Spark Plasma Sintering of Boron Carbide Using Ti_(3)SiC_(2) as a Sintering Additive

Boron carbide has unique properties for wide application possibilities;however,poor sinterability limits its applications.One approach to overcome this limitation is the addition of secondary phases into boron carbide.Boron carbide based composite ceramics are produced by the direct addition of secondary phases into the structure or via reactive sintering using a sintering additive.The present study investigated the effect of Ti_(3)SiC_(2) addition to boron carbide by reactive spark plasma sintering in the range of 1700-1900℃.Ti_(3)SiC_(2) phase decomposed at high temperatures and reacted with B4C to form secondary phases of TiB2 and SiC.The results demonstrated that the increase of Ti_(3)SiC_(2) addition(up to 15 vol%)effectively promoted the densification of B4C and yielded higher hardness.However,as the amount of Ti_(3)SiC_(2) increased further,the formation of microstructural inhomogeneity and agglomeration of secondary phases caused a decrease in hardness.

Shapes of the fastest fish and optimal underwater and floating hulls

A streamlined shape of the best swimmers removes the boundary-layer separation and ensures a laminar flow pattern.The fastest fish have a very sharp convex nose(rostrum),the purpose of which remains unclear.The bodies of revolution similar to their shapes are analyzed in steady underwater and floating motion.The sources and sinks were located on the axis of symmetry and above the water surface to estimate the pressure on the body and the vertical velocities on the water surface.It was shown that the flow patterns on a special shaped body with concave nose has no stagnation points and ensure small values of the water surface elevation.These fact allow diminishing the maximum pressure on the surface and wave drag.Special shapes with the sharp concave nose and negative pressure gradients on their surface could be parts of the low drag underwater and floating hulls.

Influence of Temperature on the Measuring Accuracy of Devices Based on Surface Plasmon Resonance Phenomenon

The main reasons for the occurrence of temperature error and perspective directions of decreasing of its value are presented by improving the device design based on the phenomenon of surface plasmon resonance (SPR) and numerical methods of processing the results of measurements by this device. The most essential influence on changes in results of measurements can be rendered by temperature changes in the analyte refractive index. It is shown that the application of the integrated temperature stabilization of the device with the test substance, and numerical processing of the measurement results for compensation of temperature changes of the test substance and the use of film heaters it is possible to reduce the measurement error of the refractive index of the analyte at least 30 times from 2.4 × 10-4 to 7.6 × 10-6.

Low-intensity Microwave Radiation of Natural Substances for Physiotherapy

The mechanisms of influence of physiotherapy procedures in ozokeriteparaffin therapy are considered in this paper.It is shown that microwave electromagnetic radiation formed by heated ozokerite-paraffin mixture is an important component of physiotherapy procedures.Using the experimental setup developed by the authors,the radiative abilities of ozokerite,paraffin and their mixtures in the microwave range were investigated.It was found that in the process of cooling the ozokerite-paraffin mixture,during the procedure,negative microwave fluxes occur,affecting the inflammatory processes in the patient’s body.The dependences of the microwave radiation level on the composition of the ozokerite-paraffin mixture are investigated.The results of experimental studies allowed us to evaluate the interaction of electromagnetic radiation of ozokerite-paraffin mixtures with human own electromagnetic radiation and to approach the choice of modes of therapeutic interaction more carefully.

Simulation of Weather Conditions on Mars

In times of active research of the possibilities of colonization of other planets,it is important to acquire the skills of forecasting weather conditions on the planets,which are the prospects for human settlement.In this research,the theoretical model is developed that describes the physical processes that occur in the atmosphere of Mars in order to calculate the surface temperature of the planet for any point of the planet’s area,time of day,and day of the year.The following theoretical model is implemented in computer software realized by Python programming language to calculate the necessary data.

Human-Computer Interaction Using Deep Fusion Model-Based Facial Expression Recognition System

A deep fusion model is proposed for facial expression-based human-computer Interaction system.Initially,image preprocessing,i.e.,the extraction of the facial region from the input image is utilized.Thereafter,the extraction of more discriminative and distinctive deep learning features is achieved using extracted facial regions.To prevent overfitting,in-depth features of facial images are extracted and assigned to the proposed convolutional neural network(CNN)models.Various CNN models are then trained.Finally,the performance of each CNN model is fused to obtain the final decision for the seven basic classes of facial expressions,i.e.,fear,disgust,anger,surprise,sadness,happiness,neutral.For experimental purposes,three benchmark datasets,i.e.,SFEW,CK+,and KDEF are utilized.The performance of the proposed systemis compared with some state-of-the-artmethods concerning each dataset.Extensive performance analysis reveals that the proposed system outperforms the competitive methods in terms of various performance metrics.Finally,the proposed deep fusion model is being utilized to control a music player using the recognized emotions of the users.

