Search results for: Generalized Weak Interactions

Authors: Samuel Oluwafemi Oyamakin, Angela Unna Chukwu

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Richrads growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richards growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richards growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richards nonlinear growth models better than the classical Richards growth model.

Keywords: height, diameter at breast height, DBH, hyperbolic sine function, Pinus caribaea, Richards' growth model

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Authors: M. Liebherr, P. Schubert, S. Kersten, C. Dietz, L. Franz, C. T. Haas

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With a long history, dual-task has become one of the most intriguing research fields regarding human brain functioning and cognition. However, findings considering effects of task-interrelations are limited (especially, in combined motor and cognitive tasks). Therefore, we aimed at developing a measurement system in order to analyse interrelation effects of cognitive and motor tasks. On the one hand, the present study demonstrates the applicability of the measurement system and on the other hand first results regarding a systematization of different task combinations are shown. Future investigations should combine imagine technologies and this developed measurement system.

Keywords: dual-task, interference, cognition, measurement

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Authors: Mohammad Younus Bhat

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The quaternion offset linear canonical transform (QOLCT), which isa time-shifted and frequency-modulated version of the quaternion linear canonical transform (QLCT), provides a more general framework of most existing signal processing tools. For the generalized QOLCT, the classical Heisenberg’s and Lieb’s uncertainty principles have been studied recently. In this paper, we first define the short-time quaternion offset linear canonical transform (ST-QOLCT) and drive its relationship with the quaternion Fourier transform (QFT). The crux of the paper lies in the generalization of several well-known uncertainty principles for the ST-QOLCT, including Donoho-Stark’s uncertainty principle, Hardy’s uncertainty principle, Beurling’s uncertainty principle, and the logarithmic uncertainty principle.

Keywords: Quaternion Fourier transform, Quaternion offset linear canonical transform, short-time quaternion offset linear canonical transform, uncertainty principle

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Authors: Nurbanu Guzey, S. Jagannathan

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Locating radio controlled (RC) devices using their unintended emissions has a great interest considering security concerns. Weak nature of these emissions requires near field localization approach since it is hard to detect these signals in far field region of array. Instead of only angle estimation, near field localization also requires range estimation of the source which makes this method more complicated than far field models. Challenges of locating such devices in a near field region and real time environment are analyzed in this paper. An ESPRIT like near field localization scheme is utilized for both angle and range estimation. 1-D search with symmetric subarrays is provided. Two 7 element uniform linear antenna arrays (ULA) are employed for locating RC source. Experiment results of location estimation for one unintended emitting walkie-talkie for different positions are given.

Keywords: localization, angle of arrival (AoA), range estimation, array signal processing, ESPRIT, Uniform Linear Array (ULA)

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Authors: F. Pires, V. Geraldo, O. N. Oliveira Jr., M. Raposo

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Catechins are powerful antioxidants which have attractive properties useful for tumor therapy. Considering their antioxidant activity, these molecules can act as a scavenger of the reactive oxygen species (ROS), alleviating the damage of cell membrane induced by oxidative stress. The complexity and dynamic nature of the cell membrane compromise the analysis of the biophysical interactions between drug and cell membrane and restricts the transport or uptake of the drug by intracellular targets. To avoid the cell membrane complexity, we used biomimetic systems as liposomes and Langmuir monolayers to study the interaction between catechin and membranes at the molecular level. Liposomes were formed after the dispersion of anionic 1,2-dipalmitoyl-sn-glycero-3-[phospho-rac-(1-glycerol)(sodium salt) (DPPG) phospholipids in an aqueous solution, which mimic the arrangement of lipids in natural cell membranes and allows the entrapment of catechins. Langmuir monolayers were formed after dropping amphiphilic molecules, DPPG phospholipids, dissolved in an organic solvent onto the water surface. In this work, we mixed epigallocatechin-3-gallate (EGCG) with DPPG liposomes and exposed them to ultra-violet radiation in order to evaluate the antioxidant potential of these molecules against oxidative stress induced by radiation. The presence of EGCG in the mixture decreased the rate of lipid peroxidation, proving that EGCG protects membranes through the quenching of the reactive oxygen species. Considering the high amount of hydroxyl groups (OH groups) on structure of EGCG, a possible mechanism to these molecules interact with membrane is through hydrogen bonding. We also investigated the effect of EGCG at various concentrations on DPPG Langmuir monolayers. The surface pressure isotherms and infrared reflection-absorption spectroscopy (PM-IRRAS) results corroborate with absorbance results preformed on liposome-model, showing that EGCG interacts with polar heads of the monolayers. This study elucidates the physiological action of EGCG which can be incorporated in lipid membrane. These results are also relevant for the improvement of the current protocols used to incorporate catechins in drug delivery systems.

