Publications

2022

• Energy awareness and energy efficiency in internet of things middleware: a systematic literature review
  
  • Borges Caldas da Silva Pedro Victor
  • Taconet Chantal
  • Chabridon Sophie
  • Conan Denis
  • Cavalcante Everton
  • Batista Thais
  Annals of Telecommunications - annales des télécommunications, Springer, 2022, 78 (1-2), pp.115–131. The Internet of Things (IoT) is characterized by a myriad of physical deices, together with high heterogeneity in both software and hardware. Middleware platforms have been proposed in order to alleviate such heterogeneity, providing relevant services and easing application development. In IoT systems, energy consumption is a key concern due to the proliferation of devices and their limited battery capacity. IoT middleware platforms can play an important role in providing applications with strategies, and support, for energy awareness and energy efficiency. Although there is a significant existing body of work related to IoT middleware, there is, as yet, no complementary overview of the state of the art on how these platforms can contribute to energy efficiency and energy awareness in IoT systems. This paper provides such an overview in the form of a systematic literature review (SLR). The SLR was carried out by following a systematic, rigorous procedure to search, select, and analyze primary studies available in the literature. Our corpus, as presented in this paper, is made up of twenty-two such studies, each presenting strategies and solutions on middleware support for energy efficiency and energy awareness in IoT systems. These strategies mainly focus on network adaptation, task offloading, and concrete implementations. However, most of these studies do not consider energy-aware/efficiency abstractions, and focus on solutions working at the end-user application side. In conclusion, this paper also raises relevant challenges and potential directions for further research resulting from the main SLR findings. (10.1007/s12243-022-00936-5)
  DOI : 10.1007/s12243-022-00936-5
• Offshore CO2 Capture and Utilization Using Floating Wind/PV Systems: Site Assessment and Efficiency Analysis in the Mediterranean
  
  • Keller Douglas
  • Somanna Vishal
  • Drobinski Philippe
  • Tard Cédric
  Energies, MDPI, 2022, 15 (23), pp.8873. A methanol island, powered by solar or wind energy, indirectly captures atmospheric CO2 through the ocean and combines it with hydrogen gas to produce a synthetic fuel. The island components include a carbon dioxide extractor, a desalinator, an electrolyzer, and a carbon dioxide-hydrogen reactor to complete this process. In this study, the optimal locations to place such a device in the Mediterranean Sea were determined, based on three main constraints: power availability, environmental risk, and methanol production capability. The island was numerically simulated with a purpose built python package pyseafuel. Data from 20 years of ocean and atmospheric simulation data were used to “force” the simulated methanol island. The optimal locations were found to strongly depend on the power availability constraint, with most optimal locations providing the most solar and/or wind power, due to the limited effect the ocean surface variability had on the power requirements of methanol island. Within this context, optimal locations were found to be the Alboran, Cretan, and Levantine Sea due to the availability of insolation for the Alboran and Levantine Sea and availability of wind power for the Cretan Sea. These locations were also not co-located with areas with larger maximum significant wave heights, thereby avoiding areas with higher environmental risk. When we simulate the production at these locations, a 10 L s−1 seawater inflow rate produced 494.21, 495.84, and 484.70 mL m−2 of methanol over the course of a year, respectively. Island communities in these regions could benefit from the energy resource diversification and independence these systems could provide. However, the environmental impact of such systems is poorly understood and requires further investigation. (10.3390/en15238873)
  DOI : 10.3390/en15238873
• The effect of spatial granularity on optimal renewable energy portfolios in an integrated climate-energy assessment model
  
  • Maimó-Far Aina
  • Homar Victor
  • Tantet Alexis
  • Drobinski Philippe
  Sustainable Energy Technologies and Assessments, Elsevier, 2022, 54, pp.102827. (10.1016/j.seta.2022.102827)
  DOI : 10.1016/j.seta.2022.102827
• Structure of the human heparan sulfate polymerase complex EXT1-EXT2
  
