The Prospects for Sustained Growth in Africa: Benchmarking the Constraints

A dozen countries had weak institutions in 1960 and yet sustained high rates of growth subsequently. We use data on their characteristics early in the growth process to create benchmarks with which to evaluate potential constraints on sustained growth for sub-Saharan Africa. This analysis suggests that what are usually regarded as first-order problems -- broad institutions, macroeconomic stability, trade openness, education, and inequality -- may not nowbe binding constraints in Africa, although the extent of ill-health, internal conflict, and societal fractionalization do stand out as problems in contemporary Africa. A key question is to what extent Africa can rely on manufactured exports as a mode of "escape from underdevelopment," a strategy successfully deployed by almost all the benchmark countries. The benchmarking comparison specifically raises two key concerns as far as a development strategy based on expanding exports of manufactures is concerned: micro-level institutions that affect the costs of exporting, and the level of the real exchange rate -- especially the need to avoid overvaluation.

Eosinophilic bronchitis, eosinophilic granuloma, and eosinophilic bronchopneumopathy in 75 dogs (2006-2016).

BackgroundEosinophilic lung disease is a poorly understood inflammatory airway disease that results in substantial morbidity.ObjectiveTo describe clinical findings in dogs with eosinophilic lung disease defined on the basis of radiographic, bronchoscopic, and bronchoalveolar lavage fluid (BAL) analysis. Categories included eosinophilic bronchitis (EB), eosinophilic granuloma (EG), and eosinophilic bronchopneumopathy (EBP).AnimalsSeventy-five client owned dogs.MethodsMedical records were retrospectively reviewed for dogs with idiopathic BAL fluid eosinophilia. Information abstracted included duration and nature of clinical signs, bronchoscopic findings, and laboratory data. Thoracic radiographs were evaluated for the pattern of infiltrate, bronchiectasis, and lymphadenomegaly.ResultsThoracic radiographs were normal or demonstrated a bronchial pattern in 31 dogs assigned a diagnosis of EB. Nine dogs had intraluminal mass lesions and were bronchoscopically diagnosed with EG. The remaining 35 dogs were categorized as having EBP based on radiographic changes, yellow green mucus in the airways, mucosal changes, and airway collapse. Age and duration of cough did not differ among groups. Dogs with EB were less likely to have bronchiectasis or peripheral eosinophilia, had lower total nucleated cell count in BAL fluid, and lower percentage of eosinophils in BAL fluid compared to dogs in the other 2 groups. In contrast to previous reports, prolonged survival (>55 months) was documented in dogs with EG.Conclusions and clinical importanceDogs with eosinophilic lung disease can be categorized based on imaging, bronchoscopic and BAL fluid cytologic findings. Further studies are needed to establish response to treatment in these groups

Drugs, Crime, and the Epigenetics of Hedonic Allostasis

Researchers have found staggering numbers of drug addicts among incarcerated populations and have conceded that drug abuse is an important correlate of deviant behavior, but few included an understanding of the biological process leading to drug addiction. Chronic drug abuse and criminality are housed within a much broader propensity of some individuals to engage in a variety of antisocial behaviors, and this article clarifies the link and proposed shared mechanisms between criminal behavior and drug abuse through a molecular-genetic and neurobiological lens. Multiple genes, enzymes, and transcription factors are involved in drug addition, with over 100 genes known to be changed with repeated cocaine exposure. The epigenetics of drug addiction, with a specific emphasis on the addiction of cocaine, are brought under examination here. The epigenetic processes of methylation and acetylation are described and their long term effects are illustrated within the processes of allostatic changes to the brain. After the establishment of the rudiments of epigenetic operation and their effects, a discussion is presented on the opponent process and incentive-sensitization models of drug addiction and how all of these factors are impacted by socio-cultural variables

Implementation of a Goal-Based Systems Engineering Process Using the Systems Modeling Language (SysML)

Building upon the purpose, theoretical approach, and use of a Goal-Function Tree (GFT) being presented by Dr. Stephen B. Johnson, described in a related Infotech 2013 ISHM abstract titled "Goal-Function Tree Modeling for Systems Engineering and Fault Management", this paper will describe the core framework used to implement the GFTbased systems engineering process using the Systems Modeling Language (SysML). These two papers are ideally accepted and presented together in the same Infotech session. Statement of problem: SysML, as a tool, is currently not capable of implementing the theoretical approach described within the "Goal-Function Tree Modeling for Systems Engineering and Fault Management" paper cited above. More generally, SysML's current capabilities to model functional decompositions in the rigorous manner required in the GFT approach are limited. The GFT is a new Model-Based Systems Engineering (MBSE) approach to the development of goals and requirements, functions, and its linkage to design. As a growing standard for systems engineering, it is important to develop methods to implement GFT in SysML. Proposed Method of Solution: Many of the central concepts of the SysML language are needed to implement a GFT for large complex systems. In the implementation of those central concepts, the following will be described in detail: changes to the nominal SysML process, model view definitions and examples, diagram definitions and examples, and detailed SysML construct and stereotype definitions

