Estimation of quantile mixtures via L-moments and trimmed L-moments

Moments or cumulants have been traditionally used to characterize a probability distribution or an observed data set. Recently, L-moments and trimmed L-moments have been noticed as appealing alternatives to the conventional moments. This paper promotes the use of L-moments proposing new parametric families of distributions that can be estimated by the method of L-moments. The theoretical L-moments are defined by the quantile function i.e. the inverse of cumulative distribution function. An approach for constructing parametric families from quantile functions is presented. Because of the analogy to mixtures of densities, this class of parametric families is called quantile mixtures. The method of L-moments is a natural way to estimate the parameters of quantile mixtures. As an example, two parametric families are introduced: the normal-polynomial quantile mixture and the Cauchy-polynomial quantile mixture. The proposed quantile mixtures are applied to model monthly, weekly and daily returns of some major stock indexes.     

Nanotechnology Facilitated Cultured Neuronal Network and Its Applications

The development of a biomimetic neuronal network from neural cells is a big challenge for researchers. Recent advances in nanotechnology, on the other hand, have enabled unprecedented tools and techniques for guiding and directing neural stem cell proliferation and differentiation in vitro to construct an in vivo-like neuronal network. Nanotechnology allows control over neural stem cells by means of scaffolds that guide neurons to reform synaptic networks in suitable directions in 3D architecture, surface modification/nanopatterning to decide cell fate and stimulate/record signals from neurons to find out the relationships between neuronal circuit connectivity and their pathophysiological functions. Overall, nanotechnology-mediated methods facilitate precise physiochemical controls essential to develop tools appropriate for applications in neuroscience. This review emphasizes the newest applications of nanotechnology for examining central nervous system (CNS) roles and, therefore, provides an insight into how these technologies can be tested in vitro before being used in preclinical and clinical research and their potential role in regenerative medicine and tissue engineering.     

Methods of artificial enlargement of the training set for statistical shape models

Due to the small size of training sets, statistical shape models often over-constrain the deformation in medical image segmentation. Hence, artificial enlargement of the training set has been proposed as a solution for the problem to increase the flexibility of the models. In this paper, different methods were evaluated to artificially enlarge a training set. Furthermore, the objectives were to study the effects of the size of the training set, to estimate the optimal number of deformation modes, to study the effects of different error sources, and to compare different deformation methods. The study was performed for a cardiac shape model consisting of ventricles, atria, and epicardium, and built from magnetic resonance (MR) volume images of 25 subjects. Both shape modeling and image segmentation accuracies were studied. The objectives were reached by utilizing different training sets and datasets, and two deformation methods. The evaluation proved that artificial enlargement of the training set improves both the modeling and segmentation accuracy. All but one enlargement techniques gave statistically significantly $(p ≪ 0.05)$ better segmentation results than the standard method without enlargement. The two best enlargement techniques were the nonrigid movement technique and the technique that combines principal component analysis (PCA) and finite element model (FEM). The optimal number of deformation modes was found to be near 100 modes in our application. The active shape model segmentation gave better segmentation accuracy than the one based on the simulated annealing optimization of the model weights.      

Power-to-ammonia in future North European 100 % renewable power and heat system

Power-to-gas and other chemicals-based storages are often suggested for energy systems with high shares of variable renewable energy. Here we study the North European power and district heat system with alternative long-term storage, the power-to-ammonia (P2A) technology. Assuming fully renewable power and heat sectors and large-scale electrification of road transport, we perform simultaneous optimization of capacity investments and dispatch scheduling of wind, solar, hydro and thermal power, energy storages as well as transmission, focusing on year 2050. We find that P2A has three major roles: it provides renewable feedstock to fertilizer industry and it contributes significantly to system balancing over both time (energy storage) and space (energy transfer). The marginal cost of power-based ammonia production in the studied scenarios varied between 431 and 528 €/t, which is in the range of recent ammonia prices. Costs of P2A plants were dominated by electrolysis. In the power and heat sector, with our cost assumptions, P2A becomes competitive compared to fossil natural gas only if gas price or CO₂ emission price rises above 70 €/MWh or 200 €/tCO₂.     

Potential of Long Non-Coding RNAs in Age-Related Macular Degeneration

Age-related macular degeneration (AMD) is the leading cause of visual impairment in the aging population with poorly known pathogenesis and lack of effective treatment. Age and family history are the strongest AMD risk factors, and several loci were identified to contribute to AMD. Recently, also the epigenetic profile was associated with AMD, and some long non-coding RNAs (lncRNAs) were shown to involve in AMD pathogenesis. The Vax2os1/2 (ventral anterior homeobox 2 opposite strand isoform 1) lncRNAs may modulate the balance between pro- and anti-angiogenic factors in the eye contributing to wet AMD. The stress-induced dedifferentiation of retinal pigment epithelium cells can be inhibited by the ZNF503-AS1 (zinc finger protein 503 antisense RNA 2) and LINC00167 lncRNAs. Overexpression of the PWRN2 (Prader-Willi region non-protein-coding RNA 2) lncRNA aggravated RPE cells apoptosis and mitochondrial impairment induced by oxidative stress. Several other lncRNAs were reported to exert protective or detrimental effects in AMD. However, many studies are limited to an association between lncRNA and AMD in patients or model systems with bioinformatics. Therefore, further works on lncRNAs in AMD are rational, and they should be enriched with mechanistic and clinical studies to validate conclusions obtained in high-throughput in vitro research.     

