Miracle-dz/UniFAR-FTUs huggingface dataset:
A decade of changes: Formal education and transborder linkages of young people in highly urbanized areas of the northern border Una década de cambios: Educación formal y nexos transfronterizos de los jóvenes en áreas muy urbanas de la frontera norte

In the current migratory and economic context, this article analyzes the statistical associations between a set of educational indicators and two transborder linkages of young people in highly urbanized areas, having been born in the United States (USA) and living in households with crossborder workers, based on microdata from the 2010 Census. Further, the results of this analysis are compared with those obtained in 2000. Findings include the following: 1) the decrease in the number of young people living in households with crossborder workers and the increase of those born in the USA in the last decade; 2) the persistent positive association between being born in the USA and high school or university enrollment in 2010, in contrast to the negative association between these post-basic education variables and recent immigration from the USA; and 3) a null relationship between having crossborder workers at home and school enrollment at the post-basic level.
Constraint Handling in E icient Global Optimization

Real-world optimization problems are oen subject to several constraints which are expensive to evaluate in terms of cost or time. Although a lot of eort is devoted to make use of surrogate models for expensive optimization tasks, not many strong surrogate-assisted algorithms can address the challenging constrained problems. Efcient Global Optimization (EGO) is a Kriging-based surrogateassisted algorithm. It was originally proposed to address unconstrained problems and later was modied to solve constrained problems. However, these type of algorithms still suer from several issues, mainly: (1) early stagnation, (2) problems with multiple active constraints and (3) frequent crashes. In this work, we introduce a new EGO-based algorithm which tries to overcome these common issues with Kriging optimization algorithms. We apply the proposed algorithm on problems with dimension d ≤ 4 from the G-function suite [16] and on an airfoil shape example.
Resistance of Bacteria Isolated from Awotan Dumpsite Leachate to Heavy Metals and Selected Antibiotics

The selection of heavy metal resistance by microorganisms often promotes for antibiotic resistance in the environment. This work investigates the potentials of selected microorganisms isolated from dumpsite leachate from Awotan dumpsite at Ibadan in Ibadan south, Oyo State to tolerate some heavy metals such as lead (Pb), Nickel (Ni), Copper (Cu) and Arsenic (As) found in the leachate and also determine their antibiotic resistance pattern. Twenty six (26) bacterial isolates belonging to seven genera were obtained from the samples of leachate. The identification of the bacteria isolated revealed they belongs to Escherichia coli, Pseudomonas sp, Proteus sp, Bacillus spp, Arthrobacter sp, Klebsiella pneumonia, Enterobacter cloacae and Staphylococcus sp. Tolerance ability of the microbial isolates to heavy metals was determined by cultivating the isolates in a basal medium in which different concentrations of heavy metals compound ranging from 1mM to 3mM was incorporated. Some of the organisms had high MIC values for Pb+ and Cu++ and low MIC value for Ni+ and Ar2+. The MIC result shows low toxicity and high toxicity respectively of the heavy metals to the organisms. On the other hand, the isolates also exhibited high tolerance to most of the antibiotics like Ampiclox (100%), Gentamicin (100%), Ciprofloxacin (50.0%), Septrin (75%), and Streptomycin (75%). The resistance of these organisms to both metals and antibiotics could cause hazard into the environment and present very serious health implication because of the ability of these organisms to pass these resistant genes which may be transfer together via plasmids to other microbial cell around will affect a whole bacterial population thereby complicating treatment.
Bank of Canada Banque du Canada Working Paper 959 / Document de travail 959 Selection of the Truncation Lag in Structural VARs ( or VECMs ) with Long-Run Restrictions

The authors examine the issue of lag-length selection in the context of a structural vector autoregression (VAR) and a vector error-correction model with long-run restrictions. First, they show that imposing long-run restrictions implies, in general, a moving-average (MA) component in the stationary multivariate representation. Then they examine the sensitivity of estimates of the permanent and transitory components to the selection of the lag length required in a VAR system to approximate this MA component. In summary, they find that using a lag structure that is too short can lead to a significant estimation bias of the permanent and transitory components. In addition, in comparing four different lag-selection criteria, they find that the Schwarz information criterion systematically underperforms relative to the other tests. More generally, as the order of the VAR that best approximates the data-generating process increases, the sequence-based tests (Wald, likelihood ratio) tend to provide more reliable results than the information-based tests (Akaike, Schwarz). Résumé Dans la présente étude, les auteurs examinent la question du choix des retards dans un modèle structurel d'autorégression vectorielle ou modèle vectoriel de correction des erreurs avec contraintes de long terme. Ils montrent tout d'abord que l'imposition de telles contraintes implique généralement qu'une composante de moyennes mobiles (MA) intervient dans la représentation stationnaire du modèle à plusieurs variables. Puis ils examinent le degré de sensibilité que les estimations des composantes permanente et temporaire du modèle doivent afficher par rapport au choix du retard dans un système autorégressif pour s'approcher de cette composante MA. En somme, ils trouvent que l'utilisation d'une structure de retard de trop courte durée peut entraîner une distortion importante de l'estimation des composantes permanente et temporaire. En outre, une comparaison de quatre critères différents du choix des retards révèle que les tests axés sur le critère d'information de Schwarz produisent toujours des résultats moins probants que les autres. De façon générale, au fur et à mesure que s'accroît l'ordre du vecteur autorégressif qui fournit la meilleure approximation du processus de génération de données, les tests séquentiels (Wald, rapport des vraisemblances) tendent à produire des résultats plus fiables que ceux qui s'appuient sur les critères d'information (Akaike, Schwarz).
Discussing the Spectra of Physics-Enhanced Machine Learning via a Survey on Structural Mechanics Applications

