Vertically aligned InGaN nanowires with engineered axial In composition for highly efficient visible light emission.

We report on the fabrication of novel InGaN nanowires (NWs) with improved crystalline quality and high radiative efficiency for applications as nanoscale visible light emitters. Pristine InGaN NWs grown under a uniform In/Ga molar flow ratio (UIF) exhibited multi-peak white-like emission and a high density of dislocation-like defects. A phase separation and broad emission with non-uniform luminescent clusters were also observed for a single UIF NW investigated by spatially resolved cathodoluminescence. Hence, we proposed a simple approach based on engineering the axial In content by increasing the In/Ga molar flow ratio at the end of NW growth. This new approach yielded samples with a high luminescence intensity, a narrow emission spectrum, and enhanced crystalline quality. Using time-resolved photoluminescence spectroscopy, the UIF NWs exhibited a long radiative recombination time (τr) and low internal quantum efficiency (IQE) due to strong exciton localization and carrier trapping in defect states. In contrast, NWs with engineered In content demonstrated three times higher IQE and a much shorter τr due to mitigated In fluctuation and improved crystal quality

Neither thermosonication nor cold sonication is better than pasteurization for milk shelf life

High-power, low-frequency ultrasound has been suggested as a novel processing technique with the potential to extend milk shelf life via inactivation of bacteria and spores that survive standard pasteurization. The primary objective of this research was to determine whether short-duration (≤60 s) sonication treatment, in conjunction with pasteurization, can increase shelf life while producing no adverse aroma effect. Skim milk was inoculated with Paenibacillus amylolyticus, a spore-forming, thermotolerant and psychrophilic milk contamination bacterium. Milk was sonicated under 6 selected amplitude and time conditions, except for control. Both cold sonicated (C-S) and thermosonicated (T-S) milk and milk treatments were pasteurized; however, T-S milk was sonicated after pasteurization (72.5 ± 0.3°C; mean ± SD), whereas C-S milk was sonicated at 12.5 ± 5°C (mean ± SD) before pasteurization. Milk was refrigerated up to 50 d and total aerobic counts were enumerated on pasteurized control, C-S, and T-S milk weekly. Neither C-S nor T-S treatments reduced total aerobic counts to an equivalent level as pasteurization alone. Counts in pasteurized controls and C-S milk did not exceed 3.00 log cfu/mL for up to 50 d; counts in T-S milk exceeded 5.00 cfu/mL by d 36. Aroma qualities (cooked, lacks freshness, and rubbery) of 2 T-S treatment intensities [170 µm peak-to-peak (p-p) for 60s and 200 µmp-p for 10 s] and pasteurized controls were evaluated by a trained descriptive sensory panel. No significant differences were observed in cooked or lacks freshness aromas among samples. Only the milk treated with 170 µmp-p for 60 s had significantly higher rubbery aroma on d 1 compared with milk treated with 200 µmp-p for 10 s. Although the sensory effects of T-S on milk may not limit the commercial feasibility of cold sonication or thermosonication, conditions that differ from those used in the present study should be considered in the future. Neither C-S nor T-S were appropriate techniques for reducing bacterial count in fluid milk beyond standard pasteurization and, in fact, increased counts of spore-forming spoilage bacteria

Observation of First-Order Metal-Insulator Transition without Structural Phase Transition in VO_2

An abrupt first-order metal-insulator transition (MIT) without structural phase transition is first observed by current-voltage measurements and micro-Raman scattering experiments, when a DC electric field is applied to a Mott insulator VO_2 based two-terminal device. An abrupt current jump is measured at a critical electric field. The Raman-shift frequency and the bandwidth of the most predominant Raman-active A_g mode, excited by the electric field, do not change through the abrupt MIT, while, they, excited by temperature, pronouncedly soften and damp (structural MIT), respectively. This structural MIT is found to occur secondarily.Comment: 4 pages, 4 figure

MLN51 and GM-CSF involvement in the proliferation of fibroblast-like synoviocytes in the pathogenesis of rheumatoid arthritis

Rheumatoid arthritis (RA) is an inflammatory autoimmune disease of unclear etiology. This study was conducted to identify critical factors involved in the synovial hyperplasia in RA pathology. We applied cDNA microarray analysis to profile the gene expressions of RA fibroblast-like synoviocytes (FLSs) from patients with RA. We found that the MLN51 (metastatic lymph node 51) gene, identified in breast cancer, is remarkably upregulated in the hyperactive RA FLSs. However, growth-retarded RA FLSs passaged in vitro expressed small quantities of MLN51. MLN51 expression was significantly enhanced in the FLSs when the growth-retarded FLSs were treated with granulocyte – macrophage colony-stimulating factor (GM-CSF) or synovial fluid (SF). Anti-GM-CSF neutralizing antibody blocked the MLN51 expression even though the FLSs were cultured in the presence of SF. In contrast, GM-CSF in SFs existed at a significant level in the patients with RA (n = 6), in comparison with the other inflammatory cytokines, IL-1β and TNF-α. Most RA FLSs at passage 10 or more recovered from their growth retardation when cultured in the presence of SF. The SF-mediated growth recovery was markedly impaired by anti-GM-CSF antibody. Growth-retarded RA FLSs recovered their proliferative capacity after treatment with GM-CSF in a dose-dependent manner. However, MLN51 knock-down by siRNA completely blocked the GM-CSF/SF-mediated proliferation of RA FLSs. Taken together, our results imply that MLN51, induced by GM-CSF, is important in the proliferation of RA FLSs in the pathogenesis of RA

Influence of Friction Stir Welding on Mechanical Properties of Butt Joints of AZ61 Magnesium Alloy

In this study, the effect of heat input on the mechanical properties and fracture behaviors of AZ61 magnesium alloy joints has been studied. Magnesium alloy AZ61 plates with thickness of 5 mm were welded at different ratios of tool rotational speed to welding speed (ω/ν). The average ultimate tensile strength of all weld conditions satisfying a ω/ν ratio of 3 reached 100% of the strength of the base material. Fractures occurred at the interface between the thermomechanical affected zone at advancing side and the stir zone in all welded specimens. From the scanning electron microscope and electron backscatter diffraction analysis, it was determined that the interface between the thermomechanical affected zone and the stir zone, which is the region where the grain orientation changes, was the weakest part; the advancing side region was relatively weaker than the retreating side region because the grain orientation change occurred more dramatically in the advancing side region

Monitoring Coastal Chlorophyll-a Concentrations in Coastal Areas Using Machine Learning Models

Harmful algal blooms have negatively affected the aquaculture industry and aquatic ecosystems globally. Remote sensing using satellite sensor systems has been applied on large spatial scales with high temporal resolutions for effective monitoring of harmful algal blooms in coastal waters. However, oceanic color satellites have limitations, such as low spatial resolution of sensor systems and the optical complexity of coastal waters. In this study, bands 1 to 4, obtained from Landsat-8 Operational Land Imager satellite images, were used to evaluate the performance of empirical ocean chlorophyll algorithms using machine learning techniques. Artificial neural network and support vector machine techniques were used to develop an optimal chlorophyll-a model. Four-band, four-band-ratio, and mixed reflectance datasets were tested to select the appropriate input dataset for estimating chlorophyll-a concentration using the two machine learning models. While the ocean chlorophyll algorithm application on Landsat-8 Operational Land Imager showed relatively low performance, the machine learning methods showed improved performance during both the training and validation steps. The artificial neural network and support vector machine demonstrated a similar level of prediction accuracy. Overall, the support vector machine showed slightly superior performance to that of the artificial neural network during the validation step. This study provides practical information about effective monitoring systems for coastal algal blooms