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Background: To compare the loss of preload in absence of loading and after a fixed number of cyclic loadings on 7-mm distal cantilever in two different connection systems using all-on-four prosthetic model. Methods: Two equal models of an edentulous mandible rehabilitated with all-on-four technique with two types of abutment system (MUA and OT-Bridge) supporting a hybrid prosthesis, were used. Initial torque values of the prosthetic fixing screw, after ten minutes from initial screw tightening and after 400,000 repeated loadings were registered using a mechanical torque gauge. Differences between initial and final torque values were reported for each anchoring system and the two systems were finally compared. Results: No statistically significant differences regarding the loss of preload between MUA and OT-Bridge system were found after 400,000 cyclic loadings; however, in MUA system it was found between anterior and posterior implant screws. A significant difference in preload loss was found only for MUA system comparing the initial screw torque to that measured after 10 min from the tightening in absence of cyclic loadings. Conclusions: Within the limits of the present study, MUA and OT-Bridge may be considered reliable prosthetic anchoring systems able to tolerate repeated cyclic occlusal loads on distal cantilever in all-on-four rehabilitation model without any significant loss of preload in screw tightening.

Infrastructure development is one of the areas most in need of climate-resilient and friendly investments. The COVID-19 pandemic will increase government spending in this direction. This paper demonstrates how the principles of reflexive governance are key to unlock the full potential of such investments. By establishing an adaptive and redundant institutional capacity in the provision of public services, reflexive governance can enable a successful path towards climate resilience and sustainability.

The presence of the olive tree in Tuscany, Italy, in its forms that have survived to the present day as an essential component of the landscape dates back many centuries. Global change is now threatening it. Therefore, it is important to find markers to enhance the olive tree environment in terms of its resilience. The aim of the research was to investigate the composition of soil bacteriomes in contrasting geochemical environments using a geochemistry approach based on the behavior of the REEs, inherited from parent rock material. Bacteriome assemblages and REE content were analyzed in 48 topsoils developed in six geochemical Tuscan environments. Combined geochemical, geoinformatic, and bioinformatic techniques highlighted the existence of four bacteriome assemblages depending on Light-REEs. Further results showed that the soil bioavailable fraction of REEs was related to parent rock materials, pH, and bacteriome composition. The most abundant bacteria were Microlunatus in graded fluvio-lacustrine soils, Gaiella in graded arenaceous soils, Bradyrizhobium in pyroclastic soils, and Rubrobacter in soils on gentle slopes of calcareous and carbonatic lithologies. This research represents a starting point to define new indicators able to assess the resilience of the olive trees in the Mediterranean landscape and characterize the territory of extra virgin olive oils.

The effects of peat burning on organic‐rich agricultural soils of the Mezzano Lowland (NE Italy) were evaluated on soil profiles variously affected by smoldering. Profiles were investigated for pH, electrical conductivity, bulk density, elemental and isotopic composition of distinct carbon (and nitrogen) fractions. The results suggest that the horizons affected by carbon loss lie at depths 10–70 cm, where the highest temperatures are developed. We suggest that the exothermal oxidation of methane (mediated by biological activity) plays a significant role in the triggering mechanism. In the interested soils we estimated a potential loss of Soil Organic Carbon of approximately 110 kg m−2 within the first meter, corresponding to 580 kg CO2 m−3. The released greenhouse gas is coupled with a loss of soil structure and nutrients. Moreover, the process plausibly triggers mobility of metals bound in organometallic complexes. All these consequences negatively affect the environment, the agricultural activities and possibly also health of the local people. Plain Language Summary Peat soils are formed by accumulation of organic matter and represent a carbon sink. Unfortunately, they are often affected by burning as the organic matter can fuel combustion for a long time, ultimately releasing carbon dioxide and other greenhouse gases, and particulate matter (PM). It is not clear how peat burning ignite and spread. This study investigates the trigger mechanisms and effects of peat burning in the Mezzano Lowland (NE Italy). For this purpose, pH, electrical conductivity, bulk density and carbon elemental and isotopic compositions of Mezzano soil profiles variously affected by peat burning have been investigated. The results suggest that the burning doesn't propagate from surface and that the horizons affected by carbon loss lie at depths 10–70 cm, with temperatures up to 750°C. The process appears spontaneous, probably due to multiple factors such as drying, biological activity and exothermal oxidations. We estimated a loss of soil carbon of approximately 110 kg for square meter, corresponding to a release of 580 kg of CO2 for cubic meter of burnt soil. This carbon loss and the consequent release of gas and PM negatively affect the environment, the agricultural activities and possibly also the health of the local people. Key Points Peat burning in the Mezzano Lowland is a process active since wetland reclamation and variously affects the soil structure and carbon content The main carbon loss occurs in the depth interval 10–70 cm, where temperature up to 750°C is recorded The process induces negative effects to surrounding environment, agriculture activities and possibly also human health

The present inquiry provides a common ground for the analysis of two strands of literature, the environmental Kuznets curve (EKC) and the pollution haven hypothesis (PHH). To this end, the study sets out a simple variational model, which identifies the structural composition of the economy and the level of economic development as the primary determinants of the magnitude of the domestic environmental degradation. The juxtaposition of the mentioned literature strands undermines the optimistic view that economic growth, in the long run, leads to the reduction of atmospheric pollution. To assess the empirical validity of the pollution haven conjecture, the study employs the OECD Environmental Policy Stringency Index and the refined data on carbon emissions embodied in imports for the dataset of 26 OECD countries in the time interval between 1995 and 2011. By employing pooled mean group (PMG) estimators, the study, for the first time, accounts for a number of issues mentioned in the literature as factors that confine the inferential power of existing empirical studies on the EKC. The strong and robust confirmation of the pollution haven conjecture indicates that at least in the context of global common pool resources, a purely national perspective of the EKC is not satisfactory.