The intersection of physics and machine learning has given rise to a paradigm that we refer to here as physics-enhanced machine learning (PEML), aiming to improve the capabilities and reduce the individual shortcomings of data- or physics-only methods. In this paper, the spectrum of physics-enhanced machine learning methods, expressed across the defining axes of physics and data, is discussed by engaging in a comprehensive exploration of its characteristics, usage, and motivations. In doing so, this paper offers a survey of recent applications and developments of PEML techniques, revealing the potency of PEML in addressing complex challenges. We further demonstrate application of select such schemes on the simple working example of a single-degree-of-freedom Duffing oscillator, which allows to highlight the individual characteristics and motivations of different `genres' of PEML approaches. To promote collaboration and transparency, and to provide practical examples for the reader, the code of these working examples is provided alongside this paper. As a foundational contribution, this paper underscores the significance of PEML in pushing the boundaries of scientific and engineering research, underpinned by the synergy of physical insights and machine learning capabilities.
Advance in Soil Pore and its Influencing Factors

Soil pore was an important part of soil structure and was one of the most important indicators of soil quality.The distributions of soil pores amounts and sizes directly determined the air permeability, water holding capacity and the stretch of crop root in the soil, and indirectly impacted on soil fertility and crop yields. Basis on the previous studies, this paper systematically summarized the soil pores types, classification methods, research techniques and main influencing factors. Furthermore, this paper presented the outlook of the research focus on soil pore structure and would guide people to take the optimal agricultural management measures.
Asian influenza. Infection, disease, and psychological factors.

INFECTION does not always result in disease or illness. Only a proportion of infected persons become sick following many epidemic and endemic infections. Social, economic, racial, and other factors obviously influence the frequency of infection and disease in a population, affecting the degree of exposure to the microorganisms and natural resistance. The impact of psychological factors upon the frequency of infection and infectious disease, however, has not been previously evaluated. The onset or exacerbation of disease during a chronic infection, such as tuberculosis, may be partly dependent upon antecedent emotional stresses.1Development of illness with acute infection, however, has not been related to psychological factors. The severity of acute infection as measured, for example, by the height and duration of fever, has not been shown to be influenced by emotional factors,2,3but psychological stresses might magnify the symptoms of illness. Delayed recovery from symptoms associated with infection
ONE-DIMENSIONAL WAVELET AND REANALYSIS OF GRAVITY WAVES

Different meteorological parameters and atmospheric circulations are known as one of the sources of excitement of gravity waves (GWs). The main purpose of this paper is to analyze the GWs and seasonal variations over Istanbul by wavelet-based computer simulations. Turbulent structures of pressure, height, and air temperature have been analyzed in this paper. These waves are in the meso-scale wave-form and, generally, are observed in spring, autumn, and winter. The FAWAV Wavelet software and the latest version of MATLAB wavelet packet are applied to analyze meteorological parameters for the north-western part of Turkey. Wavelet based computer simulation of data is generally close to the real data under consideration for the Daubechies wavelet series.
Lithospheric and upper mantle stratifications beneath Tibet: New insights from Sp conversions

We assess the upper mantle structure under the Tibetan plateau from a S‐to‐P converted waves receiver functions study. Contrary to the Ps receiver functions blurred by multiples from Moho to 350 km depth, the Sp are better suited for imaging at these depths. The Moho is clearly recovered and often exhibits a complex and warped structure. The upper crust is marked by a significant low velocity zone in the southern part of the plateau, probably associated with partial melt, which vanishes north of the Bangong suture. In the upper mantle, between the Moho and the 660 km discontinuity, four stratification levels are identified. The strongest converter at a depth ranging between 120 to 180 km corresponds to the bottom of a low shear‐wave velocity layer imaged by surface wave inversion.
Exploration of alternative assessment models for Pacific cod in the Aleutian Islands

