Integrated AlGaN quadruple-band ultraviolet photodetectors

Cataloged from PDF version of article.Monolithically integrated quadruple back-illuminated ultraviolet metalsemiconductormetal photodetectors with four different spectral responsivity bands were demonstrated on each of two different Al xGa 1-xN heterostructures. The average of the full-width at half-maximum (FWHM) of the quantum efficiency peaks was 18.15nm for sample A, which incorporated five 1000nm thick epitaxial layers. In comparison, the average FWHM for sample B was 9.98 nm, which incorporated nine 500nm thick epitaxial layers. © 2012 IOP Publishing Ltd

The chemotherapeutic agent DMXAA as a unique IRF3-dependent type-2 vaccine adjuvant

5,6-Dimethylxanthenone-4-acetic acid (DMXAA), a potent type I interferon (IFN) inducer, was evaluated as a chemotherapeutic agent in mouse cancer models and proved to be well tolerated in human cancer clinical trials. Despite its multiple biological functions, DMXAA has not been fully characterized for the potential application as a vaccine adjuvant. In this report, we show that DMXAA does act as an adjuvant due to its unique property as a soluble innate immune activator. Using OVA as a model antigen, DMXAA was demonstrated to improve on the antigen specific immune responses and induce a preferential Th2 (Type-2) response. The adjuvant effect was directly dependent on the IRF3-mediated production of type-I-interferon, but not IL-33. DMXAA could also enhance the immunogenicity of influenza split vaccine which led to significant increase in protective responses against live influenza virus challenge in mice compared to split vaccine alone. We propose that DMXAA can be used as an adjuvant that targets a specific innate immune signaling pathway via IRF3 for potential applications including vaccines against influenza which requires a high safety profile

A comparative study on the abundance and elemental composition of POM in three interconnected basins: the Black, the Marmara and the Mediterranean Seas

The abundance and elemental composition of suspended particulate organic matter in the upper layers of the interconnected Mediterranean, Marmara and Black Seas having different ecosystems were determined in 1990-1998. The aim was principally to compare the C:N:P ratio of seston and understand factors controlling the seston composition in near- and off-shore waters of these seas. In the Marmara Sea, euphotic zone average particulate concentrations varied regionally and seasonally between 10-35 ìM for POC, 0.4-4.5 ìM for PON and 0.05-0.45 ìM for PP. These concentrations are mostly above the off-shore Black Sea values but much greater than those measured in the open waters of the north-eastern Mediterranean whose near-shore data are comparable with the seston content of the deep Black Sea. Comparison of C:N:P ratios of seston reveals that atmospheric and land-based phosphorus input influences the C:P and N:P ratios in the near-shore waters. Apparent nutrient deficiencies observed in the water column were not as remarkable in the elemental composition of seston. Unexpectedly, in the NE Mediterranean, N:P ratios from regression analyses of particulate data are very low (7-9) in the coastal region but slightly increase to levels of 10-15 in the open sea. In the Sea of Marmara, the N:P ratios (7-12) of seston are as low as in the Mediterranean, being consistent with the particulate ratios of the Black Sea inflow and NO3:PO4 ratios of the Marmara sub-halocline water. The Black Sea seston is relatively rich in carbonaceous compounds with N:P ratio ranging merely between 15-17 in the open sea but 9-27 in coastal waters where riverine discharges markedly influence the stoichiometry of seston

Powder sheets additive manufacturing: Principles and capabilities for multi-material printing

In this work, a novel Metal Additive Manufacturing using Powder sheets (MAPS) method for printing multimaterial composites in one process is proposed. MAPS employs powder sheets (i.e. metal powder-polymer matrix flexible films) as the feedstock material. Its key advantages include a relatively rapid change from one material to another and a minimum wastage of materials due to the elimination of the powder bed. The powder sheets were fabricated using a 'solvent casting' method. They were then employed in a commercialised metal printer for printing metal multi-material composites. To prove the disruptive concept of MAPS, a 60-layer trimetallic multi-material composite (304 L stainless steel, In718 and CoCrFeMnNi high entropy alloy) was additively manufactured using three different types of powder sheet material in the same manufacturing system for the first time. Experimental results indicate a high density (99.80 %) multi-material composites was printed by MAPS. EDX and SEM observations of the multi-material composites revealed variations of chemical composition and microstructure along the build direction. The newly proposed MAPS manufacturing method and results of this study provide insights into a new avenue for multi-material metallic parts

Discovery of Delta Scuti variables in eclipsing binary systems II.Southern TESS field search

The presence of pulsating stars in eclipsing binary systems (EBs) makes these objects significant since they allow us to investigate the stellar interior structure and evolution. Different types of pulsating stars could be found in EBs such as Delta Scuti variables. Delta Scuti stars in EBs have been known for decades and the increasing number of such systems is important for understanding pulsational structure. Hence, in this study, a research was carried out on the southern TESS field to discover new Delta Scuti stars in EBs. We produced an algorithm to search for detached and semi-detached EBs considering three steps; the orbital period (P$_{orb}$)'s harmonics in the Fourier spectrum, skewness of the light curves, and classification of \textsc{UPSILON} program. If two of these steps classify a system as an EB, the algorithm also identifies it as an EB. The TESS pixel files of targets were also analyzed to see whether the fluxes are contaminated by other systems. No contamination was found. We researched the existence of pulsation through EBs with a visual inspection. To confirm Delta Scuti-type oscillations, the binary variation was removed from the light curve, and residuals were analyzed. Consequently, we identified 42 Delta Scuti candidates in EBs. The P$_{orb}$, $L$, and M$_{V}$ of systems were calculated. Their positions on the H-R diagram and the known orbital-pulsation period relationship were analyzed. We also examined our targets to find if any of them show frequency modulation with the orbital period and discovered one candidate of tidally tilted pulsators.Comment: Published in MNRA

