A solid-phase extraction procedure using mini-columns packed with Chelex-100 and two new chelating agents based on poly(vinyl chloride) functionalized with 3-ferrocenyl-3-hydroxydithioacrylic acid and N,N'-[1,1'-dithiobis(ethylene)]-bis(salicylideneimine) (H(2)sales) loaded on microcrystalline naphthalene, is reported. The columns were used to separate labile copper fractions in model solutions and in real samples with subsequent determination using electrothermal atomic absorption spectrometry (ETAAS). Various model solutions containing 20 microg L(-1) of Cu(2+) and 0.0, 0.2, 2.0 and 20.0 mg L(-1) of humic acid, respectively, and buffered to pH 6.0, 7.0 and 8.0 were considered. Results showed a decrease in labile copper fraction with increase in humic acid concentration. Application of the procedure to speciation of Cu, Ni, Zn and Pb in various environmental water samples yielded labile fractions in the range of 1.67-55.75% against a total dissolved fraction of 44.08-69.77%. Comparison of the three chelating agents showed that H(2)sales had a weaker metal chelating strength than Chelex-100, but PVC-FSSH had comparable chelating strength to Chelex-100.
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http://dx.doi.org/10.1016/j.jhazmat.2009.07.119 | DOI Listing |
Sci Rep
January 2025
Department of Human Movement Science, Hunan Normal University, 36 Lushan Road, Changsha, Hunan, China.
Loneliness and low self-esteem are among the more prominent mental health problems among left-behind children, but most of the current research stays in cross-sectional surveys, with fewer studies proposing specific solutions. In addition, although the effective impact of dance interventions on loneliness and self-esteem has been demonstrated, the impact in the group of left-behind children remains under-explored. Therefore, this study validated the effectiveness of a dance intervention on loneliness and self-esteem in left-behind children through a 16-week randomised controlled trial.
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January 2025
Neurofibromatosis Type 1 Center and Laboratory for Neurofibromatosis Type 1 Research, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
Deep-learning models have shown promise in differentiating between benign and malignant lesions. Previous studies have primarily focused on specific anatomical regions, overlooking tumors occurring throughout the body with highly heterogeneous whole-body backgrounds. Using neurofibromatosis type 1 (NF1) as an example, this study developed highly accurate MRI-based deep-learning models for the early automated screening of malignant peripheral nerve sheath tumors (MPNSTs) against complex whole-body background.
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January 2025
Xingtai Naknor Technology Co., Ltd, Xingtai, 054000, China.
The heating oil circuit plays an essential role in the heating calendering roller for the lithium battery pole piece. To achieve the optimization of the heating oil circuit, a fluid-thermal-structural coupling method and a multi-objective optimization procedure are proposed to obtain the optimal solution. A fluid-thermal-structural coupling flowchart based on the numerical modeling for the calendering roller temperature distribution is created to automate the analysis processes in the optimization iteration.
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January 2025
Department of Physics, Khalifa University of Science and Technology, 127788, Abu Dhabi, United Arab Emirates.
In this study, biopolymer composites based on chitosan (CS) with enhanced optical properties were functionalized using Manganese metal complexes and black tea solution dyes. The results indicate that CS with Mn-complexes can produce polymer hybrids with high absorption, high refractive index and controlled optical band gaps, with a significant reduction from 6.24 eV to 1.
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January 2025
School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, India.
This study introduces a novel ensemble learning technique namely Multi-Armed Bandit Ensemble (MAB-Ensemble), designed for lane detection in road images intended for autonomous vehicles. The foundation of the proposed MAB-Ensemble technique is inspired in terms of Multi-Armed bandit optimization to facilitate efficient model selection for lane segmentation. The benchmarking dataset namely TuSimple is used for training, validating and testing the proposed and existing lane detection techniques.
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