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Phasor estimation is fundamental for most real-time analysis, monitoring, and control tasks in power systems. New applications on microgrids and active distribution networks make such estimation increasingly important, leading to many research efforts focusing on known approaches, such as the Fourier and cosine filters, to abate the estimation errors; others rely on newly applied algorithms like the Taylor–Kalman–Fourier filter (TKF). This variety has led to discussions about the application cases of each technique, normally demoting the Fourier filter (FF). In this spirit, the FF was reworked under the Hilbert space power theory, showing its conceptual correctness and then deriving an accurate and fast alternative relying on a discrete, lead-compensated filter. Such FF is tested over an active distribution network system, showing advantages in relevant scenarios, namely impedance estimation, grid-monitoring, and fault location. The proposal exhibits better dynamic performance and overshoot than the conventional techniques, with no increased complexity, and “cleaner” results than the TKF, which is, however, faster to estimate the system's impedances.

Objective: to map diverse evidence on perspectives and challenges for implementing the Expert Patient Program. Method: this is a scoping review, guided by the method proposed by the JBI and which followed the recommendations set forth in the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews, with its research protocol registered in the Open Science Framework, with DOI:10.17605/OSF.IO/D7K6A. The search for studies was carried out in July 2022 in databases and in national and international portals of theses and dissertations. Results: the final sample consisted of six scientific articles, all written in English. Health professionals' qualification, to identify and qualify expert patients, management's commitment to the program, use of mobile technologies and Evidence-Based Practice are among the perspectives for implementation. The challenges are related to lack of understanding of the term "self-management" and to the deficit of public policies and financial investment. Conclusion: the results found emphasize the importance of implementing the Patient Expert Program for the public health context, mainly in relation to the population with chronic non-communicable diseases.

RESUMO Objetivo: Mapear evidências sobre as perspectivas e desafios para implementação do Programa Paciente Experto. Método: Trata-se de uma scoping review, orientada a partir do método proposto pelo JBI, e seguiu as recomendações do Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews, com o protocolo de pesquisa registrado no Open Science Framework DOI:10.17605/OSF.IO/D7K6A. A busca pelos estudos foi realizada no mês de julho de 2022, e ocorreu nas bases de dados e em portais de teses e dissertações nacionais e internacionais. Resultados: A amostra final foi composta por seis artigos científicos, todos redigidos na língua inglesa. Entre as perspectivas para implementação, estão a qualificação dos profissionais de saúde, para identificar e qualificar pacientes expertos, o comprometimento da gestão com o programa, o uso das tecnologias móveis e a Prática Baseada em Evidência. Já os desafios são relacionados à falta de compreensão do termo "autogestão” e ao déficit de políticas públicas e investimento financeiro. Conclusão: Os resultados encontrados enfatizam a importância da implementação do Programa Paciente Experto para o contexto de saúde pública, principalmente, em relação à população portadora de doenças crônicas não transmissíveis.

This work presents a novel method to identify the source of current unbalance during the interaction between industrial consumers and the utility. Since such unbalance yields detrimental effects over the network operation and efficiency; it must be mitigated to avoid their propagation towards the whole grid. To prevent this situation, regulations about the maximum permissible limits of unbalance are recently incorporated in grid codes. Unfortunately, in the absence of an accurate method to identify the agent inducing the unbalance; the problem, responsibility, as well as the solution, is vulnerable to misinterpretation. This situation is quite relevant, for both the consumer and the utility since imputations are subject to penalties. Prompted by this issue, we devised a method based on the computation of sequence impedance matrices. Then the underlying elements of the sequence impedance matrix will expose the occurrence of an unbalance as well as its source, which leads to a theoretically derived metric. This method is tested using real measurements of actual industrial loads connected to different voltage levels (i.e. 230 kV, 161 kV and 115 kV). The results demonstrate accuracy in the detection and identification of the cause of unbalance, considering a wide range of power consumption.

The article proposes a new method based on a Taylor–Fourier filter-bank implemented with O-splines for the detection and classification of faults. This method defines a multiresolution approach employing a specific design of bandpass filters to improve the fault detection, taking into account the transient information superimposed into the fundamental frequency produced by the faults. The proposed Taylor–Fourier filter-bank with O-splines has been validated considering different scenarios of faults in high voltage transmission lines. Then, an easily adapted classification stage that renders instantaneous classifications according to the fault type is carried out through a Petri net. The results confirm that the proposal presents important advantages since it reduces the detection time and exhibits an outstanding classification performance.

