Shared-aperture dual-band dual-polarization array using sandwiched stacked patch

An L/C dual-band dual-polarized (DBDP) shared aperture microstrip array is proposed in the paper. In the array, the sandwiched stacked patch is employed for the L-band element to exploit the bandwidth for given element thickness. Several key issues regarding the proposed structure are discussed, including: 1) benefit of proposed L band sandwiched stacked patch; 2) C-band feeding method; 3) radiation performance in both bands. A prototype array of L/C DBDP sandwiched stacked patch is designed and fabricated to verify the feasibility of the proposed structure, where the measured data are presented in the paper. © 2010 EMW Publishing. All Rights Reserved

Case study on user knowledge and design knowledge in product form design

2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Holographic Superconductors from Einstein-Maxwell-Dilaton Gravity

We construct holographic superconductors from Einstein-Maxwell-dilaton gravity in 3+1 dimensions with two adjustable couplings $\alpha$ and the charge $q$ carried by the scalar field. For the values of $\alpha$ and $q$ we consider, there is always a critical temperature at which a second order phase transition occurs between a hairy black hole and the AdS RN black hole in the canonical ensemble, which can be identified with the superconducting phase transition of the dual field theory. We calculate the electric conductivity of the dual superconductor and find that for the values of $\alpha$ and $q$ where $\alpha/q$ is small the dual superconductor has similar properties to the minimal model, while for the values of $\alpha$ and $q$ where $\alpha/q$ is large enough, the electric conductivity of the dual superconductor exhibits novel properties at low frequencies where it shows a "Drude Peak" in the real part of the conductivity.Comment: 25 pages, 13 figures; v2, typos corrected; v3, refs added, to appear in JHE

Insights into the subsurface transport of As(V) and Se(VI) in produced water from hydraulic fracturing using soil samples from Qingshankou Formation, Songliao Basin, China.

Produced water is a type of wastewater generated from hydraulic fracturing, which may pose a risk to the environment and humans due to its high ionic strength and the presence of elevated concentrations of metals/metalloids that exceed maximum contamination levels. The mobilization of As(V) and Se(VI) in produced water and selected soils from Qingshankou Formation in the Songliao Basin in China were investigated using column experiments and synthetic produced water whose quality was representative of waters arising at different times after well creation. Temporal effects of produced water on metal/metalloid transport and sorption/desorption were investigated by using HYDRUS-1D transport modelling. Rapid breakthrough and long tailings of As(V) and Se(VI) transport were observed in Day 1 and Day 14 solutions, but were reduced in Day 90 solution probably due to the elevated ionic strength. The influence of produced water on the hydrogeological conditions (i.e., change between equilibrium and non-equilibrium transport) was evidenced by the change of tracer breakthrough curves before and after the leaching of produced water. This possibly resulted from the sorption of polyacrylamide (PAM (-CH2CHCONH2-)n) onto soil surfaces, through its use as a friction reducer in fracturing solutions. The sorption was found to be reversible in this study. Minimal amounts of sorbed As(V) were desorbed whereas the majority of sorbed Se(VI) was readily leached out, to an extent which varied with the composition of the produced water. These results showed that the mobilization of As(V) and Se(VI) in soil largely depended on the solution pH and ionic strength. Understanding the differences in metal/metalloid transport in produced water is important for proper risk management

Changes in BMI before and during economic development and subsequent risk of cardiovascular disease and total mortality: A 35-year follow-up study in China

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Photocurrent measurements of supercollision cooling in graphene

The cooling of hot electrons in graphene is the critical process underlying the operation of exciting new graphene-based optoelectronic and plasmonic devices, but the nature of this cooling is controversial. We extract the hot electron cooling rate near the Fermi level by using graphene as novel photothermal thermometer that measures the electron temperature ($T(t)$) as it cools dynamically. We find the photocurrent generated from graphene $p-n$ junctions is well described by the energy dissipation rate $C dT/dt=-A(T^3-T_l^3)$, where the heat capacity is $C=\alpha T$ and $T_l$ is the base lattice temperature. These results are in disagreement with predictions of electron-phonon emission in a disorder-free graphene system, but in excellent quantitative agreement with recent predictions of a disorder-enhanced supercollision (SC) cooling mechanism. We find that the SC model provides a complete and unified picture of energy loss near the Fermi level over the wide range of electronic (15 to $\sim$3000 K) and lattice (10 to 295 K) temperatures investigated.Comment: 7pages, 5 figure

Machine learning application in personalised lung cancer recurrence and survivability prediction

