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Introduction People during extracorporeal membrane oxygenation (ECMO) as a bridge to lung transplantation find themselves in a high degree of physical and psychological vulnerability, which could cause additional problems for their health status. Therefore, this review aims to identify the interventions that shape critical nursing care to minimize patient vulnerability during ECMO as a bridge to lung transplantation. Method A literature review was performed using CINAHL, MEDLINE, PubMed, Scopus and Web of Science databases with searches conducted in March 2023, with temporal restriction of articles published between 2013 and 2023. After selecting articles involving adults in critical situations on ECMO, their quality was assessed using the critical appraisal tools from the Joanna Briggs Institute. Articles with the pediatric population, reviews, and opinion articles were excluded. A spreadsheet was built for data extraction and a narrative analysis was performed. Results Three articles were included involving 40 participants in total. Interventions that shape critical nursing care to minimize a person's vulnerability are in the physical domain (basic precautions to prevent infection) and in the psychological domain (trusting relationships, consistent and clear communication, physical presence of nurses and family members and the use of advocacy). The Awake ECMO strategy was identified as beneficial for reducing vulnerability. Conclusion By recognizing and identifying the person's vulnerability during ECMO as a bridge to lung transplantation, nurses can implement effective interventions to minimize vulnerability in this population, thus contributing to the person's well-being through personalization and individualization of care. Additionally, the results of this review could be useful for developing tools to assess the degree of vulnerability and for implementing person-centered care measures and policies. However, further research is warranted given the scarcity of literature on these topics.

The rise of robotics and the Internet of Things (IoT) could potentially represent a significant shift towards a more integrated and automated future, where the physical and digital domains may merge. However, the integration of these technologies presents certain challenges, including compatibility issues with existing systems and the need for greater interoperability between different devices. It would seem that the rigidity of traditional robotic designs may inadvertently make these difficulties worse, which in turn highlights the potential benefits of modular solutions. Furthermore, the mastery of new technologies may introduce additional complexity due to the varying approaches taken by robot manufacturers. In order to address these issues, this research proposes a Robot Operating System (ROS2)-based middleware, called the “ROS2-based gateway”, which aims to simplify the integration of robots in different environments. By focusing on the payload layer and enabling external communication, this middleware has the potential to enhance modularity and interoperability, thus accelerating the integration process. It offers users the option of selecting payloads and communication methods via a shell interface, which the middleware then configures, ensuring adaptability. The solution proposed in this article, based on the gateway concept, offers users and programmers the flexibility to specify which payloads they want to activate depending on the task at hand and the high-level protocols they wish to use to interact with the activated payloads. This approach allows for the optimisation of hardware resources (only the necessary payloads are activated), as well as enabling the programmer/user to utilise high-level communication protocols (such as RESTful, Kafka, etc.) to interact with the activated payloads, rather than low-level programming.

Smart cities and information and communications technology is a rapidly growing field in both research and real-world implementation, but it is one that is still new and with many different ideas. Unfortunately, there is less cooperation and knowledge sharing across the field, and research often fails to move into real-world applications, which holds it back from becoming fully realized. This paper aims to provide an overview of the current state of smart cities, its definitions, technologies, and technical dimensions, from architectural design to standards and data handling, and how they are handled in the real world and its impact on society. Additionally, it examines important smart city projects, their applications, and ranking systems. This text aims to forecast the future of the field, its impact, the challenges it faces, and what should be addressed to help it reach its full potential.

