Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Selection and the Earnings of Immigrants: Reply

My 1987 paper addresses a central question in the economics of immigration: Who are the immigrants? It has been traditionally assumed that immigrants are positively selected-that is, immigrants are more skilled, on average, than the typical person in the source country. One contribution of my theoretical analysis was to show that this assumption is not necessarily consistent with wealth-maximizing behavior. In fact, under some conditions the immigrant flow may be negatively selected. ' My original study focused only on the selection bias caused by immigrants endogenously sorting themselves out of the source country's population.2 Guillermina Jasso and Mark Rosenzweig point out that I ignored other types of selection biases in both my theoretical development and empirical framework. These additional biases are due to: (1) the selective emigration of the foreign-born in the United States; and (2) the fact that my empirical work was limited to immigrants originating in 41 source countries. Regarding the first of these points, Jasso and Rosenzweig restate the well-known fact that emigration (or return migration) is an important characteristic of the immigrant experience. Robert Warren and Jennifer Marks Peck (1980), for instance, estimate that perhaps as many as 30 percent of immigrants leave the United States within a decade or two after their arrival. Jasso and Rosenzweig, however, do not examine systematically how the selective emigration of the foreign-born affects either the theory or the empirical analysis. In essence, their criticism simply asserts that selective emigration is likely to cause problems. My 1987 paper, however, already made note of that fact (p. 538). Moreover, the biases caused by emigration were an integral part of my earlier critique of the econometric methodology used by most studies of immigrant earnings determination (Borjas 1985, pp. 466-67). What is obviously needed is the generalization of both my theoretical and empirical frameworks to account for the emigration of the foreign-born. Such a generalization, however, is not provided by Jasso and Rosenzweig and does not yet exist.3 The second point made by Jasso and Rosenzweig deals with the empirical results presented in my paper. Because I limited my analysis to immigrants originating in 41 countries, the sample is not representative and serious selection biases may be at work. Obviously, it is always better to use a more representative sample in the empirical analysis. The data were limited to 41 source countries because I was concerned not only with immigrant wage levels, but also with immigrant wage growth as recorded by the 2/10
Childhood maltreatment, psychopathology, and the development of hippocampal subregions during adolescence

It is well established that childhood maltreatment has a detrimental impact on the brain, particularly the hippocampus. However, the hippocampus is a functionally and structurally heterogeneous region, and little is known about how maltreatment might affect hippocampal subregion development throughout important periods of plasticity. This study investigated whether childhood maltreatment was associated with the development of hippocampal subregion volumes from early to late adolescence. It also investigated associations between onset of psychiatric disorder and hippocampal subregion volume development.
Krüppel-Like Factor 8 (KLF8) Is Expressed in Gliomas of Different WHO Grades and Is Essential for Tumor Cell Proliferation

Krüppel-like factor 8 (KLF8) has only recently been identified to be involved in tumor cell proliferation and invasion of several different tumor entities like renal cell carcinoma, hepatocellular carcinoma and breast cancer. In the present study, we show for the first time the expression of KLF8 in gliomas of different WHO grades and its functional impact on glioma cell proliferation. In order to get information about KLF8-mRNA regulation qPCR was performed and did not reveal any significant difference in samples (n = 10 each) of non-neoplastic brain (NNB), low-grade gliomas (LGG, WHO°II) and glioblastomas (GBM, WHO°IV). Immunohistochemistry of tissue samples (n = 7 LGG, 11 AA and 12 GBM) did not show any significant difference in the fraction of KLF8-immunopositive cells of all analyzed cells in LGG (87%), AA (80%) or GBM (89%). Tissue samples from cerebral breast cancer metastasis, meningiomas but also non-neoplastic brain demonstrated comparable relative cell counts as well. Moreover, there was no correlation between KLF8 expression and the expression pattern of the assumed proliferation marker Ki67, which showed high variability between different tumor grade (9% (LGG), 6% (AA) and 15% (GBM) of Ki67-immunopositive cells). Densitometric analysis of Western blotting revealed that the relative amount of KLF8-protein did also not differ between the highly aggressive and proliferative GBM (1.05) compared to LGG (0.93; p<0.05, studens t-test). As demonstrated for some other non-glial cancer entities, KLF8-knockdown by shRNA in U87-MG cells confirmed its functional relevance, leading to an almost complete loss of tumor cell proliferation. Selective blocking of KLF8 might represent a novel anti-proliferative treatment strategy for malignant gliomas. Yet, its simultaneous expression in non-proliferating tissues could hamper this approach.
Industrial Demand for Energy

