Recent research has indicated an increase in the likelihood and impact of tree failure. The potential for trees to fail relates to various biomechanical and physical factors. Strikingly, there seems to be an absence of tree risk assessment methods supported by observations, despite an increasing availability of variables and parameters measured by scientists, arborists and practitioners. Current urban tree risk assessments vary due to differences in experience, training, and personal opinions of assessors. This stresses the need for a more objective method to assess the hazardousness of urban trees. The aim of this study is to provide an overview of factors that influence tree failure including stem failure, root failure and branch failure. A systematic literature review according to the PRISMA guidelines has been performed in databases, supported by backward referencing: 161 articles were reviewed revealing 142 different factors which influenced tree failure. A meta-analysis of effect sizes and p-values was executed on those factors which were associated directly with any type of tree failure. Bayes Factor was calculated to assess the likelihood that the selected factors appear in case of tree failure. Publication bias was analysed visually by funnel plots and results by regression tests. The results provide evidence that the factors Height and Stem weight positively relate to stem failure, followed by Age, DBH, DBH squared times H, and Cubed DBH (DBH3) and Tree weight. Stem weight and Tree weight were found to relate positively to root failure. For branch failure no relating factors were found. We recommend that arborists collect further data on these factors. From this review it can further be concluded that there is no commonly shared understanding, model or function available that considers all factors which can explain the different types of tree failure. This complicates risk estimations that include the failure potential of urban trees.
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Abstract: Background: Little is known about frailty among patients hospitalized with heart failure (HF). To date, the limited information on frailty in HF is based on a unidimensional view of frailty, in which only physical aspects are considered when determining frailty. The aims of this study were to study different dimensions of frailty (physical, psychological and social) in patients with HF and the effect of different dimensions of frailty on the incidence of heart failure. Methods: The study used a cross-sectional design and included 965 patients hospitalized for heart failure and 164 healthy controls. HF was defined according to the ESC guidelines. The Tilburg Frailty Indicator (TFI) was used to assess frailty. Probit regression analyses and chi-square statistics were used to examine associations between the occurrence of heart failure and TFI domains of frailty. Results: Patients diagnosed with frailty were 15.3% more likely to develop HF compared to those not diagnosed with frailty (p < 0.001). An increase in physical, psychological and social frailty corresponded to an increased risk of HF of 2.9% (p < 0.001), 4.4% (p < 0.001) and 6.6% (p < 0.001), respectively. Conclusions: We found evidence of the association between different dimensions of frailty and incidence of HF.
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The seismic assessment of the out-of-plane (OOP) behaviour of unreinforced masonry (URM) buildings is essential since the OOP is one of the primary collapse mechanisms in URM buildings. It is influenced by several parameters, including the poor connections between structural elements, a weakness highlighted by post-earthquake observations. The paper presents a mechanical model designed to predict the contributions of various resisting mechanisms to the strength capacity of timber-joist connections in masonry cavity walls. The research presented in this paper considers two different failure modes: joist-wall interface failure, and OOP rocking behaviour of the URM walls. Consequently, two mechanical models are introduced to examine these failure modes in timber-joist connections within masonry cavity walls. One model focuses on the joist-wall interface failure, adopting a Coulomb friction model for joist-sliding further extended to incorporate the arching effect. The other model investigates the OOP rocking failure mode of walls. The combined mechanical model has been validated against the outcomes of an earlier experimental campaign conducted by the authors. The considered model can accurately predict the peak capacity of the joist connection and successfully defines the contribution of each mechanism in terms of resistance at failure.