Emotion recognition has become increasingly important in the field of Deep Learning (DL) and computer vision due to its broad applicability by using human–computer interaction (HCI) in areas such as psychology, healthcare, and entertainment. In this paper, we conduct a systematic review of facial and pose emotion recognition using DL and computer vision, analyzing and evaluating 77 papers from different sources under Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Our review covers several topics, including the scope and purpose of the studies, the methods employed, and the used datasets. The scope of this work is to conduct a systematic review of facial and pose emotion recognition using DL methods and computer vision. The studies were categorized based on a proposed taxonomy that describes the type of expressions used for emotion detection, the testing environment, the currently relevant DL methods, and the datasets used. The taxonomy of methods in our review includes Convolutional Neural Network (CNN), Faster Region-based Convolutional Neural Network (R-CNN), Vision Transformer (ViT), and “Other NNs”, which are the most commonly used models in the analyzed studies, indicating their trendiness in the field. Hybrid and augmented models are not explicitly categorized within this taxonomy, but they are still important to the field. This review offers an understanding of state-of-the-art computer vision algorithms and datasets for emotion recognition through facial expressions and body poses, allowing researchers to understand its fundamental components and trends.

Defect detection is a key element of quality control in today’s industries, and the process requires the incorporation of automated methods, including image sensors, to detect any potential defects that may occur during the manufacturing process. While there are various methods that can be used for inspecting surfaces, such as those of metal and building materials, there are only a limited number of techniques that are specifically designed to analyze specialized surfaces, such as ceramics, which can potentially reveal distinctive anomalies or characteristics that require a more precise and focused approach. This article describes a study and proposes an extended solution for defect detection on ceramic pieces within an industrial environment, utilizing a computer vision system with deep learning models. The solution includes an image acquisition process and a labeling platform to create training datasets, as well as an image preprocessing technique, to feed a machine learning algorithm based on convolutional neural networks (CNNs) capable of running in real time within a manufacturing environment. The developed solution was implemented and evaluated at a leading Portuguese company that specializes in the manufacturing of tableware and fine stoneware. The collaboration between the research team and the company resulted in the development of an automated and effective system for detecting defects in ceramic pieces, achieving an accuracy of 98.00% and an F1-Score of 97.29%.

Surface defect detection with machine learning has become an important tool in industries and a large field of study for researchers or workers in recent years. It is necessary to have a simplified source of information that helps us to better focus on one type of surface. In this systematic review, we present a classification for surface defect detection based on convolutional neural networks (CNNs) focused on surface types. Findings: Out of 253 records identified, 59 primary studies were eligible. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we analyzed the structures of each study and the concepts related to defects and their types on surfaces. The presented review is mainly focused on finding a classification for the types of surfaces most used in industry (metal, building, ceramic, wood, and special). We delve into the specifics of each surface category, offering illustrative examples of their applications within both industrial and laboratory settings. Furthermore, we propose a new taxonomy of machine learning based on the obtained results and collected information. We summarized the studies and extracted the main characteristics such as type of surface, problem types, timeline, type of network, techniques, and datasets. Among the most relevant results of our analysis, we found that the metallic surface is the most used, as it is the one found in 62.71% of the studies, and the most prevalent problem type is classification, accounting for 49.15% of the total. Furthermore, we observe that transfer learning was employed in 83.05% of the studies, while data augmentation was utilized in 59.32%. Our findings also provide insights into the cameras most frequently employed, along with the strategies adopted to address illumination challenges present in certain articles and the approach to creating datasets for real-world applications. The main results presented in this review allow for a quick and efficient search of information for researchers and professionals interested in improving the results of their defect detection projects. Finally, we analyzed the trends that could open new fields of study for future research in the area of surface defect detection.

Conventional conservation techniques such as drying, salting or freezing do not allow for preserving the original characteristics of seaweeds. The present work aims to study the impact of minimal processing, in particular “Modified Atmosphere Packaging” (MAP), on the physicochemical characteristics and food safety of two seaweed species, “laver” (Porphyra umbilicalis) and “sea-lettuce” (Ulva lactuca), stored at 6 °C for 15 days. Different parameters were evaluated using analytical methods, namely the composition of headspace gases, color, texture, microorganisms, and volatile organic compounds (VOCs). The main findings of this study were that the MAP treatment was able to inhibit the respiration rate of minimally processed seaweeds, also preserving their color and texture. There was a remarkable reduction in the microbial load for P. umbilicalis treated under modified and vacuum atmospheres, and U. lactuca exhibited relatively steady values with no notable differences between the treatments and the control. Therefore, during the 15-day study period, both seaweeds met the requirements for food safety. GC–TOF-MS allowed to conclude that both MAP and vacuum treatments were more efficient in maintaining the odor characteristics of U. lactuca compared to P. umbilicalis with no significant differences throughout the storage days. Metabolic responses to diverse sources of abiotic stress seemed to account for most of the changes observed.

