Miracle-dz/UniFAR-FTUs huggingface dataset:
Kinematically complete analysis of the CLAS data on the proton structure function F 2 in a Regge-dual model

The recently measured inclusive electron-proton cross section in the nucleon resonance region, performed with the CLAS detector at the Thomas Jefferson Laboratory, has provided new data for the nucleon structure function F2 with previously unavailable precision. In this paper we propose a description of these experimental data based on a Regge-dual model for F2. The basic inputs in the model are nonlinear complex Regge trajectories producing both isobar resonances and a smooth background. The model is tested against the experimental data, and the Q 2 dependence of the moments is calculated. The fitted model for the structure function ~inclusive cross section! is a limiting case of the more general scattering amplitude equally applicable to deeply virtual Compton scattering. The connection between the two is discussed.
Parental smoking during pregnancy and cardiovascular structures and function in childhood: the Generation R Study.

BACKGROUND Foetal smoke exposure might lead to foetal developmental adaptations that permanently affect the cardiovascular system. We assessed the associations of both maternal and paternal smoking during pregnancy with childhood cardiovascular structures and function. METHOD In a prospective cohort study among 5565 children, we examined whether maternal and paternal smoking during pregnancy are associated with blood pressure, carotid-femoral pulse wave velocity and left cardiac structures and function in 6-year-old children. RESULTS As compared with children from non-smoking mothers, children from mothers who smoked more than 10 cigarettes per day had a higher diastolic blood pressure [difference 1.43 mmHg (95% confidence interval: 0.22, 2.63)]. Maternal smoking during pregnancy was not associated with systolic blood pressure, childhood carotid-femoral pulse wave velocity or left cardiac structures. Maternal smoking of 10 or more cigarettes per day was associated with a higher fractional shortening in childhood [difference 1.01% (95% confidence interval: 0.18, 1.84)]. Among mothers who did not smoke during pregnancy, paternal smoking was associated with aortic root diameter but not with other cardiovascular outcomes. CONCLUSIONS Maternal smoking during pregnancy is associated with higher diastolic blood pressure and fractional shortening, although the effect estimates are small. The stronger effect estimates for maternal smoking compared with paternal smoking might suggest that direct intrauterine adaptive responses are involved as underlying mechanisms.
Kernel energy method: application to insulin.

In two recent articles a method has been described for calculating the total energy of large molecules. The method is called the kernel energy method (KEM) and requires knowledge of the crystal structure of interest. Calculations are simplified by adopting the approximation that a full molecule could be represented by smaller kernels of atoms. The KEM was illustrated with peptides ranging in size from 4 to 19 amino acid residues, and was found to deliver accurate results. The use of the KEM does not depend upon a particular choice of basis functions and is applicable across quantum computational methods of differing levels of accuracy. These earlier investigations suggested that the KEM could be used to calculate the ab initio quantum mechanical energy of proteins. An application has been made with the protein insulin, composed of 51 aa. Accurate KEM Hartree-Fock energies are obtained for the separate A and B chains of insulin and for their composite structure in the full insulin molecule. A limited basis is used to make possible calculation of the full insulin molecule, which can be used as a standard of accuracy for the KEM calculation. The KEM result obtained is E(KEM) = -21104.7656 a.u. It differs from a full molecule Hartree-Fock result by only 0.000002%. The solvent molecules can be treated effectively as a separate kernel. The KEM result for the fully solvated insulin molecule is E(KEM) = -26275.4127 a.u. , differing from the full molecule Hartree-Fock result by as little as 0.000023%.
A Framework for Autonomic Performance Management of Virtual Machine-Based Services

This paper presents the design for a modular framework for autonomic QoS management of virtual machine environments. The framework separates the management APIs provided by individual vir- tual machine technologies from the high-level control algorithms, which makes the design of generic controllers possible. In addition, control al- gorithms can be replaced without eort, which provides an easy way for comparing the performance of dierent control algorithms. We discuss first approaches to control algorithms that were designed the framework. In addition, we present the prototypical implementation and show a num- ber of test results that were gained during the validation of the approach. The paper closes with a conclusion and an overview on future work.
A model of diffusion, based on the equation of the Jeffreys type

The diffusion equation (DE) is widely used for approximate description of non-anomalous diffusion and Brownian motion (BM). However, the DE is wrong in describing the mean-square displacement (MSD) of a particle at small values of time, where the MSD must be ballistic. We consider the equation of the Jeffreys type as a model equation for description of diffusion. We find that the MSD in the framework of this model is the same as that in the BM described by the standard Langevin equation.
Extended Alamouti codes in correlated channels using partial feedback

