A hybrid YSZ/SnO2/MEMS SO2 gas sensor.

This study uses a solid YSZ electrolyte film in a SnO2 MEMS SO2 gas sensor of the semiconductor type to enhance the redox reaction. The YSZ film is prepared by RF sputtering. XRD analysis shows the presence of the (111), (200), (220) and (311) peaks that denote the crystallization planes of YSZ. The experimental results show that the SnO2 MEMS SO2 gas sensor with a YSZ film has a better sensor response than a pure SnO2 MEMS SO2 gas sensor or a YSZ MEMS SO2 gas sensor when the SO2 concentration and the sensor's temperature sensors are 250 ppb and 400 °C, respectively. The YSZ/SnO2 sensor's measured responses are around 6%, 45%, 20% and 16% when the sensor is respectively operated at 250 °C, 300 °C, 350 °C, and 400 °C.

Through-silicon via submount for the CuO/Cu2O nanostructured field emission display.

A three dimensional (3D) field emission display structure was prepared using CuO/Cu2O composite nanowires (NWs) and a three dimensional through silicon via (3D-TSV) technique. The experimental results indicated that the diameter and length of the Si via were about 100 µm and 200 µm, respectively. For the 3D field emission structure, high-density CuO/Cu2O composite nanowires (NWs) were grown on the concave TSV structure using thermal oxidation. The field emission turn-on field and enhancement factor of the CuO/Cu2O composite NWs were 15 V µm-1 and ∼1748, respectively. With regard to field emission displays, we successfully used the 3D field emission structure to excite the orange phosphors.

Dissipation kinetics, safety evaluation, and preharvest interval assessment of trichlorfon application on rice.

Nowadays, there is an urgent need for the investigation of the field dissipation and assessment of the preharvest interval for trichlorfon residues on rice. To protect consumers from potential health risks, this study can provide references for the safe application of trichlorfon in the rice fields. Results of the field dissipation study showed that the dissipation dynamic equations of trichlorfon were based on the first-order reaction dynamic equations and that the dissipation rates vary among rice plant, brown rice, rice bran, soil, and water. The 2-year field trials conducted in Yangzhou and Xiaogan suggested the interval of each application for trichlorfon on rice to be at least 7 days when 80 % trichlorfon SP was sprayed with a dose ranges between 80 and 160 a.i g/667 m(2). Additionally, the preharvest interval of the last application should be at least 15 days to ensure the amounts of residues below the maximum residue limits of trichlorfon on brown rice (0.1 mg/kg).

Systematic identification of multiple tumor types in microarray data based on hybrid differential evolution algorithm.

Correct classification and prediction of tumor cells are essential for microarrays to construct a diagnostic system. Differential evolution (DE) is a powerful optimization algorithm, which has been widely used in many areas. However, the standard DE and most of its variants search in the continuous space, which cannot solve the binary optimizations directly. In this paper, the hybrid framework based on the binary DE algorithm and silhouette filter, is proposed to improve searching ability to classify breast and leukemia cancers in microarray for biomarker discovery. The study is focused to use hybrid DE algorithm for gene selection and silhouette statistics as a discriminant function to classify multiple tumor types in microarray data. Distance metrics on silhouette statistics have also been discussed for high classification accuracy. Experimental results show that the hybrid method is effective to discriminate breast and leukemia cancer subtypes and find potential biomarkers for cancer diagnosis.

Systematic identification of multiple tumor types in microarray data based on hybrid differential evolution algorithm.

Correct classification and prediction of tumor cells are essential for microarrays to construct a diagnostic system. Differential evolution (DE) is a powerful optimization algorithm, which has been widely used in many areas. However, the standard DE and most of its variants search in the continuous space, which cannot solve the binary optimizations directly. In this paper, the hybrid framework based on the binary DE algorithm and silhouette filter, is proposed to improve searching ability to classify breast and leukemia cancers in microarray for biomarker discovery. The study is focused to use hybrid DE algorithm for gene selection and silhouette statistics as a discriminant function to classify multiple tumor types in microarray data. Distance metrics on silhouette statistics have also been discussed for high classification accuracy. Experimental results show that the hybrid method is effective to discriminate breast and leukemia cancer subtypes and find potential biomarkers for cancer diagnosis.