Critical assessment of protein intrinsic disorder prediction.

Intrinsically disordered proteins, defying the traditional protein structure-function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has Fmax = 0.483 on the full dataset and Fmax = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with Fmax = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude

Accident Scenarios Caused by Lightning Impact on Atmospheric Storage Tanks

In recent years, severe natural events raised the concern for the so-called NaTech (natural-technological) accident scenarios: technological accidents caused by the impact of a natural event on an industrial facility or infrastructure. Severe scenarios typical of the process industry, as fires, explosions, toxic releases, and water pollution were reported as the consequence of natural events in industrial areas. The historical analysis of accidental scenarios triggered by lightning shows that the impact of a lightning on an atmospheric storage tank might be the initiating event of a severe accident. The analysis of past accident evidences that several alternative damage mechanisms and accident scenarios may follow lightning impact. Although lightning hazard is well known and is usually considered in the risk analysis of chemical and process plants, well accepted quantitative procedures to assess the contribution of accidents triggered by lightning to industrial risk are still lacking. In particular, the approaches to the assessment of accident scenarios following lightning strike are mostly based on expert judgment. In the present study, a detailed methodology is presented for the assessment of quantified event trees following lightning impact on an atmospheric tank. Different damage mechanisms have been considered in order to assess the frequencies of loss of containment due to lightning strikes. The results were used in a case study to assess the overall risk due to lightning impact scenarios in typical lay-outs of tank farms of oil refineries.JRC.G.6-Security technology assessmen

Cascading events triggering industrial accidents: quantitative assessment of NaTech and domino scenarios

The so called cascading events, which lead to high-impact low-frequency scenarios are rising concern worldwide. A chain of events result in a major industrial accident with dreadful (and often unpredicted) consequences. Cascading events can be the result of the realization of an external threat, like a terrorist attack a natural disaster or of “domino effect”. During domino events the escalation of a primary accident is driven by the propagation of the primary event to nearby units, causing an overall increment of the accident severity and an increment of the risk associated to an industrial installation. Also natural disasters, like intense flooding, hurricanes, earthquake and lightning are found capable to enhance the risk of an industrial area, triggering loss of containment of hazardous materials and in major accidents. The scientific community usually refers to those accidents as “NaTechs”: natural events triggering industrial accidents. In this document, a state of the art of available approaches to the modelling, assessment, prevention and management of domino and NaTech events is described. On the other hand, the relevant work carried out during past studies still needs to be consolidated and completed, in order to be applicable in a real industrial framework. New methodologies, developed during my research activity, aimed at the quantitative assessment of domino and NaTech accidents are presented. The tools and methods provided within this very study had the aim to assist the progress toward a consolidated and universal methodology for the assessment and prevention of cascading events, contributing to enhance safety and sustainability of the chemical and process industry

MobiDB-lite 3.0: fast consensus annotation of intrinsic disorder flavors in proteins

Abstract Motivation The earlier version of MobiDB-lite is currently used in large-scale proteome annotation platforms to detect intrinsic disorder. However, new theoretical models allow for the classification of intrinsically disordered regions into subtypes from sequence features associated with specific polymeric properties or compositional bias. Results MobiDB-lite 3.0 maintains its previous speed and performance but also provides a finer classification of disorder by identifying regions with characteristics of polyolyampholytes, positive or negative polyelectrolytes, low-complexity regions or enriched in cysteine, proline or glycine or polar residues. Subregions are abundantly detected in IDRs of the human proteome. The new version of MobiDB-lite represents a new step for the proteome level analysis of protein disorder. Availability and implementation Both the MobiDB-lite 3.0 source code and a docker container are available from the GitHub repository: https://github.com/BioComputingUP/MobiDB-lit

NaTech scenarios caused by flooding: Evaluation of accident frequency by the use of fragility models

Natural events impacting on process plants may lead to severe technological accidents. These events are usually defined as NaTech events (Natural Hazard Triggering Technological Disasters). In order to derive the frequencies of accident scenarios associated to NaTech events for QRA (Quantitative Risk Assessment) implementation, a critical issue is the availability of equipment vulnerability models. The aim of the present study was to present a vulnerability model for the assessment of failure probability of atmospheric vessels involved in flooding events. The vulnerability model was based both on the severity of the natural event and on the construction features of the equipment. In order to explore the model features and its potentialities, the application to case-studies was carried out analysing an actual industrial layout. The results obtained confirmed that NaTech scenarios caused by floods may have an important influence on risk assessment and management of industrial facilities

Accident scenarios caused by lightning impact on atmospheric storage tanks

In recent years, severe natural events raised the concern for the so-called NaTech (natural-technological) accident scenarios: Technological accidents caused by the impact of a natural event on an industrial facility or infrastructure. Severe scenarios typical of the process industry, as fires, explosions, toxic releases, and water pollution were reported as the consequence of natural events in industrial areas. The historical analysis of accidental scenarios triggered by lightning shows that the impact of a lightning on an atmospheric storage tank might be the initiating event of a severe accident. The analysis of past accident evidences that several alternative damage mechanisms and accident scenarios may follow lightning impact. Although lightning hazard is well known and is usually considered in the risk analysis of chemical and process plants, well accepted quantitative procedures to assess the contribution of accidents triggered by lightning to industrial risk are still lacking. In particular, the approaches to the assessment of accident scenarios following lightning strike are mostly based on expert judgment. In the present study, a detailed methodology is presented for the assessment of quantified event trees following lightning impact on an atmospheric tank. Different damage mechanisms have been considered in order to assess the frequencies of loss of containment due to lightning strikes. The results were used in a case study to assess the overall risk due to lightning impact scenarios in typical lay-outs of tank farms of oil refineries. Copyright © 2013, AIDIC Servizi S.r.l

Alterazioni dermatologiche del naso del cane: l'ipercheratosi nasale

Le alterazioni dermatologiche del naso del cane in grado di indurre ipercheratosi nasale possono essere numerose. Queste sono riconducibili a infezioni virali, batteriche, protozoarie, funginee, parassitarie, ed a cause immunitarie, genetiche o ereditarie, metaboliche e disturbi della cheratinizzazione

Critical assessment of protein intrinsic disorder prediction.

Intrinsically disordered proteins, defying the traditional protein structure-function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has Fmax = 0.483 on the full dataset and Fmax = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with Fmax = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude