Electrolysis-based diaphragm actuators

This work presents a new electrolysis-based microelectromechanical systems (MEMS) diaphragm actuator. Electrolysis is a technique for converting electrical energy to pneumatic energy. Theoretically electrolysis can achieve a strain of 136 000% and is capable of generating a pressure above 200 MPa. Electrolysis actuators require modest electrical power and produce minimal heat. Due to the large volume expansion obtained via electrolysis, small actuators can create a large force. Up to 100 µm of movement was achieved by a 3 mm diaphragm. The actuator operates at room temperature and has a latching and reversing capability

Crystallization of Arabidopsis thaliana acetohydroxyacid synthase in complex with the sulfonylurea herbicide chlorimuron ethyl

Acetohydroxyacid synthase (AHAS; EC 2.2.1.6) catalyses the formation of 2-acetolactate and 2-aceto-2-hydroxybutyrate as the first step in the biosynthesis of the branched-chain amino acids valine, leucine and isoleucine. The enzyme is inhibited by a wide range of substituted sulfonylureas and imidazolinones and many of these compounds are used as commercial herbicides. Here, the crystallization and preliminary X-ray diffraction analysis of the catalytic subunit of Arabidopsis thaliana AHAS in complex with the sulfonylurea herbicide chlorimuron ethyl are reported. This is the first report of the structure of any plant protein in complex with a commercial herbicide. Crystals diffract to 3.0 Angstrom resolution, have unit-cell parameters a = b = 179.92, c = 185.82 Angstrom and belong to space group P6(4)22. Preliminary analysis indicates that there is one monomer in the asymmetric unit and that these are arranged as pairs of dimers in the crystal. The dimers form a very open hexagonal lattice, with a high solvent content of 81%

Phonon Density of States and Anharmonicity of UO2

Phonon density of states (PDOS) measurements have been performed on polycrystalline UO2 at 295 and 1200 K using time-of-flight inelastic neutron scattering to investigate the impact of anharmonicity on the vibrational spectra and to benchmark ab initio PDOS simulations performed on this strongly correlated Mott-insulator. Time-of-flight PDOS measurements include anharmonic linewidth broadening inherently and the factor of ~ 7 enhancement of the oxygen spectrum relative to the uranium component by the neutron weighting increases sensitivity to the oxygen-dominated optical phonon modes. The first-principles simulations of quasi-harmonic PDOS spectra were neutron-weighted and anharmonicity was introduced in an approximate way by convolution with wavevector-weighted averages over our previously measured phonon linewidths for UO2 that are provided in numerical form. Comparisons between the PDOS measurements and the simulations show reasonable agreement overall, but they also reveal important areas of disagreement for both high and low temperatures. The discrepancies stem largely from an ~ 10 meV compression in the overall bandwidth (energy range) of the oxygen-dominated optical phonons in the simulations. A similar linewidth-convoluted comparison performed with the PDOS spectrum of Dolling et al. obtained by shell-model fitting to their historical phonon dispersion measurements shows excellent agreement with the time-of-flight PDOS measurements reported here. In contrast, we show by comparisons of spectra in linewidth-convoluted form that recent first-principles simulations for UO2 fail to account for the PDOS spectrum determined from the measurements of Dolling et al. These results demonstrate PDOS measurements to be stringent tests for ab initio simulations of phonon physics in UO2 and they indicate further the need for advances in theory to address lattice dynamics of UO2.Comment: Text slightly modified, results unchange

Probe substrate and enzyme source-dependent inhibition of UDP-glucuronosyltransferase (UGT) 1A9 by wogonin

Background: Drug-metabolizing enzymes (DMEs) inhibition based drug-drug interaction and herb-drug interaction severely challenge the R&D process of drugs or herbal ingredients.Objective: To evaluate the inhibition potential of wogonin (an important flavonoid isolated from the root of Scutellaria baicalensis) towards one of the most important phase II DMEs, UDP-glucuronosyltransferase (UGT) 1A9.Methods: Both recombinant UGT1A9-catalyzed 4-methylumbelliferone (4-MU) glucuronidation reaction and human liver microsomes (HLMs)-catalyzed propofol glucuronidation reaction were used as two different probe reactions.Results: Wogonin noncompetitively inhibited recombinant UGT1A9-catalyzed 4-MU glucuronidation, and exerted competitive inhibition towards HLMs-catalyzed propofol glucuronidation. The inhibition kinetic parameters (Ki) were calculated to be 3.2 ìM and 52.0ìM, respectively.Conclusion: Necessary monitoring was needed when wogonin was co-administered with the clinical drugs mainly undergoing UGT1A9-mediated glucuronidation elimination. Additionally, probe reactions-dependent inhibition of wogonin towards the activity of UGT1A9 should be paid attention when translating these in vitro data into in vivo situation.Keywords: wogonin, drug-drug interaction (DDI),  UDP-glucuronosyltransferases (UGTs

