278 research outputs found
Nicotinic acid-free diet and NAPRT inhibitors as a means to sensitize cancer cells to NAMPT inhibitors
No full textDepleting NAD levels in tumors by interrupting their NAD-biosynthetic routes is an attractive anti-cancer strategy. Yet, suppressing the predominant NAD-producing salvage pathway by nicotinamide phosphoribosyltransferase (NAMPT) inhibitors failed in clinical trials, indicating that tumors can exploit alternative NAD-biosynthetic routes to escape NAMPT blockade. In this regard, the contribution of the Preiss-Handler (PH) pathway to NAD production in tumors is gaining great momentum. This pathway utilizes nicotinic acid (NA) as a substrate, which can be obtained from the diet or the gut microbiome. Herein, we demonstrate that blocking the PH pathway with an NA-free diet restored the activity of the NAMPT inhibitor FK866 in an ovarian cancer xenograft model. This combined intervention significantly reduced tumor volumes, blunted NAD levels, and impaired the energy status and metabolic activity of the tumors, while showing no systemic toxicity. In addition, combining an NA-free diet with antibiotics (to eliminate microbiota-derived NA) delayed tumor progression in the absence of NAMPT inhibitors. Furthermore, we also aimed at identifying new inhibitors to the rate-limiting enzyme of the PH pathway nicotinic acid phosphoribosyltransferase (NAPRT). We took advantage of in silico screening techniques and were able to annotate and characterize two NAPRT inhibitors that showed anti-cancer efficacy at micromolar concentrations while possessing favorable drug-like profiles. Since some NAMPT inhibitors are being currently evaluated in clinical trials, this work provides a rationale to couple NA-free diets or NAPRT inhibitors with NAMPT inhibitors in cancer patients
A network approach for managing and processing big cancer data in clouds
No full textTranslational cancer research requires integrative analysis of multiple levels of big cancer data to identify and treat cancer. In order to address the issues that data is decentralised, growing and continually being updated, and the content living or archiving on different information sources partially overlaps creating redundancies as well as contradictions and inconsistencies, we develop a data network model and technology for constructing and managing big cancer data. To support our data network approach for data process and analysis, we employ a semantic content network approach and adopt the CELAR cloud platform. The prototype implementation shows that the CELAR cloud can satisfy the on-demanding needs of various data resources for management and process of big cancer data
Overview of the Track on Author Profiling and Deception Detection in Arabic
No full text[EN] This overview presents the Author Profiling and Deception Detection in Arabic (APDA) shared task at PAN@FIRE 2019. Two have been the main aims of this years task: i) to profile the age, gender and native language of a Twitter user; ii) to determine whether an Arabic text is deceptive or not in two different genres: Twitter and news headlines. For this purpose we have created three corpora in Arabic. Altogether, the approaches of 13 participants are evaluated.This publication was made possible by NPRP 9-175-1-033 from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved
herein are solely the responsibility of the authors. The work of Paolo Rosso was
also partially funded by Generalitat Valenciana under grant PROMETEO/2019/121.Rangel, F.; Rosso, P.; Charfi, A.; Zaghouani, W.; Ghanem, B.; Sánchez-Junquera, J. (2019). Overview of the Track on Author Profiling and Deception Detection in Arabic. CEUR-WS.org. 70-83. https://riunet.upv.es/handle/10251/180742S708
Grid-enabled Workflows for Industrial Product Design
No full textThis paper presents a generic approach for developing and using Grid-based workflow technology for enabling cross-organizational engineering applications. Using industrial product design examples from the automotive and aerospace industries we highlight the main requirements and challenges addressed by our approach and describe how it can be used for enabling interoperability between heterogeneous workflow engines
Sparse nonlinear methods for predicting structured data
No full textGaussian processes are now widely used to perform key machine learning tasks such as nonlinear
regression and classification. An attractive feature of Gaussian process models is the behaviour
of the error bars, which grow in regions away from observations where there is high uncertainty
about the interpolating function. The complexity of these models scales as O(N3) with sample
size, which causes difficulties with large data sets. The goals of this work are to develop
nonlinear, nonparametric modelling techniques for structure learning and prediction problems
in which there are structured dependencies among the observed data, and to equip our models
with sparse representations which serve both to handle prior sparse connectivity assumptions
and to reduce computational complexity.
