Recent understanding of Autism Spectrum Disorder (ASD) showed that peripheral primary mechanosensitive neurons involved in touch sensation and central neurons affected in ASD share transcriptional ...regulators. Mutant mice for ASD-associated transcription factors exhibit impaired primary tactile perception and restoring those genes specifically in primary sensory neurons rescues some of the anxiety-like behavior and social interaction defects. Interestingly, peripheral mechanosensitive sensory neurons also project to internal organs including the cardiovascular system, and an imbalance of the cardio-vascular sympathovagal regulation is evidenced in ASD and intellectual disability. ASD patients have decreased vagal tone, suggesting dysfunction of sensory neurons involved in cardio-vascular sensing. In light of our previous finding that the ASD-associated Meis2 gene is necessary for normal touch neuron development and function, we investigated here if its inactivation in mouse peripheral sensory neurons also affects cardio-vascular sympathovagal regulation and baroreflex. Combining echocardiography, pharmacological challenge, blood pressure monitoring, and heart rate variability analysis, we found that Meis2 mutant mice exhibited a blunted vagal response independently of any apparent cardiac malformation. These results suggest that defects in primary sensory neurons with mechanosensitive identity could participate in the imbalanced cardio-vascular sympathovagal tone found in ASD patients, reinforcing current hypotheses on the role of primary sensory neurons in the etiology of ASD.
Air pollution is a prevailing environmental problem in cities worldwide. The future vehicle electrification (VE), which in Europe will be importantly fostered by the ban of thermal engines from 2035, ...is expected to have an important effect on urban air quality. Machine learning models represent an optimal tool for predicting changes in air pollutants concentrations in the context of future VE. For the city of Valencia (Spain), a XGBoost (eXtreme Gradient Boosting package) model was used in combination with SHAP (SHapley Additive exPlanations) analysis, both to investigate the importance of different factors explaining air pollution concentrations and predicting the effect of different levels of VE. The model was trained with 5 years of data including the COVID-19 lockdown period in 2020, in which mobility was strongly reduced resulting in unprecedent changes in air pollution concentrations. The interannual meteorological variability of 10 years was also considered in the analyses. For a 70% VE, the model predicted: 1) improvements in nitrogen dioxide pollution (−34% to −55% change in annual mean concentrations, for the different air quality stations), 2) a very limited effect on particulate matter concentrations (−1 to −4% change in annual means of PM2.5 and PM10), 3) heterogeneous responses in ground-level ozone concentrations (−2% to +12% change in the annual means of the daily maximum 8-h average concentrations). Even at a high VE increase of 70%, the 2021 World Health Organization Air Quality Guidelines will be exceeded for all pollutants in some stations. VE has a potentially important impact in terms of reducing NO2-associated premature mortality, but complementary strategies for reducing traffic and controlling all different air pollution sources should also be implemented to protect human health.
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•XGBoost model was used to estimate vehicle electrification effects on air quality.•For a 70% vehicle electrification, NO2 concentrations were reduced 34–55%.•Particulate matter concentrations were reduced very little (−1 to −4%).•O3 increased or decreased (−2% to +12%), depending on the air quality station.•The benefits for human health were quantified.
This paper proposes a control strategy based on artificial neural networks (ANNs) for a positioning system with a flexible transmission element, taking into account Coulomb friction for both motor ...and load, and using a variable learning rate for adaptation to parameter changes and accelerate convergence. A control structure consists of a feedforward ANN that approximates the manipulator's inverse dynamical model, an ANN feedback control law, a reference model, and the adaptation process of the ANNs with a variable learning rate. A supervisor that adapts the neural network's learning rate and a rule-based supervisor for online adaptation of the parameters of the reference model are proposed to maintain the stability of the system for large variations of load parameters. Simulation results highlight the performance of the controller to compensate the nonlinear friction terms, particularly Coulomb friction, and flexibility, and its robustness to the load and drive motor inertia parameter changes. Internal stability, which is a potential problem in such a system, is also verified. The controller is suitable for DSP and very large scale integration implementation and can be used to improve static and dynamic performances of electromechanical systems.
