A priori parameterisation of the CERES soil-crop models and tests against several European data sets

Mechanistic soil-crop models have become indispensable tools to investigate the effect of management practices on the productivity or environmental impacts of arable crops. Ideally these models may claim to be universally applicable because they simulate the major processes governing the fate of inputs such as fertiliser nitrogen or pesticides. However, because they deal with complex systems and uncertain phenomena, site-specific calibration is usually a prerequisite to ensure their predictions are realistic. This statement implies that some experimental knowledge on the system to be simulated should be available prior to any modelling attempt, and raises a tremendous limitation to practical applications of models. Because the demand for more general simulation results is high, modellers have nevertheless taken the bold step of extrapolating a model tested within a limited sample of real conditions to a much larger domain. While methodological questions are often disregarded in this extrapolation process, they are specifically addressed in this paper, and in particular the issue of models a priori parameterisation. We thus implemented and tested a standard procedure to parameterize the soil components of a modified version of the CERES models. The procedure converts routinely-available soil properties into functional characteristics by means of pedo-transfer functions. The resulting predictions of soil water and nitrogen dynamics, as well as crop biomass, nitrogen content and leaf area index were compared to observations from trials conducted in five locations across Europe (southern Italy, northern Spain, northern France and northern Germany). In three cases, the model’s performance was judged acceptable when compared to experimental errors on the measurements, based on a test of the model’s root mean squared error (RMSE). Significant deviations between observations and model outputs were however noted in all sites, and could be ascribed to various model routines. In decreasing importance, these were: water balance, the turnover of soil organic matter, and crop N uptake. A better match to field observations could therefore be achieved by visually adjusting related parameters, such as field-capacity water content or the size of soil microbial biomass. As a result, model predictions fell within the measurement errors in all sites for most variables, and the model’s RMSE was within the range of published values for similar tests. We conclude that the proposed a priori method yields acceptable simulations with only a 50% probability, a figure which may be greatly increased through a posteriori calibration. Modellers should thus exercise caution when extrapolating their models to a large sample of pedo-climatic conditions for which they have only limited information.

N=1 SQCD-like theories with N_f massive flavors from AdS/CFT and beta functions

We study new supergravity solutions related to large-N c N=1 supersymmetric gauge field theories with a large number N f of massive flavors. We use a recently proposed framework based on configurations with N c color D5 branes and a distribution of N f flavor D5 branes, governed by a function N f S(r). Although the system admits many solutions, under plausible physical assumptions the relevant solution is uniquely determined for each value of x ≡ N f /N c . In the IR region, the solution smoothly approaches the deformed Maldacena-Núñez solution. In the UV region it approaches a linear dilaton solution. For x < 2 the gauge coupling β g function computed holographically is negative definite, in the UV approaching the NSVZ β function with anomalous dimension γ 0 = −1/2 (approaching − 3/(32π 2)(2N c  − N f )g 3)), and with β g  → −∞ in the IR. For x = 2, β g has a UV fixed point at strong coupling, suggesting the existence of an IR fixed point at a lower value of the coupling. We argue that the solutions with x > 2 describe a"Seiberg dual" picture where N f  − 2N c flips sign.

Classification models for neurocognitive impairment in HIV infection based on demographic and clinical variables

Objective: We used demographic and clinical data to design practical classification models for prediction of neurocognitive impairment (NCI) in people with HIV infection. Methods: The study population comprised 331 HIV-infected patients with available demographic, clinical, and neurocognitive data collected using a comprehensive battery of neuropsychological tests. Classification and regression trees (CART) were developed to btain detailed and reliable models to predict NCI. Following a practical clinical approach, NCI was considered the main variable for study outcomes, and analyses were performed separately in treatment-naïve and treatment-experienced patients. Results: The study sample comprised 52 treatment-naïve and 279 experienced patients. In the first group, the variables identified as better predictors of NCI were CD4 cell count and age (correct classification [CC]: 79.6%, 3 final nodes). In treatment-experienced patients, the variables most closely related to NCI were years of education, nadir CD4 cell count, central nervous system penetration-effectiveness score, age, employment status, and confounding comorbidities (CC: 82.1%, 7 final nodes). In patients with an undetectable viral load and no comorbidities, we obtained a fairly accurate model in which the main variables were nadir CD4 cell count, current CD4 cell count, time on current treatment, and past highest viral load (CC: 88%, 6 final nodes). Conclusion: Practical classification models to predict NCI in HIV infection can be obtained using demographic and clinical variables. An approach based on CART analyses may facilitate screening for HIV-associated neurocognitive disorders and complement clinical information about risk and protective factors for NCI in HIV-infected patients.

