Window Coefficient Research Articles

Simulation-Based Design and Evaluation of Temperature Insensitive Device for SiOC on Insulator Platform

Silicon Oxycarbide (SiOC) has emerged as an intriguing material platform in integrated photonics due to its large adjustable refractive index window and low absorption coefficient. Changes in composition can tailor its physical, optical, and chemical properties over a wide range of parameters. The building-block method to circuit simulation is a useful framework for extensively exploiting photonics potential in vast implementation of complex circuits. Due to the large thermo-optic coefficient of the silicon-on-insulator (SOI) platform's core material, temperature dependency is one of the SiOC platform's key problems. In this paper, we designed and tested a temperature insensitive optical sensor using SiOC on insulator in available simulator, which only propagates single mode through the waveguide. We were able to find the first mode propagation at 600 nm to 1200 nm waveguide widths with the constant height of 220 nm. The significance of MZI based simulated sensor is that it is completely temperature insensitive at 1550 nm wavelength. We also realized from our simulated device that above 1200 nm waveguide width, the device has multimode propagation capability.

A simple and robust cell-based assay for the discovery of novel cytokinesis inhibitors.

Cytokinesis is the last step of mitotic cell division that separates the cytoplasm of dividing cells. Small molecule inhibitors targeting either the elements of the regulatory pathways controlling cytokinesis, or the terminal effectors have been of interest as potential drug candidates for the treatment of various diseases. Here we present a detailed protocol for a cell-based cytokinesis assay that can be used for the discovery of novel cytokinesis inhibitors. The assay is performed in a 96-well plate format in 48 h. Living cells, nuclei and nuclei of dead cells are identified by a single staining step using three fluorescent dyes, followed by rapid live cell imaging. The primary signal is the nuclei-to-cell ratio (NCR). In the presence of cytokinesis inhibitors, this ratio increases over time, as the ratio of multinucleated cells increases in the population. The ratio of dead nuclei to total nuclei provides a simultaneous measure of cytotoxicity. A screening window coefficient (Z`) of 0.65 indicates that the assay is suitable for screening purposes, as the positive and negative controls are well-separated. EC50 values can be reliably determined in a single 96-well plate by using only six different compound concentrations, enabling the testing of 4 compounds per plate. An excellent test-retest reliability (R2 = 0.998) was found for EC50 values covering a ~1500-fold range of potencies. Established small molecule inhibitors of cytokinesis operating via direct action on actin dynamics or nonmuscle myosin II are used to demonstrate the robustness, simplicity and flexibility of the assay.

Experimental validation of a building block of passive devices and stochastic analysis of PICs based on SiOC technology.

Silicon oxycarbide (SiOC) with a wide tunable refractive index window and low absorption coefficient has emerged as an appealing material platform in integrated photonics. Its physical, optical and chemical properties can be tailored over a large window through changes in composition. The circuit simulation based on the building-block approach is a useful framework for deep exploitation of the potential of photonics in the large-scale integration of complex circuits. In this manuscript, the simulation and experimental results of the waveguide and directional coupler based on SiOC technology have been investigated. A simplified model for the coupling coefficient, within defined limits of width, coupling length and gap, of parallel waveguides of the directional coupler has been proposed and validated experimentally. The building blocks of the waveguide and directional coupler have been prepared and parametrized. The proposed models of these passive devices have been exploited in commercially available circuit simulator for the circuit and stochastic simulations of SiOC based photonic circuits.

Multi-criteria comprehensive study on predictive algorithm of heating energy consumption of district heating station based on timeseries processing

Refined control of district heating station relies on reasonable and accurate prediction of heating energy consumption. Due to the influence of building thermal inertia and time-delay of the district heating system, certain research work is necessary to thoroughly illustrate and analyze the impact of data timeseries processing on various prediction models. Four kinds of prediction algorithms were investigated and compared in this paper. Results showed that all of three timeseries processing methods, namely time feature construction, sliding window and building thermal inertia coefficient (CBTI), can improve the prediction accuracy of all four models and CBTI had the greatest impact on model accuracy improvement. Moreover, timeseries processing method has no limitation on the types of prediction model and it is a general method to improve the model accuracy. Time feature construction and sliding window had greater influence on the non-neural network models while CBTI was the opposite. In terms of model robustness, the robustness had been significantly improved after introducing timeseries processing except random forest, and the comprehensive robustness coefficient for the other three models had been reduced by about 95%. Recurrent neural network had extremely excellent robustness under different temporal granularity.