  • Leisico Francisco
  • Omeiri Juneina
  • Le Narvor Christine
  • Beaudouin Joël
  • Hons Michael
  • Fenel Daphna
  • Schoehn Guy
  • Couté Yohann
  • Bonnaffé David
  • Sadir Rabia
  • Lortat-Jacob Hugues
  • Wild Rebekka
  Nature Communications, Nature Publishing Group, 2022, 13 (1), pp.7110. Heparan sulfates are complex polysaccharides that mediate the interaction with a broad range of protein ligands at the cell surface. A key step in heparan sulfate biosynthesis is catalyzed by the bi-functional glycosyltransferases EXT1 and EXT2, which generate the glycan backbone consisting of repeating N -acetylglucosamine and glucuronic acid units. The molecular mechanism of heparan sulfate chain polymerization remains, however, unknown. Here, we present the cryo-electron microscopy structure of human EXT1-EXT2, which reveals the formation of a tightly packed hetero-dimeric complex harboring four glycosyltransferase domains. A combination of in vitro and in cellulo mutational studies is used to dissect the functional role of the four catalytic sites. While EXT1 can catalyze both glycosyltransferase reactions, our results indicate that EXT2 might only have N -acetylglucosamine transferase activity. Our findings provide mechanistic insight into heparan sulfate chain elongation as a nonprocessive process and lay the foundation for future studies on EXT1-EXT2 function in health and disease. (10.1038/s41467-022-34882-6)
  DOI : 10.1038/s41467-022-34882-6
• Wasserstein Adversarial Regularization for learning with label noise
  
  • Fatras Kilian
  • Damodaran Bharath Bhushan
  • Lobry Sylvain
  • Flamary Remi
  • Tuia Devis
  • Courty Nicolas
  IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2022, 44 (10), pp.7296-7306. (10.1109/TPAMI.2021.3094662)
  DOI : 10.1109/TPAMI.2021.3094662
• Influence of Generated Defects by Ar Implantation on the Thermoelectric Properties of ScN
  
  • Burcea Razvan
  • Barbot Jean-François
  • Renault Pierre-Olivier
  • Eyidi Dominique
  • Girardeau Thierry
  • Marteau Marc
  • Giovannelli Fabien
  • Zenji Ahmad
  • Rampnoux Jean-Michel
  • Dilhaire Stefan
  • Eklund Per
  • Le Febvrier Arnaud
  ACS Applied Energy Materials, ACS, 2022, 5 (9), pp.11025-11033. Nowadays, making thermoelectric materials more efficient in energy conversion is still a challenge. In this work, to reduce the thermal conductivity and thus improve the overall thermoelectric performances, point and extended defects were generated in epitaxial 111-ScN thin films by implantation using argon ions. The films were investigated by structural, optical, electrical, and thermoelectric characterization methods. The results demonstrated that argon implantation leads to the formation of stable defects (up to 750 K operating temperature). These were identified as interstitial-type defect clusters and argon vacancy complexes. The insertion of these specific defects induces acceptor-type deep levels in the band gap, yielding a reduction in the free-carrier mobility. With a reduced electrical conductivity, the irradiated sample exhibited a higher Seebeck coefficient while maintaining the power factor of the film. The thermal conductivity is strongly reduced from 12 to 3 W·m–1·K–1 at 300 K, showing the influence of defects in increasing phonon scattering. Subsequent high-temperature annealing at 1573 K leads to the progressive evolution of these defects: the initial clusters of interstitials evolved to the benefit of smaller clusters and the formation of bubbles. Thus, the number of free carriers, the resistivity, and the Seebeck coefficient are almost restored but the mobility of the carriers remains low and a 30% drop in thermal conductivity is still effective (ktotal ∼ 8.5 W·m–1·K–1). This study shows that control defect engineering with defects introduced by irradiation using noble gases in a thermoelectric coating can be an attractive method to enhance the figure of merit of thermoelectric materials. (10.1021/acsaem.2c01672)
  DOI : 10.1021/acsaem.2c01672
• Middleware supporting PIS : requirements, solutions, and challenges
  
