The Maritime Boundaries of Venezuela

Venezuela has maritime boundaries with the following neighbors: two adjacent coastal states, Colombia and Guyana, and six opposite coastal states Trinidad-Tobago, Grenada, San Vincent and the Grenadinas, Sain Lucia, Dominica and Dominican Republic, one United States commonwealth associates states (Puerto Rico) and with dependent islands of the United States (Virign Islands), United Kingdom (Nevis, St. Christopher and Montserrat), France (Guadeloupe and Martinique) and Netherland (Curacao, Aruba, Bonaire, Saba and St. Eustatius). The paper discuss at length three recent Venezuelan agreements: a fishing agreement with Trinidad and Tobago (1977), plus two Exclusive Economic Zone (EEZ) delineation treaties concluded almost simultaneously in 1978; one with the United States (Puerto Rico and Virgin Islands) and the other with the Netherlands and Dutch Antilles falling with two separates sectors of the Caribbean

The development of a model to describe the influence of temperature and relative humidity on respiration rate of prickly pear cactus stems in reduced O2 conditions

Respiration rate (RO2) of prickly pear cactus stems (Opuntia spp.) was measured as a function of 4 temperature (T) and 6 relative humidity (RH) combinations for O2 partial pressures between 15 and 0.8 kPa, which were considered to support aerobic respiration. The rate of respiration (RO2) was determined based on O2 depletion of the atmosphere in sealed containers containing 1 kg of stems. The O2 partial pressure declined linearly over time and the slopes of the fitted lines were used to calculate the rate of O2 uptake. The rate of O2 uptake increased with increasing temperature and decreased with increasing RH. The respiratory rate at 25°C was approximately 30 to 40 times higher than at 5°C. The respiratory rate at 65% RH was between 30 and 90% greater than at 90% RH, depending on the temperature. Data for ln(RO2) for each RH level were regressed against the inverse of the T (K-1) to determine Arrhenius constants and calculate the apparent Ea of respiration for the six RH conditions. The Ea was similar for each RH level, varying between a low of 113 to a high of 131 kJ•mol-1. An equation having an R2 of 0.95 was developed describing respiration as a function of RH and T (°C) using only four constant

Tailoring and evaluating the Wikipedia for in-domain comparable corpora extraction

We propose a language-independent graph-based method to build a-la-carte article collections on user-defined domains from the Wikipedia. The core model is based on the exploration of the encyclopedia's category graph and can produce both mono- and multilingual comparable collections. We run thorough experiments to assess the quality of the obtained corpora in 10 languages and 743 domains. According to an extensive manual evaluation, our graph model reaches an average precision of 84% on in-domain articles, outperforming an alternative model based on information retrieval techniques. As manual evaluations are costly, we introduce the concept of domainness and design several automatic metrics to account for the quality of the collections. Our best metric for domainness shows a strong correlation with human judgments, representing a reasonable automatic alternative to assess the quality of domain-specific corpora. We release the WikiTailor toolkit with the implementation of the extraction methods, the evaluation measures and several utilities

Regulatory Framework for Renewable Energy Sources in Ecuador Case Study Province of Manabi

The purpose of the research is to expose the nature that, in matters of law and social policy, justifies promoting the elaboration and adoption of a regulatory framework that favors the use of renewable energy sources, for the generation of electricity through case analysis in the Province of Manabí. For the accomplishment of the research study has taken into account a brief theoretical analysis on the fundamentals of the regulatory doctrine, where it exposes the conceptual framework of the law and its necessity for the good development of the social relations that derive from the use of the Renewable sources of energy. A study was carried out of the specific regulatory work carried out at the International level, in order to promote the adequate use of renewable energies, as well as a national study presenting an initial vision for the study and establishment of a specific regulatory framework for the case study of the province of Manabí, as well as a group of policies and support measures that could be adopted to promote the integrated use of renewable energy sources and their contribution to the national energy matrix

Thread-level information for comment classification in community question answering

