Highly symmetric [formula omitted]-refinement Bi-frames for surface multiresolution processing

Multiresolution data representations provide an indispensable tool for the compression, progressive transmission, and visualization of scientific data. Wavelet transforms based on B-spline scaling functions are frequently used to obtain continuous surface- and volume representations at multiple levels of resolution. Starting with a fine-resolution data set, wavelet decomposition provides a sequence of coarser approximations based on B-spline scaling functions and a set of wavelet coefficients containing the geometric differences with respect to the finer levels. The inverse transform can be used to reconstruct the finer levels of resolution from these wavelet coefficients within linear computation time. Biorthogonal wavelet transforms facilitate local computation of decomposition and reconstruction. We survey the most relevant results regarding wavelets and present different biorthogonal wavelet constructions based on highly efficient and simple-to-use lifting operations. Our approaches are suitable for lossy and lossless compression of large-scale data sets.

A scalable coding scheme for three dimensional irregular meshes is proposed in this paper. Multiresolution analysis of the original triangular mesh is obtained using wavelet decomposition. A bit plane coding architecture is then performed using intra-band dependencies between wavelet coefficients. A progressive bitstream hierarchy is created making it possible to progressively reconstruct the mesh at each resolution or quality level. Experimental assessments show that the proposed codec outperforms the state-of-the-art interband mesh coding for arbitrary triangular meshes. In addition, it maintains the ability to reconstruct progressively each intermediate mesh at any resolution level.

Pt-based fuel cell catalysts with excellent activity and stability for proton-exchange membrane fuel cells (PEMFCs) have been developed through strain regulation in recent years. Herein, this work demonstrates that symmetry-induced strain regulation of Pt surface of PtGa intermetallic compounds can greatly enhance the catalytic performance of the oxygen reduction reaction (ORR). With the strain environment varies derived from the lattice mismatch of analogous PtGa core but different symmetry, the Pt surface of the PtGa alloy and the Pt3 Ga (Pm m) precisely realize 0.58% and 2.7% compressive strain compared to the Pt3 Ga (P4/mmm). Experimental and theoretical results reveal that when the compressive stress of the Pt lattice increases, the desorption process of O* intermediates becomes accelerated, which is conducive to oxygen reduction. The Pt3 Ga (Pm m) with high symmetry and compressive Pt surface exhibit the highest mass and specific activities of 2.18 A mgPt -1 and 5.36 mA cm-2 , respectively, which are more than one order of magnitude higher than those of commercial Pt/C catalysts. This work demonstrates that material symmetry can be used to precisely modulate Pt surface stress to enhance the ORR, as well as provide a distinct platform to investigate the relationship between Pt compressibility and catalytic activity.

When globally optimal designs are important and required sensitivity analysis is complicated, genetic algorithms can be effective alternatives to gradient-based optimization methods. Genetic algorithms are being used more widely in various engineering fields. However, when the design variables become large, standard genetic algorithms become difficult to use because of excessive computation time needed to obtain converged solutions. In this investigation, we consider two-dimensional structural topology optimizations based on finite element models as a large-size optimization problem. To expedite the solution convergence by orders of magnitude, the genetic algorithm in the multiscale multiresolution setting is proposed. By the multiscale setting, standard single-scale binary design variables are represented in multiple scales by the so-called Binary Wavelet Transform. Note that all genetic operators such as crossover and mutation must be redefined or modified for multiscaled design variables. A key advantage of using multiscale design variables is that the exploration of solution becomes more effective with them. If the multiresolution setting based on the multiscale variables is used, the design optimization can proceed from low to high resolution over several resolution stages where the information passing over resolutions is very effective. In this multiresolution approach, a converged population at a certain resolution level is reused as a part of the initial population at the next higher resolution level. In fact, we form the initial population in three groups: the converged population in the previous resolution, a randomly generated population and the mixture of the converged population and the random population. The detailed technique to generate the three groups is presented, which is an important part of the developed multiscale multiresolution genetic algorithm. The convergence improvement by the multiscale multiresolution approach was verified numerically with several numerical case studies.

