An extensive analysis of artificial intelligence and segmentation methods transforming cancer recognition in medical imaging.

Recent advancements in computational intelligence, deep learning, and computer-aided detection have had a significant impact on the field of medical imaging. The task of image segmentation, which involves accurately interpreting and identifying the content of an image, has garnered much attention. The main objective of this task is to separate objects from the background, thereby simplifying and enhancing the significance of the image.

Gaussian Adapted Markov Model with Overhauled Fluctuation Analysis-Based Big Data Streaming Model in Cloud.

An accurate resource usage prediction in the big data streaming applications still remains as one of the complex processes. In the existing works, various resource scaling techniques are developed for forecasting the resource usage in the big data streaming systems. However, the baseline streaming mechanisms limit with the issues of inefficient resource scaling, inaccurate forecasting, high latency, and running time.

GIT-Net: An Ensemble Deep Learning-Based GI Tract Classification of Endoscopic Images.

This paper presents an ensemble of pre-trained models for the accurate classification of endoscopic images associated with Gastrointestinal (GI) diseases and illnesses. In this paper, we propose a weighted average ensemble model called GIT-NET to classify GI-tract diseases. We evaluated the model on a KVASIR v2 dataset with eight classes.

Analysis of DNA Sequence Classification Using CNN and Hybrid Models.

In a general computational context for biomedical data analysis, DNA sequence classification is a crucial challenge. Several machine learning techniques have used to complete this task in recent years successfully. Identification and classification of viruses are essential to avoid an outbreak like COVID-19.

Effect of adsorbent and acidulants on enzymatic browning of sugarcane juice.

Enzymatic browning is a major factor affecting the quality of sugarcane juice, mainly due to the activities of polyphenol oxidase (PPO) and peroxidase (POD). Effect of bentonite (0-1%, w/v) on the activities of these enzymes, when employed alone and also in combination with acidulants, was determined. Bentonite alone could reduce the activities of PPO and POD enzymes to 160 and 24.

Characterization of Neem ( A. Juss) seed volatile compounds obtained by supercritical carbon dioxide process.

Extraction process employing Supercritical fluid carbon dioxide (SCF) yields bioactive compounds near natural forms without any artifact formation. Neem seed was subjected to SCF at different temperatures and pressure conditions. These extracts were partitioned to separate volatile fraction and were analyzed by Gas Chromatography-Mass spectroscopy along with the volatiles extracted by the hydro-distillation method.

Assessment of toxicity and biochemical mechanisms underlying the insecticidal activity of chemically characterized Boswellia carterii essential oil against insect pest of legume seeds.

The present study was undertaken to investigate the insecticidal activity of chemically characterized Boswellia carterii essential oil (EO) and its mode of action against the pulse beetle Callosobruchus chinensis and C. maculatus. GC-MS analysis depicted α-thujene (69.

Effect of edible coating on the aromatic attributes of roasted coffee beans.

Coffee is known throughout the world for its distinct aroma and flavour which results from a number of volatile compounds present in it. It is very difficult to arrest the aromatic compounds once the roasting process is complete and it becomes even more challenging to store the beans for a longer time with the retained volatiles as these compounds are easily lost during industrialized processing such as the grinding of roasted coffee beans and storage of ground coffee. Thus, an attempt was made to minimise the loss of volatile from roasted coffee beans by coating with Carboxymethyl cellulose (CMC), Hydroxypropylmethyl cellulose (HPMC) and Whey protein concentrate.

A perception on health benefits of coffee.

Coffee, consumed for its refreshing and stimulating effect, belongs to the tribe Coffea of the subfamily Cinchonoidea of Rubiaceae family. Coffee is a complex chemical mixture composed of several chemicals. It is responsible for a number of bioactivities and a number of compounds accounting for these effects.

Physicochemical characteristics of green coffee: comparison of graded and defective beans.

Defective (triage) coffee beans are beans rejected after separating the graded ones according to the size and color. These coffee beans represent about 15% to 20% of coffee production in India but are not utilized for beverages since these affect the quality of coffee brew. In the present study, physical characteristics such as bean density, brightness, titratable acidity, pH, moisture, and total soluble solids and also chemical composition, namely, caffeine, chlorogenic acids, lipids, sucrose, total polyphenols, and proteins, were evaluated in defective as well as in graded green coffee beans.

Caffeine in coffee: its removal. Why and how?

The popularity of coffee as a beverage is ever increasing despite the fact that there are reports antagonized to its consumption. Of the several factors cited, the alkaloid caffeine present in coffee can cause addiction and stimulate the central nervous system. It has an effect on the cardiovascular system with a slight increase in blood pressure and heart output.