A cellular automaton for the factor of safety field in landslides modeling

Landslide inventories show that the statistical distribution of the area of recorded events is well described by a power law over a range of decades. To understand these distributions, we consider a cellular automaton to model a time and position dependent factor of safety. The model is able to reproduce the complex structure of landslide distribution, as experimentally reported. In particular, we investigate the role of the rate of change of the system dynamical variables, induced by an external drive, on landslide modeling and its implications on hazard assessment. As the rate is increased, the model has a crossover from a critical regime with power-laws to non power-law behaviors. We suggest that the detection of patterns of correlated domains in monitored regions can be crucial to identify the response of the system to perturbations, i.e., for hazard assessment.Comment: 4 pages, 3 figure

Treatment of end-of-life concrete in an innovative heating-air classification system for circular cement-based products

A stronger commitment towards Green Building and circular economy, in response to environmental concerns and economic trends, is evident in modern industrial cement and concrete production processes. The critical demand for an overall reduction in the environmental impact of the construction sector can be met through the consumption of high-grade supplementary raw materials. Advanced solutions are under development in current research activities that will be capable of up-cycling larger quantities of valuable raw materials from the fine fractions of End-of-Life (EoL) concrete waste. New technology, in particular the Heating-Air classification System (HAS), simultaneously applies a combination of heating and separation processes within a fluidized bed-like chamber under controlled temperatures (±600 °C) and treatment times (25–40 s). In that process, moisture and contaminants are removed from the EoL fine concrete aggregates (0–4 mm), yielding improved fine fractions, and ultrafine recycled concrete particles (<0.125 mm), consisting mainly of hydrated cement, thereby adding value to finer EoL concrete fractions. In this study, two types of ultrafine recycled concrete (either siliceous or limestone EoL concrete waste) are treated in a pilot HAS technology for their conversion into Supplementary Cementitious Material (SCM). The physico-chemical effect of the ultrafine recycled concrete particles and their potential use as SCM in new cement-based products is assessed by employing substitutions of up to 10% of the conventional binder. The environmental viability of their use as SCM is then evaluated in a Life Cycle Assessment (LCA). The results demonstrated accelerated hydration kinetics of the mortars that incorporated these SCMs at early ages and higher mechanical strengths at all curing ages. Optimal substitutions were established at 5%. The results suggested that the overall environmental impact could be reduced by up to 5% when employing the ultrafine recycled concrete particles as SCM in circular cement-based products, reducing greenhouse gas emissions by as much as 41 kg CO2 eq./ton of cement (i.e. 80 million tons CO2 eq./year). Finally, the environmental impacts were reduced even further by running the HAS on biofuel rather than fossil fuel.The authors of the present paper, prepared in the framework ofthe Project VEEP "Cost-Effective Recycling of C&DW in High AddedValue Energy Efficient Prefabricated Concrete Components forMassive Retrofitting of our Built Environment", wish to acknowl-edge the European Commission for its support. This project hasreceived funding from the European Union’s Horizon 2020 researchand innovation programme under grant agreement No 723582.This paper reflects only the author’s view and the European Com-mission is not responsible for any use that may be made of theinformation it contains.The authors are also grateful to the Spanish Ministry of Science,Innovation and Universities (MICIU) and the European RegionalDevelopment Fund (FEDER) for funding this line of research(RTI2018-097074-B-C21)

Remote device access in the new accelerator controls middleware

This paper presents the Remote Device Access (RDA) package developed at CERN in the framework of the joint PS/SL Controls Middleware project. The package design reflects the Accelerator Device Model in which devices, named entities in the control system, can be controlled via properties. RDA implements this model in a distributed environment with devices residing in servers that can run anywhere in the controls network. It provides a location-independent and reliable access to the devices from control programs. By invoking the device access methods, clients can read, write and subscribe to device property values. We describe the architecture and design of RDA its API, and CORBA-based implementations in Java and C++. First applications of RDA in the CERN accelerator control systems are described as well

