Search results for: eXtreme gradient boosting

Authors: Slimani Halima

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One of the main problems of degradation of arid steppe rangelands in the southern Mediterranean is the loss of plant diversity and changes in soil properties. During the last decades, these rangelands faced two main driving forces: climate through more or less lasting and recurrent droughts and overgrazing by sheep. In the present work, the preexisting system was an arid steppe with alfa grass (Stipa tenacissima L.) as the dominant plant, which was considered to be the "keystone" species toward the whole ecosystem structure and functioning. Vegetation and soil change was monitored for 45 years along a grazing intensity gradient. Changes in species richness and diversity, in the vegetation and in the soil, enabled to better understand climate fluctuations effects in comparison to overgrazing ones. The aim is to assess the impacts of grazing and climatic variability and change on biodiversity,vegetation and soil over a period of 45 years, based on data from seven reference years.

Keywords: biodiversity, desertification, droughts, el bayadh, overgrazing, soil, steppe

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Authors: Pavan K. Rallabandi, Kailash C. Patidar

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In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence or pattern recognition/ classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: hybrid systems, hidden markov models, recurrent neural networks, deterministic finite state automata

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Authors: Anwaar O. Ali, Mahmoud Fathy Mubarak, Mahmoud Ibrahim Abdou, Hector Cano Esteban, Amany A. Aboulrous

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Corrosion resistance and lubrication are crucial characteristics required for geothermal drilling fluids. In this study, a ZnO/Fe₂O₃ nanocomposite was fabricated and incorporated into the structure of Cetyltrimethylammonium bromide (CTAB). Several physicochemical techniques were utilized to analyze and describe the synthesized nanomaterials. The surface morphology of the composite was assessed through scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDAX). The corrosion inhibition capabilities of these materials were explored across various corrosive environments. The weight loss and electrochemical methods were utilized to determine the corrosion inhibition activity of the prepared nanomaterials. The results demonstrate a high level of protection achieved by the composite. Additionally, the lubricant coefficient and extreme pressure properties were evaluated.

Keywords: nanofluid, corrosion, geothermal drilling fluids, ZnO/Fe2O3

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Authors: M. Zain, Thaung H. Aung, Naveed Anwar

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During the service life, a structure may experience extreme loading conditions. The current study proposes a new methodology that covers the effect of uncertainty involved in gravity loadings on key structural elements of new and complex structures by emphasizing on a very realistic assumption that allows the 'Performance-Based Assessment' to be executed on the structure against the gravity loadings. The methodology does not require the complete removal of an element, instead, it permits the incremental reduction in the capacity of key structural elements and preserves the same stiffness of the member in each case of capacity loss. To demonstrate the application of the proposed methodology, a 13 story complex structure is selected that comprises of a diverse structural configuration. The results ensure the structural integrity against the applied gravity loadings, as well as the effectiveness of the proposed methodology.

Keywords: force-deformation relationship, gravity loading, incremental capacity reduction, multi-linear plastic link element, SAP2000, stiffness

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Authors: H. Nacef, L. Larous

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Salin soils occupy about 7% of land area; they are characterized by unsuitable physical conditions for the growth of living organisms. However, researches showed that some microorganisms especially fungi are able to grow and adapt to such extreme conditions; it is due to their ability to develop different physiological mechanisms in their adaptation. The aim of this study is to identify qualitatively the osmolytes that the biotechnological important fungus A. oryzae accumulated and/or produced in its adaptation, which they were detected by Thin-layer chromatography technique (TLC) using several systems, from different media (Wheat brane, MNM medium and MM medium). The results showed that The moderately halotolerant fungus A. oryzae, accumulates mixture of molecules, containing polyols and sugars , some amino acids in addition to some molecules which were not defined. Wheat bran was the best medium for the extraction of these molecules, where the proportion was 85.71%, followed by MNM medium 64.28%, then the minimum medium MM 14.28%. Properties of osmolytes are becoming increasingly useful in molecular biology, agriculture pharmaceutical, medicinal, and biotechnological interests.

