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We live in an era characterized by Society 4.0 and Industry 4.0 where successive innovations that are more or less disruptive are occurring. Within this context, the modeling and simulation of dynamic supervisory and control systems require dealing with more sophistication and complexity, with effects in terms of development errors and higher costs. One of the most difficult aspects of simulating these systems is the handling of vision sensors. The current tools provide these sensors but in a specific and limited way. This paper describes a six-step approach to sensor virtualization. For testing the approach, a simulation platform based on game engines was developed. As contributions, the platform can simulate dynamic systems, including industrial processes with vision sensors. Furthermore, the proposed virtualization approach allows for the modeling of sensors in a systematic way, reducing the complexity and effort required to simulate this type of system.

Acute porphyrias are a group of rare genetic metabolic disorders, caused by a defect in one of the enzymes involved in the heme biosynthesis, which results in an abnormally high accumulation of toxic intermediates. Acute porphyrias are characterized by potentially life-threatening attacks and, for some patients, by chronic manifestations that negatively impact daily functioning and quality of life. Clinical manifestations include a nonspecific set of gastrointestinal, neuropsychiatric, and/or cutaneous symptoms. Effective diagnostic methods are widely available, but due to their clinical heterogeneity and non-specificity, many years often elapse from symptom onset to diagnosis of acute porphyrias, delaying the treatment and increasing morbidity. Therefore, increased awareness of acute porphyrias among healthcare professionals is paramount to reducing disease burden. Treatment of acute porphyrias is centered on eliminating the potential precipitants, symptomatic treatment, and suppressing the hepatic heme pathway, through the administration of hemin or givosiran. Moreover, properly monitoring patients with acute porphyrias and their relatives is fundamental to preventing acute attacks, hospitalization, and long-term complications. Considering this, a multidisciplinary panel elaborated a consensus paper, aiming to provide guidance for an efficient and timely diagnosis of acute porphyrias, and evidence-based recommendations for treating and monitoring patients and their families in Portugal. To this end, all authors exhaustively reviewed and discussed the current scientific evidence on acute porphyrias available in the literature, between November 2022 and May 2023.

In this article, the main problem under investigation is the detection and diagnosis of short-circuit faults in power transmission lines. The proposed fault detection (FDD) approach is mainly based on principal component analysis (PCA). The proposed fault diagnosis/identification (FAI) approach is mainly based on sliding-window versions of the discrete Fourier transform (DFT) and discrete Hilbert transform (DHT). The main contributions of this article are (a) a fault detection approach based on principal component analysis in the two-dimensional scores space; and (b) a rule-based fault identification approach based on human expert knowledge, combined with a probabilistic decision system, which detects variations in the amplitudes and frequencies of current and voltage signals, using DFT and DHT, respectively. Simulation results of power transmission lines in Portugal are presented in order to show the robust and high performance of the proposed FDD approach for different signal-to-noise ratios. The proposed FDD approach, implemented in Python, that can be executed online or offline, can be used to evaluate the stress to which circuit breakers (CBs) are subjected, providing information to supervision- and condition-based monitoring systems in order to improve predictive and preventive maintenance strategies, and it can be applied to high-/medium-voltage power transmission lines as well as to low-voltage electronic transmission systems.

This paper presents the development of an open-source, low-sized, BGA microcontroller breakout board, that can be used for the development of wearable and cyber-physical prototypes. The board is based on the low power, 8-bit, ATtiny20-CCU Microchip AVR microcontroller. The ATtiny20-CCU can be programmed without bootloader, using the Atmel Tiny Programming Interface (TPI), instead of In-System Programming (ISP). The C code used to program the microcontroller can be written and compiled using the Microchip Studio freeware platform. The ATtiny20-CCU Ultra Fine-pitch Ball Grid Array (UFBGA) packaging technology allows the shrinkage of the conceived Electroless Nickel-Immersion Gold (ENIG) Printed Circuit Board (PCB) to a size of only 15.5 × 13 mm. Its low cost also makes it a viable option for developing many educational electronic projects, especially for Instrumentation and Assistive Technology. The contribution of this paper is mainly the hardware prototype design, the PCB manufacturing, building and test of a very low-sized open source µ-breakout PCB board, for wearable Instrumentation applications, towards the emergent Society/Industry 5.0.

BackgroundThe digital age, with digital sensors, the Internet of Things (IoT), and big data tools, has opened new opportunities for improving the delivery of health care services, with remote monitoring systems playing a crucial role and improving access to patients. The versatility of these systems has been demonstrated during the current COVID-19 pandemic. Health remote monitoring systems (HRMS) present various advantages such as the reduction in patient load at hospitals and health centers. Patients that would most benefit from HRMS are those with chronic diseases, older adults, and patients that experience less severe symptoms recovering from SARS-CoV-2 viral infection. ObjectiveThis paper aimed to perform a systematic review of the literature of HRMS in primary health care (PHC) settings, identifying the current status of the digitalization of health processes, remote data acquisition, and interactions between health care personnel and patients. MethodsA systematic literature review was conducted using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines to identify articles that explored interventions with HRMS in patients with chronic diseases in the PHC setting. ResultsThe literature review yielded 123 publications, 18 of which met the predefined inclusion criteria. The selected articles highlighted that sensors and wearables are already being used in multiple scenarios related to chronic disease management at the PHC level. The studies focused mostly on patients with diabetes (9/26, 35%) and cardiovascular diseases (7/26, 27%). During the evaluation of the implementation of these interventions, the major difficulty that stood out was the integration of information into already existing systems in the PHC infrastructure and in changing working processes of PHC professionals (83%). ConclusionsThe PHC context integrates multidisciplinary teams and patients with often complex, chronic pathologies. Despite the theoretical framework, objective identification of problems, and involvement of stakeholders in the design and implementation processes, these interventions mostly fail to scale up. Despite the inherent limitations of conducting a systematic literature review, the small number of studies in the PHC context is a relevant limitation. This study aimed to demonstrate the importance of matching technological development to the working PHC processes in interventions regarding the use of sensors and wearables for remote monitoring as a source of information for chronic disease management, so that information with clinical value is not lost along the way.

