Enhancing clinical management of bariatric surgery using business intelligence

There is a problem with collecting information in healthcare services as it is scattered among various sources. This leads to potential impact on patient care focus. To address this issue, a Business Intelligence platform was developed and implemented at the Centre for Surgical Treatment of Obesity at Centro Hospitalar do Tâmega e Sousa. The platform developed enables knowledge extraction and aids healthcare professionals to easily access helpful information and perform better decisions, specifically in regards to the growing global concern of obesity and the increasing prevalence of bariatric surgery.This work has been supported by FCT—Fundac¸ao para a Ci ˜ encia e Tecnologia within the R&D Units Project ˆ Scope: UIDB/00319/202

Conflito adolescente-progenitores e autonomia : Abordagem psicológica

Inexistent

Testing a fault tolerant mixed-signal design under TID and heavy ions

This work presents results of three distinctradiation tests performed upon a fault tolerant data acqui-sition system comprising a design diversity redundancytechnique. The first and second experiments are Total Ion-izing Dose (TID) essays, comprising gamma and X-rayirradiations. The last experiment considers single eventeffects, in which two heavy ion irradiation campaignsare carried out. The case study system comprises threeanalog-to-digital converters and two software-based vot-ers, besides additional software and hardware resourcesused for controlling, monitoring and memory manage-ment. The applied Diversity Triple Modular Redundancy(DTMR) technique, comprises different levels of diversity(temporal and architectural). The circuit was designed ina programmable System-on-Chip (PSoC), fabricated in a130nm CMOS technology process. Results show that thetechnique may increase the lifetime of the system underTID if comparing with a non-redundant implementation.Considering the heavy ions experiments the system wasproved effective to tolerate 100% of the observed errorsoriginated in the converters, while errors in the process-ing unit present a higher criticality. Critical errors occur-ring in one of the voters were also observed. A secondheavy ion campaign was then carried out to investigatethe voters reliability, comparing the the dynamic cross sec-tion of three different software-based voter schemes im-plemented in the considered PSoC

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure < 100 mmHg (n = 1127), estimated glomerular filtration rate < 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

One-Step synthesis of PtFe/CeO2 catalyst for the Co-Preferential oxidation reaction at low temperatures

Active Pt-based catalysts at low temperature towards the preferential oxidation of carbon monoxide in hydrogen-rich stream reaction (CO-PROX) are of great importance for H-2-fueled fuel cells, but still remain a challenge. Herein, we propose a simple approach to synthesize a highly active Pt20Fe/CeO2 catalyst employing the borohydride reduction process. Transmission electronic microscopy revealed monodispersed 2.8 nm-Pt nanoparticles on CeO2, and the role of Fe species on the activity is discussed. The excellent CO conversion of 99.6% and CO2 selectivity of 92.3% carried out at ambient temperature meet the CO-PROX requirements for an adequate supply of hydrogen in fuel cell device. (C) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.Peer reviewe

Functional redundancy of Amazonian dung beetles confers community-level resistance to primary forest disturbance

Tropical forest biodiversity is being threatened by human activities, and species losses during forest disturbance can compromise important ecosystem functions and services. We assessed how species losses due to tropical forest disturbance affect community functional structure, using Amazonian dung beetles as a model group. We collected empirical data from 106 forest transects and used simulated extinction scenarios to determine how species loss influences community structure at regional and local scales. Although functional and taxonomic community metrics were largely unaffected by primary forest disturbance, they differed markedly between primary and secondary forests. However, our extinction scenarios demonstrated scale-dependence of species losses, whereby functional structure only eroded with species extinction at the local scale. Hence, we extend the spatial insurance hypothesis by demonstrating that landscape-scale functional redundancy offsets the impact of local species losses and confers community-level resistance to primary forest disturbance