The present work aimed at studying growth pattern and carcass traits in pearl grey guinea fowl fed on dietary Neem (Azadirachta indica) leaf powder (NLP) over a period of 12 weeks. Day old guinea fowl keets (n=120) were randomly assigned to four treatment groups, each with 3 replicates. The first treatment was designated as control (T0) in which no supplement was added to the feed, while in tre...

OBJECTIVE To evaluate a system we developed that connects natural language processing (NLP) for information extraction from narrative text mammography reports with a Bayesian network for decision-support about breast cancer diagnosis. The ultimate goal of this system is to provide decision support as part of the workflow of producing the radiology report. MATERIALS AND METHODS We built a syst...

An algorithmic framework for numerically approximating multiparametric nonlinear programming (mp-NLP) solutions is given, along with a method that uses mp-NLP for evaluating the adequacy of the nominal model used in Implicit Optimization. The mp-NLP algorithm builds on numerical methods for single parameter nonlinear programming and for the approximation of implicit manifolds. An example proble...

While some linguistic questions pose challenges that could be met by developing and applying NLP techniques, other problems can best be approached with a blend of old-fashioned linguistic investigation and the use of simple, well-established NLP tools. Unfortunately, this means that the NLP component is too simple to be of interest to the computationally-minded, while existing tools are often d...

This paper looks at how Computational Linguistics (CL) and Natural Language Processing (NLP) resources can be deployed in ComputerAssisted Language Learning (CALL) materials for primary school learners. We draw a broad distinction between CL and NLP technology and briefly review the use of CL/NLP in e-Learning in general, how it has been deployed in CALL to date and specifically in the primary ...

Recent years have seen a rapid growth in the use of biomedical documents and narrative clinical records for applications outside of direct patient care. Accordingly, recent years have also seen an increase in the development of NLP technologies for concept and relation extraction, summarization, and question answering on these data. This tutorial will present an overview of the biomedical and c...

Deep neural networks (DNNs) have revolutionized the field of natural language processing (NLP). Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN), the two main types of DNN architectures, are widely explored to handle various NLP tasks. CNN is supposed to be good at extracting positioninvariant features and RNN at modeling units in sequence. The state-of-the-art on many NLP ...

Dashboard is a tool for integration, validation, and visualization of Natural Language Processing (NLP) systems. It provides infrastructural facilities using which individual NLP modules may be evaluated and refined, and multiple NLP modules may be combined to build a large end-user NLP system. It helps system integration team to integrate and validate NLP systems. The tool provides a visualiza...

BACKGROUND Rhythmic behaviors are driven by endogenous biological clocks in pacemakers, which must reliably transmit timing information to target tissues that execute rhythmic outputs. During the defecation motor program in C. elegans, calcium oscillations in the pacemaker (intestine), which occur about every 50 s, trigger rhythmic enteric muscle contractions through downstream GABAergic neuron...