Electromagnetic fields and environmental noise: human health impacts in Serzedelo, Guimarães (Portugal)

The present paper investigates the risks that arise from exposure to noise from powerpoles and powerlines in Serzedelo, in the municipality of Guimarães, in Portugal. This research focused on four guiding questions: Can powerlines cause noise? Do powerlines cause discomfort? Do powerlines cause discomfort due to noise? And can powerlines effect human health? Two groups were the basis of the study: people that were exposed to electromagnetic waves and people that were not. the research pointed to the harmful influence of the presence of powerlines and high-voltage masts in residential areas and the damage to the cells in the human body. This type of environmental noise, which has the spectral content of a low frequency, typically tonal noise and a very high speed of propagation, is a complex source to explain in terms of the health profiles of the human population living in Serzedelo, located in an area that is densely occupied by high voltage powerlines and powerpole.

Automatic visual detection of human behavior: a review from 2000 to 2014

Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Generic system for human-computer gesture interaction

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

An integrated system for human action recognition from video using hidden Markov model

In this paper, we present an integrated system for real-time automatic detection of human actions from video. The proposed approach uses the boundary of humans as the main feature for recognizing actions. Background subtraction is performed using Gaussian mixture model. Then, features are extracted from silhouettes and Vector Quantization is used to map features into symbols (bag of words approach). Finally, actions are detected using the Hidden Markov Model. The proposed system was validated using a newly collected real- world dataset. The obtained results show that the system is capable of achieving robust human detection, in both indoor and outdoor environments. Moreover, promising classification results were achieved when detecting two basic human actions: walking and sitting.

Human mobility patterns at the smallest scales

We present a study on human mobility at small spatial scales. Differently from large scale mobility, recently studied through dollar-bill tracking and mobile phone data sets within one big country or continent, we report Brownian features of human mobility at smaller scales. In particular, the scaling exponents found at the smallest scales is typically close to one-half, differently from the larger values for the exponent characterizing mobility at larger scales. We carefully analyze 12-month data of the Eduroam database within the Portuguese university of Minho. A full procedure is introduced with the aim of properly characterizing the human mobility within the network of access points composing the wireless system of the university. In particular, measures of flux are introduced for estimating a distance between access points. This distance is typically non-Euclidean, since the spatial constraints at such small scales distort the continuum space on which human mobility occurs. Since two different ex- ponents are found depending on the scale human motion takes place, we raise the question at which scale the transition from Brownian to non-Brownian motion takes place. In this context, we discuss how the numerical approach can be extended to larger scales, using the full Eduroam in Europe and in Asia, for uncovering the transi- tion between both dynamical regimes.

The impact of work clothing design on workers’ comfort

Physical and physiological comfort, at work and during leisure time, is important to human health and motivation. A growing number of jobs require workers to sit. Most clothes, except those intended for wheelchair users, were designed for walking or the standing position. Clothing designs should be user-oriented and meet users’ needs. Garment design should conform to body position and posture, not just shape and size. In this paper we present the ergometric impact of a new type of trousers designed to adapt to changes in position. Concentrations of compression forces, temperature and pressure were documented in an exploratory pilot study and contrasted to traditional designs. The new trousers showed significant decreases in compression force concentration, especially in and around the knees and waist. Most participants identified comfort as an important factor when purchasing a pair of trousers and that, for working purposes, they would prefer these special trousers rather than traditional designs.

Measurement of the top pair production cross-section in 8 TeV proton-proton collisions using kinematic information in the lepton+jets final state with ATLAS

A measurement is presented of the tt¯ inclusive production cross section in pp collisions at a center-of-mass energy of s√=8  TeV using data collected by the ATLAS detector at the CERN Large Hadron Collider. The measurement was performed in the lepton+jets final state using a data set corresponding to an integrated luminosity of 20.3  fb−1. The cross section was obtained using a likelihood discriminant fit and b-jet identification was used to improve the signal-to-background ratio. The inclusive tt¯ production cross section was measured to be 260±1(stat)+22−23(stat)±8(lumi)±4(beam)  pb assuming a top-quark mass of 172.5 GeV, in good agreement with the theoretical prediction of 253+13−15  pb. The tt¯→(e,μ)+jets production cross section in the fiducial region determined by the detector acceptance is also reported.

Measurement of Spin Correlation in Top-Antitop Quark Events and Search for Top Squark Pair Production in pp Collisions at s√=8 TeV Using the ATLAS Detector

A measurement of spin correlation in tt¯ production is presented using data collected with the ATLAS detector at the Large Hadron Collider in proton-proton collisions at a center-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 20.3 fb−1. The correlation between the top and antitop quark spins is extracted from dilepton tt¯ events by using the difference in azimuthal angle between the two charged leptons in the laboratory frame. In the helicity basis the measured degree of correlation corresponds to Ahelicity=0.38±0.04, in agreement with the Standard Model prediction. A search is performed for pair production of top squarks with masses close to the top quark mass decaying to predominantly right-handed top quarks and a light neutralino, the lightest supersymmetric particle. Top squarks with masses between the top quark mass and 191 GeV are excluded at the 95% confidence level.