Keywords: catechins, lipid membrane, anticancer agent, molecular interactions

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Authors: Aysha Alshehri

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This paper provides a literature review of the sources of women’s rights under the Saudi legal framework, taking account of the constitutional primacy of Sharia under the Saudi legal system as well as the state’s obligations under international law. Building on one of the central aims of the paper, it conducts an exploration of how Saudi Arabia already has or might be further able to more clearly delineate its position and reservations in the adoptions of international human rights agreements while preserving its core religious beliefs and societal practices in regard to women’s rights at the domestic level. In this regard, the paper will consider the apparent tension between certain jurisprudential and customary aspects on gender equality and contemporary discourses of women’s rights from within and outside the Muslim world. Particular attention will be devoted to the question of the causes behind the lack of direct application of women’s rights mentioned by international reports and any challenges this may bring in the contexts of Saudi Arabia’s evolving gender equality policies.

Keywords: Islamic Constitution, executive actions, gender equality, judicial review

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Authors: Shama Urooj

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The present work investigates the relationship among financial inclusion, modernization, and energy performance in SCO member countries during the years 2011–2021. PCA is used to create composite indexes of financial inclusion, modernization, and energy performance. We used panel regression models that are both reliable and heteroscedasticity-consistent to look at the relationship among variables. The findings indicate that financial inclusion (FI) and modernization, along with the increased FDI, all appear to contribute to the energy performance in the SCO member countries. However, per capita GDP has a negative impact on energy performance. These results are unbiased and consistent with the robust results obtained by applying different econometric models. Feasible Generalized Least Square (FGLS) estimation is also used for checking the uniformity of the main model results. This research work concludes that there has been no policy coherence in SCO member countries regarding the coordination of growing financial inclusion and modernization for energy sustainability in recent years. In order to improve energy performance with modern development, policies regarding financial inclusion and modernization need be integrated both at national as well as international levels.

Keywords: financial inclusion, energy performance, modernization, technological development, SCO.

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Authors: Yuanjin Liu

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Retirement withdrawal strategies are very important to minimize the probability of ruin in retirement. The ruin probability is modeled as a function of initial withdrawal age, gender, asset allocation, inflation rate, and initial withdrawal rate. The ruin probability is obtained based on the 2019 period life table for the Social Security, IRS Required Minimum Distribution (RMD) Worksheets, US historical bond and equity returns, and inflation rates using simulation. Several popular machine learning algorithms of the generalized additive model, random forest, support vector machine, extreme gradient boosting, and artificial neural network are built. The model validation and selection are based on the test errors using hyperparameter tuning and train-test split. The optimal model is recommended for retirees to monitor the ruin probability. The optimal withdrawal strategy can be obtained based on the optimal predictive model.

Keywords: ruin probability, retirement withdrawal strategies, predictive models, optimal model

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Authors: Rachana Tank, Donald. M. Lyall, Kristin Flegal, Joey Ward, Jonathan Cavanagh

