University of Waterloo

About: University of Waterloo is a education organization based out in Waterloo, Ontario, Canada. It is known for research contribution in the topics: Population & Poison control. The organization has 36093 authors who have published 93906 publications receiving 2948139 citations. The organization is also known as: UW & uwaterloo.

Investigation of Methods for Reduction of Power Fluctuations Generated From Large Grid-Connected Photovoltaic Systems

Abstract: Photovoltaic (PV) systems are presently allowed to inject into the grid all the power they can generate. However, in the near future, utilities are expected to impose additional regulations and restrictions on the power being injected by large centralized PV systems because of their possible adverse impacts. One of the main issues associated with large PV systems is the fluctuation of their output power. These fluctuations can negatively impact the performance of the electric networks to which these systems are connected, especially if the penetration levels of these systems are high. Moreover, the fluctuations in the power of PV systems make it difficult to predict their output, and thus, to consider them when scheduling the generating units in the network. The main objective of this paper is to investigate some methods that can be used to reduce the fluctuations in the power generated from a large customer-owned PV system, in the order of megawatts. This paper focuses on three methods: 1) the use of battery storage systems; 2) the use of dump loads; and 3) curtailment of the generated power by operating the power-conditioning unit of the PV system below the maximum power point. The emphasis in the analysis presented in this paper is on investigating the impacts of implementing these methods on the economical benefits that the PV system owner gains. To estimate the maximum revenues gained by the system owner, an linear programming optimization problem is formulated and solved. Moreover, the effect of varying different parameters of the problem is investigated through sensitivity analysis.

Enhanced valley splitting in monolayer WSe2 due to magnetic exchange field

Abstract: Exploiting the valley degree of freedom to store and manipulate information provides a novel paradigm for future electronics. A monolayer transition-metal dichalcogenide (TMDC) with a broken inversion symmetry possesses two degenerate yet inequivalent valleys, which offers unique opportunities for valley control through the helicity of light. Lifting the valley degeneracy by Zeeman splitting has been demonstrated recently, which may enable valley control by a magnetic field. However, the realized valley splitting is modest (∼0.2 meV T-1). Here we show greatly enhanced valley spitting in monolayer WSe2, utilizing the interfacial magnetic exchange field (MEF) from a ferromagnetic EuS substrate. A valley splitting of 2.5 meV is demonstrated at 1 T by magnetoreflectance measurements and corresponds to an effective exchange field of ∼12 T. Moreover, the splitting follows the magnetization of EuS, a hallmark of the MEF. Utilizing the MEF of a magnetic insulator can induce magnetic order and valley and spin polarization in TMDCs, which may enable valleytronic and quantum-computing applications.

Burkholderia phytofirmans sp. nov., a novel plant-associated bacterium with plant-beneficial properties

Abstract: A Gram-negative, non-sporulating, rod-shaped, motile bacterium, with a single polar flagellum, designated strain PsJN(T), was isolated from surface-sterilized onion roots. This isolate proved to be a highly effective plant-beneficial bacterium, and was able to establish rhizosphere and endophytic populations associated with various plants. Seven related strains were recovered from Dutch soils. Based on 16S rRNA gene sequence data, strain PsJN(T) and the Dutch strains were identified as representing a member of the genus Burkholderia, as they were closely related to Burkholderia fungorum (98.7 %) and Burkholderia phenazinium (98.5 %). Analysis of whole-cell protein profiles and DNA-DNA hybridization experiments confirmed that all eight strains belonged to a single species. Strain PsJN(T) had a DNA G+C content of 61.0 mol%. Only low levels of DNA-DNA hybridization to closely related species were found. Qualitative and quantitative differences in fatty acid composition between strain PsJN(T) and closely related species were identified. The predominant fatty acids in strain PsJN(T) were 16 : 0, 18 : 1omega7c and summed feature 3 (comprising 16 : 1omega7c and/or iso-15 : 0 2-OH). Isolate PsJN(T) showed high 1-aminocyclopropane-1-carboxylate deaminase activity and is therefore able to lower the ethylene level in a developing or stressed plant. Production of the quorum-sensing signal compound 3-hydroxy-C8-homoserine lactone was detected. Based on the results of this polyphasic taxonomic study, strain PsJN(T) and the seven Dutch isolates are considered to represent a single, novel species, for which the name Burkholderia phytofirmans sp. nov. is proposed. The type strain is strain PsJN(T) (=LMG 22146(T) = CCUG 49060(T)).

DNA barcoding reveals extraordinary cryptic diversity in an amphipod genus: implications for desert spring conservation

Abstract: DNA barcoding has revealed unrecognized species in several animal groups. In this study we have employed DNA barcoding to examine Hyalella, a taxonomically difficult genus of amphipod crustaceans, from sites in the southern Great Basin of California and Nevada, USA. We assessed the extent of species diversity using a species screening threshold (SST) set at 10 times the average intrapopulation cytochrome c oxidase subunit I (COI) haplotype divergence. Despite the fact that this threshold approach is more conservative in delineating provisional species than the phylogenetic species concept, our analyses revealed extraordinary levels of cryptic diversity and endemism. The SST discriminated two provisional species within Hyalella sandra, and 33 provisional species within Hyalella azteca. COI nucleotide divergences among these provisional species ranged from 4.4% to 29.9%. These results have important implications for the conservation of life in desert springs - habitats that are threatened as a result of groundwater over-exploitation.

Data augmentation of wearable sensor data for parkinson’s disease monitoring using convolutional neural networks

Abstract: While convolutional neural networks (CNNs) have been successfully applied to many challenging classification applications, they typically require large datasets for training. When the availability of labeled data is limited, data augmentation is a critical preprocessing step for CNNs. However, data augmentation for wearable sensor data has not been deeply investigated yet. In this paper, various data augmentation methods for wearable sensor data are proposed. The proposed methods and CNNs are applied to the classification of the motor state of Parkinson’s Disease patients, which is challenging due to small dataset size, noisy labels, and large intra-class variability. Appropriate augmentation improves the classification performance from 77.54% to 86.88%.