Miracle-dz/UniFAR-FTUs huggingface dataset:
Asymptotic Electromagnetic Fields in Models of Quantum-Mechanical Matter Interacting with the Quantized Radiation Field

In models of (non-relativistic and pseudo-relativistic) electrons interacting with static nuclei and with the (ultraviolet-cutoff) quantized radiation field, the existence of asymptotic electromagnetic fields is established. Our results yield some mathematically rigorous understanding of Rayleigh scattering and of the phenomenon of relaxation of isolated atoms to their ground states. Our proofs are based on propagation estimates for electrons inspired by similar estimates known from N-body scattering theory. I Introduction In this paper we study the scattering of light at non-relativistic and pseudo-relativistic, quantum mechanical electrons moving under the influence of an external potential and minimally coupled to the soft modes of the quantized electromagnetic field. The external potential may be the Coulomb potential generated by a configuration of static nuclei. Our goal is to establish the existence of asymptotic electromagnetic fields on states of the system with the property that the velocities of all electrons present are smaller than the velocity of light, (in a sense to be made mathematically precise). This property is automatically satisfied if one chooses relativistic kinematics in the description of electrons, because the propagation velocity of a massive relativistic particle is smaller than the velocity of light. In contrast, if the kinematics of electrons is non-relativistic these particles can propagate arbitrarily fast, and the condition that the propagation velocities of electrons in a state of the system are smaller than the velocity of light is a very stringent one. It is satisfied if all electrons remain bound to nuclei. But, in realistic models, such “bound states” are not dense in the Hilbert space of the system.
Development of a Cell Phone based Remote Control System : an Effective Switching System for Controlling Home and Office Appliances

— This paper demonstrates a novel method which enable users to control their home appliances and systems from remote using a cell phone-based interface. To access the control unit, the user should send an authentication code (DTMF) along with the required/desired function/action to his/her home control system via Global S ytem for Mobile communication(GS M). Upon being properly authenticated, the cell phone-based interface at home (control unit) would relay the commands to a microcontroller that would perform the required function/action, and return a function completion code that would be sent to the source of the original command (user's cell phone). I. INTRODUCTION The aim of the proposed system is to develop a cost effective solution that will provide controlling of home appliances remotely and enable home security against intrusion in the absence of homeowner. The system provides availability due to development of a low cost system. The home appliances control system with an affordable cost was thought to be built that should be mobile providing remote access to the appliances and allowing home security. Though devices connected as home and office appliances consume electrical power. These devices should be controlled as well as turn on /off if required. Most of the times it was done manually. Now it is a necessity to control devices more effectively and efficiently at any time from anywhere. In this system, we are going to develop a cellular phone based home/office appliance controller [6], [9]. This system is designed for controlling arbitrary devices, it includes a cell phone (not included with the system kit, end user has to connect his/her cell phone to the system) which is connect to the system via head set. To active the cellular phone unit on the system a call is to be made and as the call is answered, in response the user would enter a two/three digit password to access the system to control devices. As the caller press the specific password, it results in turning ON or OFF specific device. The device switching is achieved by Relays [10]. Security preserved because these dedicated passwords owned and known by selected persons only. For instance, our system contains an alarm unit giving the user a remote on/off mechanism, which is capable of informing up to five
Towards a Model for Recognising the Social Attitude in Natural Interaction with Embodied Agents

The problem of implementing socially intelligent agents has been widely investigated in the field of both Embodied Conversational Agents (ECAs) and Social Robots that have the advantage of offering to people the possibility to relate with computer media at a social level. We focus our study on the recognition of the social response of users to embodied agents in the context of ambient intelligence. In this paper we describe how we extended a model for recognizing the social attitude in natural conversation from text by adding two additional knowledge sources: speech and gestures.
Compressed Sensing with uncertainty - the Bayesian estimation perspective

The Compressed Sensing (CS) framework outperforms the sampling rate limits given by Shannon's theory. This gap is possible since it is assumed that the signal of interest admits a linear decomposition of few vectors in a given sparsifying Basis (Fourier, Wavelet, .). Unfortunately in realistic operating systems, uncertain knowledge of the CS model is inevitable and must be evaluated. Typically, this uncertainty drastically degrades the estimation performance of sparse-based estimators in the low noise variance regime. In this work, the Off-Grid (OG) and Basis Mismatch (BM) problems are compared in a Bayesian estimation perspective. At first glance, we are tempted to think that these two acronyms stand for the same problem. However, by comparing their Bayesian Cramèr-Rao Bounds (BCRB) for the estimation of a L-sparse amplitude vector based on N measurements, it is shown that the BM problem has a lower BCRB than the OG one in a general context. To go further into the analysis we provide for i.i. d. Gaussian amplitudes and in the low noise variance regime an interesting closed-form expression of a normalized 2-norm criterion of the difference of the two BCRB matrices. Based on the analysis of this closed-form expression, we obtain two conclusions. Firstly, the two uncertainty problems cannot be confused for a non-zero mismatch error variance and with finite N and L. Secondly, the two problems turn to be similar for any mismatch error variance in the large system regime, i.e., for N, L → ∞ with constant aspect ratio N/L → ρ.
Testing a Dynamic Neural Field model of children's category labeling

