In this work, we study doping-free hybrid heterojunction interfaces based on silicon, poly(3,4-ethylene dioxythiophene)-poly(styrene sulfonate) (PEDOT:PSS) and conjugated polyelectrolyte poly [(9,9-bis(3′-(N, N-dimethylamino) propyl)-2,7-fluorene)-alt-2,7-(9,9–dioctylfluorene) (PFN). For this, three types of hybrid structures were fabricated: a single hybrid structure (ITO/PEDOT:PSS/Si–C:H (buffer)/(i) a-Si:H/(n) a-Si:H/Ag), a double hybrid structure (ITO/PEDOT:PSS/Si–C:H (buffer)/(i) a-Si:H/PFN/Al) and an inorganic a-Si:H-based structure reference. The compositional and interface characteristics were studied by secondary ion mass spectroscopy and atomic force microscopy demonstrating a good definition of the PFN and PEDOT:PSS polymer layers through the hybrid structures. However, the PEDOT:PSS/ITO interfaces show degradation with the diffusion of Sn and In into the polymer layer. Finally, to characterize the optical and electrical properties of the heterojunctions, the photovoltaic response of the structures was measured and compared with optical simulations. Good agreement between experimental and simulation results demonstrated the reliability of the deposition process of the organic layers and validates the optical model to describe and optimize the hybrid heterojunctions.
Gas-surface interactions at the Moon, Mercury and other massive planetary bodies constitute, alongside production and escape, an essential element of the physics of their gravitationally bound exospheres. From condensation and accumulation of exospheric species onto the surface in response to diurnal and seasonal changes of surface temperature, to thermal accommodation, diffusion and ultimate escape of these species from the regolith back into space, surface-interactions have a drastic impact on exospheric composition, structure and dynamics. The study of this interaction at planetary bodies combines exospheric modeling and observations with a consideration of fundamental physics and laboratory experimentation in surface science. With a growing body of earth-based and spacecraft observational data, and a renewed focus on lunar missions and exploration, the connection between the exospheres and surfaces of planetary bodies is an area of active and growing research, with advances being made on problems such as topographical and epiregolith thermal effects on volatile cold trapping, among others. In this paper we review current understanding, latest developments, outstanding issues and future directions on the topic of exosphere-surface interactions at the Moon, Mercury and elsewhere.
General relativity and its Newtonian weak field limit are not sufficient to explain the observed phenomenology in the Universe, from the formation of large-scale structures to the dynamics of galaxies, with the only presence of baryonic matter. The most investigated cosmological model, the ΛCDM, accounts for the majority of observations by introducing two dark components, dark energy and dark matter, which represent ∼95% of the mass-energy budget of the Universe. Nevertheless, the ΛCDM model faces important challenges on the scale of galaxies. For example, some very tight relations between the properties of dark and baryonic matters in disk galaxies, such as the baryonic Tully–Fisher relation (BTFR), the mass discrepancy–acceleration relation (MDAR), and the radial acceleration relation (RAR), which see the emergence of the acceleration scale a0≃1.2×10−10 m s−2, cannot be intuitively explained by the CDM paradigm, where cosmic structures form through a stochastic merging process. An even more outstanding coincidence is due to the fact that the acceleration scale a0, emerging from galaxy dynamics, also seems to be related to the cosmological constant Λ. Another challenge is provided by dwarf galaxies, which are darker than what is expected in their innermost regions. These pieces of evidence can be more naturally explained, or sometimes even predicted, by modified theories of gravity, that do not introduce any dark fluid. I illustrate possible solutions to these problems with the modified theory of gravity MOND, which departs from Newtonian gravity for accelerations smaller than a0, and with Refracted Gravity, a novel classical theory of gravity introduced in 2016, where the modification of the law of gravity is instead regulated by a density scale.
