Open-addressing hashing with unequal-probability keys

This paper describes the use of a drone in collecting data for mapping discontinuities within a marble quarry. A topographic survey was carried out in order to guarantee high spatial accuracy in the exterior orientation of images. Photos were taken close to the slopes and at different angles, depending on the orientation of the quarry walls. This approach was used to overcome the problem of shadow areas and to obtain detailed information on any feature desired. Dense three-dimensional (3D) point clouds obtained through image processing were used to rebuild the quarry geometry. Discontinuities were then mapped deterministically in detail. Joint attitude interpretation was not always possible due to the regular shape of the cut walls; for every discontinuity set we therefore also mapped the uncertainty. This, together with additional fracture characteristics, was used to build 3D discrete fracture network models. Preliminary results reveal the advantage of modern photogrammetric systems in producing detailed orthophotos; the latter allow accurate mapping in areas difficult to access (one of the main limitations of traditional techniques). The results highlight the benefits of integrating photogrammetric data with those collected through classical methods: the resulting knowledge of the site is crucially important in instability analyses involving numerical modelling.Part of the present study was undertaken within the framework of the Italian National Research Project PRIN2009, funded by the Ministry of Education, Universities and Research, which involves the collaboration between the University of Siena, ‘La Sapienza’ University of Rome, and USL1 of Massa and Carrara (Mining Engineering Operative Unit – Department of Prevention). The authors acknowledge M. Pellegri and D. Gullì (USL1, Mining Engineering Operative Unit – Department of Prevention), M. Ferrari, M. Profeti and V. Carnicelli (Cooperativa Cavatori Lorano), X. Chaoshui and P.A. Dowd (School of Civil, Environmental and Mining Engineering, University of Adelaide, South Australia) and M. Bocci (Geographike) for their support of this research

3D change detection analysis of a coastal landslide performed by multi-temporal point clouds comparison

The structure from motion (SfM) photogrammetric technique (FONSTAD et al., 2013) has become a suitable method to obtain high resolution topography data in a wide range of geomorphic environments (PASSALACQUA et al., 2015). SfM is designed to reconstruct the three-dimensional geometry of buildings and objects from randomly acquired images, and represents a low cost option respect to traditional photogrammetric and lidar techniques (FONSTAD et al., 2013). In this way, also the 3D geometry of complex natural surfaces can be achieved with a horizontal and vertical accuracy which depend on the choice of sensor for images acquisition, platform (e.g., UAV, boat, vehicle), and method of assignment of geodetic coordinates to the digital data. In advanced geomorphic applications, repeated photogrammetric surveys at different times allow to detect topographic changes in order to map or monitor erosion, deposition and develop sediment budgets. In this work we present a 3D change detection analysis related to a coastal landslide occurred on 27th October 2013 along the coastal sector of the Campi Flegrei volcanic district, Southern Italy (ESPOSITO et al., 2015). A total of four photogrammetric surveys have been carried out in about two years (Fig. 1), by using a UAV platform for one survey and boats for the other three. In order to accurately define the exterior orientation of images, a topographic survey was also carried out, measuring a series of natural and artificial ground control points external to the landslide area with a long-range Total Station. Images were processed using Agisoft PhotoScan® (http://www.agisoft.com), and 3D point clouds were compared through the "Multiscale Model to Model Cloud Comparison (M3C2)" plugin (LAGUE et al., 2013) included in CloudCompare open source software (http://www.danielgm.net/cc/). The plugin allowed us to estimate orthogonal distances between multitemporal point clouds as well as uncertainty related to each distance measurement. SfM processing of each survey resulted in dense point clouds and high-resolution orthophotos. An average coregistration error between clouds was estimated as 11 cm. As output of the M3C2 distance computation we obtained three new clouds in which each point was characterized by distance and uncertainty attributes (Fig. 2). Points corresponding to statistically significant changes were exported and interpolated in ESRI ArcGis® for volume calculation. Volumetric data show that the landslide deposit at cliff toe was progressively eroded by the sea, while landslide scar was affected by a moderate erosion in the first three months after the 2013 landslide event, as well as by a deep erosion between the second and third surveys. Nevertheless, a negligible eroded volume between 2015 and 2016 surveys was estimated in this area. Deposited sediments decreased through time in the whole landslide area so that, generally, a geomorphic evolution moving towards an equilibrium condition seems to be taking place. The study here described highlights a high potentiality of the SfM and cloud-to-cloud distance computation techniques in geomorphology, both for accurate qualitative and quantitative analysis and for hazard and risk assessment. The studied landslide threats indeed a series of residential buildings located close to the retreating cliff edge

