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In Angola, marine invertebrates comprise a group of animals with few studies carried out, and their biodiversity is considerably unknown. For this reason, this study aims to describe the diversity and ecology of crabs of the infraorder Brachyura present in the mangroves of the urban district of Morro dos Veados, Luanda - Angola from November/2022 to January/2023. For this purpose, the selected area was fragmented into 3 crab collection points, random collections were made at low tide at each point, the specimens collected were washed, photographed, fixed and identified with the aid of specialized bibliography, then quantitative analyses of the data obtained, calculations of ecological indices and multivariate analyses were carried out for each collection point. The brachiopods in the study area were found to comprise 7 species, belonging to 5 families and 6 genera. In terms of abundance, the species Uca tangeri was the most abundant in the area with around 67%, and also the most frequent. The study area in general showed low diversity, possibly associated with the dominance of the Uca tangeri species in the area. However, PCC1 and PCC2 showed similar richness values, with PCC1 having the highest richness and PCC3 the lowest richness in the study area. [ABSTRACT FROM AUTHOR]

This article aimed to analyze the use of the tax benefit of conventional remuneration of share capital (CRSC) by Portuguese companies and perceive the influence of tax policies on their financing decisions. Most of the studies are based on the relationship between financing through debt capital and taxation, in which evidence is found that tax benefits influence the capital structure of companies. There is a lack of studies in Portuguese companies. The article is relevant as it adds the increase in capital variable, because in some countries, particularly Portugal, there are also tax incentives through the own-capital financing route. Thus, this investigation provides results of Portuguese companies choosing own-capital financing before and after tax changes that incentivize its use. The empirical study was conducted through a survey questionnaire, using a sample composed of 324 Portuguese companies with economic activity. The article contributes to the study of the relationship between own-capital financing and the existing tax law in Portugal. The tax benefit of CRSC has not been enough for companies to alter their financing policy when they have to choose between resorting to debt capital and injecting new funds through capital holders. However, this incentive has led to a reduction in debt capital, through its conversion into capital, and an increase in capital through the incorporation of earnings generated, with both these practices potentially representing tax planning opportunities. Despite there being the perception that the acceptance of interest as a tax expense favors company financing through debt capital, there is recognition that this benefit incentivizes the capitalization of companies and their financing through own capital, as an alternative to debt capital, especially in medium-sized companies. [ABSTRACT FROM AUTHOR]

Objective: To screen pregnant women with positive serological results for toxoplasmosis using noninvasive, ultra-wide field retinal imaging. Methods: Prospective, descriptive longitudinal study including pregnant women with positive serological results for toxoplasmosis seen at three maternal care reference units located in Belém (PA), in the Brazilian Amazon. Patient data were collected via interview. Comprehensive eye examination, including best corrected visual acuity, biomicroscopy, tonometry and ultra-wide field imaging, was performed every three months. Results: The sample comprised 36 pregnant women. Of these, 52% had a serological profile consistent with acute toxoplasmosis, whereas 48% had a serological profile consistent with immunity. Three pregnant women had signs of chorioretinitis on ultra-wide field imaging in the first trimester. An active lesion adjacent to a scarred lesion was detected in one patient. Only women with serological results consistent with acute toxoplasmosis were treated. Treatment with systemic corticosteroids was limited to the patient with active ocular lesion. Follow-up assessment revealed resolution of the ocular lesion and normalization of visual acuity (20/20). All newborns were examined. No signs of congenital toxoplasmosis were found. Conclusion: Ophthalmological screening of pregnant women with positive serological results for toxoplasmosis should be standardized to prevent vision loss in newborns and mothers. Ultra-wide field retinal imaging can be used as an initial screening strategy to support referral for specialized care, particularly in areas with limited access ophthalmology services. [ABSTRACT FROM AUTHOR]

This paper presents the analysis of obtained result from continuous data monitoring of a 41 kWp solar PV system installed on the rooftop of faculty of medicine building at An-Najah National University, Nablus, Palestine (32°13ʹ43.67° N and 35°13ʹ15.72° E). The system was monitored for three years 2016–2018 and it consists of 128 PV panels, an inverter DC/AC, and a grid-connected gross meter. The output electricity feeding to the grid solar electricity is compared and verified with the results from the simulation software program (PVsys) by adopting the installed component specifications, operation conditions, and weather data of the site. The energy generated was fed into the existing power grid and the respective building loads through SMA inverters. The performance parameters of the plant evaluated and compared with other Mediterranean countries, Final Yield (FY) was 1684 kWh/kWp, Reference Yield (RY) was 2046.507 kWh/kWp, and Capacity Utilization Factor (CUF) was found to be 18.5%. The annual average monthly Performance Ratios (PR) for three operating years were 0.88, 0.86 and 0.85, respectively. These indicators provide good feedback for system designers, contractors and energy providers with the actual capacity and feasibility of the system that they can offer the end-users. [ABSTRACT FROM AUTHOR]