In this study we examine the characteristics of industrial demand for energy, which accounts for more than one-fourth of annual energy consumption in the United States. Our research has been focused on four topics: 1. interfuel substitution in two-digit industries; 2. substitution among energy, capital and labor; 3. technical change in energy use; and 4. dynamic structure of energy demand. The results indicate that technical change has occurred through factor augmentation at unequal rates. Statistically significant labor-using and material-saving biases are found. There also appears to have been a small energy-saving bias, but it is not statistically significant.
European enhanced space-based AIS system study

A recent study of an European consortium (TPZ, Carlo Gavazzi Space, Edisoft, Elman, ITS) led by Telespazio and co-financed by ESA has investigated about the possibility of receiving AIS signals (i.e., AIS transmissions of vessels equipped with regular AIS transponders) from space with an improved performance with respect to the current literature thanks to an optimized mission design and enhanced technical capabilities mainly in terms of antennas and signal processing. The performances is assessed by means of a dedicated end-to-end System Simulator developed during the project.
Development of an Intelligent Chair Tool System Applying New Intelligent Pneumatic Actuators

This paper develops an Intelligent Chair Tool (ICT) — a new chair-type human and machine interaction seating system powered by 36 intelligent pneumatic actuators. This tool can be used to facilitate investigation of chair shapes from spring and damping effects of seating and backrest surfaces. Each actuator used consists of five extensive elements of encoder, laser strip rod, pressure sensor, valves and PSoC microcontroller incorporated in a single device. By using the ICT, different shapes, spring and damping characteristics can be obtained to aid the design of chairs from the control inputs, i.e., position x, stiffness k s and viscous coefficient c. Several control algorithms are presented to realize the communication and control system, and to obtain all data in real-time. The control methodology presented contains an inner force loop and an outer position loop implemented using a unified control system. The specification, development design and experimental evaluation of the ICT control system and actuator used are presented and discussed.
A New Dynamic Rule Activation Method for Extended Belief Rule-Based Systems

Data incompleteness and inconsistency are common issues in data-driven decision models. To some extend, they can be considered as two opposite circumstances, since the former occurs due to lack of information and the latter can be regarded as an excess of heterogeneous information. Although these issues often contribute to a decrease in the accuracy of the model, most modeling approaches lack of mechanisms to address them. This research focuses on an advanced belief rule-based decision model and proposes a dynamic rule activation (DRA) method to address both issues simultaneously. DRA is based on “smart” rule activation, where the actived rules are selected in a dynamic way to search for a balance between the incompleteness and inconsistency in the rule-base generated from sample data to achive a better performance. A series of case studies demonstrate how the use of DRA improves the accuracy of this advanced rule-based decision model, without compromising its efficiency, especially when dealing with multi-class classification datasets. DRA has been proved to be beneficial to select the most suitable rules or data instances instead of aggregating an entire rule-base. Beside the work performed in rule-based systems, DRA alone can be regarded as a generic dynamic similarity measurement that can be applied in different domains.
Spectroscopy of clusters in the ESO Distant Cluster Survey (EDisCS) : Redshifts, velocity dispersions and substructure for 5 clusters