Recently, Dynamic Neural Field models have shed light on the flexible and dynamic processes underlying young children’s emergent categorisation and word learning (DNF; e.g., Spencer & Schoner [1]). DNF models are a distinct class of neural network in which perceptual features can be represented topologically and time continuously, complementing existing connectionist models of cognitive development by building category representations that are available for inspection at any given stage in learning. Recent research in infant categorization and word learning has demonstrated that young children’s ability to learn and generalise labels for novel object categories is profoundly affected by the perceptual variability of the to-be-learned category. We have captured these data in a DNF model of children’s category label learning. Given a known vocabulary, our model exploits mutual exclusivity via simple associative processes to map novel labels to novel categories, and is able to retain and generalize these newly-formed mappings. The model was used to generate the testable prediction that children’s generalizations of novel category labels should be contingent on the number and closeness of objects’ perceptual neighbours. We present a replication of this prediction, via an empirical study with 30-month-old children. In line with the model, children were only able to generalize novel words to completely novel objects when those objects were central to the just-encountered category, rather than peripheral. This empirical replication demonstrates the predictive validity of DNF models when applied to cognitive development. Further, the data suggest that children’s ability to categorise and learn labels is not a conceptually-based, stepwise phenomenon, but rather a graded, emergent process. As such, these data add weight to associative, dynamic systems approaches to understanding language learning, categorisation, and cognition more generally.
Efficiency and Environmental Factors in the US Electricity Transmission Industry

The electricity industry in most developed countries has been restructured over recent decades with the aim of improving both service quality and firms’ performance. Regulated segments (e.g. transmission) still provide the infrastructure for the competitive segments and represent a notable amount of the total price paid by final customers. However there is a lack of empirical studies that analyze firms’ performance in the electricity transmission sector. We conduct an empirical analysis of the US electricity transmission companies for the period 2001-2009. We use stochastic frontier models that allow us to identify determinants of firms’ inefficiency and to control for weather conditions, potentially one of the most decisive uncontrollable factors in electricity transportation. Our results suggest that there is room for improvement in the performance of the US electricity transmission system. Regulators should also take into account that more adverse conditions generate higher levels of inefficiency and that achieving long-term efficiency improvements tends to deteriorate firms’ short-term relative performance.
Effect of Breastfeeding on Childhood BMI and Obesity

AbstractThe objective of this study is to investigate the effect of breastfeeding on childhood obesity in China.We used data collected from the China Family Panel Studies, an ongoing, prospective, and nationwide longitudinal study to explore the extensive and dynamic social changes in China. A total of 7967 children were included in the analysis. Duration of breastfeeding was first treated as a continuous variable and subsequently dichotomized into ever versus never, ≥6 months versus <6 months, ≥8 months versus < 8 months, and ≥12 months versus <12 months. Multiple imputation was conducted and regressions with propensity score matching were performed. We also performed quantile regression to examine whether breastfeeding has an effect on childhood obesity among children with a specific quantile of body mass index (BMI). Consistent with findings from recent studies, in both adjusted and adjusted regressions, we did not find any statistically significant effect of breastfeeding on reducing the risk of obesity (unadjusted odds ratio, OR = 1.02, 95% confidence interval, CI 0.99, 1.05, P = 0.12; adjusted OR 1.01, 95% CI 0.98, 1.05, P = 0.36) or excessive weight (unadjusted OR = 1.01, 95% CI 0.99, 1.03, P = 0.26; adjusted OR = 1.00, 95% CI 0.98, 1.02, P = 0.90). Results were similar using various dichotomization of duration of breastfeeding. Quantile regression revealed that longer duration of breastfeeding is associated with higher BMI among children with small to medium quantile of BMI.Our findings echo recent research and caution against any population-wide strategy in attempting to reduce overweight and obesity through promotion of breastfeeding.
Weak lensing detection in CMB maps

The weak lensing effects are known to change only weakly the shape of the power spectrum of the Cosmic Mi- crowave Background (CMB) temperature fluctuations. I show here that they nonetheless induce specic non-Gaussian effects thatcanbedetectablewiththefour-pointcorrelationfunctionof the CMB anisotropies. The magnitude and geometrical depen- dences of this correlation function are investigated in details. It is thus found to scale as the square of the derivative of the two-point correlation function and as the angular correlation function of the gravitational displacement eld. It also contains specic dependences on the shape of the quadrangle formed by the four directions. When averaged at a given scale, the four-point function, that identies with the connected part of the fourth moment of the probability distribution function of the local ltered tem- perature, scales as the square of logarithmic slope of its second moment, and as the variance of the gravitational magnication at the same angular scale. All these effects have been computed for specic cosmo- logical models. It is worth noting that, as the amplitude of the gravitational lens effects has a specic dependence on the cos- mologicalparameters,thedetectionofthefour-pointcorrelation function could provide precious complementary constraints to those brought by the temperature power spectrum.
Correlation of human immunodeficiency virus type 1 RNA levels in blood and the female genital tract.

