Skin Lesion Analysis and Cancer Detection Based on Machine/Deep Learning Techniques: A Comprehensive Survey.

The skin is the human body's largest organ and its cancer is considered among the most dangerous kinds of cancer. Various pathological variations in the human body can cause abnormal cell growth due to genetic disorders. These changes in human skin cells are very dangerous. Skin cancer slowly develops over further parts of the body and because of the high mortality rate of skin cancer, early diagnosis is essential. The visual checkup and the manual examination of the skin lesions are very tricky for the determination of skin cancer. Considering these concerns, numerous early recognition approaches have been proposed for skin cancer. With the fast progression in computer-aided diagnosis systems, a variety of deep learning, machine learning, and computer vision approaches were merged for the determination of medical samples and uncommon skin lesion samples. This research provides an extensive literature review of the methodologies, techniques, and approaches applied for the examination of skin lesions to date. This survey includes preprocessing, segmentation, feature extraction, selection, and classification approaches for skin cancer recognition. The results of these approaches are very impressive but still, some challenges occur in the analysis of skin lesions because of complex and rare features. Hence, the main objective is to examine the existing techniques utilized in the discovery of skin cancer by finding the obstacle that helps researchers contribute to future research.

Residual effects of frequently available organic amendments on cadmium bioavailability and accumulation in wheat.

Wheat (Triticum aestivum L.) cultivation in cadmium (Cd) polluted soil is a core concern to food quality and food security all over the world. Cadmium toxicity is mainly associated with a Cd influx from contaminated soils to human via grain consumption. Organic amendments are widely used for Cd immobilization and enhancement in plant growth, but the residual effects of these amendments are mostly unknown. The present study addressed the long-term effects of organic amendments in contaminated soils by evaluating their residual effects on 3rd crop (wheat) in the sequence. Initially six organic amendments viz. rice husk biochar (RHB), wheat-straw biochar (WSB), cotton-stick biochar (CSB), poultry manure (PM), press mud (PrMd) and farm manure (FM) were applied once at a rate of 2% in Cd (50 mg kg-1) contaminated soil with wheat-rice rotation. After the harvest of wheat and rice crops, wheat (Var. Galaxy) was again grown in the same pots. Results revealed that plants grown under Cd stress (without any amendment) contain more tissue (root, shoot and grain) and soil AB-DTPA extractable Cd. The soil amended with RHB has shown lowest AB-DTPA extractable Cd (69% lower than control). Similarly, RHB application has significantly reduced wheat root, shoot and grain Cd concentrations compared to control and other amendments. Results have confirmed the effectiveness of RHB residual contents as an active amendment for restriction of Cd in non-bioavailable pool of soil and better growth and yield of wheat.