Miracle-dz/UniFAR-FTUs huggingface dataset:
Limited Rate Feedback Scheme for Resource Allocation in Secure Relay-Assisted OFDMA Networks

In this paper, we consider the problem of resource allocation for secure communications in decode-and-forward (DF) relay-assisted orthogonal frequency-division multiple access (OFDMA) networks. In our setting, users want to securely communicate to the base station (BS) with the help of a set of relay stations (RSs) in the presence of multiple eavesdroppers. We assume that all channel state information (CSI) of the legitimate links and only the channel distribution information (CDI) of the eavesdropper links are available. We formulate our problem as an optimization problem whose objective is to maximize the sum secrecy rate of the system subject to individual transmit power constraint for each user and RS. As a first work which considers limited feedback schemes for secure communications in cooperative OFDMA networks, we consider the limited-rate feedback case, where in addition to transmit power and subcarrier assignments, channel quantization should be performed and boundary regions of channels should be computed. We further consider the noisy feedback channel. We solve our problem using the dual Lagrange approach and propose an iterative algorithm whose convergence is analyzed. Using simulations, we evaluate the performance of the proposed scheme in numerous situations.
A Multiscale Mortar Mixed Space Based on Homogenization for Heterogeneous Elliptic Problems

We consider a second order elliptic problem with a heterogeneous coefficient written in mixed form. The nonoverlapping mortar domain decomposition method is efficient in parallel if the mortar interface coupling space has a restricted number of degrees of freedom. In the heterogeneous case, we define a new multiscale mortar space that incorporates purely local information from homogenization theory to better approximate the solution along the interfaces with just a few degrees of freedom. In the case of a locally periodic heterogeneous coefficient of period $\varepsilon$, we prove that the new method achieves both optimal order error estimates in the discretization parameters and good approximation when $\varepsilon$ is small. Moreover, we present three numerical examples to assess its performance when the coefficient is not obviously locally periodic. We show that the new mortar method works well, and better than polynomial mortar spaces.
Polyhedra Recognition by Hypothesis Accumulation

A new method is presented for the recognition of polyhedra in range data. The method is based on a hypothesis accumulation scheme which allows parallel implementations. The different objects to be recognized are modeled by a set of local geometrical patterns. Local patterns of the same nature are extracted from the scene. For the recognition of an object, local scene and model patterns having the same geometrical characteristics are matched. For each of the possible matches, the geometric transformations (i.e., rotations and translations) are computed, which allows the overlapping of the model elements with those from the scene. This transformation permits the establishment of a hypothesis on the location of the object in the scene and the determination of a point in the transformation space. The presence of an object similar to a model involves the generation of several compatible hypotheses and creates a compact cluster in the transformation space. The recognition of the object is based on the detection of this cluster. The cluster coordinates give the values of the rotations and the translations to be applied to the model such that it corresponds to the object in the scene. The exact location of this object is given by the transformed model.
Combining Statistics-Based and CNN-Based Information for Sentence Classification

Sentence classification, serving as the foundation of the subsequent text-based processing, continues attracting researchers attentions. Recently, with the great success of deep learning, convolutional neural network (CNN), a kind of common architecture of deep learning, has been widely used to this filed and achieved excellent performance. However, most CNN-based studies focus on using complex architectures to extract more effective category information, requiring more time in training models. With the aim to get better performance with less time cost on classification, this paper proposes two simple and effective methods by fully combining information both extracted from statistics and CNN. The first method is S-SFCNN, which combines statistical features and CNNbased probabilistic features of classification to build feature vectors, and then the vectors are used to train the logistic regression classifiers. And the second method is C-SFCNN, which combines CNN-based features and statistics-based probabilistic features of classification to build feature vectors. In the two methods, the Naive Bayes log-count ratios are selected as the text statistical features and the single-layer and singlechannel CNN is used as our CNN architecture. The testing results executed on 7 tasks show that our methods can achieve better performance than many other complex CNN models with less time cost. In addition, we summarized the main factors influencing the performance of our methods though experiment. Keywords-Sentence Classification; Convolutional Neural Network; Navie Bayes
Culture et classes sociales: goûts musicaux, comportements culturels et distinction sociale