  • Taconet Chantal
  • Batista Thais
  • Borges Caldas da Silva Pedro Victor
  • Bouloukakis Georgios
  • Cavalcante Everton
  • Chabridon Sophie
  • Conan Denis
  • Desprats Thierry
  • Muñante Denisse
  , 2022, pp.65-97. In this chapter, we consider the requirements for middleware to support Pervasive Information Systems (PIS) in the context of the Internet of Things (IoT). With the IoT, PIS architectures become more and more distributed and need to be supported by middleware that provides applications with an easy integration of contextual data collected from connected objects spread over the Internet. This comes with new challenges and requirements for PIS middleware. In addition to context-awareness, middleware should tackle scalability, security, privacy and interoperability and provide applications with new abstractions representing the physical environment and ensuring the quality of the data that may be used for decision-making, while keeping PIS sustainable. Through the study of the state of the art regarding PIS middleware, we show in this chapter that the middleware community still faces new challenges, such as providing high-level programming models for PIS, supporting PIS dynamic adaptation, disseminating and filtering large volumes of data, end-to-end privacy and interoperability handling, as well as enabling to deploy sustainable applications. (10.1007/978-3-031-18176-4_4)
  DOI : 10.1007/978-3-031-18176-4_4
• ToF-SIMS Li Depth Profiling of Pure and Methylated Amorphous Silicon Electrodes After Their Partial Lithiation
  
  • Feng Yue
  • Koo Bon Min
  • Seyeux Antoine
  • Światowska Jolanta
  • Henry de Villeneuve Catherine
  • Rosso Michel
  • Ozanam François
  ACS Applied Materials & Interfaces, Washington, D.C. : American Chemical Society, 2022, 14 (31), pp.35716-35725. Pure (a-Si:H) and methylated (a-Si0.95(CH3)0.05:H) amorphous silicon thin films were analyzed by time-of-flight secondary ion mass spectrometry (ToF-SIMS) after partial lithiation. Depth profiling gives insight into the lithiation mechanism of the material enabling to study the detailed biphasic process in the first lithiation process. Lithiation induces swelling and roughening of the active layer. In both a-Si:H and a-Si0.95(CH3)0.05:H, no measurable Li diffusion was observed after stopping current-induced lithiation. After applying the same lithiation charges, distinct Li profiles were observed for these two materials. Unlike a-Si:H, the Li concentration drops slowly from the heavily lithiated region to the non-lithiated region in a-Si0.95(CH3)0.05:H. This apparent progressive transition between the lithiated and lithium-free regions is attributed to the presence of nanovoids inside the material. When their concentration is high enough, these nanovoids constitute favorable quasi-percolating paths for lithium during the first lithiation. A specific model was developed to simulate the Li depth profiles, fully supporting this hypothesis. (10.1021/acsami.2c08203)
  DOI : 10.1021/acsami.2c08203
• Altiratinib blocks Toxoplasma gondii and Plasmodium falciparum development by selectively targeting a spliceosome kinase
  
  • Swale Christopher
  • Bellini Valeria
  • Bowler Matthew
  • Flore Nardella
  • Brenier-Pinchart Marie-Pierre
  • Cannella Dominique
  • Belmudes Lucid
  • Mas Caroline
  • Couté Yohann
  • Laurent Fabrice
  • Scherf Artur
  • Bougdour Alexandre
  • Hakimi Mohamed-Ali
  Science Translational Medicine, American Association for the Advancement of Science (AAAS), 2022, 14 (656), pp.17 p.. The Apicomplexa comprise a large phylum of single-celled, obligate intracellular protozoa that include Toxoplasma gondii , Plasmodium , and Cryptosporidium spp., which infect humans and animals and cause severe parasitic diseases. Available therapeutics against these diseases are limited by suboptimal efficacy and frequent side effects, as well as the emergence and spread of resistance. We use a drug repurposing strategy and identify altiratinib, a compound originally developed to treat glioblastoma, as a promising drug candidate with broad spectrum activity against apicomplexans. Altiratinib is parasiticidal and blocks the development of intracellular zoites in the nanomolar range and with a high selectivity index when used against T. gondii . We have identified Tg PRP4K of T. gondii as the primary target of altiratinib using genetic target deconvolution, which highlighted key residues within the kinase catalytic site that conferred drug resistance when mutated. We have further elucidated the molecular basis of the inhibitory mechanism and species selectivity of altiratinib for Tg PRP4K and for its Plasmodium falciparum counterpart, Pf CLK3. Our data identified structural features critical for binding of the other Pf CLK3 inhibitor, TCMDC-135051. Consistent with the splicing control activity of this kinase family, we have shown that altiratinib can cause global disruption of splicing, primarily through intron retention in both T. gondii and P. falciparum . Thus, our data establish parasitic PRP4K/CLK3 as a potential pan-apicomplexan target whose repertoire of inhibitors can be expanded by the addition of altiratinib. (10.1126/scitranslmed.abn3231)
  DOI : 10.1126/scitranslmed.abn3231
• Determining solar cell parameters and degradation rates from power production data
  
