Two-way analysis of high-dimensional collinear data

We present a Bayesian model for two-way ANOVA-type analysis of high-dimensional, small sample-size datasets with highly correlated groups of variables. Modern cellular measurement methods are a main application area; typically the task is differential analysis between diseased and healthy samples, complicated by additional covariates requiring a multi-way analysis. The main complication is the combination of high dimensionality and low sample size, which renders classical multivariate techniques useless. We introduce a hierarchical model which does dimensionality reduction by assuming that the input variables come in similarly-behaving groups, and performs an ANOVA-type decomposition for the set of reduced-dimensional latent variables. We apply the methods to study lipidomic profiles of a recent large-cohort human diabetes study.     

Relaxed Visibility Enhances Partial Order Reduction

State-space explosion is a central problem in the automatic verification (model-checking) of concurrent systems. Partial order reduction is a method that was developed to try to cope with the state-space explosion. Based on the observation that the order of execution of concurrent (independent) atomic actions is in many cases unimportant for the checked property, it allows reducing the state space by exploring fewer execution sequences. However, in order to guarantee that the reduced state space preserves the correctness of the checked property, the partial order reductions put constraints about commuting the order of atomic actions that may change the value of propositions appearing in the checked specification. In this paper we relax this constraint, allowing a weaker requirement to be imposed, and thus achieving a better reduction. We demonstrate the benefits of our improved reduction with experimental results.     

Merge of motion analysis,multibody dynamics and finite element method for the subject-specific analysis of cartilage loading patterns during gait: differences between rotation and moment-driven models of human knee joint

Understanding joint loading is important when evaluating sports training methods, sports equipment design, preventive training regimens, post-op recovery procedures, or in osteoarthritis’ etiology research. A number of methods have been introduced to estimate joint loads but they have been limited by the lack of accuracy in the joint models, including primarily the lack of patient-specific motion inputs in the models with sophisticated, fibril-reinforced material models. The method reported here records and applies patient-specific human motion for in-depth cartilage stress estimation. First, the motion analysis of a subject was conducted. Due to skin motion, multibody simulation was used to correct motion capture. These data was used as an input in a finite element model. The model geometry was based on magnetic resonance imaging and cartilage was modeled as a fibril-reinforced poroviscoelastic material. Based on the experimental motion data (motion analysis and multibody simulation), two models were created: a rotation-controlled and a moment-controlled model. For comparison, a model with motion input from the literature was created. The rotation-controlled model showed the most even stress distribution between lateral and medial compartments and smallest stresses and strains in a depth-wise manner. The model based on the literature motion simulated very high stresses and uneven stress distribution between the joint compartments. Our new approach to determine dynamic knee cartilage loading enables estimations of stresses and strains for a specific subject over the entire motion cycle.     

Logic Programs with Ordered Disjunction

Logic programs with ordered disjunction (LPODs) contain a new connective which allows representing alternative, ranked options for problem solutions in the heads of rules: A × B intuitively means that if possible A , but if A is not possible, then at least B . The semantics of logic programs with ordered disjunction is based on a preference relation on answer sets. We show how LPODs can be implemented using answer set solvers for normal programs. The implementation is based on a generator, which produces candidate answer sets and a tester which checks whether a given candidate is maximally preferred and produces a better candidate if it is not. We also discuss the complexity of reasoning tasks based on LPODs and possible applications.     

Ultraviolet photofunctionalization of nanostructured titanium surfaces enhances thrombogenicity and platelet response

The purpose of this study was to evaluate blood and platelet response to nanostructured TiO₂ coatings and to investigate the effect of Ultraviolet (UV) light treatment on blood clotting ability, platelet activation and protein adhesion. Ti-6Al-4V titanium alloy plates (n?=?138) were divided into three groups; a sol–gel derived MetAlive^TM coating (MA); hydrothermal coating (HT); and a non-coated group (NC). Sixty nine titanium substrates were further treated with UV light for 1?h. The thrombogenicity of the titanium substrates was assessed using fresh human blood with a whole blood kinetic clotting time method. The platelet adhesion test was conducted to evaluate the morphology and adhesion behavior of the platelets on the titanium substrates. Human diluted plasma and bovine fibronectin were used to evaluate protein adsorption. Total clotting time for the UV treated HT, MA and NC titanium substrates was almost 40?min compared to 60?min for non-UV substrates, the total clotting time for the UV treated groups were significantly lower than that of the non UV NC group (p?<?0.05). UV light treatment had significantly enhanced coagulation rates. The HT and MA substrates presented more platelet aggregation, spreading and pseudopod formation in comparison with the NC substrates. UV treatment did not affect the platelet activation and protein adsorption. This in vitro study concluded that nanostructured titanium dioxide implant surfaces obtained by sol–gel and hydrothermal coating methods increased coagulation rates and enhanced platelet response when compared with non-coated surfaces. UV light treatment clearly improved thrombogenicity of all examined Ti-6Al-4V surfaces.