A non-invasive imaging approach for improved assessments on the construction and the condition of historical knotted-pile carpets

The appraisal of the design and the weaving structure of Islamic knotted-pile carpets can tell plenty about the context in which they were produced, and the identification of signs of deterioration can help to establish their condition. These are often somewhat imprecise and laborious examinations, especially when considering carpets of large dimensions. Analytical methods that support these disciplines urge further exploration so that improved interpretations can be obtained.  An interdisciplinary combination of art history, analytical science and textile conservation aimed, on the one hand, to improve the weaving examination of these complex textile objects – by considering the spin of threads and the ply of yarns; the knot count and density; and the weaving structure of warps, wefts and piles – and on the other, to help their condition assessment – by mapping of damaged areas, old repairs and contaminations. For this purpose, the possibilities and limitations of several non-invasive imaging techniques, namely transmitted, raking or incident visible, ultraviolet (UV) and infrared (IR) illumination through Visual Spectral Comparator (VSC), as well as conventional X-radiography, mammography and (micro) CT scanning, were assessed to support the conventional visual examination of the weaving details and present condition of two 17th-century Safavid knotted-pile carpet fragments.  Observation with NUV and NIR imaging with VSC, as well as CT techniques, offered enriching overviews about weaving characteristics, damaged areas or contaminations that were not easily discernible with the naked eye, thus supporting the conventional visual examination. As a result, detailed digital mappings about the technological structure and the condition of the fragments could be obtained in a relatively efficient and accessible way. Moreover, combining art historical identification of the design with the analysis of the weaving structure confirmed that both carpet fragments are border corners that originally belonged to much larger carpets made in the so-called “Indo-Persian” style. The outcome of this interdisciplinary research brings very useful contributions for future art historical and conservation assessments of historical carpets, and it encourages further exploration of imaging techniques in the examination of other textile objects in museums and private collections

Myocardial biomechanics and the consequent differentially expressed genes of the left atrial ligation chick embryonic model of hypoplastic left heart syndrome

Left atrial ligation (LAL) of the chick embryonic heart is a model of the hypoplastic left heart syndrome (HLHS) where a purely mechanical intervention without genetic or pharmacological manipulation is employed to initiate cardiac malformation. It is thus a key model for understanding the biomechanical origins of HLHS. However, its myocardial mechanics and subsequent gene expressions are not well-understood. We performed finite element (FE) modeling and single-cell RNA sequencing to address this. 4D high-frequency ultrasound imaging of chick embryonic hearts at HH25 (ED 4.5) were obtained for both LAL and control. Motion tracking was performed to quantify strains. Image-based FE modeling was conducted, using the direction of the smallest strain eigenvector as the orientations of contractions, the Guccione active tension model and a Fung-type transversely isotropic passive stiffness model that was determined via micro-pipette aspiration. Single-cell RNA sequencing of left ventricle (LV) heart tissues was performed for normal and LAL embryos at HH30 (ED 6.5) and differentially expressed genes (DEG) were identified.After LAL, LV thickness increased by 33%, strains in the myofiber direction increased by 42%, while stresses in the myofiber direction decreased by 50%. These were likely related to the reduction in ventricular preload and underloading of the LV due to LAL. RNA-seq data revealed potentially related DEG in myocytes, including mechano-sensing genes (Cadherins, NOTCH1, etc.), myosin contractility genes (MLCK, MLCP, etc.), calcium signaling genes (PI3K, PMCA, etc.), and genes related to fibrosis and fibroelastosis (TGF-β, BMP, etc.). We elucidated the changes to the myocardial biomechanics brought by LAL and the corresponding changes to myocyte gene expressions. These data may be useful in identifying the mechanobiological pathways of HLHS

Ai-Drugnet: a Network-Based Deep Learning Model For Drug Repurposing and Combination therapy in Neurological Disorders

Discovering effective therapies is difficult for neurological and developmental disorders in that disease progression is often associated with a complex and interactive mechanism. Over the past few decades, few drugs have been identified for treating Alzheimer\u27s disease (AD), especially for impacting the causes of cell death in AD. Although drug repurposing is gaining more success in developing therapeutic efficacy for complex diseases such as common cancer, the complications behind AD require further study. Here, we developed a novel prediction framework based on deep learning to identify potential repurposed drug therapies for AD, and more importantly, our framework is broadly applicable and may generalize to identifying potential drug combinations in other diseases. Our prediction framework is as follows: we first built a drug-target pair (DTP) network based on multiple drug features and target features, as well as the associations between DTP nodes where drug-target pairs are the DTP nodes and the associations between DTP nodes are represented as the edges in the AD disease network; furthermore, we incorporated the drug-target feature from the DTP network and the relationship information between drug-drug, target-target, drug-target within and outside of drug-target pairs, representing each drug-combination as a quartet to generate corresponding integrated features; finally, we developed an AI-based Drug discovery Network (AI-DrugNet), which exhibits robust predictive performance. The implementation of our network model help identify potential repurposed and combination drug options that may serve to treat AD and other diseases