  • Chakar Joseph
  • Pavlov Marko
  • Bonnassieux Yvan
  • Badosa Jordi
  Energy Conversion and Management: X, Elsevier, 2022, 15, pp.100270. (10.1016/j.ecmx.2022.100270)
  DOI : 10.1016/j.ecmx.2022.100270
• Prefetching of mobile devices information: a DNS perspective
  
  • Bernard Antoine
  • Laroui Mohammed
  • Marot Michel
  • Balakrichenan Sandoche
  • Moungla Hassine
  • Ampeau Benoit
  • Afifi Hossam
  • Becker Monique
  , 2022, pp.1-7. The development of vehicular technologies and infrastructures leads to development in mobility handling for wireless communications. Improving connectivity establishment and reliability becomes an issue, especially for vehicles that may move out of antenna coverage during connection establishment. The focus of this paper is made on improving LoRaWAN connectivity for roaming devices by combining a machine learning predictor and DNS prefetching to gather information necessary for connection establishment before the device comes under coverage, thus reducing the overall latency for connection establishment. Other aspects are also studied such as comparison with other solutions and antennas memory occupation. (10.1109/ICC45855.2022.9838564)
  DOI : 10.1109/ICC45855.2022.9838564
• A novel deep reinforcement approach for IIoT microgrid energy management systems
  
  • Dridi Aicha
  • Afifi Hossam
  • Moungla Hassine
  • Badosa Jordi
  IEEE Transactions on Green Communications and Networking, IEEE, 2022, 6 (1), pp.148-159. Introducing Deep Learning in the Industrial Internet of Things (IIoT) brings many benefits, such as network resilience and bandwidth usage reduction. In this work, we propose an innovative reinforcement learning architecture to implement distributed energy management systems for microgrids. The architecture is based on novel reinforcement learning and on time series prediction. The designed reinforcement learning uses classical recurrent neural networks instead of the habitual SAR (State Action Reward) method that most of the recent bibliography considers. We applied various techniques (Exact resolution, Rule-Based, Q-Learning, and our designed reinforcement learning) on a distributed IIoT energy control architecture. The proposed method has shown better results compared to the exact resolution and the Q-Learning algorithm. It results in fast learning systems with a small number of training samples. We identified and tested several management strategies. Integer Linear Programming (ILP) optimal expressions and strategy-based implementations are derived. We utilize the obtained results to train the recurrent neural network. Comparative results are very encouraging and prone to a generalization of our approach instead of the classical methods. (10.1109/TGCN.2021.3112043)
  DOI : 10.1109/TGCN.2021.3112043
• Chiroptical properties of anionic and neutral nickel(II) bis(dithiolene) complexes based on methyl and dimethyl‐dddt ligands
  
  • Abhervé Alexandre
  • Mroweh Nabil
  • Cauchy Thomas
  • Pop Flavia
  • Vanthuyne Nicolas
  • Avarvari Narcis
  Chirality, Wiley, 2022, 34, pp.4-12. Racemic and enantiopure nickel(II) bis(dithiolene) anionic and neutral complexes based on the methyl-5,6-dihydro-1,4-dithiin-2,3-dithiolate (me-dddt) and dimethyl-5,6-dihydro-1,4-dithiin-2,3-dithiolate (dm-dddt) ligands have been experimentally and theoretically investigated with a special focus on their chiroptical properties. According to the TD DFT calculations the strong near infrared absorption bands typical for such complexes are only weakly active in CD and, moreover, they have opposite signs for the axial and equatorial conformations, due to the variation of the angle between the transition electric and magnetic dipole moments, thus leading to the mutual cancellation of their contributions and the absence of these bands in the experimental CD spectra. The influence of the number of stereogenic centres and of the oxidation state of the complexes on their chiroptical properties is highlighted. The solid state structure of the complex (TMA)[Ni(rac-me-dddt)2] (TMA = tetramethylammonium), determined by single crystal X-ray diffraction analysis, shows a rather unusual cis arrangement of the two dithiolene ligands, with the methyl substituents adopting an axial conformation, which is not the most stable one in the gas phase. (10.1002/chir.23375)
  DOI : 10.1002/chir.23375
• How Skillful Are the European Subseasonal Predictions of Wind Speed and Surface Temperature?
  