Pozol is a beverage made with maize dough that is prepared after boiling the kernels in limewater, causing a decrease in soluble sugars, with starch being the main fermentable carbohydrate in the dough. Previously, Streptococcus infantarius ssp. infantarius 25124 (Sii-25124) was identified as the most amylolytic bacteria isolated in this product. Analysis of Sii-25124 amylolytic enzymes revealed two amylases, a cytoplasmic α-amylase of 55.7 kDa and an extracellular amylopullulanase of 246.3 kDa, with two catalytic domains, one typical of an α-amylase and another typical of a pullulanase/glycogen debranching enzyme. Characterization of the joint activity of both enzymes using Sii-25124 cell lysate supernatant demonstrated stability between 30 °C and 45°C, and pH stability in a range between 6.8 and 8.0. The joint activity of Sii-25124 amylases showed a fast production of reducing sugars when starch was used as the substrate. In contrast, reducing sugar production from amylopectin was lower, but it steadily increased throughout the reaction time. The amylopullulanase produced by Sii-25124 hydrolyzes the starch in the dough to produce low molecular weight oligosaccharides, which may be transported into Sii-25124 cells, so that intracellular α-amylase hydrolyzes them to mono- and disaccharides. Amylopullulanase production by Sii-25124 could be an example of a specialized enzyme that successfully dominates starchy food fermentation.

Phase-locked loop (PLL) systems play a crucial role in grid synchronization. Since variations on the grid voltage parameters are in general uncertain, the dynamics of PLLs are by nature nonlinear. This fact imposes a relevant challenge to guarantee their stability. Unfortunately, as argued in this paper, there is a remarkable lack of global stability tests even for the most common approaches, such as the synchronous reference frame (SRF). In this case, there is only available a small-signal—linearized—model-based approach to stability. The main issue of resorting to local conclusions is that synchronization is forced to operate under conservative conditions, where large-signal variations are forbidden. Needless to say, this has a detrimental impact on applications, since performance is limited by small disturbance assumptions. Motivated by this problem, in the present work, we provide global asymptotic stability tests for two fundamental PLL algorithms. Namely, the conventional SRF-PLL and the enhanced SRF-EPLL. To do so, we use a Lyapunov approach acting directly on nonlinear trajectories. Consequently, the provided stability proofs do not rely on any linearization technique, frequency-domain conversion, or small-signal model representation. The main contribution in this paper is a set of stability conditions that are valid in a global sense. Moreover, it is shown that these results have direct practical implications in the form of new robust PLL gain tuning guidelines.

We introduce a model-free scheme that is capable of identifying topology changes in distribution networks using data from distribution-level phasor measurement units (D-PMUs). To do so, we use algebraic tools of behavioral system theory to develop easy-to-implement algorithms. The intrinsic difficulties associated with D-PMU measurements and their proposed solution are discussed as an additional challenge for the implementation of the proposed algorithms. Experimental results using real D-PMUs and laboratory real-time hardware are provided as a proof of concept using a standard IEEE-test node feeder.

A 14-year-old boy with a history of atrial tachycardia presented to the emergency department with acute right foot weakness. One month prior to presentation, he had a self-resolving diarrheal illness and bacterial pneumonia treated with antibiotics. Two weeks later, he endorsed a dull headache, increased irritability, and neck pain. One week prior to presentation, he developed intermittent urinary retention and episodes of flushing and redness of his right face. He fell 5 days prior to presentation and in the ensuing days, he complained of bilateral hip pain and paresthesias that progressively spread to involve bilateral thighs. On the day of presentation, the patient noticed weakness of his right ankle and foot. There was no history of fever. He denied joint pain, swelling, rash, or facial droop, but he did endorse mild sound sensitivity.

