Effects of caffeine ingestion and thermotherapy on blood orexin circulation in humans

Food Science and Biotechnology - Caffeine and orexin can affect awakening, neuroendocrine, and sympathetic nerve function. Our previous study has reported that caffeine intake can increase human...     

Efficient deep-blue emitters based on triphenylamine-linked benzimidazole derivatives for nondoped fluorescent organic light-emitting diodes

Two triphenylamine-substituted benzimidazole derivatives were synthesized for use as efficient deep-blue emitters in nondoped fluorescent organic light-emitting diodes (FLOLEDs). The molecular design of 4′,4′′-(1H-benzo[d]imidazole-1,2-diyl)bis(N,N-diphenylbiphenyl-4-amine) (T2B) to limit the molecular packing density enabled T2B-based devices to suppress the exciton quenching by a bulky three-dimensional structure. Nondoped FLOLEDs fabricated using T2B as a blue emitter exhibited an external quantum efficiency of 4.67% with color coordinates of (0.15, 0.08).     

Epitaxial lift-off GaAs HEMT's

An extensive study of epitaxial lift-off (ELO) Al_0.3Ga _0.7As/GaAs modulation doped heterostructure high electron mobility field-effect transistors (HEMT's) is presented. Effects of ELO on electron transport properties of two-dimensional electron gas at AlGaAs/GaAs interface are investigated. An ELO HEMT with 1.5 μm gate length had a maximum extrinsic transconductance g_m-max=125 mS/mm, a unity current gain cut-off frequency f_t=10.5 GHz, and a maximum frequency of oscillation f_max=12 GHz. Statistical distributions of maximum intrinsic transconductance of ELO HEMT's are presented and compared with their on-wafer counterparts. Stability of the ELO HEMT's has also been evaluated by continuous operation at room temperature under dc bias     

Simple K-band MMIC VCO utilizing a miniaturized hairpin resonator and a three-terminal p-HEMT varactor with low phase noise and high output power properties

Presents a fully monolithic K-band MMIC voltage-controlled oscillator (VCO) implemented by using a 0.25 /spl mu/m AlGaAs/InGaAs pseudomorphic HEMT (p-HEMT) technology. The use of a half-wavelength miniaturized hairpin-shaped resonator and a three-terminal p-HEMT varactor was effective in reducing the chip size and simplifying fabrication processes of the microwave MMIC VCO without impairing the performance of the circuit. The VCO provides a typical output power of 11.5 dBm at 20.8 GHz and a free-running phase noise of -82 dBc/Hz at 100 kHz offset and -95 dBc/Hz at 1 MHz offset. It also shows a tuning range of 70 MHz with little reduction in output power and high yield properties. The chip size of the MMIC VCO is 1.5 /spl times/ 2.0 mm/sup 2/.     

Chemosensors for pyrophosphate

The selective detection of the anion pyrophosphate (PPi) is a major research focus. PPi is a biologically important target because it is the product of ATP hydrolysis under cellular conditions, and because it is involved in DNA replication catalyzed by DNA polymerase, its detection is being investigated as a real-time DNA sequencing method. In addition, within the past decade, the ability to detect PPi has become important in cancer research. In general, the sensing of anions in aqueous solution requires a strong affinity for anions in water as well as the ability to convert anion recognition into a fluorescent or colorimetric signal. Among the variety of methods for detecting PPi, fluorescent chemosensors and colorimetric sensors for PPi have attracted considerable attention during the past 10 years. Compared with the recognition of metal ions, it is much more challenging to selectively recognize anions in an aqueous system due to the strong hydration effects of anions. Consequently, the design of PPi sensors requires the following: an understanding of the molecular recognition between PPi and the binding sites, the desired solubility in aqueous solutions, the communicating and signaling mechanism, and most importantly, selectivity for PPi over other anions such as AMP and ADP, and particularly phosphate and ATP. This Account classifies chemosensors for PPi according to topological and structural characteristics. Types of chemosensors investigated and reported in this study include those that contain metal ion complexes, metal complexes combined with excimers, those that function with a displacement approach, and those based on hydrogen-bonding interaction. Thus far, the utilization of a metal ion complex as a binding site for PPi has been the most successful strategy. The strong binding affinity between metal ions and PPi allows the detection of PPi in a 100% aqueous solution. We have demonstrated that carefully designed receptors can distinguish between PPi and ATP based on their different total anionic charge densities. We have also demonstrated that a PPi metal ion complex sensor has a bioanalytical application. This sensor can be used in a simple and quick, one-step, homogeneous phase detection method in order to confirm DNA amplification after polymerase chain reaction (PCR).     