Keywords: salinity, aspergillus oryzae, halo tolerance, osmolytes, compatible solutes

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Authors: Ainul Haque, Ameeye Kumar Nayak

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Flow enhancement and species transport in a slit hydrophobic microchannel is studied for non-Newtonian fluids with the externally imposed electric field and pressure gradient. The incompressible Poisson-Nernst-Plank equations and the Navier-Stokes equations are approximated by lubrication theory to quantify the flow structure due to hydrophobic and hydrophilic surfaces. The analytical quantification of velocity and pressure of electroosmotic flow (EOF) is made with the numerical results due to the staggered grid based finite volume method for flow governing equations. The resistance force due to fluid friction and shear force along the surface are decreased by the hydrophobicity, enables the faster movement of fluid particles. The resulting flow enhancement factor Ef is increased with the low viscous fluid and provides maximum species transport. Also, the analytical comparison of EOF with pressure driven EOF justifies the flow enhancement due to hydrophobicity and shear impact on flow variation.

Keywords: electroosmotic flow, hydrophobic surface, power-law fluid, shear effect

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Authors: Kenneth A. Rostowsky, Alexander S. Maher, Nahian F. Chowdhury, Andrei Irimia

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The clinical significance of cerebral microbleeds (CMBs) due to mild traumatic brain injury (mTBI) remains unclear. Here we use magnetic resonance imaging (MRI), diffusion tensor imaging (DTI) and connectomic analysis to investigate the statistical association between mTBI-related CMBs, post-TBI changes to the human connectome and neurological/cognitive deficits. This study was undertaken in agreement with US federal law (45 CFR 46) and was approved by the Institutional Review Board (IRB) of the University of Southern California (USC). Two groups, one consisting of 26 (13 females) mTBI victims and another comprising 26 (13 females) healthy control (HC) volunteers were recruited through IRB-approved procedures. The acute Glasgow Coma Scale (GCS) score was available for each mTBI victim (mean µ = 13.2; standard deviation σ = 0.4). Each HC volunteer was assigned a GCS of 15 to indicate the absence of head trauma at the time of enrollment in our study. Volunteers in the HC and mTBI groups were matched according to their sex and age (HC: µ = 67.2 years, σ = 5.62 years; mTBI: µ = 66.8 years, σ = 5.93 years). MRI [including T1- and T2-weighted volumes, gradient recalled echo (GRE)/susceptibility weighted imaging (SWI)] and gradient echo (GE) DWI volumes were acquired using the same MRI scanner type (Trio TIM, Siemens Corp.). Skull-stripping and eddy current correction were implemented. DWI volumes were processed in TrackVis (http://trackvis.org) and 3D Slicer (http://www.slicer.org). Tensors were fit to DWI data to perform DTI, and tractography streamlines were then reconstructed using deterministic tractography. A voxel classifier was used to identify image features as CMB candidates using Microbleed Anatomic Rating Scale (MARS) guidelines. For each peri-lesional DTI streamline bundle, the null hypothesis was formulated as the statement that there was no neurological or cognitive deficit associated with between-scan differences in the mean FA of DTI streamlines within each bundle. The statistical significance of each hypothesis test was calculated at the α = 0.05 level, subject to the family-wise error rate (FWER) correction for multiple comparisons. Results: In HC volunteers, the along-track analysis failed to identify statistically significant differences in the mean FA of DTI streamline bundles. In the mTBI group, significant differences in the mean FA of peri-lesional streamline bundles were found in 21 out of 26 volunteers. In those volunteers where significant differences had been found, these differences were associated with an average of ~47% of all identified CMBs (σ = 21%). In 12 out of the 21 volunteers exhibiting significant FA changes, cognitive functions (memory acquisition and retrieval, top-down control of attention, planning, judgment, cognitive aspects of decision-making) were found to have deteriorated over the six months following injury (r = -0.32, p < 0.001). Our preliminary results suggest that acute post-TBI CMBs may be associated with cognitive decline in some mTBI patients. Future research should attempt to identify mTBI patients at high risk for cognitive sequelae.

