Holistic Measures for Evaluating Prediction Models in Smart Grids

The performance of prediction models is often based on "abstract metrics" that estimate the model's ability to limit residual errors between the observed and predicted values. However, meaningful evaluation and selection of prediction models for end-user domains requires holistic and application-sensitive performance measures. Inspired by energy consumption prediction models used in the emerging "big data" domain of Smart Power Grids, we propose a suite of performance measures to rationally compare models along the dimensions of scale independence, reliability, volatility and cost. We include both application independent and dependent measures, the latter parameterized to allow customization by domain experts to fit their scenario. While our measures are generalizable to other domains, we offer an empirical analysis using real energy use data for three Smart Grid applications: planning, customer education and demand response, which are relevant for energy sustainability. Our results underscore the value of the proposed measures to offer a deeper insight into models' behavior and their impact on real applications, which benefit both data mining researchers and practitioners.Comment: 14 Pages, 8 figures, Accepted and to appear in IEEE Transactions on Knowledge and Data Engineering, 2014. Authors' final version. Copyright transferred to IEE

Gamma power in rural Pakistani children: links to executive function and verbal ability

Children in low- and middle-income countries are at high risk of cognitive deficits due to environmental deprivation that compromises brain development. Despite the high prevalence of unrealized cognitive potential, very little is known about neural correlates of cognition in this population. We assessed resting EEG power and cognitive ability in 105 highly disadvantaged 48-month-old children in rural Pakistan. An increase in EEG power in gamma frequency bands (21–30 Hz and 31–45 Hz) was associated with better executive function. For girls, EEG gamma power also related to higher verbal IQ. This study identifies EEG gamma power as a neural marker of cognitive function in disadvantaged children in low- and middle-income countries. Elevated gamma power may be a particularly important protective factor for girls, who may experience greater deprivation due to gender inequality.This research was supported by Grand Challenges Canada Saving Brains Initiative Grant 0061-03. The preparation of this article also was supported by a Scholar's Award from the William T. Grant Foundation to Jelena Obradovic. (0061-03 - Grand Challenges Canada Saving Brains Initiative; William T. Grant Foundation)Published versio

Novel VPS13B Mutations in Three Large Pakistani Cohen Syndrome Families Suggests a Baloch Variant with Autistic-Like Features.

BackgroundCohen Syndrome (COH1) is a rare autosomal recessive disorder, principally identified by ocular, neural and muscular deficits. We identified three large consanguineous Pakistani families with intellectual disability and in some cases with autistic traits.MethodsClinical assessments were performed in order to allow comparison of clinical features with other VPS13B mutations. Homozygosity mapping followed by whole exome sequencing and Sanger sequencing strategies were used to identify disease-related mutations.ResultsWe identified two novel homozygous deletion mutations in VPS13B, firstly a 1 bp deletion, NM_017890.4:c.6879delT; p.Phe2293Leufs*24, and secondly a deletion of exons 37-40, which co-segregate with affected status. In addition to COH1-related traits, autistic features were reported in a number of family members, contrasting with the "friendly" demeanour often associated with COH1. The c.6879delT mutation is present in two families from different regions of the country, but both from the Baloch sub-ethnic group, and with a shared haplotype, indicating a founder effect among the Baloch population.ConclusionWe suspect that the c.6879delT mutation may be a common cause of COH1 and similar phenotypes among the Baloch population. Additionally, most of the individuals with the c.6879delT mutation in these two families also present with autistic like traits, and suggests that this variant may lead to a distinct autistic-like COH1 subgroup

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition

Posterior eye shape measurement with retinal OCT compared to MRI

PURPOSE. Posterior eye shape assessment by magnetic resonance imaging (MRI) is used to study myopia. We tested the hypothesis that optical coherence tomography (OCT), as an alternative, could measure posterior eye shape similarly to MRI. METHODS. Macular spectral-domain OCT and brain MRI images previously acquired as part of the Singapore Epidemiology of Eye Diseases study were analyzed. The right eye in the MRI and OCT images was automatically segmented. Optical coherence tomography segmentations were corrected for optical and display distortions requiring biometry data. The segmentations were fitted to spheres and ellipsoids to obtain the posterior eye radius of curvature (Rc) and asphericity (Qxz). The differences in Rc and Qxz measured by MRI and OCT were tested using paired t-tests. Categorical assignments of prolateness or oblateness using Qxz were compared. RESULTS. Fifty-two subjects (67.8 ± 5.6 years old) with spherical equivalent refraction from +0.50 to -5.38 were included. The mean paired difference between MRI and original OCT posterior eye Rc was 24.03 ± 46.49 mm (P = 0.0005). For corrected OCT images, the difference in Rc decreased to -0.23 ± 2.47 mm (P = 0.51). The difference between MRI and OCT asphericity, Qxz, was -0.052 ± 0.343 (P = 0.28). However, categorical agreement was only moderate (j = 0.50). CONCLUSIONS. Distortion-corrected OCT measurements of Rc and Qxz were not statistically significantly different from MRI, although the moderate categorical agreement suggests that individual differences remained. This study provides evidence that with distortion correction, noninvasive office-based OCT could potentially be used instead of MRI for the study of posterior eye shape

First observation of low energy electron neutrinos in a liquid argon time projection chamber

