Miracle-dz/UniFAR-FTUs huggingface dataset:
Memory Polynomial Based Adaptive Digital Predistorter

Digital predistortion (DPD) is a baseband signal processing technique that corrects for impairments in RF power amplifiers (PAs). These impairments cause out-of-band emissions or spectral regrowth and in-band distortion, which correlate with an increased bit error rate (BER). Wideband signals with a high peak-to-average ratio, are more susceptible to these unwanted effects. So to reduce these impairments, this paper proposes the modeling of the digital predistortion for the power amplifier using GSA algorithm.
FACTORS ASSOCIATED WITH THE INCREASED INCIDENCE AND SPREAD OF INFECTIOUS DISEASES

The bubonic plague that swept across Europe during the Middle Ages, the smallpox that was carried to the Americas by the Spanish, and the influenza outbreak of 1918 all bear testimony to the historic relevance of infectious pathogens and their ability to cause widespread death and suffering. In many ways, however, the nature and magnitude of the threat posed by infectious pathogens are greater today than they have ever been in the past, developments in modern science notwithstanding. Emerging and reemerging infections present daily challenges to existing medical capabilities. Not only have deadly and previously unimagined illnesses, such as AIDS, Ebola, Creutzfeldt-Jakob disease, and Legionnaires’ disease, emerged in recent years, but established diseases that just a few decades ago were thought to have been tamed are also returning, many in virulent, drug-resistant varieties.1 Modern manifestations of TB, for instance, bear little resemblance to the 19th-century strains that haunted Europe. TB treatment now requires a daily drug regimen that often requires health workers to personally monitor patients to ensure that they are complying with necessary procedures.2
A robust fuzzy logic controller for robot manipulators with uncertainties

Owing to load variation and unmodeled dynamics, a robot manipulator can be classified as a nonlinear dynamic system with structured and unstructured uncertainties. In this paper, the stability and robustness of a class of the fuzzy logic control (FLC) is investigated and a robust FLC is proposed for a robot manipulator with uncertainties. In order to show the performance of the proposed control algorithm, computer simulations are carried out on a simple two-link robot manipulator.
Building of an Architecture for the Fish Disease Diagnosis Expert System Based on Multi-agent

The paper presents the architecture of the MAS-based distributed fish disease diagnosis expert system on the basis of the analysis and summary on the characteristics of the existing distributed fish disease diagnosis expert system. That gives full play to the MAS-based distributed computing and to build flexibly. For heterogeneous knowledge sources of the distributed expert system, use the distributed computing agent to achieve the distributed diagnosis and management of fish diseases, and reduce the burden of the centralized processing. Meanwhile, it uses the modified contract net model, and designs a task allocation model of the collaborative diagnosis based on MAS for the distributed fish diseases, which describes the task allocation process concretely. Experiments proved that the system not only overcomes the limitations of single expert in the field, can also be cross-regional collaborative diagnosis. It improves the efficiency of the distribution of tasks and increases the accuracy of the results of fish disease diagnosis.
On the performance of square arranged antenna array with SC and MRC receiver over Nakagami fading channel

In this paper, we investigate the performance of using a square array of four antennas for selection combining (SC), maximal-ratio combining (MRC) of Nakagami correlated signals. The closed form of average output signal-to-noise ratio (SNR) and bit error rate (BER) with SC for arbitrary 4 correlated branches will be derived and the expression of BER with MRC is also derived by utilizing the method of characteristic function (CF). Two models for angle of arrival (AOA), e.g. uniform and Gaussian, will be considered, as well as the comparison between their system performances. The effect of correlation coefficients and fading factor on the system performance are discussed by numerical results, which show that the uniform distributed AOA system outperforms the Gaussian distributed AOA system with small angular spread.
Driver distraction and the role of cognitive and visual abilities for Road Safety Practices

Driver distraction represents a significant problem in a motor vehicle is a complex activity. This study exist for evaluated part of the Multifactorial Model of distraction, Driving Safety to elucidate the relative importance of cognitive function and measures of visual function in the capacity to Drive Safely. This article investigates the nature of driver distraction at a major Algerian a motor vehicle. At present, increasing amounts of visual information from sources such as roadside advertising create visual clutter in the road environment, including the sources of distraction present, and their effects on driver performance, cognitive and visual function (CV) capacity supports goal-directedness which minimizes the influence of distracting stimuli in favor of driving-relevant stimuli. Cognitive and visual function (CV) capacity can be discriminated and are both addressed during driving. This study investigated for driving experience (n= 300, age= 18-25), These included an adaptation of the well validated Useful Field of View (UFOV) and two newer measures, namely a Hazard Perception Test (HPT), and a Hazard Change Detection Task (HCDT).
ADAPTATION OF NEURAL NETS FOR RESOURCE DISCOVERY PROBLEM IN DYNAMIC AND DISTRIBUTED P2P ENVIRONMENT

