The SEMAINE corpus of emotionally coloured character interactions

We have recorded a new corpus of emotionally coloured conversations. Users were recorded while holding conversations with an operator who adopts in sequence four roles designed to evoke emotional reactions. The operator and the user are seated in separate rooms; they see each other through teleprompter screens, and hear each other through speakers. To allow high quality recording, they are recorded by five high-resolution, high framerate cameras, and by four microphones. All sensor information is recorded synchronously, with an accuracy of 25 μs. In total, we have recorded 20 participants, for a total of 100 character conversational and 50 non-conversational recordings of approximately 5 minutes each. All recorded conversations have been fully transcribed and annotated for five affective dimensions and partially annotated for 27 other dimensions. The corpus has been made available to the scientific community through a web-accessible database.

Generalized collisional radiative model for light elements: C: Data for the B isonuclear sequence

A first stage collision database is assembled which contains electron-impact excitation, ionization,\r and recombination rate coefficients for B, B + , B 2+ , B 3+ , and B 4+ . The first stage database\r is constructed using the R-matrix with pseudostates, time-dependent close-coupling, and perturbative\r distorted-wave methods. A second stage collision database is then assembled which contains\r generalized collisional-radiative ionization, recombination, and power loss rate coefficients as a\r function of both temperature and density. The second stage database is constructed by solution of\r the collisional-radiative equations in the quasi-static equilibrium approximation using the first\r stage database. Both collision database stages reside in electronic form at the IAEA Labeled Atomic\r Data Interface (ALADDIN) database and the Atomic Data Analysis Structure (ADAS) open database.

FPGA-based minutia matching for biometric fingerprint image database retrieval

In this paper, a parallel-matching processor architecture with early jump-out (EJO) control is proposed to carry out high-speed biometric fingerprint database retrieval. The processor performs the fingerprint retrieval by using minutia point matching. An EJO method is applied to the proposed architecture to speed up the large database retrieval. The processor is implemented on a Xilinx Virtex-E, and occupies 6,825 slices and runs at up to 65 MHz. The software/hardware co-simulation benchmark with a database of 10,000 fingerprints verifies that the matching speed can achieve the rate of up to 1.22 million fingerprints per second. EJO results in about a 22% gain in computing efficiency.

sscMap: An extensible Java application for connecting small-molecule drugs using gene-expression signatures

Background
Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures.

Results
This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies.

Conclusion
The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMap

The distribution of late-Quaternary woody taxa in northern Eurasia: evidence from a new macrofossil database

We present a database of late-Quaternary plant macrofossil records for northern Eurasia (from 23 degrees to 180 degrees E and 46 degrees to 76 degrees N) comprising 281 localities, over 2300 samples and over 13,000 individual records. Samples are individually radiocarbon dated or are assigned ages via age models fitted to sequences of calibrated radiocarbon dates within a section. Tree species characteristic of modern northern forests (e.g. Picea, Larix, tree-Betula) are recorded at least intermittently from prior to the last glacial maximum (LGM), through the LGM and Lateglacial, to the Holocene, and some records locate trees close to the limits of the Scandinavian ice sheet, supporting the hypothesis that some taxa persisted in northern refugia during the last glacial cycle. Northern trees show differing spatio-temporal patterns across Siberia: deciduous trees were widespread in the Lateglacial, with individuals occurring across much of their contemporary ranges, while evergreen conifers expanded northwards to their range limits in the Holocene. (c) 2009 Elsevier Ltd. All rights reserved.

Application of connectivity mapping in predictive toxicology based on gene-expression similarity.

Connectivity mapping is the process of establishing connections between different biological states using gene-expression profiles or signatures. There are a number of applications but in toxicology the most pertinent is for understanding mechanisms of toxicity. In its essence the process involves comparing a query gene signature generated as a result of exposure of a biological system to a chemical to those in a database that have been previously derived. In the ideal situation the query gene-expression signature is characteristic of the event and will be matched to similar events in the database. Key criteria are therefore the means of choosing the signature to be matched and the means by which the match is made. In this article we explore these concepts with examples applicable to toxicology.

No association between routinely recorded infections in early life and subsequent risk of childhood-onset Type 1 diabetes: a matched case-control study using the UK General Practice Research Database

Aims To determine whether children with infections in early life (recorded routinely in general practice) have a reduced risk of Type 1 diabetes, as would be expected from the hygiene hypothesis.