Keywords: traumatic brain injury, magnetic resonance imaging, diffusion tensor imaging, connectomics

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Authors: K. Senthil Nathan, P. Rajasekaran

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Fatigue is a feeling of extreme physical or mental tiredness. Almost everyone becomes fatigued at some time, but driver’s fatigue is a serious problem that leads to thousands of automobile crashes each year. Fatigue process is often a change from the alertness and vigor state to the tiredness and weakness state. It is not only accompanied by drowsiness but also has a negative impact on mood. There have been studies to detect and quantify fatigue from the measurement of physiology variables such as electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG). This project involves a multimodal sensing of driver’s drowsiness. The first method is to count the eye blinking rate. In the second level, we authenticate the results of eye blink module with a grip sensor. The Flexiforce sensor is placed over the steering wheel. In the third level, the activities are sensed, the time elapsed from the driver’s last activity is counted here. The activities in the sense: Changing gear, applying brake, pressing sound horns, and turning the steering wheel. Absence of these activities is also an indicator of fatigue.

Keywords: eye blink sensor, Flexiforce sensor, EEG, EOG, EMG

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Authors: ByoungJoon Yu, Junkyeong Kim, Seunghee Park

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The tensile force estimation PS tendons is in great demand on monitoring the structural health condition of PSC girder bridges. Measuring the tensile force of the PS tendons inside the PSC girder using conventional methods is hard due to its location. In this paper, an embedded EM sensor based tensile force estimation of PS tendon was carried out by measuring the permeability of the PS tendons in PSC girder. The permeability is changed due to the induced tensile force by the magneto-elastic effect and the effect then lead to the gradient change of the B-H curve. An experiment was performed to obtain the signals from the EM sensor using three down-scaled PSC girder models. The permeability of PS tendons was proportionally decreased according to the increase of the tensile forces. To verify the experiment results, a simulation of tensile force estimation will be conducted in further study. Consequently, it is expected that both the experiment results and the simulation results increase the accuracy of the tensile force estimation, and then it could be one of the solutions for evaluating the performance of PSC girder.

Keywords: tensile force estimation, embedded EM sensor, PSC girder, EM sensor simulation, cross section loss

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Authors: A. Kellou, L. Rouaiguia, L. Rabahi

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In the present work, the atomic hydrogen absorption trend in the GdNi5 and GdNi4Cu rare earth compounds within the hexagonal CaCu5 type of crystal structure (space group P6/mmm) is investigated. The density functional theory (DFT) combined with the generalized gradient approximation (GGA) is used to study the site preference of atomic hydrogen at 0K. The octahedral and tetrahedral interstitial sites are considered. The formation energies and structural properties are determined in order to evaluate hydrogen effects on the stability of the studied compounds. The energetic diagram of hydrogen storage is established and compared in GdNi5 and GdNi4Cu. The magnetic properties of the selected compounds are determined using spin polarized calculations. The obtained results are discussed with and without hydrogen addition taking into account available theoretical and experimental results.

Keywords: density functional theory, hydrogen storage, rare earth compounds, structural and magnetic properties

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Authors: Chiara Cesali

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The effects of climate change are increasingly evident: increases in temperature (i.e. global warming), greater frequency of extreme weather events, i.e. storms, floods, which often affect transport infrastructures. Large-scale climatological models with long-term horizons (up to 2100) show the possibility of significant increases in precipitation in the future, according to the greenhouse gas emissions scenarios from IPCC. Consequently, the insufficiency of existing hydraulic works (i.e. bridges, culverts, drainage systems) may be more frequent, or those currently being designed may become insufficient in the future. Thus, the hydraulic design methods of transport infrastructure must begin to take into account the influence of climate change. To this purpose, criteria for applying to the hydraulic design of a railway infrastructure some of the approaches currently available for determining design rainfall intensity and/or peak discharge flow on the basis of possible climate change scenarios are defined and proposed in the paper. Some application cases are also described.