  • Goutham Naveen
  • Plougonven Riwal
  • Omrani Hiba
  • Parey Sylvie
  • Tankov Peter
  • Tantet Alexis
  • Hitchcock Peter
  • Drobinski Philippe
  Monthly Weather Review, American Meteorological Society, 2022, 150, pp.1621-1637. Subseasonal forecasts of 100-m wind speed and surface temperature, if skillful, can be beneficial to the energy sector as they can be used to plan asset availability and maintenance, assess risks of extreme events, and optimally trade power on the markets. In this study, we evaluate the skill of the European Centre for Medium-Range Weather Forecasts' subseasonal predictions of 100-m wind speed and 2-m temperature. To the authors' knowledge, this assessment is the first for the 100-m wind speed, which is an essential variable of practical importance to the energy sector. The assessment is carried out on both forecasts and reforecasts over European domain gridpoint wise and also by considering several spatially averaged domains, using several metrics to assess different attributes of forecast quality. We propose a novel way of synthesizing the continuous ranked probability skill score. The results show that the skill of the forecasts and reforecasts depends on the choice of the climate variable, the period of the year, and the geographical domain. Indeed, the predictions of temperature are better than those of wind speed, with enhanced skill found for both variables in the winter relative to other seasons. The results also indicate significant differences between the skill of forecasts and reforecasts, arising mainly due to the differing ensemble sizes. Overall, depending on the choice of the geographical domain and the forecast attribute, the results show skillful predictions beyond 2 weeks, and in certain cases, up to 6 weeks for both variables, thereby encouraging their implementation in operational decision-making. (10.1175/MWR-D-21-0207.1)
  DOI : 10.1175/MWR-D-21-0207.1
• Transcriptional regulation of photoprotection in dark-to-light transition—More than just a matter of excess light energy
  
  • Redekop Petra
  • Sanz-Luque Emanuel
  • Yuan Yizhong
  • Villain Gaelle
  • Petroutsos Dimitris
  • Grossman Arthur R
  Science Advances, American Association for the Advancement of Science (AAAS), 2022, 8 (22), pp.eabn1832. In nature, photosynthetic organisms are exposed to different light spectra and intensities depending on the time of day and atmospheric and environmental conditions. When photosynthetic cells absorb excess light, they induce nonphotochemical quenching to avoid photodamage and trigger expression of “photoprotective” genes. In this work, we used the green alga Chlamydomonas reinhardtii to assess the impact of light intensity, light quality, photosynthetic electron transport, and carbon dioxide on induction of the photoprotective genes ( LHCSR1 , LHCSR3 , and PSBS ) during dark-to-light transitions. Induction (mRNA accumulation) occurred at very low light intensity and was independently modulated by blue and ultraviolet B radiation through specific photoreceptors; only LHCSR3 was strongly controlled by carbon dioxide levels through a putative enhancer function of CIA5, a transcription factor that controls genes of the carbon concentrating mechanism. We propose a model that integrates inputs of independent signaling pathways and how they may help the cells anticipate diel conditions and survive in a dynamic light environment. (10.1126/sciadv.abn1832)
  DOI : 10.1126/sciadv.abn1832
• Indazole versus indole-based cationic merocyanines with red shifted in-cellulo emission for selective mitochondria imaging
  