Post-translational deregulation of YAP1 is genetically controlled in rat liver cancer and determines the fate and stem-like behavior of the human disease

Previous studies showed that YAP1 is over-expressed in hepatocellular carcinoma (HCC). Here we observed higher expression of Yap1/Ctgf axis in dysplastic nodules and HCC chemically-induced in F344 rats, genetically susceptible to hepatocarcinogenesis, than in lesions induced in resistant BN rats. In BN rats, highest increase in Yap1-tyr357, p73 phosphorylation and Caspase 3 cleavage occurred. In human HCCs with poorer prognosis ( 3 years survival; HCCB). In the latter, higher levels of phosphorylated YAP1-ser127, YAP1-tyr357 and p73, YAP1 ubiquitination, and Caspase 3 cleavage occurred. Expression of stemness markers NANOG, OCT-3/4, and CD133 were highest in HCCP and correlated with YAP1 and YAP1-TEAD levels. In HepG2, Huh7, and Hep3B cells, forced YAP1 over-expression led to stem cell markers expression and increased cell viability, whereas inhibition of YAP1 expression by specific siRNA, or transfection of mutant YAP1 which does not bind to TEAD, induced opposite alterations. These changes were associated, in Huh7 cells transfected with YAP1 or YAP1 siRNA, with stimulation or inhibition of cell migration and invasivity, respectively. Furthermore, transcriptome analysis showed that YAP1 transfection in Huh7 cells induces over-expression of genes involved in tumor stemness. In conclusion, Yap1 post-translational modifications favoring its ubiquitination and apoptosis characterize HCC with better prognosis, whereas conditions favoring the formation of YAP1-TEAD complexes are associated with aggressiveness and acquisition of stemness features by HCC cells

To what extent is climate change adaptation a novel challenge for agricultural modellers?

Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change

aberrant inos signaling is under genetic control in rodent liver cancer and potentially prognostic for the human disease

Mounting evidence underlines the role of inducible nitric oxidesynthase (iNOS) in hepatocellular carcinoma (HCC) develop-ment, but its functional interactions with pathways involved inHCC progression remain uninvestigated. Here, we analyzed inpreneoplastic and neoplastic livers from Fisher 344 and BrownNorway rats, possessing different genetic predisposition to HCC,in transforming growth factor-a (TGF-a) and c-Myc–TGF-atransgenic mice, characterized by different susceptibility toHCC, and in human HCC: (i) iNOS function and interactionswith nuclear factor-kB (NF-kB) and Ha-RAS/extracellularsignal-regulated kinase (ERK) during hepatocarcinogenesis;(ii) influence of genetic predisposition to liver cancer on thesepathways and role of these cascades in determining a susceptibleor resistant phenotype and (iii) iNOS prognostic value in humanHCC. We found progressive iNos induction in rat and mouse liverlesions, always at higher levels in the most aggressive models rep-resented by HCC of rats genetically susceptible to hepatocarcino-genesis and c-Myc–TGF-a transgenic mice. iNOS, inhibitor of kBkinase/NF-kB and RAS/ERK upregulation was significantly higherin HCC with poorer prognosis (as defined by patients' survivallength) and positively correlated with tumor proliferation, genomicinstability and microvascularization and negatively with apoptosis.Suppression of iNOS signaling by aminoguanidine led to decreasedHCC growth and NF-kB and RAS/ERK expression and increasedapoptosis both in vivo and in vitro. Conversely, block of NF-kBsignaling by sulfasalazine or short interfering RNA (siRNA) orERK signaling by UO126 caused iNOS downregulation in HCCcell lines. These findings indicate that iNOS cross talk with NF-kB and Ha-RAS/ERK cascades influences HCC growth and prog-nosis, suggesting that key component of iNOS signaling could rep-resent important therapeutic targets for human HCC.IntroductionHepatocellular carcinoma (HCC) is one of the most frequent anddeadliest human cancers worldwide. Current therapies do not improvesignificantly the prognosis of patients with unresectable HCC (1,2).This emphasizes the need to investigate the molecular mechanismsresponsible for HCC development to identify new targets for earlydiagnosis, chemoprevention and treatment.Numerous genes regulating susceptibility to HCC and controllinggrowth, progression and redifferentiation of preneoplastic and neo-plastic lesions have been mapped in rodents (3). Decrease in growthability and/or marked redifferentiation of preneoplastic lesion char-acterizes rodent strains resistant to hepatocarcinogenesis (3,4). Con-sequently, studies on the mechanisms underlying the acquisition ofa phenotype susceptible/resistantto hepatocarcinogenesis in rodentstrains, carrying preneoplastic lesions differently prone to progressto HCC, may lead to the discovery of prognostic markers and ther-apeutic targets for the human disease. Dysplastic nodules and HCCinduced in susceptible Fisher 344 (F344) rats show upregulation ofc-Myc, Cyclin D1, E and A and E2f1 genes, increased cyclinD1–Cdk4, cyclin E–Cdk2 and E2f1–Dp1 complexes and retinoblas-toma protein (pRb) hyperphosphorylation (4–6). These changes areabsent or less pronounced in liver lesions from resistant Brown Norway(BN) rats, where a block of

