University of Nice Sophia Antipolis
  • Nice, Provence-Alpes-Cote d'Azur, France
Recent publications
This paper presents a detailed flexibility and cost assessment study of the Greek power system for the time period 2021–2025 where for the first time the reserve requirements are determined based on the statistical analysis of the residual load variability and forecast error at hourly steps. In particular, the long-term uncertainties are modeled via forecast scenarios that incorporate different assumptions regarding temperature, load growth, renewable energy sources penetration and hydraulic conditions. In the operational time frame, the net load forecast errors are incorporated via scenarios and a two-stage stochastic unit commitment algorithm with balancing actions is implemented. Forecast error scenarios are generated with a non-parametric approach, using multivariate copula functions to capture the temporal dependencies. A Monte Carlo sampling is used to create uncertainty scenarios and a clustering algorithm to reduce their size. These scenarios are then used as input in the flexibility and cost evaluation study that is subsequently conducted. The study is carried out by solving the unit commitment problem in which all the required technical constraints are considered and then indicative reliability and flexibility metrics are calculated. The two-stage stochastic approach for estimating the reserve requirements is compared with the deterministic approach that has been used from the Greek Transmission System Operator for determining the reserve capacity. The obtained results present great interest, since in both cases the calculated reliability (LOLE) and flexibility metrics (IRRE, flexibility residual) take acceptable values, however in the stochastic approach there is a significant decrease in the system cost. Therefore, through this detailed flexibility study it is shown that the two-stage stochastic approach consists a useful alternative for assessing the reserve requirements of the Greek power system, since decreased operation costs is achieved while security of the system can be established.
Radopholus Similis (R. Similis) or burrowing nematode, is one of the most damaging and widespread nematodes attacking bananas, causing toppling or blackhead disease. A mathematical model for the population dynamics of R. Similis is considered, with the aim of investigating the impact of climatic factors on the growth of R. Similis. In this paper, based on the life cycle of R. Similis, we first propose a mathematical model to study and control the population dynamics of this banana pest. We show also how control terms based on biological and chemical controls can be integrated to reduce the population of R. Similis within banana-plantain roots. Sensitivity analysis was performed to show the most important parameters of the model. We present the theoretical analysis of the model. More precisely, we derive a threshold parameter N0, called the basic offspring number and show that the trivial equilibrium is globally asymptotically stable whenever N0≤1, while when N0>1, the non trivial equilibrium is globally asymptotically stable. After, we extend the proposed model by taking account climatic factors that influence the growth of this pest. Biological and chemical controls are now introduced through impulsive equations. Threshold and equilibria are obtained and global stabilities have been studied. The theoretical results are supported by numerical simulations. Numerical results of model with biological and chemical controls reveal that biological methods are more effective than chemical methods. We also found that the month February is the best time to apply these controls.
Demand shocks—unobservable, sudden changes in customer behavior—are a common source of forecast error in airline revenue management systems. The COVID-19 pandemic has been one example of a highly impactful macro-level shock that significantly affected demand patterns and required manual intervention from airline analysts. Smaller, micro-level shocks also frequently occur due to special events or changes in competition. Despite their importance, shock detection methods employed by airlines today are often quite rudimentary in practice. In this paper, we develop a science-based shock detection framework based on statistical hypothesis testing which enables fast detection of demand shocks. Under simplifying assumptions, we show how the properties of the shock detector can be expressed in analytical closed form and demonstrate that this expression is remarkably accurate even in more complex environments. Simulations are used to show how the shock detector can successfully be used to identify positive and negative shocks in both demand volume and willingness-to-pay. Finally, we discuss how the shock detector could be integrated into an airline revenue management system to allow for practical use by airline analysts.
Objective Despite recent progress in caring for patients born with esophageal atresia (EA), undernutrition and stunting remain common. Our study objective was to assess nutritional status in the first year after birth with EA and to identify factors associated with growth failure. Study design We conducted a population-based study of all infants born in France with EA between 2010 and 2016. Through the national EA register, we collected prenatal to 1 year follow-up data. We used body mass index and length-for-age ratio Z scores to define patients who were undernourished and stunted, respectively. Factors with P < 0.20 in univariate analyses were retained in a logistic regression model. Results Among 1,154 patients born with EA, body mass index and length-for-age ratio Z scores at 1 year were available for about 61%. Among these, 15.2% were undernourished and 19% were stunted at the age of 1 year. There was no significant catch-up between ages 6 months and 1 year. Patients born preterm (41%), small for gestational age (17%), or with associated abnormalities (55%) were at higher risk of undernutrition and stunting at age 1 year ( P < 0.05). Neither EA type nor surgical treatment was associated with growth failure. Conclusion Undernutrition and stunting are common during the first year after birth in patients born with EA. These outcomes are significantly influenced by early factors, regardless of EA type or surgical management. Identifying high-risk patient groups with EA (i.e., those born preterm, small for gestational age, and/or with associated abnormalities) may guide early nutritional support strategies.