This document represents an effort to respond to comments made by the BSAI Plan Team, the joint BSAI and GOA Plan Teams, and the SSC regarding the need to develop an age-structured model of the Pacific cod (Gadus macrocephalus) stock in the Aleutian Islands (AI). Throughout the history of management under the Magnuson-Stevens Fishery Conservation and Management Act, Pacific cod in the eastern Bering Sea (EBS) and AI have been managed as a unit. Since at least the mid-1980s, harvest specifications for the combined BSAI unit have been extrapolated from an age-structured model for Pacific cod in the EBS.
Reliability and evaluation of the potential of the i_EPIC model to estimate rice yields in Thailand

The Interactive Environmental Policy Impact Calculator (i_EPIC) model is an important tool for future agriculture and food security in Thailand. Its application requires both the identification of errors and the assessment of reliability and potential of the i_EPIC model and GIS technique in simulating rice yields. Rice yields estimated by EPIC (version 0509) were compared with agricultural statistics reports from Thailand’s Office of Agricultural Economics (OAE), Ministry of Agriculture and Cooperatives (MOAC). Validation of rice yield data proved to be satisfactory: the mean relative error (MRE %) for major rice (rainy season) being 11.77, mean absolute error (MAE %) 1.22 and root mean square error (RMSE %) 43.06. The corresponding errors for second rice (dry season) were 10.44, 26.01 and 34.91, respectively. Our results show that overall model reliability, with model efficiency (EF%), is 98% for major rice and 97% for second rice, indicating that i-EPIC model performance is reliable for estimating rice yields in Thailand. To improve data accuracy for other variables such as soil, weather and crop information is needed. Key word: i_EPIC model, EPIC0509, rice, Geographic Information Systems (GIS), Thailand
Mapping Brain Networks in Awake Mice Using Combined Optical Neural Control and fMRI 1 2

1 Mapping Brain Networks in Awake Mice Using Combined Optical Neural Control and fMRI 1 2 Desai M. *, Kahn I. *‡, Knoblich U. , Bernstein J., Atallah H. , Yang A. , Kopell, N. , Buckner 3 R.L. , Graybiel A. M. , Moore C. I. †, & Boyden E. S. † 4 5 1 McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, MIT, 6 Cambridge, MA 02139, USA; 7 2 Biomedical Engineering Department, Tufts University, Medford, MA 02155, USA; 8 3 Howard Hughes Medical Institute and Center for Brain Science, Harvard University, Cambridge, MA 9 02138, USA; 10 4 The MIT Media Laboratory and MIT Department of Biological Engineering, MIT, Cambridge, MA 11 02139, USA; 12 5 Center for Biodynamics and Departments of Mathematics and Statistics, Boston University, Boston, MA 13 02215, USA 14 ‡ Current address: Department of Phsyiology and Biophysics, Faculty of Medicine, Technion, Haifa, 15 Israel 16 17 *These authors contributed equally 18 19 Running head: Opto-fMRI in awake mice 20 21 †Corresponding authors: 22 Edward S. Boyden, MIT Media Lab, 20 Ames St., Cambridge, MA 02139, USA. 23 Phone: (617) 324-3085; Fax: (617) 258-6264; email: esb@media.mit.edu 24 25 Christopher I. Moore, Building 46-2171, 77 Massachusetts Avenue, Cambridge, MA 02139 26 Phone: (617) 452-3526; Fax: (617) 452-4119; email: cim@mit.edu 27 28 29 30 31 32
Simultaneous Localization And Mapping Using a Kinect TM In a Sparse Feature Indoor Environment

Localization and mapping are two of the most central tasks when it comes to autonomous robots. It has often been performed using expensive, accurate sensors but the fast development of consumer electronics has made similar sensors available at a more affordable price. In this master thesis a TurtleBotTM robot and a Microsoft KinectTM camera are used to perform Simultaneous Localization And Mapping, SLAM. The thesis presents modifications to an already existing open source SLAM algorithm. The original algorithm, based on visual odometry, is extended so that it can also make use of measurements from wheel odometry and a single axis gyro. Measurements are fused using an Extended Kalman Filter, EKF, operating in a multirate fashion. Both the SLAM algorithm and the EKF are implemented in C++ using the framework Robot Operating System, ROS. The implementation is evaluated on two different data sets. One set is recorded in an ordinary office room which constitutes an environment with many landmarks. The other set is recorded in a conference room where one of the walls is flat and white. This gives a partially sparse featured environment. The result by providing additional sensor information is a more robust algorithm. Periods without credible visual information does not make the algorithm lose its track and the algorithm can thus be used in a larger variety of environments including such where the possibility to extract landmarks is low. The result also shows that the visual odometry can cancel out drift introduced by wheel odometry and gyro sensors.
- 1-A Detailed Digital Model of the Human Arterial System