Numerical simulation of combined heat transfer phenomena (conduction, convection, and radiation). Application to he optimisation of thermal systems

Thermal systems interchanging heat and mass by conduction, convection, radiation (solar and thermal ) occur in many engineering applications like energy storage by solar collectors, window glazing in buildings, refrigeration of plastic moulds, air handling units etc. Often these thermal systems are composed of various elements for example a building with wall, windows, rooms, etc. It would be of particular interest to have a modular thermal system which is formed by connecting different modules for the elements, flexibility to use and change models for individual elements, add or remove elements without changing the entire code. A numerical approach to handle the heat transfer and fluid flow in such systems helps in saving the full scale experiment time, cost and also aids optimisation of parameters of the system. In subsequent sections are presented a short summary of the work done until now on the orientation of the thesis in the field of numerical methods for heat transfer and fluid flow applications, the work in process and the future work.

Integrated assessment of agricultural sustainability: the pros and cons of reductionism

In this paper I review a series of theoretical concepts that are relevant for the integrated assessment of agricultural sustainability but that are not generally included in the curriculum of the various scientific disciplines dealing with quantitative analysis of agriculture. I first illustrate with plain narratives and concrete examples that sustainability is an extremely complex issue requiring the simultaneous consideration of several aspects, which cannot be reduced into a single indicator of performance. Following, I justify this obvious need for multi-criteria analysis with theoretical concepts dealing with the epistemological predicament of complexity, starting from classic philosophical lessons to arrive to recent developments in complex system theory, in particular Rosen´s theory of modelling relation which is essential to analyze the quality of any quantitative representation. The implications of these theoretical concepts are then illustrated with applications of multi-criteria analysis to the sustainability of agriculture. I wrap up by pointing out the crucial difference between "integrated assessment" and "integrated analysis". An integrated analysis is a set of indicators and analytical models generating an analytical output. An integrated assessment is much more than that. It is about finding an effective way to deal with three key issues: (i) legitimacy – how to handle the unavoidable existence of legitimate but contrasting points of view about different meanings given by social actors to the word "development"; (ii) pertinence – how to handle in a coherent way scientific analyses referring to different scales and dimensions; and (iii) credibility – how to handle the unavoidable existence of uncertainty and genuine ignorance, when dealing with the analysis of future scenarios.

Complementarities between mathematical and computational modeling: the case of the repeated Prisoners' Dilemma

We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i.e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the mathematical model. Our main conclusion is that mathematical and computational models are good complements for research in social sciences. Indeed, while computational models are extremely useful to extend the scope of the analysis to complex scenarios hard to analyze mathematically, formal models can be useful to verify and to explain the outcomes of computational models.

Ethics Outside, Within, or Beyond OR Models

Since ethical concerns are calling for more attention within Operational Research, we present three approaches to combine Operational Research models with ethics. Our intention is to clarify the trade-offs faced by the OR community, in particular the tension between the scientific legitimacy of OR models (ethics outside OR models) and the integration of ethics within models (ethics within OR models). Presenting and discussing an approach that combines OR models with the process of OR (ethics beyond OR models), we suggest rigorous ways to express the relation between ethics and OR models. As our work is exploratory, we are trying to avoid a dogmatic attitude and call for further research. We argue that there are interesting avenues for research at the theoretical, methodological and applied levels and that the OR community can contribute to an innovative, constructive and responsible social dialogue about its ethics.