In this paper we present a family of quasi-orthogonal space-time codes for correlated MIMO (multi-input/multi-output) channels using four and eight transmit antennas when only partial channel state information is sent back to the transmitter. Transmit diversity is improved up to nearly the optimum diversity value. This high diversity can be exploited with zero forcing receivers as well as with maximum-likelihood receivers.
A novel simulation system for the performance evaluation of 3GPP LTE system in indoor scenarios

This article introduces a novel distributed simulation system for diverse simulation tasks of communications systems. With the help of its parallel distributed structure and outstanding computing power, many computationally expensive simulations can be completed in an acceptable duration. Moveover, its cooperative infrastructure is suitable for simulation tasks in multiuser scenarios or other tasks in a closed loop system. In this contribution, the general platform is applied to predict the downlink performance of a 3rd generation partnership project (3GPP) long-term-evolution (LTE) system in an indoor scenario. To achieve the required channel impulse responses (CIRs) a commercial ray tracing tool named dasiawireless insitepsila from Remcom is used. Finally two different methods to obtain the throughput are compared, first one based on the signal to noise ratio and second one based on the full channel impulse response information.
Generalizability and Simplicity as Criteria in Feature Selection: Application to Mood Classification in Music

Classification of musical audio signals according to expressed mood or emotion has evident applications to content-based music retrieval in large databases. Wrapper selection is a dimension reduction method that has been proposed for improving classification performance. However, the technique is prone to lead to overfitting of the training data, which decreases the generalizability of the obtained results. We claim that previous attempts to apply wrapper selection in the field of music information retrieval (MIR) have led to disputable conclusions about the used methods due to inadequate analysis frameworks, indicative of overfitting, and biased results. This paper presents a framework based on cross-indexing for obtaining realistic performance estimate of wrapper selection by taking into account the simplicity and generalizability of the classification models. The framework is applied on sets of film soundtrack excerpts that are consensually associated with particular basic emotions, comparing Naive Bayes, k-NN, and SVM classifiers using both forward selection (FS) and backward elimination (BE). K-NN with BE yields the most promising results - 56.5% accuracy with only four features. The most useful feature subset for k-NN contains mode majorness and key clarity, combined with dynamical, rhythmical, and structural features.
Distinct Motor Strategies Underlying Split-Belt Adaptation in Human Walking and Running

The aim of the present study was to elucidate the adaptive and de-adaptive nature of human running on a split-belt treadmill. The degree of adaptation and de-adaptation was compared with those in walking by calculating the antero-posterior component of the ground reaction force (GRF). Adaptation to walking and running on a split-belt resulted in a prominent asymmetry in the movement pattern upon return to the normal belt condition, while the two components of the GRF showed different behaviors depending on the gaits. The anterior braking component showed prominent adaptive and de-adaptive behaviors in both gaits. The posterior propulsive component, on the other hand, exhibited such behavior only in running, while that in walking showed only short-term aftereffect (lasting less than 10 seconds) accompanied by largely reactive responses. These results demonstrate a possible difference in motor strategies (that is, the use of reactive feedback and adaptive feedforward control) by the central nervous system (CNS) for split-belt locomotor adaptation between walking and running. The present results provide basic knowledge on neural control of human walking and running as well as possible strategies for gait training in athletic and rehabilitation scenes.
DASTPC: Performance of dual-polarized antenna based space-time-polarization precoding over Ricean-K channel with imperfect CSI (invited paper)

In this work, we investigate the system model, key enabling technique, and the associated performance for an Nr × Nt dual polarized MIMO (DP-MIMO) based communication system, wherein only imperfect channel state information is available at the transmitter. The DP-MIMO channel involves the imperfect spatial fading and perfect polarization fading. At the transmitter, the precoding scheme based on oblique projection is designed, which can effectively suppress the cross-polarization interference. We conduct extensive simulations to analyze the symbol error rate (SER) performance for different estimation errors and make comparisons between the 4 × 1 DP-MIMO system and uni-polarized MIMO (UP-MIMO). It is shown that the SER performance of 4 × 1 DP-MIMO at low signal noise ratio (SNR) is less sensitive to the estimation errors, comparing with UP-MIMO. Although the SER of DP-MIMO scheme does not outperform UP-MIMO at low SNR region, it can achieve better SER performance at high SNR when the transmit antenna number exceeds one certain threshold under Ricean channel.
Quand je sors d'accueil: linguistic integration of immigrant adolescents in Quebec secondary schools

