Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework.

Sensor networks generate vast amounts of data in real-time, which challenges existing predictive maintenance frameworks due to high latency, energy consumption, and bandwidth requirements. This research addresses these limitations by proposing an edge-cloud hybrid framework, leveraging edge devices for immediate anomaly detection and cloud servers for in-depth failure prediction. A K-Nearest Neighbors (KNNs) model is deployed on edge devices to detect anomalies in real-time, reducing the need for continuous data transfer to the cloud.

Status of Inappropriate Complementary Feeding and Its Associated Factors Among Infants of 9-23 Months.

Inappropriate complementary feeding during the first two years of life significantly impacts children's health, increasing risks of malnutrition and illness. : This study investigates factors influencing early feeding patterns among 600 mothers of children aged 9-23 months in selected hospitals in Punjab, Pakistan. Using a structured questionnaire, data were collected and analyzed, with associations measured by odds ratios (ORs) and 95% confidence intervals (CIs).

A novel and efficient digital image steganography technique using least significant bit substitution.

Steganography is used to hide sensitive types of data including images, audio, text, and videos in an invisible way so that no one can detect it. Image-based steganography is a technique that uses images as a cover media for hiding and transmitting sensitive information over the internet. However, image-based steganography is a challenging task due to transparency, security, computational efficiency, tamper protection, payload, etc.

Thyroid Eye Disease and Artificial Intelligence: A Comparative Study of ChatGPT-3.5, ChatGPT-4o, and Gemini in Patient Information Delivery.

Purpose: This study aimed to compare the effectiveness of 3 artificial intelligence language models-GPT-3.5, GPT-4o, and Gemini, in delivering patient-centered information about thyroid eye disease (TED). We evaluated their performance based on the accuracy and comprehensiveness of their responses to common patient inquiries regarding TED.

Development of a Tandem Mass Spectral Library for the Detection of Triterpenoids in Plant Metabolome Based on Reference Standards.

Plant triterpenoids represent a diverse group of secondary metabolites and are thought to be valuable for therapeutic applications. For drug development, lead optimization, better knowledge of biological pathways, and high-throughput detection of secondary metabolites in plant extracts are crucial. This paper describes a qualitative method for the rapid and accurate identification of various triterpenoids in plant extracts using the LC-HR-ESI-MS/MS tool in combination with the data-dependent acquisition (DD) approach.