Building fault detection data to aid diagnostic algorithm creation and performance testing.

It is estimated that approximately 4-5% of national energy consumption can be saved through corrections to existing commercial building controls infrastructure and resulting improvements to efficiency. Correspondingly, automated fault detection and diagnostics (FDD) algorithms are designed to identify the presence of operational faults and their root causes. A diversity of techniques is used for FDD spanning physical models, black box, and rule-based approaches. A persistent challenge has been the lack of common datasets and test methods to benchmark their performance accuracy. This article presents a first of its kind public dataset with ground-truth data on the presence and absence of building faults. This dataset spans a range of seasons and operational conditions and encompasses multiple building system types. It contains information on fault severity, as well as data points reflective of the measurements in building control systems that FDD algorithms typically have access to. The data were created using simulation models as well as experimental test facilities, and will be expanded over time

Waking up to sleepiness: Modafinil, the media and the pharmaceuticalisation of everyday/night life

This paper examines the social construction of the new wakefulness-promoting drug Modafinil (brand name Provigil) in the British press. Key themes in this newspaper coverage include the potential 'uses' and 'abuses' of this drug in relation to: (i) medical conditions; (ii) lifestyle choices; (iii) military operations; and (iv) sporting competition. The British press, we show, play a dual role in reporting on these trends and developments: on the one hand constructing this as something of a 'wonder drug' in relation to the treatment of a number of medical complaints or conditions, on the other hand articulating and amplifying a range of cultural concerns and anxieties about the non-medical 'uses' and 'abuses' of this drug, both now and in the future. These issues, it is argued, are best interpreted in terms of media concerns over the pharmaceuticalisation rather than the medicalisation of everyday/night life. The paper concludes with some further thoughts and reflections on these issues, including the potential reworking of notions of 'pharmaceutical Calvinism' and the 'elective affinity' between this 'smart' new drug and the spirit of (bio)capitalism

Epilepsy in Dcx Knockout Mice Associated with Discrete Lamination Defects and Enhanced Excitability in the Hippocampus

Patients with Doublecortin (DCX) mutations have severe cortical malformations associated with mental retardation and epilepsy. Dcx knockout (KO) mice show no major isocortical abnormalities, but have discrete hippocampal defects. We questioned the functional consequences of these defects and report here that Dcx KO mice are hyperactive and exhibit spontaneous convulsive seizures. Changes in neuropeptide Y and calbindin expression, consistent with seizure occurrence, were detected in a large proportion of KO animals, and convulsants, including kainate and pentylenetetrazole, also induced seizures more readily in KO mice. We show that the dysplastic CA3 region in KO hippocampal slices generates sharp wave-like activities and possesses a lower threshold for epileptiform events. Video-EEG monitoring also demonstrated that spontaneous seizures were initiated in the hippocampus. Similarly, seizures in human patients mutated for DCX can show a primary involvement of the temporal lobe. In conclusion, seizures in Dcx KO mice are likely to be due to abnormal synaptic transmission involving heterotopic cells in the hippocampus and these mice may therefore provide a useful model to further study how lamination defects underlie the genesis of epileptiform activities

Building fault detection data to aid diagnostic algorithm creation and performance testing

Measurement(s) building • heating • air conditioning • fault • temperature of air Technology Type(s) Sensor • computational modeling technique Factor Type(s) mode • day Sample Characteristic - Environment building Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.1174307

Building fault detection data to aid diagnostic algorithm creation and performance testing.

It is estimated that approximately 4-5% of national energy consumption can be saved through corrections to existing commercial building controls infrastructure and resulting improvements to efficiency. Correspondingly, automated fault detection and diagnostics (FDD) algorithms are designed to identify the presence of operational faults and their root causes. A diversity of techniques is used for FDD spanning physical models, black box, and rule-based approaches. A persistent challenge has been the lack of common datasets and test methods to benchmark their performance accuracy. This article presents a first of its kind public dataset with ground-truth data on the presence and absence of building faults. This dataset spans a range of seasons and operational conditions and encompasses multiple building system types. It contains information on fault severity, as well as data points reflective of the measurements in building control systems that FDD algorithms typically have access to. The data were created using simulation models as well as experimental test facilities, and will be expanded over time