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The widespread adoption of digital technologies in educational systems has been globally reflecting a shift in pedagogic content delivery that seems to fit modern generations of students while tackling relevant challenges faced by the current scholar context, e.g., progress traceability, pedagogic content fair access and intuitive visual representativeness, mobility issue mitigation, and sustainability in crisis situations. Among these technologies, augmented reality (AR) emerges as a particularly promising approach, allowing the visualization of computer-generated interactive data on top of real-world elements, thus enhancing comprehension and intuition regarding educational content, often in mobile settings. While the application of AR to education has been widely addressed, issues related to performance interaction and cognitive performance are commonly addressed, with lesser attention paid to the limitations associated with setup complexity, mostly related to experiences configurating tools, or contextual range, i.e., technical/scientific domain targeting versatility. Therefore, this paper introduces ARPocketLab, a digital, mobile, flexible, and scalable solution designed for the dynamic needs of modern tutorship. With a dual-interface system, it allows both educators and students to interactively design and engage with AR content directly tied to educational outcomes. Moreover, ARPocketLab’s design, aimed at handheld operationalization using a minimal set of physical resources, is particularly relevant in environments where educational materials are scarce or in situations where remote learning becomes necessary. Its versatility stems from the fact that it only requires a marker or a surface (e.g., a table) to function at full capacity. To evaluate the solution, tests were conducted with 8th-grade Portuguese students within the context of Physics and Chemistry subject. Results demonstrate the application’s effectiveness in providing didactic assistance, with positive feedback not only in terms of usability but also regarding learning performance. The participants also reported openness for the adoption of AR in pedagogic contexts.

Manual counting and packaging processes often involve repetitive, error-prone tasks. Specifically, packaging wooden handles, utilized in gardening tools and cutlery, typically relies on labor-intensive methods with dimensions varying in diameter, length and mass. These variations complicate packaging, requiring precise counting and diverse handling solutions. This article introduces an automated counting structure tailored for a wide array of wooden handles manufactured by a company in northern Portugal. Employing standardized mechanical design methodologies, we delineate crucial stages encompassing the design, development, implementation and testing of this specialized counting equipment. The machine has been partially integrated into the management system of the company, taking into account future global integration according to the Industry 4.0 concept.

Abstract Background Necrotizing soft tissue infections are associated with high morbidity and mortality, even when the correct treatment is initiated. The diagnosis of these conditions is hard and the most sensitive methods are time-consuming, expensive and not readily available. Point-of-care ultrasound can complement clinical evaluation to increase the diagnostic accuracy. Case presentation We bring a case of a woman, without comorbidities, who presented to the emergency department with signs of soft tissue infection. Bedside ultrasound showed subcutaneous tissue thickening, with fluid accumulation, and subcutaneous gas in the affected area. Based on the clinical suspicion and the ultrasound findings, the patient underwent prompt medical treatment and surgical debridement. Conclusions This case shows the utility of bedside ultrasound for the decision-making process in a disease where an early diagnosis is important. This information should always be used together with the clinical judgement, as it has a relative low sensitivity.

Abstract Background Extracorporeal shock wave lithotripsy is widely used to treat symptomatic nephrolithiasis. Complications of this procedure can occur and point-of-care ultrasound can help to diagnose and manage some of these cases. Case presentation A 61-year-old man was admitted to the hospital with intense right lumbar pain 24 h after being submitted to a extracorporeal shock wave lithotripsy. Bedside ultrasound showed a hyperechoic subcapsular lesion along the right kidney. This finding, along with the clinical examination, suggested the diagnosis of subcapsular renal hematoma. The patient was managed conservatively with clinical and ultrasound reassessments. Conclusions This case shows the use of bedside ultrasound to diagnose a subcapsular renal hematoma as a complication of extracorporeal shock wave lithotripsy. However, the sensitivity is low and other image methods can be necessary to make the diagnosis.

The increasing pervasiveness of the Internet of Things is resulting in a steady increase of cyberattacks in all of its facets. One of the most predominant attack vectors is related to its identity management, as it grants the ability to impersonate and circumvent current trust mechanisms. Given that identity is paramount to every security mechanism, such as authentication and access control, any vulnerable identity management mechanism undermines any attempt to build secure systems. While digital certificates are one of the most prevalent ways to establish identity and perform authentication, their provision at scale remains open. This provisioning process is usually an arduous task that encompasses device configuration, including identity and key provisioning. Human configuration errors are often the source of many security and privacy issues, so this task should be semi-autonomous to minimize erroneous configurations during this process. In this paper, we propose an identity management (IdM) and authentication method called YubiAuthIoT. The overall provisioning has an average runtime of 1137.8 ms ±65.11+δ. We integrate this method with the FIWARE platform, as a way to provision and authenticate IoT devices.

