scholarly journals Controlled growth of 2D ultrathin Ga2O3 crystals on liquid metal

2021 ◽  
Author(s):  
Menghan Li ◽  
Lin Li ◽  
Yixuan Fan ◽  
Le Huang ◽  
Dechao Geng ◽  
...  
Keyword(s):  
Liquid Metal ◽  
Surface Chemistry ◽  
Metal Oxides ◽  
Electronic Structures ◽  
Large Scale ◽  
Controlled Growth ◽  
High Quality ◽  
The Past

2D metal oxides (2DMOs) has drawn intensive interests in the past few years owing to their rich surface chemistry and unique electronic structures. Striving for large-scale and high-quality novel 2DMOs...

Solvent-free mechanochemical synthesis of graphene oxide and Fe3O4–reduced graphene oxide nanocomposites for sensitive detection of nitrite

2015 ◽  
Vol 3 (30) ◽  
pp. 15529-15539 ◽  
Author(s):  
G. Bharath ◽  
Rajesh Madhu ◽  
Shen-Ming Chen ◽  
Vediyappan Veeramani ◽  
D. Mangalaraj ◽  
...  
Keyword(s):  
Graphene Oxide ◽  
Surface Chemistry ◽  
Reduced Graphene Oxide ◽  
Functional Properties ◽  
Mechanochemical Synthesis ◽  
Large Scale ◽  
Solvent Free ◽  
Sensitive Detection ◽  
High Quality ◽  
Reduced Graphene

Large-scale defect-free high quality graphene was synthesized by a mechanochemical process. The surface chemistry and functional properties of the Fe3O4 nanoparticles anchored on graphene were studied for the sensitive detection of nitrite from various water sources.

scholarly journals Lifelong Domain Word Embedding via Meta-Learning

2018 ◽  
Author(s):  
Hu Xu ◽  
Bing Liu ◽  
Lei Shu ◽  
Philip S. Yu
Keyword(s):  
Lifelong Learning ◽  
Large Scale ◽  
General Purpose ◽  
Word Embedding ◽  
Experimental Results ◽  
Word Embeddings ◽  
High Quality ◽  
Domain Specific ◽  
The Past ◽  
Meta Learning

Learning high-quality domain word embeddings is important for achieving good performance in many NLP tasks. General-purpose embeddings trained on large-scale corpora are often sub-optimal for domain-specific applications. However, domain-specific tasks often do not have large in-domain corpora for training high-quality domain embeddings. In this paper, we propose a novel lifelong learning setting for domain embedding. That is, when performing the new domain embedding, the system has seen many past domains, and it tries to expand the new in-domain corpus by exploiting the corpora from the past domains via meta-learning. The proposed meta-learner characterizes the similarities of the contexts of the same word in many domain corpora, which helps retrieve relevant data from the past domains to expand the new domain corpus. Experimental results show that domain embeddings produced from such a process improve the performance of the downstream tasks.

Molecular Epidemiology and Biomarkers in Etiologic Cancer Research: The New in Light of the Old

2020 ◽  
Author(s):  
Lungwani Muungo
Keyword(s):  
Gene Expression ◽  
Cancer Research ◽  
Molecular Epidemiology ◽  
Exposure Assessment ◽  
Large Scale ◽  
First Generation ◽  
Cancer Epidemiology ◽  
Policy Changes ◽  
The Past ◽  
New Generation