Abstract Background The incidence of Merkel cell carcinoma (MCC), a rare form of skin cancer with a poor prognosis, has increased in Italy in recent decades. Avelumab, an anti-programmed death ligand 1 monoclonal antibody, is approved for the treatment of metastatic MCC (mMCC) based on the results of the phase 2 JAVELIN Merkel 200 trial. The global avelumab expanded access program (EAP) was designed to provide compassionate use of avelumab prior to approval for patients with mMCC who had limited treatment options. We report findings from a subgroup of Italian patients enrolled in the avelumab EAP. Methods Eligible patients had mMCC and progressive disease following ≥ 1 prior line of chemotherapy or were ineligible for chemotherapy or clinical trial participation. Patients received avelumab 10 mg/kg intravenously every 2 weeks. Treating physicians were provided with an initial 3-month supply of avelumab; resupply was permitted if the patient achieved a complete response, partial response, stable disease, or other clinical benefit per physician assessment. Safety and efficacy data for the EAP were reported at the treating physician’s discretion. Results Between April 1, 2016, and September 14, 2018, 109 requests for avelumab were received from Italy, and 102 were approved. All but 1 of the approved patients had received ≥ 1 prior line of therapy. At data cutoff (March 22, 2019), 95 patients had been supplied with avelumab and response data were available for 55 patients. The objective response rate in response-evaluable patients was 29.1%, including 6 patients (10.9%) who achieved a complete response and 10 patients (18.2%) who achieved a partial response; in the total population supplied with avelumab (n = 95), the proportion who had an objective response was 16.8%. The median duration of treatment in responding patients was 9.7 months (range, 3.5–41.7 months). The most frequently reported treatment-related adverse events were infusion-related reaction (single preferred term; n = 3 [3.2%]) and pyrexia (n = 2 [2.1%]). Conclusions Results from Italian patients enrolled in the avelumab EAP are consistent with the findings of the JAVELIN Merkel 200 trial and confirm the efficacy and safety of avelumab treatment in this population.

Breast cancer is the most prevalent cancer in the world and the fifth-leading cause of cancer-related death. Treatment is effective in the early stages. Thus, a need to screen considerable portions of the population is crucial. When the screening procedure uncovers a suspect lesion, a biopsy is performed to assess its potential for malignancy. This procedure is usually performed using real-time Ultrasound (US) imaging. This work proposes a visualization system for US breast biopsy. It consists of an application running on AR glasses that interact with a computer application. The AR glasses track the position of QR codes mounted on an US probe and a biopsy needle. US images are shown in the user’s field of view with enhanced lesion visualization and needle trajectory. To validate the system, latency of the transmission of US images was evaluated. Usability assessment compared our proposed prototype with a traditional approach with different users. It showed that needle alignment was more precise, with 92.67 ± 2.32° in our prototype versus 89.99 ± 37.49° in a traditional system. The users also reached the lesion more accurately. Overall, the proposed solution presents promising results, and the use of AR glasses as a tracking and visualization device exhibited good performance.