We present Kernel Dynamical Structure Learning, a Bayesian method for learning the structure
of interactions between variables in multivariate time-series. We design a mutual information
kernel to handle time-series trajectories, and show that prior knowledge about network sparsity
can be incorporated using heavy-tailed priors over parameters. We evaluate the feasibility of our
method on synthetic data, and extend the inference methodology to the handling of uncertain
input data.
Next, we tackle the problem of belief propagation in Bayesian networks with nonlinear node
relations. We propose an exact moment-matching approach for nonlinear belief propagation in
any tree-structured graph. We call this Gaussian Process Belief Propagation. We extend this
approach by the addition of hidden variables which allow nodes sharing common influences to
be conditionally independent. This constitutes a novel approach to multi-output regression on
bivariate graph structures, and we call this Dependent Gaussian Process Belief Propagation.
We describe sparse inference methods for both models, which reduce computational by learning
compact parameterisations of the available training data. We then apply our method to the
real-world systems biology problem of protein inference in transcriptional networks
Overview of the 8th Author Profiling Task at PAN 2020: Profiling Fake News Spreaders on Twitter
No full text[EN] This overview presents the Author Profiling shared task at
PAN 2020. The focus of this year's task is on determining whether or not
the author of a Twitter feed is keen to spread fake news. Two have been
the main aims: (i) to show the feasibility of automatically identifying
potential fake news spreaders in Twitter; and (ii) to show the difficulty
of identifying them when they do not limit themselves to just retweet
domain-specific news. For this purpose a corpus with Twitter data has
been provided, covering the English and Spanish languages. Altogether,
the approaches of 66 participants have been evaluated.First of all we thank the participants: 66 this year, record in terms of participants at PAN Lab since 2009! We have to thank also Martin Potthast, Matti
Wiegmann, and Nikolay Kolyada to help with the 66 Virtual Machines in the
TIRA platform. We thank Symanto for sponsoring the ex aequo award for the two best performing systems at the author profiling shared task of this year. The
work of Paolo Rosso was partially funded by the Spanish MICINN under the
research project MISMIS-FAKEnHATE on Misinformation and Miscommunication in social media: FAKE news and HATE speech (PGC2018-096212-B-C31).
The work of Anastasia Giachanou is supported by the SNSF Early Postdoc
Mobility grant under the project Early Fake News Detection on Social Media,
Switzerland (P2TIP2 181441).Rangel, F.; Giachanou, A.; Ghanem, BHH.; Rosso, P. (2020). Overview of the 8th Author Profiling Task at PAN 2020: Profiling Fake News Spreaders on Twitter. CEUR Workshop Proceedings. 2696:1-18. https://riunet.upv.es/handle/10251/166528S118269
Political regimes, trade, and labor policies in developing countries
No full textWhat, if any, is the link between labor market policies that benefit insiders - for example, regulations guaranteeing high minimum wages and strict job security - and political regimes. Is it true that in a democracy outsiders vote and impose limits on what insiders can achieve, whereas in a dictatorship the government need worry only about insiders who have real power? Or are democratic governments more likely to succumb to trade union pressure and use labor policies to give them special privileges? To test these competing hypotheses, the authors designed a two-sector political economy model that demonstrates that labor market distortions depend directly on the trade regime: the more open the trade regime, the fewer distortions in the labor market. They use cross-country regressions to test the relationship between political and civil liberties and trade and labor policies. Using data for 90 developing countries, they apply existing indices of openness and political freedom and two different constructed measures of labor market distortion. Their conclusions, based on the regression results: authoritarian systems that repress labor are more likely than democratic systems to adopt inefficient labor policies inimical to development.Economic Theory&Research,Environmental Economics&Policies,Labor Policies,Health Economics&Finance,Banks&Banking Reform,Environmental Economics&Policies,Health Economics&Finance,Banks&Banking Reform,Labor Standards,Economic Theory&Research
