Universidade Federal de Itajubá

The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years. The evaluation included the standard VOT and other popular methodologies and a new "real-time" experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The VOT2017 goes beyond its predecessors by (i) improving the VOT public dataset and introducing a separate VOT2017 sequestered dataset, (ii) introducing a realtime tracking experiment and (iii) releasing a redesigned toolkit that supports complex experiments. The dataset, the evaluation kit and the results are publicly available at the challenge website1.

This paper presents a particle swarm optimization (PSO) as a tool for loss reduction study. This issue can be formulated as a nonlinear optimization problem. The proposed application consists of using a developed optimal power flow based on loss minimization function by expanding the original PSO. The study is carried out in two steps. First, by using the tangent vector technique, the critical area of the power system is identified under the point of view of voltage instability. Second, once this area is identified, the PSO technique calculates the amount of shunt reactive power compensation that takes place in each bus. The proposed approach has been examined and tested with promising numerical results using the IEEE 118-bus system.

BACKGROUND: For more than three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has provided a framework to quantify health loss due to diseases, injuries, and associated risk factors. This paper presents GBD 2023 findings on disease and injury burden and risk-attributable health loss, offering a global audit of the state of world health to inform public health priorities. This work captures the evolving landscape of health metrics across age groups, sexes, and locations, while reflecting on the remaining post-COVID-19 challenges to achieving our collective global health ambitions. METHODS: The GBD 2023 combined analysis estimated years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 375 diseases and injuries, and risk-attributable burden associated with 88 modifiable risk factors. Of the more than 310 000 total data sources used for all GBD 2023 (about 30% of which were new to this estimation round), more than 120 000 sources were used for estimation of disease and injury burden and 59 000 for risk factor estimation, and included vital registration systems, surveys, disease registries, and published scientific literature. Data were analysed using previously established modelling approaches, such as disease modelling meta-regression version 2.1 (DisMod-MR 2.1) and comparative risk assessment methods. Diseases and injuries were categorised into four levels on the basis of the established GBD cause hierarchy, as were risk factors using the GBD risk hierarchy. Estimates stratified by age, sex, location, and year from 1990 to 2023 were focused on disease-specific time trends over the 2010-23 period and presented as counts (to three significant figures) and age-standardised rates per 100 000 person-years (to one decimal place). For each measure, 95% uncertainty intervals [UIs] were calculated with the 2·5th and 97·5th percentile ordered values from a 250-draw distribution. FINDINGS: Total numbers of global DALYs grew 6·1% (95% UI 4·0-8·1), from 2·64 billion (2·46-2·86) in 2010 to 2·80 billion (2·57-3·08) in 2023, but age-standardised DALY rates, which account for population growth and ageing, decreased by 12·6% (11·0-14·1), revealing large long-term health improvements. Non-communicable diseases (NCDs) contributed 1·45 billion (1·31-1·61) global DALYs in 2010, increasing to 1·80 billion (1·63-2·03) in 2023, alongside a concurrent 4·1% (1·9-6·3) reduction in age-standardised rates. Based on DALY counts, the leading level 3 NCDs in 2023 were ischaemic heart disease (193 million [176-209] DALYs), stroke (157 million [141-172]), and diabetes (90·2 million [75·2-107]), with the largest increases in age-standardised rates since 2010 occurring for anxiety disorders (62·8% [34·0-107·5]), depressive disorders (26·3% [11·6-42·9]), and diabetes (14·9% [7·5-25·6]). Remarkable health gains were made for communicable, maternal, neonatal, and nutritional (CMNN) diseases, with DALYs falling from 874 million (837-917) in 2010 to 681 million (642-736) in 2023, and a 25·8% (22·6-28·7) reduction in age-standardised DALY rates. During the COVID-19 pandemic, DALYs due to CMNN diseases rose but returned to pre-pandemic levels by 2023. From 2010 to 2023, decreases in age-standardised rates for CMNN diseases were led by rate decreases of 49·1% (32·7-61·0) for diarrhoeal diseases, 42·9% (38·0-48·0) for HIV/AIDS, and 42·2% (23·6-56·6) for tuberculosis. Neonatal disorders and lower respiratory infections remained the leading level 3 CMNN causes