Environmental Health

Larvicidal activity and Histopathological changes of extracts and their combination on .

In order to develop an eco-friendly botanical larvicide alternative to the synthetic larvicides, extracts were prepared from the (C.B.) and Syzygium aromaticum (S.A.) with hexane using a sonicator. The extracts were evaluated for larvicidal activity individually and in combination against the larvae. The LC value of C.B. and the S.A. hexane extracts tested individually were 184.2 and 363.7 µg/mL...

Deep learning-based waste detection in natural and urban environments.

Waste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems ...

Enhancing electrocardiographic analysis by combining a high-resolution 12-lead ECG with novel software tools.

INTRODUCTION: Signal-averaged electrocardiography is a non-invasive, computerized technique that amplifies, filters, and averages cardiac electrical s...

Cytocompatible manganese dioxide-based hydrogel nanoreactors for MRI imaging.

The application of nanoparticles in magnetic resonance imaging (MRI) has been greatly increasing, due to their advantageous properties such as nanosca...

The larvicidal effect of neemazal T/S, clove oil and ginger oil on tomato leafminer, compared to coragen.

The present study aimed to evaluate the toxicity and biochemical changes of 3 instar larvae affected by neemazal T/S, clove oil and ginger oil. These...

Embedded Data Imputation for Environmental Intelligent Sensing: A Case Study.

Recent developments in cloud computing and the Internet of Things have enabled smart environments, in terms of both monitoring and actuation. Unfortun...

A systematic literature review of deep learning neural network for time series air quality forecasting.

Rapid progress of industrial development, urbanization and traffic has caused air quality reduction that negatively affects human health and environme...

An efficient strategy for predicting river dissolved oxygen concentration: application of deep recurrent neural network model.

Dissolved oxygen (DO) concentration in water is one of the key parameters for assessing river water quality. Artificial intelligence (AI) methods have...

Development and validation of a sensitive and high throughput UPLC-MS/MS method for determination of paraquat and diquat in human plasma and urine: application to poisoning cases at emergency departments of hospitals.

PURPOSE: Paraquat and diquat are well-known toxic herbicides, at least responsible for hundreds of fatal poisoning events worldwide. However, the dete...

A deep-learning method for generating synthetic kV-CT and improving tumor segmentation for helical tomotherapy of nasopharyngeal carcinoma.

Megavoltage computed tomography (MV-CT) is used for setup verification and adaptive radiotherapy in tomotherapy. However, its low contrast and high no...

Study on the use of standard 12-lead ECG data for rhythm-type ECG classification problems.

BACKGROUND AND OBJECTIVES: Most deep-learning-related methodologies for electrocardiogram (ECG) classification are focused on finding an optimal deep-...

PEGylated ethyl cellulose micelles as a nanocarrier for drug delivery.

Natural polymers provide a better alternative to synthetic polymers in the domain of drug delivery systems (DDSs) because of their renewability, bioco...

Artificial intelligence-guided discovery of anticancer lead compounds from plants and associated microorganisms.

Plants and associated microorganisms are essential sources of natural products against human cancer diseases, partly exemplified by plant-derived anti...

Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction.

A wide range of applications based on sequential data, named time series, have become increasingly popular in recent years, mainly those based on the ...

Graphene oxide enhanced the endocrine disrupting effects of bisphenol A in adult male zebrafish: Integrated deep learning and metabolomics studies.

In our previous studies, it was found that graphene oxide (GO) reduced the endocrine disruption of bisphenol A (BPA) in zebrafish embryo and larvae, b...

Optimal ECG-lead selection increases generalizability of deep learning on ECG abnormality classification.

Deep learning (DL) has achieved promising performance in detecting common abnormalities from the 12-lead electrocardiogram (ECG). However, diagnostic ...

A community effort to assess and improve computerized interpretation of 12-lead resting electrocardiogram.

Computerized interpretation of electrocardiogram plays an important role in daily cardiovascular healthcare. However, inaccurate interpretations lead ...

Rapid and sensitive UHPLC-MS/MS methods for dietary sample analysis of 43 mycotoxins in China total diet study.

INTRODUCTION: Mycotoxins are toxic metabolites produced by fungi that commonly contaminate foods. As recommended by the World Health Organization, tot...

Prioritization of Mycotoxins Based on Their Genotoxic Potential with an In Silico-In Vitro Strategy.

Humans are widely exposed to a great variety of mycotoxins and their mixtures. Therefore, it is important to design strategies that allow prioritizing...

Identification of efflux proteins based on contextual representations with deep bidirectional transformer encoders.

Efflux proteins are the transport proteins expressed in the plasma membrane, which are involved in the movement of unwanted toxic substances through s...