Anti-Inflammatory Effect of Fermented Cabbage Extract Containing Nitric Oxide Metabolites with Silica.

The aim of this study was to evaluate the anti-inflammatory effect of fermented cabbage extract (FC) containing nitric oxide metabolites with silica (FCS) on 1-fluoro-2,4-dinitrofluorobenzene (DNFB)-induced atopic dermatitis (AD) in BALB/c mice. Atopic dermatitis-like allergic contact dermatitis was induced by DNFB challenge in the ear after DNFB sensitization on the dorsal skin of mice. FCS alleviated the severity of atopic dermatitis-like skin lesions. In addition, epidermis thickness of the ear and penetration of inflammatory cells in atopic dermatitis-like skin lesions were decreased after topical application of FCS. The serum levels of TNF-α and IL-4 were measured in atopic dermatitis mice using ELISA kits, which were observed to be significantly decreased after topical application of FCS. This study demonstrates that the FCS can be used as a potential therapeutic for the treatment and prevention of AD.

Antidiabetic Effect of Noodles Containing Fermented Lettuce Extracts.

The aim of the current study was to examine the antidiabetic effect of noodle containing fermented lettuce extract (FLE) on diabetic mice as a pre-clinical study. The γ-aminobutyric acid (GABA) content, antioxidant capacity, and total polyphenol content of the FLE noodles were analyzed and compared with those of standard noodles. In addition, oral glucose and sucrose tolerance, and fasting blood glucose tests were performed using a high-fat diet/streptozotocin-mediated diabetic mouse model. Serum metabolite profiling of mice feed standard or FLE noodles was performed using gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS) to understand the mechanism changes induced by the FLE noodles. The GABA content, total polyphenols, and antioxidant activity were high in FLE noodles compared with those in the standard noodles. In vivo experiments also showed that mice fed FLE noodles had lower blood glucose levels and insulin resistance than those fed standard noodles. Moreover, glycolysis, purine metabolism, and amino acid metabolism were altered by FLE as determined by GC-TOF-MS-based metabolomics. These results demonstrate that FLE noodles possess significant antidiabetic activity, suggesting the applicability of fermented lettuce extract as a potential food additive for diabetic food products.

Mesostructured HfxAlyO2 Thin Films as Reliable and Robust Gate Dielectrics with Tunable Dielectric Constants for High-Performance Graphene-Based Transistors.

We introduce a reliable and robust gate dielectric material with tunable dielectric constants based on a mesostructured HfxAlyO2 film. The ultrathin mesostructured HfxAlyO2 film is deposited on graphene via a physisorbed-precursor-assisted atomic layer deposition process and consists of an intermediate state with small crystallized parts in an amorphous matrix. Crystal phase engineering using Al dopant is employed to achieve HfO2 phase transitions, which produce the crystallized part of the mesostructured HfxAlyO2 film. The effects of various Al doping concentrations are examined, and an enhanced dielectric constant of ∼25 is obtained. Further, the leakage current is suppressed (∼10(-8) A/cm(2)) and the dielectric breakdown properties are enhanced (breakdown field: ∼7 MV/cm) by the partially remaining amorphous matrix. We believe that this contribution is theoretically and practically relevant because excellent gate dielectric performance is obtained. In addition, an array of top-gated metal-insulator-graphene field-effect transistors is fabricated on a 6 in. wafer, yielding a capacitance equivalent oxide thickness of less than 1 nm (0.78 nm). This low capacitance equivalent oxide thickness has important implications for the incorporation of graphene into high-performance silicon-based nanoelectronics.

Thickness scaling of atomic-layer-deposited HfO2 films and their application to wafer-scale graphene tunnelling transistors.

The downscaling of the capacitance equivalent oxide thickness (CET) of a gate dielectric film with a high dielectric constant, such as atomic layer deposited (ALD) HfO2, is a fundamental challenge in achieving high-performance graphene-based transistors with a low gate leakage current. Here, we assess the application of various surface modification methods on monolayer graphene sheets grown by chemical vapour deposition to obtain a uniform and pinhole-free ALD HfO2 film with a substantially small CET at a wafer scale. The effects of various surface modifications, such as N-methyl-2-pyrrolidone treatment and introduction of sputtered ZnO and e-beam-evaporated Hf seed layers on monolayer graphene, and the subsequent HfO2 film formation under identical ALD process parameters were systematically evaluated. The nucleation layer provided by the Hf seed layer (which transforms to the HfO2 layer during ALD) resulted in the uniform and conformal deposition of the HfO2 film without damaging the graphene, which is suitable for downscaling the CET. After verifying the feasibility of scaling down the HfO2 thickness to achieve a CET of ~1.5 nm from an array of top-gated metal-oxide-graphene field-effect transistors, we fabricated graphene heterojunction tunnelling transistors with a record-low subthreshold swing value of <60 mV/dec on an 8" glass wafer.

REEF: Retainable Evaluator Execution Framework.

Resource Managers like Apache YARN have emerged as a critical layer in the cloud computing system stack, but the developer abstractions for leasing cluster resources and instantiating application logic are very low-level. This flexibility comes at a high cost in terms of developer effort, as each application must repeatedly tackle the same challenges (e.g., fault-tolerance, task scheduling and coordination) and re-implement common mechanisms (e.g., caching, bulk-data transfers). This paper presents REEF, a development framework that provides a control-plane for scheduling and coordinating task-level (data-plane) work on cluster resources obtained from a Resource Manager. REEF provides mechanisms that facilitate resource re-use for data caching, and state management abstractions that greatly ease the development of elastic data processing work-flows on cloud platforms that support a Resource Manager service. REEF is being used to develop several commercial offerings such as the Azure Stream Analytics service. Furthermore, we demonstrate REEF development of a distributed shell application, a machine learning algorithm, and a port of the CORFU [4] system. REEF is also currently an Apache Incubator project that has attracted contributors from several instititutions.