Prolamin proteins alteration in durum wheat by species of the genus Eurygaster and Aelia (Insecta, Hemiptera)

Postprint (published version

SBI is uncommon in the absence of paediatricians' gut feeling and abnormal respiratory pattern

According to the Italian national statistical institute, severe bacterial infections (SBI) in Italy are responsible for 1.7% of mortality under five years of age and their recognition is often challenging, especially in the first stages of the disease. We tried to estimate the prevalence of SBI in our target population and to identify signs and symptoms that could guide in the initial evaluation of a child with a possible SBI

Latitudinal variation in circadian rhythmicity in <i>Nasonia vitripennis</i>

Many physiological processes of living organisms show circadian rhythms, governed by an endogenous clock. This clock has a genetic basis and is entrained by external cues, such as light and temperature. Other physiological processes exhibit seasonal rhythms, that are also responsive to light and temperature. We previously reported a natural latitudinal cline of photoperiodic diapause induction in the parasitic wasp Nasonia vitripennis in Europe and a correlated haplotype frequency for the circadian clock gene period (per). To evaluate if this correlation is reflected in circadian behaviour, we investigated the circadian locomotor activity of seven populations from the cline. We found that the proportion of rhythmic males was higher than females in constant darkness, and that mating decreased rhythmicity of both sexes. Only for virgin females, the free running period (tau) increased weakly with latitude. Wasps from the most southern locality had an overall shorter free running rhythm and earlier onset, peak, and offset of activity during the 24 h period, than wasps from the northernmost locality. We evaluated this variation in rhythmicity as a function of period haplotype frequencies in the populations and discussed its functional significance in the context of local adaptation

Photovoltaic energy systems

This report outlines the European Commission's Joint Research Centre's contribution to standardisation activities within the field of Photovoltaic Energy Systems. The Joint Research Centre (JRC) continues to play a significant role in European and international standardisation activities within the field of Photovoltaic Energy Systems. In particular JRC experts are convenors for working groups in both the relevant IEC and CENELEC technical committees, were the project leader of one standards published by the IEC in 2019 and made a significant contribution to many others. JRC is also the project leader for two more standards which are currently subject to the standardisation process.JRC.C.2-Energy Efficiency and Renewable

Relevant Physiological Indicators for Assessing Workload in Conditionally Automated Driving, Through Three-Class Classification and Regression

In future conditionally automated driving, drivers may be asked to take over control of the car while it is driving autonomously. Performing a non-driving-related task could degrade their takeover performance, which could be detected by continuous assessment of drivers' mental load. In this regard, three physiological signals from 80 subjects were collected during 1 h of conditionally automated driving in a simulator. Participants were asked to perform a non-driving cognitive task (N-back) for 90 s, 15 times during driving. The modality and difficulty of the task were experimentally manipulated. The experiment yielded a dataset of drivers' physiological indicators during the task sequences, which was used to predict drivers' workload. This was done by classifying task difficulty (three classes) and regressing participants' reported level of subjective workload after each task (on a 0–20 scale). Classification of task modality was also studied. For each task, the effect of sensor fusion and task performance were studied. The implemented pipeline consisted of a repeated cross validation approach with grid search applied to three machine learning algorithms. The results showed that three different levels of mental load could be classified with a f1-score of 0.713 using the skin conductance and respiration signals as inputs of a random forest classifier. The best regression model predicted the subjective level of workload with a mean absolute error of 3.195 using the three signals. The accuracy of the model increased with participants' task performance. However, classification of task modality (visual or auditory) was not successful. Some physiological indicators such as estimates of respiratory sinus arrhythmia, respiratory amplitude, and temporal indices of heart rate variability were found to be relevant measures of mental workload. Their use should be preferred for ongoing assessment of driver workload in automated driving

Effect of Obstacle Type and Cognitive Task on Situation Awareness and Takeover Performance in Conditionally Automated Driving

