Spatial Density Distribution Research Articles

Control of spatio-temporal patterning via cell growth in a multicellular synthetic gene circuit

A major goal in synthetic development is to build gene regulatory circuits that control patterning. In natural development, an interplay between mechanical and chemical communication shapes the dynamics of multicellular gene regulatory circuits. For synthetic circuits, how non-genetic properties of the growth environment impact circuit behavior remains poorly explored. Here, we first describe an occurrence of mechano-chemical coupling in synthetic Notch (synNotch) patterning circuits: high cell density decreases synNotch-gated gene expression in different cellular systems in vitro. We then construct, both in vitro and in silico, a synNotch-based signal propagation circuit whose outcome can be regulated by cell density. Spatial and temporal patterning outcomes of this circuit can be predicted and controlled via modulation of cell proliferation, initial cell density, and/or spatial distribution of cell density. Our work demonstrates that synthetic patterning circuit outcome can be controlled via cellular growth, providing a means for programming multicellular circuit patterning outcomes.

Non-uniform electron density estimation based on electromagnetic wave attenuation in plasma

Abstract The surface of a high-speed vehicle reentering the atmosphere is surrounded by plasma sheath. Due to the influence of the inhomogeneous flow field around the vehicle, understanding the electromagnetic properties of the plasma sheath can be challenging. Obtaining the electron density of the plasma sheath is crucial for understanding and achieving plasma stealth of vehicles. In this work, the relationship between electromagnetic wave attenuation and electron density is deduced theoretically. The attenuation distribution along the propagation path is found to be proportional to the integral of the plasma electron density. This result is used to predict the electron density profile. Furthermore, the average electron density is obtained using a back-propagation neural network algorithm. Finally, the spatial distribution of the electron density can be determined from the average electron density and the normalized derivative of attenuation with respect to the propagation depth. Compared to traditional probe measurement methods, the proposed approach not only improves efficiency but also preserves the integrity of the plasma environment.

Nanoscale mapping of local intrinsic strain-induced anomalous bandgap variations in WSe2 using selective-wavelength scanning photoconductivity microscopy

Nanoscale defects can locally tailor the optoelectronic properties of two-dimensional materials such as bandgap. However, it is still challenging to directly map and analyze the defect-induced bandgap variations in a quantitative manner. Here, we report the nanoscale mapping of local intrinsic strain-induced anomalous bandgap variations in as-grown WSe2 by using a selective-wavelength scanning photoconductivity microscopy. In this method, a conducting nanoprobe is utilized to map the spatial distributions of strain, sheet-conductance, and charge trap density (Neff) of epitaxially-grown WSe2 on sapphire while illuminating monochromatic light of selective wavelengths. Under un-illuminated conditions, the maps showed WSe2 domain structures with boundaries having slightly lower sheet-conductance and higher Neff than those in domains, presumably due to low misorientation angles between adjacent epitaxially-grown domains. By measuring wavelength-dependent photoconductance maps and fitting each pixel value of the maps, we could successfully obtain the map of local bandgap. The map clearly showed bandgap variations inside domains as well as rather low bandgaps at boundaries. By comparing with local strain map, we found that tensile strain effectively reduced bandgap following two different power-law relationships. Such anomalous bandgap variations in WSe2 could be explained by strain-induced weakening of d-orbital couplings. Furthermore, in a monolayer-bilayer WSe2 interface, bilayer WSe2 exhibited lower bandgap than the underlying monolayer WSe2, while interfacial boundaries exhibited the strain-induced bandgap values in between those of monolayer and bilayer WSe2. Since our method allows us to directly map the intrinsic strain-induced bandgap variations with a nanoscale resolution down to tens-of-nm, it can be a powerful tool for basic research and practical applications of optoelectronic devices based on two-dimensional materials.

Dynamic evolution analysis and parameter optimization design of data-driven network infectious disease model

