We describe a joint model for understanding user actions in natural language utterances. Our multi-layer generative approach uses both labeled and unlabeled utterances to jointly learn aspects regarding utterance’s target domain (e.g. movies), intention (e.g., ﬁnding a movie) along with other semantic units (e.g., movie name). We inject information extracted from unstructured web search query logs as prior information to enhance the generative process of the natural language utterance understanding model....
We present Wikulu1 , a system focusing on supporting wiki users with their everyday tasks by means of an intelligent interface. Wikulu is implemented as an extensible architecture which transparently integrates natural language processing (NLP) techniques with wikis. It is designed to be deployed with any wiki platform, and the current prototype integrates a wide range of NLP algorithms such as keyphrase extraction, link discovery, text segmentation, summarization, or text similarity.
Acquisition of phonological s y s t e m s can be insightfully studied in t e r m s of discovery procedures. T h i s paper describes a discovery procedure, i m p l e m e n t e d in Lisp, capable of determining a set of ordered phonological rules, which m a y be in opaque contexts~ from a set of surface forms arranged in paradigms.
Named Entity recognition (NER) is an important part of many natural language processing tasks. Current approaches often employ machine learning techniques and require supervised data. However, many languages lack such resources. This paper presents an (almost) unsupervised learning algorithm for automatic discovery of Named Entities (NEs) in a resource free language, given a bilingual corpora in which it is weakly temporally aligned with a resource rich language.
The discovery of efficacious new human therapeutic agents is one of humanity’s most vital
tasks. It is an enormously demanding activity that requires creativity, a vast range of scientific
knowledge, and great persistence. It is also an exceedingly expensive activity. In an
ideal world, no education would be complete without some exposure to the ways in which
new medicines are discovered and developed. For those young people interested in science
or medicine, such knowledge is arguably mandatory....
MTMF combines the best parts of the Linear Spectral Mixing model and the statistical
Matched Filter model while avoiding the drawbacks of each parent method (Boardman,
1998). It is a useful Matched Filter method without knowing all the possible endmembers in
a landscape especially in case of subtle, sub-pixel occurrences. Firstly, pixel spectra and
endmember spectra require a minimum noise fraction (MNF) (Green et al., 1988, Boardman,
1993) transformation. MNF reduces and separates an image into its most dimensional and
This book is a straightforward discussion of the concepts, principles, and processes of
Internet Protocol version 6 (IPv6) and how it is supported by the Microsoft Windows Server 2008
and Windows Vista operating systems. Note that this book does not contain programming
code-level details of the IPv6 protocol for Windows Server 2008 and Windows Vista, such as
structures, tables, buffers, or coding logic. These details are highly guarded Microsoft intellectual
property that is of interest only to a relative handful of software developers.
Worldwide, crude oil demand is unceasingly increasing. As a response, Enhanced Oil
Recovery (EOR) processes have re‐gained interest from the research and development
phases to the oilfield EOR implementation stage. This renewed interest has been also
furthered by the current high oil price environment, the maturation of oilfields
worldwide, and few new‐well discoveries. Concurrently, environmental concerns and
public pressure related to crude oil pollution control and remediation of oilcontaminated
sites are becoming greater than ever....
Great efﬁciencies have been achieved in the drug discovery process as a result of technological advances in target identiﬁcation, high-throughput screening, high-throughput organic synthesis, just-in-time in vitro ADME (absorption, distribution, metabolism, and excretion), and early pharmacokinetic screening of drug leads. These advances, spanning target selection all the way through to clinical candidate selection, have placed greater and greater demands on the analytical community to develop robust high-throughput methods.
The modern drug discovery process, in general, involves the identiﬁcation of a biochemical target (usually protein target), screening of synthetic compounds or compound libraries from combinatorial chemistry/natural sources for a lead compound, and optimization of the lead compound (activity, selectivity, pharmacokinetics, etc.) for recommending a potential clinical candidate.
Recent DCF analysis highlighted the importance of improved national aid information management systems to better
track effective development cooperation targets, including on gender equality and the empowerment of women, and to
make a wide range of timely and forward-looking information (on disbursements, forecasts, progress on results, and
gender issues) widely available to all stakeholders for accountability purposes.
Natural products are a constant source of potentially active compounds for the treatment of various disorders. The Middle East and tropical regions are believed to have the richest supplies of natural products in the world. Plant derived secondary metabolites have been used by humans to treat acute infections, health disorders and chronic illness for tens of thousands of years. Only during the last 100 years have natural products been largely replaced by synthetic drugs.
In the drug discovery area, a compound with desired therapeutic properties is identiﬁed, and its structure may be modiﬁed by synthetic alterations to enhance potency and speciﬁcity or to decrease toxicity and undesired side effects. The lead drug candidate is then transitioned into the drug development area. Only small amounts of drug (typically less than a gram) are required to support the required studies in the Drug Discovery area. However larger amounts are required to support the studies conducted in the Drug Development area.
After the ground breaking discovery of electrical charge carrier transport in
polymers in the late 1980s by Alan J. Heeger, Alan G. MacDiarmid and Hideki
Shirakawa [1–3], who were awarded the Nobel Prize in chemistry in 2000, the
question arose as to whether organic materials would also find applications as
organic semiconductors. This field really started to attract major attention after
the demonstration of the first organic light emitting device (OLED) in 1987 by
Tang and Van Slyke .
Since the discovery of X rays by Roentgen in 1895, the ionizing radiation has been
extensively utilized in a variety of medical and industrial applications. And it has also
played crucial roles in development of modern sciences and technologies, as witnessed
by more than 60 Nobel Prize winners awarded for achievements in atomic sciences
and ionizing radiation-related researches.
Data warehouses usually have some missing values due to unavailable data that affect the
number and the quality of the generated rules. The missing values could affect the coverage
percentage and number of reduces generated from a specific data set. Missing values lead to the
difficulty of extracting useful information from data set. Association rule algorithms typically
only identify patterns that occur in the original form throughout the database.
Certain developing countries and certain developed countries are especially large debtors to commercial banks and foreign
governments. Investment in debt obligations ("Sovereign Debt") issued or guaranteed by governments or their agencies ("governmental
entities") of such countries involves a high degree of risk. The governmental entity that controls the repayment of Sovereign Debt may
not be able or willing to repay the principal and/or interest when due in accordance with the terms of such debt.
In the last decade the progress of molecular biology has made a strong
influence on the theoretical framework of population genetics and evolution.
Introduction of molecular techniques in this area has resulted in many new
discoveries. As a result, a new interdisciplinary science, which may be called
'Molecular Population Genetics and Evolution', has emerged. In this book
I have attempted to discuss the development and outline of this science.
In recent years a large number of papers have been published on this
Since the discovery of the DNA structure researchers have been highly interested in the molecular basis of genome inheritance. This book covers a wide range of aspects and issues related to the field of DNA replication. The association between genome replication, repair and recombination is also addressed, as well as summaries of recent work of the replication cycles of prokaryotic and eukaryotic viruses. The reader will gain an overview of our current understanding of DNA replication and related cellular processes, and useful resources for further reading....
How variations in genes contribute to variations in disease risk has
been a subject of study for more than 100 years (IOM, 2006). Until fairly
recently research focused on single genes that give rise to rare genetic diseases
such as cystic fibrosis or Huntington’s disease.