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Physical activity following pulmonary embolism and clinical correlates in selected patients: a cross-sectional study
Full text linkBackground: There is limited knowledge regarding physical activity and clinical correlates among people who have suffered a pulmonary embolism (PE).
Objectives: To assess physical activity levels after PE and potential clinical correlates.
Methods: One hundred forty-five individuals free of major comorbidities were recruited at a mean of 23 months (range, 6-72) after PE diagnosis. Physical activity was assessed by steps/day on the Sensewear monitor for 7 consecutive days, exercise capacity with the incremental shuttle walk test, and cardiac function with left ventricular ejection fraction (LVEF). The association between physical activity and other variables was analyzed by a mixed-effects model.
Results: Participants achieved a mean of 6494 (SD, 3294; range, 1147-18.486) steps/day. The mixed-effects model showed that physical activity was significantly associated with exercise capacity (β-coefficient, 0.04; 95% CI, 0.03-0.05) and LVEF (β-coefficient, −0.81; 95% CI, −1.42 to −0.21). The analysis further showed that men became less physically active with increasing age (β-coefficient, −0.14; 95% CI, −0.24 to −0.04), whereas no change with age could be detected for women.
Conclusion: In selected post-PE patients, physical activity seems to be associated with exercise capacity and LVEF but not with quality of life, dyspnea, or characteristics of the initial PE. Men appear to become less physically active with increasing age.publishedVersio
The Norwegian language in Argentina: A first look at heritage Norwegian in a new context
Full text linkThis paper presents preliminary observations of Norwegian as a heritage language (HL) in a contact situation that has largely gone unnoticed up until now: Argentina, where Spanish is the main contact language. We discuss some lexical, morphological, and syntactic properties of Argentine Norwegian, with Norwegian as a HL in North America as a comparative backdrop, and we point out directions for future research.publishedVersio
Ethics as a minor form of politics and theory in activist research
Full text linkTo do minor activist research is to make use of prompts and displacements to mark and produce new subjectivities, spatialities, and temporalities. To do minor activist research is to unsettle received discourses, narratives, and material social practices of power to develop means of resistance in new and different registers. Training the imagination for a collaboratively accomplished re/presentation of data through creating points of encounters, engendering affirmative perspectivists ethos. Re/presenting data as a space in which own thinking is challenged providing a perspective of the storying practices across participants and across different disciplinary, ideological, or personal boundaries within the researcher´s and the researched specific positioning. It requires getting everyone to participate in the ‘analysis’ of data and then getting everyone ‘inside’ the text: situating data-inquiries in immanence. It therefore demands a liberation from old scripts, and challenges how everyone is transformed into text. A perspectivist ethos being simultaneously means and objective for avoiding reproduction of both old scripts and ethics.publishedVersio
Oppvekstreformen i barnehagen – en casestudie av praksis for psykososialt arbeid med barn i risiko i lys av oppvekstreformen
Full text linkDigitalization in the Emergency Department—An Interview Study of Nurses’ Experiences in Norway
Full text linkEmergency departments (EDs) are overcrowded and linked to an increased risk of mortality and morbidity. Digitalization in EDs has been shown to increase effectiveness, reduce wait times, and improve performance and patient experience. The purpose of this study was to explore ED nurses’ experiences with digitalization in the ED. Interviews were conducted with eight ED nurses in a Norwegian hospital. Data were analyzed using Braun and Clarke’s six-step thematic analysis. Through analysis, three themes were identified, namely (1) consequences for patient safety, (2) influencing communication in the ED, and (3) impacting acute nursing. ED nurses experienced that the digital tools had increased patient safety through accurate documentation and providing a quick overview of the patient. However, digital tools were also seen as a threat to patient safety due to taking focus away from the patient. Digital tools were experienced to have negatively changed the communication both between personnel and between personnel and patients. Also, digital tools impacted the ED nurses’ professional role to a more digitalization-focused approach rather than a patient-oriented approach. These aspects must be included when planning the implementation of new digital tools in EDs in the future.publishedVersio
