Large-scale risk analysis in the Arno river basin (Italy)

We present the methodologies adopted and the outcomes obtained in the analysis of landslide risk in the basin of the Arno River (Central Italy) in the framework of a project sponsored by the Basin Authority of the Arno River, started in the year 2002 and completed at the beginning of 2005. A new landslide inventory of the whole area was realized, using conventional (aerialphoto interpretation and field surveys) and non-conventional methods (e.g. remote sensing techniques such as DInSAR and PS-InSAR). The great majority of the mapped mass movements are rotational slides (75%), solifluctions and other shallow slow movements (17%) and flows (5%), while soil slips, and other rapid landslides, seem less frequent everywhere within the basin. The assessment of landslide hazard in terms of probability of occurrence in a given time, based for mapped landslides on direct and indirect observations of the state of activity and recurrence time, has been extended to landslide-free areas through the application of statistical methods implemented in an artificial neural network (ANN). Unique conditions units (UCU) were defined by the map overlay of landslide preparatory factors (lithology, land cover, slope gradient, slope curvature and upslope contributing area) and afterwards used to construct a series of model vectors for the training and test of the ANN. Model validation confirms that prediction results are very good, with an average percentage of correctly recognized mass movements of about 85%. The analysis also revealed the existence of a large number of unmapped mass movements, thus contributing to the completeness of the final inventory. Temporal hazard was estimated via the translation of state of activity in recurrence time and hence probability of occurrence. The definition of position, typology and characteristics of the elements at risk has been carried out with two different methodologies, partially derived from the “Plans d’Exposition au Risque” proposed in France: i) buildings and infrastructures were directly extracted from digital terrain cartography at the 1:10,000 scale, whilst ii) nonurban land use was identified and mapped based on an updated and improved CORINE land cover map at the 1:50,000 scale. The definition of the exposure of the elements at risk relies upon contingent valuation methods and form-based interviews. Landslide intensity, usually defined as proportional to kinetic energy, was obtained considering landslide typology as a proxy for expected velocity. In the case of the Arno River Basin the definition of intensity is influenced by the fact that the large majority of mass movements are deep-seated reactivated slides evolving into flows. Two main cases were so considered: deep-seated rotational slides and shallow flows or planar slides with virtually constant depth. In the latter case, intensity as a function of volume was set proportional to the area of the mapped phenomenon. In the former case, a simple geometric model was used to compute the volume. Intersection of hazard values with vulnerability and exposure figures, obtained by reclassification of digital vector mapping at 1:10,000 scale, lead to the definition of risk values for each terrain unit for different periods of time into the future. Numerical results indicate that in absence of mitigation measures, large economic losses must be expected due to landslide activity in the few next years. The final results of the research are now undergoing a process of integration and implementation within land planning and risk prevention policies and practices at local and national level

Characterisation of the porcine eyeball as an in-vitro model for dry eye

Purpose: To characterise the anatomical parameters of the porcine eye for potentially using it as a laboratory model of dry eye. Methods: Anterior chamber depth and angle, corneal curvature, shortest and longest diameter, endothelial cell density, and pachymetry were measured in sixty freshly enucleated porcine eyeballs. Results: Corneal steepest meridian was 7.85 ± 0.32 mm, corneal flattest meridian was 8.28 ± 0.32 mm, shortest corneal diameter was 12.69 ± 0.58 mm, longest corneal diameter was 14.88 ± 0.66 mm and central corneal ultrasonic pachymetry was 1009 ± 1μm. Anterior chamber angle was 28.83 ± 4.16°, anterior chamber depth was 1.77 ± 0.27 mm, and central corneal thickness measured using OCT was 1248 ± 144μm. Corneal endothelial cell density was 3250 ± 172 cells/mm2. Conclusions: Combining different clinical techniques produced a pool of reproducible data on the porcine eye anatomy, which can be used by researchers to assess the viability of using the porcine eye as an in-vitro/ex-vivo model for dry eye. Due to the similar morphology with the human eye, porcine eyeballs may represent a useful and cost effective model to individually study important key factors in the development of dry eye, such as environmental and mechanical stresses

Analisi della suscettibilità da frana a scala di bacino (Bacino del Fiume Arno, Toscana-Umbria, Italia)