Peer-to-Peer networks are complex systems that have widely s pread recently and thus providing efficient management to them is necessary and at the same time challenging task. The aims of this work are: discovering of deci sion mechanism of NeuroSearch algorithm developed in the Agora Center, testing NeuroSear ch under dynamic conditions and finding good solution for optimization problem. These thr e goals are lying on the middle part of the path to solving the main problem : developing new approach to train the core mechanism of NeuroSearch, which is base d on the MLP, under dynamic conditions and in supervised manner.
Comorbid Obsessive-Compulsive Symptoms in Schizophrenia: Insight into Pathomechanisms Facilitates Treatment

Insight into the biological pathomechanism of a clinical syndrome facilitates the development of effective interventions. This paper applies this perspective to the important clinical problem of obsessive-compulsive symptoms (OCS) occurring during the lifetime diagnosis of schizophrenia. Up to 25% of schizophrenia patients suffer from OCS and about 12% fulfil the diagnostic criteria of obsessive-compulsive disorder (OCD). This is accompanied by marked subjective burden of disease, high levels of anxiety, depression and suicidality, increased neurocognitive impairment, less favourable levels of social and vocational functioning, and greater service utilization. Comorbid patients can be assigned to heterogeneous subgroups. It is assumed that second generation antipsychotics (SGAs), most importantly clozapine, might aggravate or even induce second-onset OCS. Several epidemiological and pharmacological arguments support this assumption. Specific genetic risk factors seem to dispose patients with schizophrenia to develop OCS and risk-conferring polymorphisms has been defined in SLC1A1, BDNF, DLGAP3, and GRIN2B and in interactions between these individual genes. Further research is needed with detailed characterization of large samples. In particular interactions between genetic risk constellations, pharmacological and psychosocial factors should be analysed. Results will further define homogeneous subgroups, which are in need for differential causative interventions. In clinical practise, schizophrenia patients should be carefully monitored for OCS, starting with at-risk mental states of psychosis and longitudinal follow-ups, hopefully leading to the development of multimodal therapeutic interventions.
Inefficient or Just Different? Effects of Heterogeneity on Bank Efficiency Scores

In this paper, we show the importance of accounting for heterogeneity among sample firms in stochastic frontier analysis. For a fairly homogenous sample of German savings and cooperative banks, we analyze how alternative theoretical assumptions regarding the nature of heterogeneity can be modeled and the extent to which the respective empirical specifications affect estimated efficiency levels and rankings. We find that the level of efficiency scores is affected in the case of both cost and profitmodels. On the cost side especially, level and rank correlations show that different specifications identify different banks as being best or worst performers. Our main conclusion is that efficiency studies in general and bank efficiency studies in particular should account for heterogeneity across sample firms. Especially when efficiency measures are employed for policy purposes, a careful choice of models and transparency regarding maximization methods are essential to be able to make inferences about managerial behavior.
Analysis of SOA-based middleware service layers for polynary resources SoC

As manufacturing process technology enter into nano-phase, integrate billions of transistors on a single chip has become a reality. By combining pre-designed and configurable SoCs as complementary and independent resources, a new concept of embedded HPC system named as PRSoC was proposed. HPC architectures, MPI parallel programming specification, IPC mechanism of multi-core / multiprocessor system, the application and protocol of network-area concepts, principles of SOA and web service management middleware were introduced to the SoC design area. Asymmetric one-way write-only chip serial bus architecture for the PRSoC model was presented. The middleware service layer of PRSoC based on SOA was analyzed thoroughly.
Do Strategies to Improve Quality of Maternal and Child Health Care in Lower and Middle Income Countries Lead to Improved Outcomes? A Review of the Evidence

Objectives Efforts to scale-up maternal and child health services in lower and middle income countries will fail if services delivered are not of good quality. Although there is evidence of strategies to increase the quality of health services, less is known about the way these strategies affect health system goals and outcomes. We conducted a systematic review of the literature to examine this relationship. Methods We undertook a search of MEDLINE, SCOPUS and CINAHL databases, limiting the results to studies including strategies specifically aimed at improving quality that also reported a measure of quality and at least one indicator related to health system outcomes. Variation in study methodologies prevented further quantitative analysis; instead we present a narrative review of the evidence. Findings Methodologically, the quality of evidence was poor, and dominated by studies of individual facilities. Studies relied heavily on service utilisation as a measure of strategy success, which did not always correspond to improved quality. The majority of studies targeted the competency of staff and adequacy of facilities. No strategies addressed distribution systems, public-private partnership or equity. Key themes identified were the conflict between perceptions of patients and clinical measures of quality and the need for holistic approaches to health system interventions. Conclusion Existing evidence linking quality improvement strategies to improved MNCH outcomes is extremely limited. Future research would benefit from the inclusion of more appropriate indicators and additional focus on non-facility determinants of health service quality such as health policy, supply distribution, community acceptability and equity of care.
Lower Body Stiffness and Muscle Activity Differences Between Female Dancers and Basketball Players During Drop Jumps