Leishmania infantum, the sand fly-transmitted protozoan parasite responsible for leishmaniasis in humans, dogs, and cats, is endemic in the Iberian Peninsula. However, the impact of L. infantum infection on the conservation of the endangered Iberian lynx (Lynx pardinus) is unknown. Herein, we describe for the first time the occurrence of L. infantum infection among a population of reintroduced and wild-born L. pardinus living in the Portuguese Guadiana Valley Park. The presence of infection was addressed by molecular detection of Leishmania kinetoplast DNA (kDNA) in 35 lynxes, with further confirmation of L. infantum species performed by an internally transcribed spacer (ITS)-1 sequencing. Eight blood samples were positive for kDNA, and ITS-1 sequencing confirmed the presence of L. infantum in two of those samples. Exposure to Leishmania was screened in a group of 36 lynxes using an immunofluorescence antibody test (IFAT) and a multi-antigen enzyme-linked immunosorbent assay (ELISA), using SPLA, rK39, and CPX as Leishmania-specific antigens. Four animals presented a positive IFAT at a dilution of 1:40. Eight samples were considered seropositive to all ELISA Leishmania-specific antigens. Agreement between PCR, IFAT, and all ELISA antigens was found for 1 in 27 samples. These results highlight the susceptibility of autochthonous L. pardinus to L. infantum infection. Further investigation is required to assess the impact of L. infantum infection on this wild species conservation.

Cystic artery pseudoaneurysm (CAP) is a rare entity most often resulting from inflammatory conditions (acute cholecystitis or pancreatitis) or iatrogenic trauma (cholecystectomy). We report the case of a 73-year-old female who presented with abdominal pain and gastrointestinal bleeding after an episode of acute cholecystitis and endoscopic retrograde cholangiopancreatography for choledocolithiasis removal. Computed tomography and angiography revealed a CAP measuring 5 cm. A right hepatic artery transcatheter embolization was performed with glue, excluding the pseudoaneurysm. The next day, the patient underwent open cholecystectomy with ligation of the cystic artery. Later, ischemic hepatitis and abscess developed.

During the last two decades, many products, research projects and prototypes were announced with different characteristics and capabilities, all adopting the “smart” qualifier word. If a smartness property could not be defined simply as true or false, defining a suitable range was not an easy task. This issue led to the proposal of some classification models, frameworks and taxonomies for project classifications, but none of them provide a clear and pragmatic smartness scale able to classify smart artifacts and serve as a reference. This paper aims to propose a smartness scale to help research and non-research communities to better quantify and easily understand the features and autonomy of smart artifacts. The proposed smartness scale considers the main function of physical-device components in smart systems. The provided smartness scale is based on a uni-dimensional typology that defines 12 different smartness levels, created based on our definition of “smart artifact” and by following an evolutionary set of capabilities ranging from traceable-only and sensing-capable artifacts to autonomous, adaptable and self-driven artifacts. In order to show the feasibility of the proposed smartness scale, an analytic model was defined and applied to several research- and market-based artifacts tagged as smart in order to extract their smartness levels.

The developmental potential of early embryos is mainly dictated by the quality of the oocyte. Here, we explore the utility of the maternal spindle transfer (MST) technique as a reproductive approach to enhance oocyte developmental competence. Our proof-of-concept experiments show that replacement of the entire cytoplasm of oocytes from a sensitive mouse strain overcomes massive embryo developmental arrest characteristic of non-manipulated oocytes. Genetic analysis confirmed minimal carryover of mtDNA following MST. Resulting mice showed low heteroplasmy levels in multiple organs at adult age, normal histology and fertility. Mice were followed for five generations (F5), revealing that heteroplasmy was reduced in F2 mice and was undetectable in the subsequent generations. This pre-clinical model demonstrates the high efficiency and potential of the MST technique, not only to prevent the transmission of mtDNA mutations, but also as a new potential treatment for patients with certain forms of infertility refractory to current clinical strategies.