Modified locally-adaptive myriad filters

Modified myriad locally-adaptive filters (LAF) in a sliding data window with complex use of local activity indicators (LAIs) of previously designed myriad LAFs are proposed. Improvement of integral indicator for the whole complex one-dimensional signal and local efficiency indicators at segments of linear change, constant level and step edge of signal function was achieved according to criterion of the mean-square error. Based on LAIs comparison, the myriad LAFs switch adaptive myriad filters with adaptation of linearity parameter K depending upon local scale estimates and with different values of window length and coefficient influencing on K. In one of the proposed LAFs, the LAI are also used for approximate estimation of the noise level and for choosing the corresponding set of component filters with parameters more appropriate to the estimated noise level. The preliminary use of the robust Hampel myriad filter is proposed for better spikes removal. The algorithms are implemented in real time.

Controllable Negative Thermal Expansion by Mechanical Pulverizing in Hexagonal Mn0.965Co1.035Ge Compounds.

Negative thermal expansion (NTE) material as a compensator is very important for accurately controlling the thermal expansion of materials. Along with the magnitude of the coefficient of thermal expansion, the operating temperature window of the NTE materials is also a major concern. However, only a few of the NTE materials possess both a large operating temperature range and a large thermal expansion coefficient. To explore this type of new NTE material, the Mn0.965Co1.035Ge fine powders were prepared by mechanical ball milling (BM). These fine powders show a largely extended NTE operation temperature window simultaneously possessing a giant thermal expansion coefficient. For samples treated with different BM times, such as the BM-0.5h, BM-4h, and BM-12 h samples, the operating temperature window (Δ T) and linear thermal expansion coefficient (αL) are 167 K (222-389 K) and ∼ -63 ppm/K, 221 K (140-360 K) and ∼ -41.3 ppm/K, and 208 K (234-442 K) and ∼ -40 ppm/K, respectively, which are larger than most well-known NTE materials. More strikingly, all BM samples have a large constant linear NTE coefficient with an ultrawide temperature window covering room temperature. For these three samples, these values are ∼ -52 ppm/K (140 K), ∼ -58.3 ppm/K (110 K), and ∼ -65 ppm/K (80 K), respectively. The origin of the excellent NTE properties is discussed based on the thermomagnetic measurements and X-ray absorption spectroscopic results.

Elastocaloric effect in Ni50Fe19Ga27Co4 single crystals

The elastocaloric effect of the [001]P and [111]P orientated (subscript P represents the parent phase) Ni50Fe19Ga27Co4 (at.%) single crystals exhibiting first-order martensitic transformations have been studied at temperatures of 298–448K under different compressive stresses. The adiabatic temperature change ΔTadi shows a significant dependence on the crystal orientation. The temperature decrease caused by adiabatic removal of stress 300MPa reaches to about 9–10K in a temperature range 328–398K for [001]P specimen and 3K at temperature near Af for [111]P one. The large elastocaloric effect is essentially attributed to the entropy change during the stress-induced martensitic transformation. The accumulated defect such as the a/2〈112〉 L10 type dislocation is the main reason for the attenuation of the elastocaloric effect in a fatigue test up to 3000 cycles. Large specific adiabatic temperature (|ΔTadi/Δσ|≈35K/GPa), wide specific effective temperature window (|ΔTwin/Δσ|≈320K/GPa) and high coefficient of performance (COP≈14) in a temperature range as wide as 50K during the unloading process enable the [001]P orientated Ni50Fe19Ga27Co4 single crystal as a potential elastocaloric material.

Time-varying linkages between tourism receipts and economic growth in South Africa

The causal link between tourism receipts and GDP has recently become a major focus in the tourism economics literature. Results obtained in recent studies about the causal link appear to be sensitive with respect to the countries analysed, sample period and methodology employed. Considering the sensitivity of the causal link, we use rolling window and time-varying coefficient estimation methods to analyse the parameter stability and Granger causality based on a vector error correction model (VECM). When applied to South Africa for the period 1960–2011, the findings are as follows: results from the full-sample VECM indicate that there is no Granger causality between tourism receipts and GDP, while the findings from the time-varying coefficients model based on the state-space representation show that tourism receipts have positive-predictive content for GDP for the entire period, with the exception of the period between 1985 and 1990. Full-sample time-varying causality tests show bidirectional strong causality between tourism receipts and GDP.

