Impact of Firefighting Sprays on the Fire Performance of Structural Steel Members

Fire Technology - The feasibility of coupled computational fluid dynamics (CFD) and finite element (FE) simulations to aid the planning of fire intervention tactics and the effectiveness of...     

TAS-116, a Well-Tolerated Hsp90 Inhibitor,Prevents the Activation of the NLRP3 Inflammasome in Human Retinal Pigment Epithelial Cells

Chronic inflammation has been associated with several chronic diseases, such as age-related macular degeneration (AMD). The NLRP3 inflammasome is a central proinflammatory signaling complex that triggers caspase-1 activation leading to the maturation of IL-1β. We have previously shown that the inhibition of the chaperone protein, Hsp90, prevents NLRP3 activation in human retinal pigment epithelial (RPE) cells; these are cells which play a central role in the pathogenesis of AMD. In that study, we used a well-known Hsp90 inhibitor geldanamycin, but it cannot be used as a therapy due to its adverse effects, including ocular toxicity. Here, we have tested the effects of a novel Hsp90 inhibitor, TAS-116, on NLRP3 activation using geldanamycin as a reference compound. Using our existing protocol, inflammasome activation was induced in IL-1α-primed ARPE-19 cells with the proteasome and autophagy inhibitors MG-132 and bafilomycin A1, respectively. Intracellular caspase-1 activity was determined using a commercial caspase-1 activity kit and the FLICA assay. The levels of IL-1β were measured from cell culture medium samples by ELISA. Cell viability was monitored by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) test and lactate dehydrogenase (LDH) measurements. Our findings show that TAS-116 could prevent the activation of caspase-1, subsequently reducing the release of mature IL-1β. TAS-116 has a better in vitro therapeutic index than geldanamycin. In summary, TAS-116 appears to be a well-tolerated Hsp90 inhibitor, with the capability to prevent the activation of the NLRP3 inflammasome in human RPE cells.     

Additive manufacturing of monolithic supercapacitors with biopolymer separator

Journal of Applied Electrochemistry - In this paper, additive layer-by-layer fabrication of a fully screen printed monolithic supercapacitor exhibiting performance comparable with supercapacitors...     

Open circuit potential and leaching rate of pyrite in cupric chloride solution

As a refractory gold mineral, pyrite needs to be oxidised prior to gold leaching. In this study, the effect of [Cl^?] concentration (40.6–149.8?g/L), [Cu²⁺] concentration (0.8–31.6?g/L), pH (1.5–2.5) and temperature (25–90 –C) on the pyrite leaching rate was investigated. In addition, the open circuit potential (OCP) values of pyrite in cupric chloride solution were investigated. A linear regression model was constructed to predict pyrite dissolution rate i.e. corrosion current density. It was shown that the temperature had a significant positive effect on pyrite dissolution, while increased cupric ion concentration was also shown to provide some dissolution enhancement. According to the regression analysis, pH had no effect on the corrosion current density at OCP. Dissolution rates of pyrite varied between 0.05 and 2.9?µm/h. The activation energy values varied from 20 to 90?kJ/mol, indicated that the pyrite dissolution reaction rate was controlled by the chemical reaction or mixed mechanism rather than diffusion alone. The simultaneous increase in corrosion potential and corrosion current density indicated that the anodic pyrite dissolution reaction was rate determining at OCP.     

High-level parameterizable area estimation modeling for ASIC designs

Architectural design space exploration and early area budgeting for ASIC and IP block development require accurate high level gate count estimation methods without requiring the hardware being fully specified. The proposed method uses hierarchical and parameterizable models requiring minimal amount of information about the implementation technology to meet this goal. The modeling process flow is to: (1) create a block diagram of the design, (2) create a model for each block, and (3) sum up estimates of all sub-blocks by supplying the correct parameters to each sub-model. We discuss the model creation for a few parameterized library blocks as well as three communication blocks and a processor core from real IC projects ranging from 22 to 250 kgates. The average relative estimation error of the proposed method for the library blocks is 3.2% and for the real world examples 4.0%. The best application of this method is early in the design phase when different implementation architectures are compared.     

