2,921 research outputs found

    Advances in EEG-based functional connectivity approaches to the study of the central nervous system in health and disease

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    Functional brain connectivity is closely linked to the complex interactions between brain networks. In the last two decades, measures of functional connectivity based on electroencephalogram (EEG) data have proved to be an important tool for neurologists and clinical and non-clinical neuroscientists. Indeed, EEG-based functional connectivity may reveal the neurophysiological processes and networks underlying human cognition and the pathophysiology of neuropsychiatric disorders. This editorial discusses recent advances and future prospects in the study of EEG-based functional connectivity, with a focus on the main methodological approaches to studying brain networks in health and disease

    Debris-flow susceptibility assessment through cellular automata modeling: an example from 15?16 December 1999 disaster at Cervinara and San Martino Valle Caudina (Campania, southern Italy)

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    International audienceOn 15?16 December 1999, heavy rainfall severely stroke Campania region (southern Italy), triggering numerous debris flows on the slopes of the San Martino Valle Caudina-Cervinara area. Soil slips originated within the weathered volcaniclastic mantle of soil cover overlying the carbonate skeleton of the massif. Debris slides turned into fast flowing mixtures of matrix and large blocks, downslope eroding the soil cover and increasing their original volume. At the base of the slopes, debris flows impacted on the urban areas, causing victims and severe destruction (Vittori et al., 2000). Starting from a recent study on landslide risk conditions in Campania, carried out by the Regional Authority (PAI ?Hydrogeological setting plan, in press), an evaluation of the debris-flow susceptibility has been performed for selected areas of the above mentioned villages. According to that study, such zones would be in fact characterised by the highest risk levels within the administrative boundaries of the same villages ("HR-zones"). Our susceptibility analysis has been performed by applying SCIDDICA S3?hex ? a hexagonal Cellular Automata model (von Neumann, 1966), specifically developed for simulating the spatial evolution of debris flows (Iovine et al., 2002). In order to apply the model to a given study area, detailed topographic data and a map of the erodable soil cover overlying the bedrock of the massif must be provided (as input matrices); moreover, extent and location of landslide source must also be given. Real landslides, selected among those triggered on winter 1999, have first been utilised for calibrating SCIDDICA S3?hex and for defining "optimal" values for parameters. Calibration has been carried out with a GIS tool, by quantitatively comparing simulations with actual cases: optimal values correspond to best simulations. Through geological evaluations, source locations of new phenomena have then been hypothesised within the HR-zones. Initial volume for these new cases has been estimated by considering the actual statistics of the 1999 landslides. Finally, by merging the results of simulations, a deterministic susceptibility zonation of the considered area has been obtained. In this paper, aiming at illustrating the potential for debris-flow hazard analyses of the model SCIDDICA S3?hex, a methodological example of susceptibility zonation of the Vallicelle HR-zone is presented

    Corporate Social Performance and Non-Financial Reporting in the Cruise Industry: Paving the way towards UN Agenda 2030

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    This article investigates the role of accounting disciplines in assessing and fostering corporate social performance (CSP) of business organisations to meet the UN Agenda 2030. Drawing from legitimacy theory, this qualitative study analyses if and how non-financial reporting positively affects and fosters CSP practices and outcomes within the cruise industry. Specifically, using a case study methodology, a major cruise company has been analysed outlining its sustainable behaviour, through the manual content analysis of sustainability reports (2016–2017–2018), in achieving the sustainable development goals (SDGs) introduced by the UN Agenda 2030. The findings outline that the cruise company presents a clear sustainability and community orientation and adopts several initiatives, mostly focused on environmental and social issues, addressed to meet the 17 SDGs, where reputation and positive image have been recognised as the major antecedents in the perspective of CSP. This study contributes to the literature giving a broader and different reading of sustainability reporting as a “booster” of the CSP in meeting the SDGs and a further interesting application of the legitimacy theory, and offers managerial implications to systematise the content of non-financial reporting by improving the quality of disclosure to achieve the SDGs, with focus on CSP processes, outcomes and ways

    Pro-poor land tenure and democratic governance. Discussion paper No. 3.Oslo: Oslo Governance Centre.

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    This discussion paper provides a review of how different forms of land tenure reform relate to decentralization and local governance, in theory and practice. It will guide readers who are familiar with decentralization and local governance approaches to understand the main issues and challenges posed by land tenure reforms to achieve pro-poor impact. Because land tenure reform assigns control over resources that are critical for both identity and livelihood, it will be contentious. It is, therefore, important to distinguish among four different types of land tenure reform and critically assess the political economy context and the type of decentralization as well as national-local governance relationships in which land tenure reform will be implemented. It is equally important to understand the implications of various land tenure reform types for democratic governance and social inclusion / cohesion

    Multistakeholder environmental governance in action: REDD+ discourse coalitions in Tanzania

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    Balancing interests to achieve legitimate and effective policies is a primary and pressing challenge in countries' efforts to prepare their national reducing emissions from deforestation and forest degradation (REDD+) strategies. Using Tanzania as a country case, we investigated the most polarizing policy discourses and assessed the influence of competing discourse coalitions on the drafting of the national REDD+ strategy. We combined discourse and social network analysis to identify discourse coalitions and assess their influence. The findings indicate that the national REDD+ strategy largely reflects the positions of the discourse coalition that is controlled by powerful state actors who support central control of REDD+ financial mechanisms. The competing coalition, led by civil society organizations, has limited influence on the national strategy, despite discursive congruence and concerted political action. The findings further indicate that discursive practices and institutional rules codetermine policy outcomes

