images using Image Super-resolution and Effective Object Detection Model

It is imperative to build an automatic underwater object recognition system in place to reduce the costs of underwater inspections as well as the associated risks. An effective method of detecting underwater objects from underwater images of aquatic after enhancing them using the Image Super-resolution technique is proposed in this study. The proposed approach comprises of two major sections, Underwater Image Enhancement, and Object detection. To enhance the underwater images, a lightweight Reduced Cascading Residual Network (RCARN) is proposed that imposes the Image Super-resolution technique. Later, the enhanced images generated by the RCARN model are supplied for the object detection process, where a significant object detection model, YOLOv3 is employed in this study. To improve its performance, this YOLOv3 is trained on one of the largest datasets, the COCO data, followed by being fine-tuned using enhanced Underwater images. The dataset utilized in this work contains 6 classes of underwater objects namely dolphin, jellyfish, octopus, seahorse, starfish, and turtle. All these images are actual real field images collected from various sources. With this proposed approach, a better overall ACS and mAP of 95.44% and 75.33% are achieved here, which are improved by ~8.75% and ~15%, respectively when compared to actual collected low-resolution images

Rare cause of hyperkalemia in the newborn period: Report of two cases of pseudohypoaldosteronism Type 1

Pseudohypoaldosteronism (PHA) Type 1 is characterized by mineralocorticoid resistance, manifesting as neonatal salt wasting, hypotension, hyperkalemia, hyponatremia, and metabolic acidosis in spite of elevated aldosterone levels and plasma renin activity. It is important to differentiate children with systemic PHA from renal PHA, as these children are likely to decompensate even with mild symptoms. Here, we report two neonates with PHA that presented to us with multiorgan involvement

An evaluation of compatibility of three different impression materials to three different tray acrylic materials using tray adhesives: An In vitro Study

Background: Impressions are an integral part of prosthodontics. Elastomeric impression materials are the impressions materials of choice in fixed prosthodontics for its better surface detail reproduction. Out of the elastomers available, vinyl polysiloxane represents the state of art impression material in prosthodontics, but even these materials cannot give an accurate reproduction of the tissues if there is separation of impression materials from the tray which may results in a distorted impression leading to poor final restorations made from such impressions. Hence, tray adhesives need to be applied to the tray to obtain an accurate and consistent impression. The purpose of the study was to evaluate the compatibility of three different impression materials to three different tray acrylic materials using tray adhesive, by determining the tensile bond strength. Materials and Methods: Two acrylic discs were utilized to make one impression sample of 3 mm thickness. The dimension of each acrylic disc was 2 mm in thickness and 2 cm in diameter. Specimens were made using a standard stainless steel die of the above-mentioned dimensions. A total of 135 specimens were prepared which included 15 samples in each category of nine groups. The samples were subjected to tensile bond strength testing using the universal testing machine and the values were recorded. All the values were subjected for statistical analysis. Results: Impregum (3M) specimens had demonstrated the highest tensile bond strength value (51.60N). Statistical analysis was done using Tukey's post hoc test and one-way ANOVA. Highly Statistical significant results were evident in Impregum (3M) and Indentium, as the P = 0.00. Conclusion: In this study Impregum (3M), specimens had highest tensile bond strength values compared to the other Groups followed by Indentium

Enhancement and Detection of Objects in Underwater Images using Image Super-resolution and Effective Object Detection Model

1050-1060It is imperative to build an automatic underwater object recognition system in place to reduce the costs of underwater inspections as well as the associated risks. An effective method of detecting underwater objects from underwater images of aquatic after enhancing them using the Image Super-resolution technique is proposed in this study. The proposed approach comprises of two major sections, Underwater Image Enhancement, and Object detection. To enhance the underwater images, a lightweight Reduced Cascading Residual Network (RCARN) is proposed that imposes the Image Super-resolution technique. Later, the enhanced images generated by the RCARN model are supplied for the object detection process, where a significant object detection model, YOLOv3 is employed in this study. To improve its performance, this YOLOv3 is trained on one of the largest datasets, the COCO data, followed by being fine-tuned using enhanced Underwater images. The dataset utilized in this work contains 6 classes of underwater objects namely dolphin, jellyfish, octopus, seahorse, starfish, and turtle. All these images are actual real field images collected from various sources. With this proposed approach, a better overall ACS and mAP of 95.44% and 75.33% are achieved here, which are improved by ~8.75% and ~15%, respectively when compared to actual collected low-resolution images

Nutritional and structural evaluation of selected Black gram varieties for preparation of Fermented Thick Pancake (Dosa)

The quality characteristics of selected black gram varieties viz., VBN 5, VBN 7, ADT 3, T9 and CO 6 and were evaluated for their suitability for the preparation of thick pancake. The foaming stability and foaming capacity were found to be maximum in VBN 5, CO 6 and T9. Maximum rise in volume was recorded in CO 6 (149 ml) followed by VBN 5 (148 ml) and T9 (147 ml) which is an indication good quality of thick pancake. Thick pancake prepared using 5 black gram varieties were analyzed for the physicochemical and microbial load. The texture profile viz., springiness, cohesiveness, chewiness and gumminess was evaluated for VBN 5, CO 6, T9 and VBN 7 respectively. The protein content was higher in thick pancake prepared from VBN 5 (25.47/100 g) compared to CO 6 (24.66 g/100g). Among the selected varieties, CO 6, T9 and VBN 5 had good batter content, texture, and microstructure and were found to be most suitable for thick pancake preparation

Impact of commonly used agrochemicals on different fungal and bacterial bio-agents

Not AvailableFour fungal bio-agents viz., Trichoderma harzianum, T. viride, Paecilomyces lilacinus and Pochonia chlamydosporia and four bacterial bio-agents viz., Bacillus subtilis, B. pumilus, B. amyloliquefaciens and Pseudomonas fluorescens were tested for their in vitro compatibility with five fungicides (carbendazim, captan, mancozeb, copper oxychloride and fenamidone + mancozeb) and three pesticides (carbofuran, metam sodium and acephate) at recommended doses of the pesticides and fungicides. The results revealed that carbendazim and metam sodium were highly toxic to all fungal bio-agents and copperoxychloride, mancozeb, fenamidone + mancozeb and metam sodium were highly toxic to all bacterial bio agents. T. harzianum exhibited more tolerance to captan than T. viride, P. chlamydosporia and P. lilacinus. All fungal bio-agents exhibited tolerance to carbofuran and acephate except P. chlamydosporia. Carbendazim was comparatively safer to B. subtilis, P. fluorescens and B. pumilus, but more toxic to B. amyloliquefaciens. P. fluorescens was relatively tolerant and Bacillus spp. was more sensitive to carbofuran and acephate. This study suggests that it is safe to integrate fungal bio-agents with copper oxychloride, carbofuran and acephate and bacterial bio-agents (except B. amyloliquefaciens) with carbendazimin integrated pest management (IPM) programmes.ICAR-IIH