Currently, solutions based on the Internet of Things (IoT) concept are increasingly being adopted in several fields, namely, industry, agriculture, and home automation. The costs associated with this type of equipment is reasonably small, as IoT devices usually do not have output peripherals to display information about their status (e.g., a screen or a printer), although they may have informative LEDs, which is sometimes insufficient. For most IoT devices, the price of a minimalist display, to output and display the device’s running status (i.e., what the device is doing), might cost much more than the actual IoT device. Occasionally, it might become necessary to visualize the IoT device output, making it necessary to find solutions to show the hardware output information in real time, without requiring extra equipment, only what the administrator usually has with them. In order to solve the above, a technological solution that allows for the visualization of IoT device information in actual time, using augmented reality and a simple smartphone, was developed and analyzed. In addition, the system created integrates a security layer, at the level of AR, to secure the shown data from unwanted eyes. The results of the tests carried out allowed us to validate the operation of the solution when accessing the information of the IoT devices, verify the operation of the security layer in AR, analyze the interaction between smartphones, the platform, and the devices, and check which AR markers are most optimized for this use case. This work results in a secure augmented reality solution, which can be used with a simple smartphone, to monitor/manage IoT devices in industrial, laboratory or research environments.

The Portuguese population is aging at an increasing rate, which introduces new problems, particularly in rural areas, where the population is small and widely spread throughout the territory. These people, mostly elderly, have low income and are often isolated and socially excluded. This work researches and proposes an affordable Ambient Assisted Living (AAL)-based solution to monitor the activities of elderly individuals, inside their homes, in a pervasive and non-intrusive way, while preserving their privacy. The solution uses a set of low-cost IoT sensor devices, computer vision algorithms and reasoning rules, to acquire data and recognize the activities performed by a subject inside a home. A conceptual architecture and a functional prototype were developed, the prototype being successfully tested in an environment similar to a real case scenario. The system and the underlying concept can be used as a building block for remote and distributed elderly care services, in which the elderly live autonomously in their homes, but have the attention of a caregiver when needed.

Conservation and policy agendas, such as the European Biodiversity strategy, Aichi biodiversity (target 5) and Common Agriculture Policy (CAP), are overlooking the progress made in mountain grassland cover conservation by 2020, which has significant socio-ecological implications to Europe. However, because the existing data near 2020 is scarce, the shifting character of mountain grasslands remains poorly characterized, and even less is known about the conservation outcomes because of different governance regimes and map uncertainty. Our study used Landsat satellite imagery over a transboundary mountain region in the northwestern Iberian Peninsula (Peneda-Gerês) to shed light on these aspects. Supervised classifications with a multiple classifier ensemble approach (MCE) were performed, with post classification comparison of maps established and bias-corrected to identify the trajectory in grassland cover, including protected and unprotected governance regimes. By analysing class-allocation (Shannon entropy), creating 95% confidence intervals for the area estimates, and evaluating the class-allocation thematic accuracy relationship, we characterized uncertainty in the findings. The bias-corrected estimates suggest that the positive progress claimed internationally by 2020 was not achieved. Our null hypothesis to declare a positive progress (at least equality in the proportion of grassland cover of 2019 and 2002) was rejected (X2 = 1972.1, df = 1, p < 0.001). The majority of grassland cover remained stable (67.1 ± 10.1 relative to 2002), but loss (−32.8 ± 7.1% relative to 2002 grasslands cover) overcame gain areas (+11.4 ± 6.6%), indicating net loss as the prevailing pattern over the transboundary study area (−21.4%). This feature prevailed at all extents of analysis (lowlands, −22.9%; mountains, −17.9%; mountains protected, −14.4%; mountains unprotected, −19.7%). The results also evidenced that mountain protected governance regimes experienced a lower decline in grassland extent compared to unprotected. Shannon entropy values were also significantly lower in correctly classified validation sites (z = −5.69, p = 0.0001, n = 708) suggesting a relationship between the quality of pixel assignment and thematic accuracy. We therefore encourage a post-2020 conservation and policy action to safeguard mountain grasslands by enhancing the role of protected governance regimes. To reduce uncertainty, grassland gain mapping requires additional remote sensing research to find the most adequate spatial and temporal data resolution to retrieve this process.

