Existing and Required Modeling Capabilities for Evaluating ATM Systems and Concepts

ATM systems throughout the world are entering a period of major transition and change. The combination of important technological developments and of the globalization of the air transportation industry has necessitated a reexamination of some of the fundamental premises of existing Air Traffic Management (ATM) concepts. New ATM concepts have to be examined, concepts that may place more emphasis on: strategic traffic management; planning and control; partial decentralization of decision-making; and added reliance on the aircraft to carry out strategic ATM plans, with ground controllers confined primarily to a monitoring and supervisory role. 'Free Flight' is a case in point. In order to study, evaluate and validate such new concepts, the ATM community will have to rely heavily on models and computer-based tools/utilities, covering a wide range of issues and metrics related to safety, capacity and efficiency. The state of the art in such modeling support is adequate in some respects, but clearly deficient in others. It is the objective of this study to assist in: (1) assessing the strengths and weaknesses of existing fast-time models and tools for the study of ATM systems and concepts and (2) identifying and prioritizing the requirements for the development of additional modeling capabilities in the near future. A three-stage process has been followed to this purpose: 1. Through the analysis of two case studies involving future ATM system scenarios, as well as through expert assessment, modeling capabilities and supporting tools needed for testing and validating future ATM systems and concepts were identified and described. 2. Existing fast-time ATM models and support tools were reviewed and assessed with regard to the degree to which they offer the capabilities identified under Step 1. 3 . The findings of 1 and 2 were combined to draw conclusions about (1) the best capabilities currently existing, (2) the types of concept testing and validation that can be carried out reliably with such existing capabilities and (3) the currently unavailable modeling capabilities that should receive high priority for near-term research and development. It should be emphasized that the study is concerned only with the class of 'fast time' analytical and simulation models. 'Real time' models, that typically involve humans-in-the-loop, comprise another extensive class which is not addressed in this report. However, the relationship between some of the fast-time models reviewed and a few well-known real-time models is identified in several parts of this report and the potential benefits from the combined use of these two classes of models-a very important subject-are discussed in chapters 4 and 7

The rise and fall of the ancient northern pike master sex-determining gene

The understanding of the evolution of variable sex determination mechanisms across taxa requires comparative studies among closely related species. Following the fate of a known master sex-determining gene, we traced the evolution of sex determination in an entire teleost order (Esociformes). We discovered that the northern pike (Esox lucius) master sex-determining gene originated from a 65 to 90 million-year-old gene duplication event and that it remained sex linked on undifferentiated sex chromosomes for at least 56 million years in multiple species. We identified several independent species- or population-specific sex determination transitions, including a recent loss of a Y chromosome. These findings highlight the diversity of evolutionary fates of master sex-determining genes and the importance of population demographic history in sex determination studies. We hypothesize that occasional sex reversals and genetic bottlenecks provide a non-adaptive explanation for sex determination transitions

The rise and fall of the ancient northern pike master sex determining gene

The understanding of the evolution of variable sex determination mechanisms across taxa requires comparative studies among closely related species. Following the fate of a known master sex-determining gene, we traced the evolution of sex determination in an entire teleost order (Esociformes). We discovered that the northern pike (Esox lucius) master sex-determining gene originated from a 65 to 90 million-year-old gene duplication event and that it remained sex-linked on undifferentiated sex chromosomes for at least 56 million years in multiple species. We identified several independent species- or population-specific sex determination transitions, including a recent loss of a Y-chromosome. These findings highlight the diversity of evolutionary fates of master sex-determining genes and the importance of population demographic history in sex determination studies. We hypothesize that occasional sex reversals and genetic bottlenecks provide a non-adaptive explanation for sex determination transitions

Credible Autocoding of Convex Optimization Algorithms

International audienceThe efficiency of modern optimization methods, coupled with increasing computational resources, has led to the possibility of real-time optimization algorithms acting in safety critical roles. There is a considerable body of mathematical proofs on on-line optimization programs which can be leveraged to assist in the development and verification of their implementation. In this paper, we demonstrate how theoretical proofs of real-time optimization algorithms can be used to describe functional properties at the level of the code, thereby making it accessible for the formal methods community. The running example used in this paper is a generic semi-definite programming (SDP) solver. Semi-definite programs can encode a wide variety of optimization problems and can be solved in polynomial time at a given accuracy. We describe a top-to-down approach that transforms a high-level analysis of the algorithm into useful code annotations. We formulate some general remarks about how such a task can be incorporated into a convex programming autocoder. We then take a first step towards the automatic verification of the optimization program by identifying key issues to be adressed in future work