In this study, the correlations of human immunodeficiency virus type 1 (HIV-1) RNA levels in blood plasma, vaginal secretions, and cervical mucus of 52 HIV-1-infected women were determined. The amount of cell-free HIV-1 RNA in blood plasma was correlated with that in vaginal secretions (Spearman's rank correlation coefficient (r) = 0.64, P<. 001). In both blood plasma and vaginal secretions, the amounts of cell-free and cell-associated HIV-1 RNA were highly correlated (r=0.76, P<.01 and r=0.85, P<.01, respectively). Cell-free HIV-1 RNA levels in blood plasma and vaginal secretions were negatively correlated with CD4+ T lymphocyte count (r=-0.44, P<.01 and r=-0.40, P<.01, respectively). Similar to the effect observed in blood plasma, initiation of antiretroviral therapy significantly reduced the amount of HIV-1 RNA in vaginal secretions. These findings suggest that factors that lower blood plasma virus load may also reduce the risk of perinatal and female-to-male heterosexual transmission by lowering vaginal virus load.
Recursive prediction error parameter estimator for non-linear models

Abstract A recursive prediction error parameter estimation algorithm is derived for systems which can be represented by the NARMAX (non-linear ARMAX) model. A convergence analysis is presented using the differential equation approach, and the new concept of m-invertibility is introduced. The analysis shows that while a highly non-linear process model may be used to capture the non-linearity of the system it is advisable to fit a simple noise model. The results of applying the algorithm to both simulated and real data are included.
Comparison of Whole Blood, Serum, and Plasma for Early Detection of Candidemia by Multiplex-Tandem PCR

ABSTRACT We applied multiplex-tandem PCR (MT-PCR) to 255 EDTA whole-blood specimens, 29 serum specimens, and 24 plasma specimens from 109 patients with Candida bloodstream infection (candidemia) to determine whether a diagnosis could be expedited in comparison with the time to diagnosis by the use of standard blood culture. Overall, the MT-PCR performed better than blood culture with DNA extracted from whole blood from 52/74 (70%) patients, accelerating the time to detection (blood culture flagging) and determination of the pathogenic species (by use of the API 32C system [bioMérieux, Marcy l'Etoile, France]) by up to 4 days (mean, 2.2 days; range, 0.5 to 8 days). Candida DNA was detected more often in serum (71%) and plasma (75%) than in whole blood (54%), although relatively small numbers of serum and plasma specimens were tested. The sensitivity, specificity, positive predictive value, and negative predictive value of the assay with whole blood were 75%, 97%, 95%, and 85%, respectively. Fungal DNA was not detected by MT-PCR in 6/24 (25%) whole-blood samples drawn simultaneously with the positive blood culture sample. MT-PCR performed better with whole-blood specimens stored at −20°C (75%) and when DNA was extracted within 1 week of sampling (66%). The molecular and culture identification results correlated for 61 of 66 patients (92%); one discrepant result was due to misidentification by culture. All but one sample from 53 patients who were at high risk of candidemia but did not have proven disease were negative by MT-PCR. The results demonstrate the good potential of MT-PCR to detect candidemia, to provide Candida species identification prior to blood culture positivity, and to provide improved sensitivity when applied to with serum and plasma specimens.
Enhancement energy efficient TDMA wake up MAC protocol by clustering for wireless sensor networks

This paper proposes energy efficient self organization and medium access control (MAC) protocols for wireless sensor networks. The proposed protocol is based on Time Division Multiple Access Wake Up (TDMA-W) principle and is referred to as CBTW. In the proposed protocol a sensor utilizes its assigned slot only when it is sending or receiving information, otherwise its receiver and transmitter are turned off to avoid unnecessary neighbor listening. In order to accelerate receive response, wake-up packets are used to activate a sleeping node. In this protocol, after selecting cluster head and creating spanning tree, the nodes are scheduled based on TDMA-W method to gather data. When compared with the existing energy efficient MAC protocols, such as TDMA-W and 10% S-MAC, the performance results show that the proposed CBTW protocol consumes only 50% of the TDMA-W and 20% S-MAC power.
Hubble Space Telescope Imaging of the CFRS and LDSS Redshift Surveys. III. Field Elliptical Galaxies at 0.2 < z < 1.0

