PLATE FIN AND TUBE HEAT EXCHANGER

The main objective of the present work is to investigation of optimum design of plate fin tube heat exchanger using Computational fluid dynamic approach and maximizing thermal performance. There are total five designs of plate fin and tube heat exchanger are used in present work and CFD analysis have been performed in it to get maximum heat transfer. It has been observed from CFD analysis that the maximum heat transfer can be achieved from plate fin and tube heat exchanger with elliptical tube arrangement inclined at 30o with 23.22% more heat transfer capacity as compared to circular tube plate pin heat exchanger. So that it is recommended that if the plate fins and tube heat exchanger with inclined elliptical tube used in place of circular tube arrangement, batter heat transfer can be achieved

FORMULATION, DEVELOPMENT AND EVALUATION OF BI-LAYER TABLET OF ANTI HIV DRUG

In the last decade, interest in developing a combination of two or more Active Pharmaceutical Ingredients (API) in a single dosage form (bi-layer tablet) has increased in the pharmaceutical industry, promoting patient convenience and compliance. The Bi-layer tablets have been developed to achieve controlled delivery of different drugs with pre-defined release profiles. Bi-layer tablets can be a primary option to avoid chemical incompatibilities between API by physical separation, and to enable the development of different drug release profiles (immediate release with extended release). Despite their advantages, due to the use of different materials and complex geometric boundaries between the adjacent layers, the mechanical structures of this drug delivery system have become quite intricate, requiring complicated tablet architectures as well as patient-friendly. Bi-layer tablets offer definite advantages over conventional release formulation of the same drug. Several pharmaceutical companies are currently developing bi-layer tablets. For a variety of reasons: patent extension, therapeutic, marketing to name a few. To reduce capital investment, quite often existing but modified tablet presses are used to develop and produce such tablets. Key words: Bi-layered tablet, API (Active Pharmaceutical Ingredients), adjacent layer, conventional release, insufficient hardness

Formulation Development and Evaluation of Lansoprazole Mucoadhesive Microsphere

Lansoprazole belongs to a class of antisecretory compounds, the substituted benzimidazoles, that do not exhibit anticholinergic or histamine H2-receptor antagonist properties, but rather suppress gastric acid secretion by specific inhibition of the (H+,K+)-ATPase enzyme system at the secretary surface of the gastric parietal cell. Because this enzyme system is regarded as the acid (proton) pump within the parietal cell, lansoprazole has been characterized as a gastric acid-pump inhibitor, in that it blocks the final step of acid production. This effect is dose-related and leads to inhibition of both basal and stimulated gastric acid secretion irrespective of the stimulus. The aim of the present study was to develop lansoprazole loaded thiolated chitosan microspheres were prepared by emulsifying method using liquid paraffin light and heavy in ratio of 50:50 as a dispersing medium and glutaraldehyde used as a cross-linking agent. The prepared microspheres were evaluated for mean particle size and particle size distribution, drug content, mucoadhesion measurement and in-vitro drug release. FT-IR spectroscopic analysis was performed to ascertain drug polymer interaction. The release profiles showed first order release behavior up to 12 hours where the highest drug release was 88.89 % of the lansoprazole loaded in the thiolated chitosan microspheres, indicating a strong crosslinking between chitosan and glutaraldehyde. From the results of the present investigation it may be concluded that drug loaded chitosan microspheres can be prepared by a simple technique which avoids the use of complex apparatus and special precautions. Keywords: Lansoprazole, Thiolated chitosan, Microspheres, Glutaraldehyde, Mucoadhesion measuremen

Risk assessment of submicron PM-bound hexavalent chromium during wintertime

<p>This study reports health risk assessment of PM₁-bound carcinogenic hexavalent chromium [Cr(VI)] from central part of Indo-Gangetic plain (IGP) (PM₁: particulate matter with aerodynamic diameter ≤1µm). Cr(VI) concentration has been estimated utilizing spectrophotometer with a modified novel method. Average ratio of Cr(VI)/Cr_T was 0.39 ± 0.07 (Cr_T: Total chromium) in the central IGP (Kanpur). Our study reports that mass fraction of Cr(VI) averaging at 0.39 is ∼3 times higher than that assumed conventionally [Cr(VI)/Cr_T: 1/7]. Cancer risk assessment has been performed by assessing excess cancer risk (ECR) for the Cr(VI). ECR determined due to Cr(VI) was 57 and 14.3 (in one million) for adults and children, respectively. Our study suggests that risk due to Cr(VI) reported in previous studies were being underestimated by a factor of three. The Cr(VI)/Cr_T average ratio of 0.39 determined in this study was utilized to calculate risk assessment due to Cr(VI) from other locations in the IGP. Owing to large population of India (∼125 million), the cancer risk due to Cr(VI) inhalation itself would become very significant. Thus, future research should focus on metal speciation of PM-bound samples from different locations to better constraint the toxicological risk assessment on a regional-to-global scale.</p