Owing to the low equivalent impedance of six‐phase machines in the secondary subspace, in which currents do not contribute to torque production, low‐order current harmonics with high amplitude are likely to appear in the stator currents, increasing the harmonic distortion and the losses in the machine. In the case of permanent magnet synchronous machines (PMSMs), the main causes of these harmonics are machine asymmetries, non‐linearities of the power converters and back‐electromotive force harmonics. The existing predictive control strategies based on virtual vectors for six‐phase machines only regulate the currents mapped into the fundamental subspace, responsible for flux/torque production and leave the currents mapped into the secondary subspace uncontrolled. This study proposes a novel bi‐subspace predictive control strategy for six‐phase PMSMs with optimal amplitude virtual vectors, which is able to effectively regulate the currents in both subspaces simultaneously, leading to a significant minimisation of the current harmonic distortion. Moreover, the proposed control strategy also allows operating the six‐phase PMSM with a current unbalance between the two sets of windings. Both simulation and experimental results confirm the much better performance of the proposed strategy in comparison with other state‐of‐the‐art predictive control strategies found in the literature. [ABSTRACT FROM AUTHOR]

• Integration of data and provenance play a central role in agronomic research. • RFlow is a framework for capturing provenance of data-centric agronomic experiments. • It allows reuse of R scripts encapsulated by generic scientific meta-workflows. • RFlow save data and metadata in repositories compatible with W3C PROV recommendation. • Researchers or referees can browse information or protocols using Web interfaces. With improvements in computing and communications, the amount of scientific data in agriculture has been exploding. Thus, researchers must rely on computational simulations to model the data-driven in silico agronomic experiments, the in silico experiments are those that are completely executed by using computer models. Reproducibility, transparency, independent verification are major features of Science. However, even agricultural research of exemplary quality may have irreproducible empirical findings because of random or systematic error. Funding agencies, researchers, and reviewers are demanding improved processes and the use of open data to increase reproducibility of those experiments. Currently, there are no scientific criteria to evaluate the integration of data-driven agronomic experiments with data provenance. We propose RFlow, a framework that aid researchers to manage, share, and enact the scientific in silico experiments of research projects that use reusable R scripts. The framework uses open data standards and transparently captures provenance of the agronomic experiments. RFlow is non-intrusive, can be connected to workflow systems and does not require researchers to change their working way. Our computational experiments show that the framework can collect provenance metadata and enrich a scientific project. This study shows how RFlow can serve as the primary integration platform for statistical systems, like R, with implications for other data and compute-intensive agronomic projects. As a proof of concept, we show the concrete effectiveness and expressive power of the RFlow which was evaluated through a set of data-driven agronomic in silico experiments and provenance SQL queries that exemplifies what kind of information was gathered. [ABSTRACT FROM AUTHOR]

This study presents a new fault‐tolerant predictive power control strategy for doubly‐fed induction generators (DFIGs) used in wind energy applications, with the rotor fed by a three‐level neutral point clamped converter. The proposed control strategy is able to maintain the system in operation with a good performance after the occurrence of either open‐circuit (OC) or short‐circuit faults in the insulated‐gate bipolar transistors (IGBTs) of the rotor‐side converter (RSC), thus reducing the downtime and maintenance costs of wind turbines. The fault‐tolerant strategy takes advantage of the discrete nature and flexibility of finite control set model predictive control strategies and restricts the possible switching states of the power converter according to the type of fault and its location. A diagnosis method for IGBT OC faults in the RSC, based on voltage errors, is also proposed for the considered system. This method uses the estimated rotor voltages from the DFIG model, thus avoiding the use of any extra sensors. Accurate and fast detection of OC faults in both interior and exterior IGBTs is achieved throughout the entire DFIG operational range. The effectiveness of the fault diagnosis method and fault‐tolerant control strategy is validated with several experimental results. [ABSTRACT FROM AUTHOR]