Background and Objective:globalization and population mobility have increased the spread of infectious diseases and challenged public health security. This paper proposes a complex network epidemic model with nonlinear incidence rate and quadratic transmission. The Turing pattern, sensitivity analysis and parameter identification of the epidemic model under different network structures are studied; Methods:this paper discusses the Turing pattern of the model under different network structures, and identifies the key parameters of the model through sensitivity analysis. The influence of network dimension on the spread of infectious diseases on random networks is also explored, and the problems of minimum path and minimum cover set of random networks are further discussed. We also carry out parameter identification experiments, adopt gradient descent algorithm to realize heterogeneous spatial fitting pattern of red blood cell plasma and simulate the transmission path of COVID-19 through Markov chain Monte Carlo fitting experiment, verifying the effectiveness of the model; Results:the necessary conditions for Turing instability on homogeneous and heterogeneous networks are found. On the heterogeneous lattice network, we observe the special patterns of equal density population. Sensitivity analysis shows that the higher the infection rate, the more infected people. On random networks, the higher the dimension, the better the effect of suppressing the spread of infectious diseases. Through comparison experiment, it is found that gradient descent algorithm has the best performance in parameter identification experiments. Red blood cell plasma fitting experiment reveals the spatial density distribution of infection rate; Conclusions:this study provides theoretical support for the prevention and control of infectious diseases, and the complex network model can simulate the transmission process of infectious diseases more accurately. Sensitivity analysis and parameter identification experiments reveal the key influencing factors of propagation and the role of network structure. The effectiveness of the model is supported by actual data, which is helpful for the government health departments to formulate scientific prevention and control strategies.

Research on Target Allocation for Hard-Kill Swarm Anti-Unmanned Aerial Vehicle Swarm Systems

In response to the saturated attacks by low, slow, and small UAV swarms, there is currently a lack of effective countermeasures. Counter-UAV swarm technology is an important issue that urgently requires breakthroughs. This paper conducts research on a mid–short-range hard-kill counter-swarm scenario where fewer swarms confront multiple swarms and stronger swarms confront weaker swarms. The requirement is for counter-swarm UAVs to quickly penetrate the swarm at mid–short range and collide with as many incoming UAVs as possible to destroy them. To address the sparse solution space problem, an improved genetic algorithm that integrates multiple strategies is adopted to calculate the spatial density distribution of the incoming swarm. A baseline is identified through gradient descent that maximizes the density integral in a straight-line direction. Based on this baseline, the solution space for single strikes on the swarm is filtered. During the solution process, an elite strategy is introduced to prevent the overall degradation of the population performance. Additionally, the feasibility of the flight trajectory needs to be assessed. A piecewise cubic spline interpolation method is used to optimize the flight trajectory, minimizing the maximum curvature. Ultimately, multiple counter-swarm UAV targets within the swarm and their corresponding trajectories are obtained.

Mapping essential juvenile habitats of exploited marine fish: Complementary insights from a scientific survey-based model, fishers’ knowledge and fisheries-dependent data

In the Bay of Biscay (BoB, Northeast Atlantic), a preexisting habitat suitability model (HSM) fitted on ecological scientific trawl survey data with restricted partial coverage revealed the concentration of Young of the Year (YoY) common sole (Solea solea) on restricted coastal and estuarine nurseries. To extend the nursery map of sole in the BoB to zones where survey data are lacking and fit with the sole population and stock management extent, we crossed HSM, fishers’ ecological knowledge (FEK) and fisheries-based (FB) data. FB and FEK data also complemented knowledge on juvenile sole habitat and seasonal migration. Thirteen fishers with potential knowledge about the YoY sole distribution were directly interviewed. Direct interviews included both information about the location of juveniles and YoY distribution mapping. With good consensus among fishers, FEK allowed the identification of four new areas hosting essential juvenile habitat for the common sole, revealed the accuracy of the HSM model outside the spatial coverage of the ecological survey, and provided spatial refinement. The FB observation data confirmed the locations of the essential juvenile habitats given by FEK and the spatial distributions of YoY densities predicted from the scientific data. In addition, FB confirmed the seasonal migration of YoY sole, which was preliminarily hypothesized from a local and short-term survey-based study. Our results emphasized the local accuracy of FEK. These findings also underlined the interest in combining several sources of data and methods to map essential fish habitats outside areas well covered by ecological scientific surveys, on order to inform future spatial management measures.

Halogen substitution effects in Chlorostannate(II) hybrid material: Insights from DFT study on 2(C4H4FN3O)·SnX6·2(H2O), (X = F, Cl, Br, I)

The development of new materials is crucial for advancing technologies in material science, energy, and biology. In this study, we investigate the effect of Halogen-substitution on the compound 2(C4H4FN3O)·SnX6·2(H2O) (where X = F, Cl, Br, and I). Using extensive theoretical analysis, we examined the impact of halogen substitution on the structural properties, band gap energy (Eg), and chemical behavior. Our results show that the Eg decreases with the increasing atomic number of halogens. The I-substituted compound is the most reactive and exhibits significant intramolecular charge transfer, enhancing its antioxidant properties. The spatial distribution of electron density in the Frontier Molecular Orbitals (FMOs) indicates that the HOMO is localized on the inorganic anion and the LUMO on the organic cation, a pattern consistent across all substituted compounds. These findings highlight the potential of these compounds in electron transfer reactions and provide insights for tailoring them for specific chemical and biochemical applications.