The growing demand for everyday data insights drives the pursuit of more sophisticated infrastructures and artificial intelligence algorithms. When combined with the growing number of interconnected devices, this originates concerns about scalability and privacy. The main problem is that devices can detect the environment and generate large volumes of possibly identifiable data. Public cloud-based technologies have been proposed as a solution, due to their high availability and low entry costs. However, there are growing concerns regarding data privacy, especially with the introduction of the new General Data Protection Regulation, due to the inherent lack of control caused by using off-premise computational resources on which public cloud belongs. Users have no control over the data uploaded to such services as the cloud, which increases the uncontrolled distribution of information to third parties. This work aims to provide a modular approach that uses cloud-of-clouds to store persistent data and reduce upfront costs while allowing information to remain private and under users’ control. In addition to storage, this work also extends focus on usability modules that enable data sharing. Any user can securely share and analyze/compute the uploaded data using private computing without revealing private data. This private computation can be training machine learning (ML) models. To achieve this, we use a combination of state-of-the-art technologies, such as MultiParty Computation (MPC) and K-anonymization to produce a complete system with intrinsic privacy properties.

Virtual models' production is of high pertinence in research and business fields such as architecture, archeology, or video games, whose requirements might range between expeditious virtual building generation for extensively populating computer-based synthesized environments and hypothesis testing through digital reconstructions. There are some known approaches to achieve the production/reconstruction of virtual models, namely digital settlements and buildings. Manual modeling requires highly-skilled manpower and a considerable amount of time to achieve the desired digital contents, in a process composed by many stages that are typically repeated over time. Both image-based and range scanning approaches are more suitable for digital preservation of well-conserved structures. However, they usually require trained human resources to prepare field operations and manipulate expensive equipment (e.g., 3D scanners) and advanced software tools (e.g., photogrammetric applications). To tackle the issues presented by previous approaches, a class of cost-effective, efficient, and scarce-data-tolerant techniques/methods, known as procedural modeling, has been developed aiming at the semi- or fully-automatic production of virtual environments composed of hollow buildings exclusively represented by outer façades or traversable buildings with interiors, either for expeditious generation or reconstruction. Despite the many achievements of the existing procedural modeling approaches, the production of virtual buildings with both interiors and exteriors composed by non-rectangular shapes (convex or concave n-gons) at the floor-plan level is still seldomly addressed. Therefore, a methodology (and respective system) capable of semi-automatically producing ontology-based traversable buildings composed of arbitrarily-shaped floor-plans has been proposed and continuously developed, and is under analysis in this paper, along with its contributions towards the accomplishment of other virtual reality (VR) and augmented reality (AR) projects/works oriented to digital applications for cultural heritage. Recent roof production-related enhancements resorting to the well-established straight skeleton approach are also addressed, as well as forthcoming challenges. The aim is to consolidate this procedural modeling methodology as a valuable computer graphics work and discuss its future~directions.

No período compreendido entre janeiro de 1996 e dezembro de 1998, administramos derivados da artemisinina em 108 crianças com malária por Plasmodium falciparum, para avaliar a resposta clínica e terapêutica. Foram incluídas apenas crianças com clínica de malária moderada ou grave. No Grupo I, incluímos 62 pacientes e administramos artesunate por via endovenosa. Clinicamente, 50,8% tinham malária moderada e 49,2% malária grave; a parasitemia foi baixa em 53,2%, média em 22,6% e alta em 24,2%; no D2 a parasitemia estava negativa em 58,1%. No Grupo II,incluímos 46 pacientes que receberam artemeter (Paluter®) intramuscular. Clinicamente, 67,4% apresentavam malária moderada e 32,6% malária grave; a parasitemia foi baixa em 52,2%, média em 36,2% e alta em 15,2%; em D2, 56,5% apresentaram negativação da parasitemia. Nos dois grupos, a melhora clínica e evolução da parasitemia não mostraram diferença estatística; no D7 havia clareada a parasitemia em todos os pacientes. Para evitar recrudescência usamos mefloquina ou clindamicina.