A key focus in 21st century integrative biology and drug discovery for neglected tropical and other diseases has been the use of BLAST-based computational methods for identification of orthologous groups in pathogenic organisms to discern orthologs, with a view to evaluate similarities and differences among species, and thus allow the transfer of annotation from known/curated proteins to new/non-annotated ones. We used here a profile-based sensitive methodology to identify distant homologs, coupled to the NCBI's COG (Unicellular orthologs) and KOG (Eukaryote orthologs), permitting us to perform comparative genomics analyses on five protozoan genomes. OrthoSearch was used in five protozoan proteomes showing that 3901 and 7473 orthologs can be identified by comparison with COG and KOG proteomes, respectively. The core protozoa proteome inferred was 418 Protozoa-COG orthologous groups and 704 Protozoa-KOG orthologous groups: (i) 31.58% (132/418) belongs to the category J (translation, ribosomal structure, and biogenesis), and 9.81% (41/418) to the category O (post-translational modification, protein turnover, chaperones) using COG; (ii) 21.45% (151/704) belongs to the categories J, and 13.92% (98/704) to the O using KOG. The phylogenomic analysis showed four well-supported clades for Eukarya, discriminating Multicellular [(i) human, fly, plant and worm] and Unicellular [(ii) yeast, (iii) fungi, and (iv) protozoa] species. These encouraging results attest to the usefulness of the profile-based methodology for comparative genomics to accelerate semi-automatic re-annotation, especially of the protozoan proteomes. This approach may also lend itself for applications in global health, for example, in the case of novel drug target discovery against pathogenic organisms previously considered difficult to research with traditional drug discovery tools. [ABSTRACT FROM AUTHOR]

Abstract: Service-Oriented Architecture and Web Services technologies improve the performance of activities involved in geospatial analysis with a distributed computing architecture. However, the design of the geospatial analysis process on this platform, by combining component Web Services, presents some open issues. The automated construction of these compositions represents an important research topic. Some approaches to solving this problem are based on AI planning methods coupled with semantic service descriptions. This work presents a new approach using AI planning methods to improve the robustness of the produced geospatial Web Services composition. For this purpose, we use semantic descriptions of geospatial data quality requirements in a rule-based form. These rules allow the semantic annotation of geospatial data and, coupled with the conditional planning method, this approach represents more precisely the situations of nonconformities with geodata quality that may occur during the execution of the Web Service composition. The service compositions produced by this method are more robust, thus improving process reliability when working with a composition of chained geospatial Web Services. [Copyright &y& Elsevier]

This paper presents a new method to diagnose rotor faults in operating three-phase induction motors under the presence of time-varying loads. The proposed diagnostic strategy relies on a combined analysis of the amplitude and phase spectra of the instantaneous active and reactive powers of the motor, and allows to discriminate the effects introduced by a rotor fault from the ones caused by an oscillating load torque, even when these phenomena occur simultaneously. A theoretical analysis carried out using a linearized model of the induction motor in a synchronous reference frame, complemented with several simulation and experimental results, confirms the validity of the proposed diagnostic approach. [ABSTRACT FROM AUTHOR]

This paper presents a new diagnostic technique for the diagnosis of open-circuit faults in matrix converters operating with an Optimum Alesina-Venturini modulation scheme. Compared to previous diagnostic techniques developed for matrix converters, the technique proposed in this paper has the major advantage of not requiring the installation of any additional sensors in the converter besides the ones already present for control purposes. Hence, it can be easily integrated into the control platform of the converter at no additional cost. In addition to the diagnostic approach, a new fault-tolerant switching strategy is also presented so that after the appearance of an open-circuit fault, the matrix converter can continue to run although with degraded performance, until a repair action can be taken. Several simulation and experimental results are presented, demonstrating the effectiveness and applicability of the developed techniques. [ABSTRACT FROM AUTHOR]

The monitoring of power converters is critical for obtaining systems with self-diagnostic capabilities and fault-tolerant features. This paper presents an analytical work concerning the operation of matrix converters (MCs) under the presence of open-circuit faults and discusses the applicability of a method for the diagnosis of this type of failures. The proposed method uses the absolute values of nine modulated error voltages for the continuous monitoring of the condition of the bidirectional switches of an MC. This method allows a fast detection and location of the faulty switches, independent of the modulation strategy of the converter, its voltage transfer ratio, output frequency, or type of load connected to it, both in steady-state and transient regimes. The theory, validated by simulation and experimental results, demonstrates the applicability of the proposed technique for the diagnosis of faults in MCs. [ABSTRACT FROM AUTHOR]