AroER Tri-Screen Is a Biologically Relevant Assay for Endocrine Disrupting Chemicals Modulating the Activity of Aromatase and/or the Estrogen Receptor

Endocrine disrupting chemicals (EDCs) interfere with the biosynthesis, metabolism, and functions of steroid hormones, including estrogens and androgens. Aromatase enzyme converts androgen to estrogen. Thus, EDCs against aromatase significantly impact estrogen- and/or androgen-dependent functions, including the development of breast cancer. The current study aimed to develop a biologically relevant cell-based high-throughput screening assay to identify EDCs that act as aromatase inhibitors (AIs), estrogen receptor (ER) agonists, and/or ER antagonists. The AroER tri-screen assay was developed by stable transfection of ER-positive, aromatase-expressing MCF-7 breast cancer cells with an estrogen responsive element (ERE) driven luciferase reporter plasmid. The AroER tri-screen can identify: estrogenic EDCs, which increase luciferase signal without 17β-estradiol (E2); anti-estrogenic EDCs, which inhibit the E2-induced luciferase signal; and AI-like EDCs, which suppress a testosterone-induced luciferase signal. The assay was first optimized in a 96-well plate format and then miniaturized into a 1536-well plate format. The AroER tri-screen was demonstrated to be suitable for high-throughput screening in the 1536-well plate format, with a 6.9-fold signal-to-background ratio, a 5.4% coefficient of variation, and a screening window coefficient (Z-factor) of 0.78. The assay suggested that bisphenol A (BPA) functions mainly as an ER agonist. Results from screening the 446 drugs in the National Institutes of Health Clinical Collection revealed 106 compounds that modulated ER and/or aromatase activities. Among these, two AIs (bifonazole and oxiconazole) and one ER agonist (paroxetine) were confirmed through alternative aromatase and ER activity assays. These findings indicate that AroER tri-screen is a useful high-throughput screening system for identifying ER ligands and aromatase-inhibiting chemicals.

Improvement of window thermal performance using aerogel insulation film for building energy saving

In buildings, windows have a major influence on space heating demand and indoor environment both with respect to climate and daylight. To reduce the window coefficient of the overall heat transmission, we use aerogel. Aerogels have a high surface area, low density, open pore structure, and excellent insulation properties. We mixed pressure sensitive adhesive and aerogel (10, 15, and 20 mass%) using a homogenizer. A mixture of the adhesives and silica aerogels attached film can reduce thermal conductivity. Silica aerogels are characterized by a surface area analyzer (BET), a Fourier transform infrared spectrometer, a thermogravimetry (TG) analyzer, and probe tack method. Thermal conductivity was measured by a TCi thermal conductivity analyzer.

Direct and Unbiased Information Recovery from Liquid Chromatography–Mass Spectrometry Raw Data for Phenotype-Differentiating Metabolites Based on Screening Window Coefficient of Ion Currents

A reworking of a data mining strategy, in which statistical treatment of raw data from liquid chromatography-mass spectrometry (LC-MS) precedes recognition of chromatographic peaks, is presented. In this algorithm the tR-m/z plane of LC-MS data is divided into equal-sized segments of twelve seconds by one m/z unit each, and the total ion currents in corresponding segments as specified by the tR-m/z pair from multiple LC-MS runs are evaluated to generate mean ion currents (μ) and standard deviations (σ). The μ's and σ's of the segments, derived from contrasting classes of LC-MS data set (e.g., resistant-susceptible, case-control, etc.), are used to calculate the Z-factor (screening window coefficient) which is in turn used to rank the segments. Chromatographic peaks are recognized only where the ion currents are shown to differentiate the classes. The result-reporting format enables detection of positive as well as negative correlations between ion intensities and biological traits under study and thus points to the presence of potentially phenotype-discriminating metabolites. Examples of data analyses are presented, in which ions that may distinguish resistant and susceptible species of Aesculus to the leaf-miner Cameraria ohridella were detected.

Image Defect Recognition Based on “Super Fuzzy” Characteristic

In this paper, we propose a new defects recognition algorithm for dynamic image based on “super fuzzy” feature. With this algorithm, the image is divided into some variable windows, and the eigenvector of each window is constructed. We introduce “super fuzzy” vector to make window vectors “super fuzzy” processing, thus the window feature has “super fuzzy” characteristic with the difference of the primary and secondary. Also we present window coefficient to adjust recognition speed and accuracy according to different images. Furthermore, objective function, membership function and clustering center calculation function of fuzzy clustering algorithm with window coefficient and “super fuzzy” vector are proposed in this paper. At last, we take example for fabric defects detection with this algorithm, list recognition results, discuss recognition result influence by “super fuzzy” feature and size change of window, and make some comparison with other algorithms. The conclusion shows that this algorithm can recognize more categories of image abnormal regions with high-accuracy, high-speed, no-training and extensive application.