An Optimal Scheme for WSN Based on Compressed Sensing

Wireless sensor networks(WSNs)is one of the renowned ad hoc network technology that has vast varieties of applications such as in computer networks,bio-medical engineering,agriculture,industry and many more.It has been used in the internet-of-things(IoTs)applications.A method for data collecting utilizing hybrid compressive sensing(CS)is developed in order to reduce the quantity of data transmission in the clustered sensor network and balance the network load.Candidate cluster head nodes are chosen first from each temporary cluster that is closest to the cluster centroid of the nodes,and then the cluster heads are selected in order based on the distance between the determined cluster head node and the undetermined candidate cluster head node.Then,each ordinary node joins the cluster that is nearest to it.The greedy CS is used to compress data transmission for nodes whose data transmission volume is greater than the threshold in a data transmission tree with the Sink node as the root node and linking all cluster head nodes.The simulation results demonstrate that when the compression ratio is set to ten,the data transfer volume is reduced by a factor of ten.When compared to clustering and SPT without CS,it is reduced by 75%and 65%,respectively.When compared to SPT with Hybrid CS and Clustering with hybrid CS,it is reduced by 35%and 20%,respectively.Clustering and SPT without CS are compared in terms of node data transfer volume standard deviation.SPT with Hybrid CS and clustering with Hybrid CS were both reduced by 62%and 80%,respectively.When compared to SPT with hybrid CS and clustering with hybrid CS,the latter two were reduced by 41%and 19%,respectively.

A simple description of the temperature dependence of the width of the fission-fragment mass yield in ^(197)Au and ^(209)Bi at intermediate energies

A simple approach is proposed to describe the experimental data for the widths of the fission-fragment mass yields in^(197)Au and^(209)Bi at low and intermediate energies.The approach is based on the expressions for the temperature dependence of the width of the fission-fragment mass yield and the mass of the most probable fragment.The expression for the width of the fission-fragment mass yield depends on the mass of the most probable fragment,the surface terms of the energy level density parameter,the temperature and the stiffness parameter of the potential related to mass-asymmetric degree of freedom.It is shown that the contribution of the surface term of the energy level density parameter is important for describing the experimental data in a wide range of energies.

A workflow for Sustainable Development Goals indicators assessment based on high-resolution satellite data

For evaluating the progresses towards achieving the Sustainable Development Goals(SDGs),a global indicator framework was developed by the UN Inter-Agency and Expert Group on Sustainable Development Goals Indicators.In this paper,we propose an improved methodology and a set of workflows for calculating SDGs indicators.The main improvements consist of using moderate and high spatial resolution satellite data and state-of-the-art deep learning methodology for land cover classification and for assessing land productivity.Within the European Network for Observing our Changing Planet(ERA-PLANET),three SDGs indicators are calculated.In this research,harmonized Landsat and Sentinel-2 data are analyzed and used for land productivity analysis and yield assessment,as well as Landsat 8,Sentinel-2 and Sentinel-1 time series are utilized for crop mapping.We calculate for the whole territory of Ukraine SDG indicators:15.1.1–‘Forest area as proportion of total land area’;15.3.1–‘Proportion of land that is degraded over total land area’;and 2.4.1–‘Proportion of agricultural area under productive and sustainable agriculture’.Workflows for calculating these indicators were implemented in a Virtual Laboratory Platform.We conclude that newly available high-resolution remote sensing products can significantly improve our capacity to assess several SDGs indicators through dedicated workflows.

Developing food,water and energy nexus workflows

There is a growing recognition of the interdependencies among the supply systems that rely upon food,water and energy.Billions of people lack safe and sufficient access to these systems,coupled with a rapidly growing global demand and increasing resource constraints.Modeling frameworks are considered one of the few means available to understand the complex interrelationships among the sectors,however development of nexus related frameworks has been limited.We describe three opensource models well known in their respective domains(i.e.TerrSysMP,WOFOST and SWAT)where components of each if combined could help decision-makers address the nexus issue.We propose as a first step the development of simple workflows utilizing essential variables and addressing components of the above-mentioned models which can act as building-blocks to be used ultimately in a comprehensive nexus model framework.The outputs of the workflows and the model framework are designed to address the SDGs.