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Alzheimer’s research UK estimates by 2050, 2 million individuals will be living with Late Onset Alzheimer’s disease (LOAD). However, individuals experience considerable cognitive deficits and brain pathology over decades before reaching clinically diagnosable LOAD and studies have utilised gene candidate studies such as genome wide association studies (GWAS) and polygenic risk (PGR) scores to identify high risk individuals and potential pathways. This investigation aims to determine whether high genetic risk of LOAD is associated with worse brain MRI and cognitive performance in healthy older adults within the UK Biobank cohort. Previous studies investigating associations of PGR for LOAD and measures of MRI or cognitive functioning have focused on specific aspects of hippocampal structure, in relatively small sample sizes and with poor ‘controlling’ for confounders such as smoking. Both the sample size of this study and the discovery GWAS sample are bigger than previous studies to our knowledge. Genetic interaction between loci showing largest effects in GWAS have not been extensively studied and it is known that APOE e4 poses the largest genetic risk of LOAD with potential gene-gene and gene-environment interactions of e4, for this reason we  also analyse genetic interactions of PGR with the APOE e4 genotype. High genetic loading based on a polygenic risk score of 21 SNPs for LOAD is associated with worse brain MRI and cognitive outcomes in healthy individuals within the UK Biobank cohort. Summary statistics from Kunkle et al., GWAS meta-analyses (case: n=30,344, control: n=52,427) will be used to create polygenic risk scores based on 21 SNPs and analyses will be carried out in N=37,000 participants in the UK Biobank. This will be the largest study to date investigating PGR of LOAD in relation to MRI. MRI outcome measures include WM tracts, structural volumes. Cognitive function measures include reaction time, pairs matching, trail making, digit symbol substitution and prospective memory. Interaction of the APOE e4 alleles and PGR will be analysed by including APOE status as an interaction term coded as either 0, 1 or 2 e4 alleles. Models will be adjusted partially for adjusted for age, BMI, sex, genotyping chip, smoking, depression and social deprivation. Preliminary results suggest PGR score for LOAD is associated with decreased hippocampal volumes including hippocampal body (standardised beta = -0.04, P = 0.022) and tail (standardised beta = -0.037, P = 0.030), but not with hippocampal head. There were also associations of genetic risk with decreased cognitive performance including fluid intelligence (standardised beta = -0.08, P<0.01) and reaction time (standardised beta = 2.04, P<0.01). No genetic interactions were found between APOE e4 dose and PGR score for MRI or cognitive measures. The generalisability of these results is limited by selection bias within the UK Biobank as participants are less likely to be obese, smoke, be socioeconomically deprived and have fewer self-reported health conditions when compared to the general population. Lack of a unified approach or standardised method for calculating genetic risk scores may also be a limitation of these analyses. Further discussion and results are pending.

Keywords: Alzheimer's dementia, cognition, polygenic risk, MRI

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Authors: Areej M. Abduldaim, Nadia M. G. Al-Saidi

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Algebra is one of the important fields of mathematics. It concerns with the study and manipulation of mathematical symbols. It also concerns with the study of abstractions such as groups, rings, and fields. Due to the development of these abstractions, it is extended to consider other structures, such as vectors, matrices, and polynomials, which are non-numerical objects. Computer algebra is the implementation of algebraic methods as algorithms and computer programs. Recently, many algebraic cryptosystem protocols are based on non-commutative algebraic structures, such as authentication, key exchange, and encryption-decryption processes are adopted. Cryptography is the science that aimed at sending the information through public channels in such a way that only an authorized recipient can read it. Ring theory is the most attractive category of algebra in the area of cryptography. In this paper, we employ the algebraic structure called skew -Armendariz rings to design a neoteric algorithm for zero knowledge proof. The proposed protocol is established and illustrated through numerical example, and its soundness and completeness are proved.

Keywords: cryptosystem, identification, skew π-Armendariz rings, skew polynomial rings, zero knowledge protocol

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Authors: M. Khalfa, H. Khachai, F. Chiker, K. Bougherara, R. Khenata, G. Murtaza, M. Harmel

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A theoretical study of structural, elastic, electronic and thermodynamic properties of Fe2VX, (with X = Al and Ga), were studied by means of the full-relativistic version of the full-potential augmented plane wave plus local orbitals method. For exchange and correlation potential we used both generalized-gradient approximation (GGA) and local-density approximation (LDA). Our calculated ground state properties like as lattice constants, bulk modulus and elastic constants appear more accurate when we employed the GGA rather than the LDA approximation, and these results agree very well with the available experimental and theoretical data. Further, prediction of the thermal effects on some macroscopic properties of Fe2VAl and Fe2VGa are given in this paper using the quasi-harmonic Debye model in which the lattice vibrations are taken into account. We have obtained successfully the variations of the primitive cell volume, volume expansion coefficient, heat capacities and Debye temperature with pressure and temperature in the ranges of 0–40 GPa and 0–1500 K.