Observation of top-quark pair production in association with a photon and measurement of the t t ¯ γ production cross section in pp collisions at s =7 TeV using the ATLAS detector

A search is performed for top-quark pairs (tt¯) produced together with a photon (γ) with transverse momentum >20 GeV using a sample of tt¯ candidate events in final states with jets, missing transverse momentum, and one isolated electron or muon. The dataset used corresponds to an integrated luminosity of 4.59 fb−1 of proton--proton collisions at a center-of-mass energy of 7 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. In total 140 and 222 tt¯γ candidate events are observed in the electron and muon channels, to be compared to the expectation of 79±26 and 120±39 non-tt¯γ background events respectively. The production of tt¯γ events is observed with a significance of 5.3 standard deviations away from the null hypothesis. The tt¯γ production cross section times the branching ratio (BR) of the single-lepton decay channel is measured in a fiducial kinematic region within the ATLAS acceptance. The measured value is σfidtt¯γ=63±8(stat.)+17−13(syst.)±1(lumi.) fb per lepton flavor, in good agreement with the leading-order theoretical calculation normalized to the next-to-leading-order theoretical prediction of 48±10 fb.

Search for direct pair production of a chargino and a neutralino decaying to the 125 GeV Higgs boson in root s=8 TeV pp collisions with the ATLAS detector

A search is presented for the direct pair production of a chargino and a neutralino pp→χ~±1χ~02, where the chargino decays to the lightest neutralino and the W boson, χ~±1→χ~01(W±→ℓ±ν), while the neutralino decays to the lightest neutralino and the 125 GeV Higgs boson, χ~02→χ~01(h→bb/γγ/ℓ±νqq). The final states considered for the search have large missing transverse momentum, an isolated electron or muon, and one of the following: either two jets identified as originating from bottom quarks, or two photons, or a second electron or muon with the same electric charge. The analysis is based on 20.3 fb−1 of s√=8 TeV proton-proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with the Standard Model expectations, and limits are set in the context of a simplified supersymmetric model.

Search for Higgs Boson Pair Production in the γγbb¯ Final State using pp Collision Data at s√=8TeV from the ATLAS Detector

Searches are performed for resonant and non-resonant Higgs boson pair production in the hh→γγbb¯ final state using 20 fb−1 of proton--proton collisions at a center-of-mass energy of 8TeV recorded with the ATLAS detector at the CERN Large Hadron Collider. A 95% confidence level upper limit on the cross section times branching ratio of non--resonant production is set at 2.2 pb, while the expected limit is 1.0 pb. The corresponding limit observed for a narrow resonance ranges between 0.8 and 3.5 pb as a function of its mass.

Structure of Anopheles (Diptera: Culicidae) population in areas with different degrees of human settlement: Cantá - Roraima - Brazil

Malaria has still been one of the most important endemic diseases in the Amazonian region. This study presents the impact of human settlements on the structure of Anopheles population. Diversity, abundance, richness and distribution of the genus Anopheles were observed in two areas with different levels of human settlement in the Cantá city, Roraima State, Northern Brazil. The influence of the dry and rainy seasons on mosquito populations was also observed. Mosquito captures were performed between 6:00 and 10:00 pm during the dry (February and November) and rainy (May and August) seasons at four different sites of each area. Among the 11 species of Anopheles identified through the adults' characteristics, An. albitarsis s.l. (45.5%) and An. darlingi (19.2%) were the most abundant in the more intensively anthropized area while An. triannulatus (19.2%) was more common in the less modified area. Other species found were An. nuneztovari (10.9%), An. oswaldoi (2.0%), An. evansae (1.7%), An. brasiliensis (0.6%), An. intermedius (0.3%), An. mediopunctatus (0.5%), An. periassui (0.08%) and An. argyritarsis (0.04%). The highest mosquitoes' population density was observed in May and the lowest one was observed in February and November. These results demonstrate the existence of a high diversity of anophelines in the study areas, showing that anthropic changes in the environment and climate variability affect both the population density and relative abundance of these vectors.

Enhancement of adhesion and promotion of osteogenic differentiation of human adipose stem cells by poled electroactive poly(vinylidene fluoride)

Poly(vinylidene fluoride) (PVDF) is a biocompatible material with excellent electroactive properties. Non-electroactive α-PVDF and electroactive β-PVDF were used to investigate the substrate polarization and polarity influence on the focal adhesion size and number as well as on human adipose stem cells (hASCs) differentiation. hASCs were cultured on different PVDF surfaces adsorbed with fibronectin and focal adhesion size and number, total adhesion area, cell size, cell aspect ratio and focal adhesion density were estimated using cells expressing EGFP-vinculin. Osteogenic differentiation was also determined using a quantitative alkaline phosphatase assay. The surface charge of the poled PVDF films (positive or negative) influenced the hydrophobicity of the samples, leading to variations in the conformation of adsorbed extracellular matrix (ECM) proteins, which ultimately modulated the stem cell adhesion on the films and induced their osteogenic differentiation.