Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermostatted kinetic theory approach to the competition between cancer and immune system cells in an inhomogeneous system

The competition between a cancer and the immune system are modelled at cell scale in the framework of thermostatted kinetic theory. Cell activation and learning are reproduced by the increase of cell activity during interactions. The ﬂuctuations of system activity are controlled by a thermostat which reproduces the regulation of the learning process and memory loss through cell death. An algorithm, including spatial description and inspired from the direct simulation Monte Carlo (DSMC) method, is used to simulate stochastic trajectories for cell numbers and activities. We focus on the decisive role played by the thermostat. For ine ﬃ cient thermalization, the divergence of the number of cancer cells is obtained in spite of favored production of immune system cells. Conversely, when the activity ﬂuctuations are controlled, the development of cancer is contained even for weakened immune defenses. These results may be correlated to unexpected clinical observations in the case of di ﬀ erent cancers, such as carcinoma, lymphoma, and melanoma.
Análisis e implementación de estrategias: Caso SMA SAC

Resumen: El presente caso de negocios expone una empresa maquiladora peruana que servirá como base para el diagnóstico estratégico de los alumnos de la carrera de Administración de la Universidad de Lima. Con la información proporcionada, los estudiantes podrán realizar el análisis del microentorno, análisis de la cadena de valor, análisis funcional, elaboración de matrices estratégicas y diseño de cuadro de mando integral para controlar el desempeño organizacional. El caso fue diseñado por el docente en colaboración con los alumnos del curso de gestión de empresas y busca mostrar el emprendimiento del Sr. Málaga, quien logró posicionar rápidamente su empresa como la maquiladora líder en el mercado peruano.
Simultaneous Conventional and Plenoptic Background Oriented Schlieren Imaging

Plenoptic Background Oriented Schlieren (BOS) is an emerging schlieren technique that is capable of providing 3D qualitative and quantitative information about density gradients present in a wide range of fluid dynamics problems. In this work, the fundamental concepts of plenoptic BOS are reviewed before discussing an open-air experiment with a buoyant plume where both conventional BOS and plenoptic BOS measurements were acquired simultaneously. Both cameras had the same field-of-view for all experiments, and three different focal plane arrangements were explored: (1) the focal plane was set to the background positions and the plume varied between 11 different positions relative to this focal plane, (2) the focal plane was set to 635-millimeters in front of the background position, and (3) the nominal focal plane varied while the position of the plume remained fixed. Such discussion will provide insight on how the two techniques compare, and what additional work is required to better understand the results provided by these two imaging systems. https://ntrs.nasa. gov/search.jsp? R=20190027134 2019-08-31T14:55:07+00:00Z
Memory Properties Of Transformations Of Linear Processes And Symmetric Gini Correlation

A large class of time series processes can be modeled by linear processes, including a subset of the fractional ARIMA process. Transformation of time series is one of the most popular topics in recent years. In this dissertation, we study the memory properties of transformations of linear processes. Our results show that transformations of short-memory time series still have short-memory and transformations of long-memory time series may have different weaker memory parameters which depend on the power rank of the transformation. In particular, we provide the memory parameters of transformations of the FARIMA(p, d, q) processes. As an example, the memory properties of call option processes at different strike prices are discussed in details. When we develop the memory properties of transformations of linear processes, we use the Pearson correlation to measure memories. Correlation analysis is another big topic in statistics, which is used to measure the dependence of stochastic processes or random variables. Standard Gini correlation is one of the correlations to measure the dependence between random variables with heavy tailed distributions. However, the asymmetry of Gini covariance and correlation brings a substantial difficulty in interpretation. In this dissertation, we propose a symmetric Gini-type covariance and correlation (ρg) based on the joint rank function. The proposed correlation ρg is symmetric and is more robust than the Pearson correlation but less robust than the Kendall’s τ correlation in terms of influence functions. Furthermore, we establish the relationship between ρg and the linear correlation ρ for a class of random vectors in the family of elliptical distributions, which allows us to estimate ρ
Node-nested multi-grid method with Delaunay coarsening