Keywords: full Heusler, FP-LAPW, electronic properties, thermal properties

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Authors: Anne Öman

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Today in Sweden and in other countries, a variety of digital artefacts, such as laptops, tablets, interactive whiteboards, are being used at all school levels. From an educational perspective, digital artefacts challenge traditional teaching because they provide a range of modes for expression and communication and are not limited to the traditional medium of paper. Digital technologies offer new opportunities for representations and physical interactions with objects, which put forward the role of the body in interaction and learning. From a multimodal perspective the emphasis is on the use of multiple semiotic resources for meaning- making and the study presented here has examined the differential use of semiotic resources by pupils interacting in a digitally designed task in a primary school context. The instances analyzed in this paper come from a case study where the learning task was to create an advertising film in a film-software. The study in focus involves the analysis of a single case with the emphasis on the examination of the classroom setting. The research design used in this paper was based on a micro ethnographic perspective and the empirical material was collected through video recordings of small-group work in order to explore pupils’ communication within the group activity. The designed task described here allowed students to build, share, collaborate upon and publish the redesigned products. The analysis illustrates the variety of communicative modes such as body position, gestures, visualizations, speech and the interaction between these modes and the representations made by the pupils. The findings pointed out the importance of embodied communication during the small- group processes from a learning perspective as well as a pedagogical understanding of pupils’ representations, which were similar from a cultural literacy perspective. These findings open up for discussions with further implications for the school practice concerning the small- group processes as well as the redesigned products. Wider, the findings could point out how multimodal interactions shape the learning experience in the meaning-making processes taking into account that language in a globalized society is more than reading and writing skills.

Keywords: communicative learning, interactive learning environments, pedagogical issues, primary school education

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Authors: Maarten J. Van der Burgt

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A universe containing matter and antimatter can only exist when matter and antimatter repel each other. Such a system, where like attracts like and like repels unlike, will always expand. Calculations made for such a symmetric universe demonstrate that the expansion is consistent with Hubble’s law, the observed increase in the expansion velocity with time, the initial high acceleration and the foam structure of the universe. Conversely, these observations can be considered as proof for a symmetrical universe and for antimatter possessing a negative gravitational mass. A second proof can be found by reinterpreting the behavior of relativistic moving charged particles. Attributing their behavior to a charge defect of √(1-v2/c2) instead of to a mass defect of 1/√(1-v2/c2) makes it plausible that gravitation is an electromagnetic force, as already suggested by Feynman. This would automatically imply that antimatter has a negative gravitational mass. These proofs underpin the untenability of the Weak Equivalence Principle which states that in a gravitational field all structure less point-like particles follow the same path.

Keywords: celestial mechanics, cosmology, gravitation astrophysics, origin of structure, miscellaneous (matter and antimatter)

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Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

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In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

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Authors: Ali Noorzad, Ehsan Badakhshan, Shima Zameni

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The present paper is focused on a generalized failure criterion for geomaterials with cross-anisotropy. The cyclic behavior of granular material primarily depends on the nature and arrangement of constituent particles, particle size, and shape that affect fabric anisotropy. To account for the influence of loading directions on strength variations, an anisotropic variable in terms of the invariants of the stress tensor and fabric into the failure criterion is proposed. In an extension to original CANAsand constitutive model two concepts namely critical state and compact state play paramount roles as all of the moduli and coefficients are related to these states. The applicability of the present model is evaluated through comparisons between the predicted and the measured results. All simulations have demonstrated that the proposed constitutive model is capable of modeling the cyclic behavior of sand with inherent anisotropy.

Keywords: fabric, cohesionless media, cyclic loading, critical state, compact state, CANAsand constitutive model

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Authors: Olubukayo-Opeyemi Oyetayo, Oscar Mendez-Lucio, Andreas Bender, Hans Kiefer

