Teleophthalmology: A Model for Eye Care Delivery in Rural and Underserved Areas of India

Objectives. To describe the application of teleophthalmology in rural and underserved areas of India. Study Design. This paper describes the major teleophthalmology projects in India and its benefits. Results. Teleophthalmology is the use of telecommunication for electronic transfer of health-related data from rural and underserved areas of India to specialities in urban cities. The MDRF/WDF Rural Diabetes Project has proved to be very beneficial for improvement of quality health care in Tamilnadu and can be replicated at the national level. This community outreach programme using telemedicine facilities has increased awareness of eye diseases, improved access to specialized health care, helped in local community empowerment, and provided employment opportunities. Early detection of sight threatening disorders by teleophthalmology and prompt treatment can help decrease visual impairment. Conclusion. Teleophthalmology can be a very effective model for improving eye care delivery system in rural and underserved areas of India

Performance Analysis of Routing Protocol Using Trust-Based Hybrid FCRO-AEPO Optimization Techniques

Mobile Ad hoc Networks (MANETs) offer numerous benefits and have been used in different applications. MANETs are dynamic peer-to-peer networks that use multi-hop data transfer without the need for-existing infrastructure. Due to their nature, for secure communication of mobile nodes, they need unique security requirements in MANET. In this work, a Hybrid Firefly Cyclic Rider Optimization (FCRO) algorithm is proposed for Cluster Head (CH) selection, it efficiently selects the CH and improves the network efficiency. The Ridge Regression Classification algorithm is presented in this work to sense the malicious nodes in the network and the data is transmitted using trusted Mobile nodes for the QoS enactment metric improvement. A trust-based routing protocol (TBRP) is introduced utilizing the Atom Emperor Penguin Optimization (AEPO) algorithm, it identifies the best-forwarded path to moderate the routing overhead problem in MANET. The planned method is implemented using Matlab software and the presentation metrics are packet delivers ratio, packet loss ratio (PLR), routing overhead, throughput, end-to-end delay (E2ED), transmission delay, energy consumption and network lifetime. The suggested AEPO algorithm is compared with the prevailing PSO-GA, TID-CMGR, and MFFA. The AEPO algorithm’s performance is approximately 1.5%, 3.2%, 2%, 3%, and 4% higher than the existing methods for PLR, packet delivers ratio, throughput, and E2ED and network lifetime. The sender nodes can increase their information transmission rates and reduce delays in appreciation of this evaluation. Additionally, the suggested technique has a perfect benefit in terms of demonstrating the genuine contribution of distinct nodes to trust evaluation (TE)

A Trust and Node Capability Model for Reliable and Secure MANET Communication

The Mobile Ad-hoc Network (MANET) is a rapidly deployable network. That is valuable for industrial and domestic applications due to flexible, mobile, and wireless communication. But the network is constrained with resources and security. In this paper, we are presenting a node capability based trusted routing named TNC-AODV for MANET. It is a hybrid approach for maintaining route reliability and security. The model is composed of the property of node capability and Trust. The Node capability is defined by the quality of service parameters like remaining energy, available bandwidth, buffer length, and mobility pattern. The aim is to ensure the discovery of reliable routes. Additionally, the trust is implemented by using a local and global trust for securing the network. The TNC-AODV is implemented through modification of AODV routing. That routing technique has been tested on three security threats namely Black-hole, wormhole, and DOS flooding attack. The simulation has been carried out using the NS2 simulator. The experimental results demonstrate that TNC-AODV provides security against attacks. Additionally, improve the packet delivery ratio, and throughput. Finally, the possible and feasible future extension of the work has also been proposed

Ethnomedicinal Plants of the Tirunelveli District, Tamil Nadu, India

This study was carried out in several geographically isolated pockets of the Tirunelveli district, Tamil Nadu, India, in a region inhabited by a tribal group called the Kanikkars. The authors found that a total of 80 plant species belonging to 72 genera and 46 families were used by the natives of the study area for the treatment of such ailments as diabetes, rheumatism, jaundice, fever, cold, cough and snake bite. The full results of this study are organized in table form and include the species botanical name, parts used, method of administration, dosage, and the local or vernacular names of the species

Exploring Quantum Machine Learning Algorithms for Enhanced Data Analysis

The rapid increase of records generation throughout diverse domain names has necessitated the development of superior records analysis techniques. Quantum gadget mastering (QML) has emerged as a promising paradigm that harnesses the computational power of quantum systems to beautify information evaluation duties. This studies paper explores the software of quantum machine getting to know algorithms to cope with demanding situations in information analysis, highlighting their capacity for progressed performance and scalability. We provide an overview of key QML algorithms, talk their blessings, and gift case research demonstrating their effectiveness in actual-global statistics evaluation eventualities. Finally, we outline the cutting-edge kingdom of QML research and speak destiny directions for its software in records evaluation

Transforming Education: Understanding How Social Innovation Makes a Difference in Education Sector

