Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of the Undesired RF-IF Chain Effects on the LS-CMA based Beamformer in CDMA Mobile Communications

In mobile communications, nonideal operation of the RF-IF chain has significant effects on the signal received by the BS. Since most beamforming algorithms use the received signal parameters to steer suitable beam, any error or uncertainty cause significant degradation in beamforming performance. In this paper, effects of some of the most important RF-IF chain errors occurred in down conversion process are investigated theoretically as well as by simulation. Our investigations show that the error caused by the difference between down converters, has a significant effect on the beamformer performance. It is shown that the RF-IF chain phase and amplitude errors have a more significant effect on the beamformer performance than the other errors. Because of the higher sensitivity of the phase of the received signal, phase error has the most significant effect.
In Medication‐Overuse Headache, fMRI Shows Long‐Lasting Dysfunction in Midbrain Areas

The primary aim of our study was to evaluate if a group of medication‐overuse headache (MOH) patients present dysfunctions in the mesocorticolimbic dopamine circuit. The secondary aim was to disentangle the role of the medication overuse and of the acute/chronic headache in determining these alterations and to investigate their persistence.
Factors Contributing to Reduced Caregiver Strain in a Publicly Funded Child Mental Health System

This study examined caregiver strain in families who initiated mental health services for their child. Predictors of strain and the bidirectional relation between strain and child symptoms were examined. Participants included 218 children aged 4 to 13 with disruptive behavior problems and their caregivers, plus 96 psychotherapists, recruited from six publicly funded clinics. Child disruptive behavior severity and caregiver strain were assessed at baseline, 4, and 8 months. Multilevel models were used to examine predictors of reduced caregiver strain, and autoregressive cross-lagged models were used to examine the bidirectional relations between change in caregiver strain and behavior problems over time. There were small to medium decreases in caregiver strain over the 8 months after the initiation of mental health services, but few factors predicted change other than initial behavior problem severity. Whereas more severe initial child symptoms predicted greater reductions in caregiver strain, greater child symptom severity sustained at 4 months predicted lesser improvements in caregiver strain. Simultaneously, greater caregiver strain predicted less improvement in child symptom severity, suggesting that child symptom severity and caregiver strain affect each other over time. These results suggest that attending to both child and caregiver factors may be important in maintaining improvements after initiating usual care.
Imputation Method Adjusted for Covariates for Nonrespondents in Instruments with Applications

In clinical research, measurement instruments (or questionnaires) consisting of a number of items (questions) are often used to assess treatment effect, e.g., quality-of-life assessment, and clinical disease activity index. In many situations, instead of an individual component, it is of interest to provide an assessment of the treatment effect in some overall measures, e.g., subscale or total score. In practice, these types of data often suffer from incompleteness. A common method is to simply ignore all the item nonrespondents from the analysis. Although this method is statistically valid under the assumption of missing completely at random (MCAR), it suffers from decreasing power/efficiency. In this paper, we propose a regression imputation approach adjusted for covariates with item nonrespondents in the instrument. The proposed method provides consistent estimators, which are asymptotically normal. A bootstrap procedure is also proposed to estimate the asymptotic variance of the derived estimators. A simulation study was conducted to study the finite samples performance of the derived estimators. It is also shown that the estimators based on the imputed data set are more efficient than the estimators based on the completers only. The proposed methodology was illustrated through two applications in observational studies.
Identifying Influencing Factors of Audit Risk Model: A Combined Fuzzy ANP-DEMATEL Approach

In the professional circles, factors affecting audit risk are treated independently; however, a more objective approach in assessing detection risk should be involved the relationships among the audit risk factors. This study introduces a framework based on a fuzzy multi-criteria decision support to identify the influencing factors may affect the audit risk model considering the interdependencies among them. We first takes advantages of a fuzzy screening method to screen forty more practical factors may affect the audit risk model out of 58 potential ones. Then, we applied a combined approach of Analytic Network Process (ANP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) to weight the factors and prioritize them considering their inner and outer dependencies complemented with a case study of Iran. To be more compatible with ambiguities related to human beings and make more useful decisions in the real world, the fuzzy set theory is used. The combined approach used in this study providing correct, precise weight for each factor can explore a more rigorous framework for decision-making in risk assessment by integrating interdependent relationships within and among audit risk factors.
Creating and Managing "Lookmarks" in ParaView

This paper describes the integration of lookmarks into the ParaView visualization tool. Lookmarks are pointers to views of specific parts of a dataset. They were so named because lookmarks are to a visualization tool and dataset as bookmarks are to a browser and the World Wide Web. A lookmark can be saved and organized among other lookmarks within the context of ParaView. Then at a later time, either in the same ParaView session or in a different one, it can be regenerated, displaying the exact view of the data that had previously been saved. This allows the user to pick up where they left off, to continue to adjust the view or otherwise manipulate the data. Lookmarks facilitate collaboration between users who wish to share views of a dataset. They enable more effective data comparison because they can be applied to other datasets. They also serve as a way of organizing a user’s data. Ultimately, a lookmark is a time-saving tool that automates the recreation of a complex view of the data.
On simultaneous perturbation particle swarm optimization

