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The Canadian Institutes of Health Research - Institute of Health Services and Policy Research's (IHSPR's) Strategic Plan 2021-2026 for accelerating health system transformation is well positioned to meet the strategic priorities being outlined by many health systems in Canada and internationally (CIHR IHSPR 2021). The IHSPR Health System Impact Fellow program has been a strong influence on the embedded research and scientist program in Nova Scotia, namely, the Network of Scholars Program, which was implemented just before the pandemic. The network includes scientists and scholars from diverse academic backgrounds and skill levels including alumni of the Health System Impact Fellow program. The Network of Scholars has over 30 scholars and approximately 100 academic partners and scientists supporting embedded activities such as rapid reviews, implementation science and rapid evaluation initiatives. These embedded activities are front facing to the needs and priorities of the health system. This commentary highlights the importance of IHSPR's outlined strategic plan and direction, which are consistent with the experience and the needs for embedded supports within the Nova Scotia health system.

A gap has been identified in the literature regarding available approaches, and instruments, to measure and/or assess the readiness of post-licensure healthcare providers to participate effectively in an interprofessional collaborative healthcare team (ICHT). Globally, major changes are taking place in provision of maternal health care (WHO, 2015). Stillbirths account for over half of all perinatal deaths; and (1/3) of stillbirths take place during delivery, (i.e. are largely avoidable). Intrapartum deaths (i.e. those occurring during delivery) are closely linked to place of, and care at, delivery. In developing countries, just over 40% all deliveries occur in health facilities and little more than half take place with assistance from a doctor, midwife, or qualified nurse. Studies have shown that poor perinatal outcomes can be linked to poor interprofessional collaboration and that when effective interprofessional collaboration is in place, better health outcomes are realized (Freeth, Ayida, Berridge, Mackintosh, Norris, Sadler, & Strachan 2009; Watkins, Nagle, Kent, & Hutchinson 2017). Therefore, a Readiness to Collaborate Scale (RCS) has been developed and validated with a group of low-risk obstetrical providers to test their readiness to collaborate together in an interprofessional team. In Phase I, content validation was performed with a group of low-risk obstetrical providers (n = 9). In Phase II, construct validation included a larger group of low-risk obstetrical providers (n = 140). Using a Principal Component Analysis, four factors were identified: Readiness for Interprofessional Collaboration, Communication, Trust and, Reluctance to Collaborate. Finally, the five questions posed by Borrill et al. (2001), to determine high and low functioning teams, were used for criterion validation. A t-Test to determine significant difference was completed and p values indicated there was a difference between scores of those who were high functioning versus those who were low functioning, demonstrating that the Readiness to Collaborate Scale (RCS) can identify those who are ready to participate in an ICHT, and those who are not.

