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NRF2 signaling cascade in amyotrophic lateral sclerosis:bridging the gap between promise and reality

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Neural Regeneration Research 2024年第5期19卷 1006-1012页

作者： Pauline Tarot Christelle Lasbleiz jean-Charles Liévens MMDN Univ MontpellierEPHEINSERMMontpellierFrance CNRS ParisFranceEPHEINSERMMontpellierFrance

Amyotrophic lateral sclerosis is a very disabling disease due to the degeneration of motor neurons.Symptoms include muscle weakness and atrophy,spasticity,and progressive paralysis.Currently,there is no treatment to reverse damage to motor neurons and cure amyotrophic lateral sclerosis.The only two treatments actually approved,riluzole and edaravone,have shown mitigated beneficial effects.The difficulty to find a cure lies in the complexity and multifaceted pattern of amyotrophic lateral sclerosis pathogenesis.Among mechanisms,abnormal RNA metabolism,nucleocytoplasmic transport defects,accumulation of unfolded protein,and mitochondrial dysfunction would in fine induce oxidative damage and vice versa.A potent therapeutic strategy will be to find molecules that break this vicious circle.Sharpening the nuclear factor erythroid-2 related factor 2 signaling may fulfill this objective since nuclear factor erythroid-2 related factor 2 has a multitarget profile controlling antioxidant defense,mitochondrial functioning,and inflammation.We here discuss the interest of developing nuclear factor erythroid-2 related factor 2-based therapy in regard to the pathophysiological mechanisms and we provide a general overview of the attempted clinical assays in amyotrophic lateral sclerosis.

关键词： amyotrophic lateral sclerosis C9orf72 NRF2 oxidative defense oxidative stress sulforaphane superoxide dismutase 1 TDP43

It’s not all in your feet: Improving penalty kick performance with humanavatar interaction and machine learning

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The Innovation 2024年第2期5卷 115-121页

作者： jean-Luc Bloechle Julien Audiffren Thibaut Le Naour Andrea Alli Dylan Simoni Gabriel Wüthrich jean-Pierre Bresciani Control and Perception Laboratory University of FribourgBd Perolles 901700 FribourgSwitzerland Motion-up Le PrismePlace Albert Einstein56000 VannesFrance FC Basel 1893 Birsstrasse 320A4002 BaselSwitzerland

Penalty kicks are increasingly decisive in major international football competitions.Yet,over 30%of shootout kicks are missed.The outcome of the kick often relies on the ability of the penalty taker to exploit anticipatory movements of the goalkeeper to redirect the kick toward the open side of the goal.Unfortunately,this ability is difficult to train using classical methods.We used an augmented reality simulator displaying an holographic goalkeeper to test and train penalty kick performance with 13 young elite players.Machine learning algorithms were used to optimize the learning rate by maintaining an optimal level of training difficulty.Ten training sessions of 20 kicks reduced the redirection threshold by 120 ms,which constituted a 28%reduction with respect to the baseline threshold.Importantly,redirection threshold reduction was observed for all trained players,and all things being equal,it corresponded to an estimated 35%improvement of the success rate.

关键词： kick penalty learning

A convolutional neural network to detect possible hidden data in spatial domain images

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Cybersecurity 2024年第1期7卷 37-52页

作者： jean De La Croix Ntivuguruzwa Tohari Ahmad Department of Informatics Institut Teknologi Sepuluh Nopember(ITS)Kampus ITS Keputih SukoliloSurabaya60111Indonesia African Center of Excellence in the Internet of Things College of Science and TechnologyUniversity of Rwanda3900KigaliRwanda

