Caputo Derivatives in Viscoelasticity: A Non-Linear Finite-Deformation Theory for Tissue

Mathematics Subject Classification: 26A33, 74B20, 74D10, 74L15

Explicit Solutions of Nonlocal Boundary Value Problems, Containing Bitsadze-Samarskii Constraints

MSC 2010: 44A35, 35L20, 35J05, 35J25

Exact Solutions of Nonlocal Boundary Value Problems for One- and Two-Dimensional Heat Equation

Иван Хр. Димовски, Юлиан Ц. Цанков - Предложен е метод за намиране на явни решения на клас двумерни уравнения на топлопроводността с нелокални условия по пространствените променливи. Методът е основан на директно тримерно операционно смятане. Класическата дюамелова конволюция е комбинирана с две некласически конволюции за операторите ∂xx и ∂yy в една тримерна конволюция. Съответното операционно смятане използва мултипликаторни частни. Мултипликаторните частни позволяват да се продължи принципът на Дюамел за пространствените променливи и да се намерят явни решения на разглежданите гранични задачи. Общите разглеждания са приложени в случая на гранични условия от типа на Йонкин. Намерени са експлицитни решения в затворен вид.

Polyharmonic Hardy Spaces on the Klein-Dirac Quadric with Application to Polyharmonic Interpolation and Cubature Formulas

2010 Mathematics Subject Classification: Primary 65D30, 32A35, Secondary 41A55.

Analysis of Hue Spectra During Storage of Pepper (Capsicum annuum)

Color information is widely used in non-destructive quality assessment of perishable horticultural produces. The presented work investigated color changes of pepper (Capsicum annuum L.) samples received from retail system. The effect of storage temperature (10±2°C and 24±4°C) on surface color and firmness was analyzed. Hue spectra was calculated using sum of saturations. A ColorLite sph850 (400-700nm) spectrophotometer was used as reference instrument. Dynamic firmness was measured on three locations of the surface: tip cap, middle and shoulder. Significant effects of storage conditions and surface location on both color and firmness were observed. Hue spectra responded sensitively to color development of pepper. Prediction model (PLS) was used to estimate dynamic firmess based on hue spectra. Accuracy was very different depending on the location. Firmness of the tip cap was predicted with the highest accuracy (RMSEP=0.0335). On the other hand, middle region cannot be used for such purpose. Due to the simplicity and rapid processing, analysis of hue spectra is a promising tool for evaluation of color in postharvest and food industry.

Utilização de sismos regionais para a determinação de um modelo 1D de velocidades da onda P na Província Borborema - NE do Brasil

In this work it was performed a study to obtain parameters for an 1D regional velocity model for the Borborema Province, NE Brazil. It was used earthquakes occurred between 2001 and 2013 with magnitude greater than 2.9 mb either from epicentres determined from local seismic networks or by back azimuth determination, when possible. We chose seven events which occurred in the main seismic areas in the Borborema Province. The selected events were recorded in up to 74 seismic stations from the following networks: RSISNE, INCT-ET, João Câmara – RN, São Rafael – RN, Caruaru - PE, São Caetano - PE, Castanhão - CE, Santana do Acarau - CE, Taipu – RN e Sobral – CE, and the RCBR (IRIS/USGS—GSN). For the determination of the model parameters were inverted via a travel-time table and its fit. These model parameters were compared with other known model (global and regional) and have improved the epicentral determination. This final set of parameters model, we called MBB is laterally homogeneous with an upper crust at 11,45 km depth and total crustal thickness of 33,9 km. The P-wave velocity in the upper crust was estimated at 6.0 km/s and 6.64 km/s for it lower part. The P-wave velocity in the upper mantle we estimated at 8.21 km/s with an VP/VS ratio of approximately 1.74.