Introduction Vancomycin is one of the antibiotics most used in neonates. Continuous infusion has many advantages over intermittent infusions, but no consensus has been achieved regarding the optimal initial dose. The objectives of this study were: to develop a Machine learning (ML) algorithm based on pharmacokinetic profiles obtained by Monte Carlo simulations using a population pharmacokinetic model (POPPK) from the literature, in order to derive the best vancomycin initial dose in preterm and term neonates, and to compare ML performances with those of an literature equation (LE) derived from a POPPK previously published. Materials and methods The parameters of a previously published POPPK model of vancomycin in children and neonates were used in the mrgsolve R package to simulate 1900 PK profiles. ML algorithms were developed from these simulations using Xgboost, GLMNET and MARS in parallel, benchmarked and used to calculate the ML first dose. Performances were evaluated in a second simulation set and in an external set of 82 real patients and compared to those of a LE. Results The Xgboost algorithm yielded numerically best performances and target attainment rates: 46.9% in the second simulation set of 400–600 AUC/MIC ratio vs. 41.4% for the LE model (p = 0.0018); and 35.3% vs. 28% in real patients (p = 0.401), respectively). The Xgboost model resulted in less AUC/MIC > 600, thus decreasing the risk of nephrotoxicity. Conclusion The Xgboost algorithm developed to estimate the initial dose of vancomycin in term or preterm infants has better performances than a previous validated LE and should be evaluated prospectively.
The advantage of sex, and its fixation in some clades and species all over the eukaryote tree of life, is considered an evolutionary enigma, especially regarding its assumed two-fold cost. Several likely hypotheses have been proposed such as (1) a better response to the negative frequency-dependent selection imposed by the “Red Queen” hypothesis; (2) the competition between siblings induced by the Tangled Bank hypothesis; (3) the existence of genetic and of (4) ecological factors that can diminish the cost of sex to less than the standard assumed two-fold; and (5) a better maintenance of genetic diversity and its resulting phenotypic variation, providing a selective advantage in randomly fluctuating environments. While these hypotheses have mostly been studied separately, they can also act simultaneously. This was advocated by several studies which presented a pluralist point of view. Only three among the five causes cited above were considered yet in such a framework: the Red Queen hypothesis, the Tangled Bank and the genetic factors lowering the cost of sex. We thus simulated the evolution of a finite mutating population undergoing negative frequency-dependent selection on phenotypes and a two-fold (or less) cost of sexuality, experiencing randomly fluctuating selection along generations. The individuals inherited their reproductive modes, either clonal or sexual. We found that exclusive sexuality begins to fix in populations exposed to environmental variation that exceeds the width of one ecological niche (twice the standard deviation of a Gaussian response to environment). This threshold was lowered by increasing negative frequency-dependent selection and when reducing the two-fold cost of sex. It contributes advocating that the different processes involved in a short-term advantage of sex and recombination can act in combination to favor the fixation of sexual reproduction in populations.
This work proposes a practical methodological framework for simulating long-term discrete wind speed time series, for applications to renewable energy systems. The framework is based on the Matérn stochastic process, that is used to identify and extract the short and long-term periodic components present in the mean and variance of a wind speed time series, and to characterize the residual random component. The procedure of construction of synthetic wind speed time series is developed, rooted in a fast numerical simulation algorithm for the Matérn process. We empirically validate the usefulness of the proposed framework by numerical experiments based on three real historical wind speed datasets. The results show consistent statistical similarities between the historical and simulated wind speed time series of data.
We investigate the representation and complete representation classes for algebras of partial functions with the signature of relative complement and domain restriction. We provide and prove the correctness of a finite equational axiomatisation for the class of algebras representable by partial functions. As a corollary, the same equations axiomatise the algebras representable by injective partial functions. For complete representations, we show that a representation is meet complete if and only if it is join complete. Then we show that the class of completely representable algebras is precisely the class of atomic and representable algebras. As a corollary, the same properties axiomatise the class of algebras completely representable by injective partial functions. The universal-existential-universal axiomatisation this yields for these complete representation classes is the simplest possible, in the sense that no existential-universal-existential axiomatisation exists.
