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Horizon scanning is increasingly used in conservation to systematically explore emerging policy and management issues. We present the results of a horizon scan of issues likely to impact management of Canadian protected and conserved areas over the next 5–10 years. Eighty-eight individuals participated, representing a broad community of academics, government and nongovernment organizations, and foundations, including policymakers and managers of protected and conserved areas. This community initially identified 187 issues, which were subsequently triaged to 15 horizon issues by a group of 33 experts using a modified Delphi technique. Results were organized under four broad categories: ( i) emerging effects of climate change in protected and conserved areas design, planning, and management (i.e., large-scale ecosystem changes, species translocation, fire regimes, ecological integrity, and snow patterns); ( ii) Indigenous governance and knowledge systems (i.e., Indigenous governance and Indigenous knowledge and Western science); ( iii) integrated conservation approaches across landscapes and seascapes (i.e., connectivity conservation, integrating ecosystem values and services, freshwater planning); and ( iv) early responses to emerging cumulative, underestimated, and novel threats (i.e., management of cumulative impacts, declining insect biomass, increasing anthropogenic noise, synthetic biology). Overall, the scan identified several emerging issues that require immediate attention to effectively reduce threats, respond to opportunities, and enhance preparedness and capacity to react.

The usefulness of machine learning algorithms is highly dependent on the formulation of relevant features that sufficiently represent the model. Acoustic resonance spectra consist of a series of peaks, representing resonant modes of the system and contain detailed information about the system structure, material, boundary forces, etc. We present a technique for extracting useful features from dense acoustic resonance spectra of multi-component systems. For simple geometries, the resonance spectrum is relatively sparse and it is feasible to track individual peaks to quantify properties of the system. However, for multi-component systems, the acoustic resonance spectra consist of overlapping peaks, corresponding to resonances in different components. As a result, a high density of peaks exists, and some peak positions are sensitive to changes in the contact between components. Thus, tracking specific resonance modes becomes challenging. Instead, we combine principles from wavelet transformation, nonlinear normalization, and genetic algorithm optimization to extract useful features from complicated acoustic resonance spectra. We demonstrate this technique on simulated acoustic resonance spectra for multi-layer structures. Here, we are measuring the thickness of a specific layer, which is hampered by changes in the acoustic resonance spectrum due to variation in the other layer thicknesses as well as delamination defects.

Between the World Wars use of a concave profiled concrete surface (a sound mirror) to reflect sound waves was thought to be the answer to the early detection of aerial attack. Ultimately, this technology was superseded by radar and the experimental work on sound reflection and collection was abandoned. As a result, the south and east coast of England is scattered with the remains of such forgotten concrete structures. The only extant collection of these structures is at Greatstone in Kent, where three sound mirrors remain and have been listed as scheduled monuments. One of the largest projects funded by the Aggregate Levy Sustainability Fund and managed by English Heritage was concerned with stabilizing these structures and undertaking research into their repair.This paper aims to outline the conservation approach to the project and to detail the concrete repair techniques trialled. It also highlights some pointers for the repair of twentieth-century concrete based on the advice of a master mason ...

Objective. To determine the impact of a hospital-coordinated discharge care plan, involving a multidisciplinary team of primary health care providers, on hospital length of stay, quality of life, and both patient and general practitioner inclusion in, and satisfaction with, discharge procedures. Design. This investigation comprised a prospective, randomized, controlled, clinical trial. Setting. This multicentre and cross-jurisdictional study focused on areas of tertiary and primary health care as well as community allied health in Western Australia. Participants. Patients (n = 189) with chronic cardiorespiratory diagnoses were recruited from respiratory, cardiovascular, and general medical wards at two tertiary hospitals. Intervention. Subjects were randomly assigned to one of two groups. Intervention group patients received a discharge care plan in accordance with that outlined in the Australian Enhanced Primary Care Package, completed before discharge and sent to the patient’s general practitioner and other community service providers for review. Control patients were discharged under existing hospital processes. Outcome measures. Patients and general practitioners were surveyed pre-discharge and 7 days post-discharge for quality of life and opinion of discharge procedures. Hospital length of stay was also determined. Results. Significant improvements in discharge planning involvement, health service access, confidence with discharge procedures, and opinion of discharge based on previous experience were seen for patients who received the discharge care plan. Further, improved perceptions of mental quality of life were observed within the first week post-discharge for intervention patients. Length of stay showed no difference between groups. Extent and speed of hospital–general practitioner communication were significantly improved via the intervention. Conclusions. Our results indicate that a multidisciplinary discharge care plan, initiated before separation, improves quality of life, involvement, and satisfaction with discharge care, and hospital–general practitioner integration. As such, it possesses benefits over current Western Australian hospital discharge procedures for the care of chronically ill populations.

To examine prospectively the relationship between diabetes, glycemic control, and spirometric measures.From a community-based cohort, 495 Europid (i.e., of European descent) patients with type 2 diabetes who had no history of pulmonary disease underwent baseline spirometry between 1993 and 1994. A subset of 125 patients was restudied a mean of 7.0 years later. The main outcome measures included forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), vital capacity (VC), and peak expiratory flow (PEF) corrected for body temperature, air pressure, and water saturation and were expressed either in absolute terms or as percentage-predicted value for age, sex, and height.Mean percentage-predicted values of each spirometric measure were decreased10% in the whole cohort at baseline and absolute measures continued to decline at an annual rate of 68, 71, and 84 ml/year and 17 l/min for FVC, FEV1, VC, and PEF, respectively, in the 125 prospectively studied patients. Declining lung function measures were consistently predicted by poor glycemic control in the form of a higher updated mean HbA1c, follow-up HbA1c, or follow-up fasting plasma glucose. In a Cox proportional hazards model, decreased FEV1 percentage-predicted value was an independent predictor of all-cause mortality.Reduced lung volumes and airflow limitation are likely to be chronic complications of type 2 diabetes, the severity of which relates to glycemic exposure. Airflow limitation is a predictor of death in type 2 diabetes after adjusting for other recognized risk factors.