Background: Anterior cruciate ligament (ACL) injuries often occur during landing, with female athletes at higher injury risk than male athletes. Interestingly, female dancers have lower ACL injury rates than do female athletes in general. Hypothesis: Female dancers will have earlier and greater lower extremity muscle activity and higher sagittal knee joint and leg stiffness than will female basketball players. Study Design: Cross-sectional group comparison. Methods: Fifty-five healthy female athletes (35 dancers, 20 basketball players) performed 5 double-leg drop jumps from a 45-cm box. Surface electromyography (onsets and amplitudes; prelanding and postlanding) was recorded from the lateral gastrocnemius, medial and lateral hamstrings, lateral quadriceps muscles with a 3-dimensional electromagnetic tracking system, and forceplates recording biomechanics (leg spring stiffness and knee joint stiffness). Results: Compared with basketball players, dancers had greater leg spring stiffness (P = 0.047) but similar knee joint stiffness (P = 0.44). Although no significant differences were observed in overall muscle onset times (P = 0.22) or activation amplitudes (prelanding, P = 0.60; postlanding, P = 0.78), small to moderate effect sizes (ESs) suggest trends in dancers toward earlier (ES = 0.53) and higher medial hamstrings activation pre- (ES = 0.55) and post- (ES = 0.41) landing and lower lateral quadriceps (ES = 0.30) and higher gastrocnemius (ES = 0.33) postlanding muscle activation. Conclusions: In dancers, the higher leg spring stiffness and trends toward higher hamstrings prelanding and postlanding, as well as lower quadriceps and higher gastrocnemius activation postlanding with similar knee joint stiffness, indicate lower extremity neuromechanical differences across other joints. Clinical Relevance: Female dancers may have lower extremity neuromechanics that are different from those of basketball players during drop jumps. If dancers use ACL-protective strategies during activity, then their training routines should be further investigated to improve ACL injury prevention programs.
The conceptual structure of evolutionary biology: A framework from phenotypic plasticity

Abstract In this review, I approach the role of phenotypic plasticity as a key aspect of the conceptual framework of evolutionary biology. The concept of phenotypic plasticity is related to other relevant concepts of contemporary research in evolutionary biology, such as assimilation, genetic accommodation and canalization, evolutionary robustness, evolvability, evolutionary capacitance and niche construction. Although not always adaptive, phenotypic plasticity can promote the integration of these concepts to represent some of the dynamics of evolution, which can be visualized through the use of a conceptual map. Although the use of conceptual maps is common in areas of knowledge such as psychology and education, their application in evolutionary biology can lead to a better understanding of the processes and conceptual interactions of the complex dynamics of evolution. The conceptual map I present here includes environmental variability and variation, phenotypic plasticity and natural selection as key concepts in evolutionary biology. The evolution of phenotypic plasticity is important to ecology at all levels of organization, from morphological, physiological and behavioral adaptations that influence the distribution and abundance of populations to the structuring of assemblages and communities and the flow of energy through trophic levels. Consequently, phenotypic plasticity is important for maintaining ecological processes and interactions that influence the complexity of biological diversity. In addition, because it is a typical occurrence and manifests itself through environmental variation in conditions and resources, plasticity must be taken into account in the development of management and conservation strategies at local and global levels.
Brain-Computer Interface for high-level control of rehabilitation robotic systems

In this work, a brain-computer interface (BCI) based on steady-state visual evoked potentials (SSVEP) is presented as an input device for the human machine interface (HMI) of the semi-autonomous robot FRIEND II. The role of the BCI is to translate high-level requests from the user into control commands for the FRIEND II system. In the current application, the BCI is used to navigate a menu system and to select commands such as pouring a beverage into a glass. The low-level control of the test platform, the rehabilitation robot FRIEND II, is executed by the control architecture MASSiVE, which in turn is served by a planning instance, an environment model and a set of sensors (e.g., machine vision) and actors. The BCI is introduced as a step towards the goal of providing disabled users with at least 1.5 hours independence from care givers.
Robust tree-structured Named Entities Recognition from speech

Named Entity Recognition is a well-known Natural Language Processing (NLP) task, used as a preliminary processing to provide a semantic level to more complex tasks. Recently a new set of named entities has been defined; this set has a multilevel tree structure, where base entities are combined to define more complex ones. In this paper I describe an effective and original NER system robust to noisy speech inputs that ranked first at the 2012 ETAPE NER evaluation campaign with results far better than those of the other participating systems.
A Multiple Features Image Tracking Algorithm