Fault detection and location is a challenging issue in microgrid protection, which is increasingly more complex in the presence of distributed generators based on renewable energy, due to their inherent intermittency. In this context, a novel data-driven approach for fault detection and location in microgrids is proposed, by using graph theory representation and micro-synchrophasors also known as μ PMUs. This proposal adopts the conviction to provide an accurate fault location even under variations in short-circuit levels caused by the intermittency of distributed generators. This is in sharp contrast with traditional short-circuit rating-based methods, which are not always advisable due to the intermittent nature of power sources. This work proposes the use of a modelling specification in terms of equilibrium equations, that can reveal not only the underlying physical laws of the netowork, but also the occurrence and location of short circuits based on phasor data. The intermittency of distributed generation is modelled in the proposed approach, which permits to yield trustworthy information either distributed generators are involved in a fault or not. As a consequence, the fault location errors are significantly reduced during the fault location process. The theoretical findings of this proposal are validated via simulation results and experiments using commercial micro-synchrophasors and hardware-in-the-loop emulation of a realistic microgrid.

A new technique to improve fault location methods in AC transmission lines is introduced in this study. The identification of fault location is carried out using one-end fault location algorithms based on impedance through dynamic phasors. This timely approach relies upon the fact that a fault resistance may introduce errors in the distance estimation when a fault takes place. Therefore, active power variations caused by the fault are used to enhance the fault location algorithms, i.e. power losses increase during the fault period for non-zero fault resistances. The present approach is extensively evaluated, using ATP-EMPT software, which relies upon the computation of a compensation factor associated with the rate of change in the resistance during pre-fault and fault conditions. This is achieved through the estimated phasors for voltage and current. Furthermore, the dynamic phasor estimation technique Taylor-Kalman-Fourier Filter is compared against a static phasor method. The proposed approach is validated using three fault location algorithms which are evaluated under different fault conditions, such as fault inception, location, and fault resistance. Results show that this proposed technique improves the fault location including fault resistances by 3% with respect to existing approaches.

En este trabajo se presenta un nuevo índice de bloqueo para mejorar el rendimiento de la protección diferencial del transformador basado en la secuencia negativa. Para garantizar la confiabilidad de cualquier red eléctrica, los esquemas de protección son una tarea principal. Particularmente, los transformadores de potencia porque están sujetos a eventos transitorios tales como fallas entre espiras, corrientes de magnetización y sobreexcitación. En consecuencia, la protección del transformador debe funcionar correctamente bajo fenómenos transitorios. Para analizar fallas internas y eventos transitorios en transformadores, se implementa una protección diferencial de secuencia negativa mediante el uso del software ATP / EMTP. El esquema propuesto emplea un esquema de protección diferencial (87Q), que se basa principalmente en la diferencia angular entre secuencias negativas de corrientes primarias y secundarias utilizando un ángulo de operación de relé (ROA). Esta protección mejorada introduce un índice de bloqueo para evitar el mal funcionamiento durante la energización del transformador porque ha sido reportado que el ROA puede presentar un mal funcionamiento durante eventos transitorios. El nuevo índice introducido representa una distancia entre secuencias durante el período transitorio, lo que ayuda a discriminar las fallas internas de las corrientes de energización. En este sentido, los autores presentan una evaluación del índice de bloqueo introducido para evitar el mal funcionamiento, especialmente cuando esta protección está funcionando en condiciones desbalanceadas, o en condiciones transitorias, como la corriente de energización. Con base en los resultados, la propuesta presenta un buen desempeño y su efectividad se demuestra bajo diferentes escenarios de falla.

Mucus is a viscoelastic gel that acts as a protective barrier for epithelial surfaces. The mucosal vehicles and adjuvants need to pass through the mucus layer to make drugs and vaccine delivery by mucosal routes possible. The mucoadhesion of polymer particle adjuvants significantly increases the contact time between vaccine formulations and the mucosa; then, the particles can penetrate the mucus layer and epithelium to reach mucosa-associated lymphoid tissues. This review presents the key findings that have aided in understanding mucoadhesion and mucopenetration while exploring the influence of physicochemical characteristics on mucus–polymer interactions. We describe polymer-based particles designed with mucoadhesive or mucopenetrating properties and discuss the impact of mucoadhesive polymers on local and systemic immune responses after mucosal immunization. In future research, more attention paid to the design and development of mucosal adjuvants could lead to more effective vaccines.