globally in 2023, although both showed notable rate decreases from 2010, declining by 16·5% (10·6-22·0) and 24·8% (7·4-36·7), respectively. Injury-related age-standardised DALY rates decreased by 15·6% (10·7-19·8) over the same period. Differences in burden due to NCDs, CMNN diseases, and injuries persisted across age, sex, time, and location. Based on our risk analysis, nearly 50% (1·27 billion [1·18-1·38]) of the roughly 2·80 billion total global DALYs in 2023 were attributable to the 88 risk factors analysed in GBD. Globally, the five level 3 risk factors contributing the highest proportion of risk-attributable DALYs were high systolic blood pressure (SBP), particulate matter pollution, high fasting plasma glucose (FPG), smoking, and low birthweight and short gestation-with high SBP accounting for 8·4% (6·9-10·0) of total DALYs. Of the three overarching level 1 GBD risk factor categories-behavioural, metabolic, and environmental and occupational-risk-attributable DALYs rose between 2010 and 2023 only for metabolic risks, increasing by 30·7% (24·8-37·3); however, age-standardised DALY rates attributable to metabolic risks decreased by 6·7% (2·0-11·0) over the same period. For all but three of the 25 leading level 3 risk factors, age-standardised rates dropped between 2010 and 2023-eg, declining by 54·4% (38·7-65·3) for unsafe sanitation, 50·5% (33·3-63·1) for unsafe water source, and 45·2% (25·6-72·0) for no access to handwashing facility, and by 44·9% (37·3-53·5) for child growth failure. The three leading level 3 risk factors for which age-standardised attributable DALY rates rose were high BMI (10·5% [0·1 to 20·9]), drug use (8·4% [2·6 to 15·3]), and high FPG (6·2% [-2·7 to 15·6]; non-significant). INTERPRETATION: Our findings underscore the complex and dynamic nature of global health challenges. Since 2010, there have been large decreases in burden due to CMNN diseases and many environmental and behavioural risk factors, juxtaposed with sizeable increases in DALYs attributable to metabolic risk factors and NCDs in growing and ageing populations. This long-observed consequence of the global epidemiological transition was only temporarily interrupted by the COVID-19 pandemic. The substantially decreasing CMNN disease burden, despite the 2008 global financial crisis and pandemic-related disruptions, is one of the greatest collective public health successes known. However, these achievements are at risk of being reversed due to major cuts to development assistance for health globally, the effects of which will hit low-income countries with high burden the hardest. Without sustained investment in evidence-based interventions and policies, progress could stall or reverse, leading to widespread human costs and geopolitical instability. Moreover, the rising NCD burden necessitates intensified efforts to mitigate exposure to leading risk factors-eg, air pollution, smoking, and metabolic risks, such as high SBP, BMI, and FPG-including policies that promote food security, healthier diets, physical activity, and equitable and expanded access to potential treatments, such as GLP-1 receptor agonists. Decisive, coordinated action is needed to address long-standing yet growing health challenges, including depressive and anxiety disorders. Yet this can be only part of the solution. Our response to the NCD syndemic-the complex interaction of multiple health risks, social determinants, and systemic challenges-will define the future landscape of global health. To ensure human wellbeing, economic stability, and social equity, global action to sustain and advance health gains must prioritise reducing disparities by addressing socioeconomic and demographic determinants, ensuring equitable health-care access, tackling malnutrition, strengthening health systems, and improving vaccination coverage. We live in times of great opportunity. FUNDING: Gates Foundation and Bloomberg Philanthropies.

The importance of short-term load forecasting has been increasing lately. With deregulation and competition, energy price forecasting has become a big business. Bus-load forecasting is essential to feed analytical methods utilized for determining energy prices. The variability and nonstationarity of loads are becoming worse, due to the dynamics of energy prices. Besides, the number of nodal loads to be predicted does not allow frequent interactions with load forecasting experts. More autonomous load predictors are needed in the new competitive scenario. This paper describes two strategies for embedding the discrete wavelet transform into neural network-based short-term load forecasting. Its main goal is to develop more robust load forecasters. Hourly load and temperature data for North American and Slovakian electric utilities have been used to test the proposed methodology.