This paper proposes a new model-based diagnostic technique, which is the so-called virtual current technique (VCT), for the diagnosis of rotor faults in direct rotor field oriented controlled (DRFOC) induction motor drives. By measuring the oscillations at twice the slip frequency found in the rotor flux of the machine, and by conjugating this information with the knowledge of some motor parameters, as well as the parameters of the flux and current controllers, it is possible to generate a virtual magnetizing current which, after normalization, allows the detection and quantification of the extension of the fault. The proposed method allows one to overcome the major difficulties usually found in the diagnosis of rotor faults in closed-loop drives by providing information about the condition of the machine in a way that is independent of the working conditions of the drive such as the load level, reference speed, and bandwidth of the control loops. Although the VCT was primarily developed for traction drives used in railway applications, it can be incorporated in any DRFOC drive at almost no additional cost. Several simulation results, obtained with different types of DRFOC drives, as well as experimental results obtained in the laboratory, demonstrate the effectiveness of this new diagnostic approach. [ABSTRACT FROM AUTHOR]

This paper proposes the use of the multiple reference frames theory for the diagnosis of stator faults in three-phase induction motors. The development of a simplified mathematical motor model allowed the establishment of the equivalent circuits of the motor, in d-q-0 axes, in the presence of suitor interturn short circuits. The use of the stationary reference frame, clockwise and counterclockwise synchronous reference frames, allows the extraction and manipulation of the information contained in the motor supply currents in a way that the effects introduced by the fault are easily isolated and measured. A severity factor is defined and the simulation and experimental results presented demonstrate its independence in relation to the working conditions of the motor, such as the load level and unbalances in the voltage supply system. Although the technique is here introduced for the diagnosis of suitor faults, it is possible to extend its use for the diagnosis of other asymmetries such as broken rotor ban and air-gap eccentricity. [ABSTRACT FROM AUTHOR]

This paper deals with the use of a new diagnostic technique based on the multiple reference frames theory for the diagnosis of stator winding faults in a direct-torque-controlled (DTC) induction motor drive. The theoretical aspects underlying the use of this diagnostic technique are presented but a major emphasis is given to the integration of the diagnostic system into the digital-signal-processor (DSP) board containing the control algorithm. Taking advantage of the sensors already built in the drive for control purposes, it is possible to implement this diagnostic system at no additional cost, thus giving a surplus value to the drive itself. Experimental results show the effectiveness of the proposed technique to diagnose stator faults and demonstrate the possibility of its integration in the DSP board. [ABSTRACT FROM AUTHOR]

This paper addresses the subject of stator fault diagnosis in direct torque control (DTC) induction motor drives. The particularities of the behavior of a DTC drive, when in the presence of inter-turn short circuits, are exploited, thus allowing the proposal of two different approaches for the diagnosis of this type of fault One of the proposed diagnostic techniques is the well known motor current spectrum analysis. It is demonstrated that in a DTC induction motor drive, with stator inter-turn short circuits, the action of the torque and flux controllers introduce a strong third harmonic in the motor supply currents, which can be used to detect this type of fault. The other diagnostic technique is based on the multiple reference frames theory, recently proposed by the authors for the diagnosis of stator faults in line-connected motors. Here, its use is exploited in the diagnosis of stator faults in DTC induction motor drives. [ABSTRACT FROM AUTHOR]

The current transformers with split-core are used for installation in places where it is impossible to install classic current transformers. Moreover, this design allows for any measurement location change, and even switching one current transformer into several different shapes of bars or cables. Power network operators, striving for more accurate current measurements, require producers to provide current transformers with a special accuracy class 0.2S. Therefore, manufacturers and designers try to meet the market requirements and, similarly to non-demountable current transformers, i.e., with a toroidal core, design current transformers with split-core class 0.2S. To meet the high metrological requirements, 3D analyses of electromagnetic fields were performed, taking into account physical phenomena and not approximate analytical models. Two types of cores and four different arrangements of the secondary windings of the measuring current transformers were considered. The magnetic field distributions, current error, and phase displacement diagrams of all current transformer models were analyzed, and the model of the transformer structure with the best accuracy was selected. Computations were conducted based on the finite element numerical method, and the results were compared with the real model tests. [ABSTRACT FROM AUTHOR]

Recently, the control of multiphase electric drives has been a hot research topic due to the advantages of multiphase machines, namely the reduced phase ratings, improved fault tolerance and lesser torque harmonics. Finite control set model predictive control (FCS-MPC) is one of the most promising high performance control strategies due to its good dynamic behaviour and flexibility in the definition of control objectives. Although several FCS-MPC strategies have already been proposed for multiphase drives, a comparative study that assembles all these strategies in a single reference is still missing. Hence, this paper aims to provide an overview and a critical comparison of all available FCS-MPC techniques for electric drives based on six-phase machines, focusing mainly on predictive current control (PCC) and predictive torque control (PTC) strategies. The performance of an asymmetrical six-phase permanent magnet synchronous machine is compared side-by-side for a total of thirteen PCC and five PTC strategies, with the aid of simulation and experimental results. Finally, in order to determine the best and the worst performing control strategies, each strategy is evaluated according to distinct features, such as ease of implementation, minimization of current harmonics, tuning requirements, computational burden, among others. [ABSTRACT FROM AUTHOR]