Hundreds of millions of people on the planet are affected by malnourishment. This contributes to the vulnerability of large swaths of the population worldwide. Children under five years old and adolescent girls are especially disproportionately vulnerable to diseases and even death in less developed countries. Today, by providing a substantial share of global protein intake, as well as fatty acids and micronutrients, fisheries contribute to global food security. As fish stocks in the upper sea levels are increasingly over-exploited, there is a surge in discussion on the potential contributions of deep-sea fisheries for global food and nutrition security. Some mesopelagic fishes show potential in providing important nutrients. Another way of supplying food security might be in using mesopelagic fish as fish feed. However, fishing in the mesopelagic zone could lead to severe ecological repercussions, especially because the impact on the biological carbon pump is uncertain. This paper highlights and juxtaposes different perspectives regarding exploitation pathways of the fish riches of deep seas, and reviews best practice model projects that deal with uncertainties related to fishery management in the mesopelagic zone. The review concludes that due to the essential role of the mesopelagic zone in the global biological carbon pump and complex interaction patterns between pelagic and mesopelagic species, exploitation of the fish riches of the mesopelagic zone must be based on comprehensive data and rigorous analyses. In the face of the current uncertainty on the respective mechanisms, the authors endorse an international moratorium on deep-sea fisheries and/or the rather small-scale exploitation of mesopelagic biomass.

IntroductionThe COVID-19 pandemic has dramatically affected the Italian health systems and drastically impacted healthcare workers’ daily routine and training. Simulation is an efficient tool to provide medical education, especially in the case of incoming public health emergencies. This study investigated the role and activities of Italian simulation centres (SCs) during the acute phase of the COVID-19 pandemic.MethodsThe population was identified through a web search. The directors of Italian SCs were contacted via email and then enrolled. A structured interview was created, internally validated and administrated by phone to participants.ResultsFollowing the government’s ordinance, 37 (88.37%) SCs had to be closed to the public. Twenty (46.51%) SCs organised in situ simulation while 7 (16.28%) of them organised simulation inside the centre. Twenty-three (53.49%) SCs resorted to telematic modalities to provide training about COVID-19 and 21 (48.84%) of them for other training. Up to date, 13 SCs are still closed to the public.ConclusionsItaly has been severely hit by COVID-19, with differences between the regions. Almost all the SCs were closed, with only a few delivering training. The SCs took advantage of emergent technologies to create new ways to train people safely. Unfortunately, nearly one-fourth of Italian SCs have not reopened yet. The evolution of the COVID-19 epidemic calls for reconsideration about training activities including adequate safety measures implemented for all individuals involved.

In this paper, we explore the cross-national impact of privatization in the network industries on the access to network services. We focus on the assessment of the electricity sector in 20 Latin American countries and analyze the time series between 1985 and 2010. To control for the relevance of the subsidiarity (social commons) argument (Byrne and Mun, 2001; 2003) we assess the interaction between commodification and the role of the sub-national governments in the power sector. Privatization has a statistically significant positive effect on the level of electricity access. In the absence of federalism, privatization in the electricity sector has a greater impact on electrification than in the case with federalist government system. Federalism has a positive impact on the electricity access if electricity is generated and supplied mainly by the state-owned enterprises. Another interesting finding is the relationship between the degree of subsidiarity and electrification: A higher the degree of subsidiarity has a negative effect on the electrification. This could be a result of the increasing transaction costs and rent-seeking behavior in the decentralized settings. The study complements the existing literature by analyzing the privatization reform from the subsidiarity perspective.

The introduction of new generation hyperspectral satellite sensors, combined with advancements in deep learning methodologies, has significantly enhanced the ability to discriminate detailed land-cover classes at medium-large scales. However, a significant challenge in deep learning methods is the risk of overfitting when training networks with small labeled datasets. In this work, we propose a data augmentation technique that leverages a guided diffusion model. To effectively train the model with a limited number of labeled samples and to capture complex patterns in the data, we implement a lightweight transformer network. Additionally, we introduce a modified weighted loss function and an optimized cosine variance scheduler, which facilitate fast and effective training on small datasets. We evaluate the effectiveness of the proposed method on a forest classification task with 10 different forest types using hyperspectral images acquired by the PRISMA satellite. The results demonstrate that the proposed method outperforms other data augmentation techniques in both average and weighted average accuracy. The effectiveness of the method is further highlighted by the stable training behavior of the model, which addresses a common limitation in the practical application of deep generative models for data augmentation.

Bark beetle infestations represent a serious challenge for maintaining the health of coniferous forests. This paper proposes a few-shot learning approach leveraging contrastive learning to detect bark beetle infestations using satellite PRISMA hyperspectral data. The methodology is based on a contrastive learning framework to pre-train a one-dimensional CNN encoder, enabling the extraction of robust feature representations from hyperspectral data. These extracted features are subsequently utilized as input to support vector regression estimators, one for each class, trained on few labeled samples to estimate the proportions of healthy, attacked by bark beetle, and dead trees for each pixel. Experiments on the area of study in the Dolomites show that our method outperforms the use of original PRISMA spectral bands and of Sentinel-2 data. The results indicate that PRISMA hyperspectral data combined with few-shot learning offers significant advantages for forest health monitoring.