Stochastic Emission in Passively Fed Single-Emitter Porous-Media Ionic Liquid Ion Sources

Ionic liquid ion sources are a promising form of efficient thrust for power- and mass-constrained satellites. Flight performance requirements necessitate large arrays of emitters; however, the fundamental behaviors of the ion emission process are obscured by the simultaneous operation of multiple emitters. One such behavior is the stochastic nature of Taylor cone formation and ion emission from the emitter. To examine these phenomena, a single-emitter electrospray using a conventionally machined porous borosilicate emitter cone was operated using the ionic liquid 1-ethyl-3-methylimidazolium tetrafluoroborate. Repeated performance curves of the same emitter, measuring the emitter and extractor electrode currents as a function of the emitter voltage, vary significantly between tests. Ion current density spatial distribution maps of the plume and time-resolved emitter current and plume current while retarding potential energy analyzer sweeps are also presented. High-speed current measurements on a collector plate downstream of a different single-emitter electrospray were collected to examine the variation in the onset delay time of the Taylor cone. The onset delay time decreased with increasing emitter voltage and was effectively eliminated using bipolar switching. In monopolar mode, the onset delay rate was not sensitive to changes in the emitter voltage switching frequency across the range of tested values.

Distinctive features of measuring <I>T<SUB>e</SUB></I> and <I>n<SUB>e</SUB></I> spatial distributions in the Globus-M2 spherical tokamak using method of Thomson scattering of laser radiation

The results of measuring the electron temperature and density spatial distributions in plasma of the Globus-M2 tokamak using the Thomson scattering diagnostics are presented. The diagnostics provides measurements throughout the entire tokamak discharge, starting from time of gas breakdown. The Thomson scattering data were analyzed in order to determine the positions of the last closed flux surface, the plasma magnetic axis, and the radius of inversion during the saw-tooth oscillations. The results of measurements performed during the internal reconnection of magnetic field lines are presents, as well as the dynamics of spatial distributions of electron temperature, density and pressure during the plasma transition to the H-mode. The results of measuring the electron temperature distribution in the scrape-off layer using the Thomson scattering diagnostics are also presented for distances up to 4 cm outside the last closed flux surface.

Spatiotemporal Analysis of Open Biomass Burning in Guangxi Province, China, from 2012 to 2023 Based on VIIRS

Open biomass burning has significant adverse effects on regional air quality, climate change, and human health. Extensive open biomass burning is detected in most regions of China, and capturing the characteristics of open biomass burning and understanding its influencing factors are important prerequisites for regulating open biomass burning. The characteristics of open biomass burning have been widely investigated at the national scale, with regional studies often focusing on northeast China, but few studies have examined regional discrepancies in spatiotemporal variations over a long timescale in Guangxi province. In this study, we used the Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m active fire product (VNP14IMG), combined with land cover data and high-resolution remote sensing images, to extract open biomass burning (crop residue burning and forest fire) fire points in Guangxi province from 2012 to 2023. We explored the spatial density distribution and temporal variation of open biomass burning using spatial analysis methods and statistical methods, respectively. Furthermore, we analyzed the driving forces of open biomass burning in Guangxi province from natural (topography, climate, and plant schedule), policy, and social (crop production and cultural customs) perspectives. The results show that open biomass burning is concentrated in the central, eastern, and southern parts of the study area, where there are frequent agricultural activities and abundant forests. At the city level, the highest numbers of fire points were found in Baise, Yulin, Wuzhou, and Nanning. The open biomass burning fire points exhibited large annual variation, with high levels from 2013 to 2015 and a remarkable decrease from 2016 to 2020 under strict control measures; however, inconsistent enforcement led to a significant rebound in fire points from 2021 to 2023. Forest fires are the predominant type of open biomass burning in the region, with forest fires and crop residue burning accounting for 76.82% and 23.18% of the total, respectively. The peak period for crop residue burning occurs in the winter, influenced mainly by topography, planting schedules, crop production, and policies, while forest fires predominantly occur in the winter and spring, primarily influenced by topography, climate, and cultural customs. The results indicate that identifying the driving forces behind spatiotemporal variations is essential for the effective management of open biomass burning.

