Physics-Based Mixed-Mode Reverse Recovery Modeling And Optimization Of Si PiN And MPS Fast Recovery Diodes

The paper presents the results of the application of physics-based mixed-mode simulations to the analysis and optimization of the reverse recovery for Si-based fast recovery diodes (FREDs) using Platinum (Pt) lifetime killing. The trap model parameters are extracted from Deep Level Transient Spectroscopy (DLTS) characterization. The model is validated against experimental characterization carried out on the current International Rectifier (IR) FRED PiN technology. Improved designs, using emitter control efficiency and merged PiN-Schottky structures, are analyzed. Comparison between simulated and measured results are presente

Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images.

Assessing the degree of disease severity in biomedical images is a task similar to standard classification but constrained by an underlying structure in the label space. Such a structure reflects the monotonic relationship between different disease grades. In this paper, we propose a straightforward approach to enforce this constraint for the task of predicting Diabetic Retinopathy (DR) severity from eye fundus images based on the well-known notion of Cost-Sensitive classification. We expand standard classification losses with an extra term that acts as a regularizer, imposing greater penalties on predicted grades when they are farther away from the true grade associated to a particular image. Furthermore, we show how to adapt our method to the modelling of label noise in each of the sub-problems associated to DR grading, an approach we refer to as Atomic Sub-Task modeling. This yields models that can implicitly take into account the inherent noise present in DR grade annotations. Our experimental analysis on several public datasets reveals that, when a standard Convolutional Neural Network is trained using this simple strategy, improvements of 3- 5% of quadratic-weighted kappa scores can be achieved at a negligible computational cost. Code to reproduce our results is released at github.com/agaldran/cost_sensitive_loss_classification

Joseph Franz Barwirsch levele Lukács Györgynek

_Background:_ Acute kidney injury (AKI) is a frequently encountered complication of imported Plasmodium falciparum infection. Markers of structural kidney damage have been found to detect AKI earlier than serum creatinine-based prediction models but have not yet been evaluated in imported malaria. This pilot study aims to explore the predictive performance of neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule-1 (KIM-1) for AKI in travellers with imported P. falciparum infection. _Methods:_ Thirty-nine patients with imported falciparum malaria from the Rotterdam Malaria Cohort with available serum and urine samples at presentation were included. Ten of these patients met the criteria for severe malaria. The predictive performance of NGAL and KIM-1 as markers for AKI was compared with that of serum creatinine. _Results:_ Six of the 39 patients (15 %) developed AKI. Serum and urine NGAL and urine KIM-1 were all found to have large areas under the receiver operating characteristics curves (AUROC) for predicting AKI. Urine NGAL was found to have an excellent performance with positive predictive value (PPV) of 1.00 (95 % CI 0.54-1.00), a negative predictive value (NPV) of 1.00 (95 % CI 0.89-1.00) and an AUROC of 1.00 (95 % CI 1.00-1.00). _Conclusion:_ A good diagnostic performance of NGAL and KIM-1 for AKI was found. Particularly, urine NGAL was found to have an excellent predictive performance. Larger studies are needed to demonstrate whether these biomarkers are superior to serum creatinine as predictors for AKI in P. falciparum malaria

Current status and trends of biological invasions in the Lagoon of Venice, a hotspot of marine NIS introductions in the Mediterranean Sea

This paper provides an updated account of the occurrence and abundance of non-indigenous species (NIS) in an area of high risk of introduction: the Lagoon of Venice (Italy). This site is a known hotspot of NIS introductions within the Mediterranean Sea, hosting all the most important vectors of introduction of marine NIS—shipping, recreational boating, shellfish culture and live seafood trade. The recent literature demonstrates that the number of NIS in Venice is continuously changing, because new species are being introduced or identified, and new evidence shows either an exotic origin of species previously believed to be native, or a native origin of formerly believed ‘‘aliens’’, or demonstrates the cryptogenic nature of others. The number of NIS introduced in the Venetian lagoon currently totals 71, out of which 55 are established. This number exceeds those displayed by some nations like Finland, Portugal or Libya. Macroalgae are the taxonomic group with the highest number of introduced species (41 % of NIS): the most likely vector for their introduction is shellfish culture. The source region of NIS introduced to Venice is mainly represented by other Mediterranean or European sites (76 %). The Lagoon of Venice represents a sink but also a source of NIS in the Mediterranean Sea, as it is the site of first record of several NIS, which have since further spread elsewhere.This paper provides an updated account of the occurrence and abundance of non-indigenous species (NIS) in an area of high risk of introduction: the Lagoon of Venice (Italy). This site is a known hotspot of NIS introductions within the Mediterranean Sea, hosting all the most important vectors of introduction of marine NIS-shipping, recreational boating, shellfish culture and live seafood trade. The recent literature demonstrates that the number of NIS in Venice is continuously changing, because new species are being introduced or identified, and new evidence shows either an exotic origin of species previously believed to be native, or a native origin of formerly believed "aliens", or demonstrates the cryptogenic nature of others. The number of NIS introduced in the Venetian lagoon currently totals 71, out of which 55 are established. This number exceeds those displayed by some nations like Finland, Portugal or Libya. Macroalgae are the taxonomic group with the highest number of introduced species (41 % of NIS): the most likely vector for their introduction is shellfish culture. The source region of NIS introduced to Venice is mainly represented by other Mediterranean or European sites (76 %). The Lagoon of Venice represents a sink but also a source of NIS in the Mediterranean Sea, as it is the site of first record of several NIS, which have since further spread elsewhere

Segnalazione di nuove macroalghe per la Laguna di Venezia

The authors report on the occurence in the lagoon of Venice of three Rhodophyta Agardhiella subulata (C. Agardh) Kraft & Wynne, Solieria filiformis (K\ufctzing) Gabrielson e Dipterosiphonia rigens (Schousboe) Falkenberg and one Chlorophyta, Tellamia sp. new for the Lagoon of Venice. A brief description for each species is provided

First report of a species of Prasiola (Chlorophyta: Prasiolaceae) from the Mediterranean Sea (Lagoon of Venice)

A green alga belonging to the genus Prasiola, known from terrestrial, marine and freshwater habitats of polar and cold-temperate regions, is recorded for the first time in the Mediterranean Sea. In 2002, during a survey on soft substrata in the Lagoon of Venice (Italy), specimens referable to this genus were found in several areas. The morphological features of thalli are described and their occurrence in the Lagoon of Venice is discussed. Data on associated algal vegetation are also presented