For finite-element non-structured type meshes, the non-nested multigrid algorithms require to build a sequence of independent meshes. The paper proposes an automatic way to generate the coarse meshes given the finest one. The method first eliminates a set of points from the current mesh level and then uses the Delaunay-Voronoi algorithm to triangulate the remaining set of points. The algorithm is presented and it is shown that it owns good properties with respect to multigrid algorithms. Several examples of its application to bi-dimensional meshes are presented.
Grad’s 13 moments approximation for Enskog-Vlasov equation

Hydrodynamic models of liquid-vapor flows have to face the difficulty of describing non-equilibrium regions next to interfaces. Depending on the flow regimes and the underlying theoretical models, different answers have been given. In particular, diffuse interface models (DIMs) provide, in principle, a unified description of the whole flow field by a set of PDE’s, not much more complex than Navier-Stokes-Fourier classical equations. Unfortunately, DIMs fail to provide a proper description of kinetic layers next to interfaces. In order to develop a model incorporating kinetic effects while keeping the relative simplicity of DIMs, macroscopic transport equations—moment equations — are derived from the Enskog-Vlasov equation. The Enskog-Vlasov equation extends the Enskog equation by accounting for the attractive forces between the gas molecules. Hence, it gives a van-der-Waals-like kinetic description of a non-ideal gas, including liquid-vapor phase change. Specifically, the equation describes the liquid phase, the vapor phase, and a diffusive transition region connecting both phases. While not the most accurate model, solutions of the Enskog-Vlasov equation exhibits all relevant phenomena occurring in the evaporation and condensation of rarefied or dense vapors. In this work, Grad’s moment method is used to derive a closed set of 13 moment equations. In the appropriate limits, these reduce to the Navier-Stokes-Fourier system for liquid and vapor. Our main interest is to study non-hydrodynamic effects, in particular transport in and across the transition region, and the interplay between the transition region and Knudsen layers. We present first results of this program, including the closed transport equations for 13 moments, discussion of the limits, and solutions in simple geometries.
Residential wireless interfaces virtualization: a feasibility study

This paper investigates the possibility of virtualizing and distributing the functionality that runs on top of residential wireless communications. Specifically, we propose, describe and test a solution that transports USB communications to remote locations, for scenarios in which the in-home wireless interfaces are consumed at the server side through this type of general-purpose and widely used interfaces. We frame this study in a general architecture by which Software Defined Networking (SDN) and Network Functions Virtualization (NFV) bring economies of scale, flexibility and programmability to residential Internet of Things (IoT) environments. As a result of our tests, we prove the feasibility of the remote presence of the IoT systems through the Universal Serial Bus (USB) tunnels, and we obtain approximate bandwidth measurements that serve as a hint on the type of services that can be offloaded to the cloud. For those functionalities that would need more bandwidth, we propose to embed a lightweight virtualization environment in home and to execute in it part of the virtualized components, something that is in line with the recent fog computing approaches.
Módulo tangente do tendão calcanear em corredores

O numero de interessados pela corrida como esporte vem aumentando exponencialmente e com isso os avancos tecnologicos e as pesquisas relacionadas a essa pratica foram alavancadas, motivadas para melhorar o desempenho e a avaliacao dos corredores. O objetivo deste estudo foi avaliar o modulo tangente do tendao calcanhar (TC) de individuos praticantes de corrida. Participaram do estudo 30 individuos, onde 10 formaram o grupo confiabilidade, 8 corredores recreacionais e 12 atletas (6 da modalidade fundo e 6 de triatlo ou pentatlo). O teste consistiu em mobilizacoes passivas da articulacao do tornozelo, a uma velocidade de 5o/s, de 30o de flexao plantar ate a amplitude maxima estipulada por cada individuo, simulatâneo ao monitoramento do deslocamento da juncao miotendinea com ultrassonografia. O Coeficiente de Correlacao Intraclasse (CCI) e o Erro Tipico da Medida (ETM) foram aplicados para verificar a confiabilidade de todos os parâmetros. Nao foram encontradas diferencas significativas entre os parâmetros avaliados quando comparados os grupos de corredores recreacionais e atletas. Porem, o grupo de corredores de fundo apresentou maior modulo tangente maximo (403,67 ± 64,53 MPa) do que o dos praticantes de corrida de triatlo/pentatlo (213,15 ± 43,27 MPa). Este estudo aponta para maiores valores de rigidez do TC em corredores de fundo.
Multi-Scale Dense Networks for Hyperspectral Remote Sensing Image Classification