In questa nota vengono presentati i metodi applicati e i risultati ottenuti in una recente analisi della pericolosità da frana, condotta sul territorio del Bacino del Fiume Arno nell’ambito di una convenzione tra l’Autorità di Bacino e il Dipartimento di Scienze della Terra dell’Università di Firenze (2002-2005). Tutti i dati acquisiti, confluiti in una banca dati GIS, sono stati sintetizzati in carte tematiche e in una carta inventario delle frane. La sovrapposizione dei fattori predisponenti selezionati (pendenza, litologia, uso del suolo, curvatura di profilo e area drenata) ha permesso di definire le unità elementari per il trattamento statistico (Unità Territoriali Omogenee: UTO). La valutazione della pericolosità è stata estesa alle aree prive di movimenti franosi utilizzando metodi statistici multivariati implementati in Reti Neurali Artificiali. L’area di studio è stata suddivisa in cinque Macroaree morfologicamente e geologicamente omogenee: per ogni Macroarea, i predittori neurali sono stati addestrati su un opportuno sottoinsieme di dati, applicando poi i migliori all’intero data-set al fine di generare valori previsti dell’indice di suscettibilità per ogni UTO. Infine, i valori di uscita sono stati riclassificati in differenti livelli di pericolosità in base a criteri di soglia e validati per confronto con l’inventario. Una percentuale di area in frana compresa tra l’81 e il 96% risulta correttamente classificata dalla previsione nelle varie Macroare

Quartz-enhanced photoacoustic spectroscopy exploiting low-frequency tuning forks as a tool to measure the vibrational relaxation rate in gas species

We demonstrated that quartz-enhanced photoacoustic spectroscopy (QEPAS) is an efficient tool to measure the vibrational relaxation rate of gas species, employing quartz tuning forks (QTFs) as sound detectors. Based on the dependence of the QTF resonance frequency on the resonator geometry, a wide range of acoustic frequencies with narrow detection bandwidth was probed. By measuring the QEPAS signal of the target analyte as well as the resonance properties of different QTFs as a function of the gas pressure, the relaxation time can be retrieved. This approach has been tested in the near infrared range by measuring the CH4 (nν4) vibrational relaxation rate in a mixture of 1% CH4, 0.15 % H2O in N2, and the H2O (ν1) relaxation rate in a mixture of 0.5 % H2O in N2. Relaxation times of 3.2 ms Torr and 0.25 ms Torr were estimated for CH4 and H2O, respectively, in excellent agreement with values reported in literature

Broadband detection of methane and nitrous oxide using a distributed-feedback quantum cascade laser array and quartz-enhanced photoacoustic sensing

Here we report on the broadband detection of nitrous oxide (N2O) and methane (CH4) mixtures in dry nitrogen by using a quartz-enhanced photoacoustic (QEPAS) sensor exploiting an array of 32 distributed-feedback quantum cascade lasers, within a spectral emission range of 1190−1340 cm−1 as the excitation source. Methane detection down to a minimum detection limit of 200 ppb at 10 s lock-in integration time was achieved. The sensor demonstrated a linear response in the range of 200−1000 ppm. Three different mixtures of N2O and CH4 in nitrogen at atmospheric pressure have been analyzed. The capability of the developed QEPAS sensor to selectively determine the N2O and CH4 concentrations was demonstrated, in spite of significant overlap in their respective absorption spectra in the investigated spectral range

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Landslide hazard and risk mapping at catchment scale in the Arno River basin

We present the methodologies adopted and the outcomes obtained in the analysis of landslide risk in the basin of the Arno River (Central Italy) in the framework of a project sponsored by the Basin Authority of the Arno River, started in the year 2002 and completed at the beginning of 2005. In particular, a complete set of methods and applications for the assessment of landslide susceptibility and risk are described and discussed. A new landslide inventory of the whole area was realized, using conventional (aerial-photo interpretation and field surveys) and non-conventional methods (e.g. remote sensing techniques such as DInSAR and PS-InSAR). The great majority of the mapped mass movements are rotational slides (75%), solifluctions and other shallow slow movements (17%) and flows (5%), while soil slips, and other rapid landslides, seem less frequent everywhere within the basin. The relationships between landslide characteristics and environmental factors have been assessed through statistical analysis. As expected, the results show a strong control of land cover, lithology and morphology on landslide occurrence. The landslide frequency-size distribution shows a typical scaling behaviour already underlined in other landslide inventories worldwide. The assessment of landslide hazard in terms of probability of occurrence in a given time, based for mapped landslides on direct and indirect observations of the state of activity and recurrence time, has been extended to landslide-free areas through the application of statistical methods implemented in an artificial neural network (ANN). Unique conditions units (UCU) were defined by the map overlay of landslide preparatory factors (lithology, land cover, slope gradient, slope curvature and upslope contributing area) and afterwards used to construct a series of model vectors for the training and test of the ANN. Various different ANNs were selected throughout the basin, until each UCU was assigned a degree of membership to a susceptibility and a hazard class. Model validation confirms that prediction results are very good, with an average percentage of correctly recognized mass movements of about 85%. The analysis also revealed the existence of a large number of unmapped mass movements, thus contributing to the completeness of the final inventory. Temporal hazard was estimated via the translation of state of activity in recurrence time and hence probability of occurrence. The following intersection of hazard values with vulnerability and exposure figures, obtained by reclassification of digital vector mapping at 1:10,000 scale, lead to the definition of risk values for each terrain unit for different periods of time into the future. The final results of the research are now undergoing a process of integration and implementation within land planning and risk prevention policies and practices at local and national level