Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data

Crisis-affected communities and global organizations for international aid are becoming increasingly digital as consequence geotechnology popularity. Humanitarian sector changed in profound ways by adopting new technical approach to obtain information from area with difficult geographical or political access. Since 2011, turkey is hosting a growing number of Syrian refugees along southeastern region. Turkish policy of hosting them in camps and the difficulty created by governors to international aid group expeditions to get information, made such international organizations to investigate and adopt other approach in order to obtain information needed. They intensified its remote sensing approach. However, the majority of studies used very high-resolution satellite imagery (VHRSI). The study area is extensive and the temporal resolution of VHRSI is low, besides it is infeasible only using these sensors as unique approach for the whole area. The focus of this research, aims to investigate the potentialities of mid-resolution imagery (here only Landsat) to obtain information from region in crisis (here, southeastern Turkey) through a new web-based platform called Google Earth Engine (GEE). Hereby it is also intended to verify GEE currently reliability once the Application Programming Interface (API) is still in beta version. The finds here shows that the basic functions are trustworthy. Results pointed out that Landsat can recognize change in the spectral resolution clearly only for the first settlement. The ongoing modifications vary for each case. Overall, Landsat demonstrated high limitations, but need more investigations and may be used, with restriction, as a support of VHRSI.

Analysis and implementation of a multi-ratio switched capacitor DC-DC converter for a supercapacitor power supply

An energy harvesting system requires an energy storing device to store the energy retrieved from the surrounding environment. This can either be a rechargeable battery or a supercapcitor. Due to the limited lifetime of rechargeable batteries, they need to be periodically replaced. Therefore, a supercapacitor, which has ideally a limitless number of charge/discharge cycles can be used to store the energy; however, a voltage regulator is required to obtain a constant output voltage as the supercapacitor discharges. This can be implemented by a Switched-Capacitor DC-DC converter which allows a complete integration in CMOS technology, although it requires several topologies in order to obtain a high efficiency. This thesis presents the complete analysis of four different topologies in order to determine expressions that allow to design and determine the optimum input voltage ranges for each topology. To better understand the parasitic effects, the implementation of the capacitors and the non-ideal effect of the switches, in 130 nm technology, were carefully studied. With these two analysis a multi-ratio SC DC-DC converter was designed with an output power of 2 mW, maximum efficiency of 77%, and a maximum output ripple, in the steady state, of 23 mV; for an input voltage swing of 2.3 V to 0.85 V. This proposed converter has four operation states that perform the conversion ratios of 1/2, 2/3, 1/1 and 3/2 and its clock frequency is automatically adjusted to produce a stable output voltage of 1 V. These features are implemented through two distinct controller circuits that use asynchronous time machines (ASM) to dynamically adjust the clock frequency and to select the active state of the converter. All the theoretical expressions as well as the behaviour of the whole system was verified using electrical simulations.

Medium access control design for distributed opportunistic radio networks

Existing wireless networks are characterized by a fixed spectrum assignment policy. However, the scarcity of available spectrum and its inefficient usage demands for a new communication paradigm to exploit the existing spectrum opportunistically. Future Cognitive Radio (CR) devices should be able to sense unoccupied spectrum and will allow the deployment of real opportunistic networks. Still, traditional Physical (PHY) and Medium Access Control (MAC) protocols are not suitable for this new type of networks because they are optimized to operate over fixed assigned frequency bands. Therefore, novel PHY-MAC cross-layer protocols should be developed to cope with the specific features of opportunistic networks. This thesis is mainly focused on the design and evaluation of MAC protocols for Decentralized Cognitive Radio Networks (DCRNs). It starts with a characterization of the spectrum sensing framework based on the Energy-Based Sensing (EBS) technique considering multiple scenarios. Then, guided by the sensing results obtained by the aforementioned technique, we present two novel decentralized CR MAC schemes: the first one designed to operate in single-channel scenarios and the second one to be used in multichannel scenarios. Analytical models for the network goodput, packet service time and individual transmission probability are derived and used to compute the performance of both protocols. Simulation results assess the accuracy of the analytical models as well as the benefits of the proposed CR MAC schemes.