Introduction: Acute bacterial pneumonia is a common and potentially fatal disease where early recognition and treatment are crucial. Increasing medical literature suggests worse outcomes in patients admitted for medical and surgical conditions during the weekend. Little is known about this effect in patients with acute bacterial pneumonia. Objective: The aim of this study was to evaluate the impact of weekend and holiday hospital admission on the outcomes of acute bacterial pneumonia. Material and Methods: Retrospective analysis of adult patients (> 18 years) with acute bacterial pneumonia collected from a tertiary referral center database. Length of stay, total cost, admission to intensive care unit, development of sepsis and organ failure, and mortality were compared between patients admitted on a weekday and patients admitted during a weekend or holiday. Results: We analyzed 53 854 hospital admissions from 42 512 patients (median age 84.0 years, range 18 - 118 years), corresponding to 30 554 admissions during weekdays, 21 222 at weekends and 2078 during public holidays. Weekend and holiday admission was not associated with increased costs, length of stay, intensive care unit admission, development of sepsis, organ failure, and mortality. Conclusion: A weekend/holiday effect in acute bacterial pneumonia was not evident in our series.

Cystoseira is a common brown algal genus widely distributed throughout the Atlantic and Mediterranean regions whose taxonomical assignment of specimens is often hampered by intra- and interspecific morphological variability. In this study, three mitochondrial regions, namely cytochrome oxidase subunit 1 (COI), 23S rDNA (23S), and 23S-tRNAVal intergenic spacer (mt-spacer) were used to analyse the phylogenetic relationships of 22 Cystoseira taxa (n = 93 samples). A total of 135 sequences (48 from COI, 43 from 23S and 44 from mt-spacer) were newly generated and analysed together with Cystoseira sequences (9 COI, 31 23S and 35 mt-spacer) from other authors. Phylogenetic analysis of these three markers identified 3 well-resolved clades and also corroborated the polyphyletic nature of the genus. The resolution of Cystoseira taxa within the three clades improves significantly when the inclusion of specimens of related genera was minimized. COI and mt-spacer markers resolved the phylogeny of some of the Cystoseira taxa, such as the C. baccata, C. foeniculacea and C. usneoides. Furthermore, trends between phylogeny, embryonic development and available chemotaxonomic classifications were identified, showing that phylogenetic, chemical and morphological data should be taken into account to study the evolutionary relationships among the algae currently classified as Cystoseira. The resolution of Cystoseira macroalgae into three well supported clades achieved here is relevant for a more accurate isolation and identification of natural compounds and the implementation of conservation measures for target species.

Introdução: A Doença de Pompe é uma miopatia autossómica recessiva progressiva e incapacitante, devida ao défice da enzima isossómica α-glicosidade-ácida. A sua forma tardia tem uma apresentação heterogénea que mimetiza outras doenças neuromusculares, o que dificulta o diagnóstico. Objectivo: Desenvolver recomendações baseadas em consenso para o diagnóstico da forma tardia da doença de Pompe. Material e Métodos: Revisão bibliográfica e análise de um questionário de opinião aplicado a um grupo de especialistas com experiência no diagnóstico de várias miopatias e doenças de sobrecarga lisossomal. Discussão em reunião de consenso. Recomendações: Doentes com miopatia proximal progressiva, fadiga, cãibras e mialgias devem ser submetidos a uma avaliação complementar com determinação de níveis de creatinina fosfoquinase, electromiograma, espirometria dinâmica e, em casos inconclusivos, biópsia muscular. Nos casos suspeitos ou naqueles em que a biópsia muscular não permita outro diagnóstico deve ser determinada a atividade da enzima lisossómica α-glicosidade-ácida através de teste de gota seca (DBS – dried blood spot). A redução da atividade da enzima lisossómica α-glicosidade-ácida requer a confirmação numa segunda amostra e a sequenciação do gene da enzima lisossómica α-glicosidade-ácida. Palavras-chave: Idade de Início; Consenso; Doença de Armazenamento de Glicogénio tipo II.

We live in an era characterized by Society 4.0 and Industry 4.0 where successive innovations that are more or less disruptive are occurring. Within this context, the modeling and simulation of dynamic supervisory and control systems require dealing with more sophistication and complexity, with effects in terms of development errors and higher costs. One of the most difficult aspects of simulating these systems is the handling of vision sensors. The current tools provide these sensors but in a specific and limited way. This paper describes a six-step approach to sensor virtualization. For testing the approach, a simulation platform based on game engines was developed. As contributions, the platform can simulate dynamic systems, including industrial processes with vision sensors. Furthermore, the proposed virtualization approach allows for the modeling of sensors in a systematic way, reducing the complexity and effort required to simulate this type of system. [ABSTRACT FROM AUTHOR]