Analysis of Spatiotemporal Predictions and Drivers of Carbon Storage in the Pearl River Delta Urban Agglomeration via the PLUS-InVEST-GeoDetector Model

Land use and land cover change (LUCC) significantly influences the dynamics of carbon storage in thin terrestrial ecosystems. Investigating the interplay between land use alterations and carbon sequestration is crucial for refining regional land use configurations, sustaining the regional carbon balance, and augmenting regional carbon storage. Using land use data from the Pearl River Delta Urban Agglomeration (PRDUA) from 2010 to 2020, this study employed PLUS-InVEST models to analyze the spatiotemporal dynamics of land use and carbon storage. Projections for the years 2030, 2040, and 2050 were performed under three distinct developmental scenarios, namely, natural development (ND), city priority development (CPD), and ecological protection development (EPD), to forecast changes in land use and carbon storage. The geographic detector model was leveraged to dissect the determinants of the spatial and temporal variability of carbon storage, offering pertinent recommendations. The results showed that (1) during 2010–2020, the carbon storage in the PRDUA showed a decreasing trend, with a total decrease of 9.52 × 106 Mg, and the spatial distribution of carbon density in the urban agglomeration was imbalanced and showed an overall trend in increasing from the center to the periphery. (2) Clear differences in carbon storage were observed among the three development scenarios of the PRDUA between 2030 and 2050. Only the EPD scenario achieved an increase in carbon storage of 1.10 × 106 Mg, and it was the scenario with the greatest potential for carbon sequestration. (3) Among the drivers of the evolution of spatial land use patterns, population, the normalized difference vegetation index (NDVI), and distance to the railway had the greatest influence on LUCC. (4) The annual average temperature, annual average rainfall, and GDP exerted a significant influence on the spatiotemporal dynamics of carbon storage in the PRDUA, and the interactions between the 15 drivers and changes in carbon storage predominantly manifested as nonlinear and double-factor enhancements. The results provide a theoretical basis for future spatial planning and achieving carbon neutrality in the PRDUA.

Gas jet target with controllable density via throat diameter of conical nozzle

A supersonic gas jet has been a special target in the ultraintense laser interaction field due to its controllable atomic density distribution. This work investigates the spatial atomic density distribution in argon gas jets ejected from conical nozzles with different throat diameters. Both experiment and simulation results show that the atomic density and its distribution can be controlled by changing the throat diameter of the conical nozzle. The quantitative dependence of atomic density on the throat diameter under different backing pressures is obtained. It also agrees with that from the one-dimensional gas dynamics model. However, it is noted that for a large throat diameter at a high gas backing pressure, a radial saddle-shaped atomic density profile is demonstrated experimentally within a few millimeters away from the nozzle outlet. The results are helpful to optimize the density profile in gas-jet targets and to understand the effect of the throat diameter of the conical nozzle on cluster size in Hagena scaling law.

Self‐Assembling Design Method of Stator Slots for AC Rotating Machines

To maximize the performance of rotating machines, it is essential to establish a design method with minimal arbitrariness. This paper proposes a self‐assembling method to design stator slots for alternating current (AC) rotating machines. First, we develop a line‐current approximation model of the stator winding using pulse‐width modulation technique and realize an ideal spatial magnetic flux density distribution. Subsequently, we design the realistic stator with an acceptable current density of the winding by forming unique slot shapes in a self‐assembling manner under two synthetic conditions using the developed line‐current approximation model as the starting model. The designed stator realizes a rotating magnetic field similar to the conventional design results. Additionally, we perform an analysis of motor rotation characteristics by combining the self‐assembled stator with a surface‐mounted permanent magnet rotor to determine the possibility of a higher output compared to that when using a conventional stator. The self‐assembled motor without relying on empirical rules shows a possibility of further improving the torque characteristics, thereby contributing to designing the AC rotating machines. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Multi-diagnostic of dust growth in a capacitive Ar/C2H2 plasma

