The synthesis and characterization of the reagent 2-(5-bromothiazolylazo)-4-chlorophenol and its application in the development of a preconcentration procedure for cobalt determination using flame atomic absorption spectrometry after cloud point extraction is presented. This procedure is based on cobalt complexing and entrapment of the metal chelates into micelles of a surfactant-rich phase of Triton X-114. The preconcentration procedure was optimized by using a response surface methodology through the application of the Box-Behnken matrix. Under optimum conditions, the procedure determined the presence of cobalt with an LOD of 2.8 microg/L and LOQ of 9.3 microg/L. The enrichment factor obtained was 25. The precision was evaluated as the RSD, which was 5.5% for 10 microg/L cobalt and 6.9% for 30 microg/L. The accuracy of the procedure was assessed by comparing the results with those found using inductively coupled plasma-optical emission spectrometry. After validation, the procedure was applied to the determination of cobalt in pharmaceutical preparation samples containing cobalamin (vitamin B12).
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Sci Robot
January 2025
Department of Mechanical Engineering, University of Hong Kong, Pokfulam, Hong Kong, China.
Micro air vehicles (MAVs) capable of high-speed autonomous navigation in unknown environments have the potential to improve applications like search and rescue and disaster relief, where timely and safe navigation is critical. However, achieving autonomous, safe, and high-speed MAV navigation faces systematic challenges, necessitating reduced vehicle weight and size for high-speed maneuvering, strong sensing capability for detecting obstacles at a distance, and advanced planning and control algorithms maximizing flight speed while ensuring obstacle avoidance. Here, we present the safety-assured high-speed aerial robot (SUPER), a compact MAV with a 280-millimeter wheelbase and a thrust-to-weight ratio greater than 5.
View Article and Find Full Text PDFThe misalignment between the geometric and optical axes, combined with rotational asymmetry, poses significant challenges for achieving high-accuracy measurement of the off-axis aspheric mirror during the fabrication and polishing processes. To address this issue, this paper presents a method based on stereo deflectometry for measuring the figure of the off-axis aspheric mirror. In this method, point cloud of the off-axis aspheric mirror is first obtained using stereo deflectometry.
View Article and Find Full Text PDFOptical information synthesis, which fuses LiDAR and optical cameras, has the potential for highly detailed 3D representations. However, due to the disparity of information density between point clouds and images, conventional matching methods based on points often lose significant information. To address this issue, we propose a regional matching method to bridge the differences in information density between point clouds and images.
View Article and Find Full Text PDFSci Rep
January 2025
School of Computer Science and Technology, Liaocheng University, Liaocheng, 252000, Shandong, P.R. China.
Copy number variation (CNV) is an important part of human genetic variations, which is associated with various kinds of diseases. To tackle the limitations of traditional CNV detection methods, such as restricted detection types, high error rates, and challenges in precisely identifying the location of variant breakpoints, a new method called MSCNV (copy number variations detection method for multi-strategies integration based on a one-class support vector machine model) is proposed. MSCNV establishes a multi-signal channel that integrates three strategies: read depth, split read, and read pair.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Computer Science, Xi'an University of Architecture and Technology, Xi'an, 710055, Shaanxi Province, China.
The attention mechanism has significantly progressed in various point cloud tasks. Benefiting from its significant competence in capturing long-range dependencies, research in point cloud completion has achieved promising results. However, the typically disordered point cloud data features complicated non-Euclidean geometric structures and exhibits unpredictable behavior.
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