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The thermal melting curve of a protein provides information on its conformational stability and could provide cues on its aggregation behavior. Naturally-occurring osmolytes have been shown to improve the thermal stability of most proteins in a concentration-dependent manner. They are therefore commonly employed as additives in therapeutic protein purification and formulation. A number of intertwined and seemingly conflicting mechanisms have been put forward to explain the observed stabilizing effects, the most prominent being the preferential exclusion mechanism. We attempted to probe and summarize molecular mechanisms for thermal stabilization of a monoclonal antibody (mAb) by developing quantitative structure-activity relationships using a rationally-selected library of 120 osmolyte-like compounds in the polyhydric alcohols, amino acids and methylamines classes. Thermal stabilization potencies were experimentally determined by thermal shift assays based on differential scanning fluorimetry. The cross-validated QSAR model was developed by partial least squares regression using descriptors generated from Molecular Operating Environment software. Careful evaluation of the results with the use of variable importance in projection parameter (VIP) and regression coefficients guided the selection of the most relevant descriptors influencing mAb thermal stability. For the mAb studied and at pH 7, the thermal stabilization effects of tested compounds correlated positively with their fractional polar surface area and inversely with their fractional hydrophobic surface area. We cannot claim that the observed trends are universal for osmolyte-protein interactions because of protein-specific effects, however this approach should guide the quick selection of (de)stabilizing compounds for a protein from a chemical library. Further work with a large variety of proteins and at different pH values would help the derivation of a solid explanation as to the nature of favorable osmolyte-protein interactions for improved thermal stability. This approach may be beneficial in the design of novel protein stabilizers with optimal property values, especially when the influence of solution conditions like the pH and buffer species and the protein properties are factored in.

Keywords: thermal stability, monoclonal antibodies, quantitative structure-activity relationships, osmolytes

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Authors: Deeksha Arora

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The study aims to explore the applicability of the widely used asset pricing models, namely, Capital Asset Pricing Model (CAPM) and the Fama-French Four Factor Model in the Indian equity market. The study will be based on the companies that form part of the Nifty Fifty Index for a period of five years: 2011 to 2016. The asset pricing model is examined by forming portfolios on the basis of three variables – market capitalization (size effect), book-to-market equity ratio (value effect) and profitability. The study provides a basis to test the presence of the Fama-French Four factor model in Indian stock market. This study may provide a basis for future research in the generalized asset pricing model comprising of multiple risk factors.

Keywords: book to market equity, Fama French four factor model, market capitalization, profitability, size effect, value effect

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Authors: Mahdi Bazarganigilani

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Aortic enlargement, also known as an aortic aneurysm, can occur when the walls of the aorta become weak. This disease can become deadly if overlooked and undiagnosed. In this paper, a computer-aided diagnosis (CAD) system was introduced to accurately diagnose aortic enlargement from chest x-ray images. An enhanced convolutional neural network (CNN) was employed and then trained by transfer learning by using three different main areas from the original images. The areas included the left lung, heart, and right lung. The accuracy of the system was then evaluated on 1001 samples by using 4-fold cross-validation. A promising accuracy of 90% was achieved in terms of the F-measure indicator. The results showed using different areas from the original image in the training phase of CNN could increase the accuracy of predictions. This encouraged the author to evaluate this method on a larger dataset and even on different CAD systems for further enhancement of this methodology.

Keywords: computer-aided diagnosis systems, aortic enlargement, chest X-ray, image processing, convolutional neural networks

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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: Konstantin Nefedev, Petr Andriushchenko

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Usually under the frustrated magnetics, it understands such materials, in which ones the interaction between located magnetic moments or spins has competing character, and can not to be satisfied simultaneously. The most well-known and simplest example of the frustrated system is antiferromagnetic Ising model on the triangle. Physically, the existence of frustrations means, that one cannot select all three pairs of spins anti-parallel in the basic unit of the triangle. In physics of the interacting particle systems, the vector models are used, which are constructed on the base of the pair-interaction law. Each pair interaction energy between one-component vectors can take two opposite in sign values, excluding the case of zero. Mathematically, the existence of frustrations in system means that it is impossible to have all negative energies of pair interactions in the Hamiltonian even in the ground state (lowest energy). In fact, the frustration is the excitation, which leaves in system, when thermodynamics does not work, i.e. at the temperature absolute zero. The origin of the frustration is the presence at least of one ''unsatisfied'' pair of interacted spins (magnetic moments). The minimal relative quantity of these excitations (relative quantity of frustrations in ground state) can be used as parameter of frustration. If the energy of the ground state is Egs, and summary energy of all energy of pair interactions taken with a positive sign is Emax, that proposed frustration parameter pf takes values from the interval [0,1] and it is defined as pf=(Egs+Emax)/2Emax. For antiferromagnetic Ising model on the triangle pf=1/3. We calculated the parameters of frustration in thermodynamic limit for different 2D periodical structures of Ising dipoles, which were on the ribs of the lattice and interact by means of the long-range dipolar interaction. For the honeycomb lattice pf=0.3415, triangular - pf=0.2468, kagome - pf=0.1644. All dependencies of frustration parameter from 1/N obey to the linear law. The given frustration parameter allows to consider the thermodynamics of all magnetic systems from united point of view and to compare the different lattice systems of interacting particle in the frame of vector models. This parameter can be the fundamental characteristic of frustrated systems. It has no dependence from temperature and thermodynamic states, in which ones the system can be found, such as spin ice, spin glass, spin liquid or even spin snow. It shows us the minimal relative quantity of excitations, which ones can exist in system at T=0.