Framework for developing image-based dirt particle classifiers for dry pulp sheets

One important aspect of assessing the quality in pulp and papermaking is dirt particle counting and classification. Knowing the number and types of dirt particles present in pulp is useful for detecting problems in the production process as early as possible and for fixing them. Since manual quality control is a time-consuming and laborious task, the problem calls for an automated solution using machine vision techniques. However, the ground truth required to train an automated system is difficult to ascertain, since all of the dirt particles should be manually segmented and classified based on image information. This paper proposes a framework for developing and tuning dirt particle detection and classification systems. To avoid manual annotation, dry pulp sheets with a single dirt type in each were exploited to generate semisynthetic images with the ground truth information. To classify the dirt particles, a set of features were computed for each image segment. Sequential feature selection was employed to determine a close-to-optimal set of features to be used in classification. The framework was tested both with semisynthetically generated images based on real pulp sheets and with independent original real pulp sheets without any generation. The results of the experiments show that the semisynthetic procedure does not significantly change the properties of images and has little effect on the particle segmentation. The feature selection proved to be important when the number of dirt classes changes since it allows to improve the classification results. Using the standard classification methods, it is possible to obtain satisfactory results, although the methods modeling the data, such as the Bayesian classifier using the Gaussian Mixture Model, show better performance.     

Rigorous and approximate analysis of metallic gratings in soft X-ray and EUV regions

Abstract

In deep ultraviolet and soft X-ray regions the complex refractive indices of metals differ substantially from their values in the visible region of the spectrum. The implications of this fact are analysed for metallic gratings illuminated by electromagnetic fields with wavelengths ranging from soft X‐rays to near infrared, concentrating on short wavelengths. In particular, we study metal-stripe gratings (linear polarizers for visible light) by rigorous diffraction theory to determine the short-wavelength region in which a combination of the geometrical thin-element approximation and the theory of single-layer films can be applied. Then we study inductive grid filters for protection of X-ray detectors from infrared radiation in space applications.     

Gone with the wind? Newspaper discourse of eutrophication and blue‐green algae blooms in Finland

The mass media shape the public and policy agenda by giving prominence to certain ecosystem changes and risks, as well as by framing some policy measures as the preferred ones. Based on longitudinal analysis of the leading Finnish newspaper, this study considers the media coverage of eutrophication. The results show an increase of reporting in the late 1990s as a result of intertwined ecological and social factors – i.e. intense algal occurrences and establishment of a national communication system. The news coverage has highlighted the harmful algal blooms and health risks of algal toxins and has framed short‐term weather conditions as the key factor regulating algal occurrences. This creates a challenge for environmental management aimed at reduction in the nutrient discharges that influence the state of the environment in the long term.     

Characteristics of day‐ahead wind power forecast errors in Nordic countries and benefits of aggregation

The growing proportion of wind power in the Nordic power system increases day‐ahead forecasting errors, which have a link to the rising need for balancing power. However, having a large interconnected synchronous power system has its benefits, because it enables to aggregate imbalances from large geographical areas. In this paper, day‐ahead forecast errors from four Nordic countries and the impacts of wind power plant dispersion on forecast errors in areas of different sizes are studied. The forecast accuracy in different regions depends on the amount of the total wind power capacity in the region, how dispersed the capacity is and the forecast model applied. Further, there is a saturation effect involved, after which the reduction in the relative forecast error is not very large anymore. The correlations of day‐ahead forecast errors between areas decline rapidly when the distance increases. All error statistics show a strong decreasing trend up to the area sizes of 50,000 km². The average mean absolute error (MAE) in different regions is 5.7% of installed capacity. However, MAE of a smaller area can be over 8% of the capacity, but when all the Nordic regions are aggregated together, the capacity‐normalized MAE decreases to 2.5%. The average of the largest errors for different regions is 39.8% and when looking at the largest forecast errors for smaller areas, the largest errors can exceed 80% of the installed capacity, whereas at the Nordic level, the maximum forecast error is only 13.5% of the installed capacity. Copyright © 2016 John Wiley & Sons, Ltd.     

On-chip offset generator for accurate integral non-linearity testing of A/D converters and D/A-A/D converter pairs

It has recently shown how a constant dc offset between two low-quality test signals can be used to test the integral nonlinearity (INL) of A/D converters (ADCs) without an accurate test stimulus, and how the same method can be used to test the INL of D/A converters (DACs) as well. We propose here an on-chip offset generator for producing the constant offset and analyse its limitations. Experimental tests on the 122 × 22 μm² offset generator fabricated in 130 nm CMOS process show that it can be used to test the INL of 12-b DACs and ADCs. The generator is rail-to-rail capable so that almost the whole input/output range of converters can be tested. Moreover, if the proposed offset generator is used in a ratiometric test setup as proposed here as well, the influence of a reference voltage drift on measurement accuracy is cancelled out. Because of its small size, simple design, rail-to-rail capability and immunity to reference voltage changes, the proposed offset generator is well suited for built-in self-test usage.