Attitude of European car drivers towards electric vehicles: a survey

CO2 emissions from road transport have risen significantly in the past and projections show that they will continue to rise in the future if no adequate policy measures are implemented. Several European initiatives aim at reducing CO2 emissions from passenger vehicles. A potential option to reduce passenger vehicle CO2 emissions is the deployment of electric vehicles (EV). Consumer perception and willingness to purchase these new vehicle technologies lies at the heart of its successful large scale diffusion. This report aims at describing and analyzing how car drivers in the six countries France, Germany, Italy, Poland, Spain, and United Kingdom consider electric cars, how familiar they are with the electric car concept and its main features. It investigates, which features of EVs people consider essential in terms of propensity to consider electric cars a realistic alternative in case they wanted to purchase a new car. 600 drivers on average per each of the six Member States responded to the questionnaire. As a result we derive an “ideal” composition of an electric car in terms of car purchase price, range, re-charge time and maximum speed. The perspective of the European car drivers, as derived from this study, highlights the importance of further R&D investments to improve some of the performance characteristics of electric vehicles. It provides some guidance which performance aspects matter most for car drivers, notably costs and range. The study finds that the familiarity of car drivers with the electric vehicle aspects is lower when direct exposure or driving experience would be needed to properly assess these aspects. This stresses the need of demonstration activities in order to increase public awareness of electro-mobility and also to receive first hand feedback from car drivers on their experience operating an electric vehicle. A majority of the respondents considers that public incentives are needed to foster a wider market deployment of electric vehicles. Furthermore the study shows that an adequate re-charge network is perceived as crucial by car drivers. It can be concluded that European car drivers see the opportunities that electric vehicles could offer but that a number of pre-requisites need to be fulfilled in order to ensure that the car drivers can consider electric vehicles as a credible vehicle choice.JRC.F.6-Energy systems evaluatio

Aspirin-dependent effects on purinergic P2Y1 receptor express

Chronic treatment with aspirin in healthy volunteers (HVs) is associated with recovery of adenosine diphosphate (ADP)-induced platelet activation. The purinergic P2Y1 receptor exerts its effects via a Gq-protein, which is the same biochemical pathway activated by thromboxane-A2 receptor. We hypothesized that recovery of ADP-induced platelet activation could be attributed to increased P2Y1 expression induced by chronic aspirin exposure. We performed a multi-phase investigation which embraced both in vitro and in vivo experiments conducted in (1) human megakaryoblastic DAMI cells, (2) human megakaryocytic progenitor cell cultures, (3) platelets obtained from HVs treated with aspirin and (4) platelets obtained from aspirin-treated patients. DAMI cells treated with aspirin or WY14643 (PPARα agonist) had a significant up-regulation of P2Y1 mRNA, which was shown to be a PPARα-dependent process. In human megakaryocytic progenitors, in the presence of aspirin or WY14643, P2Y1 mRNA expression was higher than in mock culture. P2Y1 expression increased in platelets obtained from HVs treated with aspirin for 8 weeks. Platelets obtained from patients who were on aspirin for more than 2 months had increased P2Y1 expression and ADP-induced aggregation compared with patients on aspirin treatment for less than a month. Overall, our results suggest that aspirin induces genomic changes in megakaryocytes leading to P2Y1 up-regulation and that PPARα is the nuclear receptor involved in this regulation. Since P2Y1 is coupled to the same Gq-protein of thromboxane-A2 receptor, platelet adaptation in response to pharmacological inhibition seems not to be receptor specific, but may involve other receptors with the same biochemical pathway

Driving and parking patterns of European car drivers – a mobility survey

The development of innovative vehicles such as electric driven cars is an important potential option for improving the sustainability of the transport sector. A significant penetration of electric vehicles in the market is possible only if their use is compatible with mobility patterns of individuals. For instance, the driven distance should be compatible with the batteries range or parking patterns should enable re-charging. The JRC-IET together with TRT and IPSOS analyzed car mobility patterns derived from direct surveys in six European Union Member States (France, Germany, Italy, Poland, Spain and United Kingdom). The report aims at providing some insights on how electric vehicles could fit mobility habits of European car drivers. The analysis is based on the data collected within six European countries by means of a sample survey. A web-based car trips diary was filled in by on average 600 individuals in each country. The individuals logged for 7 consecutive days their driving and parking patterns in 5 minute intervals. For each trip several details such as departure and arrival time, distance and parking place were registered. Socioeconomic characteristics of individuals were also collected. The same questionnaire format was used in all countries allowing for comparability of responses. Representativeness of the derived data was ensured by weighting and aligning the received sample to the socio-demographic reference universe of each member state. Survey results are statistically analyzed to describe mobility patterns. In particular, the information on average number of car trips per day, daily travel distance, daily travel time, trip distance, distribution of parking and driving, distribution of parking places, trip purposes, duration of parking and many other parameters per Member State are analyzed and presented in the report. Moreover, the analysis of the survey data shows which share of driving patterns are compatible with the use of electric cars with their current technical features (batteries range, re-charge time) under alternative assumptions about the availability of re-charge facilities. Also differences and similarities between countries and user groups are discussed. Overall, the results of the survey provide representative driving profiles for estimating the charging profiles of electric vehicles and many other indications on how people use their car. The outcomes of the survey provide relevant methodological hints to develop similar surveys in other contexts or to repeat the survey in other countries.JRC.F.6-Energy systems evaluatio

