Forests have long been locations of contestation between people and state bureaucracies, and among the knowledge frameworks of local users, foresters, ecologists, and conservationists. An essential framing of the debate has been between the categories of primary and secondary forest. In this introduction to a collection of papers that address the questions of what basis, in what sense, and for whom primary forest is ‘primary’ and secondary forest is ‘secondary,’ and whether these are useful distinctions, we outline this debate and propose a new conceptual model that departs from the simple binary of primary and secondary forests. Rather, we propose that attention should be given to the nature of the disturbance that may alter forest ecology, the forms of regeneration that follow, and the governance context within which this takes place.Unprecedented non-pharmaceutical interventions targeted to curb the spread of COVID-19 exerted a dramatic impact on the global economy and financial markets. This study is the first attempt to investigate the influence of these government policy responses on global stock market liquidity. To this end, we examine daily data from 49 countries for the period January-April 2020. We demonstrate that the impact of the interventions is limited in scale and scope. Workplace and school closures deteriorate liquidity in emerging markets, while information campaigns on the novel coronavirus facilitate trading activity.A bottom-up multi-scale modeling approach is used to develop an Integrated Computational Materials Engineering (ICME) framework for carbon fiber reinforced polymer (CFRP) composites, which has the potential to reduce development to deployment lead time for structural applications in lightweight vehicles. In this work, we develop and integrate computational models comprising of four size scales to fully describe and characterize three types of CFRP composites. In detail, the properties of the interphase region are determined by an analytical gradient model and molecular dynamics analysis at the nano-scale, which is then incorporated into micro-scale unidirectional (UD) representative volume element (RVE) models to characterize the failure strengths and envelopes of UD CFRP composites. Then, the results are leveraged to propose an elasto-plastic-damage constitutive law for UD composites to study the fiber tows of woven composites as well as the chips of sheet molding compound (SMC) composites. Subsequently, the failure mechanisms and failure strengths of woven and SMC composites are predicted by the meso-scale RVE models. Finally, building upon the models and results from lower scales, we show that a homogenized macro-scale model can capture the mechanical performance of a hat-section-shaped part under four-point bending. Along with the model integration, we will also demonstrate that the computational results are in good agreement with experiments conducted at different scales. The present study illustrates the potential and significance of integrated multi-scale computational modeling tools that can virtually evaluate the performance of CFRP composites and provide design guidance for CFRP composites used in structural applications.Understanding brain computation requires assembling a complete catalog of its architectural components. Although the brain is organized into several anatomical and functional regions, it is ultimately the neurons in every region that are responsible for cognition and behavior. Thus, classifying neuron types throughout the brain and quantifying the population sizes of distinct classes in different regions is a key subject of research in the neuroscience community. The total number of neurons in the brain has been estimated for multiple species, but the definition and population size of each neuron type are still open questions even in common model organisms the so called “cell census” problem. CRT0066101 clinical trial We propose a methodology that uses operations research principles to estimate the number of neurons in each type based on available information on their distinguishing properties. Thus, assuming a set of neuron type definitions, we provide a solution to the issue of assessing their relative proportions. Specifically, we present a three-step approach that includes literature search, equation generation, and numerical optimization. Solving computationally the set of equations generated by literature mining yields best estimates or most likely ranges for the number of neurons in each type. While this strategy can be applied towards any neural system, we illustrate its usage on the rodent hippocampus.Occupational training and credentialing requirements for direct care workers were in place for consumers’ health and safety, but their effects on job qualities and labor shortages in the direct care industry have been controversial. Using a nationally representative sample of psychiatric, nursing, and home health aides, a series of Average Treatment Effect models were analyzed to examine the effects of occupational credentials on various measures of job qualities. The findings revealed that credential-holding was related to higher annual earnings and increased probability of working full-time, year-round, and having access to employer-provided health insurance and retirement savings plans. The positive effects, however, were modest in size and suggested that, given the current wage and benefit levels for direct care workers, training and credential requirements cannot be the key to resolving job quality and labor shortage issues in the direct care industry. Implications of these findings and alternative ways to address the issues were discussed.Vitamin D is essential for bone health and is known to be involved in immunomodulation and cell proliferation. Vitamin D status remains a significant health issue worldwide. However, there has been no clear consensus on vitamin D deficiency and its measurement in serum, and clinical practice of vitamin D deficiency treatment remains inconsistent. The major circulating metabolite of vitamin D, 25-hydroxyvitamin D (25(OH)D), is widely used as a biomarker of vitamin D status. Other metabolic pathways are recognised as important to vitamin D function and measurement of other metabolites may become important in the future. The utility of free 25(OH)D rather than total 25(OH)D needs further assessment. Data used to estimate the vitamin D intake required to achieve a serum 25(OH)D concentration were drawn from individual studies which reported dose-response data. The studies differ in their choice of subjects, dose of vitamin D, frequency of dosing regimen and methods used for the measurement of 25(OH)D concentration.