Cette recherche vise a etablir dans quelle mesure les comportements culturels (pratiques et gouts culturels) revelent des identites culturelles et des orientations esthetiques propres a des classes sociales ou des fractions de classe. Dans ce travail de these, nous soumettons a l’epreuve empirique les theses les plus discutees et les plus debattues, a l’heure actuelle, dans la litterature en sociologie de la culture et de la stratification sociale, a savoir celles qui decoulent du modele complexe elabore par Bourdieu dans La Distinction et la these d’une montee de l’eclectisme des gouts culturels formulee par Peterson et ses associes au cours des annees 1990. Les analyses portent sur des donnees statistiques issues de diverses enquetes par sondage.
Testing Web Applications Through Layout Constraints

The paper focuses on bugs in web applications that can be detected by analyzing the contents and layout of page elements inside a browser's window. Based on an empirical analysis of 35 real-world web sites and applications (such as Facebook, Dropbox, and Moodle), it provides a survey and classification of more than 90 instances of layout-based bugs. It then introduces Cornipickle, an automated testing tool that provides a declarative language to express desirable properties of a web application as a set of human-readable assertions on the page's HTML and CSS data. Such properties can be verified on-the-fly as a user interacts with an application.
Simulation of plasma ionization and spectral properties with PrismSPECT

Summary form only given. PrismSPECT is a collisional-radiative spectral analysis code designed to simulate the atomic and radiative properties of LTE and non-LTE plasmas over a wide range of conditions. For a grid of user-specified plasma conditions, PrismSPECT computes spectral properties (emission and absorption), ionization fractions, atomic level populations, and line intensity ratios by solving either time-dependent or steady-state atomic rate equations. Its capabilities include computing the properties of plasmas irradiated with external radiation fields, plasmas with non-Maxwellian electron distributions, and inner-shell (e.g., K-alpha and K-beta) satellite line emission spectra.PrismSPECT has been used in the analyses of spectra obtained from plasmas spanning a wide range of conditions, including Fe opacity measurements at the Sandia National Laboratories Z facility1, short-pulse high-intensity laser experiments carried out at the MTW facility at the University of Rochester2, and experiments involving low-temperature plasmas and vapors. We will present comparisons of simulation results with experimental spectra, and describe modeling and recent upgrades to the software.
Internet Community Group Participation: Psychosocial Benefits for Women with Breast Cancer

This study examines the psychosocial benefits of Internet community group participation for women with breast cancer. A longitudinal content analysis of more than 33,200 postings from an online breast cancer bulletin board, and thematic analysis of the “life stories” of 100 women randomly selected from the bulletin board, was conducted. Psychosocial benefits included: receiving/giving information; receiving/giving social support; affect toward the discussion board, optimism toward breast cancer, increased skill or ability to cope with the disease, improved mood, decreased psychological distress, and strategies to manage stress. Over time, a positive shift was shown in women's affect toward the breast cancer and online community, and a positive correlation was found between amount of participation and psychosocial well-being.
Berkeley Expressivity Questionnaire: Deutsche Adaptation und Validierungsbefunde

The paper presents a German version of the „Berkeley Expressivity Questionnaire“ (BEQ; Gross & John, 1995). The instrument uses 16 items to assess three dimensions of expressivity: negative expressivity, positive expressivity, and impulse strength. In study 1 (n = 385), the factor structure and the psychometric properties of the BEQ were determined using confirmatory factor analysis. In a longitudinal study (study 2) the stability and validity of the BEQ were investigated: At t1, 220 participants filled out the BEQ. At t2 (6 months later), in addition to the BEQ self-report, the judgments of two raters as well as personality characteristics, positive and negative affectivity, and psychological and physical symptoms were assessed. The results show that the dimensions of the BEQ are stable and positively correlated with the raters’ judgments. While negative expressivity and impulse strength are related to neuroticism, negative affectivity, physical complaints, and depression, positive expressivity is correlated to extraversion, openness, and positive affectivity. Women showed higher scores in all three dimensions of the BEQ which were negatively related to age.
Ieee Transactions on Computer-aided Design of Integrated Circuits and Systems 1 Reliable 3d Clock-tree Synthesis Considering Nonlinear Capacitive Tsv Model with Electrical-thermal-mechanical Coupling