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Powering Internet with power-law networking

It is generally recognized that the current routing scheme of Internet suffers from serious scalability problems. In this paper, we work with the abstract but ??Internet-like?? network model consisting of an infinite-variance power-law random graph (IVPLRG). We adopt the idea of a routing scheme proposed by Carmi, Cohen and Dolev (C-C-D). The scheme fits very naturally to the spontaneously emerging ??soft hierarchy?? architecture on an IVPLRG. The use of multiple addresses is suggested as a solution to the inflexibility of the pure C-C-D scheme. A mean-field approximation is introduced for efficient computation of relevant quantitative characteristics and applied to various problems of our scheme. We review a few recent Internet routing proposals and discuss their relation to our scheme. We find out that the topology creation of our scheme offers advantages in terms of scalability and routing policy control.     

Modelling and simulation of a copper electrolysis cell group

The energy consumption of the copper electrolysis process is relatively high. Electrical disturbances – like contact failures and short circuits – even increase the energy consumption and also reduce the quality of copper produced. To better understand and improve the process, a computationally feasible and reliable model of copper electrolysis cell group is of great importance. In this paper a multiphysical FEM model of copper electrolysis cell group is presented. A number of simplifications are proposed to make the model computationally feasible.     

Combining discrete-time Markov processes and probabilistic fracture mechanics in RI-ISI risk estimates

Based on the research conducted in the Finnish SAFIR project, which is a national nuclear energy research program, discrete-time Markov processes and probabilistic fracture mechanics (PFM) methods are further developed and applied in this paper. The purpose of this work is to increase the accuracy of risk estimates used in RI-ISI, and to quantitatively evaluate the effects of different inspection strategies on risk. Piping failure probabilities are obtained by using PFM analyses. PFM has the advantage that its results are not affected by existing in-service inspection (ISI) activities at the nuclear power plants (NPPs), unlike failure probabilities assessed from existing failure data. The PFM results for crack growth are used to construct transition matrices used in a discrete-time Markov process. The application of Markov process allows the examination of effects of inspections on the failure probabilities. Finally, the developed method and results are showcased by applying them to a selected piping system in an existing Finnish NPP.     

Mapping of understory lichens with airborne discrete-return LiDAR data

High backscatter reflectance at NIR wavelengths has been observed for reindeer lichens (Cladina sp.) in the laboratory. The results suggested that lichens could be separated from soil and other parts of forest understory using this property. An experiment was carried out to test this hypothesis in situ. The lichen vegetation of a 960-m² plot in a barren pine stand in Juupajoki, Finland was mapped in 3D, using methods of close-range photogrammetry. The data of two airborne discrete-return sensors were compared for their ability to classify understory lichen vegetation. Normalization of the LiDAR intensities was carried out, using natural targets. The results showed that lichen surfaces had a higher intensity than on average. Normalization of the intensities improved separability of lichens from other surfaces, and the best-case classification accuracy was 75%. Detailed analysis of geometric errors revealed small, decimeter-level planimetric offsets in the LiDAR datasets that affected the results notably.     

Drying of Activated Sludge Under Partial Vacuum Conditions—An Experimental Study

A typical wastewater treatment system in a pulp and paper mill in Finland treats wastewater both mechanically and biologically. Sludges resulting from these processes have to be disposed of. One possible way of doing this is to incinerate them with solid fuel in the power plant of the mill. To minimize the amount of sludge and to make the use of the sludge energy efficient, it has to be dried before incineration. Mechanical drying of the sludge from biological wastewater treatment is difficult to carry out. Using secondary energies may provide a competitive way of arranging drying: a method of doing this by using partial vacuum evaporation to utilize the low temperature secondary heat in sludge drying is under development. A laboratory study to examine the behavior of activated sludge under partial vacuum evaporation conditions was carried out using a laboratory rotating evaporator to analyze the drying of activated sludge from three mills at 40-80°C boiling temperatures. This article presents the results from the tests. These are promising; it was possible to reach high dry solids content. Also, no boiling point temperature rise was detected, fouling of the evaporator seemed low and easily avoidable, condensate from the evaporator weas relatively clean and returnable to the processes of the mill.