This article describes the social, linguistic and academic integration processes of immigrant students in an area of low-density immigration in Quebec, Canada. Interviews were conducted with 15 secondary school students who had been in the country for 2 months to 4 years, in order to get a wide sampling of their experiences of the process of integration. The 45 minute individual interviews were semi-structured to allow students' priorities and concerns to dominate the data and to obtain emic perspectives. These adolescents recounted their experiences of isolation, and the most discussed topics were conflicts between immigrants and Quebec-born students and difficulties in establishing friendships with Quebeckers. Immigrant students reported impressions of the inauthenticity of their French language learning in closed accueil classes due to their isolation from regular stream classes. The data indicate a striking segregation between students of immigrant origins and host society youth in this school, revealing problematic aspects of the system of accueil classes and the exclusionist school discourses that prevail. Policy implications include the necessity of creating inclusive school discourses and providing intercultural education for all students.
Crime and Enforcement in Immigrant Neighborhoods

Immigration and crime have received much popular and political attention in the past decade and have been a focus of episodic social attention for much of the history of the United States. Recent policy and legal discourse suggests that the stigmatic link between immigrants and crime has endured, even in the face of evidence to the contrary. This study addresses the relationship between immigration and crime in urban settings, focusing on areal units where immigrants tend to cluster spatially as well as socially. The authors ask whether immigration creates risks or benefits for neighborhoods in terms of lower crime rates. The question is animated in part by a durable claim in criminology that areas with large immigrant populations are burdened by elevated levels of social disorder and crime. In contrast, more recent theory and research suggest that “immigrant neighborhoods” may simply be differentially organized and function in a manner that reduces the incidence of crime. Accordingly, this research investigates whether immigrants are associated with differences in area crime rates. In addition, the authors ask whether there are differences in the effects of immigration on neighborhood crime rates by the racial and ethnic makeup of the foreign-born populations. Finally, the authors examine the effects of immigration on patterns of enforcement.
A Multi-Batch L-BFGS Method for Machine Learning

The question of how to parallelize the stochastic gradient descent (SGD) method has received much attention in the literature. In this paper, we focus instead on batch methods that use a sizeable fraction of the training set at each iteration to facilitate parallelism, and that employ second-order information. In order to improve the learning process, we follow a multi-batch approach in which the batch changes at each iteration. This can cause difficulties because L-BFGS employs gradient differences to update the Hessian approximations, and when these gradients are computed using different data points the process can be unstable. This paper shows how to perform stable quasi-Newton updating in the multi-batch setting, illustrates the behavior of the algorithm in a distributed computing platform, and studies its convergence properties for both the convex and nonconvex cases.
Comparing Differences in Accuracy across Conditions or Individuals: An Argument for the Use of Log Odds

In experimental psychology, the degree of difference between the proportions of correctly solved items on two related tests (such as word lists) has been calculated by different methods, for example, a simple difference (e.g. as used in within-subjects ANOVAs), difference relative to potential gain, quotient, difference between standardized z-scores, or by Signal Detection Theory's d’, every one of which may yield different results. The present article discusses the choice of methods with an example from reading research concerned with contextual facilitation in readers with different abilities. Assuming that the total number of correctly solved items captures all relevant variance in subjects’ abilities (i.e. it is a sufficient measure), it is demonstrated that the logarithm of the quotient between odds for the frequencies of correct responses (log odds) is the most suitable method of calculation. For example, calculations based on log odds provide an appropriate ranking of the subjects, from relevant for repeated-measures ANOVAs. The aims of the present paper are to draw attention to the problem of comparing differences, to evaluate current methods of calculation, and to present a consistent solution to the problem. We illustrate the problem by applying several current methods of expressing differences in proportion correct to the same set of data: they yield radically different results. The choice of an appropriate method depends on the assumptions made about the underlying metric. We argue for a solution-the log odds measure-on the basis of Rasch's (1968a, 1968b) measurement model. This relies on a demonstration that, given a set of test items given to a set of subjects, the proportion of correct is, in technical terms, a sufficient statistic -that is, it captures all relevant variation in a subject's ability (or an item's difficulty). The example for the presentation of the problem is selected from recent reading research using comparison of accuracy in two related reading tasks. Reading accuracy with two tasks is a suitable example because it is a simple, much-used design. Researchers
Stochastic modeling and signal processing of nano-scale protein-based biosensors

