Identifying Unmet Needs: Problems that Need Solutions

Invention is not an innate skill available to only a select few; it can be learned. Defining the need is the first step to determining the solution. A need statement helps define the problem concisely. Need specification is critical to defining the attributes required for device success. Invest in ideas that have the best chance of success by considering the market size, reimbursement pathways, and technology gaps. An algorithmic approach can be used in the stages of invention

Recurrent flow patterns as a basis for turbulence: predicting statistics from structures

A dynamical systems approach to turbulence envisions the flow as a trajectory through a high-dimensional state space transiently visiting the neighbourhoods of unstable simple invariant solutions (E. Hopf, Commun. Appl. Maths 1, 303, 1948). The hope has always been to turn this appealing picture into a predictive framework where the statistics of the flow follows from a weighted sum of the statistics of each simple invariant solution. Two outstanding obstacles have prevented this goal from being achieved: (1) paucity of known solutions and (2) the lack of a rational theory for predicting the required weights. Here we describe a method to substantially solve these problems, and thereby provide the first compelling evidence that the PDFs of a fully developed turbulent flow can be reconstructed with a set of unstable periodic orbits. Our new method for finding solutions uses automatic differentiation, with high-quality guesses constructed by minimising a trajectory-dependent loss function. We use this approach to find hundreds of new solutions in turbulent, two-dimensional Kolmogorov flow. Robust statistical predictions are then computed by learning weights after converting a turbulent trajectory into a Markov chain for which the states are individual solutions, and the nearest solution to a given snapshot is determined using a deep convolutional autoencoder. To our knowledge, this is the first time the PDFs of a spatio-temporally-chaotic system have been successfully reproduced with a set of simple invariant states, and provides a fascinating connection between self-sustaining dynamical processes and the more well-known statistical properties of turbulence

Exact coherent structures in two-dimensional turbulence identified with convolutional autoencoders

Convolutional autoencoders are used to deconstruct the changing dynamics of two-dimensional Kolmogorov flow as $Re$ is increased from weakly chaotic flow at $Re=40$ to a chaotic state dominated by a domain-filling vortex pair at $Re=400$. The highly accurate embeddings allow us to visualise the evolving structure of state space and are interpretable using `latent Fourier analysis' (Page {\em et. al.}, \emph{Phys. Rev. Fluids} \textbf{6}, 2021). Individual latent Fourier modes decode into vortical structures with a streamwise lengthscale controlled by the latent wavenumber, $l$, with only a small number $l \lesssim 8$ required to accurately represent the flow. Latent Fourier projections reveal a detached class of bursting events at $Re=40$ which merge with the low-dissipation dynamics as $Re$ is increased to $100$. We use doubly- ($l=2$) or triply- ($l=3$) periodic latent Fourier modes to generate guesses for UPOs (unstable periodic orbits) associated with high-dissipation events. While the doubly-periodic UPOs are representative of the high-dissipation dynamics at $Re=40$, the same class of UPOs move away from the attractor at $Re=100$ -- where the associated bursting events typically involve larger-scale ($l=1$) structure too. At $Re=400$ an entirely different embedding structure is formed within the network in which no distinct representations of small-scale vortices are observed; instead the network embeds all snapshots based around a large-scale template for the condensate. We use latent Fourier projections to find an associated `large-scale' UPO which we believe to be a finite-$Re$ continuation of a solution to the Euler equations

Information flow and optimization in transcriptional control

In the simplest view of transcriptional regulation, the expression of a gene is turned on or off by changes in the concentration of a transcription factor (TF). We use recent data on noise levels in gene expression to show that it should be possible to transmit much more than just one regulatory bit. Realizing this optimal information capacity would require that the dynamic range of TF concentrations used by the cell, the input/output relation of the regulatory module, and the noise levels of binding and transcription satisfy certain matching relations. This parameter-free prediction is in good agreement with recent experiments on the Bicoid/Hunchback system in the early Drosophila embryo, and this system achieves ~90% of its theoretical maximum information transmission.Comment: 5 pages, 4 figure

How do Malawian women rate the quality of maternal and newborn care? Experiences and perceptions of women in the central and southern regions