Dense Hebbian neural networks: a replica symmetric picture of supervised learning

We consider dense, associative neural-networks trained by a teacher (i.e., with supervision) and we investigate their computational capabilities analytically, via statistical-mechanics of spin glasses, and numerically, via Monte Carlo simulations. In particular, we obtain a phase diagram summarizing their performance as a function of the control parameters such as quality and quantity of the training dataset, network storage and noise, that is valid in the limit of large network size and structureless datasets: these networks may work in a ultra-storage regime (where they can handle a huge amount of patterns, if compared with shallow neural networks) or in a ultra-detection regime (where they can perform pattern recognition at prohibitive signal-to-noise ratios, if compared with shallow neural networks). Guided by the random theory as a reference framework, we also test numerically learning, storing and retrieval capabilities shown by these networks on structured datasets as MNist and Fashion MNist. As technical remarks, from the analytic side, we implement large deviations and stability analysis within Guerra's interpolation to tackle the not-Gaussian distributions involved in the post-synaptic potentials while, from the computational counterpart, we insert Plefka approximation in the Monte Carlo scheme, to speed up the evaluation of the synaptic tensors, overall obtaining a novel and broad approach to investigate supervised learning in neural networks, beyond the shallow limit, in general.Comment: arXiv admin note: text overlap with arXiv:2211.1406

Dense Hebbian neural networks: a replica symmetric picture of unsupervised learning

We consider dense, associative neural-networks trained with no supervision and we investigate their computational capabilities analytically, via a statistical-mechanics approach, and numerically, via Monte Carlo simulations. In particular, we obtain a phase diagram summarizing their performance as a function of the control parameters such as the quality and quantity of the training dataset and the network storage, valid in the limit of large network size and structureless datasets. Moreover, we establish a bridge between macroscopic observables standardly used in statistical mechanics and loss functions typically used in the machine learning. As technical remarks, from the analytic side, we implement large deviations and stability analysis within Guerra's interpolation to tackle the not-Gaussian distributions involved in the post-synaptic potentials while, from the computational counterpart, we insert Plefka approximation in the Monte Carlo scheme, to speed up the evaluation of the synaptic tensors, overall obtaining a novel and broad approach to investigate neural networks in general

Assessing penetration resistance in Phalaris arundinacea harvest operations under minimum tillage conditions

Harvesting operations of perennial forage crops can lead to soil compaction problems, which in turn lead to poorer soil structure, increased erosion, and reduced organic matter. The present study focuses on the evaluation of soil compaction caused by harvesting operations of Phalaris arundinacea (Reed Canary Grass) by measuring soil penetration resistance in two different areas of the farm of the University of Tuscia. The measurements were carried out in two consecutive years following the biomass harvesting operations. These field trials are part of the H2020 project CERESiS (ContaminatEd land Remediation through Energy crops for Soil improvement to liquid biofuels Strategies) (GA 101006717), which started in November 2020 and will continue until the end of the project in 2024. P. arundinacea is a species that lends itself to biomass production and phytoremediation of contaminated soils. The areas with different textures were treated with a minimum tillage system, notably, only a secondary tillage of the field with a disc harrow was carried out in late winter 2021 and sown in spring 2021. Part of each area was allocated for control and was fenced off after sowing, to avoid any trampling. The remaining areas were divided into 3 plots in which the operations were repeated. Measurements were taken in 2021 and 2022 following harvesting operations using a John Deere 5100 GF tractor with disc mower. Penetration resistance and soil moisture measurements followed, to verify the impact of the operations and the effect of soil type on compaction. For penetration resistance, 15 measurements per plot were taken up to a depth of 80 cm using an electronic penetrometer model Penetrologger (Royal Eijkelkamp Soil &Water; Giesbeek, The Netherlands). The results of the soil analysis indicate different chemical and physical characteristics between the two areas, in particular, one area has a clay texture and the other a sandy loam texture. The data collected from the measurement of penetration resistance pointed out significant differences between the plots subjected to tractor passage for harvesting operations and the control areas. Differences were also observed between the two areas, which was an expected result given the different texture and humidity recorded; thus, confirming the effect that this parameter can have on compaction and giving an indication of when to avoid entering the field. It was interesting to note that an effect on the soil can already be seen after two years, despite the minimal intervention. Inspection at different depths showed a general tendency for resistance to penetration to increase with increasing depth, a greater difference between treatments (with tractor and control) up to 40 cm and a tendency to overlap beyond this depth. It will now be interesting to see how this will evolve over the next few years and to assess how the increase in penetration resistance can be further reduced. Compaction affects many other soil parameters, in a context of climate change, it is crucial to implement strategies to reduce it in agricultural operations

