Comprehensive Study of Automatic Speech Emotion Recognition Systems

Speech emotion recognition (SER) is the technology that recognizes psychological characteristics and feelings from the speech signals through techniques and methodologies. SER is challenging because of more considerable variations in different languages arousal and valence levels. Various technical developments in artificial intelligence and signal processing methods have encouraged and made it possible to interpret emotions.SER plays a vital role in remote communication. This paper offers a recent survey of SER using machine learning (ML) and deep learning (DL)-based techniques. It focuses on the various feature representation and classification techniques used for SER. Further, it describes details about databases and evaluation metrics used for speech emotion recognition

A case of Occupational Methemoglobinemia (MetHb): A Rare Entity and Unique Treatment

Methemoglobinemia is acute emergency which have precise and effective treatment if instituted in time. Methemoglobinemia due to chemical exposure is a known entity. But it required a high index of suspicion to look for it in busy casualty. Treatment with methylene blue is safe and truly lifesaving if instituted in time. Here we are presenting a case of Occupational methemoglobinemia who was treated successfully

Conceptual Design in Metalworking Microenterprises: An Empirical Study in Tanzania

Product design is a key aspect of human intelligence and creativity, attracting not only experts but also workers and self-employed without any formal design training. Although numerous people in developing countries design and manufacture simple products in metalworking microenterprises, there is very little systematic knowledge about their design process. This paper aims to fill this gap in design knowledge. We aim at investigating some aspects of design process in the metalworking microenterprises in Tanzania. The findings reveal how they identify needs, and generate and evaluate concepts.open access</p

Anaesthetic Management for Cataract Surgery in VACTERL Syndrome Case Report

Eight year old girl, weighing 14 kg with VACTERL syndrome V: Vertebral anomalies, A: Anal malformation, C: Cardiovascular defect, TE: Tracheal and esophageal malformation, R:Renal agenesis, L: Limb anomalies., underwent cataract surgery under general anaesthesia. She had multiple congenital anomalies like esophageal atresia, imperfo-rate anus (corrected), single kidney& radial aplasia. Anticipating problems of gastro-esophageal reflux& chronic renal failure, successful management was done

Conceptual Design in Informal Metalworking Microenterprises of Tanzania

Product design is a key aspect of human intelligence and creativity, attracting not only experts but also people without any formal design training. Although numerous people in developing countries design and manufacture products in metalworking microenterprises in the informal sector, there is still little knowledge about their design process. This paper aims to fill this gap in design knowledge. We aim to investigate the design processes in metalworking microenterprises in the informal sector of Tanzania. In particular, we aim to explore how these microenterprises identify consumer needs and requirements, how they determine the specifications for the product, how they generate and evaluate alternative product concepts, and how they define product details. To address these aims, semistructured interviews were carried out in metalworking microenterprises operating in the informal sector of Tanzania. The findings reveal many facets of their design processes, providing a sound basis upon which design methods and tools can be developed to support their design activities

COMPARATIVE STUDY OF REVERSE WET GRANULATION WITH CONVENTIONAL WET GRANULATION IN SOLUBILITY ENHANCEMENT OF SIMVASTATIN

Objectives: Simvastatin is a cholesterol- lowering agent widely used in hypercholesterolemia. It belongs to BCS class II drugs having low solubility and high permeability. Simvastatin is practically insoluble in water and poorly absorbed from the gastrointestinal tract. Therefore, it is necessary to introduce an effective method to enhance the solubility and dissolution rate of the drug. The main purpose of this work was to compare the reverse wet granulation with conventional wet granulation in enhancing the solubility of Simvastatin.Methods: The Granules were prepared by both conventional wet granulation in which Simvastatin was added along with other dry excipients and reverse wet granulation in which Simvastatin was added in granulating solvent using water as granulating solvent and Povidone, Lactose, Sodium starch glycolate, Magnesium stearate and Aerosil as an Excipients. The granules were evaluated for flow properties, solubility study, X- ray diffraction and FTIR study.Results: The flow properties of reverse wet granulation were found to be improved as compared to conventional wet granulation. The tablets were formulated from either type of granules which were subjected to a Hardness, Disintegration, Weight variation, Content of active ingredient, Friability, Wetting time and Dissolution test. The Simvastatin tablets of reverse wet granulation resulted in about 1.4 fold increase in dissolution rate when compared to conventional wet granulation tablets. The significant difference between flow properties and dissolution profile in between reverse wet granulation and conventional wet granulation was validated by statistical evaluation.Conclusion: Reverse wet granulation can be successfully used over the conventional wet granulation for solubility enhancement of Simvastatin. The method is easy to adopt.Â

Radiomics for Parkinson's disease classification using advanced texture-based biomarkers

Parkinson's disease (PD) is one of the neurodegenerative diseases and its manual diagnosis leads to time-consuming process. MRI-based computer-aided diagnosis helps medical experts to diagnose PD more precisely and fast. Texture-based radiomic analysis is carried out on 3D MRI scans of T1 weighted and resting-state modalities. 43 subjects from Neurocon and 40 subjects from Tao-Wu dataset were examined, which consisted of 36 scans of healthy controls and 47 scans of Parkinson's patients. Total 360 2D MRI images are selected among around 17000 slices of T1-weighted and resting scans of selected 72 subjects. Local binary pattern (LBP) method was applied with custom variants to acquire advanced textural biomarkers from MRI images. LBP histogram helped to learn discriminative local patterns to detect and classify Parkinson's disease. Using recursive feature elimination, data dimensions of around 150-300 LBP histogram features were reduced to 13-21 most significant features based on score, and important features were analysed using SVM and random forest algorithms. Variant-I of LBP has performed well with highest test accuracy of 83.33%, precision of 84.62%, recall of 91.67%, and f1-score of 88%. Classification accuracies were obtained from 61.11% to 83.33% and AUC-ROC values range from 0.43 to 0.86 using four variants of LBP. • Parkinson's classification is carried out using an advanced biomedical texture feature. Texture extraction using four variants of uniform, rotation invariant LBP method is performed for radiomic analysis of Parkinson's disorder. • Proposed method with support vector machine classifier is experimented and an accuracy of 83.33% is achieved with 10-fold cross validation for detection of Parkinson's patients from MRI-based radiomic analysis. • The proposed predictive model has proved the potential of textures of extended version of LBP, which have demonstrated subtle variations in local appearance for Parkinson's detection