Title Reliable 3-D clock-tree synthesis considering nonlinear capacitive TSV model with electrical–thermal–mechanical coupling Author(s) (2013). Reliable 3-D clock-tree synthesis considering nonlinear capacitive TSV model with electrical–thermal–mechanical coupling. Abstract—A robust physical design of 3D-IC requires investigation on through-silicon-via (TSV). The large temperature and stress gradients can severely affect TSV delay with large variation. The traditional physical model treats TSV as resistor with linear electrical-thermal dependence, which ignores the fundamental device physics. In this paper, a physics-based electrical-thermal-mechanical delay model is developed for signal TSVs in 3D-IC. With consideration of liner material and also stress, a nonlinear model is established between electrical delay with temperature and stress. Moreover, sensitivity analysis is performed to relate the reduction of temperature and stress gradients with respect to dummy TSVs insertion. Taking the design of 3D clock-tree as a case study, we have formulated a nonlinear optimization problem for clock-skew reduction. By allocating dummy TSVs to reduce the temperature and stress gradients, the clock-skew introduced by signal TSVs and drivers can be minimized. A number of 3D clock-tree benchmarks are utilized in experiments. We have observed that with use of dummy TSV insertion, clock-skew can be reduced by 61.3% on average when the accurate nonlinear electrical-thermal-mechanical delay model is applied.
Feature selection of manifold learning using principal component analysis in brain MR image

Cerebral atrophy treated as one of the common feature of many diseases that affect the brain. In general, atrophy means that all of the brain has shrunk or it can be regional, affecting a limited area of the brain which ends up resulting in neural decrease related to functions that area of brain controls. Detection of early brain atrophy can help physicians to detect the disease at curable stage. In this paper brain atrophy with some given landmark positions has been evaluated using dimensionality reduction methods. A comparative study has been done between principal component analysis and manifold learning using Laplacian eigenmaps to quantify brain atrophy. In addition, a novel method has been proposed with combination of PCA and Manifold learning which evaluates brain atrophy with corresponding age groups. Selection of principal component scores to optimize manifold learning parameters added effective feature to the findings. The method has been applied to open database (IXI database). We applied principal component analysis to deformation maps derived from MR images of 250 normal subjects. After sampling, 42 subjects were taken whose principal component scores were used to discriminate between older subject and younger subject. We found a significant regional pattern of atrophy between distance of Anterior Commissure, Posterior Commissure, Anterior Commissure to both frontal lobe, Posterior Commissure to both frontal lobe with corresponding age. After going through T-test principal component analysis showed the best value of significant difference (p<;0.0036) over the Manifold learning (p<;0.4095). The proposed method outperformed both the dimensionality reduction method with a score of (p<;0.0030). Our findings indicates that multivariate network analysis of deformation maps detects typical feature of atrophy and provides a powerful tool to predict brain atrophy with age.
Stability of morphine sulfate in Cormed III (Kalex) intravenous bags.

The stability of various concentrations of morphine sulfate solution stored in Cormed III (Kalex) i.v. bags at two temperatures was investigated. Solutions of morphine sulfate 0.5, 15, 30, and 60 mg/mL were prepared under a horizontal-laminar-airflow hood with 0.9% sodium chloride solution and placed into 100-mL Kalex bags. Two bags were prepared for each concentration; one was stored at 5 degrees C and the other at 37 degrees C. Samples were analyzed in triplicate by high-performance liquid chromatography on days 0, 2, 5, 9, and 14. All morphine sulfate solutions were stable for 14 days at 37 degrees C, and the 0.5-, 15-, and 30-mg/mL solutions were stable for 14 days at 5 degrees C. However, the 60-mg/mL solution stored at 5 degrees C was found to contain 57% of the actual initial concentration on day 9 and 51% on day 14; the decrease coincided with the appearance of a white precipitate. Beginning on day 5, all the solutions displayed a light brown color that darkened as the study proceeded. This qualitative change was not associated with any change in morphine concentration. Solutions of morphine sulfate 0.5 to 60 mg/mL stored at 5 or 37 degrees C were stable for 14 days in Kalex bags, except for 60-mg/mL solutions stored at 5 degrees C for nine days or longer.
CHRONIC OBSTRUCTIVE PULMONARY DISEASE Respiratory viruses in exacerbations of chronic obstructive pulmonary disease requiring hospitalisation: a case-control study

