Towards a core ontology for robotics and automation

In this paper, we present the current results of the newly formed IEEE-RAS Working Group, named Ontologies for Robotics and Automation. In particular, we introduce a core ontology that encompasses a set of terms commonly used in Robotics and Automation along with the methodology we have adopted. Our work uses ISO/FDIS 8373 standard developed by the ISO/TC184/SC2 Working Group as a reference. This standard defines, in natural language, some generic terms which are common in Robotics and Automation such as robot, robotic device, etc. Furthermore, we discuss the ontology development process employed along with the problems and decisions taken.     

Managing requirements uncertainty with partial models

Models are good at expressing information that is known but do not typically have support for representing what information a modeler does not know at a particular phase in the software development process. Partial models address this by being able to precisely represent uncertainty about model content. In previous work, we developed a general approach for defining partial models and using them to reason about design models containing uncertainty. In this paper, we show how to apply our approach to managing uncertainty in requirements by providing support for uncertainty capture, elaboration, and change. In particular, we address the problem of specifying uncertainty within a requirements model, refining a model as uncertainty reduces, providing meaning to traceability relations between models containing uncertainty, and propagating uncertainty-reducing changes between related models. We describe the implementation of uncertainty management within the Model Management Tool Framework and illustrate our approach using two examples.     

A New Approach for Representing and Querying Textual Attributes in Databases

In this paper, a new approach to deal with textual attributes in databases is presented. The basic idea is to give a new representation for these attributes, so that it allows us to treat them together with and in the same way than the other database attributes in querying, data warehousing, data mining processes, etc. Additionally, the transformation process of the textual attribute implies the obtaining of a global representation, which includes a great part of the attribute meaning. Moreover, this representation can be improved by using an ontology during the querying process, which enables the semantic queries. The formal representation model is presented in the paper, as well as the mathematical bases for dealing with it. The whole implementation process is also described by using a medical database to show the experimental results. Finally, a set of semantic query examples are offered to explain the advantages of this new approach.     

Informationelle Selbstbestimmung und narrativistische Rezeption

Durch die juristische und die technische Komplexit?t von überwachung und Datenschutz muss das die informationelle Selbstbestimmung herstellende sichere Wissen heute durch Vertrauen ersetzt werden. Allerdings wird dieses Vertrauen nicht objektiv und rational, sondern subjektiv und reduziert-rational gebildet. Dies ist eine folgenreiche Einschr?nkung, da so die Voraussetzungen für gesellschaftlich breites informationelles Vertrauen variiert werden und gegenw?rtig kaum herzustellen sind.     

Learning the mean: A neural network approach

One of the key problems in machine learning theory and practice is setting the correct value of the regularization parameter; this is particularly crucial in Kernel Machines such as Support Vector Machines, Regularized Least Square or Neural Networks with Weight Decay terms. Well known methods such as Leave-One-Out (or GCV) and Evidence Maximization offer a way of predicting the regularization parameter. This work points out the failure of these methods for predicting the regularization parameter when coping with the, apparently trivial and here introduced, regularized mean problem; this is the simplest form of Tikhonov regularization, that, in turn, is the primal form of the learning algorithm Regularized Least Squares. This controlled environment gives the possibility to define oracular notions of regularization and to experiment new methodologies for predicting the regularization parameter that can be extended to the more general regression case. The analysis stems from James–Stein theory, shows the equivalence of shrinking and regularization and is carried using multiple kernels learning for regression and SVD analysis; a mean value estimator is built, first via a rational function and secondly via a balanced neural network architecture suitable for estimating statistical quantities and gaining symmetric expectations. The obtained results show that a non-linear analysis of the sample and a non-linear estimation of the mean obtained by neural networks can be profitably used to improve the accuracy of mean value estimations, especially when a small number of realizations is provided.     

Trajectories of resilience, resistance, and distress during ongoing terrorism: The case of Jews and Arabs in Israel.

