A Mobile App for Wound Localization using Deep Learning

We present an automated wound localizer from 2D wound and ulcer images by using deep neural network, as the first step towards building an automated and complete wound diagnostic system. The wound localizer has been developed by using YOLOv3 model, which is then turned into an iOS mobile application. The developed localizer can detect the wound and its surrounding tissues and isolate the localized wounded region from images, which would be very helpful for future processing such as wound segmentation and classification due to the removal of unnecessary regions from wound images. For Mobile App development with video processing, a lighter version of YOLOv3 named tiny-YOLOv3 has been used. The model is trained and tested on our own image dataset in collaboration with AZH Wound and Vascular Center, Milwaukee, Wisconsin. The YOLOv3 model is compared with SSD model, showing that YOLOv3 gives a mAP value of 93.9%, which is much better than the SSD model (86.4%). The robustness and reliability of these models are also tested on a publicly available dataset named Medetec and shows a very good performance as well.Comment: 8 pages, 5 figures, 1 tabl

A Deep Learning Study on Osteosarcoma Detection from Histological Images

In the U.S, 5-10\% of new pediatric cases of cancer are primary bone tumors. The most common type of primary malignant bone tumor is osteosarcoma. The intention of the present work is to improve the detection and diagnosis of osteosarcoma using computer-aided detection (CAD) and diagnosis (CADx). Such tools as convolutional neural networks (CNNs) can significantly decrease the surgeon's workload and make a better prognosis of patient conditions. CNNs need to be trained on a large amount of data in order to achieve a more trustworthy performance. In this study, transfer learning techniques, pre-trained CNNs, are adapted to a public dataset on osteosarcoma histological images to detect necrotic images from non-necrotic and healthy tissues. First, the dataset was preprocessed, and different classifications are applied. Then, Transfer learning models including VGG19 and Inception V3 are used and trained on Whole Slide Images (WSI) with no patches, to improve the accuracy of the outputs. Finally, the models are applied to different classification problems, including binary and multi-class classifiers. Experimental results show that the accuracy of the VGG19 has the highest, 96\%, performance amongst all binary classes and multiclass classification. Our fine-tuned model demonstrates state-of-the-art performance on detecting malignancy of Osteosarcoma based on histologic images

Possible ability of bovine follicular fluid to attract migrating bull spermatozoa

AimTo examine the potential of bovine follicular fluid (BFF) to attract bull spermatozoa. MethodsThe ability of the BFF to attract bull sperm was evaluated by observing changes in sperm migration after being placed in a cross-column chamber. The movement parameters of the heads and flagella of the sperm that were attracted to the BFF were analyzed by using the Computer Assisted Sperm Analysis system. ResultsIt was observed that 61.6% of the bull sperm migrated toward the BFF when the BFF was used at a concentration of 0.1%, but 67.2% of the sperm did not migrate toward the BFF at a concentration of 10%. Relatively larger numbers of both precapacitated and postcapacitated bull sperm migrated toward the BFF (0.1%). The ability of the 0.1% BFF to attract sperm probably affected both the normal artificial insemination (AI) fertility sperm and the poor AI fertility spermatozoa. The flagellar curvilinear ratio of the sperm winding to the 0.1% BFF was significantly higher than that of the prewinding sperm. ConclusionThese results could suggest that BFF potentially attracts bull sperm at a certain concentration, irrespective of the capacitation status of the sperm. Although the mechanism by which this attraction occurs remains unclear, these data imply that it could be related to BFF-dependent changes in the sperm flagellar curvilinear ratio.ArticleREPRODUCTIVE MEDICINE AND BIOLOGY.16(2):133-138(2017)journal articl

Removal of used motor oil from water body using modified commercial activated carbon

In this study, modification of commercial activated carbon (AC) was carried out for adsorption of used motor oil (UMO) from wastewater. The modification process involved impregnation of phosphoric acid at ratio 1: 2 followed by 500oC for 2 h for carbonization. Characterization of modified activated carbon (MAC) was done by using scanning electron microscopy with energy dispersive X-ray spectrometry and Fourier transform infrared spectroscopy to study morphology and the structural change and to identify the surface functional group of MAC. Based on the results obtained from this study, the percentage yield of the MAC was 63 with a moisture content of 37, and pH was 2.37. The adsorption of UMO by MAC was investigated. The effect of contact time, temperature, and pH to the adsorption process was studied, where the results showed that MAC had higher percentage of adsorption compared to AC. The study of the reusability of MAC was also done for 30 min and three cycles. The result showed that MAC could be regenerated and reused. The study of adsorption equilibrium was done by using Langmuir and Freundlich isotherms. The adsorption of UMO proved to fit better to Freundlich isotherm compared to Langmuir isotherm with a value of 0.9174. The adsorption kinetic study was done using pseudo-first-order and pseudo-second-order models. The adsorption data showed a better fit to pseudo-first-order kinetic model with a value of 0.9239. Adsorption capacity was found to be 3.951 oil/g (MAC). © 2019 Malaysian Institute of Chemistry. All rights reserved