Background: Stereotactic body radiation therapy (SBRT) has gradually been recognized as favorable curative treatment for localized prostate cancer (PC). However, the high rate of erectile dysfunction (ED) after traditional photon-based SBRT remains an ongoing challenge that greatly impacts the quality of life of PC survivors. Modern proton therapy allows higher conformal SBRT delivery and has the potential to reduce ED occurrence but its cost-effectiveness remains uninvestigated. Methods: A Markov decision model was designed to evaluate the cost-effectiveness of proton SBRT versus photon SBRT in reducing irradiation-related ED. Base-case evaluation was performed on a 66-year-old (median age of PC) localized PC patient with normal pretreatment erectile function. Further, stratified analyses were performed for different age groups (50, 55, 60, 65, 70, and 75 years) and threshold analyses were conducted to estimate cost-effective scenarios. A Chinese societal willingness-to-pay (WTP) threshold (37,653 US dollars [$])/quality-adjusted life-year [QALY]) was adopted. Results: For the base case, protons provided an additional 0.152 QALY at an additional cost of $7233.4, and the incremental cost-effectiveness ratio was $47,456.5/QALY. Protons was cost-effective for patients ≤62-year-old at the WTP of China (≤66-year-old at a WTP of $50,000/QALY; ≤73-year-old at a WTP of $100,000/QALY). For patients at median age, once the current proton cost ($18,000) was reduced to ≤$16,505.7 or the patient had a life expectancy ≥88 years, protons were cost-effective at the WTP of China. Conclusions: Upon assumption-based modeling, the results of current study support the use of proton SBRT in younger localized PC patients who are previously potent, for better preservation of erectile function. The findings await further validation using data from future comparative clinical trials.
We study a stochastic game with a dynamic set of players, for modeling and analyzing their computational investment strategies in distributed computing. Players obtain a certain reward for solving a problem, while incurring a certain cost based on the invested time and computational power. We present our framework while considering a contemporary application of blockchain mining, and show that the framework is applicable to certain other distributed computing settings as well. For an in-depth analysis, we consider a particular yet natural scenario where the rate of solving the problem is proportional to the total computational power invested by the players. We show that, in Markov perfect equilibrium, players with cost parameters exceeding a certain threshold, do not invest; while those with cost parameters less than this threshold, invest maximal power. We arrive at an interesting conclusion that the players need not have information about the system state as well as each others' parameters, namely, cost parameters and arrival/departure rates. With extensive simulations and insights through mean field approximation, we study the effects of players' arrival/departure rates and the system parameters on the players' utilities.
Exploiting the combination of algae and bacteria in High Rate Algal/Bacterial Ponds (HRABP) is an emerging approach for wastewater remediation and resource recovery. In this study, the advantage of adding a solid/liquid separation system to uncouple Hydraulic Retention Time (HRT) and Solid Retention Time (SRT) is explored and quantified. A long-term validated model for HRABP was run to simulate and optimize a system at large scale treating digestate. It is shown that by uncoupling HRT and SRT, adapting the liquid depth and the alkalinity content, the algae productivity increases from 9.0-14.5 g m⁻² d⁻¹ (for HRT=SRT in the range of 5 to 10 days) to 20.3 g m⁻² d⁻¹ (for HRT =0.2 d and SRT= 2 d). Simulations pointed out that maximizing the algal productivity or the fraction of recovered nitrogen in the algal biomass are conflicting goals that are achieved under different operating conditions. Conditions maximising the algal productivity favour algae and heterotrophic bacteria while algae and nitrifying bacteria dominate the system under those conditions optimizing the efficiency of nitrogen recycling. Finally, increasing the influent alkalinity and adapting the water depth can boost the algal productivity without meeting conditions favourable to N2O emission, opening new perspectives for resource recovery through algal biomass valorisation.
Ordinary differential equations are derived for the adjoint Euler equations firstly using the method of characteristics in 2D. For this system of partial-differential equations, the characteristic curves appear to be the streamtraces and the well-known C+ and C- curves of the theory applied to the flow. The differential equations satisfied along the streamtraces in 2D are then extended and demonstrated in 3D by linear combination of the original adjoint equations. These findings extend their well-konwn counterparts for the direct system and should serve analytical and possibly numerical studies of the perfect-flow model with respect to adjoint fields or sensitivity questions. Besides the analytical theory, the results are demonstrated by numerical integration of the compatibility relationships for discrete 2D flow-fields and dual-consistent adjoint fields over a very fine grid about an airfoil.