Utilização de sismos regionais para a determinação de um modelo 1D de velocidades da onda P na Província Borborema - NE do Brasil

In this work it was performed a study to obtain parameters for an 1D regional velocity model for the Borborema Province, NE Brazil. It was used earthquakes occurred between 2001 and 2013 with magnitude greater than 2.9 mb either from epicentres determined from local seismic networks or by back azimuth determination, when possible. We chose seven events which occurred in the main seismic areas in the Borborema Province. The selected events were recorded in up to 74 seismic stations from the following networks: RSISNE, INCT-ET, João Câmara – RN, São Rafael – RN, Caruaru - PE, São Caetano - PE, Castanhão - CE, Santana do Acarau - CE, Taipu – RN e Sobral – CE, and the RCBR (IRIS/USGS—GSN). For the determination of the model parameters were inverted via a travel-time table and its fit. These model parameters were compared with other known model (global and regional) and have improved the epicentral determination. This final set of parameters model, we called MBB is laterally homogeneous with an upper crust at 11,45 km depth and total crustal thickness of 33,9 km. The P-wave velocity in the upper crust was estimated at 6.0 km/s and 6.64 km/s for it lower part. The P-wave velocity in the upper mantle we estimated at 8.21 km/s with an VP/VS ratio of approximately 1.74.

Modelos em provisão de sinistros

Part of the work of an insurance company is to keep claims reserves, which is known as the technical reserves, in order to mitigate the risk inherent in their activities and comply with the legal obligations. There are several methods for estimate the claims reserves, deterministics and stochastics methods. One of the most used method is the deterministic method Chain Ladder, of simple application. However, the deterministics methods produce only point estimates, for which the stochastics methods have become increasingly popular because they are capable of producing interval estimates, measuring the variability inherent in the technical reserves. In this study the deterministics methods (Grossing Up, Link Ratio and Chain Ladder) and stochastics (Thomas Mack and Bootstrap associated with Overdispersed Poisson model) will be applied to estimate the claims reserves derived from automobile material damage occurred until December 2012. The data used in this research is based on a real database provided by AXA Portugal. The comparison of results obtained by different methods is hereby presented.

E-RUN version 1.1: Observational gridded runoff estimates for Europe, link to data in NetCDF format (69 MB)

River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first assemble an unprecedented collection of river flow observations, combining information from three distinct data bases. Observed monthly runoff rates are first tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 12) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950 - December 2015) on a 0.5° x 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring.

E-RUN version 1.0: Observational gridded runoff estimates for Europe, link to data in NetCDF format (68 MB)

River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first collect an unprecedented collection of river flow observations, combining information from three distinct data bases. Observed monthly runoff rates are first tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 11) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950-December 2014) on a 0.5° × 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring.

Modelling the influence of biotic factors on species distribution patterns

Biotic interactions can have large effects on species distributions yet their role in shaping species ranges is seldom explored due to historical difficulties in incorporating biotic factors into models without a priori knowledge on interspecific interactions. Improved SDMs, which account for biotic factors and do not require a priori knowledge on species interactions, are needed to fully understand species distributions. Here, we model the influence of abiotic and biotic factors on species distribution patterns and explore the robustness of distributions under future climate change. We fit hierarchical spatial models using Integrated Nested Laplace Approximation (INLA) for lagomorph species throughout Europe and test the predictive ability of models containing only abiotic factors against models containing abiotic and biotic factors. We account for residual spatial autocorrelation using a conditional autoregressive (CAR) model. Model outputs are used to estimate areas in which abiotic and biotic factors determine species’ ranges. INLA models containing both abiotic and biotic factors had substantially better predictive ability than models containing abiotic factors only, for all but one of the four species. In models containing abiotic and biotic factors, both appeared equally important as determinants of lagomorph ranges, but the influences were spatially heterogeneous. Parts of widespread lagomorph ranges highly influenced by biotic factors will be less robust to future changes in climate, whereas parts of more localised species ranges highly influenced by the environment may be less robust to future climate. SDMs that do not explicitly include biotic factors are potentially misleading and omit a very important source of variation. For the field of species distribution modelling to advance, biotic factors must be taken into account in order to improve the reliability of predicting species distribution patterns both presently and under future climate change.