In Mean Shift algorithm, the features of the tracked target and the image matching similarity criterion have great influence on the result of tracking. a new algorithm of target tracking is proposed. the algorithm combine local binary pattern and color information to form a new feature CL, which tracks target by using a method of centroid iteration based on maximum posterior probability. Thanks to the simplification of the LBP, the CL has higher differentiation ability and lower computational complexity. Experimental results show that the new algorithm have significantly improved the tracking performance, in comparison with original Mean Shift algorithm. in complex background, the algorithm can track the target robustly.
Real life emotions in French and English TV video clips: an integrated annotation protocol combining continuous and discrete approaches

A major barrier to the development of accurate and realistic models of human emotions is the absence of multi-cultural / multilingual databases of real-life behaviours and of a federative and reliable annotation protocol. QUB and LIMSI teams are working towards the definition of an integrated coding scheme combining their complementary approaches. This multilevel integrated scheme combines the dimensions that appear to be useful for the study of real-life emotions: verbal labels, abstract dimensions and contextual (appraisal based) annotations. This paper describes this integrated coding scheme, a protocol that was set-up for annotating French and English video clips of emotional interviews and the results (e.g. inter-coder agreement measures and subjective evaluation of the scheme).
Facial feature localization using graph matching with higher order statistical shape priors and global optimization

This paper presents a graphical model for de-formable face matching and landmark localization under an unknown non-rigid warp. The proposed model learns and combines statistics of both appearance and shape variations of facial images (learnt purely from a set of frontal training images) in a complex objective function in an unsupervised manner. Local and global shape variations are included in the objective function as binary and higher order clique potentials. The proposed approach exploits the sparseness of facial features to reduce the complexity of inference over the probabilistic model. Besides presenting a method for face feature localization, the paper proposes a framework for incorporation of statistical shape priors as higher order cliques into MRFs. The problem of optimizing the objective function is performed using the dual decomposition approach in which the higher order subproblems based on point distribution models are formulated as instances of convex quadratic programs. The evaluation of the approach for feature localization is performed both on the frontal and rotated images of the XM2VTS dataset images as well as images collected from Google. The method shows high robustness to partial occlusion, pose changes etc. The method is then applied as an initialization step for a more costly matching method and is shown to be instrumental in improving performance and reducing runtime.
Modulation of Respiratory TLR3-Anti-Viral Response by Probiotic Microorganisms: Lessons Learned from Lactobacillus rhamnosus CRL1505

Respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract illness in infants and young children. Host immune response is implicated in both protective and immunopathological mechanisms during RSV infection. Activation of Toll-like receptor (TLR)-3 in innate immune cells by RSV can induce airway inflammation, protective immune response, and pulmonary immunopathology. A clear understanding of RSV–host interaction is important for the development of novel and effective therapeutic strategies. Several studies have centered on whether probiotic microorganisms with the capacity to stimulate the immune system (immunobiotics) might sufficiently stimulate the common mucosal immune system to improve defenses in the respiratory tract. In this regard, it was demonstrated that some orally administered immunobiotics do have the ability to stimulate respiratory immunity and increase resistance to viral infections. Moreover, during the last decade scientists have significantly advanced in the knowledge of the cellular and molecular mechanisms involved in the protective effect of immunobiotics in the respiratory tract. This review examines the most recent advances dealing with the use of immunobiotic bacteria to improve resistance against viral respiratory infections. More specifically, the article discuss the mechanisms involved in the capacity of the immunobiotic strain Lactobacillus rhamnosus CRL1505 to modulate the TLR3-mediated immune response in the respiratory tract and to increase the resistance to RSV infection. In addition, we review the role of interferon (IFN)-γ and interleukin (IL)-10 in the immunoregulatory effect of the CRL1505 strain that has been successfully used for reducing incidence and morbidity of viral airways infections in children.
‘Gaining health and wellbeing from birth to three’: a web-based positive parenting programme for primary care settings

ABSTRACT Current models of pediatric care include parental support as part of health promotion in the early years. This study introduces the modality of e-health by describing the universal ‘Gaining Health and Wellbeing from Birth to Three’ programme, reporting on the level of programme satisfaction among 249 parents and 350 professionals. The average level of satisfaction was very high for both groups. The professionals showed significantly higher rates than the parents in the ‘Activity’ factor, but there were no significant differences with regard to the ‘Programme experience’ and ‘Parenting impact’ factors. Parents living in single-parent families were more satisfied, whereas professionals who were more heavily engaged with the Internet were less satisfied with the parenting impact of the programme. In sum, this study has demonstrated that a cost-efficient (brief and fully automated) structured programme was able to reach a large population of participants and satisfy their expectations about the programme.