  • Boujut Margot
  • Chevalier Arnaud
  • Schapman Damien
  • Bénard Magalie
  • Galas Ludovic
  • Gallavardin Thibault
  • Franck Xavier
  Dyes and Pigments, Elsevier, 2022, 198, pp.109988. Selective fluorophores are seminal for the development of fluorescent cell imaging allowing the simultaneous monitoring of several biological parameters. Mitochondria are one of the main targets of optical microscopy as their dynamics are related to many biological events. One of the best strategy to target them, is to design cationic dyes which accumulate preferentially in their membranes due to their high electrochemical potential. In this work, indazole scaffold was explored to build new cationic merocyanine dyes and compared with indole scaffold. This nitrogen heteroaromatic structure is still very uncommon in dyes chemistry; therefore, a lot has to be discovered about the effects of pH, solvent polarity and methylation in cyclic nitrogen on their optical properties. Finally, fluorescent imaging revealed that a red shift occurred in the emission of these molecules inside the mitochondria. (10.1016/j.dyepig.2021.109988)
  DOI : 10.1016/j.dyepig.2021.109988
• Molecular dynamics between amorphous and crystalline phases of e-beam irradiated piezoelectric PVDF thin films employing solid-state NMR spectroscopy
  
  • Potrzebowska Natalia
  • Cavani Olivier
  • Kazmierski Slawomir
  • Wegrowe Jean-Eric
  • Potrzebowski Marek
  • Clochard Marie-Claude
  Polymer Degradation and Stability, Elsevier, 2022, 195, pp.109786. (10.1016/j.polymdegradstab.2021.109786)
  DOI : 10.1016/j.polymdegradstab.2021.109786
• Cyclone generation Algorithm including a THERmodynamic module for Integrated National damage Assessment (CATHERINA 1.0) compatible with Coupled Model Intercomparison Project (CMIP) climate data
  
  • Le Guenedal Théo
  • Drobinski Philippe
  • Tankov Peter
  Geoscientific Model Development, European Geosciences Union, 2022, 15 (21), pp.8001-8039. Tropical cyclones are responsible for a large share of global damage resulting from natural disasters, and estimating cyclone-related damage at a national level is a challenge attracting growing interest in the context of climate change. The global climate models, whose outputs are available from the Coupled Model Intercomparison Project (CMIP), do not resolve tropical cyclones. The Cyclone generation Algorithm including a THERmodynamic module for Integrated National damage Assessment (CATHERINA), presented in this paper, couples statistical and thermodynamic relationships to generate synthetic tracks sensitive to local climate conditions and estimates the damage induced by tropical cyclones at a national level. The framework is designed to be compatible with the data from CMIP models offering a reliable solution to resolve tropical cyclones in climate projections. We illustrate this by producing damage projections in representative concentration pathways (RCPs) at the global level and for individual countries. The algorithm contains a module to correct biases in climate models based on the distributions of the climate variables in the reanalyses. This model was primary developed to provide the economic and financial community with reliable signals allowing for a better quantification of physical risks in the long term, to estimate, for example, the impact on sovereign debt. (10.5194/gmd-15-8001-2022)
  DOI : 10.5194/gmd-15-8001-2022
• Generating natural adversarial Remote Sensing Images
  
  • Burnel Jean-Christophe
  • Fatras Kilian
  • Flamary Rémi
  • Courty Nicolas
  IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2022, 60, pp.1-14. Over the last years, Remote Sensing Images (RSI) analysis have started resorting to using deep neural networks to solve most of the commonly faced problems, such as detection, land cover classification or segmentation. As far as critical decision making can be based upon the results of RSI analysis, it is important to clearly identify and understand potential security threats occurring in those machine learning algorithms. Notably, it has recently been found that neural networks are particularly sensitive to carefully designed attacks, generally crafted given the full knowledge of the considered deep network. In this paper, we consider the more realistic but challenging case where one wants to generate such attacks in the case of a black-box neural network. In this case, only the prediction score of the network is accessible, given a specific input. Examples that lure away the network's prediction, while being perceptually similar to real images, are called natural or unrestricted adversarial examples. We present an original method to generate such examples, based on a variant of the Wasserstein Generative Adversarial Network. We demonstrate its effectiveness on natural adversarial hyper-spectral image generation and image modification for fooling a state-of-the-art detector. Among others, we also conduct a perceptual evaluation with human annotators to better assess the effectiveness of the proposed method. (10.1109/TGRS.2021.3110601)
  DOI : 10.1109/TGRS.2021.3110601