Keywords: frustrations, parameter of order, statistical physics, magnetism

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Authors: Ha Hai Duong, Amnon Levy Livermore, Kankesu Jayanthakumaran, Oleg Yerokhin

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The issues of economic development, the environment and human health have been investigated since 1990s. Previous researchers have found different empirical evidences of the relationship between income and environmental pollution, health as determinant of economic growth, and the effects of income and environmental pollution on health in various regions of the world. This paper concentrates on integrative relationship analysis of GDP, carbon dioxide emissions, and health services and population health in context of Vietnam. We applied the dynamic generalized method of moments (GMM) estimation on datasets of Vietnam’s sixty-three provinces for the years 2000-2010. Our results show the significant positive effect of GDP on emissions and the dependence of population health on emissions and health services. We find the significant relationship between population health and GDP. Additionally, health services are significantly affected by population health and GDP. Finally, the population size too is other important determinant of both emissions and GDP.

Keywords: economic development, emissions, environmental pollution, health

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Authors: Catherine Vasnetsov, Victor Vasnetsov

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Context: Thermo-responsive polymers are materials that undergo significant changes in their physical properties in response to temperature changes. These polymers have gained significant attention in research due to their potential applications in various industries and medicine. However, the molecular mechanisms underlying their behavior are not well understood, particularly in relation to cosolvency, which is crucial for practical applications. Research Aim: This study aimed to theoretically investigate the phenomenon of cosolvency in long-chain polymers using the Flory-Huggins statistical-mechanical framework. The main objective was to understand the interactions between the polymer, solvent, and cosolvent under different conditions. Methodology: The research employed a combination of Monte Carlo computer simulations and advanced machine-learning methods. The Flory-Huggins mean field theory was used as the basis for the simulations. Spinodal graphs and ternary plots were utilized to develop an initial computer model for predicting polymer behavior. Molecular dynamic simulations were conducted to mimic real-life polymer systems. Machine learning techniques were incorporated to enhance the accuracy and reliability of the simulations. Findings: The simulations revealed that the addition of very low or very high volumes of cosolvent molecules resulted in smaller radii of gyration for the polymer, indicating poor miscibility. However, intermediate volume fractions of cosolvent led to higher radii of gyration, suggesting improved miscibility. These findings provide a possible microscopic explanation for the cosolvency phenomenon in polymer systems. Theoretical Importance: This research contributes to a better understanding of the behavior of thermo-responsive polymers and the role of cosolvency. The findings provide insights into the molecular mechanisms underlying cosolvency and offer specific predictions for future experimental investigations. The study also presents a more rigorous analysis of the Flory-Huggins free energy theory in the context of polymer systems. Data Collection and Analysis Procedures: The data for this study was collected through Monte Carlo computer simulations and molecular dynamic simulations. The interactions between the polymer, solvent, and cosolvent were analyzed using the Flory-Huggins mean field theory. Machine learning techniques were employed to enhance the accuracy of the simulations. The collected data was then analyzed to determine the impact of cosolvent volume fractions on the radii of gyration of the polymer. Question Addressed: The research addressed the question of how cosolvency affects the behavior of long-chain polymers. Specifically, the study aimed to investigate the interactions between the polymer, solvent, and cosolvent under different volume fractions and understand the resulting changes in the radii of gyration. Conclusion: In conclusion, this study utilized theoretical modeling and computer simulations to investigate the phenomenon of cosolvency in long-chain polymers. The findings suggest that moderate cosolvent volume fractions can lead to improved miscibility, as indicated by higher radii of gyration. These insights contribute to a better understanding of the molecular mechanisms underlying cosolvency in polymer systems and provide predictions for future experimental studies. The research also enhances the theoretical analysis of the Flory-Huggins free energy theory.

