Visualization of causation in social-ecological systems

In social-ecological systems (SES), where social and ecological processes are intertwined, phenomena are usually complex and involve multiple interdependent causes. Figuring out causal relationships is thus challenging but needed to better understand and then affect or manage such systems. One important and widely used tool to identify and communicate causal relationships is visualization. Here, we present several common visualization types: diagrams of objects and arrows, X-Y plots, and X-Y-Z plots, and discuss them in view of the particular challenges of visualizing causation in complex systems such as SES. We use a simple demonstration model to create and compare exemplary visualizations and add more elaborate examples from the literature. This highlights implicit strengths and limitations of widely used visualization types and facilitates adequate choices when visualizing causation in SES. Thereupon, we recommend further suitable ways to account for complex causation, such as figures with multiple panels, or merging different visualization types in one figure. This provides caveats against oversimplifications. Yet, any single figure can rarely capture all relevant causal relationships in an SES. We therefore need to focus on specific questions, phenomena, or subsystems, and often also on specific causes and effects that shall be visualized. Our recommendations allow for selecting and combining visualizations such that they complement each other, support comprehensive understanding, and do justice to the existing complexity in SES. This lets visualizations realize their potential and play an important role in identifying and communicating causation.Peer reviewe

Veterans and Agent Orange: Update 11 (2018) (2018)

Contents ACRONYMS AND ABBREVIATIONS xvii SUMMARY 1 1 INTRODUCTION 17 Previous Veterans and Agent Orange Reports, 18 Charge to the Committee, 19 Information Gathering, 20 Organization of the Report, 21 2 BACKGROUND 25 The Current Population of Vietnam Veterans,25 Military Use of Herbicides in Vietnam, 27 Exposure of Different Groups of Vietnam Veterans, 30 Characterizing Exposure, 38 Determining Increased Risk in Vietnam Veterans, 4

Progress in Classical and Quantum Variational Principles

We review the development and practical uses of a generalized Maupertuis least action principle in classical mechanics, in which the action is varied under the constraint of fixed mean energy for the trial trajectory. The original Maupertuis (Euler-Lagrange) principle constrains the energy at every point along the trajectory. The generalized Maupertuis principle is equivalent to Hamilton's principle. Reciprocal principles are also derived for both the generalized Maupertuis and the Hamilton principles. The Reciprocal Maupertuis Principle is the classical limit of Schr\"{o}dinger's variational principle of wave mechanics, and is also very useful to solve practical problems in both classical and semiclassical mechanics, in complete analogy with the quantum Rayleigh-Ritz method. Classical, semiclassical and quantum variational calculations are carried out for a number of systems, and the results are compared. Pedagogical as well as research problems are used as examples, which include nonconservative as well as relativistic systems

Measuring the dynamic mechanical response of hydrated mouse bone by nanoindentation

This study demonstrates a novel approach to characterizing hydrated bone's viscoelastic behavior at lamellar length scales using dynamic indentation techniques. We studied the submicron-level viscoelastic response of bone tissue from two different inbred mouse strains, A/J and B6, with known differences in whole bone and tissue-level mechanical properties. Our results show that bone having a higher collagen content or a lower mineral-to-matrix ratio demonstrates a trend towards a larger viscoelastic response. When normalized for anatomical location relative to biological growth patterns in the antero-medial (AM) cortex, bone tissue from B6 femora, known to have a lower mineral-to-matrix ratio, is shown to exhibit a significantly higher viscoelastic response compared to A/J tissue. Newer bone regions with a higher collagen content (closer to the endosteal edge of the AM cortex) showed a trend towards a larger viscoelastic response. Our study demonstrates the feasibility of this technique for analyzing local composition-property relationships in bone. Further, this technique of viscoelastic nanoindentation mapping of the bone surface at these submicron length scales is shown to be highly advantageous in studying subsurface features, such as porosity, of wet hydrated biological specimens, which are difficult to identify using other methods