Design of assemblies based on polymer-coated quantum dots and organic dye

During last years, photophysical properties of complexes of semiconductor quantum dots (QDs) with organic dyes have attracted increasing interest. The development of different assemblies based on QDs and organic dyes allows to increase the range of QDs applications, which include imaging, biological sensing and electronic devices.1 Some studies demonstrate energy transfer between QDs and organic dye in assemblies.2 However, for electronic devices purposes, a polymeric matrix is required to enhance QDs photostability. Thus, in order to attach the QDs to the polymer surface it is necessary to chemically modify the polymer to induce electronic charges and stabilize the QDs in the polymer. The present work aims to investigate the design of assemblies based on polymer-coated QDs and an integrated acceptor organic dye. Polymethylmethacrylate (PMMA) and polycarbonate (PC) were used as polymeric matrices, and nile red as acceptor. Additionally, a PMMA matrix modified with 2-mercaptoethylamine is used to improve the attachment between both the donor (QDs) and the acceptor (nile red), as well as to induce a covalent bond between the modified PMMA and the QDs. An enhancement of the energy transfer efficiency by using the modified PMMA is expected and the resulting assembly can be applied for energy harvesting.

Multi-temporal analysis of radiometric changes in satellite images of forest edges to infer selective-logging areas in the Amazon forest

Radiometric changes observed in multi-temporal optical satellite images have an important role in efforts to characterize selective-logging areas. The aim of this study was to analyze the multi-temporal behavior of spectral-mixture responses in satellite images in simulated selective-logging areas in the Amazon forest, considering red/near-infrared spectral relationships. Forest edges were used to infer the selective-logging infrastructure using differently oriented edges in the transition between forest and deforested areas in satellite images. TM/Landsat-5 images acquired at three dates with different solar-illumination geometries were used in this analysis. The method assumed that the radiometric responses between forest with selective-logging effects and forest edges in contact with recent clear-cuts are related. The spatial frequency attributes of red/near infrared bands for edge areas were analyzed. Analysis of dispersion diagrams showed two groups of pixels that represent selective-logging areas. The attributes for size and radiometric distance representing these two groups were related to solar-elevation angle. The results suggest that detection of timber exploitation areas is limited because of the complexity of the selective-logging radiometric response. Thus, the accuracy of detecting selective logging can be influenced by the solar-elevation angle at the time of image acquisition. We conclude that images with lower solar-elevation angles are less reliable for delineation of selecting logging.

Evaluation of geostatistical techniques to estimate the spatial distribution of aboveground biomass in the Amazon rainforest using high-resolution remote sensing data

ABSTRACT The spatial distribution of forest biomass in the Amazon is heterogeneous with a temporal and spatial variation, especially in relation to the different vegetation types of this biome. Biomass estimated in this region varies significantly depending on the applied approach and the data set used for modeling it. In this context, this study aimed to evaluate three different geostatistical techniques to estimate the spatial distribution of aboveground biomass (AGB). The selected techniques were: 1) ordinary least-squares regression (OLS), 2) geographically weighted regression (GWR) and, 3) geographically weighted regression - kriging (GWR-K). These techniques were applied to the same field dataset, using the same environmental variables derived from cartographic information and high-resolution remote sensing data (RapidEye). This study was developed in the Amazon rainforest from Sucumbíos - Ecuador. The results of this study showed that the GWR-K, a hybrid technique, provided statistically satisfactory estimates with the lowest prediction error compared to the other two techniques. Furthermore, we observed that 75% of the AGB was explained by the combination of remote sensing data and environmental variables, where the forest types are the most important variable for estimating AGB. It should be noted that while the use of high-resolution images significantly improves the estimation of the spatial distribution of AGB, the processing of this information requires high computational demand.

Multifunctional Ti–Me (Me=Al, Cu) thin film systems for biomedical sensing devices

Ti-Me binary intermetallic thin films based on a titanium matrix doped with increasing amounts of Me (Me = Al, Cu) were prepared by magnetron sputtering (under similar conditions), aiming their application in biomedical sensing devices. The differences observed on the composition and on the micro(structural) features of the films, attributed to changes in the discharge characteristics, were correlated with the electrical properties of the intermetallic systems (Ti-Al and Ti-Cu). For the same Me exposed areas placed on the Ti target (ranging from 0.25 cm2 to 20 cm2) the Cu content increased from 3.5 at.% to 71.7 at.% in the Ti-Cu system and the Al content, in Ti-Al films, ranged from 11 to 45 at.%. The structural characterization evidenced the formation of metastable Ti-Me intermetallic phases for Al/Ti atomic ratios above 0.20 and for Cu/Ti ratios above 0.25. For lower Me concentrations, the effect of the α-Ti(Me) structure domains the overall structure. With the increase amount of the Me into Ti structure a clear trend for amorphization was observed. For both systems it was observed a significant decrease of the electrical resistivity with increasing Me/Ti atomic ratios (higher than 0.5 for Al/Ti atomic ratio and higher than 1.3 for Cu/Ti atomic ratio). Although similar trends were observed in the resistivity evolution for both systems, the Ti-Cu films presented lower resistivity values in comparison to Ti-Al system.

