Application of Convolutional Neural Network for Cancer Disease Diagnosis – A Deep Learning based Approach

Human are vulnerable to the terrible disease named cancer, which is a major factor in the high mortality rate. There are currently lesser DLTs (Deep learning techniques) or MLTs (machine learning techniques) for identifying cancer, despite advances in cancer treatment approaches. The proposed work performs a comparative study which compares the some significant DLTs like RFs (Random Forests), LSTMs (Long Short Term Memories), CNNs (Convolutional Neural Networks) and BPNNs (Back Propagation Neural Networks). These techniques are used here in this work for classification problem. The techniques are made to classify the medical records into benignand cancerous. Three pathological datasets are used to evaluate the above said techniques. CNNs provide the best performance of 0.97 accuracy and it is even good at its values of precisions, recalls and F1 scores.

Baseline assessment of marine debris with soil, sediment, and water quality characteristics from the fish landing centres of South Andaman, Andaman archipelago, India

The present study investigates the issue of marine debris and the associated soil, sediment, water quality, and microbial load from the fish landing centres (Junglighat, Chatham, Wandoor, and Guptapara) of South Andaman. The results revealed that significantly (P < 0.05) higher number and weight of marine debris was found in urban landing centres such as Chatham (21.26 ± 1.03 numbers/m²) and Junglighat (268.16 ± 27.00 g/m²), respectively. Plastic debris was found to be the most abundant type of debris, among which plastic bags were dominant. Better soil, sediment, and water quality parameters were observed in rural landing centres such as Wandoor and Guptapara, whereas microbial load was found to be higher in urban landing centres. The study recommends the imperative need to generate awareness on better management practices among the stakeholders to deal with the issue of marine debris and to aim sustainable management of the coastal environment.

Enhancing nutrient recovery and compost maturity of coconut husk by vermicomposting technology

Vermicompost was prepared by five different treatments from relatively resistant coconut husk mixed with either pig slurry or poultry manure. The recovery of vermicompost varied from 35% to 43% and it resulted in significant increase in pH, microbial biomass carbon, macro and micro nutrients concentration. Among the treatments highest relative N (1.6) and K (1.3) recovery were observed for 20% feedstock substitution by pig slurry while poultry manure substitution recorded highest P recovery (2.4). Compost maturity parameters significantly differed and well correlated. The characteristics of different treatments established the maturity indices as C/N 15-20; Cw<1.8; Cw/Norg<0.55; Lignin<10-12; CHA/CFA>1.5 and HI>15.0. The manurial value of the coconut husk compost was improved by feedstock substitution with pig slurry (80:20). The results revealed the technical feasibility of converting coconut husk into valuable compost by feedstock substitution with pig slurry.

Pesticide residues in vegetable samples from the Andaman Islands, India

Vegetable samples of brinjal, okra, green chilli, crucifers, and cucurbits collected from farmers' field were tested for the presence of organochlorine (OC), organophosphorus (OP), and synthetic pyrethroid (SP) compounds using a gas chromatograph equipped with electron capture and flame thermionic detectors. Of the samples tested, 34.0% were found to have pesticide residues. Among the OC compounds, α-endosulfan, β-endosulfan, and endosulfan sulfate were detected in 14.5% of the samples with residues. These were taken from crucifer, okra, green chilli, and cucurbit samples. SP compound residues, such as α-cypermethrin, fenvalerate I, fluvalinate I, deltamethrin, and λ-cyhalothrin were detected in 32% of the samples with residues. OP compound residues such as chlorpyrifos, profenofos, monocrotophos, triazophos, ethion, dimethoate, and acephate were found in 54% of the samples with residues, which were taken from all vegetable samples. Of the positive samples, 15.3% were found to contain residues exceeding the prescribed maximum residue limit. The average pesticide residue content across all the vegetable samples was 0.108 ppm, with values ranging from 0.008 to 2.099 ppm. Multiple residues of more than one compound were detected in 34.1% of samples containing residues.

Use of an aqueous extract of Terminalia chebula as an anticaries agent: a clinical study

Plant-derived medicines have been a part of our traditional health care system, and the antimicrobial properties of plant-derived compounds are well documented. The purpose of this study is to evaluate the effect of an aqueous extract of Terminalia chebula (a medicinal plant) on salivary samples and its potential for use as an anticaries agent in the form of mouthwash. A concentrated aqueous extract was prepared from the fruit of T. chebula . A mouth rinse of 10% concentration was prepared by diluting the extract in sterile distilled water. The efficacy of the mouth rinse was assessed by testing on 50 salivary samples. Salivary samples were collected from subjects assessed to be at high risk for caries. Salivary pH, buffering capacity, and microbial activity were assessed before rinsing, immediately after, and 10 min, 30 min, and 1 h after rinsing. There was an increase in the pH and buffering capacity and decrease in microbial count. An aqueous extract of T. chebula used as a mouth rinse seems to be an effective anticaries agent.