In this paper, we describes the simultaneous perturbation particle swarm optimization which is a combination of the particle swarm optimization and the simultaneous perturbation optimization method. The method has global search capability of the particle swarm optimization and local search one of gradient method by the simultaneous perturbation. Some variations of the method are described. Comparison between these methods and the ordinary particle swarm optimization are shown through five test functions and learning problem of neural networks.
MediaCloud a Framework for Real-time Media Processing in the Network

Predicted growth of media traffic (even conservative forecasts predict an increase of 40% year over year) can only give a hint of how important video will be for future entertainment, business, and government services. But such future multimedia services will be different from what video means to all of us today. More and more people will not only consume, but will also actively produce content. These services will be used by mobile users, and personalization of content will be the common case. Service introduction, enhancements, and adoption of services will be much more dynamic than today, calling for flexible Software as a Service business and operational models.
Short- and long-term effects of early fosinopril administration in patients with acute anterior myocardial infarction undergoing intravenous thrombolysis: results from the Fosinopril in Acute Myocardial Infarction Study. FAMIS Working Party.

BACKGROUND Angiotensin-converting enzyme inhibitors are used in patients who have myocardial infarction with left ventricular (LV) dysfunction. Few data are available in patients whose LV function is within the normal range. METHODS AND RESULTS The Fosinopril in Acute Myocardial Infarction Study was a 2-year, randomized, double-blind, placebo-controlled, multicenter study of 285 patients with anterior acute myocardial infarction and was designed to investigate the effects of the early (<9 hours) administration of fosinopril and thrombolysis on (1) changes in echocardiographically evaluated LV volumes at 3 months and (2) long-term occurrence of death and congestive heart failure. LV volumes were normal at baseline in more than 70% of patients and were comparable between groups both at baseline and after 3 months of treatment. Fosinopril-treated patients showed a 30% reduction in the 2-year combined prevalence of death or moderate-to-severe congestive heart failure (New York Heart Association class III-IV) despite having a worse clinical profile at baseline. The benefit of fosinopril was confirmed both in patients without congestive heart failure at admission and in those with ejection fraction >40% at baseline. Moreover, the incidence of significant ventricular arrhythmias was lower in the fosinopril group (0.8% vs 6.0%, p < 0.02). CONCLUSIONS The results of the Fosinopril in Acute Myocardial Infarction Study suggest that early treatment with fosinopril can benefit patients with acute myocardial infarction in addition to a prevention of LV remodeling.
Multiphysics approach to numerical modelling and analysis of permanent-magnet tubular linear motors

The paper presents a multiphysics modelling through finite-element (FE) numerical field analysis for coupling electromagnetic and thermal phenomena in a permanent-magnet tubular linear motor (PMTLM). 2-D axial-symmetry FE steady-state and transient solutions are first obtained for the magnetic flux density distribution, cogging force, thrust and losses of the prototype PMTLM. The FE magnetic field results are then coupled to the 3-D FE thermal simulation in order to get the PMTLM temperature distribution. The paper proves that the multiphysics numerical analysis is a viable tool for the design and performance optimization of PMTLMs.
Pre-RAKE diversity combining for UWB systems in IEEE 802.15 UWB multipath channel

Since ultra wideband impulse radio (UWB-IR) systems can resolve many paths and are thus rich in multipath diversity, the use of the RAKE diversity combining is very effective. In the RAKE diversity combining, the bit error rate (BER) is improved with the increase of the number of fingers. The Pre-RAKE diversity combining is known as another technique to achieve the performance equivalent to the RAKE diversity combining without increasing the receiver complexity. In the Pre-RAKE diversity combining, the transmitted signals are scaled and delayed according to the delay and strength of the multipath. In this paper, we propose Pre-RAKE diversity combining techniques for UWB systems, the All-Pre-RAKE (A-Pre-RAKE) diversity combining using perfect channel information, the Selective-Pre-RAKE (S-Pre-RAKE) diversity combining using the information on the L strongest paths, and the Partial-Pre-RAKE (P-Pre-RAKE) diversity combining using the information on the first L paths. From the results of our computer simulation for UWB-IR systems in IEEE 802.15 UWB multipath channel model, we show that the proposed Pre-RAKE diversity combining techniques are effective for the UWB-IR systems to achieve good error rate performance, while keeping the complexity of the receiver low. We also show that the S-Pre-RAKE diversity combining is effective in achieving good error rate performance with less channel information.
The role of intracellular redox imbalance in nanomaterial induced cellular damage and genotoxicity: A review