Citation: Acciarri, R., Adams, C., Asaadi, J., Baller, B., Bolton, T., Bromberg, C., . . . ArgoNeu, T. C. (2017). First observation of low energy electron neutrinos in a liquid argon time projection chamber. Physical Review D, 95(7), 15. doi:10.1103/PhysRevD.95.072005The capabilities of liquid argon time projection chambers (LArTPCs) to reconstruct the spatial and calorimetric information of neutrino events have made them the detectors of choice in a number of experiments, specifically those looking to observe electron neutrino (nu(e)) appearance. The LArTPC promises excellent background rejection capabilities, especially in this "golden" channel for both short and long baseline neutrino oscillation experiments. We present the first experimental observation of electron neutrinos and antineutrinos in the ArgoNeut LArTPC, in the energy range relevant to DUNE and the Fermilab Short Baseline Neutrino Program. We have selected 37 electron candidate events and 274 gamma candidate events, and measured an 80% purity of electrons based on a topological selection. Additionally, we present a separation of electrons from gammas using calorimetric energy deposition, demonstrating further separation of electrons from background gammas

'I once wore an angry bird t-shirt and went to read Qur’an': asymmetrical institutional complexity and emerging consumption practices in Pakistan

This article brings together theories of institutional logics and the exploration of the lives of tweens in Pakistan to understand how emerging consumption practices fit within Pakistani children’s daily lives, and how institutional complexity that includes the dominance of religion under Pakistani Islamization is negotiated to separate and maintain the differences between them. We identify resolutions to asymmetrical institutional complexity in the consumption of character T-shirts: spatial–temporal practices, visual practices, symbolic substitution practices and single logic practices. We contribute to an understanding of how consumption happens in an Eastern Muslim culture, and how multiple institutional logics shape the consumption practices of children, by articulating how halal consumption practices, far from being essentialist, or presented as market segmentation, form from negotiations and reflections at the boundaries where Islam and Market logics meet

Visualization of grapevine root colonization by the Saharan soil isolate Saccharothrix algeriensis NRRL B-24137 using DOPE-FISH microscopy

Background and aim There is currently a gap of knowledge regarding whether some beneficial bacteria isolated from desert soils can colonize epi- and endophytically plants of temperate regions. In this study, the early steps of the colonization process of one of these bacteria, Saccharothrix algeriensis NRRL B-24137, was studied on grapevine roots to determine if this beneficial strain can colonize a non-natural host plant. An improved method of fluorescence in situ hybridization (FISH), the double labeling of oligonucleotide probes (DOPE)-FISH technique was used to visualize the colonization behavior of such bacteria as well as to determine if the method could be used to track microbes on and inside plants. Methods A probe specific to Saccharothrix spp. was firstly designed. Visualization of the colonization behavior of S. algeriensis NRRL B-24137 on and inside roots of grapevine plants was then carried out with DOPE-FISH microscopy. Results The results showed that 10 days after inoculation, the strain could colonize the root hair zone, root elongation zone, as well as root emergence sites by establishing different forms of bacterial structures as revealed by the DOPE-FISH technique. Further observations showed that the strain could be also endophytic inside the endorhiza of grapevine plants. Conclusions Taking into account the natural niches of this beneficial strain, this study exemplifies that, in spite of its isolation from desert soil, the strain can establish populations as well as subpopulations on and inside grapevine plants and that the DOPE-FISH tool can allow to detect it

Prediction of plant promoters based on hexamers and random triplet pair analysis

<p>Abstract</p> <p>Background</p> <p>With an increasing number of plant genome sequences, it has become important to develop a robust computational method for detecting plant promoters. Although a wide variety of programs are currently available, prediction accuracy of these still requires further improvement. The limitations of these methods can be addressed by selecting appropriate features for distinguishing promoters and non-promoters.</p> <p>Methods</p> <p>In this study, we proposed two feature selection approaches based on hexamer sequences: the Frequency Distribution Analyzed Feature Selection Algorithm (FDAFSA) and the Random Triplet Pair Feature Selecting Genetic Algorithm (RTPFSGA). In FDAFSA, adjacent triplet-pairs (hexamer sequences) were selected based on the difference in the frequency of hexamers between promoters and non-promoters. In RTPFSGA, random triplet-pairs (RTPs) were selected by exploiting a genetic algorithm that distinguishes frequencies of non-adjacent triplet pairs between promoters and non-promoters. Then, a support vector machine (SVM), a nonlinear machine-learning algorithm, was used to classify promoters and non-promoters by combining these two feature selection approaches. We referred to this novel algorithm as PromoBot.</p> <p>Results</p> <p>Promoter sequences were collected from the PlantProm database. Non-promoter sequences were collected from plant mRNA, rRNA, and tRNA of PlantGDB and plant miRNA of miRBase. Then, in order to validate the proposed algorithm, we applied a 5-fold cross validation test. Training data sets were used to select features based on FDAFSA and RTPFSGA, and these features were used to train the SVM. We achieved 89% sensitivity and 86% specificity.</p> <p>Conclusions</p> <p>We compared our PromoBot algorithm to five other algorithms. It was found that the sensitivity and specificity of PromoBot performed well (or even better) with the algorithms tested. These results show that the two proposed feature selection methods based on hexamer frequencies and random triplet-pair could be successfully incorporated into a supervised machine learning method in promoter classification problem. As such, we expect that PromoBot can be used to help identify new plant promoters. Source codes and analysis results of this work could be provided upon request.</p