We present spectroscopic observations of galaxies in 4 clusters at z = 0.7-0.8 and in one cluster at z ∼ 0.5 obtainec with the FORS2 spectrograph on the VLT as part of the ESO Distant Cluster Survey (EDisCS), a photometric and spectroscopic survey of 20 intermediate to high redshift clusters. We describe our target selection, mask design, observation and data reductior procedures, using these first 5 clusters to demonstrate how our strategies maximise the number of cluster members for which we obtain spectroscopy. We present catalogues containing positions, I-band magnitudes and spectroscopic redshifts for galaxies in the fields of our 5 clusters. These contain 236 cluster members, with the number of members per cluster ranging from 30 to 67. Our spectroscopic success rate, i.e. the fraction of spectroscopic targets which are cluster members, averages 50% and ranges from 30% to 75%. We use a robust biweight estimator to measure cluster velocity dispersions from our spectroscopic redshift samples. We also make a first assessment of substructure within our clusters. The velocity dispersions range from 400 tc 1100 km s -1 . Some of the redshift distributions are significantly non-Gaussian and we find evidence for significant substructure in two clusters, one at z ∼ 0.79 and the other at z ∼ 0.54. Both have velocity dispersions exceeding 1000 km s -1 but are clearly not fully virialised; their velocity dispersions may thus be a poor indicator of their masses. The properties of these first 5 EDisCS clusters span a wide range in redshift, velocity dispersion, richness and substructure, but are representative of the sample as a whole. Spectroscopy for the full dataset will allow a comprehensive study of galaxy evolution as a function of cluster environment and redshift.
Influence of HLA-DRB1 Alleles on the Variations of Antibody Response to Tuberculosis Serodiagnostic Antigens in Active Tuberculosis Patients

Serology-based tests for tuberculosis (TB) diagnosis, though rapid, efficient and easily implemented, have so far shown unsatisfactory levels of sensitivity and specificity, probably due to variations of the antibody response in TB patients. The number and types of seropositive antigens vary from individual to individual. The person-to-person variations of antigen recognition may be linked to genetic polymorphisms of the human leukocyte antigen (HLA) class II alleles. In the present study, we find that there is a significant increase in the frequency of HLA-DRB1*14 (P = 2.5×10−4) among subjects with high antibody response levels compared to those with low antibody levels. HLA-DRB1*15, the most frequent allelic group in the studied active TB population, positively correlates with subjects with low antibody response levels rather than subjects with high antibody response levels (P = 0.005), which indicates the loss of relevant antigens for screening of patients with this allelic group. The potential association between HLA-DRB1 allelic group and individual antigens implies that TB diagnostic yield could be improved by the addition of antigens screened at the proteome scale in infected subjects from the HLA-DRB1*15 allelic group.
Hardware Implementation of Nakagami and Weibull Variate Generators

An efficient implementation of Nakagami- m and Weibull variate generators on a single field-programmable gate array (FPGA) is presented. The hardware model first generates a correlated Rayleigh fading variate sequence and then transforms it into a sequence of Nakagami-m or Weibull fading variates. A biquad processor facilitates the compact implementation of a Rayleigh variate generator with arbitrary autocorrelation properties. A combination of logarithmic and linear domain segmentations along with piece-wise linear approximations is used to accurately implement the nonlinear numerical functions required to transform the correlated Rayleigh fading process into Nakagami-m or Weibull fading processes. When implemented on a Xilinx Virtex-5 5VSX240TFF1738-2 FPGA, the fading simulator uses only 1.6% of the configurable slices, 1.2% of the DSP48E modules and 3 block memories, while operating at 120 MHz, generating 120 million complex variates per second. The throughput can be increased up to 373 MHz with this FPGA if two separate clock sources are utilized.
Functional device design using nonuniform gate voltage: Analytical model of a novel MOSFET

A new mode of MOSFET operation with distributed gate voltage is proposed and a one-dimensional (1D) analytical model presented. Operation in the strong inversion regime of the laterally nonuniform (LNU) long channel devices is analyzed at room temperatures using gradual channel approximation considering carrier transport by drift alone. Models with linearly graded gate voltage show that these four terminal devices are capable of performing multiplication operation in a single device, making them inherently superior in speed, linearity and power dissipation to multistage multiplier circuits currently used in communication and analog VLSI circuits.
Yukawa Alignment in the Two-Higgs-Doublet Model