In the face of persistent educational challenges and the evolving demands of the 21st century, social innovation has emerged as a beacon of hope, offering a transformative approach to reimagine and reshape education systems. This paper delves into the concept of social innovation in the education sector, elucidating its defining characteristics, examining its profound benefits, and acknowledging the challenges it presents. Through a comprehensive review of existing literature, the paper showcases compelling case studies and examples of successful social innovations that have revolutionized educational landscapes. Education, the cornerstone of societal progress, faces persistent challenges in the 21st century. Social innovation emerges as a beacon of hope, offering a transformative approach to reshape education systems. Social innovation in education aims to address social needs, fosters collaborative partnerships, and prioritizes sustainability. It seeks to dismantle educational inequities and empower all learners to reach their full potential. The benefits of social innovation include enhanced learning outcomes, championed equity and inclusion, and preparation for the future. However, sustainability, scalability, measurement, and collaboration pose significant challenges. A growing body of research showcases successful social innovations that have revolutionized educational landscapes. Embracing social innovation can pave the way for a more equitable, effective, and future-ready education system

Modelling of Implantable Drug Delivery System in Tumor Microenvironment Using Molecular Communication Paradigm

© 2013 IEEE. Local delivery of anticancer drug in tumor using miniaturized implants over a prolonged period of time is a powerful treatment strategy that provides lower toxicity and higher drug bioavailability compared to conventional systemic chemotherapy. Prediction of anticancer drug distribution in tumor following implantation of the drug implant is necessary to improve and optimize the implantable drug delivery systems (IDDSs). In this paper, we develop mathematical and stochastic simulation models for the prediction of spatiotemporal concentration of anticancer doxorubicin following implantation of a dual-release implant in an isolated tumor microenvironment (TME). Our model utilizes mathematical convolution of the channel impulse response (CIR) with the drug release function based on the abstraction of molecular communication. The derived CIR can be used to obtain drug concentration profile in the surrounding tissue for various release profiles and different anticancer drugs. We derive closed-form analytical expression for anticancer drug concentration. The required release rates are obtained by fitting the experimental data on dual-release implant available in the literature to a mathematical expression. In addition, we also present a particle-based stochastic simulator and compare the results with those predicted by the analytical model. The accuracy of predictions by both the models is further verified by comparing with the published experimental data in the literature. Both the proposed models can be useful for the design optimization of the implantable drug delivery systems (IDDSs) in tumors and other tissues and can potentially reduce the number of animal experiments thus saving cost and time

Modelling of combination therapy using implantable anticancer drug delivery with thermal ablation in solid tumor.

Local implantable drug delivery system (IDDS) can be used as an effective adjunctive therapy for solid tumor following thermal ablation for destroying the residual cancer cells and preventing the tumor recurrence. In this paper, we develop comprehensive mathematical pharmacokinetic/pharmacodynamic (PK/PD) models for combination therapy using implantable drug delivery system following thermal ablation inside solid tumors with the help of molecular communication paradigm. In this model, doxorubicin (DOX)-loaded implant (act as a transmitter) is assumed to be inserted inside solid tumor (acts as a channel) after thermal ablation. Using this model, we can predict the extracellular and intracellular concentration of both free and bound drugs. Also, Impact of the anticancer drug on both cancer and normal cells is evaluated using a pharmacodynamic (PD) model that depends on both the spatiotemporal intracellular concentration as well as characteristics of anticancer drug and cells. Accuracy and validity of the proposed drug transport model is verified with published experimental data in the literature. The results show that this combination therapy results in high therapeutic efficacy with negligible toxicity effect on the normal tissue. The proposed model can help in optimize development of this combination treatment for solid tumors, particularly, the design parameters of the implant

Quantum Computing Algorithms for Solving Complex Mathematical Problems

The power of quantum mechanics, that is too complex for conventional computers, can be solved by an innovative model of computing known as quantum computing. Quantum algorithms can provide exponential speedups for some types of problems, such as many difficult mathematical ones. In this paper, we review some of the most important quantum algorithms for hard mathematical problems. When factoring large numbers, Shor's algorithm is orders of magnitude faster than any other known classical algorithm. The Grover's algorithm, which searches unsorted databases much more quickly than conventional algorithms, is then discussed. &nbsp

Modelling of multilayer biological medium under molecular communication paradigm

© 2017 IEEE. Molecular communication is an emerging paradigm that enables both the biological and synthetic nanomachines to communicate with each other within an aqueous biological environment such as the communication between living cells. Prediction of the number of drug molecules near a target site, e.g., tumor cells, is very important for determining the required drug dosages to increase positive therapeutic outcomes. In this paper, we derive an analytical expression for the received molecular signal in a multilayered biological environment. We also present development of particle-based simulator. We find the analytical results for three-layer biological medium compares well with the simulation results. The effect of the diffusion coefficient and the distance between the transmitter and the receiver (e.g., targeted cells) are also investigated