The purpose of this review is to evaluate progress inmolecular epidemiology over the past 24 years in canceretiology and prevention to draw lessons for futureresearch incorporating the new generation of biomarkers.Molecular epidemiology was introduced inthe study of cancer in the early 1980s, with theexpectation that it would help overcome some majorlimitations of epidemiology and facilitate cancerprevention. The expectation was that biomarkerswould improve exposure assessment, document earlychanges preceding disease, and identify subgroupsin the population with greater susceptibility to cancer,thereby increasing the ability of epidemiologic studiesto identify causes and elucidate mechanisms incarcinogenesis. The first generation of biomarkers hasindeed contributed to our understanding of riskandsusceptibility related largely to genotoxic carcinogens.Consequently, interventions and policy changes havebeen mounted to reduce riskfrom several importantenvironmental carcinogens. Several new and promisingbiomarkers are now becoming available for epidemiologicstudies, thanks to the development of highthroughputtechnologies and theoretical advances inbiology. These include toxicogenomics, alterations ingene methylation and gene expression, proteomics, andmetabonomics, which allow large-scale studies, includingdiscovery-oriented as well as hypothesis-testinginvestigations. However, most of these newer biomarkershave not been adequately validated, and theirrole in the causal paradigm is not clear. There is a needfor their systematic validation using principles andcriteria established over the past several decades inmolecular cancer epidemiology.

An Assessment of a Low-Cost Wastewater Disposal System after Twenty-Five Years of Operation

1987 ◽  
Vol 19 (5-6) ◽  
pp. 701-710 ◽  
Author(s):  
B. L. Reidy ◽  
G. W. Samson
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Wastewater Disposal ◽  
Industrial Base ◽  
Industrial Wastewaters ◽  
The Past ◽  
Gasification Process ◽  
Appropriate Treatment ◽  
Environmentally Safe ◽  
Coal Resource

A low-cost wastewater disposal system was commissioned in 1959 to treat domestic and industrial wastewaters generated in the Latrobe River valley in the province of Gippsland, within the State of Victoria, Australia (Figure 1). The Latrobe Valley is the centre for large-scale generation of electricity and for the production of pulp and paper. In addition other industries have utilized the brown coal resource of the region e.g. gasification process and char production. Consequently, industrial wastewaters have been dominant in the disposal system for the past twenty-five years. The mixed industrial-domestic wastewaters were to be transported some eighty kilometres to be treated and disposed of by irrigation to land. Several important lessons have been learnt during twenty-five years of operating this system. Firstly the composition of the mixed waste stream has varied significantly with the passage of time and the development of the industrial base in the Valley, so that what was appropriate treatment in 1959 is not necessarily acceptable in 1985. Secondly the magnitude of adverse environmental impacts engendered by this low-cost disposal procedure was not imagined when the proposal was implemented. As a consequence, clean-up procedures which could remedy the adverse effects of twenty-five years of impact are likely to be costly. The question then may be asked - when the total costs including rehabilitation are considered, is there really a low-cost solution for environmentally safe disposal of complex wastewater streams?

Recent Progress in Machine Learning-based Prediction of Peptide Activity for Drug Discovery

2019 ◽  
Vol 19 (1) ◽  
pp. 4-16 ◽  
Author(s):  
Qihui Wu ◽  
Hanzhong Ke ◽  
Dongli Li ◽  
Qi Wang ◽  
Jiansong Fang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Drug Discovery ◽  
Large Scale ◽  
Recent Progress ◽  
High Specificity ◽  
Learning Approaches ◽  
Anticancer Peptides ◽  
The Past ◽  
Traditional Approaches ◽  
Large Scale Screening

Over the past decades, peptide as a therapeutic candidate has received increasing attention in drug discovery, especially for antimicrobial peptides (AMPs), anticancer peptides (ACPs) and antiinflammatory peptides (AIPs). It is considered that the peptides can regulate various complex diseases which are previously untouchable. In recent years, the critical problem of antimicrobial resistance drives the pharmaceutical industry to look for new therapeutic agents. Compared to organic small drugs, peptide- based therapy exhibits high specificity and minimal toxicity. Thus, peptides are widely recruited in the design and discovery of new potent drugs. Currently, large-scale screening of peptide activity with traditional approaches is costly, time-consuming and labor-intensive. Hence, in silico methods, mainly machine learning approaches, for their accuracy and effectiveness, have been introduced to predict the peptide activity. In this review, we document the recent progress in machine learning-based prediction of peptides which will be of great benefit to the discovery of potential active AMPs, ACPs and AIPs.