For hyperspectral remote sensing image (HSI) classification, the learning process of deep neural networks has been progressively advanced in depth, but the fine features are often largely lost or even disappear in the process of depth transfer. With the increase in feature aggregation and connectivity, the complexity of the network and the training parameters increases greatly, requiring more training time. This paper proposed a multi-scale dense network (MSDN) for HSI classification that made full use of different scale information in the network structure and combined scale information throughout the network. It implemented feature extraction of HSIs in two dimensions, including the features at fine and coarse levels. In the horizontal direction, it considered the deep extraction of HSI features, and the 3-D dense connection structure was used for aggregating features at different levels. In the vertical direction, scale information was considered, and three-scale feature maps at low, middle, and high levels were generated based on the first layer of the network. The MSDN used stride convolution for downsampling and combined feature information at different scale levels. The MSDN extracted features along the diagonal line. The network implemented the reconstruction of deep feature extraction and multi-scale fusion for HSI classification. The MSDN model performed well on representative HSI datasets, namely, the Indian Pines, Pavia University, Salinas, Botswana, and Kennedy Space Center datasets. It improved the training speed and accuracy for HSI classification and especially improved the convergence speed, which effectively saved computing resources and had high stability.
Anisotropic Metasurface-Based Beam-Scanning Dual-Polarized Fan-Beam Integrated Antenna System

This paper presents a novel anisotropic metasurface (AMS)-based integrated antenna system to facilitate dual-polarized fan-beam patterns with independent beam-scanning ability. In the proposed configuration, the antenna subsystem comprises a specially designed differentially fed microstrip patch antenna (source antenna) along with a polarization rotator (PR). The differential antenna arrangement is realized using a square shaped microstrip patch capacitively coupled with two metallic strips, which are connected to a specially designed wideband hybrid coupler using two metallic vias for the microstrip feeding. This source antenna is loaded with a PR by placing it at a height of <inline-formula> <tex-math notation="LaTeX">$0.35\lambda _{0}$ </tex-math></inline-formula> from the radiating aperture. The PR comprised two identical metallic layer patterns, separated by two substrates. Depending upon the relative orientation of these layers, the polarization of the linearly polarized impinging spherical electromagnetic (EM) waves (originating from the source antenna) either remains preserved or gets rotated by 90° while transmitting through this PR. After realizing the antenna subsystem, a novel AMS lens is designed and placed above the PR. The proposed AMS lens is realized by integrating two cylindrical MS (CMS) lenses, <inline-formula> <tex-math notation="LaTeX">$\text {CMS}_{Y}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\text {CMS}_{X}$ </tex-math></inline-formula>. This integration provides a unique phase profile to the AMS lens, thus introducing appropriate phase correction to the incident orthogonally polarized spherical EM waves along their respective polarization direction. The proposed configuration of AMS lens, thus, results into formation of the independent dual-polarized fan-beam radiation beams. Finally, the steering of the generated fan-beams along the direction of their respective polarization is facilitated using the proposed system by translating the AMS lens parallel to the source antenna.
Multi-scale analysis of ulcer disease detection from WCE images