We analyze the propagation of light in the context of nonlinear electrodynamics, as it occurs in modified QED vacua. We show that the corresponding characteristic equation can be described in terms of a modification of the effective geometry of the underlying spacetime structure. We present the general form for this effective geometry and exhibit some new consequences that result from such an approach.

ABSTRACT In this study, we follow up our recent paper (Monteiro et al. 2020) and present a homogeneous sample of fundamental parameters of open clusters in our Galaxy, entirely based on Gaia DR2 data. We used published membership probability of the stars derived from Gaia DR2 data and applied our isochrone fitting code, updated as in Monteiro et al. (2020), to GBP and GRPGaia DR2 data for member stars. In doing this, we take into account the nominal errors in the data and derive distance, age, and extinction of each cluster. This work therefore provides parameters for 1743 open clusters and, as a by-product, a list of likely not physical or dubious open clusters is provided as well for future investigations. Furthermore, it was possible to estimate the mean radial velocity of 831 clusters (198 of which are new and unpublished so far), using stellar radial velocities from Gaia DR2 catalogue. By comparing the open cluster distances obtained from isochrone fitting with those obtained from a maximum likelihood estimate of individual member parallaxes, we found a systematic offset of (−0.05 ± 0.04) mas.

Early detection of faults in electrical machines, particularly in induction motors, has become necessary and critical in reducing costs by avoiding unexpected and unnecessary maintenance and outages in industrial applications. Additionally, most of these faults are due to problems in bearings. Thus, in this paper, experimental bearing fault detection of a three-phase induction motor is performed by analyzing the squared envelope spectrum of the stator current. Spectral kurtosis-based algorithms, namely, the fast kurtogram and the wavelet kurtogram, are also applied to improve the envelope analysis. Experimental tests are performed, considering outer bearing faults at different stages, and the results are promising.

This paper describes the third public data release (DR3) of the Calar Alto Legacy Integral Field Area (CALIFA) survey. Science-grade quality data for 667 galaxies are made public, including the 200 galaxies of the second public data release (DR2). Data were obtained with the integral-field spectrograph PMAS/PPak mounted on the 3.5 m telescope at the Calar Alto Observatory. Three different spectral setups are available: i) a low-resolution V500 setup covering the wavelength range 3745–7500 Å (4240–7140 Å unvignetted) with a spectral resolution of 6.0 Å (FWHM) for 646 galaxies, ii) a medium-resolution V1200 setup covering the wavelength range 3650–4840 Å (3650–4620 Å unvignetted) with a spectral resolution of 2.3 Å (FWHM) for 484 galaxies, and iii) the combination of the cubes from both setups (called COMBO) with a spectral resolution of 6.0 Å and a wavelength range between 3700–7500 Å (3700–7140 Å unvignetted) for 446 galaxies. The Main Sample, selected and observed according to the CALIFA survey strategy covers a redshift range between 0.005 and 0.03, spans the color-magnitude diagram and probes a wide range of stellar masses, ionization conditions, and morphological types. The Extension Sample covers several types of galaxies that are rare in the overall galaxy population and are therefore not numerous or absent in the CALIFA Main Sample. All the cubes in the data release were processed using the latest pipeline, which includes improved versions of the calibration frames and an even further improved image reconstruction quality. In total, the third data release contains 1576 datacubes, including ~1.5 million independent spectra.