Abstract. Past studies on soil moisture spatial variability have been mainly conducted at catchment scales where soil moisture is often sampled over a short time period; as a result, the observed soil moisture often exhibited smaller dynamic ranges, which prevented the complete revelation of soil moisture spatial variability as a function of mean soil moisture. In this study, spatial statistics (mean, spatial variability and skewness) of in situ soil moisture, modeled and satellite-retrieved soil moisture obtained in a warm season (198 days) were examined over three large climate regions in the US. The study found that spatial moments of in situ measurements strongly depend on climates, with distinct mean, spatial variability and skewness observed in each climate zone. In addition, an upward convex shape, which was revealed in several smaller scale studies, was observed for the relationship between spatial variability of in situ soil moisture and its spatial mean when statistics from dry, intermediate, and wet climates were combined. This upward convex shape was vaguely or partially observable in modeled and satellite-retrieved soil moisture estimates due to their smaller dynamic ranges. Despite different environmental controls on large-scale soil moisture spatial variability, the correlation between spatial variability and mean soil moisture remained similar to that observed at small scales, which is attributed to the boundedness of soil moisture. From the smaller support (effective area or volume represented by a measurement or estimate) to larger ones, soil moisture spatial variability decreased in each climate region. The scale dependency of spatial variability all followed the power law, but data with large supports showed stronger scale dependency than those with smaller supports. The scale dependency of soil moisture variability also varied with climates, which may be linked to the scale dependency of precipitation spatial variability. Influences of environmental controls on soil moisture spatial variability at large scales are discussed. The results of this study should be useful for diagnosing large scale soil moisture estimates and for improving the estimation of land surface processes.

Nanoscience promises to transform today's world in the same way that integrated semiconductor devices transformed the world of electronics and computation. In the post-genomic era, the greatest challenge is to make connections between the structures and functions of biomolecules at the nanometre-scale level in order to underpin the understanding of larger scale systems in the fields of human biology and physiology. To achieve this, instruments with new capabilities need to be researched and developed, with particular emphasis on new levels of sensitivity, precision and resolution for biomolecular analysis. This paper describes an instrument able to analyse structures that range from tenths of a nanometre (proteins, DNA) to micron-scale structures (living cells), which can be investigated non-destructively in their normal state and subsequently in chemical- or biochemical-modified conditions. The high-resolution scanning Kelvin nanoprobe (SKN) measures the work-function changes at molecular level, instigated by local charge reconfiguration due to translational motion of mobile charges, dipolar relaxation of bound charges, interfacial polarization and structural and conformational modifications. In addition to detecting surface electrical properties, the instrument offers, in parallel, the surface topographic image, with nanometre resolution. The instrument can also be used to investigate subtle work function/topography variations which occur in, for example, corrosion, contamination, adsorption and desorption of molecules, crystallographic studies, mechanical stress studies, surface photovoltaic studies, material science, biocompatibility studies, microelectronic characterization in semiconductor technology, oxide and thin films, surface processing and treatments, surfaces and interfaces characterization. This paper presents the design and development of the instrument, the basic principles of the method and the challenges involved to achieve nanometric resolution and sub-millivolt sensitivity, for both the topographic imaging of surface micromorphology and surface potential and work-function determination.

An issue-oriented framework for Marine Spatial Planning—A case study of Koh Lan, Thailand

The present paper is concerned with the study of parallel approaches for the relaxation algorithms associated to Markov Random Fields (MRF) models in image analysis, [2]. MRF-based relaxation algorithms are known to be intrinsically parallel and massive parallelizations by updating at once independent variables of the field have been early described, [4]. We present here a different approach based on relaxation algorithms running in parallel at different and interacting periodically. The proposed approach is based on parallel Markov chains which have been studied by Aarts et al., [l], and Graffigne, [3], for global optimization using simulated annealing. In our method, parallel Markov chains are coupled with a new multiscale exploration of the configuration space for MRF. This multiscale exploration can be implemented efficiently by considering a sequence of multiresolution MRF models whose parameters and neighborhood structures are obtained from the original MRF model. The designed algorithm is suited for MIMD computers and can be outlined as follows. First MRF models at different scales are computed from the original MRF model. The relaxations at different scales are stochastic and cooperative : every p iterations - one iteration corresponding to a full sweep on the image - a processor attempts to transfer local estimates to the processor controlling the next finer scale. With the low resolution levels of the hierarchy are associated high temperatures in the stochastic relaxation, [3]. A high temperature allows to escape from local minima of the energy function. With the intermediate resolution levels are associated lower temperatures. At these levels, the relaxation process becomes more sensitive to local minima and visits the large or medium size valleys of the energy landscape. At the finest resolution level deterministic relaxation is adopted : the estimation is ultimately refined at that level. The proposed parallelization approach is compared to sequential deterministic and stochastic relaxation in the context of optical flow estimation. The multiscale algorithm exhibits fast convergence properties, comparable to multigrid deterministic relaxation, and the obtained estimates are close to the near optimal solutions obtained by time consuming sequential stochastic methods.

