Transductive Learning with String Kernels for Cross-Domain Text Classification

For many text classification tasks, there is a major problem posed by the lack of labeled data in a target domain. Although classifiers for a target domain can be trained on labeled text data from a related source domain, the accuracy of such classifiers is usually lower in the cross-domain setting. Recently, string kernels have obtained state-of-the-art results in various text classification tasks such as native language identification or automatic essay scoring. Moreover, classifiers based on string kernels have been found to be robust to the distribution gap between different domains. In this paper, we formally describe an algorithm composed of two simple yet effective transductive learning approaches to further improve the results of string kernels in cross-domain settings. By adapting string kernels to the test set without using the ground-truth test labels, we report significantly better accuracy rates in cross-domain English polarity classification.Comment: Accepted at ICONIP 2018. arXiv admin note: substantial text overlap with arXiv:1808.0840

Weighted Low-Regularity Solutions of the KP-I Initial Value Problem

In this paper we establish local well-posedness of the KP-I problem, with initial data small in the intersection of the natural energy space with the space of functions which are square integrable when multiplied by the weight y. The result is proved by the contraction mapping principle. A similar (but slightly weaker) result was the main Theorem in the paper " Low regularity solutions for the Kadomstev-Petviashvili I equation " by Colliander, Kenig and Staffilani (GAFA 13 (2003),737-794 and math.AP/0204244). Ionescu found a counterexample (included in the present paper) to the main estimate used in the GAFA paper, which renders incorrect the proof there. The present paper thus provides a correct proof of a strengthened version of the main result in the GAFA paper

Reliability of Strategic Environmental Assessment for Territorial Management: General Criticisms and a Proposed Approach in the Presence of Relevant Accident Risk Facilities

The Strategic Environmental Assessment (SEA) is a procedure with a wide application, that has a very important role in sustainable territorial development. The aim of this work is to make some evaluations after the initial period of application also based on data of a particular complex territory, Lombardy Region (Northern Italy), which is characterized by a very high concentration of population, industrial activities and economic interests. The evaluations reveal some critical aspects that negatively influence the correct application of the SEA in Italy, with consequences on the territorial governance and the determination of expected effects corresponding to specific aims. One of these critical aspects is the need to define specific standards and parameters for carrying out a SEA on the different environmental themes. One of these is the assessment of the anthropic risk, which may initially be approximately identified as the industrial risk during territorial planning and programming. On this matter, we suggest adopting a methodological approach that is found in specific guidelines for anyone that produces the Environmental Report to support the SEA, and for councils that have to produce a Technical Examination Paper of the Relevant Accident Risk, to assess the industrial risk, also when there are companies with a relevant accident risk

Metabolic alterations in experimental models of depression

Introduction: Major depressive disorder is one of the most prevalent psychiatric disorders and is associated with a severe impact on the personal functioning, thus with incurring significant direct and indirect costs. The presence of depression in patients with medical comorbidities increases the risks of myocardial infarction and decreases diabetes control, and adherence to treatment. The mechanism through which these effects are produced is still uncertain. Objectives of this study were to evaluate the metabolic alterations in female Wistar rats with induced depression, with and without administration of Agomelatine. The methods included two experiments. All data were analyzed by comparison with group I (control), and with each other. In the first experiment we induced depression by: exposure to chronic mild stress-group II; olfactory bulbectomy-group III; and exposure to chronic mild stress and hyperlipidic/ hyper caloric diet-group IV. The second experiment was similar with the first but the rats received Agomelatine (0.16mg/ animal): group V (depression induced through exposure to chronic mild stress), VI (depression induced through olfactory bulbectomy) and VII (depression induced through exposure to chronic mild stressing hyperlipidic/ hypercaloric diet). Weight, cholesterol, triglycerides and glycaemia were measured at day 0 and 28, and leptin value was measured at day 28. The results in the 1st experiment revealed significant differences (pconclusion, significant correlations were found between high level of triglycerides and depression induced by chronic stress and olfactory bulbectomy. Agomelatine groups had a lower increase of triglycerides levels

A para-differential renormalization technique for nonlinear dispersive equations

For \alpha \in (1,2) we prove that the initial-value problem \partial_t u+D^\alpha\partial_x u+\partial_x(u^2/2)=0 on \mathbb{R}_x\times\mathbb{R}_t; u(0)=\phi, is globally well-posed in the space of real-valued L^2-functions. We use a frequency dependent renormalization method to control the strong low-high frequency interactions.Comment: 42 pages, no figure