The SEMAINE Database: Annotated Multimodal Records of Emotionally Colored Conversations between a Person and a Limited Agent

SEMAINE has created a large audiovisual database as a part of an iterative approach to building Sensitive Artificial Listener (SAL) agents that can engage a person in a sustained, emotionally colored conversation. Data used to build the agents came from interactions between users and an operator simulating a SAL agent, in different configurations: Solid SAL (designed so that operators displayed an appropriate nonverbal behavior) and Semi-automatic SAL (designed so that users' experience approximated interacting with a machine). We then recorded user interactions with the developed system, Automatic SAL, comparing the most communicatively competent version to versions with reduced nonverbal skills. High quality recording was provided by five high-resolution, high-framerate cameras, and four microphones, recorded synchronously. Recordings total 150 participants, for a total of 959 conversations with individual SAL characters, lasting approximately 5 minutes each. Solid SAL recordings are transcribed and extensively annotated: 6-8 raters per clip traced five affective dimensions and 27 associated categories. Other scenarios are labeled on the same pattern, but less fully. Additional information includes FACS annotation on selected extracts, identification of laughs, nods, and shakes, and measures of user engagement with the automatic system. The material is available through a web-accessible database. © 2010-2012 IEEE.

The Belfast Induced Natural Emotion Database

For many years psychological research on facial expression of emotion has relied heavily on a recognition paradigm based on posed static photographs. There is growing evidence that there may be fundamental differences between the expressions depicted in such stimuli and the emotional expressions present in everyday life. Affective computing, with its pragmatic emphasis on realism, needs examples of natural emotion. This paper describes a unique database containing recordings of mild to moderate emotionally coloured responses to a series of laboratory based emotion induction tasks. The recordings are accompanied by information on self-report of emotion and intensity, continuous trace-style ratings of valence and intensity, the sex of the participant, the sex of the experimenter, the active or passive nature of the induction task and it gives researchers the opportunity to compare expressions from people from more than one culture.

TMAX – a Database System Integrating Tissue Biomarker & Genomic Data

Background: Popular approaches in human tissue-based biomarker discovery include tissue microarrays (TMAs) and DNA Microarrays (DMAs) for protein and gene expression profiling respectively. The data generated by these analytic platforms, together with associated image, clinical and pathological data currently reside on widely different information platforms, making searching and cross-platform analysis difficult. Consequently, there is a strong need to develop a single coherent database capable of correlating all available data types.

Method: This study presents TMAX, a database system to facilitate biomarker discovery tasks. TMAX organises a variety of biomarker discovery-related data into the database. Both TMA and DMA experimental data are integrated in TMAX and connected through common DNA/protein biomarkers. Patient clinical data (including tissue pathological data), computer assisted tissue image and associated analytic data are also included in TMAX to enable the truly high throughput processing of ultra-large digital slides for both TMAs and whole slide tissue digital slides. A comprehensive web front-end was built with embedded XML parser software and predefined SQL queries to enable rapid data exchange in the form of standard XML files.

Results & Conclusion: TMAX represents one of the first attempts to integrate TMA data with public gene expression experiment data. Experiments suggest that TMAX is robust in managing large quantities of data from different sources (clinical, TMA, DMA and image analysis). Its web front-end is user friendly, easy to use, and most importantly allows the rapid and easy data exchange of biomarker discovery related data. In conclusion, TMAX is a robust biomarker discovery data repository and research tool, which opens up the opportunities for biomarker discovery and further integromics research.

The UMIST Database for Astrochemistry 2012

We present the fifth release of the UMIST Database for Astrochemistry (UDfA). The new reaction network contains 6173 gas-phase
reactions, involving 467 species, 47 of which are new to this release. We have updated rate coefficients across all reaction types.
We have included 1171 new anion reactions and updated and reviewed all photorates. In addition to the usual reaction network, we
also now include, for download, state-specific deuterated rate coefficients, deuterium exchange reactions and a list of surface binding
energies for many neutral species. Where possible, we have referenced the original source of all new and existing data. We have tested
the main reaction network using a dark cloud model and a carbon-rich circumstellar envelope model. We present and briefly discuss
the results of these models.

SHEPARD: Scheduling on heterogeneous platforms using application resource demands

Heterogeneous computing technologies, such as multi-core CPUs, GPUs and FPGAs can provide significant performance improvements. However, developing applications for these technologies often results in coupling applications to specific devices, typically through the use of proprietary tools. This paper presents SHEPARD, a compile time and run-time framework that decouples application development from the target platform and enables run-time allocation of tasks to heterogeneous computing devices. Through the use of special annotated functions, called managed tasks, SHEPARD approximates a task's performance on available devices, and coupled with the approximation of current device demand, decides which device can satisfy the task with the lowest overall execution time. Experiments using a task parallel application, based on an in-memory database, demonstrate the opportunity for automatic run-time task allocation to achieve speed-up over a static allocation to a single specific device. © 2014 IEEE.