Molecular Structure of Nickel Octamethylporphyrin—Rare Experimental Evidence of a Ruffling Effect in Gas Phase

The structure of a free nickel (II) octamethylporphyrin (NiOMP) molecule was determined for the first time through a combined gas-phase electron diffraction (GED) and mass spectrometry (MS) experiment, as well as through quantum chemical (QC) calculations. Density functional theory (DFT) calculations do not provide an unambiguous answer about the planarity or non-planar distortion of the NiOMP skeleton. The GED refinement in such cases is non-trivial. Several approaches to the inverse problem solution were used. The obtained results allow us to argue that the ruffling effect is manifested in the NiOMP molecule. The minimal critical distance between the central atom of the metal and nitrogen atoms of the coordination cavity that provokes ruffling distortion in metal porphyrins is about 1.96 Å.

Solving the Inverse Problem of Recovering the 3D Surface of a Detail According to its 2D Projections in the Modelling of Electroplating Processes

The article considers the influence of the surface geometry of a detail on the deposition of coating thickness in the simulation of electroplating processes. The methods for obtaining sets of points describing the surface of a detail are analyzed. Solving the inverse problem (recovering the 3D surface of a detail according to its 2D drawings) is the most promising method. The inverse problem solution is decomposed into simpler geometric problems: input data processing; obtaining primitives; obtaining the desired surface of a detail by applying logical operations to primitives. Mathematical statements are formulated and solution algorithms are proposed for solving these problems. The inverse problem solution is implemented through software. The distribution of the nickel coating thickness is shown for a detail, the surface of which is obtained by solving the inverse problem.

Derivation of Heat Conductivity from Temperature and Heat Flux Measurements in Soil

The general inverse problem formulation for a heat conductance equation is adopted for the types of measurement routinely carried out in the soil active layer. The problem solution delivers a constant thermal diffusivity coefficient a0 (in general, different from true value a) and respective heat conductivity λ0 for the layer, located between two temperature sensors and equipped with a temperature or heat flux sensor in the middle. We estimated the error of solution corresponding to systematic shifts in sensor readings and mislocation of sensors in the soil column. This estimation was carried out by a series of numerical experiments using boundary conditions from observations on Mukhrino wetland (Western Siberia, Russia), performed in summer, 2019. Numerical results were corroborated by analytical estimates of inverse problem solution sensitivity derived from classical Fourier law. The main finding states that heat conductivity error due to systematic shifts in temperature measurements become negligible when using long temperature series, whereas the relative error of a is approximately twice the relative error of sensor depth. The error a0−a induced by heat flux plate displacement from expected depth is 3–5 times less than the same displacement of thermometers, which makes the requirements for heat flux installation less rigid. However, the relative errors of heat flux observation typical for modern sensors (±15%) cause the uncertainty of a above 15% in absolute value. Comparison of the inverse problem solution to a estimated from in situ moss sampling on Mukhrino wetland proves the feasibility of the method and corroborates the conclusions of the error sensitivity study.

STUDY OF UNCERTAINTY OF THE INVERSION OF DISPERSION CURVES OF SURFACE WAVES USING ARTIFICIAL NEURAL NETWORKS

The results of using an adapted sampling algorithm by the Monte Carlo method to estimate the ambiguity domain of the inversion of synthetic dispersion curves of the phase velocities of surface waves using artificial neural networks are discussed in the paper. The expediency of using the considered algorithm for calculating a probabilistic estimate of the results of the inverse problem solution in the method of multichannel analysis of surface waves has been confirmed.

Photon Phase Shift Imaging Research on Frequency Domain Diffuse Optic Tomography

Diffuse optic imaging is an important biomedical optic research tool. Diffuse optic tomography (DOT) modality needs progressive philosophical approaches for scientific contribution. Technological developments and philosophical approaches should both go forward. Phase-shift based frequency domain (FD) diffuse optical tomography (FDDOT) method was well established in the literature. The instruments were tested for brain neurofunctional imaging. A mixture of AC laser intensity and phase data were used at these works. According to those works; deep volume resolution was improved by only using phase data. Because phase data is only related to the photon mean free path in imaging tissue media. Besides this advantage, laser intensity data is also affected by noisy background light and electrical artifacts. Another most important advantage of only using phase data can be explained as time-resolved temporal change can be directly related to phase shift of modulated frequency source. At this work, the frequency domain (FD) DOT imaging method which uses phase shift data were used for simulation phantom. Laser source-driven forward model problem weight matrix simulation data was given to the simple pseudo-inverse-based inverse problem solution algorithm for one inclusion example. The inclusion image was reconstructed and demonstrated successfully. Forward model problem weight functions inside the tissue simulation media were calculated and used based on the phase shifts at the same core modulation frequency. 100 MHz modulation frequency was selected due to its FDDOT standard. 13 sources and 13 detectors were placed on the back-reflected imaging surface. 40 x, y, z cartesian coordinate grid elements were used in the image reconstruction algorithm. Photon absorption coefficient: ma = 0.1 cm-1, and scattering coefficient: ms = 100 cm-1 values were set for background simulation phantom. One inclusion object was embedded inside the imaging tissue simulation phantom background. x, y, z cartesian coordinate grid sizes were selected for 100 mm for each direction. Photon phase shift fluencies were added to the forward model problem. The forward model problem was built according to the frequency domain photon migration diffusion approximation. Forward model problem photon fluencies were calculated according to the diffusion equation approximation. The simple pseudoinverse mathematical inverse problem solution algorithm was applied to test the results. The embedded inclusion object was reconstructed successfully with the high-resolution image quality. In general, DOT techniques suffer for the low image quality, but in this work, the high-quality image was reconstructed and demonstrated. The philosophical approach has future promising DOT imaging capability. The phase shift version of the FDDOT modality has an important advantage for future purpose.

Possibilities for separation of scalar and vector characteristics of acoustic scatterer in tomographic polychromatic regime

The inverse wave problem of tomographic type is considered. It consists in reconstruction of several scatterer’s characteristics in the form of spatial distributions for sound speed, medium density, absorption coefficient and power index of its frequency dependence, as well as vector of flow velocity. In the form of a survey material (based on several publications), a sequence of steps is discussed that leads to reconstruction of each individual spatial distribution in the presence of different combinations of the mentioned characteristics. The minimum number of frequencies required for reconstruction is discussed when the complete set of scattering data is available at each of the frequencies. For the first time, two possible approaches to reconstruct the scatterer characteristics in the presence of inhomogeneous spatial distributions of the density and the flow velocity vector are compared, and attention is drawn to the perspectives of reconstruction by functional algorithms in this case. The possibility of separating the sought spatial distributions during the inverse problem solution is illustrated by numerical modeling.