A quality control program for mutation detection in KIT and PDGFRA in gastrointestinal stromal tumours.

BACKGROUND: Although most gastrointestinal stromal tumours (GIST) carry oncogenic mutations in KIT exons 9, 11, 13 and 17, or in platelet-derived growth factor receptor alpha (PDGFRA) exons 12, 14 and 18, around 10% of GIST are free of these mutations. Genotyping and accurate detection of KIT/PDGFRA mutations in GIST are becoming increasingly useful for clinicians in the management of the disease. METHOD: To evaluate and improve laboratory practice in GIST mutation detection, we developed a mutational screening quality control program. Eleven laboratories were enrolled in this program and 50 DNA samples were analysed, each of them by four different laboratories, giving 200 mutational reports. RESULTS: In total, eight mutations were not detected by at least one laboratory. One false positive result was reported in one sample. Thus, the mean global rate of error with clinical implication based on 200 reports was 4.5%. Concerning specific polymorphisms detection, the rate varied from 0 to 100%, depending on the laboratory. The way mutations were reported was very heterogeneous, and some errors were detected. CONCLUSION: This study demonstrated that such a program was necessary for laboratories to improve the quality of the analysis, because an error rate of 4.5% may have clinical consequences for the patient.

Joint Information and Jamming Beamforming for Secrecy Rate Maximization in Cognitive Radio Networks

In this paper, we consider the secure beamforming design for an underlay cognitive radio multiple-input singleoutput broadcast channel in the presence of multiple passive eavesdroppers. Our goal is to design a jamming noise (JN) transmit strategy to maximize the secrecy rate of the secondary system. By utilizing the zero-forcing method to eliminate the interference caused by JN to the secondary user, we study the joint optimization of the information and JN beamforming for secrecy rate maximization of the secondary system while satisfying all the interference power constraints at the primary users, as well as the per-antenna power constraint at the secondary transmitter. For an optimal beamforming design, the original problem is a nonconvex program, which can be reformulated as a convex program by applying the rank relaxation method. To this end, we prove that the rank relaxation is tight and propose a barrier interior-point method to solve the resulting saddle point problem based on a duality result. To find the global optimal solution, we transform the considered problem into an unconstrained optimization problem. We then employ Broyden-Fletcher-Goldfarb-Shanno (BFGS) method to solve the resulting unconstrained problem which helps reduce the complexity significantly, compared to conventional methods. Simulation results show the fast convergence of the proposed algorithm and substantial performance improvements over existing approaches.

Real-time depth camera tracking with CAD models and ICP

In recent years, depth cameras have been widely utilized in camera tracking for augmented and mixed reality. Many of the studies focus on the methods that generate the reference model simultaneously with the tracking and allow operation in unprepared environments. However, methods that rely on predefined CAD models have their advantages. In such methods, the measurement errors are not accumulated to the model, they are tolerant to inaccurate initialization, and the tracking is always performed directly in reference model's coordinate system. In this paper, we present a method for tracking a depth camera with existing CAD models and the Iterative Closest Point (ICP) algorithm. In our approach, we render the CAD model using the latest pose estimate and construct a point cloud from the corresponding depth map. We construct another point cloud from currently captured depth frame, and find the incremental change in the camera pose by aligning the point clouds. We utilize a GPGPU-based implementation of the ICP which efficiently uses all the depth data in the process. The method runs in real-time, it is robust for outliers, and it does not require any preprocessing of the CAD models. We evaluated the approach using the Kinect depth sensor, and compared the results to a 2D edge-based method, to a depth-based SLAM method, and to the ground truth. The results show that the approach is more stable compared to the edge-based method and it suffers less from drift compared to the depth-based SLAM.

Likelihood-Based Inference for Partially Observed Multi-Type Markov Branching Processes

Thesis (Ph.D.)--University of Washington, 2016-08