In the context of inductive power transfer (IPT) for electric vehicle (EV) charging, the precise determination of the mutual inductance between the magnetic pads is of critical importance. The value of this inductance varies depending on the EV positioning, affecting the power transfer capability. Therefore, the precise determination of its value yields various advantages, particularly by contributing to the optimization of the charging process of the EV batteries, since it offers the possibility of adjusting the position of the vehicle depending on the level of misalignment. Within this framework, algorithms grounded in artificial intelligence (AI) techniques emerge as promising solutions. This research work revolves around the estimation of the mutual inductance in a wireless inductive power transfer system using a resonant converter topology, implemented in MATLAB/Simulink® R2021b. The system output was developed to emulate the behavior of a battery charger. To estimate this parameter, an artificial neural network (ANN) was developed. Given the characteristics of the system, the features were chosen in a way that they could provide a clear indication to the ANN if the vehicle position changed, independently of the charging power. In the pursuit of creating a robust AI model, the training dataset contained approximately 1% of the available data. Upon the analysis of the results, it was verified that the largest estimation error observed was around 3%, occurring at the lowest charging power considered. Hence, it can be inferred that the proposed ANN exhibits the capability to accurately estimate the value of mutual inductance in this type of system. [ABSTRACT FROM AUTHOR]

The problem of precise modeling of Synchronous Generator (SG) devices is demanding and crucial for monitoring, stability, and control of electric grids and microgrids. SGs are known to exhibit nonlinear behavior, and because they may work in a wide range of operating points due to different electric network phenomena like load changes, current intermittent renewable energy resources, temperature variations, topological changes, etc., the modeling task of SG can be a challenging problem. This paper proposes a new method to find a global model for a synchronous generator from the input and output measurement data using state-of-the-art methods in artificial intelligence (AI) like fuzzy clustering, subspace identification, and Takagi–Sugeno (T–S) fuzzy modeling. The fuzzy C-means method is utilized to cluster the measurement data, and then using a subspace identification method based on Markov parameters concepts, the dynamic model of SG for each cluster is obtained in the form of a state space model. A Takagi–Sugeno fuzzy model is applied to determine the corresponding outputs based on the measured inputs and the available state space models. The effectiveness of the proposed approach is illustrated by applying it to the data obtained from simulations on a known fourth-order SG nonlinear model and the data obtained from real-world experimental tests. [ABSTRACT FROM AUTHOR]

Objectives: The National Registry of Healthcare Facilities is a system with the registry of every healthcare facility in Brazil with information on the capacity building and healthcare workforce regarding its public or private nature. Despite being publicly available, it can only be accessed in separated disjoint tables, with different primary units of analysis. The objective is to offer an interoperable dataset containing monthly data from 2005 to 2021 with information on healthcare facilities, including their physical and human resources, services and teams, enriched with municipal information. Data description: Database with historical data and geographic information for each health facility in Brazil. It is composed by 5 distinct tables, organized according to combinations of time, space, and types of resources, services and teams. This database opens up a range of possibilities for research topics, from case studies in a single health facility and period, analysis of a group of health facilities with characteristics of interest, to a broader study using the entire dataset and aggregated data by municipality. Furthermore, the fact that there is a row for each health facility/month/year facilitates the integration with other datasets from the Brazilian healthcare system. In addition to being a potential object of study in the health area, the dataset is also convenient in data science, especially for studies focused on time series. [ABSTRACT FROM AUTHOR]

Wind turbines are increasingly expanding worldwide and Doubly‐Fed Induction Generator (DFIG) is a key component of most of them. Stator winding fault is a major fault in this equipment and its incipient detection is of vital importance. However, there is a paucity of research in this field. In this study, a novel machine learning‐based method is proposed for incipient detection of inter‐turn short‐circuit fault (ITF) in the DFIG stator based on the current signals of the stator. The proposed method makes use of state‐of‐the‐art deep learning methods along with conventional signal processing tools and general machine learning techniques. More specifically, the incipient fault detection problem is regarded as a multi‐class classification problem and a Long Short‐Term Memory network, which is more appropriate for time‐series data is utilised for inference. Furthermore, a variant of the celebrated Empirical mode Decomposition analysis tool is used to extract some well‐known statistical features among which the most informative ones are selected using a new feature selection method. Our tests using experimental data in steady‐state conditions show that the proposed method can accurately detect ITF fault at its initial stage when only one turn is shorted. Moreover, its performance is considerably higher than that of a variety of machine learning‐based methods. [ABSTRACT FROM AUTHOR]