Weeds are a crucial threat to agriculture, and in order to preserve crop productivity, spreading agrochemicals is a common practice with a potential negative impact on the environment. Methods that can support intelligent application are needed. Therefore, identification and mapping is a critical step in performing site-specific weed management. Unmanned aerial vehicle (UAV) data streams are considered the best for weed detection due to the high resolution and flexibility of data acquisition and the spatial explicit dimensions of imagery. However, with the existence of unstructured crop conditions and the high biological variation of weeds, it remains a difficult challenge to generate accurate weed recognition and detection models. Two critical barriers to tackling this challenge are related to (1) a lack of case-specific, large, and comprehensive weed UAV image datasets for the crop of interest, (2) defining the most appropriate computer vision (CV) weed detection models to assess the operationality of detection approaches in real case conditions. Deep Learning (DL) algorithms, appropriately trained to deal with the real case complexity of UAV data in agriculture, can provide valid alternative solutions with respect to standard CV approaches for an accurate weed recognition model. In this framework, this paper first introduces a new weed and crop dataset named Chicory Plant (CP) and then tests state-of-the-art DL algorithms for object detection. A total of 12,113 bounding box annotations were generated to identify weed targets (Mercurialis annua) from more than 3000 RGB images of chicory plantations, collected using a UAV system at various stages of crop and weed growth. Deep weed object detection was conducted by testing the most recent You Only Look Once version 7 (YOLOv7) on both the CP and publicly available datasets (Lincoln beet (LB)), for which a previous version of YOLO was used to map weeds and crops. The YOLOv7 results obtained for the CP dataset were encouraging, outperforming the other YOLO variants by producing value metrics of 56.6%, 62.1%, and 61.3% for the mAP@0.5 scores, recall, and precision, respectively. Furthermore, the YOLOv7 model applied to the LB dataset surpassed the existing published results by increasing the mAP@0.5 scores from 51% to 61%, 67.5% to 74.1%, and 34.6% to 48% for the total mAP, mAP for weeds, and mAP for sugar beets, respectively. This study illustrates the potential of the YOLOv7 model for weed detection but remarks on the fundamental needs of large-scale, annotated weed datasets to develop and evaluate models in real-case field circumstances.
We present the first high spatial resolution radio continuum survey of the southern Galactic plane. The CORNISH project has mapped the region defined by 295○ < l < 350○; |b| < 1○ at 5.5-GHz, with a resolution of 2.5″ (FWHM). As with the CORNISH-North survey, this is designed to primarily provide matching radio data to the Spitzer GLIMPSE survey region. The CORNISH-South survey achieved a root mean square noise level of ∼ 0.11 mJy beam−1, using the 6A configuration of the Australia Telescope Compact Array (ATCA). In this paper, we discuss the observations, data processing and measurements of the source properties. Above a 7σ detection limit, 4701 sources were detected, and their ensemble properties show similar distributions with their northern counterparts. The catalogue is highly reliable and is complete to 90 per cent at a flux density level of 1.1 mJy. We developed a new way of measuring the integrated flux densities and angular sizes of non-Gaussian sources. The catalogue primarily provides positions, flux density measurements and angular sizes. All sources with IR counterparts at 8μm have been visually classified, utilizing additional imaging data from optical, near-IR, mid-IR, far-IR and sub-millimetre galactic plane surveys. This has resulted in the detection of 524 H II regions of which 255 are ultra-compact H II regions, 287 planetary nebulae, 79 radio stars and 6 massive young stellar objects. The rest of the sources are likely to be extra-galactic. These data are particularly important in the characterization and population studies of compact ionized sources such as UCHII regions and PNe towards the Galactic mid-plane.
The advanced and personalised experience that modern cars offer makes them more and more data-hungry. For example, the cabin preferences of the possible drivers must be recorded and associated to some identity, while such data could be exploited to deduce sensitive information about the driver’s health. Therefore, drivers’ privacy must be taken seriously, requiring a dedicated risk assessment framework, as presented in this paper through a double assessment combining the asset-oriented ISO approach with the threat-oriented STRIDE approach. The framework is tailored to the level of specific car brand and demonstrated on the ten top-selling brands as well as, due to its innovative character, Tesla. The two approaches yield different, but complementary findings, demonstrating the additional insights gained through their parallel adoption.
We report on one of the first solar-eruptive events that was simultaneously observed by three of the remote-sensing instruments onboard Solar Orbiter during the cruise phase. The Extreme Ultraviolet Imager (EUI) observed an eruption on 22 April 2021. The corresponding CME was recorded by the coronagraph Metis. Finally, the Spectrometer/Telescope for Imaging X-rays (STIX) sampled the associated X-ray flare, which was partially occulted. From the Earth, the eruption-source region was observed close to disk center. We provide an analysis of the eruption as observed by these various instruments. In particular, we show that in this eruption, continuous magnetic reconnection and heating have to be present even well after the impulsive phase. The need for this is derived from multiple independent lines of evidence – using both flare and CME observations – that have not been reported before for a single event. The combination of data from Solar Orbiter, as well as other space-based assets, clearly showcases the scientific potential for the science phase of Solar Orbiter, and the unique observations available.