Keywords: climate change, hydraulic design, precipitation, railway

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Authors: Rami El-Hajj Mohamad, Mahmoud Skafi, Ali Massoud Haidar

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Several meteorological parameters were used for the prediction of monthly average daily global solar radiation on horizontal using recurrent neural networks (RNNs). Climatological data and measures, mainly air temperature, humidity, sunshine duration, and wind speed between 1995 and 2007 were used to design and validate a feed forward and recurrent neural network based prediction systems. In this paper we present our reference system based on a feed-forward multilayer perceptron (MLP) as well as the proposed approach based on an RNN model. The obtained results were promising and comparable to those obtained by other existing empirical and neural models. The experimental results showed the advantage of RNNs over simple MLPs when we deal with time series solar radiation predictions based on daily climatological data.

Keywords: recurrent neural networks, global solar radiation, multi-layer perceptron, gradient, root mean square error

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Authors: Abdoulnabi Tavangari, Nasim Salehzadeh

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We presume a cylindrical medium that is under a uniform loading and there is a penny shaped crack located in the center of cylinder. In the crack growth analysis, the Stress Intensity Factor (SIF) is a fundamental prerequisite. In the present study, according to the RITZ method and by considering a cylindrical coordinate system as the main coordinate and a local polar coordinate, the mode-I SIF of threedimensional penny-shaped crack is obtained. In this method the unknown coefficients will be obtained with minimizing the potential energy that is including the strain energy and the external force work. By using the hook's law, stress fields will be obtained and then by using the Irvine equations, the amount of SIF will be obtained near the edge of the crack. This question has been solved for extreme medium in the Tada handbook and the result of the present research has been compared with that.

Keywords: three-dimensional cracks, penny-shaped crack, stress intensity factor, fracture mechanics, Ritz method

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Authors: S. H. Arnaud Kanga, O. Hili, S. Dabo-Niang

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Spatial prediction is an issue appealing and attracting several fields such as agriculture, environmental sciences, ecology, econometrics, and many others. Although multiple non-parametric prediction methods exist for spatial data, those are based on the conditional expectation. This paper took a different approach by examining a non-parametric spatial predictor of the conditional quantile. The study especially observes the stationary multidimensional spatial process over a rectangular domain. Indeed, the proposed quantile is obtained by inverting the conditional distribution function. Furthermore, the proposed estimator of the conditional distribution function depends on three kernels, where one of them controls the distance between spatial locations, while the other two control the distance between observations. In addition, the almost complete convergence and the convergence in mean order q of the kernel predictor are obtained when the sample considered is alpha-mixing. Such approach of the prediction method gives the advantage of accuracy as it overcomes sensitivity to extreme and outliers values.

Keywords: conditional quantile, kernel, nonparametric, stationary

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Authors: Mehrdad Azimzadeh, Seyed Mohammadreza Jabbari, Mohammadreza Hosseinzadeh Alherd

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This paper includes experimental results and analytical studies about increasing resistance of single-span reinforced concreted frames against impact factor and their modeling according to optimization methods and optimizing the behavior of these frames under impact loads. During this study, about 30 designs for different frames were modeled and made using specialized software like ANSYS and Sap and their behavior were examined under variable impacts. Then suitable strategies were offered for frames in terms of concrete mixing in order to optimize frame modeling. To reduce the weight of the frames, we had to use fine-grained stones. After designing about eight types of frames for each type of frames, three samples were designed with the aim of controlling the impact strength parameters, and a good shape of the frame was created for the impact resistance, which was a solid frame with muscular legs, and as a bond away from each other as much as possible with a 3 degree gradient in the upper part of the beam.

Keywords: optimization, reinforced concrete, optimization methods, impact load, earthquake

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Authors: Jian Peng, Wenhui Xiong, Zheng Lu

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An optimal recipe of amendment (nutrients and electron acceptors) was developed and dominant indigenous benzene-degrading microorganisms were characterized in this study. Lessons were learnt from the development of the optimal amendment recipe: (1) salinity and substantial initial concentration of benzene were detrimental for benzene biodegradation; (2) large dose of amendments can shorten the lag time for benzene biodegradation occurrence; (3) toluene was an essential co-substance for promoting benzene degradation activity. The stable isotope probing study identified incorporation 13C from 13C-benzene into microorganisms, which can be considered as a direct evidence of the occurrence of benzene biodegradation. The dominant mechanism for benzene removal was identified by quantitative polymerase chain reaction analysis to be nitrate reduction. Microbial analyses (denaturing gradient gel electrophoresis and 16S ribosomal RNA) demonstrated that members of genus Dokdonella spp., Pusillimonas spp., and Advenella spp. were predominant within the microbial community and involved in the anaerobic benzene bioremediation.

Keywords: benzene, enhanced anaerobic bioremediation, stable isotope probing, biosep biotrap

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Authors: Jingjing Yan, Gengen He, Anahid Basiri

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The design of an indoor navigation system for fire evacuation support requires not only physical feasibility but also a relatively thorough consideration of the human factors. This study has taken a survey to investigate the fire response performances (FRP) of the indoor occupants in age of 20s, virtually in an environment for their routine life, focusing on the aspects of indoor familiarity (spatial cognition), psychological stress and decision makings. For indoor familiarity, it is interested in three factors, i.e., the familiarity to exits and risky places as well as the satisfaction degree of the current indoor sign installation. According to the results, males have a higher average familiarity with the indoor exits while both genders have a relatively low level of risky place awareness. These two factors are positively correlated with the satisfaction degree of the current installation of the indoor signs, and this correlation is more evident for the exit familiarity. The integration of the height factor with the other two indoor familiarity factors can improve the degree of indoor sign satisfaction. For psychological stress, this study concentrates on the situated cognition of moving difficulty, nervousness, and speed reduction when using a bending posture during the fire evacuation to avoid smoke inhalation. The results have shown that both genders have a similar mid-level of hardness sensation. The females have a higher average level of nervousness, while males have a higher average level of speed reduction sensation. This study has assumed that the growing indoor spatial cognition can help ease the psychological hardness and nervousness. However, it only seems to be true after reaching a certain level. When integrating the effects from indoor familiarity and the other two psychological factors, the correlation to the sensation of speed change can be strengthened, based on a stronger positive correlation with the integrated factors. This study has also investigated the participants’ attitude to the navigation support during evacuation, and the majority of the participants have shown positive attitudes. For following the guidance under some extreme cases, i.e., changing to a longer path and to an alternative exit, the majority of the participants has shown the confidence of keeping trusting the guidance service. These decisions are affected by the combined influences from indoor familiarity, psychological stress, and attitude of using navigation service. For the decision time of the selected extreme cases, it costs more time in average for deciding to use a longer route than to use an alternative exit, and this situation is more evident for the female participants. This requires further considerations when designing a personalized smartphone-based navigation app. This study has also investigated the calming factors for people being trapped during evacuation. The top consideration is the distance to the nearest firefighters, and the following considerations are the current fire conditions in the surrounding environment and the locations of all firefighters. The ranking of the latter two considerations is very gender-dependent according to the results.

Keywords: fire response performances, indoor spatial cognition, situated cognition, survey analysis

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Authors: Hosein Falahaty, Hitoshi Gotoh, Abbas Khayyer

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Performance of a Hamiltonian based particle method in simulation of nonlinear structural dynamics is subjected to investigation in terms of stability and accuracy. The governing equation of motion is derived based on Hamilton's principle of least action, while the deformation gradient is obtained according to Weighted Least Square method. The hyper-elasticity models of Saint Venant-Kirchhoff and a compressible version similar to Mooney- Rivlin are engaged for the calculation of second Piola-Kirchhoff stress tensor, respectively. Stability along with accuracy of numerical model is verified by reproducing critical stress fields in static and dynamic responses. As the results, although performance of Hamiltonian based model is evaluated as being acceptable in dealing with intense extensional stress fields, however kinds of instabilities reveal in the case of violent collision which can be most likely attributed to zero energy singular modes.

Keywords: Hamilton's principle of least action, particle-based method, hyper-elasticity, analysis of stability

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Authors: Z. A. Ahmad, R. C. Omar, I. Z. Baharuddin, R. Roslan

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Assessments of social vulnerability, carried out holistically, can provide an important guide to the planning process and to decisions on resource allocation at various levels, and can help to raise public awareness of geo-hazard risks. The assessments can help to provide answers for basic questions such as the human vulnerability at the geo-hazard prone or disaster areas causing health damage, economic loss, loss of natural heritage and vulnerability impact of extreme natural hazard event. To overcome these issues, integrated framework for assessing the increasing human vulnerability to environmental changes caused by geo-hazards will be introduced using an indicator from landslide risk map that is related to agent based modeling platform. The indicators represent the underlying factors, which influence a community’s ability to deal with and recover from the damage associated with geo-hazards. Scope of this paper is particularly limited to landslides.

Keywords: social, vulnerability, geo-hazard, methodology, indicators

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Authors: Sagir M. Yusuf, Chris Baber

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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Armansyah, I. P. Almanar, M. Saiful Bahari Shaari, M. Shamil Jaffarullah

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Finite element approach have been used via three-dimensional models by using Altair Hyper Work, a commercially available software, to describe heat gradients along the welding zones (axially and coronaly) in Friction Stir Welding (FSW). Transient thermal finite element analyses are performed in AA 6061-T6 Aluminum Alloy to obtain temperature distribution in the welded aluminum plates during welding operation. Heat input from tool shoulder and tool pin are considered in the model. A moving heat source with a heat distribution simulating the heat generated by frictions between tool shoulder and work piece is used in the analysis. The developed model was then used to show the effect of various input parameters such as total rate of welding speed and rotational speed on temperature distribution in the work piece.

Keywords: Frictions Stir Welding (FSW), temperature distribution, Finite Element Method (FEM), altair hyperwork

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Authors: M. A. Ghebouli, H. Choutri, B. Ghebouli , M. Fatmi, L. Louail

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We employed the density-functional perturbation theory (DFPT) within the generalized gradient approximation (GGA), the local density approximation (LDA) and the virtual-crystal approximation (VCA) to study the effect of composition on the structure, stability, energy gaps, electron effective mass, the dynamic effective charge, optical and acoustical phonon frequencies and static and high dielectric constants of the rock-salt CaxMg1-xSe and CaxMg1-xTe alloys. The computed equilibrium lattice constant and bulk modulus show an important deviation from the linear concentration. From the Voigt-Reuss-Hill approximation, CaxMg1-xSe and CaxMg1-xTe present lower stiffness and lateral expansion. For Ca content ranging between 0.25-0.75, the elastic constants, energy gaps, electron effective mass and dynamic effective charge are predictions. The elastic constants and computed phonon dispersion curves indicate that these alloys are mechanically stable.

Keywords: CaxMg1-xSe, CaxMg1-xTe, band structure, phonon

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Authors: Ci Lin, Tet Yeap, Iluju Kiringa

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This paper introduces the subspace rotation algorithm (SRA) to train the Restricted Hopfield Network (RHN) as an auto-associative memory. Subspace rotation algorithm is a gradient-free subspace tracking approach based on the singular value decomposition (SVD). In comparison with Backpropagation Through Time (BPTT) on training RHN, it is observed that SRA could always converge to the optimal solution and BPTT could not achieve the same performance when the model becomes complex, and the number of patterns is large. The AUTS case study showed that the RHN model trained by SRA could achieve a better structure of attraction basin with larger radius(in general) than the Hopfield Network(HNN) model trained by Hebbian learning rule. Through learning 10000 patterns from MNIST dataset with RHN models with different number of hidden nodes, it is observed that an several components could be adjusted to achieve a balance between recovery accuracy and noise resistance.