Seismic data are routinely used to infer in situ properties of earth materials on many scales, ranging from global studies to investigations of surficial geological formations. While inversion and imaging algorithms utilizing these data have improved steadily, there are remaining challenges that make detailed measurements of the properties of some geologic materials very difficult. For example, the determination of the concentration and orientation of fracture systems is prohibitively expensive to simulate on the fine grid and, thus, some type of coarse-grid simulations are needed. In this paper, we describe a new multiscale finite element algorithm for simulating seismic wave propagation in heterogeneous media. This method solves the wave equation on a coarse grid using multiscale basis functions and a global coupling mechanism to relate information between fine and coarse grids. Using a mixed formulation of the wave equation and staggered discontinuous basis functions, the proposed multiscale methods have the following properties. • The total wave energy is conserved. • Mass matrix is diagonal on a coarse grid and explicit energy-preserving time discretization does not require solving a linear system at each time step. • Multiscale basis functions can accurately capture the subgrid variations of the solution and the time stepping is performed on a coarse grid. We discuss various subgrid capturing mechanisms and present some preliminary numerical results.

We consider the impact of using time-lapse seismic data in addition to production data for permeability estimation in a porous medium with multiphase fluid flows, such as a petroleum reservoir under water-assisted production. Since modeling seismic wave propagation in addition to modeling fluid flows in the reservoir is quite involved, it is assumed that the time-lapse seismic data have already been inverted into fluid saturation differences (pseudoseismic data). Because an inversion process often leads to considerable error growth, we will consider pseudoseismic data with large uncertainties. The impact of pseudoseismic data is assessed through permeability estimation with and without such data and through application of some uncertainty measures for the estimated parameters. A multiscale algorithm is used for the parameter estimations, so that potential differences in attainable permeability resolution will be easily revealed. The numerical examples clearly indicate that the permeability estimation problem is stabilized at a higher level of resolution when pseudoseismic data are applied in addition to production data, even if the pseudoseismic data have large associated uncertainties. Use of the parameter uncertainty measures confirm these results.