Introduction: Pneumococcal conjugate vaccine was introduced in the private market in Portugal in 2001, reaching over the years a moderately high coverage. In July 2015, it was included in the National Immunisation Program. The aim of this study was to characterize invasive pneumococcal disease in a pediatric hospital before universal use of the vaccine. Material and Methods: Retrospective analysis of medical records of all children with Streptococcus pneumoniae identified by culture and/or molecular biology (available since 2008), in products obtained from sterile sites, from January 1995 to June 2015. We evaluated demographic, clinical and microbiological data. Serotype results are available since 2004. Results: Over those 20 years, 112 invasive pneumococcal disease cases were identified, with a median age of 15 months (1 month - 15 years). The median number of cases /year was 4, the highest between 2001 - 2002 (8/year) and 2007 - 2012 (7 - 11/year). The identification occurred mostly in blood culture (72), cerebrospinal fluid (24), pleural fluid (11) an others (5). The most frequent diagnoses were pneumonia (38%), occult bacteraemia (34%) and meningitis (21%). Over the period under review, there was an increase of pneumonia and slight increase of OB, with meningitis cases remaining relatively unchanged. Discussion: In the last two decades, there was no reduction in the number of cases of invasive pneumococcal disease. There was an increase in isolates from pneumonia and occult bacteraemia that might be due to the introduction of molecular biological methods for Streptococcus pneumoniae detection. Vaccine serotypes were predominant. Conclusion: This retrospective analysis before universal vaccination will contribute to evaluate the impact of vaccination in the Portuguese pediatric population.

O objetivo deste estudo foi descrever a perceção da qualidade de vida em indivíduos acima dos 70 anos, tendo em conta a participação em programas de exercício físico em contexto comunitário e idosos institucionalizados. Para o efeito foi realizado um estudo transversal onde foram avaliados 250 idosos (74.8% do sexo feminino) segundo 4 contextos distintos. Grupo 1 (n=148) corresponde aos idosos comunitários a praticar exercício (frequência: 2 sessões/semana; duração: 45 minutos); No grupo 2 (n=41), incluem-se os idosos que pertencem à comunidade e não fazem exercício; No grupo 3 (centro de dia; n=37) e grupo 4 (institucionalizados; n= 24), correspondem aos idosos institucionalizados que não praticam exercício. Para avaliar a perceção da qualidade de vida utilizou-se o questionário SF36. Utilizou-se a regressão linear múltipla para estimar a tendência dos scores por grupo de avaliação. Nos domínios da Função Física, Saúde Mental e Vitalidade, após ajuste para a idade, observou-se uma tendência significativa (p para a tendência

The world population growth is increasing the demand for food production. Furthermore, the reduction of the workforce in rural areas and the increase in production costs are challenges for food production nowadays. Smart farming is a farm management concept that may use Internet of Things (IoT) to overcome the current challenges of food production. This work uses the preferred reporting items for systematic reviews (PRISMA) methodology to systematically review the existing literature on smart farming with IoT. The review aims to identify the main devices, platforms, network protocols, processing data technologies and the applicability of smart farming with IoT to agriculture. The review shows an evolution in the way data is processed in recent years. Traditional approaches mostly used data in a reactive manner. In more recent approaches, however, new technological developments allowed the use of data to prevent crop problems and to improve the accuracy of crop diagnosis.

Wireless body area networks (WBANs) are a fascinating research field offering wearable and implantable sensor technology [...]

A fibrodisplasia óssea é uma patologia congénita rara com predileção pelos ossos craniofaciais, envolvendo frequentemente os seios perinasais, órbita e base do crânio. Os autores apresentam 2 casos de fibrodisplasia óssea monostótica craniofacial e realizam uma breve revisão da literatura sobre o tema. O primeiro trata-se de um caso de fibrodisplasia óssea do frontal, num homem de 20 anos, e o segundo de um caso de fibrodisplasia óssea do esfenoide, num homem de 65 anos. O primeiro caso, dada a idade jovem, crescimento e repercussão estética da lesão, foi submetido a cirurgia, não evidenciando sinais de recidiva após um ano de seguimento. O segundo caso, tratou-se de um achado imagiológico sem sinais de crescimento, num homem mais velho e assintomático, pelo que se optou pelo tratamento conservador e vigilância. Ambos foram orientados de forma multidisciplinar e ilustram a diversidade de apresentação, orientação e evolução que a mesma patologia pode assumir.

