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Cover page of Reduced integration schemes in micromorphic computational homogenization of elastomeric mechanical metamaterials

Reduced integration schemes in micromorphic computational homogenization of elastomeric mechanical metamaterials

(2020)

Exotic behaviour of mechanical metamaterials often relies on an internal transformation of the underlying microstructure triggered by its local instabilities, rearrangements, and rotations. Depending on the presence and magnitude of such a transformation, effective properties of a metamaterial may change significantly. To capture this phenomenon accurately and efficiently, homogenization schemes are required that reflect microstructural as well as macro-structural instabilities, large deformations, and non-local effects. To this end, a micromorphic computational homogenization scheme has recently been developed, which employs the particular microstructural transformation as a non-local mechanism, magnitude of which is governed by an additional coupled partial differential equation. Upon discretizing the resulting problem it turns out that the macroscopic stiffness matrix requires integration of macro-element basis functions as well as their derivatives, thus calling for a higher-order integration rules. Because evaluation of constitutive law in multiscale schemes involves an expensive solution of a non-linear boundary value problem, computational efficiency can be improved by reducing the number of integration points. Therefore, the goal of this paper is to investigate reduced-order schemes in computational homogenization, with emphasis on the stability of the resulting elements. In particular, arguments for lowering the order of integration from the expensive mass-matrix to a cheaper stiffness-matrix equivalent are first outlined. An efficient one-point integration quadrilateral element is then introduced and proper hourglass stabilization discussed. Performance of the resulting set of elements is finally tested on a benchmark bending example, showing that we achieve accuracy comparable to the full quadrature rules.

Cover page of A qualitative examination of barriers against effective medical education and practices related to breastfeeding promotion and support in Lebanon.

A qualitative examination of barriers against effective medical education and practices related to breastfeeding promotion and support in Lebanon.

(2020)

Background: Insufficient breastfeeding promotion and support by physicians contribute to suboptimal breastfeeding rates globally. Understanding setting-specific barriers against breastfeeding promotion and support from the perspective of medical students and addressing those that can be modified through undergraduate medical education may help improve learning outcomes, medical practice, and ultimately health outcomes associated with breastfeeding.Objectives: We selected the underserved and under-supported public medical school in Lebanon to explore psychosocial, institutional, and societal barriers hindering effective preventative medicine practices using breastfeeding promotion and support as an exemplar case.Methods: One-on-one semi-structured interviews, each lasting around 60 min, were conducted with medical interns (in Med III and Med IV) at their training hospitals. Interviews were voice-recorded, transcribed verbatim, coded, and analyzed thematically based on Theory of Planned Behavior.Results: Interns (n= 49; 96% response rate) completed the study. Five major themes emerged addressing barriers at various levels. At the health care system level at large, interns identified the predominant focus on pathophysiology and treatment rather than on disease prevention and health promotion as a barrier. At the level of trainees and their education experiences, interns reported limited and optional clerkship training in obstetrics/gynecology and in neonatology which contributes to their insufficient knowledge and low self-efficacy. Competing financial interests from infant formula companies and social pressures to promote infant formula were identified as two main barriers at the level of physicians and clinical practice.Conclusions: Our work using breastfeeding as an exemplary case highlights how undergraduate medical education and its learning outcomes and how medical practices and patient behavior are highly intertwined with psychosocial, institutional, and social drivers and constraints. Re-evaluating the success of undergraduate medical curricula in light of overcoming these constraints and not only based on meeting national accreditation and certification guidelines might prove helpful in improving medical education and ultimately clinical practice.

Cover page of A fast algorithm for computing a matrix transform used to detect trends in noisy data

A fast algorithm for computing a matrix transform used to detect trends in noisy data

(2020)

A recently discovered universal rank-based matrix method to extract trends from noisy time series is described in [1] but the formula for the output matrix elements, implemented there as an open-access supplement MATLAB computer code, is ${\cal O}(N^4)$, with $N$ the matrix dimension. This can become prohibitively large for time series with hundreds of sample points or more. Based on recurrence relations, here we derive a much faster ${\cal O}(N^2)$ algorithm and provide code implementations in MATLAB and in open-source JULIA. In some cases one has the output matrix and needs to solve an inverse problem to obtain the input matrix. A fast algorithm and code for this companion problem, also based on the above recurrence relations, are given. Finally, in the narrower, but common, domains of (i) trend detection and (ii) parameter estimation of a linear trend, users require, not the individual matrix elements, but simply their accumulated mean value. For this latter case we provide a yet faster ${\cal O}(N)$ heuristic approximation that relies on a series of rank one matrices. These algorithms are illustrated on a time series of high energy cosmic rays with $N > 4 \times 10^4$. [1] Universal Rank-Order Transform to Extract Signals from Noisy Data, Glenn Ierley and Alex Kostinski, Phys. Rev. X 9 031039 (2019).

Cover page of Informative experimentation in intuitive science: Children select and learn from their own causal interventions.

Informative experimentation in intuitive science: Children select and learn from their own causal interventions.

(2020)

We investigated whether children preferentially select informative actions and make accurate inferences from the outcome of their own interventions in a causal learning task. Four- to six-year-olds were presented with a novel system composed of gears that could operate according to two possible causal structures (single or multiple cause). Given the choice between interventions (i.e., removing one of the two gears to observe the remaining gear in isolation), children demonstrated a clear preference for the action that revealed the true causal structure, and made subsequent causal judgments that were consistent with the outcome observed. Experiment 2 addressed the possibility that performance was driven by children's tendency to select an intervention that would produce a desirable effect (i.e., spinning gears), rather than to disambiguate the causal structure. These results replicate our initial findings in a context in which the informative action was less likely to produce a positive outcome than the uninformative one. Experiment 3 serves as a control demonstrating that children's success in the previous experiments is not due to their use of low-level strategies. We discuss these findings in terms of their significance for understanding the development of scientific reasoning and the role of self-directed actions in early causal learning.

Cover page of Proning in Non-Intubated (PINI) in Times of COVID-19: Case Series and a Review.

Proning in Non-Intubated (PINI) in Times of COVID-19: Case Series and a Review.

(2020)

It has been well known for decades that prone positioning (PP) improves oxygenation. However, it has gained widespread acceptance only in the last few years since studies have shown significant survival benefit. Many centers have established prone ventilation in their treatment algorithm for mechanically ventilated patients with severe acute respiratory distress syndrome (ARDS). Physiologically, PP should also benefit awake, non-intubated patients with acute hypoxemic respiratory failure. However, proning in non-intubated (PINI) patients did not gain any momentum until a few months ago when the Coronavirus disease 2019 (COVID-19) pandemic surged. A large number of sick patients overwhelmed the health care system, and many centers faced a dearth of ventilators. In addition, outcomes of patients placed on mechanical ventilation because of COVID-19 infection have been highly variable and often dismal. Hence, increased focus has shifted to using various strategies to prevent intubation, such as PINI. There is accumulating evidence that PINI is a low-risk intervention that can be performed even outside intensive care unit with minimal assistance and may prevent intubation in certain patients with ARDS. It can also be performed safely at smaller centers and, therefore, may reduce the patient transfer to larger institutions that are overwhelmed in the current crisis. We present a case series of 2 patients with acute hypoxemic respiratory failure who experienced significant improvements in oxygenation with PP. In addition, the physiology of PP is described, and concerns such as proning in obese and patient's anxiety are addressed; an educational pamphlet that may be useful for both patients and health care providers is provided.