A new real‐time method able to diagnose multiple semiconductor open‐circuit (OC) faults in a three‐level neutral‐point clamped inverter is introduced in this paper. The proposed diagnostic method is based on the evaluation of the output pole voltages and output currents of the inverter. The proposed method allows a real‐time detection and localisation of multiple OC faults in all active power switches and clamp‐diodes within one modulation period. Experimental results obtained for different operating conditions of the inverter demonstrate the applicability and performance of the proposed diagnostic approach. [ABSTRACT FROM AUTHOR]

Objectives: Surveillance of infant and fetal deaths is of paramount importance in thinking about government strategies to reduce these rates, provide greater visibility of these mortality figures in the country, enable the adoption of prevention measures, as well as contribute to a better record of deaths. Data description: The dataset comprises fetal, neonatal, early neonatal, late neonatal, and perinatal Mortality Rates of Brazilian municipalities with their respective information, between 2010 to 2020, aggregated by epidemiological week. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for fault diagnosis in three-level neutral point clamped inverters. The proposed method is based on the average values of the positive and negative parts of normalized output currents. This method is capable of detecting and locating multiple open-circuit faults in the controlled power switches of converters in half of a fundamental period of those currents. The implementation of this diagnostic approach only requires two output currents of the inverter. Therefore, no additional sensors are needed other than the ones already used by the control system of a drive based on this type of converter. Moreover, through the normalization of currents, the diagnosis is independent of the load level of the converter. The performance and effectiveness of the proposed diagnostic technique are validated by experimental results obtained under steady-state and transient conditions. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the application of the on-load exciting current Extended Park''s Vector Approach to diagnose incipient turn-to-turn winding faults in operating power transformers. Experimental and simulation test results demonstrate the effectiveness of the proposed technique, which is based on the spectral analysis of the AC component of the on-load exciting current Park''s Vector modulus. [Copyright &y& Elsevier]

Here a new sensitive fault detection criterion is proposed, based on the stationary wavelet transform (SWT) decomposition components of the stator currents, for the online detection of stator winding turn‐to‐turn faults at an early stage of development. The energies of the desired detail components are calculated and the normalized Euclidean distance of the energy differences between the three phases is used as a new fault detection criterion. The robustness of the proposed technique against the presence of rotor turn‐to‐turn faults and loading variations is demonstrated. In addition, an adaptive threshold level as a function of the voltage unbalance factor is proposed to guarantee the robustness of the diagnostic technique against unbalanced voltage sources. Experimental results demonstrate the effectiveness and sensitivity of the proposed diagnostic approach for the detection of stator faults in line‐connected and inverter‐fed motors. [ABSTRACT FROM AUTHOR]

Objectives: Neonatal mortality is a global public health problem, and the efforts to reduce child mortality is one of the goals of the 2030 Agenda for Sustainable Development, launched in 2015 by the United Nations. The availability of historical neonatal mortality rates (NMR) data in Brazilian municipalities is crucial to evaluate trends at local, regional and national level, identifying gaps and vulnerable territories. Therefore, the objective of this article is to offer an integrated dataset containing monthly data in a historical series from 1996 to 2017 with information on all births, neonatal deaths, and NMR (total, early and late components) enriched with information related to the municipality. Data description: It is a dataset of historical data with information on the number of births, the number of neonatal deaths, the neonatal mortality rate (including early and late), and geographic information for each month (between January 1996 and December 2017) and Brazilian municipality. [ABSTRACT FROM AUTHOR]