Targeting the Lactate Transporter MCT1 in Endothelial Cells Inhibits Lactate-Induced HIF-1 Activation and Tumor Angiogenesis

Switching to a glycolytic metabolism is a rapid adaptation of tumor cells to hypoxia. Although this metabolic conversion may primarily represent a rescue pathway to meet the bioenergetic and biosynthetic demands of proliferating tumor cells, it also creates a gradient of lactate that mirrors the gradient of oxygen in tumors. More than a metabolic waste, the lactate anion is known to participate to cancer aggressiveness, in part through activation of the hypoxia-inducible factor-1 (HIF-1) pathway in tumor cells. Whether lactate may also directly favor HIF-1 activation in endothelial cells (ECs) thereby offering a new druggable option to block angiogenesis is however an unanswered question. In this study, we therefore focused on the role in ECs of monocarboxylate transporter 1 (MCT1) that we previously identified to be the main facilitator of lactate uptake in cancer cells. We found that blockade of lactate influx into ECs led to inhibition of HIF-1-dependent angiogenesis. Our demonstration is based on the unprecedented characterization of lactate-induced HIF-1 activation in normoxic ECs and the consecutive increase in vascular endothelial growth factor receptor 2 (VEGFR2) and basic fibroblast growth factor (bFGF) expression. Furthermore, using a variety of functional assays including endothelial cell migration and tubulogenesis together with in vivo imaging of tumor angiogenesis through intravital microscopy and immunohistochemistry, we documented that MCT1 blockers could act as bona fide HIF-1 inhibitors leading to anti-angiogenic effects. Together with the previous demonstration of MCT1 being a key regulator of lactate exchange between tumor cells, the current study identifies MCT1 inhibition as a therapeutic modality combining antimetabolic and anti-angiogenic activities

The effect of a preoperative subconjuntival injection of dexamethasone on blood–retinal barrier breakdown following scleral buckling retinal detachment surgery: a prospective randomized placebo-controlled double blind clinical trial

textabstractBackground: Blood-retinal barrier breakdown secondary to retinal detachment and retinal detachment repair is a factor in the pathogenesis of proliferative vitreoretinopathy (PVR). We wished to investigate whether an estimated 700 to 1000 ng/ml subretinal dexamethasone concentration at the time of surgery would decrease the blood-retinal barrier breakdown postoperatively. Methods: Prospective, placebo-controlled, double blind clinical trial. In 34 patients with rhegmatogenous retinal detachment scheduled for conventional scleral buckling retinal detachment surgery, a subconjunctival injection of 0.5 ml dexamethasone diphosphate (10 mg) or 0.5 ml placebo was given 5-6 hours before surgery. Differences in laser flare photometry (KOWA) measurements taken 1, 3 and 6 weeks after randomisation between dexamethasone and placebo were analysed using mixed model ANOVA, while correcting for the preoperative flare measurement. Results: Six patients did not complete the study, one because of recurrent detachment within 1 week, and five because they missed their postoperative laser flare visits. The use of dexamethasone resulted in a statistically significant decrease in laser flare measurements at the 1-week postoperative visit. Conclusion: The use of a preoperative subconjunctival injection of dexamethasone decreased 1-week postoperative blood-retina barrier breakdown in patients undergoing conventional scleral buckling retinal detachment surgery. This steroid priming could be useful as a part of a peri-operative regime that would aim at decreasing the incidence of PVR

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales

While wetlands are the largest natural source of methane (CH4) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by similar to 17 +/- 11 days, and lagged air and soil temperature by median values of 8 +/- 16 and 5 +/- 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4. At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.Peer reviewe

Gap-filling eddy covariance methane fluxes : Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting halfhourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).Peer reviewe