Formation of high-quality Ag-based ohmic contacts to p-type GaN

Low resistance and high reflectance ohmic contacts on p-type GaN were achieved using an Ag-based metallization scheme. Oxidation annealing was the key to achieve ohmic behavior of Ag-based contacts on p-type GaN. A low contact resistivity of similar to 5x10(-5) Omega cm(2) could be achieved from Me (=Ni, Ir, Pt, or Ru)/Ag (50/1200 angstrom) contacts after annealing at 500 degrees C for 1 min in O(2) ambient. Oxidation annealing promoted the out-diffusion of Ga atoms from the GaN layer, and Ga atoms dissolved in the in-diffused Ag layer with the formation of Ag-Ga solid solution, resulting in ohmic contact formation. Using Ru/Ni/Au (500/200/500 angstrom) overlayers on the Me/Ag contacts, the excessive incorporation of oxygen molecules into the contact interfacial region, and the out-diffusion and agglomeration of Ag, were effectively prevented during oxidation annealing. As a result, a high reflectance of 87.2% at the 460 nm wavelength and a smooth surface morphology could be obtained simultaneously. (C) 2008 The Electrochemical Society.open111618sciescopu

Efficient and Privacy Preserving Group Signature for Federated Learning

Federated Learning (FL) is a Machine Learning (ML) technique that aims to reduce the threats to user data privacy. Training is done using the raw data on the users' device, called clients, and only the training results, called gradients, are sent to the server to be aggregated and generate an updated model. However, we cannot assume that the server can be trusted with private information, such as metadata related to the owner or source of the data. So, hiding the client information from the server helps reduce privacy-related attacks. Therefore, the privacy of the client's identity, along with the privacy of the client's data, is necessary to make such attacks more difficult. This paper proposes an efficient and privacy-preserving protocol for FL based on group signature. A new group signature for federated learning, called GSFL, is designed to not only protect the privacy of the client's data and identity but also significantly reduce the computation and communication costs considering the iterative process of federated learning. We show that GSFL outperforms existing approaches in terms of computation, communication, and signaling costs. Also, we show that the proposed protocol can handle various security attacks in the federated learning environment

A Feasibility Study on the Application of TVDI on Accessing Wildfire Danger in the Korean Peninsula

Wildfire is a major natural disaster affecting socioeconomics and ecology. Remote sensing data have been widely used to estimate the wildfire danger with an advantage of higher spatial resolution. Among the several wildfire related indices using remote sensing data, Temperature Vegetation Dryness Index (TVDI) assesses wildfire danger based on both Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). Although TVDI has physical advantages by considering both weather and vegetation condition, previous studies have shown TVDI does not performed well compare to other wildfire related indices over the Korean Peninsula. In this study we have attempted multiple modification to improve TVDI performance over the study region. In-situ measured air temperature was employed to increase accuracy, regression line was generated using monthly data to include seasonal effect, and TVDI was calculated at each province level to consider vegetation type and local climate. The modified TVDI calculation method was evaluated in wildfire cases and showed significant improvement in wildfire danger estimation

PPM1A Controls Diabetic Gene Programming through Directly Dephosphorylating PPAR?? at Ser273

Peroxisome proliferator-activated receptor gamma (PPAR gamma) is a master regulator of adipose tissue biology. In obesity, phosphorylation of PPAR gamma at Ser273 (pSer273) by cyclin-dependent kinase 5 (CDK5)/extracellular signal-regulated kinase (ERK) orchestrates diabetic gene reprogramming via dysregulation of specific gene expression. Although many recent studies have focused on the development of non-classical agonist drugs that inhibit the phosphorylation of PPAR gamma at Ser273, the molecular mechanism of PPAR gamma dephosphorylation at Ser273 is not well characterized. Here, we report that protein phosphatase Mg2+/Mn2+-dependent 1A (PPM1A) is a novel PPAR gamma phosphatase that directly dephosphorylates Ser273 and restores diabetic gene expression which is dysregulated by pSer273. The expression of PPM1A significantly decreases in two models of insulin resistance: diet-induced obese (DIO) mice and db/db mice, in which it negatively correlates with pSer273. Transcriptomic analysis using microarray and genotype-tissue expression (GTEx) data in humans shows positive correlations between PPM1A and most of the genes that are dysregulated by pSer273. These findings suggest that PPM1A dephosphorylates PPAR gamma at Ser273 and represents a potential target for the treatment of obesity-linked metabolic disorders

Electrospun materials as potential platforms for bone tissue engineering

Nanofibrous materials produced by electrospinning processes have attracted considerable interest in tissue regeneration, including bone reconstruction. A range of novel materials and processing tools have been developed to mimic the native bone extracellular matrix for potential applications as tissue engineering scaffolds and ultimately to restore degenerated functions of the bone. Degradable polymers, bioactive inorganics and their nanocomposites/hybrids nanofibers with suitable mechanical properties and bone bioactivity for osteoblasts and progenitor/stem cells have been produced. The surface functionalization with apatite minerals and proteins/peptides as well as drug encapsulation within the nanofibers is a promising strategy for achieving therapeutic functions with nanofibrous materials. Recent attempts to endow a 3D scaffolding technique to the electrospinning regime have shown some promise for engineering 3D tissue constructs. With the improvement in knowledge and techniques of bone-targeted nanofibrous matrices, bone tissue engineering is expected to be realized in the near future

Switching Magnetism and Superconductivity with Spin-Polarized Current in Iron-Based Superconductor

We have explored a new mechanism for switching magnetism and superconductivity in a magnetically frustrated iron-based superconductor using spin-polarized scanning tunneling microscopy (SPSTM). Our SPSTM study on single crystal Sr$_2$VO$_3$FeAs shows that a spin-polarized tunneling current can switch the Fe-layer magnetism into a non-trivial $C_4$ (2$\times$2) order, not achievable by thermal excitation with unpolarized current. Our tunneling spectroscopy study shows that the induced $C_4$ (2$\times$2) order has characteristics of plaquette antiferromagnetic order in Fe layer and strongly suppressed superconductivity. Also, thermal agitation beyond the bulk Fe spin ordering temperature erases the $C_4$ state. These results suggest a new possibility of switching local superconductivity by changing the symmetry of magnetic order with spin-polarized and unpolarized tunneling currents in iron-based superconductors.Comment: 33 pages, 16 figure