Background: Acute exacerbations of chronic obstructive pulmonary disease (AE-COPD) are a common cause of hospital admission. Many exacerbations are believed to be due to upper and/or lower respiratory tract viral infections, but the incidence of these infections in patients with COPD is still undetermined. Methods: Respiratory syncytial virus (RSV), influenza A and B, parainfluenza 3, and picornaviruses were detected by nested reverse transcription polymerase chain reaction (RT-PCR) in upper (nasal lavage) and lower respiratory tract specimens (induced sputum). In a 2:1 case-control set up, 85 hospitalised patients with AE-COPD and 42 patients with stable COPD admitted for other medical reasons were studied. Results: Respiratory viruses were found more often in sputum and nasal lavage of patients with AE-COPD (48/85, 56%) than in patients with stable COPD (8/42, 19%, p<0.01). The most common viruses were picornaviruses (21/59, 36%), influenza A (15/59, 25%), and RSV (13/59, 22%). When specimens were analysed separately, this difference was seen in induced sputum (exacerbation 40/85 (47%) v stable 4/42 (10%), p<0.01) but was not significant in nasal lavage (exacerbation 26/85 (31%) v stable 7/42 (17%), p=0.14). In patients with AE-COPD, fever was more frequent in those in whom viruses were detected (12/48, 25%) than in those in whom viruses were not detected (2/37, 5%, p=0.03). Conclusion: Viral respiratory pathogens are found more often in respiratory specimens of hospitalised patients with AE-COPD than in control patients. Induced sputum detects respiratory viruses more frequently than nasal lavage in these patients. These data indicate that nasal lavage probably has no additional diagnostic value to induced sputum in cross-sectional studies on hospitalised patients with AE-COPD and that the role of viral infection in these patients is still underestimated.
Serial Analysis of Plasma Proteomic Signatures in Pediatric Patients with Severe Acute Respiratory Syndrome and Correlation with Viral Load

An outbreak of severe acute respiratory syndrome (SARS) has affected 33 countries on five continents, with 8098 suspected and probable cases and 774 deaths. During the SARS epidemic, more than 1700 infected cases have been reported in Hong Kong. The disease is infectious, particularly within the healthcare setting. Early diagnosis is essential to control the spread of SARS by identifying and isolating infected patients (1)(2). Diagnostic tests have been developed that detect either antibodies to or reverse transcription-PCR (RT-PCR) products of the SARS coronavirus (SARS-CoV). SARS-CoV antibodies can be reliably detected only around 20 days after disease onset (3)(4). Quantitative real-time RT-PCR assays, on the other hand, allow the detection of SARS-CoV within the first week of illness. Our recent study showed that detection sensitivity could approach 80% for plasma and serum samples from SARS patients (5)(6). Aside from improving the analytical and clinical sensitivity of the RT-PCR assays, it is also possible to develop new types of assays on the basis of other biological variables and/or technologies. In the past few years, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) has been applied to the discovery of diagnostic proteomic signatures for cancers such as prostate cancer, ovarian cancer, breast cancer, and hepatocellular carcinoma (7)(8). Here we report the presence of plasma proteomic signatures in serial blood samples from eight pediatric patients with SARS and their correlation with SARS-CoV RNA concentrations in plasma (6). The serial plasma samples investigated in this study were those examined for SARS-CoV RNA by real-time RT-PCR in our recently reported study (6). The pediatric patients were admitted to the New Territories East Cluster of Hospital Authority Hospitals in Hong Kong and satisfied the WHO surveillance case definition for SARS (9). These patients were recruited between March …
Use of Turbidimetric Growth Curves for Early Determination of Antifungal Drug Resistance of Filamentous Fungi

