Understanding European cross-border cooperation: a framework for analysis

European integration has had a dual impact on border regions. On the one hand, borders were physically dismantled across most of the EU’s internal territory. On the other hand, they have become a fertile ground for territorial co-operation and institutional innovation. The degree of cross-border co-operation and organization achieved varies considerably from one region to another depending on a combination of various facilitating factors for effective cross-border co-operation, more specifically, economic, political leadership, cultural/identity and state formation, and geographical factors. This article offers a conceptual framework to understand the growth and diversity of cross-border regionalism within the EU context by focusing on the levels of and drives for co-operation

Development and tests of a new prototype detector for the XAFS beamline at Elettra Synchrotron in Trieste

The XAFS beamline at Elettra Synchrotron in Trieste combines X-ray absorption spectroscopy and X-ray diffraction to provide chemically specific structural information of materials. It operates in the energy range 2.4-27 keV by using a silicon double reflection Bragg monochromator. The fluorescence measurement is performed in place of the absorption spectroscopy when the sample transparency is too low for transmission measurements or the element to study is too diluted in the sample. We report on the development and on the preliminary tests of a new prototype detector based on Silicon Drift Detectors technology and the SIRIO ultra low noise front-end ASIC. The new system will be able to reduce drastically the time needed to perform fluorescence measurements, while keeping a short dead time and maintaining an adequate energy resolution to perform spectroscopy. The custom-made silicon sensor and the electronics are designed specifically for the beamline requirements.Comment: Proceeding of the 6YRM 12th-14th Oct 2015 - L'Aquila (Italy). Accepted for publication on Journal of Physics: Conference Serie

Modeling Actual Evapotranspiration with MSI-Sentinel Images and Machine Learning Algorithms

The modernization of computational resources and application of artificial intelligence algorithms have led to advancements in studies regarding the evapotranspiration of crops by remote sensing. Therefore, this research proposed the application of machine learning algorithms to estimate the ETrF (Evapotranspiration Fraction) of sugar can crop using the METRIC (Mapping Evapotranspiration at High Resolution with Internalized Calibration) model with data from the Sentinel-2 satellites constellation. In order to achieve this goal, images from the MSI sensor (MultiSpectral Instrument) from the Sentinel-2 and the OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) sensors from the Landsat-8 were acquired nearly at the same time between the years 2018 and 2020 for sugar cane crops. Images from OLI and TIR sensors were intended to calculate ETrF through METRIC (target variable), while for the MSI sensor images, the explanatory variables were extracted in two approaches, using 10 m (approach 1) and 20 m (approach 2) spatial resolution. The results showed that the algorithms were able to identify patterns in the MSI sensor data to predict the ETrF of the METRIC model. For approach 1, the best predictions were XgbLinear (R2 = 0.80; RMSE = 0.15) and XgbTree (R2 = 0.80; RMSE = 0.15). For approach 2, the algorithm that demonstrated superiority was the XgbLinear (R2 = 0.91; RMSE = 0.10), respectively. Thus, it became evident that machine learning algorithms, when applied to the MSI sensor, were able to estimate the ETrF in a simpler way than the one that involves energy balance with the thermal band used in the METRIC model

Towards deterministically controlled InGaAs/GaAs lateral quantum dot molecules

We report on the fabrication, detailed characterization and modeling of lateral InGaAs quantum dot molecules (QDMs) embedded in a GaAs matrix and we discuss strategies to fully control their spatial configuration and electronic properties. The three-dimensional morphology of encapsulated QDMs was revealed by selective wet chemical etching of the GaAs top capping layer and subsequent imaging by atomic force microscopy (AFM). The AFM investigation showed that different overgrowth procedures have a profound consequence on the QDM height and shape. QDMs partially capped and annealed in situ for micro- photoluminescence spectroscopy consist of shallow but well-defined quantum dots (QDs) in contrast to misleading results usually provided by surface morphology measurements when they are buried by a thin GaAs layer. This uncapping approach is crucial for determining the QDM structural parameters, which are required for modeling the system. A single-band effective-mass approximation is employed to calculate the confined electron and heavy-hole energy levels, taking the geometry and structural information extracted from the uncapping experiments as inputs. The calculated transition energy of the single QDM shows good agreement with the experimentally observed values. By decreasing the edge-to-edge distance between the two QDs within a QDM, a splitting of the electron (hole) wavefunction into symmetric and antisymmetric states is observed, indicating the presence of lateral coupling. Site control of such lateral QDMs obtained by growth on a pre-patterned substrate, combined with a technology to fabricate gate structures at well-defined positions with respect to the QDMs, could lead to deterministically controlled devices based on QDMs. © IOP Publishing Ltd and Deutsche Physikalische Gesellschaft