In multi-Higgs-doublet models the alignment in flavor space of the relevant Yukawa matrices guarantees the absence of tree-level flavor-changing couplings of the neutral scalar fields. We analyze the consequences of this condition within the two-Higgs-doublet model and show that it leads to a generic Yukawa structure which contains as particular cases all known specific implementations of the model based on Z{sub 2} symmetries. All possible freedom in the Yukawa sector gets parametrized in terms of three complex couplings {sigma}{sub f}. In spite of having flavor conservation in the neutral scalar couplings, the phases of these three parameters represent potential new sources of CP violation.
An end-user oriented graph-based visualization for spreadsheets

One of the difficulties in understanding and debugging spreadsheets is due to the invisibility of the data flow structure which is associated with cell formulas. In this paper, we present a spreadsheet visualization approach that is mainly based on the Markov Clustering (MCL) algorithm in an attempt to help spreadsheet users understand and debug their spreadsheets. The MCL algorithm helps in visualizing large graphs by generating clusters of cells. In our visualization approach, we also use compound fisheye views and treemaps to help in the navigation of the generated clusters. Compound fish eye views help to view members of a particular cluster while showing their linkages with other clusters. Treemaps help to visualize the depth we are at while navigating a cluster tree. Our initial experiments show that graph-based spreadsheet visualization using the MCL algorithm generates clusters which match with the corresponding logical areas of a given spreadsheet. Our experiments also show that analysis of the clusters helps us to identify some errors in the spreadsheets.
Asymptotic Padé-approximant methods and QCD current correlation functions

Asymptotic Pad\'e-approximant methods are utilized to estimate the leading-order unknown (i.e., not-yet-calculated) contributions to the perturbative expansions of two-current QCD correlation functions obtained from scalar-channel fermion and gluon currents, as well as from vector-channel fermion currents. Such contributions to the imaginary part of each correlator are polynomials of logarithms whose coefficients (other than the constant term within the polynomial) may be extracted from prior-order contributions by use of the renormalization-group (RG) equation appropriate for each correlator. We find surprisingly good agreement between asymptotic Pad\'e-approximant predictions and RG determinations of such coefficients for each correlation function considered, although such agreement is seen to diminish with increasing ${n}_{f}. $ The RG-determined coefficients we obtain are then utilized in conjunction with asymptotic Pad\'e-approximant methods to predict the RG-inaccessible constant terms of the leading-order unknown contributions for all three correlators. The vector channel predictions lead to estimates for the $O({\ensuremath{\alpha}}_{s}^{4})$ contribution to $R(s)\ensuremath{\equiv}[\ensuremath{\sigma}{(e}^{+}{e}^{\ensuremath{-}}\ensuremath{\rightarrow}\mathrm{hadrons})/\ensuremath{\sigma}{(e}^{+}{e}^{\ensuremath{-}}\ensuremath{\rightarrow}{\ensuremath{\mu}}^{+}{\ensuremath{\mu}}^{\ensuremath{-}})]$ for three, four, and five flavors.
WSN Based Personal Mobile Physiological Monitoring and Management System for Chronic Disease

This paper describes a robust healthcare monitoring system which possess multiple physiological signals measurements on real time that applicable to various environments which integrates wireless sensor network (WSN) technology and code division multiple assess (CDMA) with extended feature of locally standalone diagnosis algorithms that implemented in cell phone. A simple database is created inside the cell phone which eases patients to store, assess and manage their personal health records and information through this powerful integrated information management tool in anywhere and anytime. Any suspected or unknown patterns of signals will be immediately forwarded to hospital server using cell phone for doctors' evaluation. This features enable the patients realize the importance of self-health checking so that the preventive actions can be taken earlier because "Prevention is better than Cure". Appropriate self-monitoring and self-management can cure disease and relieve pain especially patients who suffer from chronic diseases that need long term observation.
Pricing Optimal Distributions to Overlapping Generations: A Corollary to Efficiency Pricing [A Complete Characterization of Efficiency in a General Capital Accumulation Model]