Two-dimensional surface photometry has been performed on a magnitude-limited sample of 46 field galaxies that are classified as ellipticals based on two-dimensional fitting of their luminosity profiles using Hubble Space Telescope imaging. These galaxies are described well by a de Vaucouleurs R1/4 profile. The sample was selected from the combined Canada-France and LDSS redshift surveys and spans the redshift range 0.20 < z < 1.00. This analysis reveals several clear evolutionary trends. First, the relationship between galaxy half-light radius and luminosity evolves with redshift such that a galaxy of a given size is more luminous by ΔMB = -0.97 ± 0.14 mag at z = 0.92 relative to the local cluster elliptical relation. Second, the mean rest-frame color shifts blueward with redshift by Δ(U-V) = -0.68 ± 0.11 at z = 0.92 relative to the same relation in the Coma Cluster. These shifts in color and luminosity of field elliptical galaxies are similar to those measured for cluster ellipticals. Approximately one-third of these elliptical galaxies (independent of redshift) exhibit [O II] 3727 emission lines with equivalent widths >15 Å, indicating ongoing star formation. Therefore, field elliptical galaxies are not composed entirely of very old stellar populations. Estimated star formation rates (SFR) together with stellar population evolutionary models imply that ≤5% of the stellar mass in the elliptical galaxy population has been formed since z = 1. We find some evidence that the dispersion in color among field ellipticals at z ~ 0.55 may be larger than that seen among samples of cluster ellipticals and S0 galaxies at similar redshift. We see no evidence for a decline in the space density of early-type galaxies with look-back time. Both the ⟨V/Vmax⟩ statistics and a comparison with local luminosity functions are consistent with the view that the population of massive early-type galaxies was largely in place by z ~ 1. This implies that merging is not required since that time to produce the present-day space density of elliptical galaxies. However, the statistics are poor: a larger sample is required to produce a decisive result.
Improved Portfolio Optimization Combining Multiobjective Evolutionary Computing Algorithm and Prediction Strategy

In conventional mean-variance model of portfolio optimization problem the expected return is taken as the mean of the past returns. This assumption is not correct and hence the method leads to poor portfolio optimization performance. Hence an alternative but efficient method is proposed in which the mean and variance of expected return are first predicted with a low complexity functional link artificial neural network model (FLANN). The predicted values of mean and variance are consequently used in multi objective swarm intelligence techniques for achieving better performance. The multi objective swarm intelligence techniques chosen are non-dominated sorting genetic algorithm-II (NSGA – II) and multi objective particle swarm optimization (MOPSO). The performance of the proposed prediction based portfolio optimization model has been compared with the Markowitz mean-variance model. The comparison of the performance includes three performance metrics, Pareto front and nonparametric statistical test using the Sign test. On examining the performance metrics it is observed that the proposed prediction based portfolio optimization model approach provided improved Pareto solutions but maintaining adequate diversity.
A review of podcasting in higher education: Its influence on the traditional lecture

This paper examines the possible influence of podcasting on the traditional lecture in higher education. Firstly, it explores some of the benefits and limitations of the lecture as one of the dominant forms of teaching in higher education. The review then moves to explore the emergence of podcasting in education and the purpose of its use, before examining recent relevant literature about podcasting for supporting, enhancing, and indeed replacing the traditional lecture. The review identifies three broad types of use of podcasting: substitutional, supplementary and creative use. Podcasting appears to be most commonly used to provide recordings of past lectures to students for the purposes of review and revision (substitutional use). The second most common use was in providing additional material, often in the form of study guides and summary notes, to broaden and deepen students' understanding (supplementary use). The third and least common use reported in the literature involved the creation of student generated podcasts (creative use). The review examines three key questions: What are the educational uses of podcasting in teaching and learning in higher education? Can podcasting facilitate more flexible and mobile learning? In what ways will podcasting influence the traditional lecture? These questions are discussed in the final section of the paper, with reference to future policies and practices.
Black-box optimization of sensor placement with elevation maps and probabilistic sensing models

This paper proposes a framework for the optimization of sensor placement. Traditional schemes rely on simple sensor behaviours and environmental factors. The consequences of these oversimplifications are unrealistic simulation of sensor performance and, thus, suboptimal sensor placement. In this paper, we develop a novel framework to tackle the sensor placement problem using a probabilistic coverage and corresponding membership functions for sensing range and sensing angle, which takes into consideration sensing capacity probability as well as critical environmental factors such as terrain topography. We then implement several optimization schemes for sensor placement optimization, including simulated annealing, L-BFGS, and CMA-ES.