Hiding secret data in digital multimedia has been essential to protect the data.Nevertheless,attackers with a steganalysis technique may break them.Existing steganalysis methods have good results with conventional Machine Learning(ML)techniques;however,the introduction of Convolutional Neural Network(CNN),a deep learning paradigm,achieved better performance over the previously proposed ML-based techniques.Though the existing CNN-based approaches yield good results,they present performance issues in classification accuracy and stability in the network training phase.This research proposes a new method with a CNN architecture to improve the hidden data detection accuracy and the training phase stability in spatial domain images.The proposed method comprises three phases:pre-processing,feature extraction,and classification.Firstly,in the pre-processing phase,we use spatial rich model filters to enhance the noise within images altered by data hiding;secondly,in the feature extraction phase,we use two-dimensional depthwise separable convolutions to improve the signal-to-noise and regular convolutions to model local features;and finally,in the classification,we use multi-scale average pooling for local features aggregation and representability enhancement regardless of the input size variation,followed by three fully connected layers to form the final feature maps that we transform into class probabilities using the softmax function.The results identify an improvement in the accuracy of the considered recent scheme ranging between 4.6 and 10.2%with reduced training time up to 30.81%.

关键词： Information security Spatial domain steganalysis Deep learning Convolutional neural network Infrastructure

Design and Experimental Testing of a Moving Coil Actuator with Compensation Coil

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 707-716页

作者： Boyuan Yin Xianwu Zeng John Frederick Eastham Emelie Nilsson jean-francois Rouquette jean Rivenc Ludovic Ybanez Xiaoze Pei Department of Electronics&Electrical Engineering University of BathBathBA27AYUnited Kingdom Airbus UpNext BlangnacFrance Airbus CRT BlangnacFrance Department of Mechanical Engineering University of BathBathBA27AYUnited Kingdom

Hydrogen-powered electric aircraft have attracted significant interests aiming to achieve decarbonization targets.Onboard DC electric networks are facing great challenges in DC fault protection requirements.Vacuum interrupters are widely used in low voltage and medium voltage power systems due to being environmentally friendly with low maintenance.In this paper a moving coil actuator with compensation coils for a vacuum interrupter,as part of a hybrid direct current circuit breaker,is designed and experimentally tested.Compensation coils are used to improve operating speed compared with original moving coil actuator.Comparisons between four possible connections of compensation coils and original moving coil actuator are carried out.Experimental results show comparisons between different connections of actuator coils in terms of opening time and coil current with a range of pre-charged capacitor voltages.Dynamic performance of each actuator connection is also compared.The actuator with compensation coils is shown to have a higher current rising rate and achieve faster opening speed,which is a critical requirement for electric aircraft network protection.The parallel connection actuator achieves the highest opening speed within 3.5 ms with capacitor voltage of 50 V.

关键词： Circuit breaker compensation coil moving coil actuator vacuum interrupter

Tanaka Formula and Local Time for a Class of Interacting Branching Measure-valued Diffusions

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Acta Mathematica Sinica,English Series 2024年第4期40卷 1059-1098页

作者： Donald A.DAWSON jean VAILLANCOURT Hao WANG School of Mathematics and Statistics Carleton UniversityOttawaCanada Department of Decision Sciences HECMontrealCanada Department of Mathematics University of OregonEugeneUSA

We construct superprocesses with dependent spatial motion(SDSMs)in Euclidean spaces R^(d)with d≥1 and show that,even when they start at some unbounded initial positive Radon measure such as Lebesgue measure on R^(d),... 详细信息

关键词： Measure-valued diffusions stochastic partial differential equations superprocesses branching processes local time Tanaka formula

Mitochondrial recruitment in myelin:an anchor for myelin dynamics and plasticity?

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Neural Regeneration Research 2024年第7期19卷 1401-1402页

作者： jean-David M.Gothié Timothy E.Kennedy Department of Neurology and Neurosurgery Montreal Neurological InstituteMcGill UniversityMontrealQCCanada

Optimal propagation of neuronal electrical impulses depends on the insulation of axons by myelin,produced in the central nervous system by oligodendrocytes.Myelin is an extension of the oligodendrocyte plasma membrane,which wraps around an axon to form a compact multi-layered sheath.Myelin is composed of a substantially higher proportion of lipids compared to other biological membranes and enriched in a small number of specialized proteins.

