Hyperspectral monitoring of green roof vegetation health state in sub-mediterranean climate: preliminary results

In urban and industrial environments, the constant increase of impermeable surfaces has produced drastic changes in the natural hydrological cycle. Decreasing green areas not only produce negative effects from a hydrological-hydraulic perspective, but also from an energy point of view, modifying the urban microclimate and generating, as shown in the literature, heat islands in our cities. In this context, green infrastructures may represent an environmental compensation action that can be used to re-equilibrate the hydrological and energy balance and reduce the impact of pollutant load on receiving water bodies. To ensure that a green infrastructure will work properly, vegetated areas have to be continuously monitored to verify their health state. This paper presents a ground spectroscopy monitoring survey of a green roof installed at the University of Calabria fulfilled via the acquisition and analysis of hyperspectral data. This study is part of a larger research project financed by European Structural funds aimed at understanding the influence of green roofs on rainwater management and energy consumption for air conditioning in the Mediterranean area. Reflectance values were acquired with a field-portable spectroradiometer that operates in the range of wavelengths 350–2500 nm. The survey was carried out during the time period November 2014–June 2015 and data were acquired weekly. Climatic, thermo-physical, hydrological and hydraulic quantities were acquired as well and related to spectral data. Broadband and narrowband spectral indices, related to chlorophyll content and to chlorophyll–carotenoid ratio, were computed. The two narrowband indices NDVI705 and SIPI turned out to be the most representative indices to detect the plant health status

Temperature Accelerated Monte Carlo (TAMC): a method for sampling the free energy surface of non-analytical collective variables

We introduce a new method to simulate the physics of rare events. The method, an extension of the Temperature Accelerated Molecular Dynamics, comes in use when the collective variables introduced to characterize the rare events are either non-analytical or so complex that computing their derivative is not practical. We illustrate the functioning of the method by studying the homogeneous crystallization in a sample of Lennard-Jones particles. The process is studied by introducing a new collective variable that we call Effective Nucleus Size $\mathcal N$. We have computed the free energy barriers and the size of critical nucleus, which result in agreement with data available in literature. We have also performed simulations in the liquid domain of the phase diagram. We found a free energy curve monotonically growing with the nucleus size, consistent with the liquid domain

Towards Seismic Design of Nonstructural Elements: Italian Code-Compliant Acceleration Floor Response Spectra

Seismic risk reduction of a building system, meant as primary building structure and nonstructural elements (NSEs) as a whole, must rely upon an adequate design of each of these two items. As far as NSEs are concerned, adequate seismic design means understanding of some basic principles and concepts that involve different actors, such as designers, manufacturers, installers, and directors of works. The current Italian Building Code, referred to as NTC18 hereinafter, defines each set of tasks and responsibilities in a sufficiently detailed manner, rendering now evident that achieving the desired performance level stems from a jointed contribution of all actors involved. Bearing in mind that seismic design is nothing else than proportioning properly seismic demand, in terms of acceleration and/or displacement, and the corresponding capacity, this paper gives a synthetic and informative overview on how to evaluate these two parameters. To shed some light on this, the concept of acceleration floor response spectrum (AFRS) is firstly brought in, along with basics of building structure-NSEs interaction, and is then deepened by means of calculation methods. Both the most rigorous method based on nonlinear dynamic simulations and the simplified analytical formulations provided by the NTC18 are briefly discussed and reviewed, trying to make them clearer even to readers with no structural/earthquake engineering background because, as a matter of fact, NSEs are often selected by architects and/or mechanical or electrical engineers. Lastly, a simple case study, representative of a European code-compliant five-storey masonry-infilled reinforced concrete frame building, is presented to examine differences between numerical and analytical AFRS and to quantify accuracy of different NTC18 procedures

Local-spin-density functional for multideterminant density functional theory

Based on exact limits and quantum Monte Carlo simulations, we obtain, at any density and spin polarization, an accurate estimate for the energy of a modified homogeneous electron gas where electrons repel each other only with a long-range coulombic tail. This allows us to construct an analytic local-spin-density exchange-correlation functional appropriate to new, multideterminantal versions of the density functional theory, where quantum chemistry and approximate exchange-correlation functionals are combined to optimally describe both long- and short-range electron correlations.Comment: revised version, ti appear in PR

Results on Proton-Irradiated 3D Pixel Sensors Interconnected to RD53A Readout ASIC

Test beam results obtained with 3D pixel sensors bump-bonded to the RD53A prototype readout ASIC are reported. Sensors from FBK (Italy) and IMB-CNM (Spain) have been tested before and after proton-irradiation to an equivalent fluence of about $1$ $\times$ $10^{16}$ $\text{n}_{\text{eq}}$ cm$^{-2}$ (1 MeV equivalent neutrons). This is the first time that one single collecting electrode fine pitch 3D sensors are irradiated up to such fluence bump-bonded to a fine pitch ASIC. The preliminary analysis of the collected data shows no degradation on the hit detection efficiencies of the tested sensors after high energy proton irradiation, demonstrating the excellent radiation tolerance of the 3D pixel sensors. Thus, they will be excellent candidates for the extreme radiation environment at the innermost layers of the HL-LHC experiments.Comment: Conference Proceedings of VCI2019, 15th Vienna Conference of Instrumentation, February 18-22, 2019, Vienna, Austria. arXiv admin note: text overlap with arXiv:1903.0196

Sarcoptic mange in Felidae: does Sarcoptes scabiei var. felis exist? A first molecular study.

