Automatic detection of COVID-19 in chest radiographs using serially concatenated deep and handcrafted features.

Since the infectious disease occurrence rate in the human community is gradually rising due to varied reasons, appropriate diagnosis and treatments are essential to control its spread. The recently discovered COVID-19 is one of the contagious diseases, which infected numerous people globally. This contagious disease is arrested by several diagnoses and handling actions. Medical image-supported diagnosis of COVID-19 infection is an approved clinical practice. This research aims to develop a new Deep Learning Method (DLM) to detect the COVID-19 infection using the chest X-ray. The proposed work implemented two methods namely, detection of COVID-19 infection using (i) a Firefly Algorithm (FA) optimized deep-features and (ii) the combined deep and machine features optimized with FA. In this work, a 5-fold cross-validation method is engaged to train and test detection methods. The performance of this system is analyzed individually resulting in the confirmation that the deep feature-based technique helps to achieve a detection accuracy of > 92% with SVM-RBF classifier and combining deep and machine features achieves > 96% accuracy with Fine KNN classifier. In the future, this technique may have potential to play a vital role in testing and validating the X-ray images collected from patients suffering from the infection diseases.

Challenges associated in stability of food grade nanoemulsions.

Food grade nanoemulsions are being increasingly used in the food sector for their physico-chemical properties towards efficient encapsulation, entrapment of bioactive compounds, solubilization, targeted delivery, and bioavailability. Nanoemulsions are considered as one of the important vehicles for the sustained release of food bioactive compounds due to their smaller size (nm), increased surface area, and unique morphological characteristics. Nanoemulsification is an ideal technique for fabricating the bioactive compounds in a nano form. Formation and stabilization of nanoemulsion depends on the physi-cochemical characteristics of its constituents including oil phase, aqueous phase, and emulsifiers. This review is mainly focused on the instability mechanisms of nanoemulsion such as flocculation, Ostwald ripening, creaming, phase separation, coalescence, and sedimentation. Further, the major factors associated with these instability mechanisms like ionic strength, temperature, solubilization, particle size distribution, particle charge, pH strength, acid stability, and heat treatment are also discussed. Finally, safety issues of food grade nanoemulsions are highlighted.

Influence of electrical and hybrid heating on bread quality during baking.

Energy efficiency and product quality are the key factors for any food processing industry. The aim of the study was to develop energy and time efficient baking process. The hybrid heating (Infrared + Electrical) oven was designed and fabricated using two infrared lamps and electric heating coils. The developed oven can be operated in serial or combined heating modes. The standardized baking conditions were 18 min at 220°C to produce the bread from hybrid heating oven. Effect of baking with hybrid heating mode (H-1 and H-2, hybrid oven) on the quality characteristics of bread as against conventional heating mode (C-1, pilot scale oven; C-2, hybrid oven) was studied. The results showed that breads baked in hybrid heating mode (H-2) had higher moisture content (28.87%), higher volume (670 cm(3)), lower crumb firmness value (374.6 g), and overall quality score (67.0) comparable to conventional baking process (68.5). Moreover, bread baked in hybrid heating mode showed 28% reduction in baking time.

A cost-effective smart metering approach towards affordable deployment strategy.

Revamping the power grid into a smart grid and modernizing it with advanced metering infrastructure are essential steps in addressing ongoing energy challenges. Smart meters play a pivotal role in power grid modernization by providing real-time energy-related data which fuels the control activities of modern grid. While the advantages of smart meters are evident, their deployment necessitates a comprehensive redesign of the grid architecture, involving smart end devices for monitoring and communication networks for efficient data exchange. Yet, achieving cost-effective and widespread adoption of these technologies poses a challenge, particularly in developing and underdeveloped nations due to high capital costs, technological constraints and uneconomical deployment strategies. Moreover, the prevailing research often advocates a complete transition to new smart meters to achieve 'smartness,' neglecting the potential of existing metering infrastructure upgrades. To address these concerns, this study proposes and simulates the design of a low-cost Smart Network Meter. Notably, this meter upgrades the existing meter infrastructure while validating a cost-effective deployment strategy. Furthermore, a consumer opinion survey was also conducted to compelling evidence supporting the adoption of the proposed low-cost smart metering solution.

Green and eco-friendly approaches for the extraction of chitin and chitosan: A review.

Chitin is one of the most diverse and naturally occurring biopolymers, and it is mainly present in crustaceans, insects, and fungi. Chitosan is derived from chitin by deacetylation process. It is important to note that the conventional chemical method of extracting chitin includes disadvantages and it poses various environmental issues. Recently, the green extraction techniques have perceived substantial development in the field of polymer chemistry. A variety of methods have been successfully developed using green extraction techniques for extracting chitin and chitosan from various resources. It includes the use of ionic liquids (ILs), deep eutectic solvents (DES), microbial fermentation, enzyme-assisted extraction (EAE), microwave-assisted extraction (MAE), ultrasonic-assisted extraction (UAE), subcritical water extraction (SWE), and electrochemical extraction (ECE). In this review, the extraction of chitin and chitosan using greener approaches were summarized. In addition, challenges, opportunities and future perspectives of green extraction methods have also been narrated.