Complement or competition? Airbnb-based tourism and local housing markets in four Norwegian cities
Full text linkAirbnb listings can stand in competition with traditional rental markets in dynamically growing local markets, which suggests a competitive, rather than complementary relationship between Airbnb listings and local housing markets. The present chapter explores how the Airbnb-housing-market relationship develops over time in urban contexts, considering Airbnb-based tourism and ownership-based and rental-based housing markets. We investigate the long-term spillover effects between these partial markets at local level with empirical data that cover the four largest Norwegian cities, Oslo, Bergen, Trondheim, and Stavanger, all of which have a growing population, significant tourism activities, and a dynamic housing market. Our findings suggest no indication of a short-term spillover effect from Airbnb-based tourism on local housing markets, both those based upon ownership of housing space and rental markets in the cities for the period studied (with the exception of Trondheim). This points to a rather complementary relationship of Airbnb-based tourism and local housing markets in the context of these Norwegian cities. However, there might exist long-term effects between the traditional rental market and Airbnb accommodation in some of the cities, which could have positive or negative effects for local housing markets. Keywords: Airbnb-based tourism, local housing markets, competitive relationship, spillover effects, institutional factors.acceptedVersio
Expectations of a new eating disorder treatment and its delivery: Perspectives of patients and new therapists
Full text linkBackground
A significant number of people with bulimia nervosa (BN) or binge-eating disorder (BED) do not seek professional help. Important reasons include limited knowledge of eating disorders (EDs), feelings of shame, treatment costs, and restricted access to specialized healthcare. In this study, we explored if a novel therapy delivered in a primary care setting could overcome these barriers. We investigated factors such as motivation and expectations and included the patients' and newly trained therapists' perspectives.
Method
We interviewed 10 women with BN (n = 2) or BED (n = 8), enrolled in the Physical Exercise and Dietary therapy (PED-t) program, in a Healthy Life Center (HLC) located in a primary healthcare facility. Interview topics discussed were motivations for and expectations of therapy, and the treatment location. In addition, 10 therapists from HLC's were interviewed on their experiences with the PED-t training program and expectations of running PED-t within their service. The semi-structured interviews were analyzed using reflexive thematic analysis.
Results
Most patients had limited knowledge about EDs and first realized the need for professional help after learning about PED-t. Patients exhibited strong motivations for treatment and a positive perception of both the PED-t, the new treatment setting, and the therapists' competencies. The therapists, following a brief training program, felt confident in their abilities to treat EDs and provide PED-t. With minor operational adjustments, PED-t can seamlessly be integrated into national HLC service locations.
Conclusion
PED-t is an accessible therapeutic service that can be delivered in a primary care environment in a stepped-care therapy model.
Public Significance
This study investigates the views and experiences of patients and newly trained therapists of PED-t (Physical Exercise and Dietary therapy), a new program-led primary care therapy for binge-eating spectrum eating disorders. The treatment and the locations for the intervention, that is, local health care centers, were found to be highly acceptable to both patients and therapists, thus PED-t could easily be integrated as a first step into a step-care delivery model.publishedVersio
Federated Bayesian optimization XGBoost model for cyberattack detection in internet of medical things
Full text linkBackground
Hospitals and medical facilities are increasingly concerned about network security and patient data privacy as the Internet of Medical Things (IoMT) infrastructures continue to develop. Researchers have studied customized network security frameworks and cyberattack detection tools driven by Artificial Intelligence (AI) to counter different types of attacks, such as spoofing, data alteration, and botnet attacks. However, carrying out routine IoMT services and tasks during an under-attack scenario is challenging. Machine Learning has been extensively suggested for detecting cyberattacks in IoMT and IoT infrastructures. However, the conventional centralized approach in ML cannot effectively detect newly emerging attacks without compromising patient data privacy and network flow data confidentiality.
