AI Article Synopsis
- A new method using cloud point extraction (CPE) was developed for isolating trace amounts of cadmium (Cd) before measuring it with flame atomic absorption spectrometry.
- Cadmium forms hydrophobic chelates with 8-hydroxyquinoline, which are then extracted using a surfactant in an alkaline environment, while octanol helps lower the cloud point during extraction.
- The method shows high accuracy with a linear detection range of 10-500 μg/L, low detection limits (0.21 μg/L), and good recovery rates (94.1-103.8%) from spiked water samples.
Article Abstract
A method based on cloud point extraction (CPE) separation/preconcentration of trace cadmium (Cd) as a prior step to its determination by flame atomic absorption spectrometry has been developed. Cadmium reacted with 8-hydroxyquinoline to form hydrophobic chelates, which were extracted into the micelles of nonionic surfactant oligoethylene glycol monoalkyl ether (Genapol X-080) in an alkaline medium. Octanol was used to depress the cloud point of Genapol X-080 in the extraction process. The chemical variables that affect the CPE, such as pH of complexation reaction, amount of chelating agent, Genapol X-080 and octanol were evaluated and optimized. Under optimized conditions, linearity was obeyed in the range of 10-500 μg/L, with the correlation coefficient of 0.9993. For 5 mL of sample solution, the enhancement factor was about 20. The limit of detection and limit of quantification of the method were 0.21 and 0.63 μg/L, respectively. The relative standard deviations (n = 6) was 3.2% for a solution containing 100 μg/L of Cd. The accuracy of the preconcentration system was evaluated by recovery measurements on spiked water samples. Recoveries of spiked samples varied in the range of 94.1-103.8%.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.2166/wst.2014.263 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
LBNP: Learning features between neighboring points for point cloud classification.
PLoS One
January 2025
School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing, China.
Inspired by classical works, when constructing local relationships in point clouds, there is always a geometric description of the central point and its neighboring points. However, the basic geometric representation of the central point and its neighborhood is insufficient. Drawing inspiration from local binary pattern algorithms used in image processing, we propose a novel method for representing point cloud neighborhoods, which we call Point Cloud Local Auxiliary Block (PLAB).
View Article and Find Full Text PDFEnhancing land feature classification with the BTR Extractor: A novel software package for high-accuracy analysis of aerial laser scan data.
MethodsX
June 2025
Department of Remote Sensing and GIS, Science and Research Branch, Islamic Azad University, Tehran, Iran.
The semi-automatic and automatic extraction of land features such as buildings, trees, and roads using aerial laser scan data is crucial in land use change studies and urban management. This research introduces the "BTR" extractor, a novel software package designed to enhance classification accuracy of phenomena identified in the super points obtained from aerial laser scanners. Our method focuses on:-Comparing classification methods using airborne laser scanning data.
View Article and Find Full Text PDFNear real-time change detection tool for photogrammetric flood preparedness.
Environ Monit Assess
January 2025
Technische Hochschule Nürnberg Georg Simon Ohm, Institute of Hydraulic Engineering and Water Resources Management, Nuremberg, Germany.
Through the mobilization of movable objects due to the extreme hydraulic conditions during a flood event, blockages, damage to infrastructure, and endangerment of human lives can occur. To identify potential hazards from aerial imagery and take appropriate precautions, a change detection tool (CDT) was developed and tested using a study area along the Aisch River in Germany. The focus of the CDT development was on near real-time analysis of point cloud data generated by structure from motion from aerial images of temporally separated surveys, enabling rapid and targeted implementation of measures.
View Article and Find Full Text PDFHybrid salp swarm maximum power point tracking algorithm for photovoltaic systems in highly fluctuating environmental conditions.
Sci Rep
January 2025
Department of Electrical Engineering, Imam Khomeini Naval Science University of Nowshahr, Nowshahr, Iran.
The maximum power delivered by a photovoltaic system is greatly influenced by atmospheric conditions such as irradiation and temperature and by surrounding objects like trees, raindrops, tall buildings, animal droppings, and clouds. The partial shading caused by these surrounding objects and the rapidly changing atmospheric parameters make maximum power point tracking (MPPT) challenging. This paper proposes a hybrid MPPT algorithm that combines the benefits of the salp swarm algorithm (SSA) and hill climbing (HC) techniques.
View Article and Find Full Text PDFParkinson's disease screening using a fusion of gait point cloud and silhouette features.
PLoS One
January 2025
Department of Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia.
Article Synopsis
- Parkinson's Disease (PD) is a progressive neurodegenerative disorder characterized by slow movement, and while there is no cure, early detection can improve outcomes.
- Vision-based methods for PD detection focus on analyzing gait, utilizing both appearance-based and model-based approaches.
- A new method that combines these two approaches has shown promising results, achieving an AUC of 0.87 and F1-Scores of 0.82 in distinguishing between normal and Parkinsonian gait.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!