Rehabilitation of COVID-19 patients

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The Role of Laparoscopy in the Management of a Diagnostic Dilemma: Jejunal Ectopic Pancreas Developing into Jejunojejunal Intussusception

Ectopic pancreas (EP) is a rare congenital anomaly defined as the presence of pancreatic tissue in topographic anomaly. It is usually silent but it may become clinically evident when complicated by acute conditions. The development of laparoscopic surgery has changed the way to manage such conditions, especially in the setting of emergency surgery, thanks to its diagnostic and therapeutic role with excellent results. We decided to perform an emergency diagnostic exploratory laparoscopy in a 29-year-old man with an acute abdomen and nonspecific radiological images for intestinal occlusion. A jejunojejunal intussusception was found, caused by a mass. We decided to carry out minilaparotomy to perform a resection of the affected jejunum. Histological examination confirmed the presence of a jejunal ectopic pancreas. Adult intussusception caused by EP represents 5% of all cases of intussusception. As CT scan, especially when performed in emergency setting for small bowel obstruction diagnosis, can usually demonstrate nondiagnostic findings suggestive of intussusception of unknown origin, laparoscopic exploration could help surgeons in order to perform a resolute diagnosis and treat the pathology

Reaction: Italian referendum and Matteo Renzi’s resignation

Italian Prime Minister, Matteo Renzi, has announced he will resign following defeat in the country’s constitutional referendum. We asked a number of EUROPP contributors for their immediate thoughts on the result, Renzi’s resignation, and where Italy is heading next. Alberto Alemanno: “The vote has killed the dream of once in a generation change” James Newell: “The result was not simply another anti-establishment revolt” Andrea Lorenzo Capussela: “Rationality imposed itself, and in large numbers” Silvia Merler: “Italy is now headed for a complex and delicate period of political and economic uncertainty” Lorenzo Piccoli: “Renzi did not have much choice but to resign” Jonas Bergan Draege: “Both the M5S and Lega Nord could emerge strengthened from the No vote” Angelo Martelli: “The determinant factor of Renzi’s defeat has been the sluggish pace of the Italian recovery” Davide Morisi: “The correlation is clear: Renzi’s personalisation strategy has backfired” Mattia Guidi: “Listening to the will of the people will be a hard task: several questions have no answer at present” James Dennison: “This was no Brexit-Trump moment: The package of reforms was complex and broad enough for citizens of all stripes to find cause for concern” Fabio Bordignon: “Renzi’s 41% – ironically, the same result he had obtained at the 2014 European election – became the symbol of his defeat

Probing Single-Cell Fermentation Fluxes and Exchange Networks via pH-Sensing Hybrid Nanofibers

The homeostatic control of their environment is an essential task of living cells. It has been hypothesized that, when microenvironmental pH inhomogeneities are induced by high cellular metabolic activity, diffusing protons act as signaling molecules, driving the establishment of exchange networks sustained by the cell-to-cell shuttling of overflow products such as lactate. Despite their fundamental role, the extent and dynamics of such networks is largely unknown due to the lack of methods in single-cell flux analysis. In this study, we provide direct experimental characterization of such exchange networks. We devise a method to quantify single-cell fermentation fluxes over time by integrating high-resolution pH microenvironment sensing via ratiometric nanofibers with constraint-based inverse modeling. We apply our method to cell cultures with mixed populations of cancer cells and fibroblasts. We find that the proton trafficking underlying bulk acidification is strongly heterogeneous, with maximal single-cell fluxes exceeding typical values by up to 3 orders of magnitude. In addition, a crossover in time from a networked phase sustained by densely connected "hubs" (corresponding to cells with high activity) to a sparse phase dominated by isolated dipolar motifs (i.e., by pairwise cell-to-cell exchanges) is uncovered, which parallels the time course of bulk acidification. Our method addresses issues ranging from the homeostatic function of proton exchange to the metabolic coupling of cells with different energetic demands, allowing for real-time noninvasive singlecell metabolic flux analysis