Robust quantification of the exposure to operational risk: Bringing economic sense to economic capital

Operational risk is commonly analyzed in terms of the distribution of aggregate yearly losses. Risk measures can then be computed as statistics of this distribution that focus on the region of extreme losses. Assuming independence among the operational risk events and between the likelihood that they occur and their magnitude, separate models are made for the frequency and for the severity of the losses. These are then combined to estimate the distribution of aggregate losses. While the detailed form of the frequency distribution does not significantly affect the risk analysis, the choice of model for the severity often has a significant impact on operational risk measures. For heavy-tailed distributions these measures are dominated by extreme losses, whose probability cannot be reliably extrapolated from the available data. With limited empirical evidence, it is difficult to distinguish among alternative models that produce very different values of the risk measures. Furthermore, the estimates obtained can be unstable and overly sensitive to the presence or absence of single extreme events. Setting a bound on the maximum amount that can be lost in a single event reduces the dependence on the distributional assumptions and improves the robustness and stability of the risk measures, while preserving their sensitivity to changes in the risk profile. This bound should be determined by expert assessment on the basis of economic arguments and validated by the regulator, so that it can be used as a control parameter in the risk analysis.     

Acoustic scattering solver based on single level FMM for multi-GPU systems

In this paper, we present a heterogeneous parallel solver of a high frequency single level Fast Multipole Method (FMM) for the Helmholtz equation applied to acoustic scattering. The developed solution uses multiple GPUs to tackle the compute bound steps of the FMM (aggregation, disaggregation, and near interactions) while the CPU handles a memory bound step (translation) using OpenMP. The proposed solver performance is measured on a workstation with two GPUs (NVIDIA GTX 480) and is compared with that of a distributed memory solver run on a cluster of 32 nodes (HP BL465c) with an Infiniband network. Some energy efficiency results are also presented in this work.     

A collaborative platform for cognitive decision making in the Knowledge Society

Two key aspects of the Knowledge Society are the interconnection between the actors involved in the decision making processes and the importance of the human factor, particularly the citizen’s continuous learning and education. This paper presents a new module devoted to knowledge extraction and diffusion that has been incorporated into a previously developed decision making tool concerning the Internet and related with the multicriteria selection of a discrete number of alternatives (PRIOR-Web). Quantitative and qualitative procedures using data and text mining methods have been employed in the extraction of knowledge. Graphical visualisation tools have been incorporated in the diffusion stage of the methodological approach suggested when dealing with decision making in the Knowledge Society. The resulting collaborative platform is being used as the methodological support for the cognitive democracy known as e-cognocracy.     

A Java simulator of Rescorla and Wagner's prediction error model and configural cue extensions

In this paper we present the "R&W Simulator" (version 3.0), a Java simulator of Rescorla and Wagner's prediction error model of learning. It is able to run whole experimental designs, and compute and display the associative values of elemental and compound stimuli simultaneously, as well as use extra configural cues in generating compound values; it also permits change of the US parameters across phases. The simulator produces both numerical and graphical outputs, and includes a functionality to export the results to a data processor spreadsheet. It is user-friendly, and built with a graphical interface designed to allow neuroscience researchers to input the data in their own "language". It is a cross-platform simulator, so it does not require any special equipment, operative system or support program, and does not need installation. The "R&W Simulator" (version 3.0) is available free.     

Scale-effects on mean and standard deviation of the mechanical properties of condensed matter: an energy-based unified approach

The size effects on the mean values of the mechanical properties of condensed matter and on the related variances are analysed by means of a unified approach based on the multiscale character of energy dissipation. In particular, the scaling law for fragmentation energy density is obtained taking into account the self-similarity of fragments. It is based on a generalization of the three classical comminution laws that has been performed to evaluate the energy dissipation, computing volume and surface area of the particles for one- two- and three-dimensional fragmented objects. The result is general and can be applied to different fractal energy dissipation mechanisms, e.g., plasticity. Based on this approach, the scaling laws for mean and standard deviation values of the main mechanical properties of materials can be derived, like Young's and shear elastic moduli, ultimate normal and shear stresses and strains, fracture energy and toughness.     

Proteomics and Extracellular Vesicles as Novel Biomarker Sources in Peritoneal Dialysis in Children

Peritoneal dialysis (PD) represents the dialysis modality of choice for pediatric patients with end-stage kidney disease. Indeed, compared with hemodialysis (HD), it offers many advantages, including more flexibility, reduction of the risk of hospital-acquired infections, preservation of residual kidney function, and a better quality of life. However, despite these positive aspects, PD may be associated with several long-term complications that may impair both patient’s general health and PD adequacy. In this view, chronic inflammation, caused by different factors, has a detrimental impact on the structure and function of the peritoneal membrane, leading to sclerosis and consequent PD failure both in adults and children. Although several studies investigated the complex pathogenic pathways underlying peritoneal membrane alterations, these processes remain still to explore. Understanding these mechanisms may provide novel approaches to improve the clinical outcome of pediatric PD patients through the identification of subjects at high risk of complications and the implementation of personalized interventions. In this review, we discuss the main experimental and clinical experiences exploring the potentiality of the proteomic analysis of peritoneal fluids and extracellular vesicles as a source of novel biomarkers in pediatric peritoneal dialysis.     

