Data Mining to Uncover Heterogeneous Water Use Behaviors From Smart Meter Data

Knowledge on the determinants and patterns of water demand for different consumers supports the design of customized demand management strategies. Smart meters coupled with big data analytics tools create a unique opportunity to support such strategies. Yet, at present, the information content of smart meter data is not fully mined and usually needs to be complemented with water fixture inventory and survey data to achieve detailed customer segmentation based on end use water usage. In this paper, we developed a data‐driven approach that extracts information on heterogeneous water end use routines, main end use components, and temporal characteristics, only via data mining existing smart meter readings at the scale of individual households. We tested our approach on data from 327 households in Australia, each monitored with smart meters logging water use readings every 5 s. As part of the approach, we first disaggregated the household‐level water use time series into different end uses via Autoflow. We then adapted a customer segmentation based on eigenbehavior analysis to discriminate among heterogeneous water end use routines and identify clusters of consumers presenting similar routines. Results revealed three main water end use profile clusters, each characterized by a primary end use: shower, clothes washing, and irrigation. Time‐of‐use and intensity‐of‐use differences exist within each class, as well as different characteristics of regularity and periodicity over time. Our customer segmentation analysis approach provides utilities with a concise snapshot of recurrent water use routines from smart meter data and can be used to support customized demand management strategies.TU Berlin, Open-Access-Mittel - 201

Searching for the expelled hydrogen envelope in Type I supernovae via late-time H-alpha emission

We report the first results from our long-term observational survey aimed at discovering late-time interaction between the ejecta of hydrogen-poor Type I supernovae and the hydrogen-rich envelope expelled from the progenitor star several decades/centuries before explosion. The expelled envelope, moving with a velocity of ~10 -- 100 km s$^{-1}$, is expected to be caught up by the fast-moving SN ejecta several years/decades after explosion depending on the history of the mass-loss process acting in the progenitor star prior to explosion. The collision between the SN ejecta and the circumstellar envelope results in net emission in the Balmer-lines, especially in H-alpha. We look for signs of late-time H-alpha emission in older Type Ia/Ibc/IIb SNe having hydrogen-poor ejecta, via narrow-band imaging. Continuum-subtracted H-alpha emission has been detected for 13 point sources: 9 SN Ibc, 1 SN IIb and 3 SN Ia events. Thirty-eight SN sites were observed on at least two epochs, from which three objects (SN 1985F, SN 2005kl, SN 2012fh) showed significant temporal variation in the strength of their H-alpha emission in our DIAFI data. This suggests that the variable emission is probably not due to nearby H II regions unassociated with the SN, and hence is an important additional hint that ejecta-CSM interaction may take place in these systems. Moreover, we successfully detected the late-time H-alpha emission from the Type Ib SN 2014C, which was recently discovered as a strongly interacting SN in various (radio, infrared, optical and X-ray) bands.Comment: 8 pages, 7 figures, accepted in Ap

Drawing on two methodological approaches: A collaborative approach to interview interpretation

Explicating interview approaches is significant for education research in understanding how the nuances of meaning from personal narratives uncover challenges and opportunities for investigating the lived experience across contexts. This paper considers interview approaches that focus on the reflexivity and meaning-making possible over a longitudinal timeframe for researcher and interviewee. Two methodological frameworks enabled a narrative oral history interview and a phenomenological lifeworld interview to establish variation in individual meaning-making, whilst eliciting understandings of shared social phenomena. We elucidate examples shared from the experience of teachers deemed as expert and interrogate the deliberations taken throughout a three-interview process. Reflexivity and the researcher's attendance to language, timing and open-ended prompting are some techniques considered for clarifying meaning in a small-scale Australian study. We argue that interrogating interview approaches for accessing deeper meaning-making of teacher professional learning further develops our understanding of interviewer-interviewee dynamics and the application of analytical frames

A conserved filamentous assembly underlies the structure of the meiotic chromosome axis.

The meiotic chromosome axis plays key roles in meiotic chromosome organization and recombination, yet the underlying protein components of this structure are highly diverged. Here, we show that 'axis core proteins' from budding yeast (Red1), mammals (SYCP2/SYCP3), and plants (ASY3/ASY4) are evolutionarily related and play equivalent roles in chromosome axis assembly. We first identify 'closure motifs' in each complex that recruit meiotic HORMADs, the master regulators of meiotic recombination. We next find that axis core proteins form homotetrameric (Red1) or heterotetrameric (SYCP2:SYCP3 and ASY3:ASY4) coiled-coil assemblies that further oligomerize into micron-length filaments. Thus, the meiotic chromosome axis core in fungi, mammals, and plants shares a common molecular architecture, and likely also plays conserved roles in meiotic chromosome axis assembly and recombination control

Rainbow trout (Oncorhynchus mykiss) urea cycle and polyamine synthesis gene families show dynamic expression responses to inflammation

The research was supported by a studentship to T. Clark funded between the University of Aberdeen and BioMar Ltd.Peer reviewedPostprin

Thalamocortical connectivity in major depressive disorder

Background: Major Depressive Disorder (MDD) is highly prevalent and potentially devastating, with widespread aberrations in brain activity. Thalamocortical networks are a potential candidate marker for psychopathology in MDD, but have not yet been thoroughly investigated. Here we examined functional connectivity between major cortical areas and thalamus. Method: Resting-state fMRI from 54 MDD patients and 40 healthy controls were collected. The cortex was segmented into six regions of interest (ROIs) consisting of frontal, temporal, parietal, and occipital lobes and pre-central and post-central gyri. BOLD signal time courses were extracted from each ROI and correlated with voxels in thalamus, while removing signals from every other ROI. Results: Our main findings showed that MDD patients had predominantly increased connectivity between medial thalamus and temporal areas, and between medial thalamus and somatosensory areas. Furthermore, a positive correlation was found between thalamo-temporal connectivity and severity of symptoms. Limitations: Most of the patients in this study were not medication naïve and therefore we cannot rule out possible long-term effects of antidepressant use on the findings. Conclusion: The abnormal connectivity between thalamus and temporal, and thalamus and somatosensory regions may represent impaired cortico-thalamo-cortical modulation underlying emotional, and sensory disturbances in MDD. In the context of similar abnormalities in thalamocortical systems across major psychiatric disorders, thalamocortical dysconnectivity could be a reliable transdiagnostic marker