HIT09 (Italy)

Gas turbine fuel burn for an aircraft engine can be obtained analytically using thermodynamic cycle analysis. For large-diameter ultra-high bypass ratio turbofans, the impact of nacelle drag and propulsion system integration must be accounted for in order to obtain realistic estimates of the installed specific fuel consumption. However, simplified models cannot fully represent the complexity of installation effects. In this paper, we present a method that combines thermodynamic cycle analysis with detailed Computational Fluid Dynamics (CFD) modelling of the installation aerodynamics to obtain the fuel consumption at a given mission point. The flow field and propulsive forces arising in a transport aircraft powered by an ultra-high bypass ratio turbofan at cruise are first examined to characterise the operating conditions and measure the sensitivity to variations of the incidence at transonic flight. The proposed methodology, in which dynamic balance of the vehicle is achieved at each integration point, is then applied along a cruise segment to calculate the cumulative fuel burn and the change in the specific fuel consumption.

Longhorn beetles are commonly moved among continents within wood packaging materials used in trades. Visual inspections carried out at points of entry often fail to detect exotic longhorn beetles as infested materials may have little or no sign of colonization. Black-colored traps baited with pheromones and host volatiles are thus used to improve chances of detection. Here we tested whether existing surveillance protocols for longhorn beetles can be further improved using trap colors different than black. Baited traps of eight different colors (i.e., grey, yellow, green, red, blue, brown, purple and black) were deployed in a randomized complete block design at 16 sites in northern Italy in 2019. A total of 6,001 individuals from 56 longhorn beetle species were trapped. In general, yellow and blue traps caught a significantly higher number of longhorn beetle species than black traps. In addition, trap color significantly affected species richness and abundance at the subfamily and species level, with mixed response mostly linked to the habit of visiting flowers for food. Flower-visiting longhorn beetles mainly exhibited clear preference for flower-related colors, i.e., yellow, green and blue, whereas non-flower-visiting species were more attracted by dark and long-wavelength-dominated colors, like red and brown. Our results clearly indicate that generic surveillance programs should not rely exclusively on black traps and that the use of more trap colors can strongly improve the chance of detecting native and exotic longhorn beetles potentially moved with trades.

“You may not be able to put the book down” (“Preface”, p. xi): Glen O. Gabbard correctly predicts in his enthusiastic preface to this engaging book. It is striking how much more this applies in the...

More and more sophisticated assisted/autonomous vehicles are becoming available in the market. Automation levels 2 and 3 have been given for settled just a couple of years ago, and the path to fully autonomous car seemed to have no obstacles. In reality, OEMs started recently realizing that the impact of semi and/or fully robotized cars on drivers as well as on passengers is all but predictable. VI-grade has more than ten years experience with developing turn-key solution driving simulators, and has been working for more than five years on a research project to collect meaningful bio-signals from the driver during simulator sessions, in collaboration with the BACPIC of the Catholic University of Sacred Heart and the DPIA of the University of Udine. Recently, a collaboration with the Human Inspired Technology Research Center of University of Padova allowed the extension of the assessment at physio-emotional level.

Abstract The neocortex is organized into discrete layers of excitatory neurons: layer 4 receives the densest ‘bottom up’ projection carrying external sensory data, while layers 2/3 and 5 receive ‘top down’ inputs from higher cortical areas that may convey sensory expectations and behavioral goals. A subset of cortical somatostatin (SST) neurons gate top down input and control sensory computation by inhibiting the apical dendrites of pyramidal cells in layers 2/3 and 5. However, it is unknown whether an analogous inhibitory mechanism separately and specifically controls activity in layer 4. We hypothesized that distinct SST circuits might exist to inhibit specific cortical layers. By enforcing layer-specific inhibition, distinct SST subnetworks could mediate pathway-specific gain control, such as regulating the balance between bottom up and top down input. Employing a combination of high precision circuit mapping, in vivo optogenetic perturbations, and single cell transcriptional profiling, we reveal distinct and complementary SST circuits that specifically and reciprocally interconnect with excitatory cells in either layer 4 or layers 2/3 and 5. Our data further define a transcriptionally distinct SST neuronal sub-class that powerfully gates bottom up sensory activity during active sensation by regulating layer 4 activity. This integrated paradigm further represents a potentially generalizable approach to identify and characterize neuronal cell types and reveal their in vivo function.

LoRaWAN networks are growing in popularity and adoption, mainly thanks to the inexpensive devices, the affordable gateway costs, and the possibility to opt for a private deployment or the use of global network providers. While the main use case for these networks is sensor data collection, the standard also defines confirmed messages, for which downlink transmissions are required. In this paper we show that an incautious use of this feature can bring a sharp decrease in the performance of the network, especially for large scale deployments. Additionally, we present some insights on how certain design choices for downlink communication in LoRaWAN are impairing confirmed traffic usage and propose some solutions to mitigate the issue.