Keywords: molecular modelling, flory-huggins, cosolvency, stimuli-responsive polymers

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Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Andres Nieto-Leal, Victor N. Kaliakin, Tania P. Molina

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The nature of most engineering materials is quite complex. It is, therefore, difficult to devise a general mathematical model that will cover all possible ranges and types of excitation and behavior of a given material. As a result, the development of mathematical models is based upon simplifying assumptions regarding material behavior. Such simplifications result in some material idealization; for example, one of the simplest material idealization is to assume that the material behavior obeys the elasticity. However, soils are nonhomogeneous, anisotropic, path-dependent materials that exhibit nonlinear stress-strain relationships, changes in volume under shear, dilatancy, as well as time-, rate- and temperature-dependent behavior. Over the years, many constitutive models, possessing different levels of sophistication, have been developed to simulate the behavior geomaterials, particularly cohesive soils. Early in the development of constitutive models, it became evident that elastic or standard elastoplastic formulations, employing purely isotropic hardening and predicated in the existence of a yield surface surrounding a purely elastic domain, were incapable of realistically simulating the behavior of geomaterials. Accordingly, more sophisticated constitutive models have been developed; for example, the bounding surface elastoplasticity. The essence of the bounding surface concept is the hypothesis that plastic deformations can occur for stress states either within or on the bounding surface. Thus, unlike classical yield surface elastoplasticity, the plastic states are not restricted only to those lying on a surface. Elastoplastic bounding surface models have been improved; however, there is still need to improve their capabilities in simulating the response of anisotropically consolidated cohesive soils, especially the response in extension tests. Thus, in this work an improved constitutive model that can more accurately predict diverse stress-strain phenomena exhibited by cohesive soils was developed. Particularly, an improved rotational hardening rule that better simulate the response of cohesive soils in extension. The generalized definition of the bounding surface model provides a convenient and elegant framework for unifying various previous versions of the model for anisotropically consolidated cohesive soils. The Generalized Bounding Surface Model for cohesive soils is a fully three-dimensional, time-dependent model that accounts for both inherent and stress induced anisotropy employing a non-associative flow rule. The model numerical implementation in a computer code followed an adaptive multistep integration scheme in conjunction with local iteration and radial return. The one-step trapezoidal rule was used to get the stiffness matrix that defines the relationship between the stress increment and the strain increment. After testing the model in simulating the response of cohesive soils through extensive comparisons of model simulations to experimental data, it has been shown to give quite good simulations. The new model successfully simulates the response of different cohesive soils; for example, Cardiff Kaolin, Spestone Kaolin, and Lower Cromer Till. The simulated undrained stress paths, stress-strain response, and excess pore pressures are in very good agreement with the experimental values, especially in extension.

Keywords: bounding surface elastoplasticity, cohesive soils, constitutive model, modeling of geomaterials

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Authors: Edwin Njoroge Kimani, Alan M. Munyao

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Despite Kenya’s status as a regional economic powerhouse, it struggles with economic shocks that expose the consumers. This, however, seems not to affect major cooperates such as those in the telecommunication and energy sectors. Through their operations, they have not only been able to fluctuate prices at will but also they have been accused of curtailing their rivals from penetrating the market. This study, through literature review of the legal and institutional framework, reports and publications interrogates the law and uncovers the following; i) failings of the legal framework to define market dominance and abuse of such positions, ii) the participation of the state, iii) the inertia of the government to prosecute corporations that abuse their market dominance, iv) the role of the state as a market player and as a regulator through the Competition Authority of Kenya. This study concludes that the market distortion is as a result of weak legal and institutional framework as well as conflict of interest by the government. Not much has been researched in the field of competition law the greater East Africa. This research is intended to form part of the growing research in the field and inform legal reform.