ABSTRACT A previously described microbroth kinetic system (J. Meletiadis, J. F. Meis, J. W. Mouton, and P. E. Verweij, J. Clin. Microbiol. 39:478-484, 2001) based on continuous monitoring of changes in the optical density of fungal growth was used to describe turbidimetric growth curves of different filamentous fungi in the presence of increasing concentrations of antifungal drugs. Therefore, 24 clinical mold isolates, including Rhizopus oryzae, Aspergillus fumigatus, Aspergillus flavus, and Scedosporium prolificans, were tested against itraconazole, terbinafine, and amphotericin B according to NCCLS guidelines. Among various parameters of the growth curves, the duration of the lag phase was strongly affected by the presence of antifungal drugs. Exposure to increasing drug concentrations resulted in prolonged lag phases of the turbidimetric growth curves. The lag phases of the growth curves at drug concentrations which resulted in more than 50% growth (for itraconazole and terbinafine) and more than 75% growth (for amphotericin B) after 24 h of incubation for R. oryzae, 48 h for Aspergillus spp. , and 72 h for S. prolificans were 4 h longer than the lag phases of the growth curves at the corresponding drug-free growth controls which varied from 4.4 h for R. oryzae, 6.5 h for A. flavus, 7.9 h for A. fumigatus, and 11.6 h for S. prolificans. The duration of the lag phases showed small experimental and interstrain variability, with differences of less than 2 h in most of the cases. Using this system, itraconazole and terbinafine resistance (presence of >50% growth) as well as amphotericin B resistance (presence of >75% growth) was determined within incubation periods of 5.0 to 7.7 h for R. oryzae (for amphotericin B resistance incubation for up to 12 h was required), 8.8 to 11.4 h for A. fumigatus, 6.7 to 8.5 h for A. flavus, and 13 to 15.6 h for S. prolificans while awaiting formal MIC determination by the NCCLS reference method.
Simultaneous Identification and δ13C Classification of Drugs Using GC with Concurrent Single Quadrupole and Isotope Ratio Mass Spectrometers *

Abstract: In this study, δ13C values of six cocaine samples were identified and classified using a single quadrupole mass spectrometer and an isotope ratio mass spectrometry (IRMS) as simultaneous gas chromatography detectors. Our instrument modification is simple to use and is useful (i) when the sample is of limited size or can only be injected once, (ii) to help identify peaks in a complicated IRMS chromatogram, and (iii) to help differentiate very simple systems when impurity profiling is not possible. The EI‐MS confirmed the identity of cocaine in each sample. The IRMS data distinguished 12 of the 15 possible pair‐wise comparisons at the 95% CL. Three samples could not be differentiated by their δ13C ratios for cocaine. ANOVA demonstrated that the measurement variance was consistently larger than the sample variance. As the δ13C values clearly show, this technique enables the exclusion of a potential common source even when two samples have otherwise identical chemical and physical properties.
The Effectiveness of Activated Surface Kapok on Removalof Heavy Metal in Wastewater

Kapok (Ceiba pentandra) fiber is a natural hollow fiber with thin shell and large cavity. It is seldom used as adsorbent for heavy metal ions. In this paper, kapok fibers is chemically modified using Diammonium Hydrogen Phosphate, (NH4)2HPO4 by impregnation treatment step after the pre-oxidation step to produce an activated surface kapok. Activated surface kapok has greater porosity that will increase the adsorption rate. Lead (Pb2+) ionic solution is used as the test material. The effectiveness of the low cost activated carbon prepared from kapok fibers, for the removal of lead from aqueous solution is investigated using experimental parameters including solution pH, contact time, adsorbent dose and initial metal ions concentration. The amount of metal residue in the solution is analyze using Atomic Absorption Spectroscopy method. Results show that heavy metal removal is optimum at pH 6.0, equilibrium contact time of 1 hour, kapok dose of 0.3 mg and initial concentration of 40 – 50 mg/L. Activated surface kapok is proven to be effective for removing heavy metals in wastewater.