Background: While perceived quality of care is now widely recognized to influence health service utilization, limited research has been conducted to explore and measure perceived quality of care using quantitative tools. Our objective was to measure women’s perceived quality of maternal and newborn care using a composite scale and to identify individual and service delivery factors associated with such perceptions in Malawi. Methods: We conducted a cross-sectional survey in selected health facilities from March to May 2013. Exit interviews were conducted with 821 women convenience sampled at antenatal, delivery, and postnatal clinics using structured questionnaires. Experiences and the corresponding perceived quality of care were measured using a composite perception scale based on 27 items, clustered around three dimensions of care: interpersonal relations, conditions of the consultation and delivery rooms, and nursing care services. Statements reflecting the 27 items were read aloud and the women were asked to rate the quality of care received on a visual scale of 1 to 10 (10 being the highest score). For each dimension, an aggregate score was calculated using the un-weighted item means, representing three outcome variables. Descriptive statistics were used to display distribution of explanatory variables and one-way analysis of variance was used to analyse bivariate associations between the explanatory and the outcome variables. Results: A high perceived quality of care rating was observed on interpersonal relations, conditions of the examination rooms and nursing care services with an overall mean score of 9/10. Self-introduction by the health worker, explanation of examination procedures, consent seeking, encouragement to ask questions, confidentiality protection and being offered to have a guardian during delivery were associated with a high quality rating of interpersonal relations for antenatal and delivery care services. Being literate, never experienced a still birth and, first ANC visit were associated with a high quality rating of room conditions for antenatal care service. Conclusions: The study highlights some of the multiple factors associated with perceived quality of care. We conclude that proper interventions or practices and policies should consider these factors when making quality improvements

Self-Organization, Layered Structure, and Aggregation Enhance Persistence of a Synthetic Biofilm Consortium

Microbial consortia constitute a majority of the earth’s biomass, but little is known about how these cooperating communities persist despite competition among community members. Theory suggests that non-random spatial structures contribute to the persistence of mixed communities; when particular structures form, they may provide associated community members with a growth advantage over unassociated members. If true, this has implications for the rise and persistence of multi-cellular organisms. However, this theory is difficult to study because we rarely observe initial instances of non-random physical structure in natural populations. Using two engineered strains of Escherichia coli that constitute a synthetic symbiotic microbial consortium, we fortuitously observed such spatial self-organization. This consortium forms a biofilm and, after several days, adopts a defined layered structure that is associated with two unexpected, measurable growth advantages. First, the consortium cannot successfully colonize a new, downstream environment until it selforganizes in the initial environment; in other words, the structure enhances the ability of the consortium to survive environmental disruptions. Second, when the layered structure forms in downstream environments the consortium accumulates significantly more biomass than it did in the initial environment; in other words, the structure enhances the global productivity of the consortium. We also observed that the layered structure only assembles in downstream environments that are colonized by aggregates from a previous, structured community. These results demonstrate roles for self-organization and aggregation in persistence of multi-cellular communities, and also illustrate a role for the techniques of synthetic biology in elucidating fundamental biological principles

Exploiting the emergent nature of mixed methods designs: insights from a mixed methods impact evaluation in Malawi.

The application of mixed methods in Health Policy and Systems Research (HPSR) has expanded remarkably. Nevertheless, a recent review has highlighted how many mixed methods studies do not conceptualize the quantitative and the qualitative component as part of a single research effort, failing to make use of integrated approaches to data collection and analysis. More specifically, current mixed methods studies rarely rely on emergent designs as a specific feature of this methodological approach. In our work, we postulate that explicitly acknowledging the emergent nature of mixed methods research by building on a continuous exchange between quantitative and qualitative strains of data collection and analysis leads to a richer and more informative application in the field of HPSR. We illustrate our point by reflecting on our own experience conducting the mixed methods impact evaluation of a complex health system intervention in Malawi, the Results Based Financing for Maternal and Newborn Health Initiative. We describe how in the light of a contradiction between the initial set of quantitative and qualitative findings, we modified our design multiple times to include additional sources of quantitative and qualitative data and analytical approaches. To find an answer to the initial riddle, we made use of household survey data, routine health facility data, and multiple rounds of interviews with both healthcare workers and service users. We highlight what contextual factors made it possible for us to maintain the high level of methodological flexibility that ultimately allowed us to solve the riddle. This process of constant reiteration between quantitative and qualitative data allowed us to provide policymakers with a more credible and comprehensive picture of what dynamics the intervention had triggered and with what effects, in a way that we would have never been able to do had we kept faithful to our original mixed methods design