Abstract The interest in the production of nanoparticles (NPs) within Ar/C2H2 reactive plasmas is increasing, driven by their potential applications in functional materials or for their analogy to cosmic dust. The growth process of NPs has been thoroughly examined using a broad array of diagnostic tools. Significant among these tools are those that determine two-dimensional distributions of NP sizes and densities. The inherent complexity of these techniques has resulted in a limited number of works that integrate these measurements with a multitude of other diagnostic tools. Here, we show a multi-diagnostic exploration of the growing process of NPs in Ar/C2H2 plasmas. The combination of in-situ techniques, such as scattered light images, optical emission spectroscopy, light extinction, quadrupole mass signals, or self-bias voltage, with ex-situ scanning electron microscopy images and FTIR spectra of the deposited dust, provides a detailed picture of the growth process. The temporal evolution of plasma parameters, coupled with chemical composition measurements, provides a comprehensive description of the dust growth phases, and the FTIR measurements reveal an appreciable difference in chemical composition between the core and shell of the NPs. Furthermore, employing a method based on the terminal falling velocity of NPs in the afterglow, the intrinsic mass density of NPs is estimated. The asymmetries observed in the spatial distributions of NP size and density are qualitatively discussed in terms of neutral drag, ion drag, and electrostatic forces.

Development of functionally graded structure for hip endoprosthesis stem based on lattice-type metamaterial

The paper reports on design and studies of a promising configuration of a hip endoprosthesis stem. The femoral component of the endoprosthesis is constructed based on a metamaterial produced by additive technologies, representing a periodic porous structure of variable topology. The central goal of the design procedure was to numerically determine the spatially graded relative density of the lattice structure within the implant volume by solving the optimization problem. The first stage of development comprised finite element modeling of a system with a solid implant attached, i.e., the optimization space, for seven different loading scenarios. These scenarios were constructed to represent the most typical cases of human motor activity. The second step was to determine the optimal spatial distribution of relative density of the lattice structure in the implant volume, obtained by solving the topological optimization problem under the given loading. After the optimization problem was solved, the distribution of the relative density of the lattice structure was obtained, serving as a basis for constructing a geometric model of a functionally graded porous scaffold for implantation. This result allows achieving an optimal ratio of stiffness and mass properties under the given loading conditions. The approach was verified by direct finite element modeling of the constructed lattice geometry of the implant under specific loading scenarios. Analyzing the stress fields in the volume of the endoprosthesis, we concluded that there were no critical regions in the developed structure, so the approach taken to develop the metamaterial-based endoprosthesis can be deemed correct.

Random forest regression kriging modeling for soil organic carbon density estimation using multi-source environmental data in central Vietnamese forests

Forest soil organic carbon plays a vital role in the terrestrial carbon cycle. Accurately analyzing the spatial distribution of soil organic carbon density (SOCD) is therefore necessary for sustainable forest management and climate change mitigation. Previous studies explored the potential of random forest (RF) in modeling forest SOCD using various environmental data sources. However, how forest SOCD prediction would be affected by using random forest regression kriging (RFRK), which integrates the predictive power of RF in generating deterministic trends and the capability of the ordinary kriging (OK) in handling spatial autocorrelation structure of residuals, based on the environmental data sources and their combinations remains elusive and deserves further exploration. For this purpose, 104 soil samples were collected at a depth of 30 cm in forest ecosystems of Central Vietnam, and 33 environmental covariates were derived from Sentinel-2 (S2) imagery, Advanced Land Observing Satellite-2 Phased Array L-band Synthetic Aperture Radar-2 (AL2) imagery, digital elevation model (DEM), and climatic data. Using a leave-one-out cross-validation procedure to evaluate and compare the model performances, four metrics, including coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE), and relative improvement (RI), were calculated. The results showed that enhanced RFRK performance for forest SOCD estimation was found with the inclusion of additional environmental data sources, with RFRK based on all data sources achieving a high accuracy (R2 = 0.78, MAE = 8.28 t·ha−1, and RMSE = 10.54 t·ha−1). The comparison of the RF and RFRK models exhibited that additionally interpolated residuals by OK were more accurate than only considering the influences of predictor covariates. The relative improvement of the RFRK models over the RF models in forest SOCD estimation was notable, with RIR2 ranging from 8.20 to 65.00%, RIMAE ranging from 8.18 to 21.07%, and RIRMSE ranging from 6.76 to 18.18%. The result from our case study emphasizes the robustness of RFRK using S2, AL2, DEM, and climatic data in accurately predicting forest SOCD.

