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Background: The benefits of physical activity and adequate sleep are well documented, and their importance strengthens with the increasing prevalence of chronic diseases and multimorbidity (MM). Interventions to promote physical activity and sleep that use commercial activity trackers may be useful non-pharmacological approaches to managing individual health; however, limited evidence exists on their use to improve physical activity in elderly patients with MM. Methods: This study aims to measure the effects of behavioral change techniques (BCTs) delivered by a wearable device on physical activity (PA) and quality of sleep (QS) in elderly patients with MM. We designed an open-label randomized controlled trial with participants recruited through primary care and a specialist outpatient clinic. Participants must be more than 65 years old, have MM, and have access to smartphones. All eligible participants will receive PA promotion content and will be randomly assigned to wear a smartwatch. The primary outcome will be the participants' PA measurement at six months using the IPAQ-SF. Secondary outcomes will include changes in the participants' frailty status, biometric measurements, quality of life, and biopsychosocial assessments. A sample size of 40 participants per arm was calculated to detect group differences, with 50 participants recruited and randomized into each arm. Discussion: This study aims to contribute to a better understanding of PA patterns and the impact of wearable-based PA interventions in patients with MM. In addition, we aim to contribute to more knowledge about the relationship between PA patterns, Patient Reported Outcomes Measures (PROMs), and healthcare resource utilization in patients with MM. To achieve this, the study will leverage a locally developed PROMs registry and assess data from participants' medical records, in order to understand the added impact of wearable data and medical information data on predicting PROMs and unplanned hospital admissions. Trial registration: Awaiting number assignment on ClinialTrials.gov

In recent years, most hospitals have implemented Electronic Health Records to manage and integrate a wide range of medical information, including diagnostics, medication admission and laboratory test results. Certain laboratory variables may serve as indicators of a patient’s clinical deterioration, making laboratory data a valuable tool for identifying high-risk patients. This work introduces a framework for predicting imminent health outcomes (IHO) of multimorbidity patients using laboratory test data. Our cohort includes 322,316 multimorbidity patients that performed laboratory tests in a large teaching hospital between January 2007 and August 2021. Two Imminent Health Outcomes predictive tools were developed. The first considers all patients in the dataset. The second was developed using a subset of patients with Heart Failure (HF) as the main comorbidity (5% of the entire dataset), considering that HF is a highly prevalent syndrome in multimorbidity patients. This predictive model achieved a reasonable predictive performance (AUROC= 0.718, 95% CI 0.708-0.756, andAUPRC= 0.663, 95% CI 0.630-0.701). C-reactive protein and NT-proBNP are the lab tests that most positively contribute to the prediction of IHO. The IHO predictive tool has the potential to help the medical team identify patients at high-risk of an imminent adverse event, highlighting the laboratory variables that are most contributing to the deterioration of the patient.

