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Institution

Harbin Institute of Technology

EducationHarbin, China
About: Harbin Institute of Technology is a education organization based out in Harbin, China. It is known for research contribution in the topics: Microstructure & Control theory. The organization has 88259 authors who have published 109297 publications receiving 1603393 citations. The organization is also known as: HIT.


Papers
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Journal ArticleDOI
TL;DR: One-dimension manganese dioxides (α- and β-MnO2) were discovered as effective PDS activators among the diverse manganes oxides for selective degradation of organic contaminants in wastewater and provides a novel catalytic system for selective removal of organic contamination in wastewater.
Abstract: Minerals and transitional metal oxides of earth-abundant elements are desirable catalysts for in situ chemical oxidation in environmental remediation. However, catalytic activation of peroxydisulfate (PDS) by manganese oxides was barely investigated. In this study, one-dimension manganese dioxides (α- and β-MnO2) were discovered as effective PDS activators among the diverse manganese oxides for selective degradation of organic contaminants. Compared with other chemical states and crystallographic structures of manganese oxide, β-MnO2 nanorods exhibited the highest phenol degradation rate (0.044 min-1, 180 min) by activating PDS. A comprehensive study was conducted utilizing electron paramagnetic resonance, chemical probes, radical scavengers, and different solvents to identity the reactive oxygen species (ROS). Singlet oxygen (1O2) was unveiled to be the primary ROS, which was generated by direct oxidation or recombination of superoxide ions and radicals from a metastable manganese intermediate at neutral pH. The study dedicates to the first mechanistic study into PDS activation over manganese oxides and provides a novel catalytic system for selective removal of organic contaminants in wastewater.

733 citations

Proceedings ArticleDOI
01 Nov 2016
TL;DR: The authors proposed a deep memory network for aspect level sentiment classification, which explicitly captures the importance of each context word when inferring the sentiment polarity of an aspect, such importance degree and text representation are calculated with multiple computational layers, each of which is a neural attention model over an external memory.
Abstract: We introduce a deep memory network for aspect level sentiment classification. Unlike feature-based SVM and sequential neural models such as LSTM, this approach explicitly captures the importance of each context word when inferring the sentiment polarity of an aspect. Such importance degree and text representation are calculated with multiple computational layers, each of which is a neural attention model over an external memory. Experiments on laptop and restaurant datasets demonstrate that our approach performs comparable to state-of-art feature based SVM system, and substantially better than LSTM and attention-based LSTM architectures. On both datasets we show that multiple computational layers could improve the performance. Moreover, our approach is also fast. The deep memory network with 9 layers is 15 times faster than LSTM with a CPU implementation.

731 citations

Journal ArticleDOI
TL;DR: A novel tool, purge_dups, is presented, that uses sequence similarity and read depth to automatically identify and remove both haplotigs and heterozygous overlaps and can reduce heter allele duplication and increase assembly continuity while maintaining completeness of the primary assembly.
Abstract: Motivation Rapid development in long-read sequencing and scaffolding technologies is accelerating the production of reference-quality assemblies for large eukaryotic genomes. However, haplotype divergence in regions of high heterozygosity often results in assemblers creating two copies rather than one copy of a region, leading to breaks in contiguity and compromising downstream steps such as gene annotation. Several tools have been developed to resolve this problem. However, they either focus only on removing contained duplicate regions, also known as haplotigs, or fail to use all the relevant information and hence make errors. Results Here we present a novel tool, purge_dups, that uses sequence similarity and read depth to automatically identify and remove both haplotigs and heterozygous overlaps. In comparison with current tools, we demonstrate that purge_dups can reduce heterozygous duplication and increase assembly continuity while maintaining completeness of the primary assembly. Moreover, purge_dups is fully automatic and can easily be integrated into assembly pipelines. Availability and implementation The source code is written in C and is available at https://github.com/dfguan/purge_dups. Supplementary information Supplementary data are available at Bioinformatics online.

728 citations

Journal ArticleDOI
TL;DR: In this article, the authors reviewed the existing global pumped hydro energy storage capacities, technological development, and hybrid systems and recommended the best possible options for small autonomous island grids and massive energy storage, where the energy efficiency of PHES varies in practice between 70% and 80%.
Abstract: The pumped hydro energy storage (PHES) is a well-established and commercially-acceptable technology for utility-scale electricity storage and has been used since as early as the 1890s. Hydro power is not only a renewable and sustainable energy source, but its flexibility and storage capacity also make it possible to improve grid stability and to support the deployment of other intermittent renewable energy sources such as wind and solar. As a result, a renewed interest in PHES and a demand for the rehabilitation of old small hydro power plants are emerging globally. With regard to PHES, advances in turbine design are required to enhance plant performance and flexibility and new strategies for optimizing storage capacity and for maximizing plant profitability in the deregulated energy market. In the early 2000s, this technology has again emerged as an economically and technologically acceptable option for peak load shaving and wind and solar energy storage for power quality assurance. Furthermore, renewable energy sources due to their fluctuating nature cannot maintain or regulate continuous supply of power and hence require bulk electricity storage. The present study aims at reviewing the existing global PHES capacities, technological development, and hybrid systems (wind-hydro, solar pv-hydro, and wind-pv-hydro) and recommending the best possible options. The review explores that PHES is the most suitable technology for small autonomous island grids and massive energy storage, where the energy efficiency of PHES varies in practice between 70% and 80% with some claiming up to 87%. Around the world, PHES size mostly nestles in the range of 1000–1500 MW, being as large as 2000–3000 MW. On the other hand, photovoltaic based pumped storage systems have been used for very small scale (load of few houses) only.

723 citations

Journal ArticleDOI
TL;DR: In this article, the authors reviewed the fouling control in ultra-filtration technology for drinking water production in terms of different effective pretreatments and operation methods and discussed specific mechanisms and future research required are also discussed.

719 citations


Authors

Showing all 89023 results

NameH-indexPapersCitations
Jiaguo Yu178730113300
Lei Jiang1702244135205
Gang Chen1673372149819
Xiang Zhang1541733117576
Hui-Ming Cheng147880111921
Yi Yang143245692268
Bruce E. Logan14059177351
Bin Liu138218187085
Peng Shi137137165195
Hui Li1352982105903
Lei Zhang135224099365
Jie Liu131153168891
Lei Zhang130231286950
Zhen Li127171271351
Kurunthachalam Kannan12682059886
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023383
20221,895
202110,083
20209,817
20199,659
20188,215