Goal-Function Tree Modeling for Systems Engineering and Fault Management

The draft NASA Fault Management (FM) Handbook (2012) states that Fault Management (FM) is a "part of systems engineering", and that it "demands a system-level perspective" (NASAHDBK- 1002, 7). What, exactly, is the relationship between systems engineering and FM? To NASA, systems engineering (SE) is "the art and science of developing an operable system capable of meeting requirements within often opposed constraints" (NASA/SP-2007-6105, 3). Systems engineering starts with the elucidation and development of requirements, which set the goals that the system is to achieve. To achieve these goals, the systems engineer typically defines functions, and the functions in turn are the basis for design trades to determine the best means to perform the functions. System Health Management (SHM), by contrast, defines "the capabilities of a system that preserve the system's ability to function as intended" (Johnson et al., 2011, 3). Fault Management, in turn, is the operational subset of SHM, which detects current or future failures, and takes operational measures to prevent or respond to these failures. Failure, in turn, is the "unacceptable performance of intended function." (Johnson 2011, 605) Thus the relationship of SE to FM is that SE defines the functions and the design to perform those functions to meet system goals and requirements, while FM detects the inability to perform those functions and takes action. SHM and FM are in essence "the dark side" of SE. For every function to be performed (SE), there is the possibility that it is not successfully performed (SHM); FM defines the means to operationally detect and respond to this lack of success. We can also describe this in terms of goals: for every goal to be achieved, there is the possibility that it is not achieved; FM defines the means to operationally detect and respond to this inability to achieve the goal. This brief description of relationships between SE, SHM, and FM provide hints to a modeling approach to provide formal connectivity between the nominal (SE), and off-nominal (SHM and FM) aspects of functions and designs. This paper describes a formal modeling approach to the initial phases of the development process that integrates the nominal and off-nominal perspectives in a model that unites SE goals and functions of with the failure to achieve goals and functions (SHM/FM). This methodology and corresponding model, known as a Goal-Function Tree (GFT), provides a means to represent, decompose, and elaborate system goals and functions in a rigorous manner that connects directly to design through use of state variables that translate natural language requirements and goals into logical-physical state language. The state variable-based approach also provides the means to directly connect FM to the design, by specifying the range in which state variables must be controlled to achieve goals, and conversely, the failures that exist if system behavior go out-of-range. This in turn allows for the systems engineers and SHM/FM engineers to determine which state variables to monitor, and what action(s) to take should the system fail to achieve that goal. In sum, the GFT representation provides a unified approach to early-phase SE and FM development. This representation and methodology has been successfully developed and implemented using Systems Modeling Language (SysML) on the NASA Space Launch System (SLS) Program. It enabled early design trade studies of failure detection coverage to ensure complete detection coverage of all crew-threatening failures. The representation maps directly both to FM algorithm designs, and to failure scenario definitions needed for design analysis and testing. The GFT representation provided the basis for mapping of abort triggers into scenarios, both needed for initial, and successful quantitative analyses of abort effectiveness (detection and response to crew-threatening events)

Meta-analysis of glioblastoma multiforme versus anaplastic astrocytoma identifies robust gene markers

<p>Abstract</p> <p>Background</p> <p>Anaplastic astrocytoma (AA) and its more aggressive counterpart, glioblastoma multiforme (GBM), are the most common intrinsic brain tumors in adults and are almost universally fatal. A deeper understanding of the molecular relationship of these tumor types is necessary to derive insights into the diagnosis, prognosis, and treatment of gliomas. Although genomewide profiling of expression levels with microarrays can be used to identify differentially expressed genes between these tumor types, comparative studies so far have resulted in gene lists that show little overlap.</p> <p>Results</p> <p>To achieve a more accurate and stable list of the differentially expressed genes and pathways between primary GBM and AA, we performed a meta-analysis using publicly available genome-scale mRNA data sets. There were four data sets with sufficiently large sample sizes of both GBMs and AAs, all of which coincidentally used human U133 platforms from Affymetrix, allowing for easier and more precise integration of data. After scoring genes and pathways within each data set, we combined the statistics across studies using the nonparametric rank sum method to identify the features that differentiate GBMs and AAs. We found >900 statistically significant probe sets after correction for multiple testing from the >22,000 tested. We also used the rank sum approach to select >20 significant Biocarta pathways after correction for multiple testing out of >175 pathways examined. The most significant pathway was the hypoxia-inducible factor (HIF) pathway. Our analysis suggests that many of the most statistically significant genes work together in a <it>HIF1A</it>/<it>VEGF</it>-regulated network to increase angiogenesis and invasion in GBM when compared to AA.</p> <p>Conclusion</p> <p>We have performed a meta-analysis of genome-scale mRNA expression data for 289 human malignant gliomas and have identified a list of >900 probe sets and >20 pathways that are significantly different between GBM and AA. These feature lists could be utilized to aid in diagnosis, prognosis, and grade reduction of high-grade gliomas and to identify genes that were not previously suspected of playing an important role in glioma biology. More generally, this approach suggests that combined analysis of existing data sets can reveal new insights and that the large amount of publicly available cancer data sets should be further utilized in a similar manner.</p