Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy-Efficient Wireless Sensor Networks: A Novel Dynamic Clustered and Cross-Layer Cooperation Approach

In Wireless sensor networks (WSNs), energy efficiency is a foremost challenge. This paper studies energy-efficiency from cross-layer design in clustered WSNs. We propose a dynamic clustering method that combines TDMA-based real clustering and CSMA-based virtual clustering. It achieves the whole network synchronization in a reasonable scale. This clustering mechanism is adopted in a cross-layer cooperation framework as Dynamic Clustered and Cross-layer Cooperation (DCCC), which aims to make wise decision on cooperative node selection, cooperative cluster selection, and node action to promote energy-efficiency. Through performance analysis, we propose optimization strategies for DCCC theoretically. As a highlight, our thesis integrates dynamic clustering, cross-layer, and cooperation communication, which yield to three levels of cooperation in clustered architecture, and promote cooperation efficiency to the full. Simulation results show our scheme can promote system performance while maintaining reasonable energy efficiency.
Ultrasound diagnosis of polycystic ovarian syndrome: current guidelines, criticism and possible update

The US diagnosis of PCOS is still an open problem. The frequency of over diagnosis in particular phase of reproductive age, the contrasting guidelines and the technological advances lead to be a difficult charge for the sonographer. Follicle number and disposition and ovarian volume represents most used criteria, but other aspects as stromal study and ovarian vascularization could help. On the other hand, recently, the introduction of Anti-mullerian hormone assay introduced a support for US diagnosis.
The availability of noun properties during the interpretation of novel noun phrases

The current experiments examine whether recent exposure to a modifier-noun phrase (e.g., unripe peaches) affects the representation of the head noun (e.g, peach). Experiment 1 demonstrates that a property true of the head noun (e.g, sweet) takes longer to verify when preceded by a phrase for which this property is not true (e.g., unripe peaches) than by a phrase for which the property remains true (e.g., orchard peaches). Experiment 2 replicates this finding and, in addition, demonstrates that properties that remain true of both prime phrases (e.g., fuzzy) are equally available during the processing of the head noun. These findings suggest that interpreting a modifier-noun phrase affects the head noun’s representation such that properties that are incompatible with the entire phrase temporarily become less available during subsequent processing of the head noun than do properties that remain compatible with the phrase.
The effect of Dimethyl Sulfoxide on hepatogenic differentiation of Mesenchymal Stem Cells

Background Adipose tissue mesenchymal stem cells (AT-MSCs) are suitable choices in treatment of liver associated diseases. Dimethyl Sulfoxide (DMSO) is an amphipathic molecule with potential of delivering both lipophilic and hydrophilic agents into cells. Few protocols used DMSO for induction of AT-MSCs towards hepatocyte like cells but the effect of DMSO on hepatogenic differentiation were not surveyed, previously. In the present study, we aimed at evaluation of the effect of DMSO in differentiation of AT-MSCs into hepatic lineage. Methods: We isolated MSCs from adipose tissue then multi-potency and surface markers of AT-MSCs was evaluated. Isolated AT-MSCs randomly dispensed in four groups including group 1: HGF treated, 2: HGF+DMSO treated, 3: HGF+ DMSO+ OMS treated, and group control for a period of 3 weeks in the expansion medium without serum, EGF and bFGF was also included in the first stage of inductions. The morphologic changes during induction period was observed with microscopy. The protein levels of albumin and a-fetoprotein (AFP) of the differentiating MSCs was investigated by ELISA and urea production was evaluated by colorimetric assay. The qRT-PCR was performed for quantitation of hepatocyte marker genes including a-fetoprotein (AFP), CK18, HNF4a, and HNF6. The glycogen storage of differentiated cells was visualized by periodic-acid Schiff‘s staining. Results: The results demonstrate that DMSO speeds up hepatic differentiation of AT-MSCs characterized by rapid changes in morphology, higher expression of hepatic marker gene (AFP) in both mRNA and protein level (P<0.05), also, increased transcriptional levels of other hepatic genes including CK18, HNF4a, and HNF6 (P<0.01) moreover, greater percentage of glycogen storage( p< 0.05) in DMSO treated groups. Conclusion: DMSO catalyzes hepatic differentiation, therefore using DMSO for acceleration of the hepatogenic protocols of AT-MSCs appears advantageous. Keywords: Adipose Tissue, Mesenchymal Stem Cells, Hepatic differentiation.
Software Configuration Engineering in Practice Interviews, Survey, and Systematic Literature Review