Keywords: hopfield neural network, restricted hopfield network, subspace rotation algorithm, hebbian learning rule

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Authors: Jiayue Yang

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Based on an analysis of China's database of certified disabled persons in 2021, this study reveals several key findings. Firstly, the proportion of certified mentally disabled persons among China's certified disabled population (Certification rate 1) shows a decreasing distribution from the East to the West and from the South to the North. Secondly, the spatial distribution of the number of mentally disabled persons per 1,000 people holding certificates (certification rate 2) shows a relatively scattered pattern, with significant variations observed between cities in the eastern region. However, on an overall scale, a south-north gradient can still be observed, with higher rates in the North and lower rates in the west, while the central region demonstrates higher rates compared to the western region. The variation in the rate of mentally handicapped certificates among regions is influenced not only by traditional culture and welfare level but also exhibits a certain correlation with the level of economic development.

Keywords: certified disabled persons, mentally disabled persons, spatial distribution, China

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Authors: G. M. Vlasceanu, H. Iovu, E. Vasile, M. Ionita

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Herein, the synthesis and characterization of chitosan-gelatin highly porous scaffold reinforced with graphene oxide, and hydroxyapatite (HAp), crosslinked with genipin was targeted. In tissue engineering, chitosan and gelatin are two of the most robust biopolymers with wide applicability due to intrinsic biocompatibility, biodegradability, low antigenicity properties, affordability, and ease of processing. HAp, per its exceptional activity in tuning cell-matrix interactions, is acknowledged for its capability of sustaining cellular proliferation by promoting bone-like native micro-media for cell adjustment. Genipin is regarded as a top class cross-linker, while graphene oxide (GO) is viewed as one of the most performant and versatile fillers. The composites with natural bone HAp/biopolymer ratio were obtained by cascading sonochemical treatments, followed by uncomplicated casting methods and by freeze-drying. Their structure was characterized by Fourier Transform Infrared Spectroscopy and X-ray Diffraction, while overall morphology was investigated by Scanning Electron Microscopy (SEM) and micro-Computer Tomography (µ-CT). Ensuing that, in vitro enzyme degradation was performed to detect the most promising compositions for the development of in vivo assays. Suitable GO dispersion was ascertained within the biopolymer mix as nanolayers specific signals lack in both FTIR and XRD spectra, and the specific spectral features of the polymers persisted with GO load enhancement. Overall, correlations between the GO induced material structuration, crystallinity variations, and chemical interaction of the compounds can be correlated with the physical features and bioactivity of each composite formulation. Moreover, the HAp distribution within follows an auspicious density gradient tuned for hybrid osseous/cartilage matter architectures, which were mirrored in the mice model tests. Hence, the synthesis route of a natural polymer blend/hydroxyapatite-graphene oxide composite material is anticipated to emerge as influential formulation in bone tissue engineering. Acknowledgement: This work was supported by the project 'Work-based learning systems using entrepreneurship grants for doctoral and post-doctoral students' (Sisteme de invatare bazate pe munca prin burse antreprenor pentru doctoranzi si postdoctoranzi) - SIMBA, SMIS code 124705 and by a grant of the National Authority for Scientific Research and Innovation, Operational Program Competitiveness Axis 1 - Section E, Program co-financed from European Regional Development Fund 'Investments for your future' under the project number 154/25.11.2016, P_37_221/2015. The nano-CT experiments were possible due to European Regional Development Fund through Competitiveness Operational Program 2014-2020, Priority axis 1, ID P_36_611, MySMIS code 107066, INOVABIOMED.

Keywords: biopolymer blend, ectopic osteoinduction, graphene oxide composite, hydroxyapatite

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Authors: Bohli Afef

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The fifth-generation (5G) wireless systems is featured by extreme densities of cell stations to overcome the higher future demand. Hence, interference management is a crucial challenge in 5G ultra-dense cellular networks. In contrast to the classical inter-cell interference coordination approach, which is no longer fit for the high density of cell-tiers, this paper proposes a novel virtual coordination based on the dynamic common cognitive monitor channel protocol to deal with the inter-cell interference issue. A tractable and flexible model for the coverage probability of a typical user is developed through the use of the stochastic geometry model. The analyses of the performance of the suggested protocol are illustrated both analytically and numerically in terms of coverage probability.

