Evaluation of method for simultaneous determination of pesticide residues in fruits and vegetables by collaborative study

A collaborative study involving 8 laboratories was conducted to evaluate a method for the simultaneous determination of pesticide residues in 6 types of fruits and vegetables (spinach, tomato, apple, radish, cabbage and carrot). The method of analysis was the same as reported by Kakimoto et al. in 2003. One hundred and thirty-nine pesticides were spiked by each of 8 laboratories at levels of 0.1 microg/g (pesticides analyzed by GC/MS) or 0.5 microg/g (pesticides analyzed by HPLC) into the 6 kinds of samples. Statistical analysis showed that 111 pesticides could be analyzed with practical precision by this method. For screening purposes, the method could analyze 118 pesticides. The median values of the limits of detection were 0.001-0.041 microg/g. The calibration curves were linear in the range of 0.5-5 microg/mL for most pesticides with median correlation coefficients of 0.983-1.000.     

Deep-ultraviolet Raman microspectroscopy: characterization of wide-gap semiconductors

We have developed a high-throughput deep-ultraviolet (DUV) Raman microspectrometer with excitation from a continuous wave (cw) laser operated at 244 nm that enables us to characterize thin surface layers of wide-gap semiconductors. This spectrometer system consists of a filter spectrometer for the rejection of stray light and a high-dispersion spectrograph combined with a liquid nitrogen cooled charge-coupled device (CCD) detector and extends the low-frequency limit of the observable spectral range down to 170 cm(-1). In the microscope we use a Cassegrain reflective objective for the collection of the scattered light and an off-axis mirror for introduction of the excitation laser light. DUV Raman spectroscopy has been applied for studying wide-gap semiconductors including SiC and AlGaN epitaxial films and shallow implanted layers of these materials. Raman spectra of various crystals have also been measured for examining the performance of this system. Resonance enhancement of Raman bands has been observed for several semiconductors, and the results are discussed.     

Performance evaluation system for probabilistic neural network hardware

The probabilistic neural network (PNN) is one of the most promising neural networks, and is now applied to some real-world applications. In order to speed up the PNN calculation considerably, we have developed a PNN hardware system for video image recognition. The performance of the PNN hardware cannot be evaluated precisely until the evaluation system is completed. In this study, we developed a performance evaluation system for the PNN hardware and demonstrated it using the developed evaluation system.This work was presented, in part, at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

Selection of manipulator system for multiple-goal task by evaluating task completion time and cost with computational time constraints

The focus of this study is on the problem of manipulator system selection for a multiple-goal task by evaluating task completion time and cost with computational time constraints. An approach integrating system selection, structural configuration design, layout design, motion planning, and relative cost calculation is proposed to solve this problem within a reasonable computational time. In the proposed approach, multiple-objective particle swarm optimization (MOPSO) is utilized to search for the appropriate manipulator system with appropriate structural configuration from a set of candidate systems. Particle swarm optimization (PSO) and the nearest neighborhood algorithm are employed in layout design and motion planning due to their high convergence speed. Three methods involving a random search algorithm are compared to the proposed approach through a simulation. The simulation is done with a set of tasks and the result shows the effectiveness of the proposed approach.     

A new Landsat 8 cloud discrimination algorithm using thresholding tests

ABSTRACT

In this work, we propose a Cloud Discrimination Algorithm for Landsat 8 (CDAL8) to improve a high-frequency automatic land change detection system developed at the National Institute of Advanced Industrial Science and Technology (AIST), Japan for large-scale satellite image analysis. Although the land change detection system can process several kinds of satellite remote sensing data, improvements are needed to enable practical applications using Landsat 8 data. Cloud discrimination is a necessary pre-processing step for land cover change detection. Currently, most of the prediction errors on land change detection are caused by the false cloud discrimination results as a pre-processing step. Therefore, we introduce an improved cloud discrimination algorithm (CDAL8) in this study to improve the overall performance of our land change detection system. The algorithm was developed based on a Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask algorithm and Cloud and Aerosol Unbiased Decision Intellectual Algorithm (CLAUDIA). CDAL8 is distinct in that it switches judgment tests and their thresholds using a threshold brightness temperature and uses separate features in cloud judgment and clear-sky judgment. To evaluate the accuracy of the proposed algorithm, we compared it with the Automated Cloud-Cover Assessment algorithm (ACCA) and Function of Mask (Fmask) version 3.3 using US Geological Survey Landsat 8 cloud cover assessment validation data, which contain 96 cloud masks. Our proposed cloud discrimination algorithm (CDAL8) have promising results with an accuracy of 88.1%, which was greater than that of the ACCA (82.5%) and Fmask (84.6%). Furthermore, we also confirmed that the average accuracy of CDAL8 was approximately 91.2% when low solar elevation scenes were removed.     

Rapid somatic growth after birth in children with neuroblastoma: A survey of 1718 patients with childhood cancer in Kyushu-Okinawa district

OBJECTIVE: To evaluate the association of somatic growth from birth through diagnosis with the development of childhood cancer. METHODS: The weights and heights of 1718 children with cancers were determined and converted into standard deviation (SD) scores, both at birth and at diagnosis, by using the means and SD values of the general population. RESULTS: Among patients with neuroblastoma and acute lymphoblastic leukemia, the percentages of children with body weight and height over mean + 2 SDs were significantly higher at diagnosis than the expected value in the general population. The percentage of children with neuroblastoma and body weight over mean + 2 SD increased significantly from birth through diagnosis (P =.04). Although the medians of weight SD scores decreased from birth through diagnosis in patients with representative cancers except for neuroblastoma, the value significantly increased in patients with neuroblastoma diagnosed before 1 year of age (P =.03), especially in those whose cancer was detected by mass screening at 6 months of age (P <.01). CONCLUSIONS: Rapid somatic growth from birth through diagnosis in patients with neuroblastoma diagnosed before 1 year of age suggests a possible involvement of certain growth factors in these patients.     

Formation and characterization of copper tetrakis (4-cumylphenoxy) phthalocyanine:perylene solar cells

Perylene-based bulk heterojunction solar cells with copper tetrakis (4-cumylphenoxy) phthalocyanine (Tc-CuPc) and heterojunction solar cells with copper phthalocyanine (CuPc) were produced and characterized. A device based on CuPc and perylene provided better efficiency, fill factor, short-circuit current and open-circuit voltage compared to those of a device based on Tc-CuPc and perylene. The Tc-CuPc:perylene structure was examined by transmission electron microscopy, which indicated mixtured microstructure. Energy levels of the molecules were calculated and discussed.