A detailed model of the human circulation is developed. The large systemic arteries are presented by the branching system of straight viscoelastic tubes which corresponds topology of the human circulation. Terminal elements at the outlets of the system are presented by tree-like systems with a given topology (with/without anastomoses) and certain geometrical relations between the lengths and diameters of the vessels of different branching orders and the relation between the maximal total length of the vasculature and diameter of the feeding artery. The relations have been obtained by analysis of the morphometric data. They allow correct calculations of the hydraulic resistance and wave impedance of the arterial beds of different organs. The proposed outflow boundary conditions are more preferable then the Windkessels and the regular tree-like systems because they describe both resonant properties of the intraorgan vasculatures and the distributed sources of the reflected waves. The model describes realistic pressure and flow waves and pressure-flow dependences either in the aorta or in the feeding arteries of the inner organs. The latter underlies possibility of the novel noninvasive diagnostics of the state (normal or pathological) of the intraorgan circulation by noninvasive measuring the wall oscillations and blood flow velocity in any cross-section of the feeding artery of the organ.
Inhibition of viral replication reverses respiratory syncytial virus-induced NF-kappaB activation and interleukin-8 gene expression in A549 cells

Previous studies have demonstrated that respiratory syncytial virus (RSV) infection of airway epithelial cells results in the expression of a number of cytokines, such as interleukin-8 (IL-8), that are transcriptionally regulated by nuclear factor kappaB (NF-kappaB). In the studies reported here, we demonstrate that treatment of RSV-infected A549 cells with 100 microg of ribavirin (a viral replication inhibitor) per ml results in reversal of RSV-induced NF-kappaB activation, IL-8 mRNA expression, and IL-8 protein production in A549 cells. These data confirm that viral replication is a key step in RSV-induced NF-kappaB activation and IL-8 production.
Sparse Channel Estimation for Multicarrier Underwater Acoustic Communication: From Subspace Methods to Compressed Sensing

In this paper, we investigate various channel estimators that exploit channel sparsity in the time and/or Doppler domain for a multicarrier underwater acoustic system. We use a path-based channel model, where the channel is described by a limited number of paths, each characterized by a delay, Doppler scale, and attenuation factor, and derive the exact inter-carrier-interference (ICI) pattern. For channels that have limited Doppler spread we show that subspace algorithms from the array processing literature, namely Root-MUSIC and ESPRIT, can be applied for channel estimation. For channels with Doppler spread, we adopt a compressed sensing approach, in form of Orthogonal Matching Pursuit (OMP) and Basis Pursuit (BP) algorithms, and utilize overcomplete dictionaries with an increased path delay resolution. Numerical simulation and experimental data of an OFDM block-by-block receiver are used to evaluate the proposed algorithms in comparison to the conventional least-squares (LS) channel estimator. We observe that subspace methods can tolerate small to moderate Doppler effects, and outperform the LS approach when the channel is indeed sparse. On the other hand, compressed sensing algorithms uniformly outperform the LS and subspace methods. Coupled with a channel equalizer mitigating ICI, the compressed sensing algorithms can effectively handle channels with significant Doppler spread.
Water Harvesting and Flashflood Mitigation-Wadi Watier Case Study (South Sinai, Egypt)

2 Abstract: Egypt's Sinai Peninsula is suffering from water shortages. Although Sinai has limited rainfall, flashfloods are responsible for huge losses of lives and infrastructure. The objective is to evaluate the water harvesting potential in, the semi-arid, water scarce and flashflood prone, 3600 km Wadi Watier, South Sinai, 2 Egypt. The analysis is based on the Integrated Water Resources Management (IWRM) guidelines. Therefore, physical, social, environmental andinstitutional analyses were carried out. The potential runoff was estimated by applying the Soil Conservation Services (SCS) method using the Hydrologic Engineering Center (HEC-1) model. Additionally, interviews were done with local residents (Bedouins) to reflect water harvesting social acceptance, water consumption andwater uses. Besides, Institutional and Environmental analysis were reviewed from literature. Later, ArcGIS software was used to examine the potential sites by combining different geology, slope and land users layers. The results showed a promising potential for water harvesting with the area. Estimated 0.24, 0.45 and 2.7 million m could be harvested respectively for 2-,3-and 3 25-year return periods. Moreover, water harvesting techniques are socially accepted by Bedouins (91% of the interview sample) but not in funding these techniques. Also, 85% of the respondents prefer to use the harvested water for drinking, while 45 % of them favour it for grazing as a second choice. Consequently, wadi-bed and off-wadi water harvesting systems have been proposed with 6 techniques, such as Cisterns and Jessour. In conclusion, water harvesting could also provide one more conventional water resource andsimultaneously, mitigate flashflood hazards downstream by impounding water in specific locations upstream.