Keywords: ultra dense heterogeneous networks, dynamic common channel protocol, cognitive radio, stochastic geometry, coverage probability

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Authors: A.Zitouni, S.Bentata, B.Bouadjemi, T.Lantri, W. Benstaali, Z.Aziz, S.Cherid, A. Sefir

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Structural, electronic, and magnetic properties of Co and Mn-doped CdTe have been studied by employing the full potential linear augmented plane waves (FP-LAPW) method within the spin-polarized density functional theory (DFT). The electronic exchange-correlation energy is described by generalized gradient approximation (GGA) as exchange–correlation (XC) potential. We have calculated the lattice parameters, bulk modulii and the first pressure derivatives of the bulk modulii, spin-polarized band structures, and total and local densities of states. The value of calculated magnetic moment per Co and Mn impurity atoms is found to be 2.21 µB for CdCoTe and 3.20 µB for CdMnTe. The calculated densities of states presented in this study identify the half-metallic of Co and Mn-doped CdTe.

Keywords: electronic structure, density functional theory, band structures, half-metallic, magnetic moment

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Authors: Bharatendra Rai

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The sequence of words in text data has long-term dependencies and is known to suffer from vanishing gradient problems when developing deep learning models. Although recurrent networks such as long short-term memory networks help to overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine the advantages of long short-term memory networks and convolutional neural networks can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning.

Keywords: long short-term memory networks, convolutional recurrent networks, text classification, hyperparameter tuning, Tukey honest significant differences

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Authors: Mengdie Ruan

Abstract:

The authors investigate how subjective well-being (SWB) and social trust changed in China over the period 2010–2020 by relying on data from six rounds of the China Family Panel Studies (CFPS), then re-examine Easterlin’s hypothesis for China, with a more focus on the role of social trust and estimate income-compensating differentials for social trust. They find that the evolution of well-being is not sensitive to the measures of well-being one uses. Specifically, self-reported life satisfaction scores and hedonic happiness scores experienced a significant increase across all income groups from 2010 to 2020. Social trust seems to have increased based on CFPS in China for all socioeconomic classes in recent years, and male, urban resident individuals with higher income have a higher social trust at a given point in time and over time. However, when we use an alternative measure of social trust, out-group trust, which is a more valid measure of generalized trust and represents “most people”, social trust in China literally declines, and the level is extremely low. In addition, this paper also suggests that in the typical query on social trust, the term "most people" mostly denotes in-groups in China, which contrasts sharply with most Western countries where it predominantly connotes out-groups. Individual fixed effects analysis of well-being that controls for time-invariant variables reveals social trust and relative social status are important correlates of life satisfaction and happiness, whereas absolute income plays a limited role in boosting an individual’s well-being. The income-equivalent value for social capital is approximately tripling of income. It has been found that women, urban and coastal residents, and people with higher income, young people, those with high education care more about social trust in China, irrespective of measures on SWB. Policy aiming at preserving and enhancing SWB should focus on social capital besides economic growth.

Keywords: subjective well-being, life satisfaction, happiness, social trust, China

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Authors: Martin Cermak, Tomas Karasek, Jaroslav Rojicek

Abstract:

The key role in phenomenological modelling of cyclic plasticity is good understanding of stress-strain behaviour of given material. There are many models describing behaviour of materials using numerous parameters and constants. Combination of individual parameters in those material models significantly determines whether observed and predicted results are in compliance. Parameter identification techniques such as random gradient, genetic algorithm, and sensitivity analysis are used for identification of parameters using numerical modelling and simulation. In this paper genetic algorithm and sensitivity analysis are used to study effect of 4 parameters of modified AbdelKarim-Ohno cyclic plasticity model. Results predicted by Finite Element (FE) simulation are compared with experimental data from biaxial ratcheting test with semi-elliptical loading path.

Keywords: genetic algorithm, sensitivity analysis, inverse approach, finite element method, cyclic plasticity, ratcheting

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