The adoption of edge and fog systems, along with the introduction of privacy-preserving regulations, compel the usage of tools for expressing complex data queries in an ephemeral way. That is, queried data should not persist. Database engines partially address this need, as they provide domain-specific languages for querying data. Unfortunately, using a database in an ephemeral setting has inessential issues related to throughput bottlenecks, scalability, dependency management, and security ( e.g. , query injection). Moreover, databases can impose specific data structures and data formats, which can hinder the development of microservice architectures that integrate heterogeneous systems and handle semi-structured data. In this article, we present Jolie/Tquery, the first query framework designed for ephemeral data handling in microservices. Jolie/Tquery joins the benefits of a technology-agnostic, microservice-oriented programming language, Jolie, and of one of the most widely-used query languages for semi-structured data in microservices, the MongoDB aggregation framework. To make Jolie/Tquery reliable for the users, we follow a cleanroom software engineering process. First, we define Tquery, a theory for querying semi-structured data compatible with Jolie and inspired by a consistent variant of the key operators of the MongoDB aggregation framework. Then, we describe how we implemented Jolie/Tquery following Tquery and how the Jolie type system naturally captures the syntax of Tquery and helps to preserve its invariants. To both illustrate Tquery and Jolie/Tquery, we present the use case of a medical algorithm and build our way to a microservice that implements it using Jolie/Tquery. Finally, we report microbenchmarks that validate the expectation that, in the ephemeral case, using Jolie/Tquery outperforms using an external database (MongoDB, specifically).
Background: Additional long-term treatments are needed for moderate-to-severe atopic dermatitis (AD). An ongoing, open-label, 5-year extension trial, ECZTEND (NCT03587805), assesses tralokinumab plus optional topical corticosteroids in participants from previous tralokinumab parent trials (PTs) with moderate-to-severe AD. Objective: To evaluate safety and efficacy of up to 2 years tralokinumab treatment in a post hoc interim analysis. Methods: Safety analyses included adults from completed PTs enrolled in ECZTEND, regardless of tralokinumab exposure duration. Efficacy analyses included adult participants treated with tralokinumab in ECZTEND for ≥1 year, and subgroup analyses of those on tralokinumab for 2 years (1 year from PT, 1 year in ECZTEND). Primary endpoint was number of adverse events (AEs) with additional efficacy endpoints. Results: Participants on tralokinumab had an exposure-adjusted rate of 237.8 AEs/100 patient-years exposure (N=1174) in the safety analysis set. Exposure-adjusted incidence rates of common AEs were comparable to PTs, although at lower rates. With 2 years of tralokinumab, improvements in extent and severity of AD were sustained, with EASI-75 in 82.5% of participants (N=345). Limitations: Possible selection bias; no placebo arm; some participants experienced treatment gaps between PTs and ECZTEND. Conclusion: Over 2 years, tralokinumab was well-tolerated and maintained long-term control of AD signs and symptoms.
Entomologists have often used computational modeling to study the dynamics of insects in agricultural landscapes. Recently, important issues such as the movement of adults and immatures associated with insect resistance to GMO (genetically modifed organism) crops have been addressed using computational models. We developed an individual-based model using the cellular automata approach (CA) to investigate how an intercropping system composed of maize engineered with Bacillus thuringiensis (Bt) gene, refuge areas (non-Bt maize), and grasses combined with of-season periods might infuence the evolution of resistance in Spodoptera frugiperda (Lepidoptera: Noctuidae), one of the leading agricultural pests targeted by GMOs. We designed the Bt and non-Bt plants in two diferent arrangements: (a) a seed mixture and (b) strips rows, adding grasses in areas adjacent to the feld. We added the seasonal planting dynamics (crop season and of-season), to evaluate a total of six agricultural scenarios. We followed a crop calendar from the United States to create simulations close to agricultural practice. The results showed that the frequency of the resistance allele was strongly related to the landscape arrangements and their dynamics. Since the adult insects are mobile, the seed-mixture scenario increased the frequency of the resistance the most (95.86%), followed by strips (82.10%), without grass felds. The maize harvest made it possible to reduce the frequency of resistance allele below 1%. Based on our results, we can expect that the maintenance of pasture areas, for instance next to the corn crops, will act as a reservoir of susceptible insects during of-season periods.
Institution pages aggregate content on ResearchGate related to an institution. The members listed on this page have self-identified as being affiliated with this institution. Publications listed on this page were identified by our algorithms as relating to this institution. This page was not created or approved by the institution. If you represent an institution and have questions about these pages or wish to report inaccurate content, you can contact us here.
3,798 members
Philippe R Franken
  • Faculty of Medicine
Bernard Moussian
  • Institut Sophia Agrobiotech (UMR ISA 1355 INRA / UNS / 7254 CNRS)
Pascal Staccini
  • Risk Engineering and Medical Informatics
28 avenue de Valrose, 06103, Nice, Provence-Alpes-Cote d'Azur, France
Head of institution
Pr. Frédérique Vidal
+33 (0)4 92 07 60 60