High-aspect-ratio tridimensional electrode arrays for neural applications

Tese de Doutoramento em Engenharia Biomédica.

Design of bio-based supramolecular structures through self-assembly of α-lactalbumin and lysozyme

Bovine α-lactalbumin (α-La) and lysozyme (Lys), two globular proteins with highly homologous tertiary structures and opposite isoelectric points, were used to produce bio-based supramolecular structures under various pH values (3, 7 and 11), temperatures (25, 50 and 75 °C) and times (15, 25 and 35 min) of heating. Isothermal titration calorimetry experiments showed protein interactions and demonstrated that structures were obtained from the mixture of α-La/Lys in molar ratio of 0.546. Structures were characterized in terms of morphology by transmission electron microscopy (TEM) and dynamic light scattering (DLS), conformational structure by circular dichroism and intrinsic fluorescence spectroscopy and stability by DLS. Results have shown that protein conformational structure and intermolecular interactions are controlled by the physicochemical conditions applied. The increase of heating temperature led to a significant decrease in size and polydispersity (PDI) of α-La–Lys supramolecular structures, while the increase of heating time, particularly at temperatures above 50 °C, promoted a significant increase in size and PDI. At pH 7 supramolecular structures were obtained at microscale – confirmed by optical microscopy – displaying also a high PDI (i.e. > 0.4). The minimum size and PDI (61 ± 2.3 nm and 0.14 ± 0.03, respectively) were produced at pH 11 for a heating treatment of 75 °C for 15 min, thus suggesting that these conditions could be considered as critical for supramolecular structure formation. Its size and morphology were confirmed by TEM showing a well-defined spherical form. Structures at these conditions showed to be stable at least for 30 or 90 days, when stored at 25 or 4 °C, respectively. Hence, α-La–Lys supramolecular structures showed properties that indicate that they are a promising delivery system for food and pharmaceutical applications.

A design of experiments to assess phosphorous removal and crystal properties in struvite precipitation of source separated urine using different Mg sources

Supplementary data associated with this article can be found, in the online version, at: http://dx.doi.org/10.1016/j.cej.2016.03.148.

Variação Temporal no Prognóstico e Tratamento da Insuficiência Cardíaca Avançada - Antes e Após 2000

Fundamento: O tratamento da insuficiência cardíaca evoluiu nas últimas décadas, sugerindo que sua sobrevida tem aumentado. Objetivo: Verificar se houve melhora na sobrevida dos pacientes com insuficiência cardíaca avançada. Métodos: Comparamos retrospectivamente os dados de seguimento e tratamento de duas coortes de pacientes com insuficiência cardíaca sistólica admitidos para compensação até o ano 2000 (n = 353) e após 2000 (n = 279). Foram analisados: morte hospitalar, re-hospitalizações e morte no seguimento de 1 ano. Utilizamos os testes U de Mann-Whitney e qui-quadrado para comparação entre os grupos. Os preditores de mortalidade foram identificados pela análise de regressão por meio do método dos riscos proporcionais de Cox e análise de sobrevida pelo método de Kaplan-Meier. Resultados: Os pacientes internados até o ano 2000 eram mais jovens, tinham menor comprometimento ventricular esquerdo e receberam menor proporção de betabloqueadores na alta. A sobrevida dos pacientes hospitalizados antes de 2000 foi menor do que a dos hospitalizados após 2000 (40,1% vs. 67,4%; p < 0,001). Os preditores independentes de mortalidade na análise de regressão foram: a etiologia chagásica (hazard ratio: 1,9; intervalo de confiança de 95%: 1,3-3,0), inibidores da enzima conversora da angiotensina (hazard ratio: 0,6; intervalo de confiança de 95%: 0,4-0,9), betabloqueador (hazard ratio: 0,3; intervalo de confiança de 95%: 0,2-0,5), creatinina ≥ 1,4 mg/dL (hazard ratio: 2,0; intervalo de confiança de 95%: 1,3-3,0), sódio sérico ≤ 135 mEq/L (hazard ratio: 1,8; intervalo de confiança de 95%: 1,2-2,7). Conclusões: Pacientes com insuficiência cardíaca avançada apresentaram melhora significativa na sobrevida e redução nas re-hospitalizações. O bloqueio neuro-hormonal, com inibidores da enzima conversora da angiotensina e betabloqueadores, teve papel importante no aumento da sobrevida desses pacientes com insuficiência cardíaca avançada.