Modern software applications are adapted to different situations (e.g., memory limits, enabling/disabling features, database credentials) by changing the values of configuration options, without any source code modifications. According to several studies, this flexibility is expensive as configuration failures represent one of the most common types of software failures. They are also hard to debug and resolve as they require a lot of effort to detect which options are misconfigured among a large number of configuration options and values, while comprehension of the code also is hampered by sprinkling conditional checks of the values of configuration options. Although researchers have proposed various approaches to help debug or prevent configuration failures, especially from the end users’ perspective, this paper takes a step back to understand the process required by practitioners to engineer the run-time configuration options in their source code, the challenges they experience as well as best practices that they have or could adopt. By interviewing 14 software engineering experts, followed by a large survey on 229 Java software engineers, we identified 9 major activities related to configuration engineering, 22 challenges faced by developers, and 24 expert recommendations to improve software configuration quality. We complemented this study by a systematic literature review to enrich the experts’ recommendations, and to identify possible solutions discussed and evaluated by the research community for the developers’ problems and challenges. We find that developers face a variety of challenges for all nine configuration engineering activities, starting from the creation of options, which generally is not planned beforehand and increases the complexity of a software system, to the non-trivial comprehension and debugging of configurations, and ending with the risky maintenance of configuration options, since developers avoid touching and changing configuration options in a mature system. We also find that researchers thus far focus primarily on testing and debugging configuration failures, leaving a large range of opportunities for future work.
The Need Fora Standardized Set of Usability Metrics

A critical problem for the advancement of our discipline is the lack of consensus about metrics for measuring the dimensions of usability. What matters to users and to those who want users to adopt a system or product is usability from the users' perspective, and what should matter to designers and researchers is the question of what influences that perspective. Solving this problem would add structure to research on user interface methodologies and new design techniques. It would allow the research to be integrated more effectively. It would provide a way for industry to assess when the benefits of applying the results from the lab are justified by the cost, and it would support the creation of more useful guidance for the practitioner on when to apply new methodologies and techniques.
Mortality attributable to cigarette smoking in the United States

Cigarette smoking is an especially pernicious behavior because of its high prevalence and mortality risk. We use the powerful methodology of life tables with covariates and employ the National Health Interview Survey-Multiple Cause of Death file to illuminate the interrelationships of smoking with other risk factors and the combined influences of smoking prevalence and population size on mortality attributable to smoking. We find that the relationship between smoking and mortality is only modestly affected by controlling for other risk factors. Excess deaths attributable to smoking among adults in the United States in the year 2000 were as high as 340,000. Better knowledge of the prevalence and mortality risk associated with different cigarette smoking statuses can enhance the future health and longevity prospects of the population. Copyright 2005 The Population Council, Inc.
El Portfolio como estrategia de evaluación compartida de la comprensión lectora

El Portfolio, como estrategia de evaluacion compartida de la comprension lectora en el aula de Educacion Primaria, motiva al alumno a seleccionar y justificar aquellos trabajos que muestran su esfuerzo y logro en tareas de comprension, antes, durante o despues de la lectura. Se trata de un instrumento de diagnostico que puede ser usado por los estudiantes para reflexionar sobre como construyen significado fortaleciendo de ese modo su desarrollo metacognitivo como lectores. El presente trabajo es una contribucion al proceso de implantacion en nuestro Instituto del Portfolio Europeo de las Lenguas (PEL), durante el curso 2006/2007, y tiene como objetivos: 1) identificar los fundamentos teoricos que sustentan el uso del Portfolio en el ambito del desarrollo de la comprension lectora; 2) concebir el Portfolio como un instrumento de cambio en los procesos de evaluacion tradicional, que asumen que evaluar exige casi con exclusividad que el estudiante se limite a memorizar y “re-citar” fragmentos de un texto cualquiera y 3) aportar orientaciones practicas sobre como trabajar con este instrumento de desarrollo de la capacidad lectora. La escasa o nula aplicacion de esta estrategia de autoevaluacion en la Etapa de Primaria sugiere la necesidad de difundir y promover el uso de este instrumento que suscita en los estudiantes, la responsabilidad y el control sobre su propio proceso de construccion de significado lector.
A Fast File System for UNIX (Revised July 27, 1983)

A reimplementation of the UNIX file system is described. The reimplementation provides substantially higher throughput rates by using more flexible allocation policies, that allow better locality of reference and that can be adapted to a wide range of peripheral and processor characteristics. The new file system clusters data that is sequentially accessed and provides two block sizes to allow fast access for large files while not wasting large amounts of space for small files. File access rates of up to ten times faster than the traditional UNIX file system are experienced. Long needed enhancements to the user interface are discussed. These include a mechanism to lock files, extensions of the name space across file systems, the ability to use arbitrary length file names, and provisions for efficient administrative control of resource usage.
A new QRS detection algorithm based on the Hilbert transform

