Institution
Guangzhou University
Education•Guangzhou, China•
About: Guangzhou University is a education organization based out in Guangzhou, China. It is known for research contribution in the topics: Cloud computing & Adsorption. The organization has 13274 authors who have published 14154 publications receiving 167042 citations. The organization is also known as: Guǎngzhōu dàxué.
Topics: Cloud computing, Adsorption, Population, Encryption, Catalysis
Papers published on a yearly basis
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Daniel J. Klionsky1, Fábio Camargo Abdalla2, Hagai Abeliovich3, Robert T. Abraham4 +1284 more•Institutions (463)
TL;DR: These guidelines are presented for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
4,316 citations
TL;DR: Protein Analysis Through Evolutionary Relationships is a resource for the evolutionary and functional classification of genes from organisms across the tree of life, and an entirely new PANTHER GO-slim is developed, containing over four times as many Gene Ontology terms as the previous GO- slim.
Abstract: PANTHER (Protein Analysis Through Evolutionary Relationships, http://pantherdb.org) is a resource for the evolutionary and functional classification of genes from organisms across the tree of life. We report the improvements we have made to the resource during the past two years. For evolutionary classifications, we have added more prokaryotic and plant genomes to the phylogenetic gene trees, expanding the representation of gene evolution in these lineages. We have refined many protein family boundaries, and have aligned PANTHER with the MEROPS resource for protease and protease inhibitor families. For functional classifications, we have developed an entirely new PANTHER GO-slim, containing over four times as many Gene Ontology terms as our previous GO-slim, as well as curated associations of genes to these terms. Lastly, we have made substantial improvements to the enrichment analysis tools available on the PANTHER website: users can now analyze over 900 different genomes, using updated statistical tests with false discovery rate corrections for multiple testing. The overrepresentation test is also available as a web service, for easy addition to third-party sites.
2,162 citations
TL;DR: To achieve efficient data dynamics, the existing proof of storage models are improved by manipulating the classic Merkle Hash Tree construction for block tag authentication, and an elegant verification scheme is constructed for the seamless integration of these two salient features in the protocol design.
Abstract: Cloud Computing has been envisioned as the next-generation architecture of IT Enterprise. It moves the application software and databases to the centralized large data centers, where the management of the data and services may not be fully trustworthy. This unique paradigm brings about many new security challenges, which have not been well understood. This work studies the problem of ensuring the integrity of data storage in Cloud Computing. In particular, we consider the task of allowing a third party auditor (TPA), on behalf of the cloud client, to verify the integrity of the dynamic data stored in the cloud. The introduction of TPA eliminates the involvement of the client through the auditing of whether his data stored in the cloud are indeed intact, which can be important in achieving economies of scale for Cloud Computing. The support for data dynamics via the most general forms of data operation, such as block modification, insertion, and deletion, is also a significant step toward practicality, since services in Cloud Computing are not limited to archive or backup data only. While prior works on ensuring remote data integrity often lacks the support of either public auditability or dynamic data operations, this paper achieves both. We first identify the difficulties and potential security problems of direct extensions with fully dynamic data updates from prior works and then show how to construct an elegant verification scheme for the seamless integration of these two salient features in our protocol design. In particular, to achieve efficient data dynamics, we improve the existing proof of storage models by manipulating the classic Merkle Hash Tree construction for block tag authentication. To support efficient handling of multiple auditing tasks, we further explore the technique of bilinear aggregate signature to extend our main result into a multiuser setting, where TPA can perform multiple auditing tasks simultaneously. Extensive security and performance analysis show that the proposed schemes are highly efficient and provably secure.
1,422 citations
TL;DR: A future land use simulation (FLUS) model that explicitly simulates the long-term spatial trajectories of multiple LUCCs, and the simulation accuracy is higher than other well-accepted models, such as CLUE-S and CA models.