Inducible APOBEC3G-Vif Double Stable Cell Line as a High-Throughput Screening Platform To Identify Antiviral Compounds

Inhibition of the interaction of the human cytidine-deaminase APOBEC3G (A3G) with the human immunodeficiency virus (HIV) type 1-specific viral infectivity factor (Vif) represents a novel therapeutic approach in which a cellular factor with potent antiviral activity (A3G) plays a key role. In HIV-infected cells, the interaction of Vif with A3G leads to the subsequent degradation of A3G by the 26S proteasome via the ubiquitin pathway and to the loss of antiviral activity. To establish a stable and convenient cellular testing platform for the high-throughput screening of potential antiviral compound libraries, we engineered a double transgenic cell line constitutively expressing an enhanced yellow fluorescent protein expressor (EYFP-A3G) fusion as well as a Tet-Off controllable Vif protein. With this cell line, we were able to measure precisely the Vif-induced degradation of A3G in the presence of potential antiviral compounds in an easy-to-handle, robust, and practical high-throughput multiwell plate format with an excellent screening window coefficient (Z factor) of 0.67.

Automating a 96-well microtitre plate model for Staphylococcus aureus biofilms: an approach to screening of natural antimicrobial compounds

The purpose of this study was to establish and automate an assay to be used for screening novel antimicrobial agents against biofilm-forming Staphylococcus aureus bacteria. The selected assay was based on crystal violet staining, which is a well used method for staining bacterial biofilms. The method was first optimised manually, antibiotic susceptibility was established and biofilm formation in plates was confirmed using atomic force microscopy. Automation of the assay was done using a Thermo Scientific Multidrop ® Combi dispenser and Biomek ® 3000 liquid handling workstation. A detailed comparison of the performance between the manual and the automated method was made in terms of screening window coefficient as well as other statistical parameters and repeatability measurements, such as plate-to-plate and day-to-day variability. Automated screening of an in-house library of natural products gave the same positive hits as previously reported, therefore the developed assay can be regarded as a reliable screening tool.

Improved fluorogenic histone deacetylase assay for high-throughput-screening applications

Histone deacetylases (HDACs) are key targets for chemotherapeutic intervention in malignant diseases. In this paper, a highly sensitive, nonisotopic, homogenous assay for high-throughput screening of HDAC inhibitors is presented. The assay is based on a new fluorogenic peptidic substrate of HDACs comprising an ε-acetylated lysyl moiety and an adjacent 4-methylcoumarin-7-amide moiety at the C terminus of the peptide chain. Upon deacetylation of the acetylated lysyl moiety, molecules are recognized as substrates by trypsin, which releases highly fluorescent 7-amino-4-methylcoumarin molecules in a subsequent step of the assay. The fluorescence increase is directly proportional to the amount of deacetylated substrate molecules, i.e., HDAC activity. Validation of an improved version of the assay revealed (i) a significantly lower enzyme consumption, (ii) an increased screening window coefficient, (iii) a good tolerance toward organic solvents, and (iv) a good suitability for a whole range of different HDAC-like enzymes. The novel assay thus will expedite studies of HDAC-like enzymes and in vitro screening for drug discovery.

A Simple Statistical Parameter for Use in Evaluation and Validation of High Throughput Screening Assays.

The ability to identify active compounds (³hits²) from large chemical libraries accurately and rapidly has been the ultimate goal in developing high-throughput screening (HTS) assays. The ability to identify hits from a particular HTS assay depends largely on the suitability or quality of the assay used in the screening. The criteria or parameters for evaluating the ³suitability² of an HTS assay for hit identification are not well defined and hence it still remains difficult to compare the quality of assays directly. In this report, a screening window coefficient, called ³Z-factor,² is defined. This coefficient is reflective of both the assay signal dynamic range and the data variation associated with the signal measurements, and therefore is suitable for assay quality assessment. The Z-factor is a dimensionless, simple statistical characteristic for each HTS assay. The Z-factor provides a useful tool for comparison and evaluation of the quality of assays, and can be utilized in assay optimization and validation.

Discrete time window functions with arbitrarily low sidelobe level

The most common approach to establish a set of window coefficients, representing the discrete time window (data window), is to select a suitable one from the well-known collections of continuous time window functions by simply sampling techniques. The simplicity of this approach has its price in certain complications which become more and more obvious as the number N of window coefficients decreases to small values ( N about 20 or less). It can be shown, that the DFT-even sampling technique as proposed by Harris [1] is not the most suitable one. Since both the aliasing effects as well as the relative position of the sampling raster gain influence on the resulting window magnitude spectrum in such a way that they must be checked individually, it turns out to be better to change the whole design strategy. The design of discrete windows is changed into an optimization problem within the set of all potential window coefficient vectors of given dimension. We apply the optimization criterion of Landau and Pollak [9]. One important advantage of this approach is that the optimization of the window coefficients is reduced to the proper selection of one single parameter which in a monotonic manner controls the trade-off between the two relevant window features mainlobe width and sidelobe level.