This study explores: (a) previous conceptions of parents/professionals about the quality of life of youth with special needs, and their fit with the Schalock and Verdugo’s core dimensions; (b) possible differences in its pattern throughout development. The participants responded to a collective, semi-structured questionnaire that provided a sort of characteristics or aspects related to the quality of life (from the participant standpoint) of young persons with special education needs. The obtained characteristics were content analyzed, and developmental phases were compared. The results were discussed according to the existing literature, as well as some implications to research, training and practice.

Ambient Intelligence promises to transform current spaces into electronic environments that are responsive, assistive and sensitive to human presence. Those electronic environments will be fully populated with dozens, hundreds or even thousands of connected devices that share information and thus become intelligent. That massive wave of electronic devices will also invade everyday objects, turning them into smart entities, keeping their native features and characteristics while seamlessly promoting them to a new class of thinking and reasoning everyday objects. Although there are strong expectations that most of the users’ needs can be fulfilled without their intervention, there are still situations where interaction is required. This paper presents work being done in the field of human-computer interaction, focusing on smart home environments, while being a part of a larger project called Aging Inside a Smart Home. This initiative arose as a way to deal with a large scourge of our country, where lots of elderly persons live alone in their homes, often with limited or no physical mobility. The project relies on the mobile agent computing paradigm in order to create a Virtual Butler that provides the interface between the elderly and the smart home infrastructure. The Virtual Butler is receptive to user questions, answering them according to the context and knowledge of the AISH. It is also capable of interacting with the user whenever it senses that something has gone wrong, notifying next of kin and/or medical services, etc. The Virtual Butler is aware of the user location and moves to the computing device which is closest to the user, in order to be always present. Its avatar can also run in handheld devices keeping its main functionality in order to track user when s/he goes out. According to the evaluation carried out, the Virtual Butler is assessed as a very interesting and loved digital friend, filling the gap between the user and the smart home. The evaluation also showed that the Virtual Butler concept can be easily ported to other types of possible smart and assistive environments like airports, hospitals, shopping malls, offices, etc.

A body area network (BAN) comprises a set of devices that sense their surroundings, activate and communicate with each other when an event is detected in its environment. Although BAN technology was developed more than 20 years ago, in recent years, its popularity has greatly increased. The reason is the availability of smaller and more powerful devices, more efficient communication protocols and improved duration of portable batteries. BANs are applied in many fields, healthcare being one of the most important through gathering information about patients and their surroundings. A continuous stream of information may help physicians with making well-informed decisions about a patient’s treatment. Based on recent literature, the authors review BAN architectures, network topologies, energy sources, sensor types, applications, as well as their main challenges. In addition, the paper focuses on the principal requirements of safety, security, and sustainability. In addition, future research and improvements are discussed.

The technological advances in medical sensors, low-power microelectronics and miniaturization, wireless communications and networks have enabled the appearance of a new generation of wireless sensor networks: the so-called wireless body area networks (WBAN). These networks can be used for continuous monitoring of vital parameters, movement, and the surrounding environment. The data gathered by these networks contributes to improve users’ quality of life and allows the creation of a knowledge database by using learning techniques, useful to infer abnormal behaviour. In this paper we present a wireless body area network architecture to recognize human movement, identify human postures and detect harmful activities in order to prevent risk situations. The WBAN was created using tiny, cheap and low-power nodes with inertial and physiological sensors, strategically placed on the human body. Doing so, in an as ubiquitous as possible way, ensures that its impact on the users’ daily actions is minimum. The information collected by these sensors is transmitted to a central server capable of analysing and processing their data. The proposed system creates movement profiles based on the data sent by the WBAN’s nodes, and is able to detect in real time any abnormal movement and allows for a monitored rehabilitation of the user.