Sensitivity of simulated soil water content, evapotranspiration, gross primary production and biomass to climate change factors in Euro-Mediterranean grasslands

Grassland models often yield more uncertain outputs than arable crop models due to more complex interactions and the largely undocumented sensitivity of grassland models to environmental factors. The aim of the present study was to assess the impact of single-factor changes in temperature, precipitation, and atmospheric [CO2] on simulated soil water content (SWC), actual evapotranspiration (ET), gross primary production (GPP) and yield biomass, and also to link the sensitivity analysis with experimental results. We employed an unprecedented multi-model framework consisting of seven grassland models at nine sites with different environmental characteristics in Europe and Israel, with two management options at three sites. For warming/cooling and wetting/drying, models showed general consistency in the direction of SWC and ET changes, but less agreement regarding GPP and biomass changes. The simulated responses consistently revealed an overall positive effect of CO2 enrichment on GPP and biomass, while the direction of change differed for SWC and ET. Comparing with single-factor experimental manipulations, SWC simulations slightly underestimated the observed effect of warming, while the overall mean model sensitivity for biomass (+7.5%) closely matched the mean response observed with 1–2 °C warming (+6.6%). The models exhibited lower sensitivity of SWC to wetting or drying compared to the experiments. The overall mean sensitivity of biomass to drying was -4.3%, contrasting with the mean experimental effect size of -9.6%, which proved to be more realistic than the mean wetting effect (+3.2%, against +38.9% in the field trials). The simulated sensitivity of SWC to CO2 enrichment was markedly underestimated, while the biomass response (+12.0%) closely matched the observations (+17.5%). Although the multi-model averaging did not manifestly improve the realism of the simulations, it ensured a realistic response in the direction of change to varying conditions. The results suggest a paradigm shift in grassland modelling meaning that the usual practice of model optimisation/validation needs to be complemented by a sensitivity analysis following the approach presented. The results also highlight the importance of model improvements, especially in terms of soil hydrology representation, a key environmental driver of grassland functioning

Testing an expanded set of sustainable forest management indicators in Mediterranean coppice area

Although coppice forests represent a significant part of the European forest area, especially across southern Countries, they received little attention within the Sustainable Forest Management (SFM) processes and scenarios, whose guidelines have been mainly designed to high forests and national scale. In order to obtain “tailored” information on the degree of sustainability of coppices on the scale of the stand, we evaluated (i) whether the main coppice management options result in different responses of the SFM indicators, and (ii) the degree to which the considered SFM indicators were appropriate in their application at stand level. The study considered three different management options (Traditional Coppice TC, coppice under Natural Evolution NE, and coppice under Conversion to high forest by means of periodical thinning CO). In each of the 43 plots considered in the study, which covered three different European Forest Types, we applied a set of eighteen “consolidated” SFM indicators, covering all the six SFM Criteria (FOREST EUROPE, 2020) and, additionally, tested other sixteen novel indicators shaped for agamic forests and/or applicable at stand level. Results confirmed that several consolidated indicators related to resources status (Growing stock and Carbon stock), health (Defoliation and Forest damage), and socio-economic functions (Net revenue, Energy and Accessibility) were highly appropriate for evaluating the sustainability of coppice at stand level. In addition, some novel indicators related to resources status (Total above ground tree biomass), health (Stand growth) and protective functions (Overstorey cover and Understorey cover) proved to be highly appropriate and able to support the information obtained by the consolidated ones. As a consequence, a subset of consolidated SFM indicators, complemented with the most appropriate novel ones, may represent a valid option to support the evaluation of coppice sustainability at stand level. An integrated analysis of the SFM indicators showed that NE and CO display significant higher environmental performances as compared with TC. In addition, CO has positive effects also on socio-economic issues, while TC -which is an important cultural heritage and a silvicultural option that may help to keep local communities engaged in forestry – combines high wood harvesting rates with dense understory cover. Overall, each of the three management options showed specific sustainability values; as a consequence, their coexistence at a local scale and in accordance with the specific environmental conditions and the social-economic context, is greatly recommended since it may fulfill a wider array of sustainability issues