Abstract We evaluate the performance of a large ensemble of Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) over South America for a recent past reference period and examine their projections of twenty-first century precipitation and temperature changes. The future changes are computed for two time slices (2040–2059 and 2080–2099) relative to the reference period (1995–2014) under four Shared Socioeconomic Pathways (SSPs, SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5). The CMIP6 GCMs successfully capture the main climate characteristics across South America. However, they exhibit varying skill in the spatiotemporal distribution of precipitation and temperature at the sub-regional scale, particularly over high latitudes and altitudes. Future precipitation exhibits a decrease over the east of the northern Andes in tropical South America and the southern Andes in Chile and Amazonia, and an increase over southeastern South America and the northern Andes—a result generally consistent with earlier CMIP (3 and 5) projections. However, most of these changes remain within the range of variability of the reference period. In contrast, temperature increases are robust in terms of magnitude even under the SSP1–2.6. Future changes mostly progress monotonically from the weakest to the strongest forcing scenario, and from the mid-century to late-century projection period. There is an increase in the seasonality of the intra-annual precipitation distribution, as the wetter part of the year contributes relatively more to the annual total. Furthermore, an increasingly heavy-tailed precipitation distribution and a rightward shifted temperature distribution provide strong indications of a more intense hydrological cycle as greenhouse gas emissions increase. The relative distance of an individual GCM from the ensemble mean does not substantially vary across different scenarios. We found no clear systematic linkage between model spread about the mean in the reference period and the magnitude of simulated sub-regional climate change in the future period. Overall, these results could be useful for regional climate change impact assessments across South America.

OBJECTIVE: Deposition of monosodium urate monohydrate (MSU) crystals in the joints promotes an intense inflammatory response and joint dysfunction. This study evaluated the role of the NLRP3 inflammasome and 5-lipoxygenase (5-LOX)-derived leukotriene B(4) (LTB(4) ) in driving tissue inflammation and hypernociception in a murine model of gout. METHODS: Gout was induced by injecting MSU crystals into the joints of mice. Wild-type mice and mice deficient in NLRP3, ASC, caspase 1, interleukin-1β (IL-1β), IL-1 receptor type I (IL-1RI), IL-18R, myeloid differentiation factor 88 (MyD88), or 5-LOX were used. Evaluations were performed to assess neutrophil influx, LTB(4) activity, cytokine (IL-1β, CXCL1) production (by enzyme-linked immunosorbent assay), synovial microvasculature cell adhesion (by intravital microscopy), and hypernociception. Cleaved caspase 1 and production of reactive oxygen species (ROS) were analyzed in macrophages by Western blotting and fluorometric assay, respectively. RESULTS: Injection of MSU crystals into the knee joints of mice induced neutrophil influx and neutrophil-dependent hypernociception. MSU crystal-induced neutrophil influx was CXCR2-dependent and relied on the induction of CXCL1 in an NLRP3/ASC/caspase 1/IL-1β/MyD88-dependent manner. LTB(4) was produced rapidly after injection of MSU crystals, and this was necessary for caspase 1-dependent IL-1β production and consequent release of CXCR2-acting chemokines in vivo. In vitro, macrophages produced LTB(4) after MSU crystal injection, and LTB(4) was relevant in the MSU crystal-induced maturation of IL-1β. Mechanistically, LTB(4) drove MSU crystal-induced production of ROS and ROS-dependent activation of the NLRP3 inflammasome. CONCLUSION: These results reveal the role of the NLRP3 inflammasome in mediating MSU crystal-induced inflammation and dysfunction of the joints, and highlight a previously unrecognized role of LTB(4) in driving NLRP3 inflammasome activation in response to MSU crystals, both in vitro and in vivo.

We study the Dalitz plot of the decay ${D}^{+}\ensuremath{\rightarrow}{K}^{\ensuremath{-}}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{+}$ with a sample of 15090 events from Fermilab experiment E791. Modeling the decay amplitude as the coherent sum of known $K\ensuremath{\pi}$ resonances and a uniform nonresonant term, we do not obtain an acceptable fit. If we allow the mass and width of the ${K}_{0}^{*}(1430)$ to float, we obtain values consistent with those from PDG but the ${\ensuremath{\chi}}^{2}$ per degree of freedom of the fit is still unsatisfactory. A good fit is found when we allow for the presence of an additional scalar resonance, with mass $797\ifmmode\pm\else\textpm\fi{}19\ifmmode\pm\else\textpm\fi{}43\text{ }\mathrm{M}\mathrm{e}\mathrm{V}/{\mathrm{c}}^{\mathrm{2}}$ and width $410\ifmmode\pm\else\textpm\fi{}43\ifmmode\pm\else\textpm\fi{}87\text{ }\mathrm{M}\mathrm{e}\mathrm{V}/{\mathrm{c}}^{2}$. The mass and width of the ${K}_{0}^{*}(1430)$ become $1459\ifmmode\pm\else\textpm\fi{}7\ifmmode\pm\else\textpm\fi{}5\text{ }\mathrm{M}\mathrm{e}\mathrm{V}/{\mathrm{c}}^{\mathrm{2}}$ and $175\ifmmode\pm\else\textpm\fi{}12\ifmmode\pm\else\textpm\fi{}12\text{ }\mathrm{M}\mathrm{e}\mathrm{V}/{\mathrm{c}}^{\mathrm{2}}$, respectively. Our results provide new information on the scalar sector in hadron spectroscopy.