Reorganization energy from charge transport measurements in a monolithically−-integrated molecular device

Intermolecular charge transfer reactions are key processes in physical chemistry. The electron-transfer rates depend on a few system's parameters, such as temperature, electromagnetic field, distance between adsorbates and, especially, the molecular reorganization energy. This microscopic greatness is the energetic cost to rearrange each single$-$molecule and its surrounding environment when a charge is transferred. Reorganization energies are measured by electrochemistry and spectroscopy techniques as well as at the single-molecule limit using atomic force microscopy approaches, but not from temperature$-$dependent charge transport measurements nor in a monolithically$-$integrated molecular device. Nowadays self$-$rolling nanomembrane (rNM) devices, with strain$-$engineered mechanical properties, on$-$a$-$chip monolithic integration, and operable in distinct environments, overcome those challenges. Here, we investigate the charge transfer reactions occurring within a ca. 6 nm thick copper$-$phthalocyanine (CuPc) film employed as electrode-spacer in a monolithically integrated nanocapacitor. Employing the rNM technology allows us to measure the molecules' charge$-$transport dependence on temperature for different electric fields. Thereby, the CuPc reorganization energy is determined as (930 $\pm$ 40) meV, whereas density functional theory (DFT) calculations support our findings with the atomistic picture of the CuPc charge transfer reaction. Our approach presents a consistent route towards electron transfer reaction characterization using current$-$voltage spectroscopy and provides insight into the role of the molecular reorganization energy when it comes to electrochemical nanodevices.Comment: 17 pages, 5 figure

A Cellular Automata Model for Citrus Variagated Chlorosis

A cellular automata model is proposed to analyze the progress of Citrus Variegated Chlorosis epidemics in S\~ao Paulo oranges plantation. In this model epidemiological and environmental features, such as motility of sharpshooter vectors which perform L\'evy flights, hydric and nutritional level of plant stress and seasonal climatic effects, are included. The observed epidemics data were quantitatively reproduced by the proposed model varying the parameters controlling vectors motility, plant stress and initial population of diseased plants.Comment: 10 pages, 10 figures, Scheduled tentatively for the issue of: 01Nov0

First results of a novel Silicon Drift Detector array designed for low energy X-ray fluorescence spectroscopy

We developed a trapezoidal shaped matrix with 8 cells of Silicon Drift Detectors (SDD) featuring a very low leakage current (below 180 pA/cm2 at 20 \ub0C) and a shallow uniformly implanted p+ entrance window that enables sensitivity down to few hundreds of eV. The matrix consists of a completely depleted volume of silicon wafer subdivided into 4 square cells and 4 half-size triangular cells. The energy resolution of a single square cell, readout by the ultra-low noise SIRIO charge sensitive preamplifier, is 158 eV FWHM at 5.9 keV and 0 \ub0C. The total sensitive area of the matrix is 231 mm2 and the wafer thickness is 450\u3bcm. The detector was developed in the frame of the INFN R&D project ReDSoX in collaboration with FBK, Trento. Its trapezoidal shape was chosen in order to optimize the detection geometry for the experimental requirements of low energy X-ray fluorescence (LEXRF) spectroscopy, aiming at achieving a large detection angle. We plan to exploit the complete detector at the TwinMic spectromicroscopy beamline at the Elettra Synchrotron (Trieste, Italy). The complete system, composed of 4 matrices, increases the solid angle coverage of the isotropic photoemission hemisphere about 4 times over the present detector configuration. We report on the layout of the SDD matrix and of the experimental set-up, as well as the spectroscopic performance measured both in the laboratory and at the experimental beamline. \ua9 2015 Elsevier B.V