Wireless capsule endoscopy (WCE) proves its robustness as a great technology to examine the entire digestive tract or the small intestine. An automatic computer-aided design method is proposed in this study, in a manner to differentiate between ulcer disease and normal WCE images. A multi-scale analysis-based grey-level co-occurrence matrix (GLCM) is conducted here. The main step, the co-occurrence matrix (GLCM), is computed from each sub-band Laplacian pyramid decomposition, so as to extract the common Haralick features. Moreover, the p-value and area under the curve are used to select the relevant characteristics from the feature descriptor. This proposed approach was separately applied to the components of CIELab colour space. Ulcer detection was performed using the support vector machine. The findings demonstrate an encouraging detection rate performance of 95.38% for accuracy and 97.42% for sensitivity based on the first dataset and an average accuracy of 99.25 and 98.51% of sensitivities for the second dataset.
Is Responsive Feeding Difficult? A Case Study in Teso South Sub-County, Kenya

Responsive infant and young child feeding as a reciprocal relationship between the child and his or her caregiver is recommended by the WHO but has received less attention than dietary diversity or meal frequency up to now. The current study assessed common (non)responsive child feeding practices and factors that facilitate or hinder caregivers to improve feeding practices in rural Teso South Sub-County, Western Kenya. The qualitative study used focus group discussion (n = 93) and Trials of Improved Practices (TIPs) (n = 48) to identify challenges and opportunities in household food distribution and feeding practices. Overall, the implementation of responsive feeding practices was feasible for the caregivers. Parents reported mainly positive experiences in terms of the child’s feeding behavior and effects on child health. Traditional beliefs, practices, and cultural norms hindered some households to change intrahousehold food distribution. Households who manage to implement responsive feeding even in food insecure regions should be consulted to (a) improve existing nutrition education messages that acknowledge these cultural norms, (b) to include more responsive feeding information in nutrition education material, and (c) to address gender norms to create awareness of the importance of responsive feeding practices and the need for adequate time allocation for infant and young child feeding.
From Constant to Stochastic Volatility: Black-Scholes Versus Heston Option Pricing Models

The Nobel Prize-winning the Black-Scholes Model for stock option pricing has a simple formula to calculate the option price, but its simplicity comes with crude assumptions. The two major assumptions of the model are that the volatility is constant and that the stock return is normally distributed. Since 1973, and especially in the 1987 Financial Crisis, these assumptions have been proven to limit the accuracy and applicability of the model, although it is still widely used. This is because, in reality, observing a stock return distribution graph would show that there is an asymmetry or a leptokurtic shown in the stock return. Therefore, we propose that by introducing the Heston Model, we can tackle these two problematic assumptions in the Black-Scholes Model. The Heston Model considers the leverage effect and the clustering effect, which allows the volatility itself to be random and also allows it to take the non-normally distributed stock return into account. In our project, we aim to show whether the Heston model can actually improve the option pricing estimates by using the S&P 500 Index European Call Option to compare it to the BlackScholes Model. We find that even though the results show that the Heston Model performs worse than the Black-Scholes Model when the option expiration date is soon to expire, the Heston Model significantly outperforms the Black-Scholes Model in almost all combinations of moneyness and maturity scenarios. There remains further work to improve the Heston Model.
PALONN: Parallel Ant Lion Optimizer and Artificial Neural Network for Power Flow Control of the Micro Grid-Connected System

In this paper, parallel ant-lion optimizer (ALO) and artificial neural network (ANN) for the micro-grid (MG) connected system with AC load is proposed. The proposed algorithm is the combined performance of ALO type I and II algorithms. The aim of the proposed algorithm is to increase the power transfer capability between the source and load sides and to offer several benefits like enhanced predicting capability, degradation in complexity, and randomization. ALO type I is utilized for active power controller parameter optimization with enhanced searching behaviour like crossover and mutation. Using the ALO type II, the reactive power controller parameters’ optimization is performed with online predictor ANN. The exact control signals of the power controller are determined based on the system power deviations using the parallel operation of the algorithms. With the performance of the proposed controller, the power exchange is enhanced and ensured between the sources to load. The implementation is done by the MATLAB/Simulink platform. The performance of the proposed method is analysed using comparison analysis with the existing techniques.
Large time behavior in a forager–exploiter model with different taxis strategies for two groups in search of food