Harvesting of <Emphasis Type="Italic">Scenedesmus obliquus</Emphasis> cultivated in seawater using electro-flotation

Seawater, when supplemented to a growth medium, appears to stimulate auto-flocculation of a certain microalgae species like Scenedesmus obliquus and thus renders its harvesting easy. To make use of this unique response for the purpose of biomass harvesting, S. obliquus was grown in a seawater-added medium and then collected in electrochemically- mediated ways. Significantly higher harvesting efficiency and energy saving were observed with electroflotation (EF) than with electro-coagulation-flotation (ECF) and the standard BG11 medium. An optimal EF condition, the highest recovery rate with least energy use, was found with a supply of 0.5 A. Seawater amendment was most beneficial in a level of 10%. All this clearly showed that applying EF to cells cultivated in the seawater-supplemented medium is a promising harvesting means that enables one to obtain algae biomass without interfering with the downstream process of biodiesel production.     

Electrochemical synthesis of ammonia from water and nitrogen catalyzed by nano-Fe<Subscript>2</Subscript>O<Subscript>3</Subscript> and CoFe<Subscript>2</Subscript>O<Subscript>4</Subscript> suspended in a molten LiCl-KCl-CsCl electrolyte

Nano-Fe₂O₃ and CoFe₂O₄ were suspended in molten salt of alkali-metal chloride (LiCl-KCl-CsCl) and their catalytic activity in electrochemical ammonia synthesis was evaluated from potentiostatic electrolysis at 600 K. The presence of nanoparticle suspension in the molten chloride resulted in improved production of NH₃, recording NH₃ synthesis rate of 1.78×10^?10 mol s^?1 cm^?2 and 3.00×10^?10 mol s^?1 cm^?2 with CoFe₂O₄ and Fe₂O₃, which are 102% and 240% higher than that without the use of a nanocatalyst, respectively. We speculated that the nanoparticles triggered both the electrochemical reduction of nitrogen and also chemical reaction between nitrogen and hydrogen that was produced from water electro-reduction on cathode. The use of nanocatalysts in the form of suspension offers an effective way to overcome the sluggish nature of nitrogen reduction in the molten chloride electrolyte.     

CuO formation control as a function of mixed ratio of Cu-free powders in the synthesis of YBCO superconductors on Cu substrates

YBa₂Cu₃O_x (Y123) superconducting films were fabricated on Cu substrates using a simple screen-printing method, from Cu-free powders (Y₂O₃ and BaCO₃). In the process, CuO, which causes superconducting properties of Y123 films to deteriorate, was formed on the film surface. By varying the atomic ratio of Y to Ba (Y:Ba = 1:1∼1:4), the ratio needed to prevent CuO formation was found for the film surface that had been heat-treated at 980^∘C for 17 s. The film, with the ratio of Y to Ba (Y:Ba = 1:1), is reheat-treated at 930^∘C for 9 min 30 s to form a superconducting Y123 phase. It was possible to prevent CuO formation by controlling the ratio of Cu-free powders in the mixture and to fabricate YBCO superconductors on Cu substrates using a two-step heat-treatment.     

Structural and optical properties of GaxIn1−xP layers grown by chemical beam epitaxy

Chemical beam epitaxial (CBE) Ga_xIn_1?xP layers (x≈0.5) grown on (001) GaAs substrates at temperatures ranging from 490 to 580°C have been investigated using transmission electron diffraction (TED), transmission electron microscopy, and photoluminescence (PL). TED examination revealed the presence of diffuse scattering 1/2{111}_B positions, indicating the occurrence of typical CuPt-type ordering in the GaInP CBE layers. As the growth temperature decreased from 580 to 490°C, maxima in the intensity of the diffuse scattering moved from ½{111}_B to ½{?1+δ,1?δ,0} positions, where δ is a positive value. As the growth temperature increased from 490 to 550°C, the maxima in the diffuse scattering intensity progressively approached positions of $\frac{1}{2}\{\bar 110\} $ , i.e., the value of δ decreased from 0.25 to 0.17. Bandgap reduction (～45 meV) was observed in the CBE GaInP layers and was attributed to the presence of ordered structures.     

A transfer cost-sensitive boosting approach for cross-project defect prediction

Software defect prediction has been regarded as one of the crucial tasks to improve software quality by effectively allocating valuable resources to fault-prone modules. It is necessary to have a sufficient set of historical data for building a predictor. Without a set of sufficient historical data within a company, cross-project defect prediction (CPDP) can be employed where data from other companies are used to build predictors. In such cases, a transfer learning technique, which extracts common knowledge from source projects and transfers it to a target project, can be used to enhance the prediction performance. There exists the class imbalance problem, which causes difficulties for the learner to predict defects. The main impacts of imbalanced data under cross-project settings have not been investigated in depth. We propose a transfer cost-sensitive boosting method that considers both knowledge transfer and class imbalance for CPDP when given a small amount of labeled target data. The proposed approach performs boosting that assigns weights to the training instances with consideration of both distributional characteristics and the class imbalance. Through comparative experiments with the transfer learning and the class imbalance learning techniques, we show that the proposed model provides significantly higher defect detection accuracy while retaining better overall performance. As a result, a combination of transfer learning and class imbalance learning is highly effective for improving the prediction performance under cross-project settings. The proposed approach will help to design an effective prediction model for CPDP. The improved defect prediction performance could help to direct software quality assurance activities and reduce costs. Consequently, the quality of software can be managed effectively.