    Parallel Genetic Algorithms for calibrating Cellular Automata models: Application to lava flows

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    Cellular Automata are highly nonlinear dynamical systems which are suitable for simulating natural phenomena whose behaviour may be specified in terms of local interactions. The Cellular Automata model SCIARA, developed for the simulation of lava flows, demonstrated to be able to reproduce the behaviour of Etnean events. However, in order to apply the model for the prediction of future scenarios, a thorough calibrating phase is required. This work presents the application of Genetic Algorithms, general-purpose search algorithms inspired to natural selection and genetics, for the parameters optimisation of the modelSCIARA. Difficulties due to the elevated computational time suggested the adoption a Master-Slave Parallel Genetic Algorithm for the calibration of the model with respect to the 2001 Mt. Etna eruption. Results demonstrated the usefulness of the approach, both in terms of computing time and quality of performed simulations

    BCR-ABL1 doubling-times and halving-times may predict CML response to tyrosine kinase inhibitors

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    In Chronic Myeloid Leukemia (CML), successful treatment requires accurate molecular monitoring to evaluate disease response and provide timely interventions for patients failing to achieve the desired outcomes. We wanted to determine whether measuring BCR-ABL1 mRNA doubling-times (DTs) could distinguish inconsequential rises in the oncogene’s expression from resistance to tyrosine kinase inhibitors (TKIs). Thus, we retrospectively examined BCR-ABL1 evolution in 305 chronic-phase CML patients receiving imatinib mesylate (IM) as a first line treatment. Patients were subdivided in two groups: those with a confirmed rise in BCR-ABL1 transcripts without MR3.0 loss and those failing IM. We found that the DTs of the former patients were significantly longer than those of patients developing IM resistance (57.80 vs. 41.45 days, p = 0.0114). Interestingly, the DT values of individuals failing second-generation (2G) TKIs after developing IM resistance were considerably shorter than those observed at the time of IM failure (27.20 vs. 41.45 days; p = 0.0035). We next wanted to establish if decreases in BCR-ABL1 transcripts would identify subjects likely to obtain deep molecular responses. We therefore analyzed the BCR-ABL1 halving-times (HTs) of a different cohort comprising 174 individuals receiving IM in first line and observed that, regardless of the time point selected for our analyses (6, 12, or 18 months), HTs were significantly shorter in subjects achieving superior molecular responses (p = 0.002 at 6 months; p < 0.001 at 12 months; p = 0.0099 at 18 months). Moreover, 50 patients receiving 2G TKIs as first line therapy and obtaining an MR3.0 (after 6 months; p = 0.003) or an MR4.0 (after 12 months; p = 0.019) displayed significantly shorter HTs than individuals lacking these molecular responses. Our findings suggest that BCR-ABL1 DTs and HTs are reliable tools to, respectively, identify subjects in MR3.0 that are failing their assigned TKI or to recognize patients likely to achieve deep molecular responses that should be considered for treatment discontinuation

    Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy

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    Schizophrenia is among the most debilitating neuropsychiatric disorders. However, clear neurophysiological markers that would identify at-risk individuals represent still an unknown. The aim of this study was to investigate possible alterations in the resting alpha oscillatory activity in normal population high on schizotypy trait, a physiological condition known to be severely altered in patients with schizophrenia. Direct comparison of resting-state EEG oscillatory activity between Low and High Schizotypy Group (LSG and HSG) has revealed a clear right hemisphere alteration in alpha activity of the HSG. Specifically, HSG shows a significant slowing down of right hemisphere posterior alpha frequency and an altered distribution of its amplitude, with a tendency towards a reduction in the right hemisphere in comparison to LSG. Furthermore, altered and reduced connectivity in the right fronto-parietal network within the alpha range was found in the HSG. Crucially, a trained pattern classifier based on these indices of alpha activity was able to successfully differentiate HSG from LSG on tested participants further confirming the specific importance of right hemispheric alpha activity and intrahemispheric functional connectivity. By combining alpha activity and connectivity measures with a machine learning predictive model optimized in a nested stratified cross-validation loop, current research offers a promising clinical tool able to identify individuals at-risk of developing psychosis (i.e., high schizotypy individuals)

    The Catania 1669 lava eruptive crisis: simulation of a new possible eruption

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    SCIARA (Smart Cellular Interactive Automata for modeling the Rheology of Aetnean lava flows, to be read as “shea’rah”), our first two-dimensional Cellular Automata model for the simulation of lava flows, was tested and validated with success on several lava events like the 1986/87 Etnean eruption and the last phase of the 1991/93 Etnean one. Real and simulated events are satisfying within limits to forecast the surface covered by the lava flow. Moreover, improved versions have been adopted in testing other real lava flows of Mount Etna and of Reunion Island (Indian Ocean). The model has been applied with success in the determination of risk zones in the inhabited areas of Nicolosi, Pedara, S. Alfio and Zafferana (Sicily). The main goal of the present work has been the verification of the effects, in volcanic risk terms, in the Etnean area from Nicolosi to Catania, of a eruptive crisis similar to the event that occurred in 1669, as if the episode would happen nowadays. Catania has been severely interested in some major Etnean events in history, the most famous one being, namely, the 1669 eruption, involving 1 km3 of lava during 130 days. The simulation of lava tubes and the usage of different histories within the experiments have been crucial in the determination of a new risk area for Catania. In fact, simulations carried out without the introduction of lava tubes, never involved the city, proving the fact that lava tubes, played a fundamental role in the 1669 Catania lava crisis
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