A long-term, multiarea, and multistage model for the supply/interconnections expansion planning of integrated electricity and natural gas (NG) is presented in this paper. The proposed Gas Electricity Planning (GEP) model considers the NG value chain, i.e., from the supply to end-consumers through NG pipelines and the electrical systems value chain, i.e., power generation and transmission, in an integrated way. The sources of NG can be represented by NG wells, liquefied natural gas (LNG) terminals and storages of NG and LNG. The electricity generation may be composed by hydro plants, wind farms, or thermal plants where the latter represent the link between the gas and the electricity chain. The proposed model is formulated as a mixed-integer linear optimization problem which minimizes the investment and operation costs to determine the optimal location, technologies, and installation times of any new facilities for power generation, power interconnections, and the complete natural gas chain value (supply/transmission/storage) as well as the optimal dispatch of existing and new facilities over a long range planning horizon. A didactic case study as well as the Brazilian integrated gas/electricity system are presented to illustrate the proposed framework.

BACKGROUND: Timely and comprehensive analyses of causes of death stratified by age, sex, and location are essential for shaping effective health policies aimed at reducing global mortality. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides cause-specific mortality estimates measured in counts, rates, and years of life lost (YLLs). GBD 2023 aimed to enhance our understanding of the relationship between age and cause of death by quantifying the probability of dying before age 70 years (70q0) and the mean age at death by cause and sex. This study enables comparisons of the impact of causes of death over time, offering a deeper understanding of how these causes affect global populations. METHODS: GBD 2023 produced estimates for 292 causes of death disaggregated by age-sex-location-year in 204 countries and territories and 660 subnational locations for each year from 1990 until 2023. We used a modelling tool developed for GBD, the Cause of Death Ensemble model (CODEm), to estimate cause-specific death rates for most causes. We computed YLLs as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. Probability of death was calculated as the chance of dying from a given cause in a specific age period, for a specific population. Mean age at death was calculated by first assigning the midpoint age of each age group for every death, followed by computing the mean of all midpoint ages across all deaths attributed to a given cause. We used GBD death estimates to calculate the observed mean age at death and to model the expected mean age across causes, sexes, years, and locations. The expected mean age reflects the expected mean age at death for individuals within a population, based on global mortality rates and the population's age structure. Comparatively, the observed mean age represents the actual mean age at death, influenced by all factors unique to a location-specific population, including its age structure. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 250-draw distribution for each metric. Findings are reported as counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2023 include a correction for the misclassification of deaths due to COVID-19, updates to the method used to estimate COVID-19, and updates to the CODEm modelling framework. This analysis used 55 761 data sources, including vital registration and verbal autopsy data as well as data from surveys, censuses, surveillance systems, and cancer registries, among others. For GBD 2023, there were 312 new country-years of vital registration cause-of-death data, 3 country-years of surveillance data, 51 country-years of verbal autopsy data, and 144 country-years of other data types that were added to those used in previous GBD rounds. FINDINGS: The initial years of the COVID-19 pandemic caused shifts in long-standing rankings of the leading causes of global deaths: it ranked as the number one age-standardised cause of death at Level 3 of the GBD cause classification hierarchy in 2021. By 2023, COVID-19 dropped to the 20th place among the leading global causes, returning the rankings of the leading two causes to those typical across the time series (ie, ischaemic heart disease and stroke). While ischaemic heart disease and stroke persist as leading causes of death, there has been progress in