A robust new algorithm for QRS defection using the properties of the Hilbert transform is proposed. The method allows R waves to be differentiated from large, peaked T and P waves with a high degree of accuracy and minimizes the problems associated with baseline drift, motion artifacts and muscular noise. The performance of the algorithm was tested using the records of the MIT-BIH Arrhythmia Database. Beat by beat comparison was performed according to the recommendation of the American National Standard for ambulatory ECG analyzers (ANSI/AAMI EC38-1998). A QRS detection rate of 99.64%, a sensitivity of 99.81% and a positive prediction of 99.83% was achieved against the MIT-BIH Arrhythmia database. The noise tolerance of the new proposed QRS detector was also tested using standard records from the MIT-BIH Noise Stress Test Database. The sensitivity of the detector remains about 94% even for signal-to-noise ratios (SNR) as low as 6 dB.
Ronda clínica y epidemiológica: club de revistas

En esta edicion de la ronda clinica y epidemiologica analizamos los resultados del estudio SPRINT, que plantea un control mas intensivo de la presion arterial para la prevencion de los eventos cardiovasculares. Tambien exponemos los resultados del estudio REVERT, en el que se uso una modificacion de la maniobra de Valsalva para tratar pacientes con taquicardias supraventriculares estables. Kane y colaboradores exploran la mejoria de la calidad de vida de pacientes con su primer episodio psicotico, tras recibir un enfoque multidisciplinario en comparacion con el tratamiento comunitario habitual. Por ultimo, Toledo y colaboradores estudian la incidencia del cancer de mama en el estudio PREDIMED luego de seguir un regimen alimentario basado en la dieta mediterranea.
Looking into nostalgia and the Boca Doce brand in online communications: a netnographic exploration of a Portuguese instant dessert.

As in many other geographies, in the Portuguese context, especially in academic literature, qualitative methods in marketing research are clearly under-represented when compared with quantitative methods. This happens all the more as qualitative methods are used in isolation over mixed-methods approaches. It follows that in the Portuguese context, netnography, the ethnographic/qualitative study of social networks conceptualized and developed by Robert Kozinets (e.g. Kozinets, 2002, 2009, 2015) remains largely unused. The following research is a first attempt at bringing netnography to the Portuguese context by studying online communication around one of its most popular dessert brands, Boca Doce, an instant dessert produced by Kraft foods and distributed in Portugal by the AMD company. Netnography is herewith used as a qualitative method in isolation while the structure of the study follows other netnographic research examples, such as the study of Listerine (Kozinets, 2010). Results points to two major themes in online communication around the brand: emotions and feelings about Boca Doce (generally coupled with feelings of nostalgia) versus-consumer driven innovations. Some final considerations are given to possibilities of brand innovation that can unfold when cultural and netnographic views are brought into play.
Face and kinship image based on combination descriptors-DIEDA for large scale features

In this paper, we introduce an efficient linear similarity learning system for face verification. Humans can easily recognize each other by their faces and since the features of the face are unobtrusive to the condition of illumination and varying expression, the face remains as an access of active recognition technique to the human. The verification refers to the task of teaching a machine to recognize a pair of match and non-match faces (kin or No-kin) based on features extracted from facial images and to determine the degree of this similarity. There are real problems when the discriminative features are used in traditional kernel verification systems, such as concentration on the local information zones, containing enough noise in non-facing and redundant information in zones overlapping in certain blocks, manual adjustment of parameters and dimensions high vectors. To solve the above problems, a new method of robust face verification with combining with a large scales local features based on Discriminative-Information based on Exponential Discriminant Analysis (DIEDA). The projected histograms for each zone are scored using the discriminative metric learning. Finally, the different region scores corresponding to different descriptors at various scales are fused using Support Vector Machine (SVM) classifier. Compared with other relevant state-of-the-art work, this system improves the efficiency of learning while controlling the effectiveness. The experimental results proved that both of these two initializations are efficient and outperform performance of the other state-of-the-art techniques.
Vehicle Type Classification Using Convolutional Neural Network

Automation of vehicles' classification and recognition is one of the most important challenges in contemporary road safety and intelligent transportation system. The development of image processing, pattern recognition and deep learning technologies has overcome many obstacles to achieve this aim. In this paper, we present a vehicle type classification system based on deep learning technology. This system is constituted of two steps. In the first step, we apply data augmentation to attenuate the imbalanced dataset problem. In the second step, we build a convolutional neural network (CNN) model with different architectures using parameters that are learned from the training dataset. This system is part of a integrated application that will enable automated traffic signal management based on vehicle type automatic detection.
The Design of Low Temperature Coefficient Band-Gap Reference