Summary Background The benefit of initiation of insulin pump therapy (continuous subcutaneous insulin infusion; CSII) in patients with type 1 diabetes using continuous glucose monitoring (CGM) has not been studied. We aimed to assess glycaemic outcomes when switching from multiple daily injections (MDI) to CSII in adults with type 1 diabetes using CGM. Methods In this multicentre, randomised controlled trial, 75 adults with type 1 diabetes in the CGM group of the DIAMOND trial were randomly assigned via the study website using a computer-generated sequence to continue MDI or switch to CSII, with continuation of CGM, for 28 weeks. The primary outcome was CGM-measured time in the glucose concentration range of 70–180 mg/dL (3·9–10·0 mmol/L). This study is registered with ClinicalTrials.gov, number NCT02282397. Findings Between April 14, 2015, and May 5, 2016, 37 participants were randomly assigned to the CGM plus CSII group and 38 participants were randomly assigned to the CGM plus MDI group. The study was completed by 36 (97%) of 37 participants in the CGM plus CSII group and 35 (92%) of 38 participants in the CGM plus MDI group. Mean CGM use was 6·7 days per week (SD 0·8) in the CGM plus CSII group and 6·9 days per week (0·3) in the CGM plus MDI group (p=0·86). No participants in the CGM plus CSII group who completed the trial discontinued CSII. Over the follow-up period, mean time in the glucose concentration range of 70–180 mg/dL (3·9–10·0 mmol/L) was 791 min per day (SD 157) in the CGM plus CSII group and 741 min per day (225) in the CGM plus MDI group (adjusted mean treatment group difference: 83 min, 95% CI 17–149; p=0·01). Participants in the CGM plus CSII group had a greater reduction in CGM-measured mean glucose (p=0·005) and hyperglycaemia (on four metrics: p=0·007 for >180 mg/dL [>10·0 mmol/L], p=0·02 for >250 mg/dL [>13·9 mmol/L], p=0·04 for >300 mg/dL [>16·6 mmol/L], and p=0·02 for the area under the curve for 180 mg/dL [10·0 mmol/L]), but also an increase in CGM-measured hypoglycaemia (p=0·0001 for 1c change from baseline to 28 weeks was 0·3% (SD 0·9; 3·3 mmol/mol [SD 9·8]) in the CGM plus CSII group and 0·1% (0·4; 1·1 mmol/mol [4·4]) in the CGM plus MDI group (p=0·32). Severe hypoglycaemia occurred in one participant in the CGM plus MDI group, and diabetic ketoacidosis and severe hyperglycaemia occurred in one participant each in the CGM plus CSII group. Interpretation Our findings show that glycaemic control measured by time in the glucose range of 70–180 mg/dL (3·9–10·0 mmol/L) is improved by initiation of CSII in adults with type 1 diabetes. However, biochemical hypoglycaemia also was increased in the study, which will be important to consider when incorporating these results into clinical practice. Funding Dexcom.

A Monte Carlo simulation of simultaneous approaches performed by two transport category aircraft from the final approach fix to a pair of closely spaced parallel runways was conducted to explore the aft boundary of the safe zone in which separation assurance and wake avoidance are provided. The simulation included variations in runway centerline separation, initial longitudinal spacing of the aircraft, crosswind speed, and aircraft speed during the approach. The data from the simulation showed that the majority of the wake encounters occurred near or over the runway and the aft boundaries of the safe zones were identified for all simulation conditions.

The predominant melodic source, frequently the singing voice, is an important component of musical signals. In this paper, we describe a method for extracting the predominant source and corresponding melody from ldquoreal-worldrdquo polyphonic music. The proposed method is inspired by ideas from computational auditory scene analysis. We formulate predominant melodic source tracking and formation as a graph partitioning problem and solve it using the normalized cut which is a global criterion for segmenting graphs that has been used in computer vision. Sinusoidal modeling is used as the underlying representation. A novel harmonicity cue which we term harmonically wrapped peak similarity is introduced. Experimental results supporting the use of this cue are presented. In addition, we show results for automatic melody extraction using the proposed approach.

Clustering based on the normalized cut criterion, and more generally, spectral clustering methods, are techniques originally proposed to model perceptual grouping tasks, such as image segmentation in computer vision. In this work, it is shown how such techniques can be applied to the problem of dominant melodic source separation in polyphonic music audio signals. One of the main advantages of this approach is the ability to incorporate mutiple perceptually‐inspired grouping criteria into a single framework without requiring multiple processing stages, as many existing computational auditory science analysis approaches do. Experimental results for several tasks, including dominant melody pitch detection, are presented. The system is based on a sinusoidal modeling analysis front‐end. A novel similarity cue based on harmonicity (harmonically‐wrapped peak similariy) is also introduced. The proposed system is data‐driven (i.e., requires no prior knowledge about the extracted source), causal, robust, practical, and efficient (close to real‐time on a fast computer). Although a specific implementation is presented, one of the main advantages of the proposed approach is its ability to utilize different analysis front‐ends and grouping criteria in a straightforward manner.