Take-the-best and other simple strategies: Why and when they work 'well' in binary choice

The effectiveness of decision rules depends on characteristics of bothrules and environments. A theoretical analysis of environments specifiesthe relative predictive accuracies of the lexicographic rule 'take-the-best'(TTB) and other simple strategies for binary choice. We identify threefactors: how the environment weights variables; characteristics of choicesets; and error. For cases involving from three to five binary cues, TTBis effective across many environments. However, hybrids of equal weights(EW) and TTB models are more effective as environments become morecompensatory. In the presence of error, TTB and similar models do not predictmuch better than a naïve model that exploits dominance. We emphasizepsychological implications and the need for more complete theories of theenvironment that include the role of error.

Ethics outside, within or beyond OR models

Since ethical concerns are calling for more attention within OperationalResearch, we present three approaches to combine Operational Researchmodels with ethics. Our intention is to clarify the trade-offs faced bythe OR community, in particular the tension between the scientificlegitimacy of OR models (ethics outside OR models) and the integrationof ethics within models (ethics within OR models). Presenting anddiscussing an approach that combines OR models with the process of OR(ethics beyond OR models), we suggest rigorous ways to express the relationbetween ethics and OR models. As our work is exploratory, we are trying toavoid a dogmatic attitude and call for further research. We argue thatthere are interesting avenues for research at the theoretical,methodological and applied levels and that the OR community can contributeto an innovative, constructive and responsible social dialogue about itsethics.

A test of the predictive validity of non-linear QALY models using time trade-off utilities

This paper presents a test of the predictive validity of various classes ofQALY models (i.e., linear, power and exponential models). We first estimatedTTO utilities for 43 EQ-5D chronic health states and next these states wereembedded in health profiles. The chronic TTO utilities were then used topredict the responses to TTO questions with health profiles. We find that thepower QALY model clearly outperforms linear and exponential QALY models.Optimal power coefficient is 0.65. Our results suggest that TTO-based QALYcalculations may be biased. This bias can be avoided using a power QALY model.

Dispersal probability distributions and the wave-front speed problem

The speed and width of front solutions to reaction-dispersal models are analyzed both analytically and numerically. We perform our analysis for Laplace and Gaussian distribution kernels, both for delayed and nondelayed models. The results are discussed in terms of the characteristic parameters of the models

Cystamine and cysteamine increase brain levels of BDNF in Huntington disease via HSJ1b and transglutaminase

There is no treatment for the neurodegenerative disorder Huntington disease (HD). Cystamine is a candidate drug; however, the mechanisms by which it operates remain unclear. We show here that cystamine increases levels of the heat shock DnaJ-containing protein 1b (HSJ1b) that are low in HD patients. HSJ1b inhibits polyQ-huntingtin¿induced death of striatal neurons and neuronal dysfunction in Caenorhabditis elegans. This neuroprotective effect involves stimulation of the secretory pathway through formation of clathrin-coated vesicles containing brain-derived neurotrophic factor (BDNF). Cystamine increases BDNF secretion from the Golgi region that is blocked by reducing HSJ1b levels or by overexpressing transglutaminase. We demonstrate that cysteamine, the FDA-approved reduced form of cystamine, is neuroprotective in HD mice by increasing BDNF levels in brain. Finally, cysteamine increases serum levels of BDNF in mouse and primate models of HD. Therefore, cysteamine is a potential treatment for HD, and serum BDNF levels can be used as a biomarker for drug efficacy.

The referent : a new referential methodology and procedure in live drawing

My research in live drawing and new technologies uses a combination of a human figure in live in composition, overlaid with a digital projection of a second human figure. The aim is to explore, to amplify and thoroughly analyse the search for distinctive identities and graphic languages of representation for live and projected models.

Semiclassical back reaction in the formation of a straight cosmic string

We derive the back reaction on the gravitational field of a straight cosmic string during its formation due to the gravitational coupling of the string to quantum matter fields. A very simple model of string formation is considered. The gravitational field of the string is computed in the linear approximation. The vacuum expectation value of the stress tensor of a massless scalar quantum field coupled to the string gravitational field is computed to one loop order. Finally, the back-reaction effect is obtained by solving perturbatively the semiclassical Einsteins equations.