Mixed reality is expanding in the industrial market and several companies in various fields are adapting this set of technologies for various purposes, such as optimizing processes, improving the programming tasks and promoting the interactivity of their products with the users, or even improving teaching or training. Robotics is another area that can benefit from these recent technologies. In fact, most of the current and futuristic robotic applications, namely, the areas related to advanced manufacturing tasks (e.g. additive-manufacturing, collaborative robotics, etc.), require new technics to actually perceive the result of several actions, including programming tasks, anticipate trajectories, visualize the motion and related information, interface with programmers and users and several other human–machine interfaces. Consequently, this paper aims to explain a new concept of human–machine interfaces aiming to improve the interaction between advanced users and industrial robotic work cells.,The presented concept uses two different applications (apps) developed to explore the advanced features of the Microsoft HoloLens device. The objectives of the project reported in this paper are to optimize robot paths, just by allowing the advanced user to adjust the selected path through the mixed reality environment, and create new paths, just by allowing the advanced user to insert points in the mixed reality environment, correct them as needed, connect them using a certain type of motion, parametrize them (in terms of velocity, motion precision, etc.) and command them to the robot controller.,The solutions demonstrated in this paper show how mixed reality can be used to allow users, with limited programming experience, to fully use the robotics fields. They also show clearly that the integration of the mixed reality technology in the current robot systems will be a turning point in reducing the complexity for end-users.,There are two challenges in the developed applications. The first relates to the robot tool identification, which is very sensitive to lighting conditions or to very complex robot tools. This can result in positioning errors when the software shows the path in the mixed reality scene. The paper presents solutions to overcome this problem. Another unattended challenge is associated with handling the robot singularities when adjusting or creating new paths. Ongoing work is concentrated in creating mechanisms that prevent the end-user to create paths that contain unreachable points or paths that are not feasible because of bad motion parameters.,This paper demonstrates the utilization of mixed reality device to improve the tasks of programming and commanding manufacturing work cells based on industrial robots [see video in (Pires et al., 2018)]. As the presented devices and robot cells are the basis for Industry 4.0 objectives, this demonstration has a vast field of application in the near future, positively influencing the way complex applications, that require much close cooperation between humans and machines, are thought, planned and built. The paper presents two different applications fully ready to use in industrial environments. These applications are scientific experiments designed to demonstrate the principles and technologies of mixed reality applied to industrial robotics, namely, for improving the programming task.,Although the HoloLens device opens outstanding new areas for robot command and programming, it is still expensive and somehow heavy for everyday use. Consequently, this opens an opportunity window to combine these devices with other mobile devices, such as tablets and phones, building applications that take advantage of their combined features.,The paper presents two different applications fully ready to use in industrial environments. These applications are scientific experiments designed to demonstrate the principles and technologies of mixed reality applied to industrial robotics, namely, for improving the programming task. The first application is about path visualization, i.e. enables the user to visualize, in a mixed reality environment, any path preplanned for the robot cell. With this feature, the advanced user can follow the robot path, identify problems, associate any difficulty in the final product with a particular issue in the robot paths, anticipate execution problems with impact on the final product quality, etc. This is particularly important for not only advanced applications, but also for cases where the robot path results from a CAD package (in an offline fashion). The second application consists of a graphical path manipulation procedure that allows the advanced user to create and optimize a robot path. Just by exploring this feature, the end-user can adjust any path obtained from any programming method, using the mixed reality approach to guide (visually) the path manipulation procedure. It can also create a completely new path using a process of graphical insertion of point positions and paths into the mixed reality scene. The ideas and implementations of the paper are original and there is no other example in the literature applied to industrial robot programming.

Faster spread of epidemics has turned local concerns into global crises; antimicrobial resistance (AMR) is being considered a major threat to public health in the twenty-first century. Antibiotic misuse plays a great role in accelerated AMR; thus, understanding and discussing consumption patterns has been a trend topic over the past years. Developing countries, such as Brazil, have high growth rates in antibiotic consumption, potentially impacting global environmental safety. This study presents the compiled information from the Brazilian Health Regulatory Agency (ANVISA) on antibiotic dispensation across the country and maps the consumption trends between the years of 2013 and 2016. The most consumed substances were beta-lactams (amoxicillin and cephalexin) and macrolides (azithromycin). National relative growth consumption in the mentioned period was 18%. At the local level, growth of consumption ranged from 4 to 85%, with rampage growth concentrated in the North and Northeast regions. Brazilian laws, such as restriction of over-the-counter sales and mandatory report on dispensation, seem to have little effect on the national antibiotic consumption growth. This phenomenon growth is still elevated if compared with developed countries, demonstrating the need for further surveillance as well as coordinated efforts aiming at antibiotic use and AMR prevention.