Aim. Based on the proposed methods, to improve the quality of surgical treatment of patients with diabetic foot syndrome by improving the method of surgical treatment of the stump and fixation of the skin after phalangeal amputation. Materials and Methods. The analysis of the results of treatment of 114 patients treated in the surgical department of the TL of Ternopil during 2014-18 years for purulent-necrotic lesions of toes in type II diabetes mellitus was carried out. The age of patients ranged from 44 to 75 years. The following methods are supported by patents for utility model. Results and Discussion. Usually, during small amputations, the necrotic part of the bone phalanx of the finger is removed with the help of Liuer or Liston cutters. The indicated methods have certain disadvantages, as they cause additional traumatization of healthy tissue within which amputation is carried out. Removing necrotic tissue with manual mechanical amputation tools requires the application of force and compression, which leaves microcracks and splinters at the immediate location of the instrument on the healthy residual bone tissue and also injures the surrounding tissue, adversely affecting the wound healing process and treatment as a whole. However, the fixation of the skin after the amputation of the phalanx of the finger is preceded by the removal of the necrotic part of the phalanx or the entire phalanx, the cleansing of the open wound surface of fine particles of destructive tissue, treatment of the wound with an antiseptic on a water basis (chlorhexidine, decasan), removal of liquid tissues, blood, lymph and amorphous component, wound tamponade, or seam fixation. The methods of surgical treatment of the foot and the fixation of the skin flap proposed by us improve the existing other methods, where the execution of amputation of the dead part of the phalanx of the finger or even the heads of the metatarsals is carried out using a cut-off metal disk rotating at a speed of 20,000 rpm (revolutions per minute), followed by gradual polishing of the cutoff point of healthy bone tissue. The fixation of the skin flap is carried out by seamless method after preliminary treatment with certain aqueous solutions of antiseptics and an even distribution of the amorphous component, which is formed as a result of mechanical treatment of the stump with a corundum grinding nozzle up to 10 mm in diameter in the form of a layer for 1-2 minutes at a speed of 10,000 rpm.  Conclusion. The proposed method of amputation of the phalanx of the finger is characterized by rapid and qualitative cut off of the dead part of the phalanx, absence of additional traumatization of the stump of the bone and surrounding tissues. The method of fixing the skin flap after the amputation of the phalanx of the finger allows preserving the liquid tissues on the wound surface that provide nutrition and fixation of the transplanted skin flap closing the wound. This approach to treatment of purulent-necrotic wounds in patients with diabetic foot syndrome provides significant acceleration of wound healing, reduces the risk of implantation infection, eliminates additional tissue injuries during overlaying and sewing, and, accordingly, reduces the patient's stay in hospital treatment to 5 to10  days.

This paper presents a new interpolatory Loop scheme and an unified and mixed interpolatory and approximation subdivision scheme for triangular meshes. The former which is C1 continuous as same as the modified Butterfly scheme has better effect in some complex models. The latter can be used to solve the “popping effect” problem when switching between meshes at different levels of resolution. The scheme generates surfaces coincident with the Loop subdivision scheme in the limit condition having the coefficient k equal 0. When k equal 1, it will be changed into a new interpolatory subdivision scheme. Eigen‐structure analysis demonstrates that subdivision surfaces generated using the new scheme are C1 continuous. All these are achieved only by changing the value of a parameter k. The method is a completely simple one without constructing and solving equations. It can achieve local interpolation and solve the “popping effect” problem which are the method's advantages over the modified Butterfly scheme.

Compression of 3D triangular meshes with progressive precision

Abstract: In this work, we develop a hydrological model designed to simulate the water balance and runoff processes at the catchment-scale. Instead of using a rectangular grid discretization, the model represents the catchment using a non-homogeneous two-dimensional triangular mesh framework (similar to a triangular mesh in the Finite Element method). This discretization fits a more flexible representation of complex topography and land boundaries. The model is implemented in the Fortran programming language. It depends on the Digital Elevation Model (DEM) to extract the flow pathways starting from upstream and reaching downstream. That guarantees a physically consistent and explicit flow-routing structure across the triangular mesh.Evapotranspiration is calculated using the Penman–Monteith equation, as the parameters are considered to suit coastal climate conditions. The model utilizes temperature, solar radiation, wind speed, and vapor pressure as atmospheric inputs. The SCS Curve Number method is used to estimate the surface runoff, considering slope, land cover, and soil properties. Meteorological data measurements, including precipitation, temperature, humidity, as well as inflow and outflow discharges, are integrated into the simulations.Due to its efficient numerical structure, the model supports simulations with numerous spatial elements and long time series while maintaining the computational cost at its lowest limits. This makes it well-suited for large-scale watershed applications and provides a strong basis for future high-performance computing developments. Keywords: hydrological modeling, watershed triangulation, flow routing, numerical simulation

Electric vehicles (EVs) have a fast expanding market share due to their reduced carbon footprint and dependence on fossil fuels. The development of EVs is directly impacted by the slow battery technology progress. Present battery technology has a poor energy density, and with limited battery capacity, buyers are anxious that their electric vehicles would fail on the road. Charge-on-the-move (CoM) or Dynamic wireless power transfer (DWPT) technique provides a convenient solution for the battery issue. A DWPT strategy requires changes in infrastructure, which can be very expensive. This article also discusses vehicle-to-vehicle electric charging, which may address EV charging concerns without requiring a drastic change in the infrastructure.