This paper will exploit the structural similarity of the two period overlapping generations model and the dynamic capital accumulation model to provide a pricing characterization of Pareto optimal distributions. With some very simple structural interpretations, the techniques which were developed to characterize efficient capital accumulation, apply directly to the overlapping generations model of the most general form; where generations consist of heterogenous consumer types of varying lifespans.
On the Location of the Snow Line in a Protoplanetary Disk

In a protoplanetary disk, the inner edge of the region where the temperature falls below the condensation temperature of water is referred to as the snow line. Outside the snow line, water ice increases the surface density of solids by a factor of 4. The mass of the fastest growing planetesimal (the isolation mass) scales as the surface density to the 3/2 power. It is thought that ice-enhanced surface densities are required to make the cores of the gas giants (Jupiter and Saturn) before the disk gas dissipates. Observations of our solar system's asteroid belt suggest that the snow line occurred near 2.7 AU. In this paper we revisit the theoretical determination of the snow line. In a minimum-mass disk characterized by conventional opacities and a mass accretion rate of 10-8 M☉ yr-1, the snow line lies at 1.6-1.8 AU, just past the orbit of Mars. The minimum-mass disk, with a mass of 0.02 M☉, has a lifetime of 2 million years with the assumed accretion rate. Moving the snow line past 2.7 AU requires that we increase the disk opacity, accretion rate, and/or disk mass by factors ranging up to an order of magnitude above our assumed baseline values.
Multi-agent system based portfolio management in prior-to-crisis and crisis period

We analyze portfolio creation techniques in a high frequency trading domain and randomly changing environments. We aim to create the best risk/reward portfolio based on thousands of profit histories of automated trading robots. We show that the effectiveness of standard portfolio weight calculation rules depends on the dimensionality, N, and the sample size, L, ratio. To resolve dimensionality / sample size dilemma we suggest designing a multistage feed-forward multi-agent system (MAS). At first we make simple 1/N Portfolio based expert agents. Then we use them and the regularized mean-variance framework to form a large number of more complex fusion agents. Finally we use a trained cost sensitive set of perceptrons to recognize the most successful fusion agents for making a final 1/N Portfolio based weights calculation. Experiments with 7708-dimensional 2004-2012 data confirm the effectiveness of the new approach.
Surface Electromyography Assessments of the Vastus medialis and Rectus femoris Muscles and Creatine Kinase after Eccentric Contraction Following Glutamine Supplementation

Purpose L-glutamine is the most abundant amino acid found in human muscle and plays an important role in protein synthesis and can reduce the levels of inflammation biomarkers and creatine kinase (CK) after training sessions. Delayed onset muscle soreness (DOMS) develops after intense exercise and is associated with an inflammatory response. The purpose of this study was to investigate the effect of glutamine supplementation on surface electromyography activity of the vastus medialis muscle (VMM) and rectus femoris muscle (RFM) and levels of creatine kinase after an eccentric contraction. Methods Seventeen healthy men (age: 22.35±2.27yr; body mass: 69.91± 9.78kg; height: 177.08±4.32cm) were randomly assigned to experimental (n=9) and control groups (n=8) in a double-blind manner. In both groups, subjects were given L-glutamine supplementation (0.1g.kg-1) or placebo three times a week for 4 weeks. Median frequency (MDF) and mean power frequency (MPF) for VMM and RFM muscles and also CK measurements were performed before, 24h and 48 h after a resistance training session. The resistance training included 6 sets of eccentric leg extensions to exhaustion with 75% of 1RM. Results There was no significant difference between groups for MDF or MPF in VMM and RFM. The difference of CK level between the groups was also not significant. Conclusion The results of this study indicate that glutamine supplementation has no positive effect on muscle injury markers after a resistance training session.