Real-time effective density monitor (DENSMO) for aerosol nanoparticle production

A new instrument, density monitor (DENSMO), for aerosol particle size distribution characterization and monitoring has been developed. DENSMO is operationally simple and capable of measuring the effective density as well as the aerodynamic and the mobility median diameters with a time resolution of 1 s, from unimodal particle size distributions. The characterization is performed with a zeroth order mobility analyzer in series with a low pressure impactor and a filter stage. The operation of DENSMO was investigated with sensitivity analysis and, based on the results, optimal operation parameters were determined. DENSMO was also compared, in lab test measurements, against a reference method with several particle materials with bulk densities from 0.92 to 10.5 g/cm³. The results show that the deviation from the reference method was less than 25% for suitable materials.

Copyright © 2016 American Association for Aerosol Research     

Titania and titania-silver nanoparticle deposits made by Liquid Flame Spray and their functionality as photocatalyst for organic- and biofilm removal

Titania and titania-silver nanoparticle deposits were made by Liquid Flame Spray technique, in which the liquid precursor is injected into a high temperature flame, where it will evaporate and nucleate to nanosize particles. One-step and two-step methods were used for preparation of titania-silver deposits. The amount of silver added was 1 wt%. The deposits were collected in the flame zone on steel and glass surfaces and were analyzed by TEM, EDS, XPS and SAXS. The titania deposits consisted of porous nanosized titania agglomerates of primary particles (~10 nm). With silver addition, small spherical silver metal particles (~2 nm) were detected on the agglomerates. An increase in the photocatalytic activity was verified by stearic acid decomposition and biofilm removal using Deinococcus geothermalis as the model organism.     

Iron Behavior in the Ozonation and Filtration of Groundwater

In Finnish groundwater, the main substances that require treatment are iron and manganese. In addition to this, groundwaters are soft and acidic. Iron removal is usually relatively effective by oxidizing dissolved iron into an insoluble form, either by aeration or chemical oxidization and removing the formed precipitate by sand filtration. Sometimes, if the untreated water contains high amounts of organic matter, problems may arise for iron removal. In Finland, it is quite common that groundwater contains high levels of both iron and natural organic matter, mainly as humic substances. The groundwater of the Kukkala intake plant in Liminka has been found to be problematic, due to its high level of natural organic matter. This research studied the removal of iron from this water by means of oxidation with ozone and filtration. While the oxidation of iron by ozone was rapid, the precipitate particles formed were small, and thus could not be removed by sand and anthracite filtration, and the iron residue in the treated water was more than 2 mgL^?1. And while the filtration was able to remove iron well without the feed of ozone, the iron residue in the treated water was only 0.30 mgL^?1. In this case, iron was led to the filter in a bivalent dissolved form. So, the result of iron removal was the best when the sand/anthracite filter functioned largely as an adsorption filter.     

Sensor validation using minimum mean square error estimation

Sensor fault can be detected and corrected in a multichannel measurement system with enough redundancy using solely the measurement data. A single or multiple sensors can be estimated from the remaining sensors if training data from the functioning sensor network are available. The method is based on the minimum mean square error (MMSE) estimation, which is applied to the time history data, e.g. accelerations. The faulty sensor can be identified and replaced with the estimated sensor. Both spatial and temporal correlation of the sensors can be utilized. Using the temporal correlation is justified if the number of active structural modes is larger than the number of sensors. The disadvantages of the temporal model are discussed. Experimental multichannel vibration measurements are used to verify the proposed method. Different, and also simultaneous, sensor faults are studied. The effects of environmental variability and structural damage are discussed.     

Endothelial cell-matrix interactions

Dynamic interactions between endothelial cells and components of their surrounding extracellular matrix are necessary for the invasion, migration, and survival of endothelial cells during angiogenesis. These interactions are mediated by matrix receptors that initiate intracellular signaling cascades in response to binding to specific extracellular matrix molecules. The interactions between endothelial cells and their environment are also modulated by enzymes that degrade different matrix components and thus enable endothelial invasion. Recent reports on gene targeting in mice have confirmed the role of two classes of matrix receptors, integrins and cell surface heparan sulfate proteoglycans, and a group of matrix degrading proteolytic enzymes, matrix metalloproteinases, in angiogenesis. The significance of endothelial cell-matrix interactions is further supported by several ongoing clinical trials that analyze the effects of drugs blocking this interaction on angiogenesis-dependent growth of human tumors.     