Ozone (O3) is both a greenhouse gas and a secondary air pollutant causing adverse impacts on forests ecosystems at different scales, from cellular to ecosystem level. Specifically, the phytotoxic ...nature of O3 can impair CO2 assimilation that, in turn affects forest productivity. This study aims to evaluate the effects of tropospheric O3 on Gross Primary Production (GPP) at 37 European forest sites during the time period 2000–2010. Due to the lack of carbon assimilation data at O3 monitoring stations (and vice-versa) this study makes a first attempt to combine high resolution MODIS Gross Primary Production (GPP) estimates and O3 measurement data. Partial Correlations, Anomalies Analysis and the Random Forests Analysis (RFA) were used to quantify the effects of tropospheric O3 concentration and its uptake on GPP and to evaluate the most important factors affecting inter-annual GPP changes. Our results showed, along a North-West/South-East European transect, a negative impact of O3 on GPP ranging from 0.4% to 30%, although a key role of meteorological parameters respect to pollutant variables in affecting GPP was found. In particular, meteorological parameters, namely air temperature (T), soil water content (SWC) and relative humidity (RH) are the most important predictors at 81% of test sites. Moreover, it is interesting to highlight a key role of SWC in the Mediterranean areas (Spanish, Italian and French test sites) confirming that, soil moisture and soil water availability affect vegetation growth and photosynthesis especially in arid or semi-arid ecosystems such as the Mediterranean climate regions.
Considering the pivotal role of GPP in the global carbon balance and the O3 ability to reduce primary productivity of the forests, this study can help in assessing the O3 impacts on ecosystem services, including wood production and carbon sequestration.
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•Assessment of the surface O3 effects on Gross Primary Production (GPP)•GPP is negatively related to O3 concentration and positively to O3 fluxes•Temperature and relative humidity were the most important factors controlling GPP.•Key role of the Soil Water Content in the Mediterranean regions.
European standards for the protection of forests from ozone (O3) are based on atmospheric exposure (AOT40) that is not always representative of O3 effects since it is not a proxy of gas uptake ...through stomata (stomatal flux). MOTTLES “MOnitoring ozone injury for seTTing new critical LEvelS” is a LIFE project aimed at establishing a permanent network of forest sites based on active O3 monitoring at remote areas at high and medium risk of O3 injury, in order to define new standards based on stomatal flux, i.e. PODY (Phytotoxic Ozone Dose above a threshold Y of uptake). Based on the first year of data collected at MOTTLES sites, we describe the MOTTLES monitoring station, together with protocols and metric calculation methods. AOT40 and PODY, computed with different methods, are then compared and correlated with forest–health indicators (radial growth, crown defoliation, visible foliar O3 injury). For the year 2017, the average AOT40 calculated according to the European Directive was even 5 times (on average 1.7 times) the European legislative standard for the protection of forests. When the metrics were calculated according to the European protocols (EU Directive 2008/50/EC or Modelling and Mapping Manual LTRAP Convention), the values were well correlated to those obtained on the basis of the real duration of the growing season (i.e. MOTTLES method) and were thus representative of the actual exposure/flux. AOT40 showed opposite direction relative to PODY. Visible foliar O3 injury appeared as the best forest–health indicator for O3 under field conditions and was more frequently detected at forest edge than inside the forest. The present work may help the set–up of further long–term forest monitoring sites dedicated to O3 assessment in forests, especially because flux-based assessments are recommended as part of monitoring air pollution impacts on ecosystems in the revised EU National Emissions Ceilings Directive.
•The MOTTLES network for active O3 monitoring in forests is described.•In 2017, AOT40 exceeded twice the limit of the European Directive for forests.•O3 metrics from European protocols were representative of actual exposure/fluxes.•AOT40 and PODy were inversely correlated.•Visible foliar injury was the best forest–health indicator for O3.
Present standards for protecting ecosystems from ozone (O3), such as AOT40, use atmospheric concentrations. A stomatal flux-based approach (Phytotoxic O3 Dose, PODY) has been suggested. We compared ...the spatial and temporal distribution of AOT40 and PODY – with and without a hourly threshold of uptake (POD1 and POD0) – for Pinus halepensis and Fagus sylvatica in South-eastern France and North-western Italy. Ozone uptake was simulated by including limitation due to soil water content, as this is an important parameter in water-limited environments. Both AOT40 and POD1 exceeded the critical levels suggested for forests. AOT40 suggested a larger O3 risk relative to PODY. No significant spatial and temporal difference occurred between POD1 and POD0. The use of POD0 in the assessment of ambient O3 risk for vegetation is thus recommended, because it is more biologically-meaningful than AOT40 and easier to be calculated than POD1. Canopy Moisture Content (CMC), a proxy of foliar water content, was modelled and tested as a potential plant O3 response indicator. CMC response to O3 was species-specific, and thus cannot be recommended in the epidemiology of O3 injury to forests.