关键词： plasticity insulation dynamics

Monitoring absolute vertical land motions and absolute sea-level changes from GPS and tide gauges data over French Polynesia

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Geodesy and Geodynamics 2024年第1期15卷 13-26页

作者： Xianjie Li jean-Pierre Barriot Bernard Ducarme Marania Hopuare Yidong Lou Geodesy Observatory of Tahiti University of French PolynesiaFaa'a 98702French Polynesia Catholic University of Louvain Georges Lemaître Centre for Earth and Climate Research(ELI)1348 Louvain-la-NeuveBelgium GNSS Research Center Wuhan UniversityWuhan 430079China State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhan 430079China

In this study,we estimate the absolute vertical land motions at three tidal stations with collocated Global Navigation Satellite System(GNSS)receivers over French Polynesia during the period 2007-2020,and obtain,as ancillary results,estimates of the absolute changes in sea level at the same locations.To verify our processing approach to determining vertical motion,we first modeled vertical motion at the International GNSS Service(IGS)THTI station located in the capital island of Tahiti and compared our estimate with previous independent determinations,with a good agreement.We obtained the following estimates for the vertical land motions at the tide gauges:Tubuai island,Austral Archipelago-0.92±0.17 mm/yr,Vairao village,Tahiti Iti:-0.49±0.39 mm/yr,Rikitea,Gambier Archipelago-0.43±0.17 mm/yr.The absolute variations of the sea level are:Tubuai island,Austral Archipelago 5.25±0.60 mm/yr,Vairao village,Tahiti Iti:3.62±0.52 mm/yr,Rikitea,Gambier Archipelago 1.52±0.23 mm/yr.We discuss these absolute values in light of the values obtained from altimetric measurements and other means in French Polynesia.

关键词： GPS Tide gauges Sea level changes Vertical land motion

A reinforcement learning approach for thermostat setpoint preference learning

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Building Simulation 2024年第1期17卷 131-146页

作者： Hussein Elehwany Mohamed Ouf Burak Gunay Nunzio Cotrufo jean-Simon Venne Department of Environmental Engineering Carleton UniversityOttawaCanada Departmentof Building Civiland Environmental EngineeringConcordia UniversityMontrealCanada BrainBox Al Inc. MontrealCanada

Occupant-centric controls(OcC)is an indoor climate control approach whereby occupant feedback is used in the sequence of operation of building energy systems.While OcC has been used in a wide range of building applications,an OcC category that has received considerable research interest is learning occupants'thermal preferences through their thermostat interactions and adapting temperature setpoints accordingly.Many recent studies used reinforcement learning(RL)as an agent for OcC to optimize energy use and occupant comfort.These studies depended on predicted mean vote(PMV)models or constant comfort ranges to represent comfort,while only few of them used thermostat interactions.This paper addresses this gap by introducing a new off-policy reinforcement learning(RL)algorithm that imitates the occupant behaviour by utilizing unsolicited occupant thermostat overrides.The algorithm is tested with a number of synthetically generated occupant behaviour models implemented via the Python APl of EnergyPlus.The simulation results indicate that the RL algorithm could rapidly learn preferences for all tested occupant behaviour scenarios with minimal exploration events.While substantial energy savings were observed with most occupant scenarios,the impact on the energy savings varied depending on occupants'preferences and thermostat use behaviour stochasticity.

关键词： reinforcement learning preference learning occupant-centric controls smart thermostats off-policy learning

Origin and diversification of maize: Two teosintes but different contributions

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Molecular Plant 2024年第2期17卷 233-235页

作者： Jonathan Acosta-Bayona Gloria Leon-Martinez jean-Philippe Vielle-Calzada Grupo de Desarrollo Reproductivo y Apomixis UGA Laboratorio Nacional de Genomica para la BiodiversidadCinvestav IrapuatoIrapuato Gto CP36825Mexico

The unique topographic,climatic,and latitudinal heterogeneity of Mesoamerica is crucial to understanding the evolutionary emergence of one of the richest cultural and biological regions in the planet and its impact on food production.Broadly divided between two regions of large biodiversity-lowland tropical or coastal zones and temperate or subtropical highlands sculpted by parallel sierras and their central plateau-the Mexican territory harbors more than 2000 endemic monocotyledonous species,including several hundred grasses(Poaceae),particularly those belonging to the genus Zea,composed of maize(Zea mays ssp.mays)and its wild relatives,collectively referred as teosintes.

关键词： collective planet harbor