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BackgroundSelf-management is endorsed in clinical practice guidelines for the care of musculoskeletal pain. In a randomized clinical trial, we tested the effectiveness of an artificial intelligence–based self-management app (selfBACK) as an adjunct to usual care for patients with low back and neck pain referred to specialist care. ObjectiveThis study is a process evaluation aiming to explore patients’ engagement and experiences with the selfBACK app and specialist health care practitioners’ views on adopting digital self-management tools in their clinical practice. MethodsApp usage analytics in the first 12 weeks were used to explore patients’ engagement with the SELFBACK app. Among the 99 patients allocated to the SELFBACK interventions, a purposive sample of 11 patients (aged 27-75 years, 8 female) was selected for semistructured individual interviews based on app usage. Two focus group interviews were conducted with specialist health care practitioners (n=9). Interviews were analyzed using thematic analysis. ResultsNearly one-third of patients never accessed the app, and one-third were low users. Three themes were identified from interviews with patients and health care practitioners: (1) overall impression of the app, where patients discussed the interface and content of the app, reported on usability issues, and described their app usage; (2) perceived value of the app, where patients and health care practitioners described the primary value of the app and its potential to supplement usual care; and (3) suggestions for future use, where patients and health care practitioners addressed aspects they believed would determine acceptance. ConclusionsAlthough the app’s uptake was relatively low, both patients and health care practitioners had a positive opinion about adopting an app-based self-management intervention for low back and neck pain as an add-on to usual care. Both described that the app could reassure patients by providing trustworthy information, thus empowering them to take actions on their own. Factors influencing app acceptance and engagement, such as content relevance, tailoring, trust, and usability properties, were identified. Trial RegistrationClinicalTrials.gov NCT04463043; https://clinicaltrials.gov/study/NCT04463043

Previous physical activity interventions for children (5-12yrs) have aimed to change determinants associated with self-report physical activity behaviour (PAB) and/or sedentary behaviour (SB), however, the associations between these determinants and PAB/SB in different settings are uncertain. The present study aimed to identify modifiable determinants targeted in previous PAB/SB interventions for children. Intervention effects on the determinants and their associations with self-report PAB/SB were assessed across settings. Search of relevant interventions from pre-defined databases was conducted up to July 2023. Randomized and non-randomized controlled trials with modifiable determinants were included. Data extraction and risk of bias assessments were conducted by two independent researchers. Where data could be pooled, we performed Robust Bayesian meta-analyses. Heterogeneity, publication bias and certainty of evidence were assessed. Fifteen studies were deemed eligible to be included. Thirty-seven unique determinants within four settings were identified-school, family, school with family/home, and community with(out) other settings. Ninety-eight percent of determinants belonged to individual/interpersonal determinant categories. Narratively, intervention effects on student perception of teachers' behaviour (school), self-management, perceived barriers, external motivation, exercise intention, parental modeling on SB (school with family/home) and MVPA expectations (community) were weak to strong, however, corresponding PAB/SB change was not evident. There were negligible effects for all other determinants and the corresponding PAB/SB. Meta-analyses on self-efficacy, attitude, subjective norm and parental practice and PAB/SB in two settings showed weak to strong evidence against intervention effect, while the effect on knowledge could not be determined. Similarly, publication bias and heterogeneity for most analyses could not be ascertained. We found no concrete evidence of association between the modifiable determinants and self-report PAB/SB in any settings. This is presumably due to intervention ineffectiveness. Design of future interventions should consider to follow the systems-based approach and identify determinants unique to the context of a setting, including policy and environmental determinants.

Smart Grids (SG) envision the exchange of both power and data, enabling system and customers to generate and transfer energy in a more efficient and balanced way. Among the relevant communication technologies, we find Power-Line Communications (PLC), which allow for data transmission on the electrical cables used for power delivery. Despite the hostile medium, PLC offer reliability and data rates to support exchange of control traffic, smart metering and sensor network applications. The distribution portion of the power delivery network, which we focus on in this work, is topologically complex, which makes channel prediction complicated. We show how random realistic topologies can be generated and then used to train a Machine Learning (ML) algorithm to infer PLC link quality (based on channel response) exploiting solely topology descriptors. We eventually show how precisely the communication quality can be inferred from the SG topology through ML. In doing so, we also discuss how the ML approach offers the common ground between top-down and bottom-up approaches for network characterization and how it enables smart decision making in the SG.