The terms oxidative stress, free radical generation, and intracellular antioxidant protection have become part of everyday nanotoxicology terminology. In recent years, an ever increasing number of in vitro and in vivo studies have implicated disruptions to the redox balance and oxidative stress as one of the main contributors to nanomaterial (NM) induced adverse effects. One of the most important and widely investigated of these effects is genotoxicity. In general, systems that defend an organism against oxidative damage to DNA are very complex and include prevention of reactive oxygen species (ROS) production, neutralizing ROS (scavengers), enzymatic nucleotide pool sanitation, and DNA repair. This review discusses the importance of the maintenance of the redox balance in this context before examining studies that have investigated engineered NM induced redox imbalance and genotoxicity. Furthermore, we identify data gaps, and highlight a number of issues that exist with the methodologies that are routinely utilized to investigate intracellular ROS production or anti‐oxidant depletion. We conclude that for a large number of engineered NM types changes in the redox balance toward oxidative stress are normally associated with DNA damage. Environ. Mol. Mutagen. 56:111–124, 2015. © 2014 Wiley Periodicals, Inc.
Relationship between Small Airway Function and Health Status, Dyspnea and Disease Control in Asthma

Background: Small airways play important roles in the pathophysiology of asthma. However, relationships between small airway involvement and health status and dyspnea have not been investigated. Objectives: It was the aim of this study to assess the relationships between proximal and peripheral airway functions and health status, dyspnea and disease control in patients with asthma, using impulse oscillometry (IOS). Methods: We performed IOS, spirometry and assessment of health status (Asthma Quality of Life Questionnaire and St. George’s Respiratory Questionnaire), dyspnea (Baseline Dyspnea Index) and disease control (Asthma Control Questionnaire) in 65 asthmatics and evaluated their relationships. Results: Peripheral airway function as evaluated by IOS [R5–R20 (the fall in resistance from 5 to 20 Hz) and X5 (reactance at 5 Hz)], in addition to the proximal airway index (R20), significantly correlated with health status, dyspnea and disease control. Multiple regression analyses revealed that peripheral airway function significantly contributes to these, independently of the proximal airway index. In contrast, forced expiratory volume in 1 s did not significantly contribute to health status or dyspnea. Conclusions: IOS correlated better with clinical symptoms and asthma control than spirometry in patients with asthma. Peripheral and proximal airway functions as assessed separately by IOS independently contribute to health status, dyspnea and disease control, indicating that peripheral airways also represent an important therapeutic target.
Bayesian Methods for Highly Correlated Exposure Data

Studies that include individuals with multiple highly correlated exposures are common in epidemiology. Because standard maximum likelihood techniques often fail to converge in such instances, hierarchical regression methods have seen increasing use. Bayesian hierarchical regression places prior distributions on exposure-specific regression coefficients to stabilize estimation and incorporate prior knowledge, if available. A common parametric approach in epidemiology is to treat the prior mean and variance as fixed constants. An alternative parametric approach is to place distributions on the prior mean and variance to allow the data to help inform their values. As a more flexible semiparametric option, one can place an unknown distribution on the coefficients that simultaneously clusters exposures into groups using a Dirichlet process prior. We also present a semiparametric model with a variable-selection prior to allow clustering of coefficients at 0. We compare these 4 hierarchical regression methods and demonstrate their application in an example estimating the association of herbicides with retinal degeneration among wives of pesticide applicators.
Does Film Smoking Promote Youth Smoking in Middle-Income Countries?: A Longitudinal Study among Mexican Adolescents

Objective: To determine whether exposure to smoking imagery in films predicts smoking onset among never-smoking Mexican adolescents. Methods: The analytic sample was comprised of 11- to 14-year-old secondary school students who reported never having tried smoking at baseline, 83% (1,741/2,093) of whom were successfully followed-up after 1 year. Exposure to 42 popular films that contained smoking was assessed at baseline, whereas smoking behavior and risk factors were assessed at baseline and at follow-up. Logistic regression was used to estimate bivariate and adjusted relative risks (ARR) of trying smoking and current smoking at follow-up. Results: At follow-up, 36% reported having tried smoking and 8% reported having smoked in the previous month. Students who were successfully followed-up were exposed to an average of 43.8 minutes of smoking in the films they reported viewing at baseline. ARRs indicated that students in the two highest levels of exposure to film smoking were more than twice as likely to have smoked in the previous 30 days at follow-up [ARR3v1 = 2.44; 95% confidence interval (CI), 1.31-4.55; ARR4v1 = 2.23; 95% CI, 1.19-4.17]. The ARR of having tried smoking by the time of follow-up reached statistical significance only when comparing the third highest to the lowest exposure group (ARR3v1 = 1.54; 95% CI, 1.01-2.64). Having a parent or best friend who smoked at baseline were the only other variables that independently predicted both outcomes. Conclusions: Exposure to movie smoking is a risk factor for smoking onset among Mexican youth, although this risk appears weaker than in countries with stronger tobacco marketing regulations. (Cancer Epidemiol Biomarkers Prev 2009;18(12):3444–50)
Whole-exome sequencing to analyze population structure, parental inbreeding, and familial linkage