Integrated procurement of pulpwood and energy wood from early thinnings using whole-tree bundling

To increase the volume of energy wood and pulpwood harvested from early thinnings, their procurement costs will have to be significantly reduced. This can be done through the integration of pulpwood and energy wood procurement applying a newly-developed supply chain based on whole-tree bundling. In 2007, the first prototype of the bundle harvester capable of incorporating compaction into the cutting phase was launched. Cost savings, especially in primary and secondary transportation, can be achieved by increasing the load sizes by replacing undelimbed whole trees with bundles. The bundles can be hauled by a standard forwarder to the roadside storage area, from where they are transported by a standard timber truck to the pulp mill. Batches of bundles are then fed into a wood flow consisting of conventional delimbed pulpwood. Separation of the bundles into pulpwood and energy wood fractions does not take place until the wood reaches the debarking drum.In this feasibility study, the required productivity level of bundle harvesting (i.e., cutting and bundling) in Scots pine-dominated stands was assessed by comparing the total supply chain costs based on whole-tree bundling with those of the other pulpwood and energy wood supply chains by means of system analysis. The cost calculations indicated that whole-tree bundling enables the procurement costs to be reduced to below the current cost level of separate pulpwood and energy wood procurement in early thinnings. The greatest cost-saving potential lies in small-diameter (d_1.3 = 7-10 cm) first-thinning stands, which are currently unprofitable for conventional pulpwood procurement.     

Optimum geometry of fixed volume plate fin for maximizing heat transfer

A method is presented for finding the plate fin geometry for maximizing total heat transfer when cooled by forced or natural convection. The method is based on an approximate treatment of conjugated heat transfer in which analytical results are utilized. As a result of this type of approach, non-dimensional variables have been found that contain the geometrical and thermal properties of a fin and the flow. An essential fact is that there is no need to evaluate convection heat transfer coefficients. Only one variable with a fixed value is needed to determine the geometry of a fixed volume fin that gives the maximum heat transfer.     

Transformation of self-assembled InAs/InP quantum dots into quantum rings without capping

Transformation of self-assembled InAs quantum dots (QDs) on InP(100) into quantum rings (QRs) is studied. In contrast to the typical approach to III--V semiconductor QR growth, the QDs are not capped to form rings. Atomic force micrographs reveal a drastic change from InAs QDs into rings after a growth interruption in tertiarybutylphosphine ambient. Strain energy relief in the InAs QD is discussed and a mechanism for dot-to-ring transformation by As/P exchange reactions is proposed.     

Estimating materials parameters in thin-film BAW resonators using measured dispersion curves

The dispersion curves of Lamb-wave modes propagating along a multilayer structure are important for the operation of thin-film bulk acoustic wave (BAW) devices. For instance, the behavior of the side resonances that may contaminate the electrical response of a thin-film BAW resonator depends on the dispersion relation of the layer stack. Because the dispersion behavior depends on the materials parameters (and thicknesses) of the layers in the structure, measurement of the dispersion curves provides a tool for determining the materials parameters of thin films. We have determined the dispersion curves for a multilayer structure through measuring the mechanical displacement profiles over the top electrode of a thin-film BAW resonator at several frequencies using a homodyne Michelson laser interferometer. The layer thicknesses are obtained using scanning electron microscope (SEM) measurements. In the numerical computation of the dispersion curves, the piezoelectricity and full anisotropy of the materials are taken into account. The materials parameters of the piezoelectric layer are determined through fitting the measured and computed dispersion curves.     

Engineering the substrate specificity of xylose isomerase

Xylose isomerase (XI) catalyzes the isomerization and epimerization of hexoses, pentoses and tetroses. In order to clarify the reasons for the low reaction efficiency of a pentose sugar, L-arabinose, we determined the crystal structure of Streptomyces rubiginosus XI complexed with L-arabinose. The crystal structure revealed that, when compared with D-xylose and D-glucose, L-arabinose binds to the active site in a partially different position, in which the ligand has difficulties in binding the catalytic metal M2. Lys183 has been thought to stabilize the open substrate conformation by hydrogen bonding to oxygen O1. Our results with L-arabinose showed that the substrate stays in a linear form even without a hydrogen bond between Lys183 and oxygen O1. We engineered mutations to the active site of Actinoplanes missouriensis XI to improve the reaction efficiency with L-arabinose. The mutation F26W was intended to shift the position of oxygen O1 of L-arabinose closer to the catalytic metal M2. This effect of F26W was modeled by free energy perturbation simulations. In line with this, F26W increased 2-fold the catalytic efficiency of XI with L-arabinose; the increase was seen mainly in kcat. The mutation Q256D was outside the sphere of the catalytic residues and probably modified the electrostatic properties of the active site. It improved 3-fold the catalytic efficiency of XI with L-arabinose; this increase was seen in both Km and kcat. This study showed that it is possible to engineer the substrate specificity of XI.