This work deals with a taxis cascade model for food consumption in two populations, namely foragers directly orienting their movement upward the gradients of food concentration and exploiters taking a parasitic strategy in search of food via tracking higher forager densities. As a consequence, the dynamics of both populations are adapted to the space distribution of food which is dynamically modified in time and space by the two populations. This model extends the classical one-species chemotaxis-consumption systems by additionally accounting for a second taxis mechanism coupled to the first in a consecutive manner. It is rigorously proved that for all suitably regular initial data, an associated Neumann-type initial-boundary value problem for the spatially one-dimensional version of this model possesses a globally defined bounded classical solution. Moreover, it is asserted that the considered two populations will approach spatially homogeneous distributions in the large time limit, provided that either the total population number of foragers or that of exploiters is appropriately small.
Time-To-Collision: A Sensitive Measure of Driver Interaction with Traffic in a Simulated Driving Task

In the future, on-board driver monitoring systems could use time-to-collision (TTC) metric algorithms as a real-time measure of driving performance, and alert the driver if performance falls below minimum performance criteria. Such monitoring systems remain years away, but it is currently possible to measure TTC in a simulator. This paper discusses a study to determine whether TTC varies as a function of driver impairment in a simulated driving task. Alcohol was administered to eleven participants, and TTC measures were obtained at 0.00%, 0.04% and 0.08% blood alcohol concentrations (BAC). The results support use of the median TTC, which varied as a function of BAC, as a measure of in-traffic maneuvering performance.
Testing the epidemic change in nearly nonstationary autoregressive processes

Consider random variables X1, X2, . , Xn with parameters of interest θ1, . , θn, n > 2. Testing an epidemic type change (or changed segment) in these parameters means testing null hypothesis θ1 = θ2 = · · · = θn against the alternative θ1 = · · · = θk∗ = θm∗+1 = · · · = θn = μ0 and θk∗+1 = · · · = θm∗ = μ1 for some unknown 1 < k∗ < m∗ 6 n and μ0 6= μ1. Here k∗ is the beginning, m∗ is the end and `∗ = m∗ − k∗ is the length or duration of the epidemic state. To the best of our knowledge such a problem for independent observations have been formulated for the first time by Levin and Kline [1] (we also refer to [2, Sect. 1.4]). Yao [3] have studied various test statistics in order to detect an epidemic change in the mean values of a sequence of independent normally distributed random variables. Ramanayake and Gupta [4, 5] investigated various likelihood ratio type statistics and independent random variables from an exponential family. Graiche et al. [6] investigated the changed segment problem for α-mixing random variables. For more information on this subject, see [7, Sects. 9.3, 9.4] and [8–11].
Orthogonal frequency division multiplexing simulation based on MATLAB

OFDM (Orthogonal Frequency Division Multiplexing) is one of the core technologies in the fourth generation mobile communication system. It is a widely-used method of the multi-carrier modulations based on IFFT and FFT transform, it can achieve the lowest complexity and effectively combat frequency selective fading. In this paper, we successfully use MATLAB to do the simulation of OFDM, and obtained good results, in which successful recovery out of the original signal under real channel condition, and error is less than 5% with the original signal.
Zeros of the 3-state Potts model partition function for the square lattice revisited

We compute the exact partition function for the 3-state Potts model on square lattices of several sizes larger than previously accessible. Making comparison with the exactly solved Ising model we show that, for aspects of the analytic structure close to the ferromagnetic transition point, these lattices are large enough to approach the thermodynamic limit. Subject to certain assumptions this allows for computation of estimates for the specific heat critical exponent. We thus obtain an estimate for this exponent. The estimate is consistent with the known result, thus demonstrating the potential use of this method for other models. We also discuss the antiferromagnetic transition.