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The prevention and diagnosis of frailty syndrome (FS) in cardiac patients requires innovative systems to support medical personnel, patient adherence, and self-care behavior. To do so, modern medicine uses a supervised machine learning approach (ML) to study the psychosocial domains of frailty in cardiac patients with heart failure (HF). This study aimed to determine the absolute and relative diagnostic importance of the individual components of the Tilburg Frailty Indicator (TFI) questionnaire in patients with HF. An exploratory analysis was performed using machine learning algorithms and the permutation method to determine the absolute importance of frailty components in HF. Based on the TFI data, which contain physical and psychosocial components, machine learning models were built based on three algorithms: a decision tree, a random decision forest, and the AdaBoost Models classifier. The absolute weights were used to make pairwise comparisons between the variables and obtain relative diagnostic importance. The analysis of HF patients’ responses showed that the psychological variable TFI20 diagnosing low mood was more diagnostically important than the variables from the physical domain: lack of strength in the hands and physical fatigue. The psychological variable TFI21 linked with agitation and irritability was diagnostically more important than all three physical variables considered: walking difficulties, lack of hand strength, and physical fatigue. In the case of the two remaining variables from the psychological domain (TFI19, TFI22), and for all variables from the social domain, the results do not allow for the rejection of the null hypothesis. From a long-term perspective, the ML based frailty approach can support healthcare professionals, including psychologists and social workers, in drawing their attention to the nonphysical origins of HF.
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Background—Self-management interventions are widely implemented in care for patients with heart failure (HF). Trials however show inconsistent results and whether specific patient groups respond differently is unknown. This individual patient data meta-analysis assessed the effectiveness of self-management interventions in HF patients and whether subgroups of patients respond differently. Methods and Results—Systematic literature search identified randomized trials of selfmanagement interventions. Data of twenty studies, representing 5624 patients, were included and analyzed using mixed effects models and Cox proportional-hazard models including interaction terms. Self-management interventions reduced risk of time to the combined endpoint HF-related all-0.71- in Conclusions—This study shows that self-management interventions had a beneficial effect on time to HF-related hospitalization or all-cause death, HF-related hospitalization alone, and elicited a small increase in HF-related quality of life. The findings do not endorse limiting selfmanagement interventions to subgroups of HF patients, but increased mortality in depressed patients warrants caution in applying self-management strategies in these patients.
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Failure is a popular topic of research. It has long been a source of study in fields such as sociology and anthropology, science and technology studies, privacy and surveillance, cultural, feminist and media studies, art, theatre, film, and political science. When things go awry, breakdown, or rupture they lead to valuable insights into the mundane mechanisms of social worlds. Yet, while failure is a familiar topic of research, failure in and as a tactic of research is far less visible, valued, and explored.In this book the authors reflect upon the role of creative interventions as a critical mode for methods, research techniques, fieldwork, and knowledge transmission or impact. Here, failure is considered a productive part of engaging with and in the field. It is about acknowledging the ‘mess’ of the social and how we need methods, modes of attunement, and knowledge translation that address this complexity in nuanced ways. In this collection, interdisciplinary researchers and practitioners share their practices, insights, and challenges around rethinking failure beyond normalized tropes. What does failure mean? What does it do? What does putting failure under the microscope do to our assumptions around ontology and epistemologies? How can it be deployed to challenge norms in a time of great uncertainty, crisis, and anxiety? And what are some of the ways resilience and failure are interrelated?
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The seismic assessment of unreinforced masonry (URM) buildings with cavity walls is a relevant issue in many countries, such as in Central and Northern Europe, Australia, New Zealand, China and several other countries. A cavity wall consists of two separate parallel masonry walls (called leaves) connected by metal ties: an inner loadbearing wall and an outer veneer having mostly aesthetic and insulating functions. Cavity walls are particularly vulnerable structural elements. If the two leaves of the cavity wall are not properly connected, their out-of-plane strength may be significantly smaller than that of an equivalent solid wall with the same thickness.The research presented in this paper focuses on a mechanical model developed to predict the failure mode and the strength capacity of metal tie connections in masonry cavity walls. The model considers six possible failures, namely tie failure, cone break-out failure, pull-out failure, buckling failure, piercing failure and punching failure. Tie failure is a predictable quantity when the possible failure modes can be captured. The mechanical model for the ties has been validated against the outcomes of an experimental campaign conducted earlier by the authors. The mechanical model is able to capture the mean peak force and the failure mode obtained from the tests. The mechanical model can be easily adopted by practising engineers who aim to model the wall ties accurately in order to assess the strength and behaviour of the structures against earthquakes. Furthermore, the proposed mechanical model is used to extrapolate the experimental results to untested configurations, by performing parametric analyses on key parameters including a higher strength mortar of the calcium silicate brick masonry, a different cavity depth, a different tie embedment depth, and solid versus perforated clay bricks.