Sometimes, the high-resolution A/D or D/A converter all need a high precision reference, the voltage of reference will determine the precision of the conversion result. In whole system, it always requires that the conversion result should be in a specified range in a wide temperature range. In order to release the variation range of conversion result, it requires that the temperature coefficient of reference should be very small. In this paper, it introduces one higher order compensated band-gap reference, it uses the current $\mathrm{I}_{\mathrm{b}}$ from the existing structure to compensate the higher-order voltage of $\mathbf{V}_{\mathrm{BE}}$. In this way, the temperature coefficient of this Band-Gap Reference will be less than 1ppm/°C in theory.
Recommendation System Based on Data Analysis-Application on Tweets Sentiment Analysis

Recommendation are at the heart of our web activity, they are part of the personalization of access to information, to offer the user items that correspond to his expectations. This article discusses the different types of approaches on which recommendation systems are based. First, we will talk about the different types of recommendation systems and approaches used with its advantages and disadvantages and some work related to the recommendation systems. In this article we will present our approach of recommendation which is based on the analysis of the feelings of the users from consumers reviews on articles. Example of application on twitter by analyzing the sentiment contained in the comments of the tweets.
Discrete-Time Model-Based Eigen-Value Stability Analysis for Multiple-VSC System

With an increasing application of voltage source converter technologies in distribution systems, the dynamic performance is becoming of particular interesting for the designing and stability analysis. In this context, this paper presents discrete-time modeling and stability analysis method for VSC-based AC/DC systems. The converters are defined in this paper through discrete-time modeling, and the dynamic characteristics and stability of the system can be discussed by analyzing the eigenvalues of the state space matrix, in s-plane. According to the case study and simulation results, the accuracy of the method and the theoretical analyses are validated. The modelling can be effectively applied to the design of the controller parameters and the prediction of the stability boundaries.
Model Predictive Control of H5 Inverter for Transformerless PV Systems with Maximum Power Point Tracking and Leakage Current Reduction

Transformerless grid-connected solar photovoltaic (PV) systems have given rise to more research and commercial interests due to their multiple merits, e.g., low leakage current and small size. In this paper, a model-predictive-control (MPC)-based strategy for controlling transformerless H5 inverter for single-phase PV distributed generation system is proposed. The method further reduces the PV leakage current in a cost-effective and safe manner and it shows a satisfactory fault-ride-through capability. Moreover, for the first of its kind, PV maximum power point tracking is implemented in the single-stage H5 inverter using MPC-based controllers. Various case studies are carried out, which provide the result comparisons between the proposed and conventional control methods and verify the promising performance of the proposed method.
A Deep Learning Based Method for Heat Pump Dryer User Classification

Energy consumption by the residential sector contributes significantly to overall worldwide energy consumption. Insights from residential energy usage play an important role in efficient use of appliances. The condenser dryer is among the highest energy consuming appliance. In this article, a Deep Learning based method is proposed to identify efficient heat-pump dryers. Results indicate the proposed method performs better than traditional event based and machine learning methods. The method presented has been successfully implemented and deployed in a cloud-based distributed big data platform and provides services to a live product currently offered to more than 300,000 European customers.
2.5D Palmprint Recognition using Signal level Fusion and Graph based Matching

Effective fusion schemes for combining complementary information from multiple sensors can improve the performance of applications like multi-biometric recognition. Multi-biometric recognition have become very popular as a counter measure for direct spoofing attack. Palmprint has evolved as a popular trait over the years for multi-biometric recognition due to its non-intrusiveness, low cost for capture device, and stable feature set. However, 2D and 3D palmprint in isolation can become vulnerable to spoofing attacks. In this paper, we propose a signal level fusion scheme for 2D and 3D palmprints to obtain an improved multimodal biometric system. In particular, we first generate a 2.5D palmprint data using standard deviation based locally adaptive signal level fusion of 2D and 3D palmprints. A graph based template matching framework is designed next for the purpose of recognition. Comprehensive comparisons with several existing works indicate the benefit of our proposed solution.
Exploring the Detectability of Short-Circuit Faults in Inverter-Fed Induction Motors

This paper explores the possibility of creating an automatic method for assessing the condition of induction motor circuits fed by inverters. The stator current and magnetic flux are processed in the frequency domain and a feature selection stage is employed to pinpoint the most informative components to further be fed to a classifier that performs the assessment of the motor circuit. The results are promising, indicating that short circuit detection as well as quantification is feasible using noninvasive techniques.