In this work, we present the most updated catalog of Io hot spots based on Juno/JIRAM data. We find 242 hot spots, including 23 previously undetected. Over the half of the new hot spots identified, are located at high northern and southern latitudes (>70°). We observe a latitudinal variability and a larger concentration of hot spots in the polar regions, in particular in the North. The comparison between JIRAM and the most recent Io hot spot catalogs listing power output (Veeder et al., 2015, https://doi.org/10.1016/j.icarus.2014.07.028; de Kleer, de Pater, et al., 2019, https://doi.org/10.3847/1538-3881/ab2380), shows JIRAM detected 63% and 88% of the total number of hot spots, respectively. Furthermore, JIRAM observed 16 of the 34 faint hot spots previously identified. JIRAM data revealed thermal emission from 5 dark pateræ inferred to be active from color ratio images, thus confirming that these are hot spots.
Outgassing or thruster’s generated contaminants are critical for optical surfaces and optical payloads because scientific measurements and, in general, the performances can be degraded or jeopardized by uncontrolled contamination. This is a well-known issue in space technology that is demonstrated by the growing usage of quartz crystal microbalances as a solution for measuring material outgassing properties data and characterizing the on-orbit contamination environment. Operation in space requires compatibility with critical requirements, especially the mechanical and thermal environments to be faced throughout the mission. This work provides the design of a holding structure based on 3D printing technology conceived to meet the environmental characteristics of space application, and in particular, to face harsh mechanical and thermal environments. A kinematic mounting has been conceived to grant compatibility with a large temperature range, and it has been designed by finite element methods to overcome loading during the launch phases and cope with a temperature working range down to cryogenic temperatures. Qualification in such environments has been performed on a mockup by testing a prototype of the holding assembly between −110 ∘C and 110 ∘C and allowing verification of the mechanical resistance and stability of the electrical contacts for the embedded heater and sensor in that temperature range. Moreover, mechanical testing in a random environment characterized by an RMS acceleration level of 500 m/s2 and excitation frequency from 20 to 2000 Hz was successfully performed. The testing activity allowed for validation of the proposed design and opened the road to the possible implementation of the proposed design for future flight opportunities, also onboard micro or nanosatellites. Moreover, exploiting the manufacturing technology, the proposed design can implement an easy assembling and mounting of the holding system. At the same time, 3D printing provides a cost-effective solution even for small series production for ground applications, like monitoring the contaminants in thermo-vacuum chambers or clean rooms, or depositions chambers.
The interest of the scientific community in Titan, Saturn’s largest moon, is still strong. In fact, after the successful Cassini–Huygens mission, which landed the Huygens capsule on Titan, other missions are planned in the coming years. The aims of this work are to provide the extent of global aerodynamic force, to provide thermal and aerodynamic loads on a capsule entering Titan atmosphere, and to evaluate the effects of chemistry on 1) flowfield parameters, 2) surface catalyticity, 3) temperature and pressure distributions on a heat shield, and 4) global aerodynamic force. To develop this study, the authors used the Huygens capsule and related entry trajectory. The study was carried out in the altitude interval of 295–470 km by means of the direct simulation Monte Carlo codes: DS2V for the solution of two-dimensional/axisymmetric flowfields, and DS3V for the solution of three-dimensional flowfields. The Titan atmosphere is a mixture of nitrogen, methane, and argon. The chemical model is made of 221 reactions, making gas around the capsule a mixture of 18 species. Chemistry strongly influences local aerodynamic quantities, both in the flowfield and on the capsule surface; whereas the chemical effects on the global aerodynamic force are negligible. Our computations also verified the lack of ionization.
An essential part of cloud computing, IoT, and in general the broad field of digital systems, is constituted by the mechanisms which provide access to a number of services or applications. Biometric techniques aim to manage the access to such systems based on personal data; however, some biometric traits are openly exposed in the daily life, and in consequence, they are not secret, e.g., voice or face in social networks. In many cases, biometric data are non-cancelable and non-renewable when compromised. This document examines the vulnerabilities and proposes hardware and software countermeasures for the protection and confidentiality of biometric information using randomly created supplementary information. Consequently, a taxonomy is proposed according to the operating principle and the type of supplementary information supported by protection techniques, analyzing the security, privacy, revocability, renewability, computational complexity, and distribution of biometric information. The proposed taxonomy has five categories: (1) biometric cryptosystems, (2) cancelable biometrics, (3) protection schemes based on machine learning or deep learning, (4) hybrid protection schemes, and (5) multibiometric protection schemes. Furthermore, this document proposes quantitative evaluation measures to compare the performance of protection techniques. Likewise, this research highlights the advantages of injective and linear mapping for the protection of authentication and identification systems, allowing the non-retraining of these systems when the protected biometric information is canceled and renewed. Finally, this work mentions commercial products for cancelable biometric systems and proposes future directions for adaptive and cancelable biometric systems in low-cost IoT devices.
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