Formulation of polymeric inhibitor for viscosity reduction of crude oil

Generally, waxes and asphaltenes are classified as solid category which involved with deposition of high-molecular-weighted compounds along pipelines which leads to production issues. This study presents the effect of different mixture concentration consisting of copolymer and solvent on crude oil viscosity in order to find a solution for reduction of wax and asphalthene deposition along the surface of pipelines. There were two proportions used which are ethylene-vinyl acetate 25 (EVA 25), methylcyclohexane (MCH) and paraxylene as first proportion and EVA 40, MCH and paraxylene as second proportion. EVA is a polymer that comprises of linear chain of polyethylene fragment and vinyl acetate molecule which has the ability in controlling the size of formed wax crystals. Laboratory experiments were designed by response surface methodology (RSM) specifically using central composite design (CCD) to formulate ratio and analyzed optimum percentage composition of mixture to obtain a good model. The optimum parameters were 10.02% of EVA 25, 10.00% of MCH and 79.98% of paraxylene for first proportion and 10.00% of EVA 40, 45.78% of MCH and 44.22% of paraxylene for second proportion to minimize the viscosity of crude oil

Optimization study on the effects of shear rate and concentration of inhibitor on wax and asphaltene deposition from crude oil using copolymer and aromatic compounds

In this study, the effects of shear rate and an ethylene-vinyl acetate (EVA)-based wax inhibitor towards the viscosity of crude oil was investigated. The viscosity of crude oil decreased when the shear rate increased and the most effective shear rate (in terms of rotational speed) was 100 rpm, which could reduce viscosity as high as 62.96 compared to the lowest shear rate applied (20 rpm). The EVA-based wax inhibitor could reach up to 80.66 of viscosity reduction of crude oil original viscosity when the weight percentage of EVA, methylcyclohexane (MCH) and para-xylene (PX) were 10.00, 45.78 and 44.22, respectively. PX was used as the asphaltene depressant along with the inhibitor. An optimization study evaluated that the most optimum conditions were found to be 10.00, 40.09 and 49.90 respectively for EVA, MCH and PX. © 2019 Malaysian Institute of Chemistry. All rights reserved

Wax inhibitor based on ethylene vinyl acetate with methyl methacrylate and diethanolamine for crude oil pipeline

Wax precipitation and deposition is one of the most significant flow assurance challenges in the production system of the crude oil. Wax inhibitors are developed as a preventive strategy to avoid an absolute wax deposition. Wax inhibitors are polymers which can be known as pour point depressants as they impede the wax crystals formation, growth, and deposition. In this study three formulations of wax inhibitors were prepared, ethylene vinyl acetate, ethylene vinyl acetate co-methyl methacrylate (EVA co-MMA) and ethylene vinyl acetate co-diethanolamine (EVA co-DEA) and the comparison of their efficiencies in terms of cloud point pour point, performance inhibition efficiency (PIE) and viscosity were evaluated. The cloud point and pour point for both EVA and EVA co-MMA were similar, 15°C and 10-5°C, respectively. Whereas, the cloud point and pour point for EVA co-DEA were better, 10°C and 10-5°C respectively. In conclusion, EVA co-DEA had shown the best PIE (28.42) which indicates highest percentage reduction of wax deposit as compared to the other two inhibitors. © Published under licence by IOP Publishing Ltd

Solid–liquid mass transfer coefficients in an ultrasound-irradiated extraction of iota-carrageenan

A 20-kHz intensity ultrasound was used in the extraction of iota-carrageenan from Eucheuma denticulatum seaweed by using water as solvent. In a simplified extraction procedure, the seaweed particle size of 0.7125E-03 m, 1.2E-3 m, and 1.7E-03 m diameter were studied at different ultrasonic amplitude levels, ranging from 2.08E-06 to 6.4E-06 m and the temperatures from 30 to 60 °C. The maximum iota-carrageenan yield obtained was 57.2 %. This study suggested that ultrasound intensity employed reduced the extraction time required and improved the yield of iota-carrageenan by 6 %. The particle diameter variation during the extraction was found to be a linear equation. The solid-liquid mass transfer coefficient was correlated for ultrasound extraction of iota-carrageenan in terms of operating conditions employed in this investigation as kL = 0:0027A0.866Dp -0.533(T)0.133