Politiques et institutions à l’appui des petites exploitations agricoles
No full textRésuméCet article défend l'idée que les petites exploitations agricoles doivent être placées au cœur du processus de développement, principalement dans les pays du Sud, notamment parce que la moitié des populations qui, dans le monde, souffrent de la faim, habitent des zones rurales et disposent de moins de 2 hectares, et parce que près de 2 milliards d'êtres humains dépendent de l'agriculture familiale. L'auteur, éminent représentant de la FAO, préconise l'insertion de la petite exploitation dans les circuits agro-industriels. Il s'agit de construire une politique différente, qui vise à rapprocher les petits agriculteurs des marchés en développant une chaîne de valeur (c'est-à-dire des arrangements contractuels au sein des chaînes de valeur agro-industrielles) et en proposant des stratégies de transition.Hafez Ghanem, Policies and Institutions in Support of Small FarmsThis paper argues that small farms need to be placed at the heart of the development process (primarily in southern countries), since half of the population affected by famine live in rural areas and have less than 2 hectares of land at their disposal, and nearly 2 billion people are dependent on family farming. The author, an eminent representative of the FAO, recommends that small farms should be integrated into agro-industrial networks. The aim is to develop a different policy aimed at bringing small farmers closer to markets by developing a value chain (i.e. contractual arrangements within agro-industrial value chains) and by proposing transition strategies
IDAT@FIRE2019: Overview of the Track on Irony Detection in Arabic Tweets
No full text[EN] This overview paper describes the first shared task on irony
detection for the Arabic language. The task consists of a binary classification of tweets as ironic or not using a dataset composed of 5,030
Arabic tweets about different political issues and events related to the
Middle East and the Maghreb. Tweets in our dataset are written in
Modern Standard Arabic but also in different Arabic language varieties
including Egypt, Gulf, Levantine and Maghrebi dialects. Eighteen teams
registered to the task among which ten submitted their runs. The methods of participants ranged from feature-based to neural networks using
either classical machine learning techniques or ensemble methods. The
best performing system achieved F-score value of 0.844, showing that
classical feature-based models outperform the neural ones.This publication was made possible by NPRP grant 9-175-1-033 from the Qatar
National Research Fund (a member of Qatar Foundation). The findings achieved
herein are solely the responsibility of the last author. The work of Paolo Rosso
was also partially funded by Generalitat Valenciana under grant PROMETEO/2019/121.Ghanem, B.; Karoui, J.; Benamara, F.; Moriceau, V.; Rosso, P. (2019). IDAT@FIRE2019: Overview of the Track on Irony Detection in Arabic Tweets. CEUR-WS.org. 380-390. https://riunet.upv.es/handle/10251/180744S38039
Privatization of Gulf Industrial Institutions: The Secret of Success
No full text[No abstract available]*AL PARTN, MIDDL E LAWS KUW; ALABDULLAH H, 1997, INTERVIEW ABC QATAR; *CRED SUISS, 2007, SAUD AR STRONG INFL; Ehteshami A, 2007, INT AFF, V83, P913, DOI 10.1111-j.1468-2346.2007.00662.x; Fasano U., 2003, GCC COUNTRIES OIL DE; Hakim SR, 2008, MIDDLE EAST POLICY, V15, P70, DOI 10.1111-j.1475-4967.2008.00339.x; Hammoudeh S., 2008, INT REV FINANC ANAL, V17, P47, DOI 10.1016-j.irfa.2005.01.002; Hertog S, 2007, MIDDLE EAST POLICY, V14, P52, DOI 10.1111-j.1475-4967.2007.00283.x; *KAMCO RES, 2007, GCC EQ MARK MONTHL R; MCLAURIN JR, 2006, ACAD STUDIES INT BUS, V6, P19; *OXF AN DAIL BRIEF, 2001, GULF STAT DIL DEL NE, P1; PITTAWAY J, 1995, INT FINANCIAL LAW RE, V14, P23; *POG, 2004, PROGR GOV AR REG; *SHUAA CAP, 2008, VIS 2008 SAUD AR EQ; *TRANSP INT, TRANSP INT 2003 CORR0
- …