The Temporal Winner-Take-All Readout

How can the central nervous system make accurate decisions about external stimuli at short times on the basis of the noisy responses of nerve cell populations? It has been suggested that spike time latency is the source of fast decisions. Here, we propose a simple and fast readout mechanism, the temporal Winner-Take-All (tWTA), and undertake a study of its accuracy. The tWTA is studied in the framework of a statistical model for the dynamic response of a nerve cell population to an external stimulus. Each cell is characterized by a preferred stimulus, a unique value of the external stimulus for which it responds fastest. The tWTA estimate for the stimulus is the preferred stimulus of the cell that fired the first spike in the entire population. We then pose the questions: How accurate is the tWTA readout? What are the parameters that govern this accuracy? What are the effects of noise correlations and baseline firing? We find that tWTA sensitivity to the stimulus grows algebraically fast with the number of cells in the population, N, in contrast to the logarithmic slow scaling of the conventional rate-WTA sensitivity with N. Noise correlations in first-spike times of different cells can limit the accuracy of the tWTA readout, even in the limit of large N, similar to the effect that has been observed in population coding theory. We show that baseline firing also has a detrimental effect on tWTA accuracy. We suggest a generalization of the tWTA, the n-tWTA, which estimates the stimulus by the identity of the group of cells firing the first n spikes and show how this simple generalization can overcome the detrimental effect of baseline firing. Thus, the tWTA can provide fast and accurate responses discriminating between a small number of alternatives. High accuracy in estimation of a continuous stimulus can be obtained using the n-tWTA

Stroke Rehabilitation Reaches a Threshold

Motor training with the upper limb affected by stroke partially reverses the loss of cortical representation after lesion and has been proposed to increase spontaneous arm use. Moreover, repeated attempts to use the affected hand in daily activities create a form of practice that can potentially lead to further improvement in motor performance. We thus hypothesized that if motor retraining after stroke increases spontaneous arm use sufficiently, then the patient will enter a virtuous circle in which spontaneous arm use and motor performance reinforce each other. In contrast, if the dose of therapy is not sufficient to bring spontaneous use above threshold, then performance will not increase and the patient will further develop compensatory strategies with the less affected hand. To refine this hypothesis, we developed a computational model of bilateral hand use in arm reaching to study the interactions between adaptive decision making and motor relearning after motor cortex lesion. The model contains a left and a right motor cortex, each controlling the opposite arm, and a single action choice module. The action choice module learns, via reinforcement learning, the value of using each arm for reaching in specific directions. Each motor cortex uses a neural population code to specify the initial direction along which the contralateral hand moves towards a target. The motor cortex learns to minimize directional errors and to maximize neuronal activity for each movement. The derived learning rule accounts for the reversal of the loss of cortical representation after rehabilitation and the increase of this loss after stroke with insufficient rehabilitation. Further, our model exhibits nonlinear and bistable behavior: if natural recovery, motor training, or both, brings performance above a certain threshold, then training can be stopped, as the repeated spontaneous arm use provides a form of motor learning that further bootstraps performance and spontaneous use. Below this threshold, motor training is “in vain”: there is little spontaneous arm use after training, the model exhibits learned nonuse, and compensatory movements with the less affected hand are reinforced. By exploring the nonlinear dynamics of stroke recovery using a biologically plausible neural model that accounts for reversal of the loss of motor cortex representation following rehabilitation or the lack thereof, respectively, we can explain previously hard to reconcile data on spontaneous arm use in stroke recovery. Further, our threshold prediction could be tested with an adaptive train–wait–train paradigm: if spontaneous arm use has increased in the “wait” period, then the threshold has been reached, and rehabilitation can be stopped. If spontaneous arm use is still low or has decreased, then another bout of rehabilitation is to be provided

Leveraging human capital to reduce maternal mortality in India: enhanced public health system or public-private partnership?

Developing countries are currently struggling to achieve the Millennium Development Goal Five of reducing maternal mortality by three quarters between 1990 and 2015. Many health systems are facing acute shortages of health workers needed to provide improved prenatal care, skilled birth attendance and emergency obstetric services – interventions crucial to reducing maternal death. The World Health Organization estimates a current deficit of almost 2.4 million doctors, nurses and midwives. Complicating matters further, health workforces are typically concentrated in large cities, while maternal mortality is generally higher in rural areas. Additionally, health care systems are faced with shortages of specialists such as anaesthesiologists, surgeons and obstetricians; a maldistribution of health care infrastructure; and imbalances between the public and private health care sectors. Increasingly, policy-makers have been turning to human resource strategies to cope with staff shortages. These include enhancement of existing work roles; substitution of one type of worker for another; delegation of functions up or down the traditional role ladder; innovation in designing new jobs;transfer or relocation of particular roles or services from one health care sector to another. Innovations have been funded through state investment, public-private partnerships and collaborations with nongovernmental organizations and quasi-governmental organizations such as the World Bank. This paper focuses on how two large health systems in India – Gujarat and Tamil Nadu – have successfully applied human resources strategies in uniquely different contexts to the challenges of achieving Millennium Development Goal Five