Regulation of receptor-coupling to (multiple) G proteins. A challenge for basic research and drug discovery

G protein-coupled receptors induce intracellular signals via interaction of with cytosolic/peripheral membrane proteins, mainly G proteins. There has been much debate about the mode of interaction between the receptors, G proteins and effectors, their mobility and the ways of determining the specificity of interaction. Additional complexity has been added to system upon the discovery of i) coupling of single receptors to several G proteins and ii) active direction of this by different ligands (stimulus trafficking). These data suggest that the most primary unit in the signal transduction is the receptor complexed with a specific G protein, making the investigation of the mechanism of receptor-G protein selection and interaction even more important. In this review, I will summarize the general knowledge of receptor interaction with G proteins and effectors and the ways of investigating this.     

What goes down must come up? Trends of industrial electricity use in the North-West of Russia

This article uses decomposition method to analyse industrial electricity consumption in North-Western Russia, namely in Archangelsk oblast, the Republic of Karelia and Murmansk oblast. The case sectors, forestry and electricity, have in most cases developed similarly in the chosen regions during 1990–2001. The decomposition analysis shows that the reduction of economic activity has reduced electricity consumption in all three regions but that it is not always the main factor reducing consumption. The changes in energy efficiency increased consumption in the forestry sector in all regions while in the electricity sector it led to a reduction. The changes in the structures of the regional economies increased electricity consumption in electricity industry which gained importance due to developments in the manufacturing industry. In Murmansk, forestry sector has almost disappeared during the observation period. This was the main observed electricity consumption reduction caused by structural changes. Many of the developments can be better understood against the general knowledge of transition factors.     

Two-tier relaxed heaps

We introduce a data structure which provides efficient heap operations with respect to the number of element comparisons performed. Let n denote the size of the heap being manipulated. Our data structure guarantees the worst-case cost of O(1) for finding the minimum, inserting an element, extracting an (unspecified) element, and replacing an element with a smaller element; and the worst-case cost of O(lg n) with at most lg n + 3 lg lg n + O(1) element comparisons for deleting an element. We thereby improve the comparison complexity of heap operations known for run-relaxed heaps and other worst-case efficient heaps. Furthermore, our data structure supports melding of two heaps of size m and n at the worst-case cost of O(min {lg m, lg n}). A preliminary version of this paper [8] was presented at the 17th International Symposium on Algorithms and Computation held in Kolkata in December 2006. Partially supported by the Danish Natural Science Research Council under contracts 21-02-0501 (project Practical data structures and algorithms) and 272-05-0272 (project Generic programming—algorithms and tools).     

Optical performance characterization of flexible mobile displays

The high interest in the display industry to produce curved or flexible displays for mobile, wearable, and television markets has raised concerns on the performance of displays in their bent state. Flexible display technologies have been developed for this purpose, but their optical characteristics have not been previously reported at various degrees of curvature. The measurement of flexible displays is possible only with special measurement arrangements using common display characterization devices. A conoscope with a working distance of 15 mm was used to demonstrate the curvature dependence of luminance, viewing angle, and color coordinates of the white point of a flexible active‐matrix organic light‐emitting display. The results show that the effect of curvature on the optical characteristics of the display is most evident at the smallest measured bending radii of +/?50 mm and that the effects are most visible when viewing the bent ends of the display, from the central normal vantage point, with uniform curvature along the display.     

Normalising OLAP cubes for controlling sparsity

A poorly designed OLAP (on-line analytical processing) cube can have a size much larger than the volume of information, potentially leading to problems with performance and usability. We give a new normal form for OLAP cube design and synthesis and decomposition algorithms to produce normalised OLAP cube schemata. OLAP cube normalisation controls the structural sparsity resulting from inter-dimensional functional dependencies. We assume that functional dependencies are used to describe the constraints of the application universe of discourse. Our methods help the user to identify cube schemata with structural sparsity, and to change the design in order to obtain more economy of space.