Polymer Boron-Containing Composite for Protecting Astronauts of Manned Orbital Stations from Secondary Neutron Radiation

This article considers the prospects of using heat-resistant polyimide boron-containing composites to protect astronauts of manned orbital stations from secondary neutron radiation. Variant calculations are performed regarding neutron and gamma-quanta flux distributions in a polyimide composite material with different boron content used to reduce capture radiation. The dependences of spatial distributions of thermal neutron flux density and the gamma-quanta dose rate in a polyimide composite layer with a boron content of 0 to 5% are obtained. An experimental assessment of the energy distribution of neutron and gamma radiation behind the protective polyimide composite is carried out. The introduction of boron atoms in an amount of 3.0 wt.% shows the absence of bursts of secondary gamma radiation energy in the composite, which is due to the high cross-section of thermal neutron absorption by boron atoms. As a result, with a material layer thickness of 3–10 cm, the gamma-quanta dose rate decreases by 2–3 times. The differential thermal analysis method showed that the upper limit of the working temperature of the polyimide composite is 500 °C. The polyimide matrix filled with boron atoms can find effective application in the development of new radiation-protective polymer materials used in manned orbital stations.

Regional socioeconomic characteristics and density of general practitioners in Germany: A nationwide cross-sectional and longitudinal spatial analysis

ObjectivesLimited healthcare availability impacts population health. Regional disparities in GP density across Germany raise questions about their association with regional socioeconomic characteristics. Study designThis longitudinal nationwide ecological German study used regional data at the county level (n = 401) from 2015 to 2019 provided by the Federal Institute for Research on Building, Urban Affairs and Spatial Development (BBSR). The outcome was general practitioners (GPs) density, defined as the number of GPs per 10,000 inhabitants. MethodsUnivariate Moran's I, cluster analysis (LISA), and spatial lag of X (SLX) models were employed to analyse the spatial distribution of GP density and its correlation with various regional socioeconomic characteristics from a cross-sectional and longitudinal perspective. ResultsIn contrast to the univariate analysis, rural counties showed the highest GP density the multivariate model. Several counties were identified as embedded in low- or high-GP-density clusters. In 2015 and 2019, larger household size (2015: std. β = −2.31, p = 0.021; 2019: std. β = −4.14, p < 0.001) and higher unemployment rate (2015: std. β = −2.84, p = 0.005; 2019: std. β = −5.47, p < 0.001) were associated with lower GP density. In the longitudinal model, a greater increase in the unemployment rate was related to a greater decrease in GP density (std. β = −2.17, p = 0.030). ConclusionA higher regional unemployment rate is linked to lower GP availability in Germany, and a greater increase in the unemployment rate was related to a greater decrease in GP availability over time. This necessitates policy intervention to avoid socioeconomic disparities in GP care.

Pattern dynamics in a predator–prey model with Smith growth function and prey refuge in predator poisoned environment

In this article, we investigate temporal as well as spatiotemporal dynamics of a predator–prey system where prey grows according to Smith growth function and prey refuges in predator poisoned environment. Self as well as cross diffusion are taken into consideration to describe spatial moment of the species which make the system more realistic. This study aims to investigate the role of prey refuge, toxin-carrying carcass and the impact of cross-diffusion on the spatial distribution of species densities and associated patterns. The existence of equilibria and their stability conditions for non-spatial system are derived. We discuss the occurrence of Hopf bifurcation and detect the stability of limit cycle by computing first Lyapunov number. Temporal dynamics of the system is studied by varying the significant parameters. Study reveals that both prey refuge and fatality rate of predator due to toxin-carrying carcass, initially makes the system stable for low refuge and fatality rate but predator population goes to extinction as those effects increase. Turing instability conditions are listed and different instability regions so formed are discussed. In Turing region, pattern selection with the help of amplitude equation via weakly nonlinear analysis are performed which also numerically supported. Intensity of refuge and fatality rate due to toxin carrying carcass result paradox with real ecological world due to the presence of cross diffusion. Various kind of patterns such as mixture of stripe and spot, spot, irregular chaotic patterns emerge due to Hopf and Turing instability. Particularly, spatiotemporal chaos is a controversial topic because of its significant consequences for population dynamics. The results of this work are expected to contribute to a better understanding the level of prey refuge, use of toxin-carrying carcass considering movement in population and effect of cross-diffusion.

The piezoelectric activity in the HfO2 nanoclusters

In this paper the piezoelectric effects in infinite free-standing HfO2 film and HfO2 cluster under mechanical action are studied by methods of the density functional theory and first-principles pseudopotential based on own program code. The spatial distribution of valence electron density, the forces that act on an individual atom from the electronic and ionic subsystems, and Coulomb potential along transverse direction are calculated. It was found that a polarization charge distribution of valence electrons, which leads to piezoelectric effects, was observed in HfO2 nanofilms, while in HfO2 nanoclusters the charge distribution remained uniform both in the uncompressed and in the compressed state.