This paper considers the dynamic modeling and signal processing of a biosensor incorporating gramicidin A (gA) ion channels. The gA ion channel based biosensor provides improved sensitivity in rapid detection of biological analytes and is easily adaptable to detect a wide range of analytes. In this paper, the electrical dynamics of the biosensor are modeled by an equivalent second order linear system. The chemical dynamics of the biosensor response to analyte concentration are modeled by a two-time scale nonlinear system of differential equations. An optimal input excitation is designed for the biosensor to minimize the covariance of the channel conductance estimate. By using the theory of singular perturbation, we show that the channel conductance varies according to one of three possible modes depending on the concentration of the analyte present. A multi-hypothesis testing algorithm is developed to classify the analyte concentration in the system as null, medium or high. Finally experimental data collected from the biosensor in response to various analyte concentrations are used to verify the modeling of the biosensor as well as the performance of the multi-hypothesis testing algorithm.
Enhancing Film Discovery through Social Media Traces Using Sentiment Analysis and Machine Learning Combined Approach

Films have historically played a significant role in cultural expression and entertainment, influencing global people and affecting society on various levels. In the contemporary era of digital technology, characterized by vast amounts of data, the accessibility and discovery of films have become crucial. Nevertheless, efficiently searching for relevant movies within this vast data landscape poses a significant challenge. Current search systems primarily rely on textual and visual analysis and often fail to incorporate users' social interactions as social media traces valuable on various social platforms. To address this challenge, we introduce Social media-Enhanced Ranking Framework (SERF) that aims to enhance the research process and gain a deeper understanding of users' sentiments and preferences. Our research aligns with the United Nations Sustainable Development Goal 9, which emphasizes innovation in industry, technology and infrastructure. The objective is to redefine how we discover films combining between traditional information retrieval methods and the dynamic feedback loop offered by social media. In the proposed approach, film recommendations are determined through a combination of textual scores and a social search model. This last relies on the frequency of generated social media traces and sentiment analysis conducted by machine learning algorithms. Our empirical experiments reveal the pivotal impact of the exploitation of the reactive and the descriptive social traces on the repositioning of cinematic materials into the final re-ranked list. Additionally, our findings highlight the superior performance of the deep RNN-LSTM model with embedding, outperforming traditional machine learning algorithms with an AUC score of 89%, affirming the effectiveness of deep learning techniques in enhancing predictive accuracy of relevant documents.
Spatial Compliant Motion of a Rigid Body Constrained by a Frictional Contact

In this paper, we study the quasi-static motion of an elastically suspended, unilaterally constrained rigid body. The motion of the rigid body is determined, in part, by the position controlled motion of its support base and by the behavior of the elastic suspension that couples the part to the support. The motion is also determined, in part, by contact with a frictional surface that both couples the rigid body to the unilateral constraint and generates a friction force. The unknown friction force, however, is determined in part by the unknown direction of the rigid-body motion. We derive an analytically solvable set of equations that simultaneously determines both the friction force and the resulting rigid-body motion. We also address the issues of whether a solution to these equations exists and whether the obtained solution is unique. We show that, for any passive compliant system in which the nominal motion imposes contact, a solution to the set of motion equations always exists. We also show that, for any passive system with an upper bounded friction coefficient, the solution is unique. Two sufficient conditions that guarantee the uniqueness of the solution are presented.
An Exact Statistical Representation of $\alpha-\eta-\kappa-\mu$ Fading Model for THz Wireless Communication

The $\alpha-\eta-\kappa-\mu$ is one of the most generalized and flexible channel models having an excellent fit to experimental data from diverse propagation environments. The existing statistical results on the envelope of $\alpha-\eta-\kappa-\mu$ model contain an infinite series, prohibiting its widespread application in the performance analysis of wireless systems. This paper employs a novel approach to derive density and distribution functions of the envelope of the $\alpha-\eta-\kappa-\mu$ fading channel without an infinite series approximation. The derived statistical results are presented using a single Fox's H-function for tractable performance analysis, especially for high-frequency mmWave and terahertz wireless transmissions. We also develop an asymptotic analysis using the Gamma function, which converges to the exact values within a reasonable range of channel parameters. To further substantiate the proposed analysis, we present the exact outage probability and average bit-error-rate (BER) performance of a wireless link subjected to the $\alpha-\eta-\kappa-\mu$ fading model using a single trivariate Fox's H-function. We obtain the diversity order of the system by analyzing the outage probability at a high signal-to-noise (SNR) ratio. We use simulations to demonstrate the significance of the developed statistical results compared with the existing infinite series representation of the $\alpha-\eta-\kappa-\mu$ model.