This paper introduces a new single switch DC-DC fourth-order boost converter. The proposed converter is the improved version of an existing converter known as the super-boost converter. The improved super-boost ISP converter achieves a smaller input current ripple than the super-boost converter when the same parameters in passive components are used. Conversely, smaller components can be used to achieve the same input current ripple, which leads to a compact and cheaper design. A comparative evaluation showed a reduction of 37.3% of stored energy in inductors to comply with a required input current ripple in comparison with the super-boost converter for a particular design. Experimental results are provided to corroborate this benefit of the ISB proposed topology.

This work proposes a data-driven approach to controlling the alternating current (AC) voltage via a static synchronous compensator (STATCOM). This device offers a fast dynamic response injecting reactive power to compensate the voltage profile, not only during load variations but also depending on the operating point established by the grid. The proposed control scheme is designed to improve the dynamic grid performance according to the defined operating point into the grid. The mathematical fundamentals of the proposed control strategy are described according to a (model-free) data-driven-based controller. The robustness of the proposed scheme is proven with several tests carried out using Matlab/Simulink software. The analysis is performed with the well-known test power system of two areas, demonstrating that the proposed controller can enhance the dynamic performance under transient scenarios. As the main strength of the present work with respect to the current state-of-the-art, we highlight the fact that no prior knowledge of the system is required for the controller implementation, that is, a model or a system representation. The synthesis of the controller is obtained in a pure numerical way from data, while it can simultaneously ensure stability in a rigorous way, by satisfying Lyapunov conditions.

Turn-to-turn short circuits occur due to insulation damage in transformer windings and these may potentially result in catastrophic faults affecting electric networks. In fact, transformer diagnosis plays an important role for preventing large energy outages. A new sensitive method based on wavelet transform for identifying interturn faults during energization of single-distribution transformers is presented. The diagnosis is performed utilizing the magnetizing currents obtained during transformer energization under healthy and faulty conditions. Magnetization currents are processed with the wavelet transform and using correlation matrices, which in turn are used to obtain a time-frequency power spectral density (PSD); these are used to quantify the damage level when transformer windings are experiencing faults during their energization. The proposed method was analyzed during simulations using ATP-EMPT software and experimental tests were also carried out in laboratory to validate the results.

This study describes an extended approach to the differential protection of power transformers to identify turn-to-turn faults based on the second central moment (SCM). The proposal uses the differential currents as the input signals to the algorithm. Differential currents are filtered and normalised to allow the proposed algorithm to be independent of the transformer parameters (power, reactance, connection etc.). Then, the SCM magnitude of the differential currents is computed and compared with an established threshold to detect the internal faults. If the SCM magnitude exceeds the limit, an internal fault is detected. Otherwise, the event is determined as a transient event or steady state. The proposed algorithm was implemented in MATLAB and was tested on a three-phase system using a Real-Time Digital Simulator. For laboratory experiments, a real 55-kVA transformer setup was used to validate the effectiveness of the algorithm. The algorithm successfully identified turn-to-turn faults from steady state, as well as during transformer energisations, in over 1000 cases.

Objectives The aim of this study was to investigate the feasibility of saliva sampling as a non-invasive and safer tool to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and to compare its reproducibility and sensitivity with nasopharyngeal swab samples (NPS). The use of sample pools was also investigated. Methods A total of 2107 paired samples were collected from asymptomatic healthcare and office workers in Mexico City. Sixty of these samples were also analyzed in two other independent laboratories for concordance analysis. Sample processing and analysis of virus genetic material were performed according to standard protocols described elsewhere. A pooling analysis was performed by analyzing the saliva pool and the individual pool components. Results The concordance between NPS and saliva results was 95.2% (kappa 0.727, p = 0.0001) and 97.9% without considering inconclusive results (kappa 0.852, p = 0.0001). Saliva had a lower number of inconclusive results than NPS (0.9% vs 1.9%). Furthermore, saliva showed a significantly higher concentration of both total RNA and viral copies than NPS. Comparison of our results with those of the other two laboratories showed 100% and 97% concordance. Saliva samples are stable without the use of any preservative, and a positive SARS-CoV-2 sample can be detected 5, 10, and 15 days after collection when the sample is stored at 4 °C. Conclusions The study results indicate that saliva is as effective as NPS for the identification of SARS-CoV-2-infected asymptomatic patients. Sample pooling facilitates the analysis of a larger number of samples, with the benefit of cost reduction.