Design of an impact evaluation using a mixed methods model – an explanatory assessment of the effects of results-based financing mechanisms on maternal healthcare services in Malawi

Background: In this article we present a study design to evaluate the causal impact of providing supply-side performance-based financing incentives in combination with a demand-side cash transfer component on equitable access to and quality of maternal and neonatal healthcare services. This intervention is introduced to selected emergency obstetric care facilities and catchment area populations in four districts in Malawi. We here describe and discuss our study protocol with regard to the research aims, the local implementation context, and our rationale for selecting a mixed methods explanatory design with a quasi-experimental quantitative component. Design: The quantitative research component consists of a controlled pre- and post-test design with multiple post-test measurements. This allows us to quantitatively measure ‘equitable access to healthcare services’ at the community level and ‘healthcare quality’ at the health facility level. Guided by a theoretical framework of causal relationships, we determined a number of input, process, and output indicators to evaluate both intended and unintended effects of the intervention. Overall causal impact estimates will result from a difference-in-difference analysis comparing selected indicators across intervention and control facilities/catchment populations over time. To further explain heterogeneity of quantitatively observed effects and to understand the experiential dimensions of financial incentives on clients and providers, we designed a qualitative component in line with the overall explanatory mixed methods approach. This component consists of in-depth interviews and focus group discussions with providers, service user, non-users, and policy stakeholders. In this explanatory design comprehensive understanding of expected and unexpected effects of the intervention on both access and quality will emerge through careful triangulation at two levels: across multiple quantitative elements and across quantitative and qualitative elements. Discussion Combining a traditional quasi-experimental controlled pre- and post-test design with an explanatory mixed methods model permits an additional assessment of organizational and behavioral changes affecting complex processes. Through this impact evaluation approach, our design will not only create robust evidence measures for the outcome of interest, but also generate insights on how and why the investigated interventions produce certain intended and unintended effects and allows for a more in-depth evaluation approach

Enhancing the Connectedness Between Undergraduate Students, Faculty, and the DPT Program Within the Same Institution

Background Minimal data exists on optimizing the retention of undergraduate students to the DPT program within the same academic institution. Many DPT programs provide information and resources for applicants to explain admission requirements and overview the program curriculum. Purpose Identify and understand undergraduate student and faculty member’s knowledge, perceptions and resources regarding the DPT program within the same institution. Develop resources and tools to enhance the connectedness within the undergraduate and graduate DPT program in the same institution and fill identified gaps. Participants 41 undergraduate Science and Kinesiology students 6 Kinesiology faculty members 5 Science faculty members 4 active DPT students who attended CSP as undergraduates 18 active DPT students Methods Qualitative data collection via surveys and focus groups Triangulation of data, coding and development of themes Action research strategies used to create tangible products and resources Results Majority of undergraduate students choose their major in high school or freshman year of college. Undergraduate students expressed a lack of resources and understanding of the DPT program within their institution (Figure 1). Undergraduate students expressed desire for admission requirements, informational meetings and mentorship (Figure 2). Faculty echoed lack of resources and provided ideas for potential products. Conclusion Themes emerged that students and faculty were provided with little information regarding the DPT program within their home institution. Analysis of student and staff focus groups, questionnaires, and interviews, determined the need for a variety of products including: Program resource guide, Mentorship program, Social media (Facebook & Instagram), On campus marketing, and informational events. Implications Designing and implementing products may help bridge the gap between the undergraduate and graduate populations in the same institution. Future research will examine the impact of products and to also determine if graduate applications within institution increased. Future phases may include admissions, undergraduate student advisors and other CSP undergraduate departments