CSNL: A cost-sensitive non-linear decision tree algorithm

This article presents a new decision tree learning algorithm called CSNL that induces Cost-Sensitive Non-Linear decision trees. The algorithm is based on the hypothesis that nonlinear decision nodes provide a better basis than axis-parallel decision nodes and utilizes discriminant analysis to construct nonlinear decision trees that take account of costs of misclassification. The performance of the algorithm is evaluated by applying it to seventeen datasets and the results are compared with those obtained by two well known cost-sensitive algorithms, ICET and MetaCost, which generate multiple trees to obtain some of the best results to date. The results show that CSNL performs at least as well, if not better than these algorithms, in more than twelve of the datasets and is considerably faster. The use of bagging with CSNL further enhances its performance showing the significant benefits of using nonlinear decision nodes. The performance of the algorithm is evaluated by applying it to seventeen data sets and the results are compared with those obtained by two well known cost-sensitive algorithms, ICET and MetaCost, which generate multiple trees to obtain some of the best results to date. The results show that CSNL performs at least as well, if not better than these algorithms, in more than twelve of the data sets and is considerably faster. The use of bagging with CSNL further enhances its performance showing the significant benefits of using non-linear decision nodes

Understanding the Dynamics of Ancillary Pelagic Species in the Adriatic Sea

The status of fishery resources in the Mediterranean Sea is critical: most of the fish and shellfish stocks are in overexploitation and only half of them are routinely assessed. This manuscript presents the use of Surplus Production Models (SPMs) as a valid option to increase the number of assessed stocks, with specific attention to the Adriatic basin. Particularly, the stock of European sprat (Sprattus sprattus), Mediterranean horse mackerel (Trachurus mediterraneus), and Atlantic horse mackerel (Trachurus trachurus) living in the Adriatic Sea have been evaluated comparing three SPMs: Catch Maximum Sustainable Yields (CMSY), Stochastic surplus Production model in Continuous Time (SPiCT), and Abundance Maximum Sustainable Yields (AMSY). The different approaches present some variations; however, they generally agree on describing all the stocks close to the reference values for both biomass and fishing mortality in the most recent year. For the European sprat, AMSY results are the most robust model for this species’ survey data allow depicting a clearer picture of the history of this stock. Indeed, for the horse mackerel species, CMSY or SPiCT results are the preferred models, since for these species landings are not negligible. Notwithstanding, age-structured assessments remain the most powerful approach for evaluating the status of resources, but SPMs have proved to be a powerful tool in a data-limited context

Quantification of strain through linear dichroism in the Si 1s edge X-ray absorption spectra of strained Si1-xGex thin films

We have quantitatively measured the angle dependence in the Silicon 1s X-ray absorption spectra of strained Si1-xGex thin films prepared by epitaxial growth on Si(1 0 0) substrates, through surface sensitive total electron yield detection. The linear dichroism difference extracted from these angle dependent X-ray absorption spectra is proportional to the degree of strain, as measured separately by Raman spectroscopy. This quantitative relationship provides a means to measure the compressive strain in Si 1-xGex thin films. This strain-dependent X-ray absorption spectroscopy has the potential to realize a semiconductor strain metrology through high spatial resolution X-ray spectromicroscopy.Peer reviewed: YesNRC publication: Ye

Defining a procedure for integrating multiple oceanographic variables in ensemble models of marine species distribution

Marine species distribution models are largely used in ecology and fishery science to support the management of marine exploited resources. This study was focused on defining a procedure to develop an ensemble model, combining 5 differents modeling approaches. For each approach, we implemented spatial training and test data set to evaluate the best performance of 9 models through a set of indicators. These models include a different combination of covariates, starting with the simplest model (depth, year, and spatiotemporal variables) to the most complex one (including also oceanographic variables and effort). We applied this procedure to develop a robust ensemble of models to describe accurately the distribution in space and time of European hake (Merluccius merluccius) in the Adriatic and Ionian sea

Relative survival scenarios: An application to undersized common sole (Solea solea L.) in a beam trawl fishery in the Mediterranean Sea

Fishery discard survival depends on multiple conditions; caution is essential when survival study outputs are employed to support management decisions. The study presents a stepwise procedure, devised to estimate discard survival, that accounts for the variability characterizing commercial fishing practices. The procedure was applied to the first survival study performed onboard rapido trawlers targeting Solea solea in the Mediterranean Sea. Undersized specimens collected during sorting were assessed for vitality; some were retained for captive observation. The main drivers affecting discard survival at the time of catch sorting (immediate survival) were identified and used to outline four different operational conditions set (scenarios). Immediate survival in each scenario was subsequently modified by applying a hazard coefficient of survival after 5 days of captive observation in relation to each vitality class, thus obtaining relative survival estimates following discarding. Temperature and air exposure duration were found to exert a major effect on survival, with catch weight and seabed type being additional important factors. The relative survival rate showed an aggregate value of 22.9% (10.5-33.4%). Scenario approach can enhance our understanding of the stressors influencing discard survival. The outcomes are discussed to explore the potential applications of the procedure to the identification of mitigation strategies