reducing their age-standardised mortality rates globally. Four other leading causes have also shown large declines in global age-standardised mortality rates across the study period: diarrhoeal diseases, tuberculosis, stomach cancer, and measles. Other causes of death showed disparate patterns between sexes, notably for deaths from conflict and terrorism in some locations. A large reduction in age-standardised rates of YLLs occurred for neonatal disorders. Despite this, neonatal disorders remained the leading cause of global YLLs over the period studied, except in 2021, when COVID-19 was temporarily the leading cause. Compared to 1990, there has been a considerable reduction in total YLLs in many vaccine-preventable diseases, most notably diphtheria, pertussis, tetanus, and measles. In addition, this study quantified the mean age at death for all-cause mortality and cause-specific mortality and found noticeable variation by sex and location. The global all-cause mean age at death increased from 46·8 years (95% UI 46·6-47·0) in 1990 to 63·4 years (63·1-63·7) in 2023. For males, mean age increased from 45·4 years (45·1-45·7) to 61·2 years (60·7-61·6), and for females it increased from 48·5 years (48·1-48·8) to 65·9 years (65·5-66·3), from 1990 to 2023. The highest all-cause mean age at death in 2023 was found in the high-income super-region, where the mean age for females reached 80·9 years (80·9-81·0) and for males 74·8 years (74·8-74·9). By comparison, the lowest all-cause mean age at death occurred in sub-Saharan Africa, where it was 38·0 years (37·5-38·4) for females and 35·6 years (35·2-35·9) for males in 2023. Lastly, our study found that all-cause 70q0 decreased across each GBD super-region and region from 2000 to 2023, although with large variability between them. For females, we found that 70q0 notably increased from drug use disorders and conflict and terrorism. Leading causes that increased 70q0 for males also included drug use disorders, as well as diabetes. In sub-Saharan Africa, there was an increase in 70q0 for many non-communicable diseases (NCDs). Additionally, the mean age at death from NCDs was lower than the expected mean age at death for this super-region. By comparison, there was an increase in 70q0 for drug use disorders in the high-income super-region, which also had an observed mean age at death lower than the expected value. INTERPRETATION: We examined global mortality patterns over the past three decades, highlighting-with enhanced estimation methods-the impacts of major events such as the COVID-19 pandemic, in addition to broader trends such as increasing NCDs in low-income regions that reflect ongoing shifts in the global epidemiological transition. This study also delves into premature mortality patterns, exploring the interplay between age and causes of death and deepening our understanding of where targeted resources could be applied to further reduce preventable sources of mortality. We provide essential insights into global and regional health disparities, identifying locations in need of targeted interventions to address both communicable and non-communicable diseases. There is an ever-present need for strengthened health-care systems that are resilient to future pandemics and the shifting burden of disease, particularly among ageing populations in regions with high mortality rates. Robust estimates of causes of death are increasingly essential to inform health priorities and guide efforts toward achieving global health equity. The need for global collaboration to reduce preventable mortality is more important than ever, as shifting burdens of disease are affecting all nations, albeit at different paces and scales. FUNDING: Gates Foundation.

The purpose of maintenance is to extend equipment lifetime, or at least the mean time to the next failure. While too little maintenance may have very costly consequences, maintenance, too, incurs expenditures and it may not be economical to perform it too frequently. Therefore, the two costs must be balanced. In the past, attempts to approximate this balance have often been based on trial and error. In this paper, a probabilistic model is proposed for the purpose, and a computer program based on this model is described. The model provides a quantitative connection between reliability and maintenance, a link missing in the heuristic approaches. The component ageing process is modelled, and the mean and distribution of the remaining life to failure are predicted for any stage of ageing. The method is applied to a practical example.