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AIM: To compare the shear bond strength (SBS) after aging of two dual-curing composite resin cements to multiphase composite resin (experiment) and glass-ceramics (control).METHODS: Seventy computer-aided design/computer-aided manufacturing (CAD/CAM) blocks were prepared: 24 multiphase composite resin blocks (Lava Ultimate; experiment), and 12 control blocks (groups 5 and 6: 6 IPS e.max CAD, 6 IPS Empress CAD). Surface treatments of the experiment groups were: 1) Al2O3 airborne particle abrasion; 2) bur-roughening; 3) silica-coated aluminum oxide particle abrasion; and 4) hydrofluoric (HF) acid etching. Per study group, Variolink II (a) and RelyX Ultimate (b) were used as cements. Per treatment group, four cement cylinders were adhered to the conditioned blocks (n = 12). After thermocyclic aging (10.000x, 5°C to 55°C), notch-edge shear testing was applied. Modes of failure were examined. A P value of 0.05 was considered significant.RESULTS: Groups 1a (18.68 ± 3.81) and 3a (17.09 ± 3.40) performed equally to 6a (20.61 ± 4.10). Group 5a (14.39 ± 2.80) did not significantly differ from groups 1a, 3a, and 4a (15.21 ± 4.29). Group 2a (11.61 ± 3.39) showed the lowest bond strength. For the RelyX Ultimate specimens, mean bond strengths were: 1b (18.12 ± 2.84) > 4b (15.57 ± 2.31) > 2b (12.34 ± 1.72) = 3b (11.54 ± 2.45) = 6b (12.31 ± 1.87) > 5b (0.78 ± 0.89). Failure mode analysis showed a significant association between bond strength values and modes of failure (chi-square).CONCLUSION: The SBS of the composite cements to the multiphase composite resin that was treated by Al2O3 or silica-coated aluminum oxide particle abrasion is comparable to the bond of the control groups.
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Corporate Social Responsibility affects Corporate Governance as it stretches the accountability of companies beyond its traditional boundaries. This however may conflict with the corporate objective of maximizing stockholder wealth. The paper provides an overview of various academic theories and corporate attitudes on this issue and discusses the merits and disadvantages of the two main governance modes: the stockholder mode and the stakeholder mode.
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Background: INTELLiVENT-adaptive support ventilation (ASV) is an automated closed-loop mode of invasive ventilation for use in critically ill patients. INTELLiVENT-ASV automatically adjusts, without the intervention of the caregiver, ventilator settings to achieve the lowest work and force of breathing. Aims: The aim of this case series is to describe the specific adjustments of INTELLiVENT-ASV in patients with acute hypoxemic respiratory failure, who were intubated for invasive ventilation. Study design: We describe three patients with severe acute respiratory distress syndrome (ARDS) because of COVID-19 who received invasive ventilation in our intensive care unit (ICU) in the first year of the COVID-19 pandemic. Results: INTELLiVENT-ASV could be used successfully, but only after certain adjustments in the settings of the ventilator. Specifically, the high oxygen targets that are automatically chosen by INTELLiVENT-ASV when the lung condition ‘ARDS’ is ticked had to be lowered, and the titration ranges for positive end expiratory pressure (PEEP) and inspired oxygen fraction (FiO2) had to be narrowed. Conclusions: The challenges taught us how to adjust the ventilator settings so that INTELLiVENT-ASV could be used in successive COVID-19 ARDS patients, and we experienced the benefits of this closed-loop ventilation in clinical practice. Relevance to clinical practice: INTELLiVENT-ASV is attractive to use in clinical practice. It is safe and effective in providing lung-protective ventilation. A closely observing user always remains needed. INTELLiVENT-ASV has a strong potential to reduce the workload associated with ventilation because of the automated adjustments.
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