Addressing Binary Classification over Class Imbalanced Clinical Datasets Using Computationally Intelligent Techniques

Nowadays, healthcare is the prime need of every human being in the world, and clinical datasets play an important role in developing an intelligent healthcare system for monitoring the health of people. Mostly, the real-world datasets are inherently class imbalanced, clinical datasets also suffer from this imbalance problem, and the imbalanced class distributions pose several issues in the training of classifiers. Consequently, classifiers suffer from low accuracy, precision, recall, and a high degree of misclassification, etc. We performed a brief literature review on the class imbalanced learning scenario. This study carries the empirical performance evaluation of six classifiers, namely Decision Tree, k-Nearest Neighbor, Logistic regression, Artificial Neural Network, Support Vector Machine, and Gaussian Na&iuml;ve Bayes, over five imbalanced clinical datasets, Breast Cancer Disease, Coronary Heart Disease, Indian Liver Patient, Pima Indians Diabetes Database, and Coronary Kidney Disease, with respect to seven different class balancing techniques, namely Undersampling, Random oversampling, SMOTE, ADASYN, SVM-SMOTE, SMOTEEN, and SMOTETOMEK. In addition to this, the appropriate explanations for the superiority of the classifiers as well as data-balancing techniques are also explored. Furthermore, we discuss the possible recommendations on how to tackle the class imbalanced datasets while training the different supervised machine learning methods. Result analysis demonstrates that SMOTEEN balancing method often performed better over all the other six data-balancing techniques with all six classifiers and for all five clinical datasets. Except for SMOTEEN, all other six balancing techniques almost had equal performance but moderately lesser performance than SMOTEEN

A Novel Grid and Place Neuron’s Computational Modeling to Learn Spatial Semantics of an Environment

Health-related limitations prohibit a human from working in hazardous environments, due to which cognitive robots are needed to work there. A robot cannot learn the spatial semantics of the environment or object, which hinders the robot from interacting with the working environment. To overcome this problem, in this work, an agent is computationally devised that mimics the grid and place neuron functionality to learn cognitive maps from the input spatial data of an environment or an object. A novel quadrant-based approach is proposed to model the behavior of the grid neuron, which, like the real grid neuron, is capable of generating periodic hexagonal grid-like output patterns from the input body movement. Furthermore, a cognitive map formation and their learning mechanism are proposed using the place&ndash;grid neuron interaction system, which is meant for making predictions of environmental sensations from the body movement. A place sequence learning system is also introduced, which is like an episodic memory of a trip that is forgettable based on their usage frequency and helps in reducing the accumulation of error during a visit to distant places. The model has been deployed and validated in two different spatial data learning applications, one being the 2D object detection by touch, and another is the navigation in an environment. The result analysis shows that the proposed model is significantly associated with the expected outcomes

From Assistive Technologies to Metaverse: Technologies in Inclusive Higher Education for Students with Specific Learning Difficulties

The development of new technologies and their expanding use in a wide range of educational environments are driving the transformation of higher education. Assistive technologies are a subset of cutting-edge technology that can help students learn more effectively and make education accessible to everyone. Assistive technology can enhance, maintain, or improve the capacities of students with learning difficulties. Students with learning difficulties will be greatly benefited from the use of assistive technologies. If these technologies are used effectively, students with learning difficulties can compete with their peers and complete their academic tasks. We aim to conduct this review to better understand the role of assistive technologies in providing inclusive higher education for students with learning difficulties. The review begins with the introduction of learning difficulties and their causes; inclusive education and the need for assistive technologies; the reasoning for conducting this review; and a summary of related reviews on assistive technologies for students with learning difficulties in inclusive higher education. Then, we discuss the preliminaries for the learning difficulties type and assistive technology. Later, we discuss the effects of assistive technology on inclusive higher education for students with learning difficulties. Additionally, we discuss related projects and support tools available in inclusive higher education for students with learning difficulties. We also explore the challenges and possible solutions related to using assistive technology in higher education to provide inclusive education for students with learning difficulties. We conclude the review with a discussion of potential promising future directions.Comment: Submitted to peer revie