Introduction Chronic widespread pain (CWP) and diabetes commonly co-occur; however, it is unclear whether CWP infers an additional risk for diabetes among those with known risk factors for type 2 diabetes. We aimed to examine if CWP magnifies the effect of adverse lifestyle factors on the risk of diabetes.Research design and methods The study comprised data on 25 528 adults in the Norwegian HUNT Study without diabetes at baseline (2006–2008). We calculated adjusted risk ratios (RRs) with 95% CIs for diabetes at follow-up (2017–2019), associated with CWP and body mass index (BMI), physical activity, and insomnia symptoms. The relative excess risk due to interaction (RERI) was calculated to investigate the synergistic effect between CWP and adverse lifestyle factors.Results Compared with the reference group without chronic pain and no adverse lifestyle factors, those with BMI ≥30 kg/m2 with and without CWP had RRs for diabetes of 10.85 (95% CI 7.83 to 15.05) and 8.87 (95% CI 6.49 to 12.12), respectively; those with physical activity

Peritoneal dialysis (PD) pericatheter exit-site leaks most commonly occur early, within 30 days of catheter insertion. Late exit-site leaks are rare. The distinction between early and late exit-site leaks is important because the causes and subsequent management strategies may be different. Early leaks can often be first treated by delaying or holding PD therapy, allowing the prolongation of the healing time because fibrous tissue continues to form around the deep cuff. Late leaks are less likely to heal with cessation of PD alone and often require PD catheter replacement. In this case report, we provide an overview of the diagnosis and management of PD catheter exit-site leaks while highlighting a case of a late presenting exit-site leak resulting from a unique cause of PD catheter trauma.

ITER is of key importance in the European fusion roadmap as it aims to prove the scientific and technological feasibility of fusion as a future energy source. The EUROfusion consortium of labs within Europe is contributing to the preparation of ITER scientific exploitation and operation and aspires to exploit ITER outcomes in view of DEMO. The paper provides an overview of the major progress obtained recently, carried out in the frame of the new (initiated in 2021) EUROfusion work-package called ‘ Pr eparation of I TER O peration’ (PrIO). The overview paper is directly supported by the eleven EUROfusion PrIO contributions given at the 29th Fusion Energy Conference (16–21 October 2023) London, UK [ https://www.iaea.org/events/fec2023 ]. The paper covers the following topics: (i) development and validation of tools in support to ITER operation (plasma breakdown/burn-through with evolving plasma volume, new infra-red synthetic diagnostic for off-line analysis and wall monitoring using Artificial Intelligence techniques, synthetic diagnostics development, development and exploitation of multi-machine databases); (ii) R&D for the radio-frequency ITER neutral beam sources leading to long duration of negative deuterium/hydrogen ions current extraction at ELISE and participation in the neutral beam test facility with progress on the ITER source SPIDER, and, the commissioning of the 1 MV high voltage accelerator (MITICA) with lessons learned for ITER; (iii) validation of neutronic tools for ITER nuclear operation following the second JET deuterium–tritium experimental campaigns carried out in 2021 and in 2023 (neutron streaming and shutdown dose rate calculation, water activation and activated corrosion products with advanced fluid dynamic simulation; irradiation of several materials under 14.1 MeV neutron flux etc).

Abstract Machine learning algorithms, however effective, are known to be vulnerable in adversarial scenarios where a malicious user may inject manipulated instances. In this work, we focus on evasion attacks, where a model is trained in a safe environment and exposed to attacks at inference time. The attacker aims at finding a perturbation of an instance that changes the model outcome.We propose a model-agnostic strategy that builds a robust ensemble by training its basic models on feature-based partitions of the given dataset. Our algorithm guarantees that the majority of the models in the ensemble cannot be affected by the attacker. We apply the proposed strategy to decision tree ensembles, and we also propose an approximate certification method for tree ensembles that efficiently provides a lower bound of the accuracy of a forest in the presence of attacks on a given dataset avoiding the costly computation of evasion attacks.Experimental evaluation on publicly available datasets shows that the proposed feature partitioning strategy provides a significant accuracy improvement with respect to competitor algorithms and that the proposed certification method allows ones to accurately estimate the effectiveness of a classifier where the brute-force approach would be unfeasible.