Linguistic modeling of complex irregular systems constitutes the heart of many control and decision making systems, and fuzzy logic represents one of the most effective algorithms to build such linguistic models. In this paper, a linguistic (qualitative) modeling approach is proposed. The approach combines the merits of the fuzzy logic theory, neural networks, and genetic algorithms (GA's). The proposed model is presented in a fuzzy-neural network (FNN) form which can handle both quantitative (numerical) and qualitative (linguistic) knowledge. The learning algorithm of an FNN is composed of three phases. The first phase is used to find the initial membership functions of the fuzzy model. In the second phase, a new algorithm is developed and used to extract the linguistic-fuzzy rules. In the third phase, a multiresolutional dynamic genetic algorithm (MRD-GA) is proposed and used for optimized tuning of membership functions of the proposed model. Two well-known benchmarks are used to evaluate the performance of the proposed modeling approach, and compare it with other modeling approaches.

The application of marginal cost in pricing the transmission services has shown not effective mainly due to revenue reconciliation problems. To overcome this, a set of other methods derived from the MW-mile rule has been suggested to allocate transmission fixed costs. This paper compares such methods known as embedded cost methods in a centralized transmission network environment. Although these methods actually share the total cost and are very simple, they are usually rejected due to the lack of a good economic reasoning. The economic issue and the impact on the system expansion planning of such allocation are addressed in this paper. Some examples with the Brazilian transmission system illustrate the results derived from this analysis.

The unique properties of polymer-hybrid nanosystems enable them to play an important role in different fields such as biomedical applications. Hybrid materials, which are formed by polymer and inorganic- or organic-base systems, have been the focus of many recently published studies whose results have shown outstanding improvements in drug targeting. The development of hybrid polymer materials can avoid the synthesis of new molecules, which is an overall expensive process that can take several years to get to the proper elaboration and approval. Thus, the combination of properties in a single hybrid system can have several advantages over non-hybrid platforms, such as improvements in circulation time, structural disintegration, high stability, premature release, low encapsulation rate and unspecific release kinetics. Thus, the aim of the present review is to outline a rapid and well-oriented scenario concerning the knowledge about polymer-hybrid nanoparticles use in biomedical platforms. Furthermore, the ultimate methodologies adopted in synthesis processes, as well as in applications in vitro/in vivo, are the focus of this review.

This paper presents a new methodology to evaluate loss of load indices, with particular emphasis on LOLC (loss of load cost) assessment, for composite generation and transmission systems considering time varying loads for different areas or buses. The proposed approach, named pseudo-chronological simulation, retains the computational efficiency of nonsequential Monte Carlo simulation and the ability to model chronological load curves in sequential simulation. It considers the actual blocks of unsupplied energy per consumer class, per bus, and the respective duration, to accurately characterize the interruption process. Case studies on the IEEE-MRTS (Modified Reliability Test System) and the BSS (Brazilian South-Southeastern System) are presented and discussed.

The South Atlantic Subtropical Anticyclone (SASA) is the main feature of the atmospheric circulation over the South Atlantic Ocean, and its study is of great importance to explain many characteristics of the Brazilian weather and climate. Therefore, this study aims to present (1) a review of the literature on SASA including the drivers of the semi-permanent anticyclones and (2) the main features of the SASA in the future climate obtained through the projections of three global climate models (HadGEM2-ES, GFDL-ESM2M and MPI-ESM-MR), from the Coupled Model Intercomparison Project (CMIP5), using the Representative Concentration Pathway 8.5 (RCP8.5) scenario. SASA is zonally wider in winter and retracted to the east in summer, when it presents a more circular format. These features of the SASA in the present climate (1979-2005) are well represented by the three global climate models, which also project this same SASA seasonal pattern for the future climate (2065-2095). Considering the projections, they indicate a slightly poleward expansion of the SASA, which is associated with the widening of the Hadley cell. At the SASA core, the pressure can be similar or slightly more intense than the present climate.

An ultra-low-voltage ultra-low-power CMOS Miller operational transconductance amplifier (OTA) with rail-to-rail input/output swing is presented. The topology is based on combining bulk-driven differential pair and dc level shifters, with the transistors work in weak inversion. The improved Miller OTA has been successfully verified in a standard 0.35-mum CMOS process. Experimental results have confirmed that, at a minimum supply voltage of 600 mV, lower than the threshold voltage, the topology presents almost rail-to-rail input and output swings and consumes only 550 nW.