Wireless Body Area Networks (WBANs) supporting healthcare applications are in early development stage but offer valuable contributions at monitoring, diagnostic, or therapeutic levels. They cover real-time medical information gathering obtained from different sensors with secure data communication and low power consumption. As a consequence of the increasing interest in the application of this type of networks, several articles dealing with different aspects of such systems have been published recently. In this paper, we compile and compare technologies and protocols published in the most recent researches, seeking WBAN issues for medical monitoring purposes to select the most useful solutions for this area of networking. The most important features under consideration in our analysis include wireless communication protocols, frequency bands, data bandwidth, transmission distance, encryption, authentication methods, power consumption, and mobility. Our study demonstrates that some characteristics of surveyed protocols are very useful to medical appliances and patients in a WBAN domain.

INDUSTRIAL RESTRUCTURING IN PORTUGAL IN THE EIGHTIES - This paper analyses the territorial changes un manufacturing activity in mainland Portugal during the eighties. A shift-share analysis was applied to regional employment. Its results are presented and the main reasons that explain regional differences are discussed

WORK PROPOSAL TO MAKE TWO CLASSIFICATIONS OF ECONOMIC ACTIVITIES COMPATIBLE - In this work the new national classification of economic activity is compared with the previous one, in order to use both of them. When the new and the former classification are compared conceptual and structural differences appear, mainly among the economic activities that have emerged in the last two decades. The new classification is more detailed, specially in the trade, reflecting an adaptation to the new productive system

In human systemic lupus erythematosus (SLE), diverse autoantibodies accumulate over years before disease manifestation. Unaffected relatives of SLE patients frequently share a sustained production of autoantibodies with indiscriminable specificity, usually without ever acquiring the disease. We studied relations of IgG autoantibody profiles and peripheral blood activated regulatory T-cells (aTregs), represented by CD4(+)CD25(bright) T-cells that were regularly 70-90% Foxp3(+). We found consistent positive correlations of broad-range as well as specific SLE-associated IgG with aTreg frequencies within unaffected relatives, but not patients or unrelated controls. Our interpretation: unaffected relatives with shared genetic factors compensated pathogenic effects by aTregs engaged in parallel with the individual autoantibody production. To study this further, we applied a novel analytic approach named coreferentiality that tests the indirect relatedness of parameters in respect to multivariate phenotype data. Results show that independently of their direct correlation, aTreg frequencies and specific SLE-associated IgG were likely functionally related in unaffected relatives: they significantly parallelled each other in their relations to broad-range immunoblot autoantibody profiles. In unaffected relatives, we also found coreferential effects of genetic variation in the loci encoding IL-2 and CD25. A model of CD25 functional genetic effects constructed by coreferentiality maximization suggests that IL-2-CD25 interaction, likely stimulating aTregs in unaffected relatives, had an opposed effect in SLE patients, presumably triggering primarily T-effector cells in this group. Coreferentiality modeling as we do it here could also be useful in other contexts, particularly to explore combined functional genetic effects.

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In the past, wireless sensor networks emerged and so did some state-of-the-art applications that ran above them. Most of those applications followed the centralized model and were mainly focused on environmental data gathering, where sensor nodes sensed data from the environment to be sent to an external data server for later processing. Further research took wireless sensor networks to new application areas and, today, this technology gained the ubiquitous status. However, the use of wireless sensor networks is still reserved to experts, mainly due to the huge gap between user applications and the network. This fact has led us to successfully develop a new software stack, capable of running in any sensor node even in the most resource-constrained ones. The new software stack offers a truly service-oriented approach to design and implement applications and follows a widely accepted programming language and programming paradigm.

Artigo sobre o Teatro Avenida, em Lisboa.