Community Question Answering (cQA) is a new application of QA in social contexts (e.g., fora). It presents new interesting challenges and research directions, e.g., exploiting the dependencies between the different comments of a thread to select the best answer for a given question. In this paper, we explored two ways of modeling such dependencies: (i) by designing specific features looking globally at the thread; and (ii) by applying structure prediction models. We trained and evaluated our models on data from SemEval-2015 Task 3 on Answer Selection in cQA. Our experiments show that: (i) the thread-level features consistently improve the performance for a variety of machine learning models, yielding state-of-the-art results; and (ii) sequential dependencies between the answer labels captured by structured prediction models are not enough to improve the results, indicating that more information is needed in the joint model

On Implementing Autonomic Systems with a Serverless Computing Approach: The Case of Self-Partitioning Cloud Caches

The research community has made significant advances towards realizing self-tuning cloud caches; notwithstanding, existing products still require manual expert tuning to maximize performance. Cloud (software) caches are built to swiftly serve requests; thus, avoiding costly functionality additions not directly related to the request-serving control path is critical. We show that serverless computing cloud services can be leveraged to solve the complex optimization problems that arise during self-tuning loops and can be used to optimize cloud caches for free. To illustrate that our approach is feasible and useful, we implement SPREDS (Self-Partitioning REDiS), a modified version of Redis that optimizes memory management in the multi-instance Redis scenario. A cost analysis shows that the serverless computing approach can lead to significant cost savings: The cost of running the controller as a serverless microservice is 0.85% of the cost of the always-on alternative. Through this case study, we make a strong case for implementing the controller of autonomic systems using a serverless computing approach

Overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims. Task 1: Check-Worthiness

We present an overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims, with focus on Task 1: Check-Worthiness. The task asks to predict which claims in a political debate should be prioritized for fact-checking. In particular, given a debate or a political speech, the goal was to produce a ranked list of its sentences based on their worthiness for fact checking. We offered the task in both English and Arabic, based on debates from the 2016 US Presidential Campaign, as well as on some speeches during and after the campaign. A total of 30 teams registered to participate in the Lab and seven teams actually submitted systems for Task 1. The most successful approaches used by the participants relied on recurrent and multi-layer neural networks, as well as on combinations of distributional representations, on matchings claims' vocabulary against lexicons, and on measures of syntactic dependency. The best systems achieved mean average precision of 0.18 and 0.15 on the English and on the Arabic test datasets, respectively. This leaves large room for further improvement, and thus we release all datasets and the scoring scripts, which should enable further research in check-worthiness estimation

Overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims. Task 2: Factuality

We present an overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims, with focus on Task 2: Factuality. The task asked to assess whether a given check-worthy claim made by a politician in the context of a debate/speech is factually true, half-true, or false. In terms of data, we focused on debates from the 2016 US Presidential Campaign, as well as on some speeches during and after the campaign (we also provided translations in Arabic), and we relied on comments and factuality judgments from factcheck.org and snopes.com, which we further refined manually. A total of 30 teams registered to participate in the lab, and five of them actually submitted runs. The most successful approaches used by the participants relied on the automatic retrieval of evidence from the Web. Similarities and other relationships between the claim and the retrieved documents were used as input to classifiers in order to make a decision. The best-performing official submissions achieved mean absolute error of .705 and .658 for the English and for the Arabic test sets, respectively. This leaves plenty of room for further improvement, and thus we release all datasets and the scoring scripts, which should enable further research in fact-checking

Overview of the CLEF-2018 checkthat! lab on automatic identification and verification of political claims

We present an overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims. In its starting year, the lab featured two tasks. Task 1 asked to predict which (potential) claims in a political debate should be prioritized for fact-checking; in particular, given a debate or a political speech, the goal was to produce a ranked list of its sentences based on their worthiness for fact-checking. Task 2 asked to assess whether a given check-worthy claim made by a politician in the context of a debate/speech is factually true, half-true, or false. We offered both tasks in English and in Arabic. In terms of data, for both tasks, we focused on debates from the 2016 US Presidential Campaign, as well as on some speeches during and after the campaign (we also provided translations in Arabic), and we relied on comments and factuality judgments from factcheck.org and snopes.com, which we further refined manually. A total of 30 teams registered to participate in the lab, and 9 of them actually submitted runs. The evaluation results show that the most successful approaches used various neural networks (esp. for Task 1) and evidence retrieval from the Web (esp. for Task 2). We release all datasets, the evaluation scripts, and the submissions by the participants, which should enable further research in both check-worthiness estimation and automatic claim verification