Aim
This study discusses a Federated Bayesian Optimization XGBoost framework that employs multimodal sensory signals from patient vital signs and network flow data to detect attack patterns and malicious network traffic in IoMT infrastructure while ensuring data privacy and detecting previously unknown attacks.
Methodology
The proposed model employs a Federated Bayesian Optimisation XGBoost approach, which allows us to search the parameter space quickly and find an optimal solution from each local server while aggregating the model parameters from each local server to the centralised server. The XGBoost algorithm generates a new tree by taking into account the previously estimated value for the tree's input data and then optimizing the prediction gain. This study used a dataset with 44 attributes and 16 318 instances. During the preprocessing phase, 10 features were dropped, and the remaining 34 features were used to evaluate the network flows and biometric data (patient vital signs).
Results
The performance evaluation reveals that the proposed model predicts data alteration, malware, and spoofing attacks in patients' vital signs and network flow data with a prediction accuracy of 0.96. The results obtained from the experiment demonstrate that both the centralized and federated models are synchronized, with the latter occasionally being slightly reduced.
Conclusion
The findings indicate that the suggested model can be incorporated into the IoMT domain to detect malicious patterns while maintaining data privacy and confidentiality efficiently.publishedVersio
A Comprehensive Review on Deep Learning-Based Motion Planning and End-To-End Learning for Self-Driving Vehicle
Full text linkSelf-Driving Vehicles (SDVs) are increasingly popular, with companies like Google, Uber, and Tesla investing significantly in self-driving technology. These vehicles could transform commuting, offering safer, and efficient transport. A key SDV aspect is motion planning, generating secure, and efficient routes. This ensures safe navigation and prevents collisions with obstacles, pedestrians, and other vehicles. Deep Learning (DL) could aid SDV motion planning. AI tools and algorithms, like Artificial Neural Networks (ANNs), Machine Learning (ML) and DL can learn from data to create effective driving strategies, enhancing SDV adaptability to changing conditions for improved safety and efficiency. This survey gives a DL-based motion planning overview for SDVs, covering behaviour planning, trajectory planning, and End to End Learning (E2EL). It assesses various DL-based behaviour and trajectory planning methods, comparing and summarizing them. It also reviews diverse E2EL techniques including Imitation Learning (IL) and Reinforcement Learning (RL) gaining traction lately. Additionally, this review emphasizes the significance of two crucial enablers: datasets and simulation deployment frameworks for SDVs. The survey compares strategies using multiple metrics and highlights DL-based SDV implementation challenges, including simulation and real-world use cases. This article also suggests future research directions to address E2EL and DL-based motion planning limitations. The presented article is an excellent reference for scholars, engineers, and decision-makers who have an interest in DL-based SDV motion planning.publishedVersio
Adversarial attack detection framework based on optimized weighted conditional stepwise adversarial network
Full text linkArtificial Intelligence (AI)-based IDS systems are susceptible to adversarial attacks and face challenges such as complex evaluation methods, elevated false positive rates, absence of effective validation, and time-intensive processes. This study proposes a WCSAN-PSO framework to detect adversarial attacks in IDS based on a weighted conditional stepwise adversarial network (WCSAN) with a particle swarm optimization (PSO) algorithm and SVC (support vector classifier) for classification. The Principal component analysis (PCA) and the least absolute shrinkage and selection operator (LASSO) are used for feature selection and extraction. The PSO algorithm optimizes the parameters of the generator and discriminator in WCSAN to improve the adversarial training of IDS. The study presented three distinct scenarios with quantitative evaluation, and the proposed framework is evaluated with adversarial training in balanced and imbalanced data. Compared with existing studies, the proposed framework accomplished an accuracy of 99.36% in normal and 98.55% in malicious traffic in adversarial attacks. This study presents a comprehensive overview for researchers interested in adversarial attacks and their significance in computer security.publishedVersio