Background: Poncet's disease is a rare syndrome characterized by articular impairment in a form of rare tuberculid. One of the theories of its cause involves an autoimmune response induced by the intravesical administration of the Calmette-Guerin Bacillus or the treatment of bladder carcinoma. Furthermore, there may be an appearance of oligoarticular or polyarticular arthritis, beginning 1-3 months after the start of therapy. Few physicians know the disease and the literature related to that syndrome is scarce and restricted to case reports, which contributes to its under diagnosis. Case presentation: Female patient, 64 years old, Caucasian, in whom was noticed firstly dark urine, without haematuria or dysuria. Later felt also colic pain in the hypogastric region. Microscopically, the conclusive diagnosis was a high grade non-invasive papillary urothelial carcinoma. Thereupon, the treatment of the tumour began with transurethral resection technique and intravesical instillation of Calmette-Guérin Bacillus as adjuvant treatment. Eight months after the beginning of treatment, the lingering presence of the carcinoma was identified. Nevertheless, arthritis was identified through radiographs, after an increase in the clavicle capitation, right knee and left ankle in bone scintigraphy. Coinciding with the joint manifestations, the patient developed fever and purulent urethral discharge (culture was negative). Therefore, trying to investigate the cause of the arthritis, Purified Protein Derivate was taken, with reactive results. An increase of acute phase reactants was found, with other tests resulting normal: blood chemistry, Complete Blood Count, immunology and serology. Human Leukocyte Antigen typing by polymerase chain reaction revealed the presence of A24/AX, B44, B27, BW4/BW4, DQ7 and DQ5. Consequently, Poncet's disease was the diagnostic conclusion. The treatment with intravesical Calmette-Guérin Bacillus was immediately discontinued. The patient received corticosteroids associated with etoricoxib and isoniazid for 4 months, achieving disappearance of the inflammatory joint signs in 3 months. After 6 months, no joint pain recurrence or other manifestations suggesting active disease had been seen. Conclusions: Therefore, such diagnosis should be considered when confronted with an osteoarticular clinical picture in patients treated with intravesical Calmette-Guérin Bacillus, especially patients with HLA-B27 (+) and B7 (+), as Poncet's disease is a reactive arthritis. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of a wound rotor induction motor (WRIM) under rotor inter-turn short circuit (SC) fault. Magnetic equivalent circuit (MEC) and finite elements method (FEM) are used to model the machine. Impacts of the fault on the signals of the machine including rotor current, stator current, and developed torque of the motor are addressed. Current of SC turns is also the signal that is considered here. A method based on the MEC is used to estimate different inductances of WRIM in which the impact of yokes, stator and rotor tooth, windings distribution and also core saturation are included. The obtained inductances are compared with that of the FEM and effect of the SC turns on the inductances are investigated. Finally, the fault is diagnosed using Fourier transform of the stator current and verified by experimental results. [ABSTRACT FROM AUTHOR]

The operational reliability and high efficiency of modern electrical machines depend on the ability to transfer heat in the construction parts of the machine. Therefore, many authors study various thermal models and work on the development of effective heat dissipation. New insights and methods lead to improved techniques for the thermal design of electrical machines. This paper presents an experimentally validated thermal model of a permanent magnet synchronous motor (PMSM) with an improved slot winding model. It also deals with various approaches to homogenization and equivalent material properties of a tooth-coil winding sub-model. First, an algorithm for building a lumped-parameter thermal network (LPTN) of PMSM is described and its properties and problems are discussed. Subsequently, a sub-model of a slot with a winding based on the finite element method (FEM) is introduced. This sub-model is able to generate different conductor distributions based on probabilistic methods for a specified fill factor. This allows the verification of various homogenization approaches and at the same time it is a tool that automatically calculates thermal resistances for the LPTN. [ABSTRACT FROM AUTHOR]

Uninterruptible Power Supplies (UPS) have been demonstrated to be the key technology in feeding either single- and three-phase loads in a wide range of critical applications, such as high-tier datacenters and medical facilities. To increase the overall system power capacity and resilience, UPS systems are usually connected in parallel. When UPS systems are parallel connected, a circulating current can rise, inhibiting correct system operation. Moreover, having a controlled load power distribution is another fundamental requirement in paralleled UPS systems. However, strategies to ensure these two topics have not been explored to date for UPS systems with a load-side neutral connection. This paper proposes an innovative Finite Control Set Model Predictive Control (FCS-MPC) strategy that ensures circulating current elimination and controlled load power distribution for paralleled UPS systems that use an additional inverter leg for load neutral point connection. Additionally, a system topology based on two parallel-connected UPS systems that can simultaneously supply single- and three-phase critical loads is proposed. Experimental results show the effectiveness and robustness of the proposed control techniques even when different types of loads are connected to the UPS systems. [ABSTRACT FROM AUTHOR]

In modern power systems, since most loads are inductive by nature, there is an ongoing power quality issue and researchers' interest in improving the power factor is widespread, as inductive loads have a low power factor that depletes the system's capacity and has an adverse effect on the voltage level. The measurement and acute analysis of voltage- and current-level waveforms is essential to tackle power quality issues. This article presents a detailed case study and analysis of real-time data measured from a frequency converter, which is used to operate the motor of a ventilation system. The output of the frequency converter is a highly distorted current wave. A hybrid Fourier transform (FT)- and wavelet transform-based solution has been proposed here to diagnose and identify the causes of motor failure in the ventilation system. The traditional FT did not give a detailed analysis of this type of signal, which is highly contaminated by noise. Therefore, first, the signal is preprocessed for data denoising using the wavelet transform. Second, the Fourier analysis is performed on the filtered signal for frequency analysis and segregation of fundamental frequency components, higher-order harmonics, and suppressed noise. The spectrum analysis reveals that the noise is generated due to the rapidly switching circuits in the frequency converter and this unfiltered signal at the output of the frequency converter causes motor failure. [ABSTRACT FROM AUTHOR]