This is the 1st longitudinal examination of trajectories of resilience and resistance (rather than ill-being) among a national sample under ongoing threat of mass casualty. The authors interviewed a nationally representative sample of Jews and Arabs in Israel (N = 709) at 2 times during a period of terrorist and rocket attacks (2004?2005). The resistance trajectory, exhibiting few or no symptoms of traumatic stress and depression at both time points, was substantially less common (22.1%) than has previously been documented in studies following single mass casualty events. The resilience trajectory, exhibiting initial symptoms and becoming relatively nonsymptomatic, was evidenced by 13.5% of interviewees. The chronic distress trajectory was documented among a majority of participants (54.0%), and a small proportion of persons were initially relatively symptom-free but became distressed (termed delayed distress trajectory; 10.3%). Less psychosocial resource loss and majority status (Jewish) were the most consistent predictors of resistance and resilience trajectories, followed by greater socioeconomic status, greater support from friends, and less report of posttraumatic growth. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Structure and morphology of solution blended poly(vinylidene fluoride)/montmorillonite nanocomposites

Nanocomposites based on poly(vinylidene fluoride) were prepared with montmorillonite by solution blending. The samples were characterized by small angle X‐ray scattering, wide angle X‐ray diffraction, Fourier transform infrared spectroscopy, and differential scanning calorimetry. Different crystallization conditions, that is, evaporation of the solvent and coprecipitation with two different antisolvents, H₂O or supercritical CO₂ (scCO₂), were tested and their influence on the resulting structure and morphology of the samples were studied. Coprecipitation with scCO₂ induced an ordinate crystalline framework and an intercalated morphology of clay, with a consequent large improvement in modulus. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Microsatellite Instability: From the Implementation of the Detection to a Prognostic and Predictive Role in Cancers

Microsatellite instability (MSI) has been identified in several tumors arising from either germline or somatic aberration. The presence of MSI in cancer predicts the sensitivity to immune checkpoint inhibitors (ICIs), particularly PD1/PD-L1 inhibitors. To date, the predictive role of MSI is currently used in the selection of colorectal cancer patients for immunotherapy; moreover, the expansion of clinical trials into other cancer types may elucidate the predictive value of MSI for non-colorectal tumors. In clinical practice, several assays are used for MSI testing, including immunohistochemistry (IHC), polymerase chain reaction (PCR) and next-generation sequencing (NGS). In this review, we provide an overview of MSI in various cancer types, highlighting its potential predictive/prognostic role and the clinical trials performed. Finally, we focus on the comparison data between the different assays used to detect MSI in clinical practice.     

What Are the Biomarkers for Immunotherapy in SCLC?

Small-cell lung cancer (SCLC) is an aggressive malignancy that exhibits a rapid doubling time, a high growth fraction, and the early development of widespread metastases. The addition of immune checkpoint inhibitors to first-line chemotherapy represents the first significant improvement of systemic therapy in several decades. However, in contrast to its effects on non-SCLC, the advantageous effects of immunotherapy addition are modest in SCLC. In particular, only a small number of SCLC patients benefit from immune checkpoint inhibitors. Additionally, biomarkers selection is lacking for SCLC, with clinical trials largely focusing on unselected populations. Here, we review the data concerning the major biomarkers for immunotherapy, namely, programmed death ligand 1 expression and tumour mutational burden. Furthermore, we explore other potential biomarkers, including the role of the immune microenvironment in SCLC, the role of genetic alterations, and the potential links between neurological paraneoplastic syndromes, serum anti-neuronal nuclear antibodies, and outcomes in SCLC patients treated with immunotherapy.     

Consecutive steps of PET recycling by injection: evaluation of the procedure and of the mechanical properties

The procedure of five consecutive recycling steps by injection moulding of postconsumer PET was evaluated on the basis of processing and drying parameters. The equations that govern the increase in sample mass of the polymer while in contact with the atmosphere were obtained on the basis of weight variation measurements before and after drying. Two series of consecutive recycling steps were also carried out, starting from virgin material (with and without sieving), which showed that, for the sieved material, the decrease in productivity was always in the same order of magnitude as the decrease in viscosity. Thus, the remaining differences, which exceeded 400%, can be attributed to the presence of powder. The crystallinity, transition temperatures, concentration of carboxyl end‐groups, tensile properties, and impact resistance of the samples obtained in each step were determined. The number of carboxyl end groups increased by about three times after the five recycling steps and the crystallinity was enhanced, going from 23% to 37%, which explains the alterations in the modulus of elasticity, elongation at break, and impact resistance. © 2000 John Wiley & Sons, Inc. J Appl Polym Sci 76: 266–275, 2000