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•Stomatal ozone flux (POD) is a better metric than AOT40 for the protection of forests.•We recommend POD0 rather than POD1.•We cannot recommend CMC as a plant-response indicator.
Abstract Objective This study assessed the effects of particulate matter (PM), equal or less than 10 μm in aerodynamic diameter (PM10 ), from the Middle-Eastern Dust events on public health in the ...megacity of Kermanshah (Iran). Study design This study used epidemiological modeling and monitored ambient air quality data to estimate the potential PM10 impacts on public health. Methods The AirQ2.2.3 model was used to calculate mortality and morbidity attributed to PM10 as representative of dust events. Using Visual Basic for Applications, the programming language of Excel software, hourly PM10 concentrations obtained from the local agency were processed to prepare input files for the AirQ2.2.3 model. Results Using baseline incidence, defined by the World Health Organization, the number of estimated excess cases for respiratory mortality, hospital admissions for chronic obstructive pulmonary disease, for respiratory diseases, and for cardiovascular diseases were 37, 39, 476, and 184 persons, respectively, from 21st March, 2014 to 20th March, 2015. Furthermore, 92% of mortality and morbidity cases occurred in days with PM10 concentrations lower than 150 μg/m3 . The highest percentage of person-days occurred for daily concentrations range of 100–109 μg/m3 , causing the maximum health end-points among the citizens of Kermanshah. Conclusions Calculating the number of cumulative excess cases for mortality or morbidity attributed to PM10 provides a good tool for decision and policy-makers in the field of health care to compensate their shortcomings particularly at hospital and healthcare centers for combating dust storms. To diminish these effects, several immediate actions should be managed in the governmental scale to control dust such as spreading mulch and planting new species that are compatible to arid area.
In this paper, an adaptive fuzzy control scheme is introduced for permanent magnet synchronous machines (PMSMs). The adaptive control strategy consists of a Lyapunov stability-based fuzzy speed ...controller that capitalizes on the machine's inverse model to achieve accurate tracking with unknown nonlinear system dynamics. As such, robustness to modeling and parametric uncertainties is achieved. Moreover, no explicit currents loop regulation is needed, which simplifies the control structure and unlike other control strategies, no a priori offline training, weights initialization, parameters knowledge, voltage, or current transducer is required. The system's convergence and stability are proved by Lyapunov stability theory, which yields an improved performance. Simulation results for different situations highlight the performance of the proposed controller in transient, steady-state, and standstill conditions. Furthermore, the adaptive fuzzy systems inherent parallelism makes them a good candidate for implementation in real-time PMSM drive systems.
In this paper, we propose an insulated gate bipolar transistor (IGBT) gate driver that provides an optimal gate signal to manage the IGBT switching mechanism, without the need of a feedback current ...measurement across the parasitic inductance of the circuit. Our approach is based on the Posicast method, which allows determining an optimal gate signal shape from pulses whose characteristics are determined from the IGBT model. Experimental results demonstrate the effectiveness of the proposed method to minimize electrical switching constraints.
This paper presents a Proton Exchange Membrane Fuel Cell model suitable for water management analysis. In order to be integrated into a complete fuel cell vehicle simulation for real-time control and ...energy management designs, Energetic Macroscopic Representation is used. An experimental validation is performed and electric and gaseous behaviors are studied in particular. The integration of the developed model into a vehicle simulation, in which the FC is used as a range extender, demonstrates the use of the model and allows the study of the behavior of this system.
► This paper presents a Proton Exchange Membrane Fuel Cell model suitable for water management analysis. ► An experimental validation of the model is proposed. ► The objectives of the model are: integration into a system simulation, local & control design. ► As an example, the model is integrated into a complete vehicle simulation.