This article presents a high-performance lead-free piezoelectric energy harvester (LPEH) system for magnetic field. It based on a Ba0.85Ca0.15Ti0.90Zr0.10O3 + CuO 0.3 wt% (BCTZC0.3) composite was fabricated by sintering at 1450 °C. The BCTZC0.3 composite, which has an enhanced high energy conversion constant ( d 33 × g 33 ), shows improved piezoelectric power-generation performance when compared with conventional piezoelectric energy harvesters. The BCTZC0.3-based LPEH produces instantaneous maximum power of 8.2 mW and an energy density of 107.9 mW/cm3 in a weak magnetic field of 250 μT. This system can be used to charge a capacitor and operate a wireless sensor network (WSN) system to provide temperature sensing and radio-frequency (RF) transmission in a 250 μT magnetic field. The proposed LPEH is a promising green-energy device for potentially self-powering WSN systems when applied. [ABSTRACT FROM AUTHOR]

This article presents a comparative analysis for the design considerations for a solar power generation transformer. One of the main existing problems in transformer manufacturing is in the renewable energy field, specifically the solar power generation, where the transformer connected to the inverter is operated under a certain harmonic content and operating conditions. The operating conditions of the transformer connected to the inverter are particularly unknown for each solar power plant; thus, the transformer will be subject to a particular harmonic content, which is defined by the inverter of the solar power plant. First, the fundamental calculations for solar power plant transformer and the proposed methodology for the design calculation of the distribution pad-mounted three phase transformer are presented. Then, a design study case is described where a distribution transformer and an inverter of a particular solar power plant are used for the analysis. Next, the transformer under analysis is modeled using finite element analysis in ANSYS Maxwell® software, where the transformer will be designed for a non-harmonic and harmonic content application. Lastly, the main design parameters, flux density, the core losses and the winding excitation voltage of the transformer are calculated and presented in results and discussion section. [ABSTRACT FROM AUTHOR]

Power transformers play an important role in electrical systems; being considered the core of electric power transmissions and distribution networks, the owners and users of these assets are increasingly concerned with adopting reliable, automated, and non-invasive techniques to monitor and diagnose their operating conditions. Thus, monitoring the conditions of power transformers has evolved, in the sense that a complete characterization of the conditions of oil–paper insulation can be achieved through dissolved gas analysis (DGA) and furan compounds analysis, since these analyses provide a lot of information about the phenomena that occur in power transformers. The Duval triangles and pentagons methods can be used with a high percentage of correct predictions compared to the known classical methods (key gases, International Electrotechnical Commission (IEC), Rogers, Doernenburg ratios), because, in addition to the six types of basic faults, they also identify four sub-types of thermal faults that provide important additional information for the appropriate corrective actions to be applied to the transformers. A new approach is presented based on the complementarity between the analysis of the gases dissolved in the transformer oil and the analysis of furan compounds, for the identification of the different faults, especially when there are multiple faults, by extending the diagnosis of the operating conditions of the power transformers, in terms of paper degradation. The implemented software system based on artificial neural networks was tested and validated in practice, with good results. [ABSTRACT FROM AUTHOR]

Nowadays, uninterruptible power supplies (UPS) play an important role in feeding critical loads in the electric power systems such as data centers or large communication hubs. Due to the increasing power of these loads and frequent need for expansion or redundancy, UPS systems are frequently connected in parallel. However, when UPS systems are parallel-connected, two fundamental requirements must be verified: potential circulating currents between the systems must be eliminated and the load power must be distributed between the systems according to UPS systems availability. Moreover, a high-quality load voltage waveform must be permanently ensured. In this paper innovative control strategies are proposed for paralleled UPS systems based on Finite Control Set Model Predictive Control (FCS-MPC). The proposed strategies simultaneously provide: controlled load power distribution, circulating current suppression and a high-quality load voltage waveform. A new dynamic converters deactivation mechanism is proposed. This new technique provides improved overall system efficiency and reduced power switches stress. In this paper, two multilevel based UPS systems are parallel-connected. Each UPS contains two three-level Neutral Point-Clamped-Converters (3LNPC) and a three-level DC-DC converter. The presented experimental results demonstrate the effectiveness of the proposed control strategies in several operating conditions. [ABSTRACT FROM AUTHOR]