Need for a paradigm for application of outcome measure (QOL scales) in head and neck cancer patients in India

Quality of life (QOL) is a multidimensional construct that minimally includes broadly defined assessments of the physical, psychological, and social domains of functioning. However, measuring this QOL is complicated by the fact that there are many different validated questionnaires available. In India, with people now wanting self-directed care and greater autonomy, we must direct increased efforts towards QOL and its assessment. We propose the Assessment, Translation & Validation, Application and Audit method to increase the use of QOL scales in our country

Experimental implementation of smart glove incorporating piezoelectric actuator for hand tremor Control

This paper examines the effectiveness of a glove specifically designed to compensate human hand tremor by incorporating a type of piezoelectric actuator. In this paper, the experimental results are divided into two parts involving actual human hand tremor and model hand-arm tremor. Both experiments were done using same measurement equipments, experimental setup and programming to evaluate the effectiveness of the glove in reducing the hand tremor. The initial experiment was done by measuring human hand tremor to determine the coherence frequency while other was performed on a hand-arm model with artificial vibration exciter to validate the response of the actual hand tremor. A number of selected sample frequencies were chosen for the experiment. Next, a piezoelectric actuator was employed as the main active element for the compensation of the tremors in both systems. The results presented both in time and frequency domains show that most tremors are readily suppressed to demonstrate the effectiveness of the proposed systems. They are considered as useful data that can be used for further investigation into the technique of effective human hand tremor suppression, particularly applicable to patients suffering from uncontrollable shaking or trembling such as in Parkinson's disease, white hand syndrome, etc. Subsequently, the output of this investigation can be also used to assist in developing advanced control strategies that involve the generation of controlled signals as the input for the piezoelectric actuator or other similar device to suppress the hand tremor. The presented system is notable for simplicity and low cost

Current status and future prospects in prosthetic voice rehabilitation following laryngectomy

Total laryngectomy or laryngopharyngectomy remains the procedure of choice for advanced-stage (UICC T3 and T4) laryngeal carcinoma around the world despite advances in conservative laryngeal surgery and radiotherapy. However, it has profound effects on respiration and deglutition, in addition to the most disabling effect-the loss of verbal communication. Successful voice restoration can be attained with any of three speech options, namely esophageal speech, electrolarynx, and tracheoesophageal (TO) speech using an artificial valve. Although, no single method is considered the best for every patient, the tracheoesophageal puncture has become the preferred method in the past decade. Several types of voice prostheses have been produced since the first prosthesis was introduced in 1980 by Blom and Singer. However, eventually all prostheses are confronted by the same problem, i.e., the development of a biofilm, leading to deterioration and ultimately to dysfunction of the prostheses, necessitating replacement. This article attempts to sum up the historical background as well as the current state of surgical voice rehabilitation following laryngectomy; we review the recent major advances as well as the future prospects. Data was collected by conducting a computer-aided search of the MEDLINE and PubMed databases, supplemented by hand searches of key journals. Over 50 articles published in the last three decades on the topic have been reviewed, out of which about 20 were found to be of relevance for this article

Federated Learning Based Enhanced FedBA with MobileNet Convolutional Neural Network for the Identification of Columnar Cactus

With the advancement in artificial intelligence (AI) technology and Internet of Things (IoT) growing popularity, the use of unmanned aerial vehicles (UAVs) as IoT devices is also being studied. However, privacy issues and limited communication resources restrict the use of unmanned aerial vehicles. Federated Learning (FL) has emerged as a promising approach for training machine learning models on decentralized devices while maintaining data privacy and reducing the communication costs. To aggregate the model on the server-side FL server uses various aggregation algorithms. One such promising aggregation algorithm is FedBA for non-identically and independently distributed (non-IID) data via UAVs. However, despite its advantages, FedBA may face challenges related to convergence speed, robustness to malicious clients, and overall efficiency. To solve these challenges, this study presents a FL model aggregation technique in which clients and servers communicate parameters as opposed to data, thereby enhancing privacy, and reducing communication costs UAVs images. This research proposes enhancements to the FedBA algorithm aimed at addressing these challenges and improving its performance. The method proposes federated learning based enhanced FedBA with MobileNet Convolutional Neural Network (CNN) for the identification of columnar cactus in the Tehuacán-Cuicatlán Valley of Mexico. Using a public dataset of over 20,000 remote sensing images, the suggested model is evaluated and found to be superior to InceptionV3 and modified MobileNet CNN. The key contributions of this work include the introduction of momentum for faster convergence, adaptive learning rates for better optimization and model aggregation clipping to prevent extreme updates. The proposed FL framework mitigates the issue of slow convergence and communication cost for non-IID data from UAVs. Enhanced FedBA more effective than typical FL algorithms. The classification accuracy before aggregation is 95% and improved to 97% after aggregation

A review: Simultaneous localization and mapping algorithms

Simultaneous Localization and Mapping (SLAM) involves creating an environmental map based on sensor data, while concurrently keeping track of the robot’s current position. Efficient and accurate SLAM is crucial for any mobile robot to perform robust navigation. It is also the keystone for higher-level tasks such as path planning and autonomous navigation. The past two decades have seen rapid and exciting progress in solving the SLAM problem together with many compelling implementations of SLAM methods. In this paper, we will review the two common families of SLAM algorithms: Kalman filter with its variations and particle filters. This article complements other surveys in this ?eld by reviewing the representative algorithms and the state-of-the-art in each family. It clearly identifies the inherent relationship between the state estimation via the KF versus PF techniques, all of which are derivations of Bayes rule

Assessment of pond water quality in Lubok Bongor, Kelantan area

Recently, the water quality is deteriorating day by day due to anthropogenic input of dissolved nutrient and organic matter and industrial effluent which is built up on its bank. So it is of vital importance to monitor and simulate the water quality parameters to ascertain whether the water is still suitable Tor various uses. Therefore in this paper, determination of the BOD and COD in the pond water samples in Lubok Bongor, Kelantan area. The BOD and COD were identified based on dissolved oxygen (DO). The results showed the value of BOD in the range of 2.58 ± 1.17 mg/L which indicated moderately clean and the demand for oxygen by the bacteria is lower. The observed value of COD was 94 .2 ± 2.44 mg/L which showed tbe presence of high concentration of chemical present in pond water. Therefore, based on the results, it can be concluded that the pond water at Lubok Bongor are still safely to use for plants

A rare myoepithelioma of the sinonasal cavity: case report

Myoepithelioma is a rare benign neoplasm. Pure accounting for less than 1% of all salivary gland tumors. Only three cases of sinonasal myoepithelioma have been reported in the literature. Diagnosis of myoepithelioma through light microscopy is possible and immunohistochemistry is done to facilitate the diagnosis. The lesion is so rare that there are no specific indications/guidelines for its treatment. We report to you a rare case of sinonasal myoepithelioma in a 57 year old Asian female

Need for a paradigm for application of outcome measure (QOL scales) in head and neck cancer patients in India

Quality of life (QOL) is a multidimensional construct that minimally includes broadly defined assessments of the physical, psychological, and social domains of functioning. However, measuring this QOL is complicated by the fact that there are many different validated questionnaires available. In India, with people now wanting self-directed care and greater autonomy, we must direct increased efforts towards QOL and its assessment. We propose the Assessment, Translation & Validation, Application and Audit method to increase the use of QOL scales in our country