Significance We compared the information provided by whole-exome sequencing (WES) and genome-wide single-nucleotide variant arrays in terms of principal component analysis, homozygosity rate estimation, and linkage analysis using 110 subjects originating from different regions of the world. WES provided an accurate prediction of population substructure using high-quality variants with a minor allele frequency > 2% and reliable estimation of homozygosity rates using runs of homozygosity. Finally, homozygosity mapping in 15 consanguineous families showed that WES led to powerful linkage analyses, particularly in coding regions. Overall, our study shows that WES could be used for several analyses that are very helpful to optimize the search for disease-causing exome variants. Principal component analysis (PCA), homozygosity rate estimations, and linkage studies in humans are classically conducted through genome-wide single-nucleotide variant arrays (GWSA). We compared whole-exome sequencing (WES) and GWSA for this purpose. We analyzed 110 subjects originating from different regions of the world, including North Africa and the Middle East, which are poorly covered by public databases and have high consanguinity rates. We tested and applied a number of quality control (QC) filters. Compared with GWSA, we found that WES provided an accurate prediction of population substructure using variants with a minor allele frequency > 2% (correlation = 0.89 with the PCA coordinates obtained by GWSA). WES also yielded highly reliable estimates of homozygosity rates using runs of homozygosity with a 1,000-kb window (correlation = 0.94 with the estimates provided by GWSA). Finally, homozygosity mapping analyses in 15 families including a single offspring with high homozygosity rates showed that WES provided 51% less genome-wide linkage information than GWSA overall but 97% more information for the coding regions. At the genome-wide scale, 76.3% of linked regions were found by both GWSA and WES, 17.7% were found by GWSA only, and 6.0% were found by WES only. For coding regions, the corresponding percentages were 83.5%, 7.4%, and 9.1%, respectively. With appropriate QC filters, WES can be used for PCA and adjustment for population substructure, estimating homozygosity rates in individuals, and powerful linkage analyses, particularly in coding regions.
Attribute-aware data aggregation using dynamic routing in wireless sensor networks

Data aggregation has been widely recognized as an efficient method to reduce energy consumption in wireless sensor networks, which can support a wide range of applications such as monitoring temperature, humidity, level, speed etc. The data sampled by the same kind of sensors have much redundancy since the sensor nodes are usually quite dense in wireless sensor networks. To make data aggregation more efficient, the packets with the same attribute, defined as the identifier of different data sampled by different sensors such as temperature sensors, humidity sensors, etc., should be gathered together. However, to the best of our knowledge, present data aggregation mechanisms did not take packet attribute into consideration. In this paper, we take the lead in introducing packet attribute into data aggregation and propose an Attribute-aware Data Aggregation mechanism using Dynamic Routing (ADADR) which can make packets with the same attribute convergent as much as possible and therefore improve the efficiency of data aggregation. This goal cannot be achieved by present static routing schemes employed in most of data aggregation mechanisms since they construct routes before transmitting the sampled data and thus can not dynamically forward packets in response to the variation of packets at intermediate nodes. Hence, we present a potential-based dynamic routing scheme which employs the concept of potential in physics and pheromone in ant colony to achieve our goal. The results of simulations in series of scenarios show that ADADR indeed conserve energy by reducing the average number of transmissions each packet needs to reach the sink and is scalable with regard to the network size.
On the Use of Growth Curve in Loss Reserving

This paper propose some modification of the method of prediction of incurred but not reported (IBNR) claim reserves in non-life insurance based on the growth curve modelling. Literature put forwards a wide variety of methods to predict the IBNR claim reserves, mostly using the chain-ladder technique. The method discussed herein is based on two-stage estimation of the expected amount of losses to emerge: the estimation of the ultimate loss by year and the estimation of the pattern of the loss emergence. In this procedure, a non-linear model of the growth curve is applied in which two restricting assumptions are made. Firstly, it is assumed that incremental losses follow an over-dispersed Poisson (ODP) distribution. Secondly, as the pattern of the loss to emerge, two-parametric log-logistic and Weibull growth curves are assumed. A different non-linear model is proposed in this paper to predict the IBNR claim reserves. In it, the threeparametric Gompertz growth curve is adopted. In order to estimate the model parameters, the non-linear (weighted) least squares (NLS) method is applied, in which incremental losses follow the normal distribution. Moreover, a non-parametric approach to the growth curve modelling based on spline fitting is proposed as an alternative. All calculations are carried out in R party using the package {ChainLadder}.