Abstract: Land use and land cover change (LUCC) simulation models are effective and reproducible tools for analyzing both the causes and consequences of future landscape dynamics under various scenarios. Current simulation models primarily focus on the evolution of specific land use types under the influence of human activities, but they rarely consider background climatic effects. However, these background climate changes significantly affect the landscape dynamics and should be incorporated into long-term LUCC simulations under various human-climate-included scenarios. In this paper, we propose a future land use simulation (FLUS) model that explicitly simulates the long-term spatial trajectories of multiple LUCCs. The top-down system dynamics and bottom-up cellular automata were interactively coupled during the projection period, which improved the model’s ability to accurately simulate future land use patterns. A self-adaptive inertia and competition mechanism was developed within the CA model to process the complex competitions and interactions between the different land use types. The proposed model was applied to an LUCC simulation in China from 2000 to 2010. The results show promising grid-to-grid agreement compared to actual land use, and the simulation accuracy is higher than other well-accepted models, such as CLUE-S and CA models. The model was further applied to the simulation of four scenarios from 2010 to 2050 that depict different development strategies by considering various socio-economic and natural climatic factors. The simulation results and findings demonstrate that the proposed model is effective for future LUCC simulation under variously designed scenarios. FLUS is available for free download at http://www.geosimulation.cn/FLUS.html .
773 citations
TL;DR: A variety of strategies such as structural tuning, composition control, doping, hybrid structures, heterostructures, defect control, temperature effects and porosity effects on metal sulfide nanocrystals are discussed and how they are exploited to enhance performance and develop future energy materials.
Abstract: In recent years, nanocrystals of metal sulfide materials have attracted scientific research interest for renewable energy applications due to the abundant choice of materials with easily tunable electronic, optical, physical and chemical properties. Metal sulfides are semiconducting compounds where sulfur is an anion associated with a metal cation; and the metal ions may be in mono-, bi- or multi-form. The diverse range of available metal sulfide materials offers a unique platform to construct a large number of potential materials that demonstrate exotic chemical, physical and electronic phenomena and novel functional properties and applications. To fully exploit the potential of these fascinating materials, scalable methods for the preparation of low-cost metal sulfides, heterostructures, and hybrids of high quality must be developed. This comprehensive review indicates approaches for the controlled fabrication of metal sulfides and subsequently delivers an overview of recent progress in tuning the chemical, physical, optical and nano- and micro-structural properties of metal sulfide nanocrystals using a range of material fabrication methods. For hydrogen energy production, three major approaches are discussed in detail: electrocatalytic hydrogen generation, powder photocatalytic hydrogen generation and photoelectrochemical water splitting. A variety of strategies such as structural tuning, composition control, doping, hybrid structures, heterostructures, defect control, temperature effects and porosity effects on metal sulfide nanocrystals are discussed and how they are exploited to enhance performance and develop future energy materials. From this literature survey, energy conversion currently relies on a limited range of metal sulfides and their composites, and several metal sulfides are immature in terms of their dissolution, photocorrosion and long-term durability in electrolytes during water splitting. Future research directions for innovative metal sulfides should be closely allied to energy and environmental issues, along with their advanced characterization, and developing new classes of metal sulfide materials with well-defined fabrication methods.
685 citations
Authors
Showing all 13422 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yang Yang | 164 | 2704 | 144071 |
Denis Bastieri | 135 | 473 | 62620 |
Haiyan Wang | 119 | 1674 | 86091 |
Jian Liu | 117 | 2090 | 73156 |
Wei Zhang | 104 | 2911 | 64923 |
Hong Liu | 100 | 1905 | 57561 |
Wei Wang | 95 | 3544 | 59660 |
Xihong Lu | 88 | 337 | 29367 |
Yong Xu | 88 | 1391 | 39268 |
Peng Cheng | 84 | 749 | 27599 |
Lin Liu | 78 | 937 | 24389 |
Wei Zhang | 76 | 1932 | 34966 |
Lei Guo | 75 | 1589 | 27943 |
Hong Hao | 68 | 795 | 19057 |
Jing Li | 68 | 982 | 18991 |