Testing an expanded set of sustainable forest management indicators in Mediterranean coppice area

Although coppice forests represent a significant part of the European forest area, especially across southern Countries, they received little attention within the Sustainable Forest Management (SFM) processes and scenarios, whose guidelines have been mainly designed to high forests and national scale. In order to obtain “tailored” information on the degree of sustainability of coppices on the scale of the stand, we evaluated (i) whether the main coppice management options result in different responses of the SFM indicators, and (ii) the degree to which the considered SFM indicators were appropriate in their application at stand level. The study considered three different management options (Traditional Coppice TC, coppice under Natural Evolution NE, and coppice under Conversion to high forest by means of periodical thinning CO). In each of the 43 plots considered in the study, which covered three different European Forest Types, we applied a set of eighteen “consolidated” SFM indicators, covering all the six SFM Criteria (FOREST EUROPE, 2020) and, additionally, tested other sixteen novel indicators shaped for agamic forests and/or applicable at stand level. Results confirmed that several consolidated indicators related to resources status (Growing stock and Carbon stock), health (Defoliation and Forest damage), and socio-economic functions (Net revenue, Energy and Accessibility) were highly appropriate for evaluating the sustainability of coppice at stand level. In addition, some novel indicators related to resources status (Total above ground tree biomass), health (Stand growth) and protective functions (Overstorey cover and Understorey cover) proved to be highly appropriate and able to support the information obtained by the consolidated ones. As a consequence, a subset of consolidated SFM indicators, complemented with the most appropriate novel ones, may represent a valid option to support the evaluation of coppice sustainability at stand level. An integrated analysis of the SFM indicators showed that NE and CO display significant higher environmental performances as compared with TC. In addition, CO has positive effects also on socio-economic issues, while TC -which is an important cultural heritage and a silvicultural option that may help to keep local communities engaged in forestry – combines high wood harvesting rates with dense understory cover. Overall, each of the three management options showed specific sustainability values; as a consequence, their coexistence at a local scale and in accordance with the specific environmental conditions and the social-economic context, is greatly recommended since it may fulfill a wider array of sustainability issue

MAGGnet: an international network to foster mitigation of agricultural greenhouse gases.

Research networks provide a framework for review, synthesis and systematic testing of theories by multiple scientists across international borders critical for addressing global-scale issues. In 2012, a GHG research network referred to as MAGGnet (Managing Agricultural Greenhouse Gases Network) was established within the Croplands Research Group of the Global Research Alliance on Agricultural Greenhouse Gases (GRA). With involvement from 46 alliance member countries, MAGGnet seeks to provide a platform for the inventory and analysis of agricultural GHG mitigation research throughout the world. To date, metadata from 315 experimental studies in 20 countries have been compiled using a standardized spreadsheet. Most studies were completed (74%) and conducted within a 1-3-year duration (68%). Soil carbon and nitrous oxide emissions were measured in over 80% of the studies. Among plant variables, grain yield was assessed across studies most frequently (56%), followed by stover (35%) and root (9%) biomass. MAGGnet has contributed to modeling efforts and has spurred other research groups in the GRA to collect experimental site metadata using an adapted spreadsheet. With continued growth and investment, MAGGnet will leverage limited-resource investments by any one country to produce an inclusive, globally shared meta-database focused on the science of GHG mitigation