Sulfamethoxazole (SMX) has been commonly detected in wastewater treatment plant (WWTP) effluents. SMX and other antibiotics can be considered as environmental contaminants of emerging concern. Due to their toxicity effects and their potential for the development of bacterial resistance their presence in aquatic compartment becomes a threat to human health. This study evaluated the bioremediation of SMX in WWTP effluents using a tertiary treatment composed by microalgae-bacteria consortium under low intensity artificial LED illumination, and also the assessment of sulfonamide resistance gene (sul1). The removal of SMX from WWTP effluents were 54.34 ± 2.35%, in which the microalgae-bacteria consortium improves the removal performance of SMX. The main process of SMX removal can be attributed to the symbiotic biodegradation by bacteria due to the increase of oxygen released by the microalgae photosynthetic process. Therefore, the microalgae-bacteria consortium used in this study, demonstrated to be a promising alternative for bioremediation of SMX, with potential for removal others contaminants from wastewater effluent. However, the residual SMX and the relative abundance of antibiotics resistance genes (ARG) found in this study suggest that SMX contributes to selective pressure for ARG maintenance and proliferation in WWTP effluent. Thus, further studies to removal ARG from WWTP effluent are needed.

Illegal fishing is a critical activity that affects a wide range of species, leading to a decline in total abundance and the overexploitation of target and non-target species. In Portugal, despite fishing for eel juveniles not being allowed, a substantial amount of illegal fishing takes place during the migratory season (October–March). The aim of this study was to investigate the effects of glass eel fishing in the Mondego estuary on target and non-target species. Samples were collected between November 2011 and March 2013 during the autumn and winter (dry and regular respectively with regard to hydrological characteristics) in 2 years. No differences in glass eel catches were observed between fishing seasons; however, a higher number of non-target species was observed in 2012–13 (regular year). There was higher species diversity in the regular year, as well as the highest number of individuals. Higher catches of the most abundant species were also observed in the regular year, compared with the dry year, suggesting that the magnitude of the effect of these illegal practices is related to hydrological cycles. Despite the low replication (2 years), the present study shows that non-selective practices have considerable effects on the species captured, as well as on the functioning of the estuarine ecosystem.

Nitrogen is the most extracted element by rice crop. Although it can exceed 100kg ha -1 , there is not always a response for its application. This study was carried out in field conditions, in a Dark Red Latosol, loamy texture. A center-pivot system applying water was used according to the necessity of the crop. Two rice cultivars: Carajas and IAC – 202, 4 doses of N (urea) (0, 40, 80 and 160kg ha -1 of N) at sidedressing in two periods (30 and/or 50 days after plant emergency) were used. A fixed dose of 20kg ha -1 of N was applied at sowing, and a control treatment did not receive nitrogen application. The higher yield was reached with 20kg ha -1 N at sowing and 40kg ha -1 N at 30 and 50 days after plant germination

were decided by residents. The most diagnosed infections were urinary tract infection (UTI) (17.7%), community acquired pneumonia (CAP) (16.3%) and tonsillitis (11.5%). Antibiotics were prescribed in 6.2% of noninfectious diagnoses. Monotherapy prescriptions accounted for 81.3% of the cases: 41.7% of penicillins and 21.6% of quinolones. For UTI, the most frequently prescribed antibiotics were quinolones (37.5%), sulfonamides (22.2%) and penicillins (20.8%); regarding CAP, quinolones (28.1%) and penicillins (21.9%) were also the preferred options. For tonsillitis, prescribers chose mainly penicillins (76.1%) and macrolides (10.9%). Combined antibiotherapy represented 14.4% of the prescriptions and it was the option in almost half (42.6%) of CAP prescriptions: the most frequent association was penicillin/ cephalosporin and macrolide (23.5%). Most patients were discharged; however, 26.6% were admitted to internal medicine wards, 70.3% of them because of lower respiratory tract infections. The antibiotherapy prescribed at the EDwasmaintained in 80.2% until the discharge. There were 51.3% of appropriate prescriptions: 69.4% for UTI, 58.7% for tonsillitis and 45.3% for CAP. Conclusions: We concluded that almost half of the antibiotic prescriptions at the ED were inappropriate for the established diagnosis, according to the available guidelines. However, ED misdiagnosis was not possible to exclude. In patients admitted to the internal medicine ward, the nondescalation of the large spectrum antibiotherapy prescribed at the ED was an additional example of discordance between daily practices and national recommendations. We also unraveled some of the predictive factors for antibiotic prescription appropriateness. Improving appropriate antibiotic therapy at the emergency department reveals that it is an essential step towards healthcare quality.