For several years, farmers have been questioning the effects of electromagnetic fields and stray electrical currents on the health of their animals. Observing changes in behavior or a decline in livestock productivity, farmers suspect that electrical installations on or near the farm may be responsible. Indeed, these systems can generate fault currents or stray currents, some of which may pass through the animals, affecting their well-being and productivity. To identify the origin and address this issue, an electrical diagnosis can be performed. In this study, diagnostics were carried out in eleven bovine farms considered “healthy”. These measurements included earth resistance equipment insulation resistance, continuity, leakage currents, as well as contact and step voltages, with some farms presenting non-conformities. This study will better understand the potential links between electrical installations and animal well-being, correlate the results of this study with those obtained in diagnostics conducted on farms experiencing such concerns and implement appropriate preventative and corrective measures.

A large overlap in the ultrasound (US) features of focal pancreatic lesions (FPLs) in cats is reported. Furthermore, only a small number of studies describing the contrast-enhanced ultrasound (CEUS) features of FPLs in cats have been conducted today. The aim of this study is to describe the B-mode US and CEUS features of FPLs in cats. Ninety-eight cats cytologically diagnosed with FPL were included. The lesions were classified as adenocarcinoma (n = 40), lymphoma (n = 11), nodular hyperplasia (n = 17), other benign lesion (OBL) (n = 20), cyst (n = 4) or other malignant lesion (OML) (n = 6). Several qualitative and quantitative B-mode and CEUS features were described in each case. OMLs and cysts were not included in the statistical analysis. A decision tree to classify the lesions based on their B-mode and CEUS features was developed. The overall accuracy of the cross-validation of the decision tree was 0.74 (95% CI: 0.63–0.83). The developed decision tree had a very high sensitivity and specificity for nodular hyperplasia (1 and 0.94, respectively) as well as good sensitivity and specificity for both adenocarcinomas (0.85 and 0.77, respectively) and OBLs also (0.70 and 0.93, respectively). The algorithm was unable to detect any specific feature for classifying lymphomas, and almost all the lymphomas were classified as adenocarcinomas. The combination between CEUS and B-mode US is very accurate in the classification of some FPLs, especially nodular hyperplasia and adenocarcinomas. Cytopathology and or histopathology is still a fundamental step FPL diagnostic workflow.

Introduction Physical activity among children and adolescents remains insufficient, despite the substantial efforts made by researchers and policymakers. Identifying and furthering our understanding of potential modifiable determinants of physical activity behaviour (PAB) and sedentary behaviour (SB) is crucial for the development of interventions that promote a shift from SB to PAB. The current protocol details the process through which a series of systematic literature reviews and meta-analyses (MAs) will be conducted to produce a best-evidence statement (BESt) and inform policymakers. The overall aim is to identify modifiable determinants that are associated with changes in PAB and SB in children and adolescents (aged 5–19 years) and to quantify their effect on, or association with, PAB/SB.Methods and analysis A search will be performed in MEDLINE, SportDiscus, Web of Science, PsychINFO and Cochrane Central Register of Controlled Trials. Randomised controlled trials (RCTs) and controlled trials (CTs) that investigate the effect of interventions on PAB/SB and longitudinal studies that investigate the associations between modifiable determinants and PAB/SB at multiple time points will be sought. Risk of bias assessments will be performed using adapted versions of Cochrane’s RoB V.2.0 and ROBINS-I tools for RCTs and CTs, respectively, and an adapted version of the National Institute of Health’s tool for longitudinal studies. Data will be synthesised narratively and, where possible, MAs will be performed using frequentist and Bayesian statistics. Modifiable determinants will be discussed considering the settings in which they were investigated and the PAB/SB measurement methods used.Ethics and dissemination No ethical approval is needed as no primary data will be collected. The findings will be disseminated in peer-reviewed publications and academic conferences where possible. The BESt will also be shared with policy makers within the DE-PASS consortium in the first instance.Systematic review registration CRD42021282874.

(1) Background: Osteoid osteoma (OO) is one of the most common benign bone tumors. This type of osteogenic tumor is generally characterized by a well-defined lytic area with a vascularized central nidus surrounded by sclerosis and bone thickening. The wrist and hand bones are infrequent sites for osteoid osteoma: only 10% of the cases arise in these areas. Standard treatments are surgical excision and radio-frequency ablation (RFA), both with advantages and disadvantages. This study aimed to compare the two techniques to prove if RFA could be a potential alternative to surgery in the treatment of OO of the hand. (2) Methods: Patients treated for OO of the hand between January 2011 and December 2020 were evaluated and data was collected regarding the lesions’ characteristics and the treatment outcome. Each patient was followed up for 24 months and VAS pain (Visual Analogue Scale), DASH (Disability of the Arm, Shoulder and Hand), and PRWE (Patient-Related Wrist Evaluation) scores were collected. (3) Results: A total of 27 patients were included in the study: 19 surgical and 8 RFA. Both treatments showed a significant improvement in pain and functionality. Surgery was associated with a higher complication rate (stiffness and pain), while RFA was associated with a higher recurrence rate (2/8 patients). RFA allowed for a speedier return to work. (4) Conclusions: We believe that osteoid osteoma treatment with RFA in the hand should be an available alternative to surgery as it allows rapid pain relief and a swift return to work. Surgery should be reserved for cases of diagnostic uncertainty or periosteal localization.