Keywords: competition law, economic power, dominance, Kenya

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Authors: D. Reich, R. Stark

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To provide reliable and valid findings when evaluating innovative in-car devices in the automotive context highly realistic driving environments are recommended. Nowadays, in-car devices are mostly evaluated due to driving simulator studies followed by real car driving experiments. Driving simulators are characterized by high internal validity, but weak regarding ecological validity. Real car driving experiments are ecologically valid, but difficult to standardize, more time-robbing and costly. One economizing suggestion is to implement more immersive driving environments when applying driving simulator studies. This paper presents research comparing non-immersive standard PC conditions with mobile and highly immersive Oculus Rift conditions while performing the Lane Change Task (LCT). Subjective data with twenty participants show advantages regarding presence and immersion experience when performing the LCT with the Oculus Rift, but affect adversely cognitive workload and simulator sickness, compared to non-immersive PC condition.

Keywords: immersion, oculus rift, presence, situation awareness

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Authors: Madiha Tariq, Hena Rabbani

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Recently, cavity-optomechanics becomes an extensive research field that has manipulated the mechanical effects of light for coupling of the optical field with other physical objects specifically with regards to dynamical localization. We investigate the dynamical localization (both in momentum and position space) for a vibrational mirror in a Fabry-Pérot cavity driven by a single mode optical field and a transverse probe field. The weak probe field phenomenon results in classical chaos in phase space and spatio temporal dynamics in position |ψ(x)²| and momentum space |ψ(p)²| versus time show quantum localization in both momentum and position space. Also, we discuss the parametric dependencies of dynamical localization for a designated set of parameters to be experimentally feasible. Our work opens an avenue to manipulate the other optical phenomena and applicability of proposed work can be prolonged to turn-able laser sources in the future.

Keywords: dynamical localization, cavity optomechanics, Hamiltonian chaos, probe field

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Authors: T. K. Hung

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Terrorism acts have occurred across both developed and developing states, with well-identified motivation and causes. For many years, terrorism eradication has become a major topic yet only passive actions were taken in response to acts. The linkage between the location of terrorism occurrence and breeding ground is not well-documented, resulting in the passive approach used in counter-terrorism nowadays. The evaluation investigates all post-9/11 terrorism affairs considering their state capacity, safety, ease of border access control, religion diversity, and technology access, to measure the level of breeding ground of the states. Those "weak" states with poor border access control, resources capacity and domestic safety are the best breeding ground for terrorists. Although many attacks were caused by religious motivation, religion diversity does not predict the breeding ground. States with censored technology access, particular computer-mediated communication, predict on the terrorism breeding ground, moderated by the level of breeding ground of neighboring states.

Keywords: counter-terrorism, lethality, security, terrorism

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Authors: Reni M. Sagayaraj, Anand Gnana S. Selvam, Reynald R. Susainathan

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In this paper, we consider stochastic queueing models for Steady-state behavior of a multi-phase M/M/1 queue in random evolution subject to catastrophe failure. The arrival flow of customers is described by a marked Markovian arrival process. The service times of different type customers have a phase-type distribution with different parameters. To facilitate the investigation of the system we use a generalized phase-type service time distribution. This model contains a repair state, when a catastrophe occurs the system is transferred to the failure state. The paper focuses on the steady-state equation, and observes that, the steady-state behavior of the underlying queueing model along with the average queue size is analyzed.

Keywords: M/G/1 queuing system, multi-phase, random evolution, steady-state equation, catastrophe failure

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Authors: A. Eghbali, M. Goodarzi, M. Hagh Panahi

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In this article process of direct extrusion of axisymmetric bimetallic tube with conic die profile and constant Mandrel by upper bound method has been analyzed and finite element method is simulated. Deformation area is divided into six smaller deformation areas and are calculated by presenting two generalized velocity field and applicable input and output sections separately (velocity profile with logarithmic curve for input section and spherical velocity profile for materials output ) for each die profile in spherical coordinate system strain rate values in every deformation area. After internal power, shearing power and material friction power is obtained, extrusion force is calculated. The results of upper bound analysis method with given results from other researcher's experiments and simulation by finite parts method (Abaqus software) are compared for conic die.

Keywords: extrusion, upper bound, axisy metric, deformation velocity field

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