On the design of peer punishment experiments

We discuss how technologies of peer punishment might bias the results that are observed in experiments. A crucial parameter is the “fine-to-fee” ratio, which describes by how much the punished subjects income is reduced relatively to the fee the punishing subject has to pay to inflict punishment. We show that a punishment technology commonly used in experiments embeds a variable fine-to-fee ratio and show that it confounds the empirical findings about why, whom, and how much subjects punish.

Improved temporal resolution for functional studies with reduced number of segments with three-dimensional echo planar imaging.

PURPOSE: To introduce a new k-space traversal strategy for segmented three-dimensional echo planar imaging (3D EPI) that encodes two partitions per radiofrequency excitation, effectively reducing the number excitations used to acquire a 3D EPI dataset by half. METHODS: The strategy was evaluated in the context of functional MRI applications for: image quality compared with segmented 3D EPI, temporal signal-to-noise ratio (tSNR) (the ability to detect resting state networks compared with multislice two-dimensional (2D) EPI and segmented 3D EPI, and temporal resolution (the ability to separate cardiac- and respiration-related fluctuations from the desired blood oxygen level-dependent signal of interest). RESULTS: Whole brain images with a nominal voxel size of 2 mm isotropic could be acquired with a temporal resolution under half a second using traditional parallel imaging acceleration up to 4× in the partition-encode direction and using novel data acquisition speed-up of 2× with a 32-channel coil. With 8× data acquisition speed-up in the partition-encode direction, 3D reduced excitations (RE)-EPI produced acceptable image quality without introduction of noticeable additional artifacts. Due to increased tSNR and better characterization of physiological fluctuations, the new strategy allowed detection of more resting state networks compared with multislice 2D-EPI and segmented 3D EPI. CONCLUSION: 3D RE-EPI resulted in significant increases in temporal resolution for whole brain acquisitions and in improved physiological noise characterization compared with 2D-EPI and segmented 3D EPI. Magn Reson Med 72:786-792, 2014. © 2013 Wiley Periodicals, Inc.

Design and evaluation of a solid sampler for the monitoring of airborne 1,6-hexamethylene diisocyanate (HDI) and its prepolymers in 2-component spray painting

An active, solvent-free solid sampler was developed for the collection of 1,6-hexamethylene diisocyanate (HDI) aerosol and prepolymers. The sampler was made of a filter impregnated with 1-(2-methoxyphenyl)piperazine contained in a filter holder. Interferences with HDI were observed when a set of cellulose acetate filters and a polystyrene filter holder were used; a glass fiber filter and polypropylene filter cassette gave better results. The applicability of the sampling and analytical procedure was validated with a test chamber, constructed for the dynamic generation of HDI aerosol and prepolymers in commercial two-component spray paints (Desmodur(R) N75) used in car refinishing. The particle size distribution, temporal stability, and spatial uniformity of the simulated aerosol were established in order to test the sample. The monitoring of aerosol concentrations was conducted with the solid sampler paired to the reference impinger technique (impinger flasks contained 10 mL of 0.5 mg/mL 1-(2-methoxyphenyl)piperazine in toluene) under a controlled atmosphere in the test chamber. Analyses of derivatized HDI and prepolymers were carried out by using high-performance liquid chromatography and ultraviolet detection. The correlation between the solvent-free and the impinger techniques appeared fairly good (Y = 0.979X - 0.161; R = 0.978), when the tests were conducted in the range of 0.1 to 10 times the threshold limit value (TLV) for HDI monomer and up to 60-mu-g/m3 (3 U.K. TLVs) for total -N = C = O groups.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.