Analytic Lifshitz black holes in higher dimensions

We generalize the four-dimensional R^2-corrected z=3/2 Lifshitz black hole to a two-parameter family of black hole solutions for any dynamical exponent z and for any dimension D. For a particular relation between the parameters, we find the first example of an extremal Lifshitz black hole. An asymptotically Lifshitz black hole with a logarithmic decay is also exhibited for a specific critical exponent depending on the dimension. We extend this analysis to the more general quadratic curvature corrections for which we present three new families of higher-dimensional D>=5 analytic Lifshitz black holes for generic z. One of these higher-dimensional families contains as critical limits the z=3 three-dimensional Lifshitz black hole and a new z=6 four-dimensional black hole. The variety of analytic solutions presented here encourages to explore these gravity models within the context of non-relativistic holographic correspondence.Comment: 14 page

Ultraviolet emission of silicon quantum tips

Silicon tips used as field emitters have dimensions that are within the quantum confinement regime. Therefore they can be considered as freestanding silicon tips. In this letter, a photoluminescence spectrum of a 100×100100×100 array of silicon tips was taken at 10 K. Narrow ultraviolet luminescence peaks were observed. Using the empirical pseudopotential homojunction model, it is demonstrated that these luminescence peaks come from energy levels arising from quantum confinement. By fitting the theoretical result to the experimental result, we conclude that the luminescence peaks come from Si quantum tips of about 20 Å in width and that they are covered by silicon dioxide. © 1999 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71101/2/APPLAB-74-3-386-1.pd

Fusion of colour contrasted images for early detection of oesophageal squamous cell dysplasia from endoscopic videos in real time

Standard white light (WL) endoscopy often misses precancerous oesophageal changes due to their only subtle differences to the surrounding normal mucosa. While deep learning (DL) based decision support systems benefit to a large extent, they face two challenges, which are limited annotated data sets and insufficient generalisation. This paper aims to fuse a DL system with human perception by exploiting computational enhancement of colour contrast. Instead of employing conventional data augmentation techniques by alternating RGB values of an image, this study employs a human colour appearance model, CIECAM, to enhance the colours of an image. When testing on a frame of endoscopic videos, the developed system firstly generates its contrast-enhanced image, then processes both original and enhanced images one after another to create initial segmentation masks. Finally, fusion takes place on the assembled list of masks obtained from both images to determine the finishing bounding boxes, segments and class labels that are rendered on the original video frame, through the application of non-maxima suppression technique (NMS). This deep learning system is built upon real-time instance segmentation network Yolact. In comparison with the same system without fusion, the sensitivity and specificity for detecting early stage of oesophagus cancer, i.e. low-grade dysplasia (LGD) increased from 75% and 88% to 83% and 97%, respectively. The video processing/play back speed is 33.46 frames per second. The main contribution includes alleviation of data source dependency of existing deep learning systems and the fusion of human perception for data augmentation

Analytical study on holographic superconductors in external magnetic field

We investigate the holographic superconductors immersed in an external magnetic field by using the analytical approach. We obtain the spatially dependent condensate solutions in the presence of the magnetism and find analytically that the upper critical magnetic field satisfies the relation given in the Ginzburg-Landau theory. We observe analytically the reminiscent of the Meissner effect where the magnetic field expels the condensate. Extending to the D-dimensional Gauss-Bonnet AdS black holes, we examine the influence given by the Gauss-Bonnet coupling on the condensation. Different from the positive coupling, we find that the negative Gauss-Bonnet coupling enhances the condensation when the external magnetism is not strong enough.Comment: revised version, to appear in JHE

Disease diagnosis in smart healthcare: Innovation, technologies and applications

To promote sustainable development, the smart city implies a global vision that merges artificial intelligence, big data, decision making, information and communication technology (ICT), and the internet-of-things (IoT). The ageing issue is an aspect that researchers, companies and government should devote efforts in developing smart healthcare innovative technology and applications. In this paper, the topic of disease diagnosis in smart healthcare is reviewed. Typical emerging optimization algorithms and machine learning algorithms are summarized. Evolutionary optimization, stochastic optimization and combinatorial optimization are covered. Owning to the fact that there are plenty of applications in healthcare, four applications in the field of diseases diagnosis (which also list in the top 10 causes of global death in 2015), namely cardiovascular diseases, diabetes mellitus, Alzheimer’s disease and other forms of dementia, and tuberculosis, are considered. In addition, challenges in the deployment of disease diagnosis in healthcare have been discussed