In multiracial societies, the diversity of names in the workforce may reflect racial inclusivity. There is scant data on racial representation among Canadian physicians, prompting our analysis of naming diversity. We profiled the race and gender demographics of the names of physicians in Canadian academic radiology departments. Further, we devised a structured classification methodology using a commercial artificial intelligence and naming database to classify 1,727 names according to national origin and gender. The names were retrieved from faculty websites. A Z-test of proportions was used to compare radiologists’ name demographics to demographics from the 2016 Canadian census. In close agreement with much of the literature on gender demographics, 31.99% of names were classified as female. Names that were classified as belonging to Indigenous, Black, Latin American, and Filipino name-bearers were underrepresented. Names classified as belonging to the following groups were overrepresented: South Asian, Chinese, Arab, Southeast Asian, West Asian, and Korean. Names associated with White subjects in the corpus were proportionally represented for full names and overrepresented for given names. Faculty with full names classified as Southeast Asian, Korean, and Chinese often had given names that fell into the White category. The structured methodology showed high inter-rater reliability for race classifications. The racial disparities we observed mirrored those found in surveys of medical students, suggesting that the bottleneck occurs at the level of medical school admissions. Thus, onomastics can provide valuable data to diversity initiatives.

Eivind Schjelderup Skarpsno,1,2 Paul Jarle Mork,1 Knut Hagen,3,4 Tom Ivar Lund Nilsen,1,5 Anna Marcuzzi1 1Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; 2Department of Neurology and Clinical Neurophysiology, St. Olavs Hospital, Trondheim, Norway; 3Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; 4Clinical Research Unit Central Norway, St. Olavs Hospital, Trondheim, Norway; 5Clinic of Anaesthesia and Intensive Care, St. Olavs Hospital, Trondheim University Hospital, Trondheim, NorwayCorrespondence: Eivind Schjelderup SkarpsnoDepartment of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Håkon Jarls Gate 11, Samfunnsmedisinbygget, Trondheim 7030, NorwayTel +47 97521297Email eivind.s.skarpsno@ntnu.noStudy Objectives: To examine the association between the number of chronic nighttime insomnia symptoms and the risk of chronic widespread pain (CWP) and pain-related disability.Methods: A prospective study of 10,847 participants in the Norwegian HUNT Study without chronic musculoskeletal pain at baseline in 2006– 2008. We used a modified Poisson regression model to estimate adjusted risk ratios (RRs) with a 95% confidence interval (CI) for CWP and pain-related disability at follow-up in 2017– 2019 associated with insomnia and number of nighttime insomnia symptoms at baseline. Chronic insomnia was defined according to the current classification system and grouped into three categories based on the number of reported nighttime symptoms (ie, difficulty initiating sleep, trouble maintaining sleep and early morning awakenings).Results: Compared to the reference group of people without insomnia, people with insomnia had RRs for CWP and pain-related disability of 1.64 (1.26– 2.14) and 1.63 (1.37– 1.94), respectively. When people with insomnia were categorized based on the number of nighttime symptoms, people who reported one, two, or three nighttime symptoms had RRs of CWP of 1.19 (95% CI 0.80– 1.78), 1.78 (95 CI 1.13– 2.80) and 3.08 (95% CI 1.93– 4.92), respectively, compared to people without insomnia. The corresponding RRs for pain-related disability were 1.49 (95% CI 1.17– 1.89), 1.46 (95% CI 2.04– 2.05), and 2.46 (95% CI 1.76– 3.42).Conclusion: These findings indicate that people with insomnia characterized by symptoms in all phases of the sleep period have a substantially increased risk of CWP and pain-related disability.Keywords: sleeplessness, insomnia disorder, chronic insomnia, musculoskeletal, pain, chronic, widespread chronic pain, relative risk, epidemiology