Copyright © 2022 The Authors. Machine learning is an important artificial intelligence technique that is widely applied in cancer diagnosis and detection. More recently, with the rise of personalised and precision medicine, there is a growing trend towards machine learning applications for prognosis prediction. However, to date, building reliable prediction models of cancer outcomes in everyday clinical practice is still a hurdle. In this work, we integrate genomic, clinical and demographic data of lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) patients from The Cancer Genome Atlas (TCGA) and introduce copy number variation (CNV) and mutation information of 15 selected genes to generate predictive models for recurrence and survivability. We compare the accuracy and benefits of three well-established machine learning algorithms: decision tree methods, neural networks and support vector machines. Although the accuracy of predictive models using the decision tree method has no significant advantage, the tree models reveal the most important predictors among genomic information (e.g. KRAS, EGFR, TP53), clinical status (e.g. TNM stage and radiotherapy) and demographics (e.g. age and gender) and how they influence the prediction of recurrence and survivability for both early stage LUAD and LUSC. The machine learning models have the potential to help clinicians to make personalised decisions on aspects such as follow-up timeline and to assist with personalised planning of future social care needs.Funding from the UK Engineering & Physical Sciences Research Council (EPSRC) for the Future Targeted Healthcare Manufacturing Hub hosted at University College London with UK university partners is gratefully acknowledged (Grant Reference: EP/P006485/1). Financial and in-kind support from the consortium of industrial users and sector organisations is also acknowledged

Remineralization of demineralized dentin using a dual analog system.

ObjectiveImproved methods are needed to remineralize dentin caries in order to promote conservation of dentin tissue and minimize the surgical interventions that are currently required for clinical treatment. Here, we test the hypothesis that bulk substrates can be effectively mineralized via a dual analog system proposed by others, using a tripolyphosphate (TPP) "templating analog" and a poly(acrylic acid) (PAA) or poly(aspartic acid) (pAsp) "sequestration analog," the latter of which generates the polymer-induced liquid-precursor (PILP) mineralization process studied in our laboratory.Material & methodsDemineralized human dentin slices were remineralized with and without pre-treatment with TPP, using either PAA or pAsp as the PILP process-directing agent. A control experiment with no polymer present was used for comparison.ResultsNo mineralization was observed in any of the PAA groups. In both the pAsp and no polymer groups, TPP inhibited mineralization on the surfaces of the specimens but promoted mineralization within the interiors. Pre-treatment with TPP enhanced overall mineralization of the pAsp group. However, when analysed via TEM, regions with little mineral were still present.ConclusionPoly(acrylic acid) was unable to remineralize demineralized dentin slices under the conditions employed, even when pre-treated with TPP. However, pre-treatment with TPP enhanced overall mineralization of specimens that were PILP-remineralized using pAsp

Acute rejection is associated with antibodies to non-Gal antigens in baboons using Gal-knockout pig kidneys

We transplanted kidneys from α1,3-galactosyltransferase knockout (GalT-KO) pigs into six baboons using two different immunosuppressive regimens, but most of the baboons died from severe acute humoral xenograft rejection. Circulating induced antibodies to non-Gal antigens were markedly elevated at rejection, which mediated strong complement-dependent cytotoxicity against GalT-KO porcine target cells. These data suggest that antibodies to non-Gal antigens will present an additional barrier to transplantation of organs from GalT-KO pigs to humans. © 2005 Nature Publishing Group

Simple models of the chemical field around swimming plankton

Background. Cervical cancer is the fourth most common cancer in women, and we recently reported human leukocyte antigen (HLA) alleles showing strong associations with cervical neoplasia risk and protection. HLA ligands are recognized by killer immunoglobulin-like receptors (KIRs) expressed on a range of immune cell subsets, governing their proinflammatory activity. We hypothesized that the inheritance of particular HLA-KIR combinations would increase cervical neoplasia risk. Methods. Here, we used HLA and KIR dosages imputed from single-nucleotide polymorphism genotype data from 2143 cervical neoplasia cases and 13 858 healthy controls of European decent. Results. The following 4 novel HLA alleles were identified in association with cervical neoplasia, owing to their linkage disequilibrium with known cervical neoplasia-associated HLA-DRB1 alleles: HLA-DRB3*9901 (odds ratio [OR], 1.24; P = 2.49 × 10−9), HLA-DRB5*0101 (OR, 1.29; P = 2.26 × 10−8), HLA-DRB5*9901 (OR, 0.77; P = 1.90 × 10−9), and HLA-DRB3*0301 (OR, 0.63; P = 4.06 × 10−5). We also found that homozygosity of HLA-C1 group alleles is a protective factor for human papillomavirus type 16 (HPV16)-related cervical neoplasia (C1/C1; OR, 0.79; P = .005). This protective association was restricted to carriers of either KIR2DL2 (OR, 0.67; P = .00045) or KIR2DS2 (OR, 0.69; P = .0006). Conclusions. Our findings suggest that HLA-C1 group alleles play a role in protecting against HPV16-related cervical neoplasia, mainly through a KIR-mediated mechanism