Therapeutic sequences in patients with grade 1−2 neuroendocrine tumors (NET): an observational multicenter study from the ELIOS group

Purpose: Many different treatments are suggested by guidelines to treat grade 1−2 (G1−G2) neuroendocrine tumors (NET). However, a precise therapeutic algorithm has not yet been established. This study aims at identifying and comparing the main therapeutic sequences in G1−G2 NET. Methods: A retrospective observational Italian multicenter study was designed to collect data on therapeutic sequences in NET. Median progression-free survival (PFS) was compared between therapeutic sequences, as well as the number and grade of side effects and the rate of dose reduction/treatment discontinuation. Results: Among 1182 patients with neuroendocrine neoplasia included in the ELIOS database, 131 G1–G2 gastroenteropancreatic, lung and unknown primary NET, unresectable or persistent/relapsing after surgery, treated with ≥2 systemic treatments, were included. Four main therapeutic sequences were identified in 99 patients: (A) somatostatin analogs (SSA) standard dose to SSA high dose (n = 36), (B) SSA to everolimus (n = 31), (C) SSA to chemotherapy (n = 17), (D) SSA to peptide receptor radionuclide therapy (PRRT) (n = 15). Median PFS of the second-line treatment was not reached in sequence A, 33 months in sequence B, 20 months in sequence C, 30 months in sequence D (p = 0.16). Both total number and severity of side effects were significantly higher in sequences B and C than A and D (p = 0.04), as well as the rate of dose reduction/discontinuation (p = 0.03). Conclusions: SSA followed by SSA high dose, everolimus, chemotherapy or PRRT represent the main therapeutic sequences in G1−G2 NET. Median PFS was not significantly different between sequences. However, the sequences with SSA high dose or PRRT seem to be better tolerated than sequences with everolimus or chemotherapy

Finite driving rate and anisotropy effects in landslide modeling

In order to characterize landslide frequency-size distributions and individuate hazard scenarios and their possible precursors, we investigate a cellular automaton where the effects of a finite driving rate and the anisotropy are taken into account. The model is able to reproduce observed features of landslide events, such as power-law distributions, as experimentally reported. We analyze the key role of the driving rate and show that, as it is increased, a crossover from power-law to non power-law behaviors occurs. Finally, a systematic investigation of the model on varying its anisotropy factors is performed and the full diagram of its dynamical behaviors is presented.Comment: 8 pages, 9 figure

Anti-HBV treatment induces novel reverse transcriptase mutations with reflective effect on HBV S antigen

The identification of novel reverse-transcriptase (RT) drug-resistance mutations is critical in predicting the probability of success to anti-HBV treatment. Furthermore, due to HBV-RT/HBsAg gene-overlap, they can have an impact on HBsAg-detection and quantification

The ACEGES 1.0 Documentation: Simulated Scenarios of Conventional Oil Production

he ACEGES (Agent-based Computational Economics of the Global Energy System) 1.0 model is an agent-based model of conventional oil production for 93 countries. The model accounts for four key uncertainties, namely Estimated Ultimate Recovery (EUR), estimated growth in oil demand, estimated growth in oil production and assumed peak/decline point. This documentation provides an overview of the ACEGES model capabilities and an example of how it can be used for long-term (discrete and continuous) scenarios of conventional oil production

The ACEGES 1.0 Documentation: Simulated Scenarios of Conventional Oil Production

he ACEGES (Agent-based Computational Economics of the Global Energy System) 1.0 model is an agent-based model of conventional oil production for 93 countries. The model accounts for four key uncertainties, namely Estimated Ultimate Recovery (EUR), estimated growth in oil demand, estimated growth in oil production and assumed peak/decline point. This documentation provides an overview of the ACEGES model capabilities and an example of how it can be used for long-term (discrete and continuous) scenarios of conventional oil production