In conditionally automated driving, several factors can affect the driver’s situation awareness and ability to take over control. To better understand the influence of some of these factors, 88 participants spent 20 minutes in a conditionally automated driving simulator. They had to react to four obstacles that varied in danger and movement. Half of the participants were required to engage in a verbal cognitive non-driving-related task. Situation awareness, takeover performance and physiological responses were measured for each situation. The results suggest that obstacle movement influences obstacle danger perception, situation awareness, and response time, while the latter is also influenced by obstacle danger. The cognitive verbal task also had an effect on the takeover response time. These results imply that the driver’s cognitive state and the driving situation (e.g. the movement/danger of entities present around the vehicle) must be considered when conveying information to drivers through in-vehicle interfaces

3,5-Diiodo-L-Thyronine Modifies the Lipid Droplet Composition in a Model of Hepatosteatosis

Background/Aims: Fatty acids are the main energy stores and the major membrane components of the cells. In the hepatocyte, fatty acids are esterified to triacylglycerols (TAGs) and stored in lipid droplets (LDs). The lipid lowering action of 3,5-diiodo-L-thyronine (T 2 ) on an in vitro model of hepatosteatosis was investigated in terms of fatty acid and protein content of LDs, lipid oxidation and secretion. Methods: FaO cells were exposed to oleate/ palmitate, then treated with T 2 . Results: T 2 reduced number and size of LDs, and modified their acyl composition by decreasing the content of saturated (SFA) vs monounsaturated (MUFA) fatty acids thus reversing the SFA/MUFA ratio. The expression of the LD-associated proteins adipose differentiation-related protein (ADRP), oxidative tissue-enriched PAT protein (OXPAT), and adipose triglyceride lipase (ATGL) was increased in 'steatotic' cells and further up-regulated by T 2 . Moreover, T 2 stimulated the mitochondrial oxidation by up-regulating carnitine-palmitoyl-transferase (CPT1), uncoupling protein 2 (UCP2) and very long-chain acylcoenzyme A dehydrogenase (VLCAD). Conclusions: T 2 leads to mobilization of TAGs from LDs and stimulates mitochondrial oxidative metabolism of fatty acids, in particular of SFAs, and thus enriches of MUFAs the LDs. This action may protect the hepatocyte from excess of SFAs that are more toxic than MUFAs

A dataset on the physiological state and behavior of drivers in conditionally automated driving

This dataset contains data of 346 drivers collected during six experiments conducted in a fixed-base driving simulator. Five studies simulated conditionally automated driving (L3 SAE), and the other one simulated manual driving (L0-SAE). The dataset includes physiological data (electrocardiogram (ECG), electrodermal activity (EDA), and respiration (RESP)), driving and behavioral data (reaction time, steering wheel angle, …), performance data of non-driving-related tasks, and questionnaire responses. Among them, measures from standardized questionnaires were collected, either to control the experimental manipulation of the driver's state, or to measure constructs related to human factors and driving safety (drowsiness, mental workload, affective state, situation awareness, situational trust, user experience). In the provided dataset, some raw data have been processed, notably physiological data from which physiological indicators (or features) have been calculated. The latter can be used as input for machine learning models to predict various states (sleep deprivation, high mental workload, ...) that may be critical for driver safety. Subjective self-reported measures can also be used as ground truth to apply regression techniques. Besides that, statistical analyses can be performed using the dataset, in particular to analyze the situational awareness or the takeover quality of drivers, in different states and different driving scenarios. Overall, this dataset contributes to better understanding and consideration of the driver's state and behavior in conditionally automated driving. In addition, this dataset stimulates and inspires research in the fields of physiological/affective computing and human factors in transportation, and allows companies from the automotive industry to better design adapted human-vehicle interfaces for safe use of automated vehicles on the roads

Standards for the assessment of the environmental performance of photovoltaic modules, power conversion equipment and photovoltaic systems

To support the on-going preparatory activities on the feasibility of applying the EcoDesign, EU Energy label, EU Ecolabel and Green Public Procurement (GPP) policy instruments to solar photovoltaic modules, inverters and systems, this report aims to: • Identify, describe and compare existing standards and new standards under development, relevant to energy performance, reliability, degradation and lifetime. • Identify aspects not covered by existing standards, for which transitional methods may be needed.JRC.C.2-Energy Efficiency and Renewable