Domestic and wild felids are considered suitable hosts for the parasitic mite Sarcoptes scabiei, and sarcoptic mange is reported in several felid species in the scientific literature. However, the historic classification of Sarcoptes mites into host-specific varieties does not include S. scabiei var. felis. It is unclear whether sarcoptic mange transmission in felids involves canids, other sympatric species, or exclusively felids. This study aimed to characterize the genetic structure of S. scabiei mites from domestic cats (Felis catus) and Eurasian lynx (Lynx lynx carpathicus), comparing them with Sarcoptes mites from sympatric domestic and wild carnivores. Ten Sarcoptes microsatellite markers were used to genotype 81 mites obtained from skin scrapings of 36 carnivores: 4 domestic cats, one dog (Canis lupus familiaris), 4 Eurasian lynx, 23 red foxes (Vulpes vulpes), and 4 grey wolves (Canis lupus lupus) from either Italy, Switzerland or France. Two genetic clusters of S. scabiei with a geographical distribution pattern were detected: mites from cats originating from Central Italy clustered with those from sympatric wolves. In contrast, all the other mites from Switzerland, France and Northern Italy clustered together. These results strengthen the previously advanced hypothesis that genetic variants of S. scabiei have a predominant geographic-related distribution with cryptic transmission patterns. These patterns may rely on the interactions between different hosts living in the same ecological niche rather than a simple infection among hosts belonging to the same taxon, reinforcing the idea that the S. scabiei historic classification into "var" might have little ongoing relevance

A new stroke mimic prediction scale in a stroke center with a high thrombolysis rate

Patients reaching the emergency department (ED) with symptoms of acute ischemic stroke (AIS) may be affected by a stroke mimics (SMs). A prompt clinical diagnosis could avoid unnecessary thrombolysis. We evaluated a new and rapid approach, the Santa Maria Nuova-Stroke Mimic (SMN-SM) scale, to improve a prompt clinical diagnosis. 340 consecutive patients admitted to the ED with suspected AIS were evaluated. The final diagnosis was: AIS in 267 (78,5%) and SMs in 73 (21,5%) patients. Multivariate logistical analysis showed that the following features – lack of facial paralysis, dizziness, migraine, seizure disorders, blood pressure <150, cognitive impairment, and female sex – were significantly more abundant in patients with SMs than in AIS. To each of these features we assigned a numerical score and we performed a receiver operating characteristic analysis. When the score of the scale was above 8 (cut-point), we obtained a specificity of 93% and a sensitivity of 56% for a SM diagnosis. Thus, the SMN-SM scale seems a rather useful tool to improve SMs diagnosis

A Machine-Learning Approach to Target Clinical and Biological Features Associated with Sarcopenia: Findings from Northern and Southern Italian Aging Populations

Epidemiological and public health resonance of sarcopenia in late life requires further research to identify better clinical markers useful for seeking proper care strategies in preventive medicine settings. Using a machine-learning approach, a search for clinical and fluid markers most associated with sarcopenia was carried out across older populations from northern and southern Italy. A dataset of adults >65 years of age (n = 1971) made up of clinical records and fluid markers from either a clinical-based subset from northern Italy (Pavia) and a population-based subset from southern Italy (Apulia) was employed (n = 1312 and n = 659, respectively). Body composition data obtained by dual-energy X-ray absorptiometry (DXA) were used for the diagnosis of sarcopenia, given by the presence of either low muscle mass (i.e., an SMI 2 for males or 2 for females) and of low muscle strength (i.e., an HGS < 27 kg for males or <16 kg for females) or low physical performance (i.e., an SPPB ≤ 8), according to the EWGSOP2 panel guidelines. A machine-learning feature-selection approach, the random forest (RF), was used to identify the most predictive features of sarcopenia in the whole dataset, considering every possible interaction among variables and taking into account nonlinear relationships that classical models could not evaluate. Then, a logistic regression was performed for comparative purposes. Leading variables of association to sarcopenia overlapped in the two population subsets and included SMI, HGS, FFM of legs and arms, and sex. Using parametric and nonparametric whole-sample analysis to investigate the clinical variables and biological markers most associated with sarcopenia, we found that albumin, CRP, folate, and age ranked high according to RF selection, while sex, folate, and vitamin D were the most relevant according to logistics. Albumin, CRP, vitamin D, and serum folate should not be neglected in screening for sarcopenia in the aging population. Better preventive medicine settings in geriatrics are urgently needed to lessen the impact of sarcopenia on the general health, quality of life, and medical care delivery of the aging population