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In this paper, we analyze a mixture of Lognormal and Log-Logistic distribution. We estimate the parameters of the introduced distribution by using the expectation-maximization (EM) algorithm. Various phenomena in the field of medicine and economy could be modeled by this mixture. In this paper, it is used to construct new mortality model for determining the unisex premium rates in life insurance. The application of the model is illustrated in the case of Serbian population and its advantages are presented in the context of life insurance premium calculation.

Due to the increased use of yttrium in agriculture and industry, there is a growing interest in the impact of yttrium on the environment and human health. Developing novel procedures to detect and quantify species of yttrium represents an important task. In this work, we apply laser desorption/ionization-mass spectrometry (LDI-MS) to detect cluster ions of the solution of yttrium(III) chloride (YCl3) at different pH values. The density functional theory (DFT) calculations were used to reveal the energetically most favored structures of the anions and cations chosen from the LDI-MS results. Examination of the positive and negative mode LDI mass spectra of YCl3 showed the presence of the heterogeneous mononuclear and polynuclear clusters, such as [YCl(OH) (H2O)3][Formula: see text], [Y2(H2O)][Formula: see text], [Y4H2(H2O)4][Formula: see text], and [Y5O4H3][Formula: see text] (at pH 2 and 5) and [Y2Cl2(H2O)2][Formula: see text], [Y2O5(HCl)(OH)][Formula: see text], and [Y3OH3(OH)2(H2O)][Formula: see text] (at pH 2, 5, and 10). The variation in the pH solution of YCl3 slightly affects the LDI mass spectrum of these yttrium clusters. It has only been noticed that the [Y4H2(H2O)4][Formula: see text] cluster ions were not detected at pH 10. These results can become a guide in the detection of yttrium chloride by LDI-MS in real samples in different fields (ecological, food, and human).

Advanced research frontiers are extended from biophysics relations on the Earth upto the discovering any type of alive matter within the whole space. Microorganisms’ motion within the molecular biology processes integrates variety of microorgnisms functions. In continuation of our Brownian motion phenomena research, we consistently build molecular-microorganisms structures hierarchy. We recognize everywhere biomimetic similarities between the particles in alive and nonalive matter. The research data are based on real experiments, without external energy impulses. So, we develop the analysis, inspired by fractal nature Brownian motion, as recognized joint parameter between particles in alive and nonalive biophysical systems. This is also in line with advance trends in hybrid submicroelectronic integrations. The important innovation in this paper is that we introduced approximation of trajectory and error calculations, using discrete mean square approximation, what cumulatively provide much more precise biophysical systems parameters. By this paper, we continue to generate new knowledge in direction to get complex relations between the particles clusters in biophysical systems condensed matter.

The electronic packaging and systems are very important topics as the limitation of miniaturization approaches in semiconductor industry. Regarding the optimal materials microstructure for these applications, we studied different alloys such as Sn-3.0Ag-0.5Cu (wt.%)/organic solderability preservative (SAC305/OSP) Cu and SAC305–0.05Ni/OSP Cu solder joints. We implemented the fractal dimension characterization and microstructure morphology reconstruction. This is the first time that we applied fractals on such alloys. The morphology reconstruction is important for predicting and designing the optimal microstructure for the advanced desirable properties these alloys. These analyzed parameters are important for the hand-held devices and systems especially for the exploitation. The fractal reconstruction was applied on the prepared microstructures with five different magnifications. The results confirmed successful application of fractals in this area of materials science considering the grains and shapes reconstructions.

Biophysical and condensed matter systems connection is of great importance nowadays due to the need for a new approach in microelectronic biodevices, biocomputers or biochips advanced development. Considering that the living and nonliving systems’ submicroparticles are identical, we can establish the biunivocally correspondent relation between these two particle systems, as a biomimetic correlation based on Brownian motion fractal nature similarities, as the integrative property. In our research, we used the experimental results of bacterial motion under the influence of energetic impulses, like music, and also some biomolecule motion data. Our goal is to define the relation between biophysical and physical particle systems, by introducing mathematical analytical forms and applying Brownian motion fractal nature characterization and fractal interpolation. This work is an advanced research in the field of new solutions for high-level microelectronic integrations, which include submicrobiosystems like part of even organic microelectronic considerations, together with some physical systems of particles in solid-state solutions as a nonorganic part. Our research is based on Brownian motion minimal joint properties within the integrated biophysical systems in the wholeness of nature.

The materials’ consolidation, especially ceramics, is very important in advanced research development and industrial technologies. Science of sintering with all incoming novelties is the base of all these processes. A very important question in all of this is how to get the more precise structure parameters within the morphology of different ceramic materials. In that sense, the advanced procedure in collecting precise data in submicro-processes is also in direction of advanced miniaturization. Our research, based on different electrophysical parameters, like relative capacitance, breakdown voltage, and [Formula: see text], has been used in neural networks and graph theory successful applications. We extended furthermore our neural network back propagation (BP) on sintering parameters’ data. Prognosed mapping we can succeed if we use the coefficients, implemented by the training procedure. In this paper, we continue to apply the novelty from the previous research, where the error is calculated as a difference between the designed and actual network output. So, the weight coefficients contribute in error generation. We used the experimental data of sintered materials’ density, measured and calculated in the bulk, and developed possibility to calculate the materials’ density inside of consolidated structures. The BP procedure here is like a tool to come down between the layers, with much more precise materials’ density, in the points on morphology, which are interesting for different microstructure developments and applications. We practically replaced the errors’ network by density values, from ceramic consolidation. Our neural networks’ application novelty is successfully applied within the experimental ceramic material density [Formula: see text] [kg/m3], confirming the direction way to implement this procedure in other density cases. There are many different mathematical tools or tools from the field of artificial intelligence that can be used in such or similar applications. We choose to use artificial neural networks because of their simplicity and their self-improvement process, through BP error control. All of this contributes to the great improvement in the whole research and science of sintering technology, which is important for collecting more efficient and faster results.

The dielectric properties of Neodymium zinc titanium oxide (NZT) and Neodymium magnesium titanium oxide (NMT) were investigated. The single-phase ceramic was synthesized at various temperatures below 1650[Formula: see text]C. The result shows that the value of temperature of resonant frequency [Formula: see text] for NMT is higher than NZT. Our findings also indicate that the rare earth materials produce high property dielectric materials, despite the fact some elements produce lower negative value of temperature of resonant frequency [Formula: see text]. By doping a compound such as CaTiO3 which has a very positive temperature of resonant frequency ([Formula: see text] ppm/[Formula: see text]C) and a very high relative permittivity [Formula: see text], it is possible to tune NZT and MNT to achieve an excellent dielectric material. This work is under consideration. The results of this scientific research could be very important for modern advance applications in microelectronic miniaturization.

The goal of our research is to establish the direction of coronavirus chaotic motion to control corona dynamic by fractal nature analysis. These microorganisms attaching the different cells and organs in the human body getting very dangerous because we don’t have corona antivirus prevention and protection but also the unpredictable these viruses motion directions what resulting in very important distractions. Our idea is to develop the method and procedure to control the virus motion direction with the intention to prognose on which cells and organs could attach. We combined very rear coronavirus motion sub-microstructures images from worldwide experimental microstructure analysis. The problem of the recording this motion is from one point of view magnification, but the other side in resolution, because the virus size is minimum 10 times less than bacterizes. But all these images have been good data to resolve by time interval method and fractals, the points on the motion trajectory. We successfully defined the diagrams on the way to establish control over Brownian chaotic motion as a bridge between chaotic disorder to control disorder. This opens a very new perspective to future research to get complete control of coronavirus cases.