Synthesis and Biological Evaluation of Small Molecules as Potential Anticancer Multitarget Agents

Twenty-six triazole-based derivatives were designed for targeting both PD-L1 (programmed death receptor ligand 1) and VEGFR-2 (vascular endothelial growth factor receptor 2). These compounds were synthetized and biologically evaluated as multitarget inhibitors of VEGFR-2, PD-L1 and c-Myc proteins. The antiproliferative activity of these molecules on several tumor cell lines (HT-29, A-549, and MCF-7) and on the non-tumor cell line HEK-293 was determined. The effects on the abovementioned biological targets were evaluated for some selected compounds. Compound 23, bearing a p-chlorophenyl group, showed better results than sorafenib in regard to the downregulation of VEGFR-2 and a similar effect to BMS-8 on both PD-L1 and c-Myc proteins. The antiangiogenic and antivascular activities of chloro derivatives were also established by endothelial microtube formation assay on Matrigel^®.     

Establishing In-House Cutoffs of CSF Alzheimer’s Disease Biomarkers for the AT(N) Stratification of the Alzheimer Center Barcelona Cohort

Background: Clinical diagnosis of Alzheimer’s disease (AD) increasingly incorporates CSF biomarkers. However, due to the intrinsic variability of the immunodetection techniques used to measure these biomarkers, establishing in-house cutoffs defining the positivity/negativity of CSF biomarkers is recommended. However, the cutoffs currently published are usually reported by using cross-sectional datasets, not providing evidence about its intrinsic prognostic value when applied to real-world memory clinic cases. Methods: We quantified CSF Aβ1-42, Aβ1-40, t-Tau, and p181Tau with standard INNOTEST^® ELISA and Lumipulse G^® chemiluminescence enzyme immunoassay (CLEIA) performed on the automated Lumipulse G600II. Determination of cutoffs included patients clinically diagnosed with probable Alzheimer’s disease (AD, n = 37) and subjective cognitive decline subjects (SCD, n = 45), cognitively stable for 3 years and with no evidence of brain amyloidosis in 18F-Florbetaben-labeled positron emission tomography (FBB-PET). To compare both methods, a subset of samples for Aβ1-42 (n = 519), t-Tau (n = 399), p181Tau (n = 77), and Aβ1-40 (n = 44) was analyzed. Kappa agreement of single biomarkers and Aβ1-42/Aβ1-40 was evaluated in an independent group of mild cognitive impairment (MCI) and dementia patients (n = 68). Next, established cutoffs were applied to a large real-world cohort of MCI subjects with follow-up data available (n = 647). Results: Cutoff values of Aβ1-42 and t-Tau were higher for CLEIA than for ELISA and similar for p181Tau. Spearman coefficients ranged between 0.81 for Aβ1-40 and 0.96 for p181TAU. Passing–Bablok analysis showed a systematic and proportional difference for all biomarkers but only systematic for Aβ1-40. Bland–Altman analysis showed an average difference between methods in favor of CLEIA. Kappa agreement for single biomarkers was good but lower for the Aβ1-42/Aβ1-40 ratio. Using the calculated cutoffs, we were able to stratify MCI subjects into four AT(N) categories. Kaplan–Meier analyses of AT(N) categories demonstrated gradual and differential dementia conversion rates (p = 9.815⁻²⁷). Multivariate Cox proportional hazard models corroborated these findings, demonstrating that the proposed AT(N) classifier has prognostic value. AT(N) categories are only modestly influenced by other known factors associated with disease progression. Conclusions: We established CLEIA and ELISA internal cutoffs to discriminate AD patients from amyloid-negative SCD individuals. The results obtained by both methods are not interchangeable but show good agreement. CLEIA is a good and faster alternative to manual ELISA for providing AT(N) classification of our patients. AT(N) categories have an impact on disease progression. AT(N) classifiers increase the certainty of the MCI prognosis, which can be instrumental in managing real-world MCI subjects.     

Postischemic Neuroprotection of Aminoethoxydiphenyl Borate Associates Shortening of Peri-Infarct Depolarizations

Brain stroke is a highly prevalent pathology and a main cause of disability among older adults. If not promptly treated with recanalization therapies, primary and secondary mechanisms of injury contribute to an increase in the lesion, enhancing neurological deficits. Targeting excitotoxicity and oxidative stress are very promising approaches, but only a few compounds have reached the clinic with relatively good positive outcomes. The exploration of novel targets might overcome the lack of clinical translation of previous efficient preclinical neuroprotective treatments. In this study, we examined the neuroprotective properties of 2-aminoethoxydiphenyl borate (2-APB), a molecule that interferes with intracellular calcium dynamics by the antagonization of several channels and receptors. In a permanent model of cerebral ischemia, we showed that 2-APB reduces the extent of the damage and preserves the functionality of the cortical territory, as evaluated by somatosensory evoked potentials (SSEPs). While in this permanent ischemia model, the neuroprotective effect exerted by the antioxidant scavenger cholesteronitrone F2 was associated with a reduction in reactive oxygen species (ROS) and better neuronal survival in the penumbra, 2-APB did not modify the inflammatory response or decrease the content of ROS and was mostly associated with a shortening of peri-infarct depolarizations, which translated into better cerebral blood perfusion in the penumbra. Our study highlights the potential of 2-APB to target spreading depolarization events and their associated inverse hemodynamic changes, which mainly contribute to extension of the area of lesion in cerebrovascular pathologies.