Mapping Power

2018 ◽  
Keyword(s):  
Political Economy ◽  
Comprehensive Analysis ◽  
Electricity Sector ◽  
Operational Performance ◽  
The Political ◽  
Government Reform ◽  
High Quality ◽  
The Past ◽  
Economic Forces ◽  
Political Economy Analysis

Electricity is critical to enabling India’s economic growth and providing a better future for its citizens. In spite of several decades of reform, the Indian electricity sector is unable to provide high-quality and affordable electricity for all, and grapples with the challenge of poor financial and operational performance. To understand why, Mapping Power provides the most comprehensive analysis of the political economy of electricity in India’s states. With chapters on fifteen states by scholars of state politics and electricity, this volume maps the political and economic forces that constrain and shape decisions in electricity distribute on. Contrary to conventional wisdom, it concludes that attempts to depoliticize the sector are misplaced and could worsen outcomes. Instead, it suggests that a historically grounded political economy analysis helps understand the past and devise reforms to simultaneously improve sectoral outcomes and generate political rewards. These arguments have implications for the challenges facing India’s electricity future, including providing electricity to all, implementing government reform schemes, and successfully managing the rise of renewable energy.

Evaluating Qualitative Research

2017 ◽  
Author(s):  
Jeasik Cho
Keyword(s):  
Qualitative Research ◽  
Large Scale ◽  
Academic Research ◽  
Research Community ◽  
Assessment Tools ◽  
Journal Articles ◽  
Journal Editors ◽  
The Past ◽  
Grant Proposals

This book provides the qualitative research community with some insight on how to evaluate the quality of qualitative research. This topic has gained little attention during the past few decades. We, qualitative researchers, read journal articles, serve on masters’ and doctoral committees, and also make decisions on whether conference proposals, manuscripts, or large-scale grant proposals should be accepted or rejected. It is assumed that various perspectives or criteria, depending on various paradigms, theories, or fields of discipline, have been used in assessing the quality of qualitative research. Nonetheless, until now, no textbook has been specifically devoted to exploring theories, practices, and reflections associated with the evaluation of qualitative research. This book constructs a typology of evaluating qualitative research, examines actual information from websites and qualitative journal editors, and reflects on some challenges that are currently encountered by the qualitative research community. Many different kinds of journals’ review guidelines and available assessment tools are collected and analyzed. Consequently, core criteria that stand out among these evaluation tools are presented. Readers are invited to join the author to confidently proclaim: “Fortunately, there are commonly agreed, bold standards for evaluating the goodness of qualitative research in the academic research community. These standards are a part of what is generally called ‘scientific research.’ ”

scholarly journals Global climatology and trends in convective environments from ERA5 and rawinsonde data

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Mattia Marchio ◽  
Harold E. Brooks
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Convective Available Potential Energy ◽  
Global Climate Models ◽  
Convective Precipitation ◽  
The Past ◽  
The Tropics ◽  
Rawinsonde Data

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.

Tiered Sampling

2021 ◽  
Vol 15 (5) ◽  
pp. 1-52
Author(s):  
Lorenzo De Stefani ◽  
Erisa Terolli ◽  
Eli Upfal
Keyword(s):  
Large Scale ◽  
Analysis Of Algorithms ◽  
Base Layer ◽  
Single Edge ◽  
Real World Data ◽  
High Quality ◽  
Large Graphs ◽  
Massive Graphs ◽  
Variance Estimate ◽  
Low Probability

We introduce Tiered Sampling , a novel technique for estimating the count of sparse motifs in massive graphs whose edges are observed in a stream. Our technique requires only a single pass on the data and uses a memory of fixed size M , which can be magnitudes smaller than the number of edges. Our methods address the challenging task of counting sparse motifs—sub-graph patterns—that have a low probability of appearing in a sample of M edges in the graph, which is the maximum amount of data available to the algorithms in each step. To obtain an unbiased and low variance estimate of the count, we partition the available memory into tiers (layers) of reservoir samples. While the base layer is a standard reservoir sample of edges, other layers are reservoir samples of sub-structures of the desired motif. By storing more frequent sub-structures of the motif, we increase the probability of detecting an occurrence of the sparse motif we are counting, thus decreasing the variance and error of the estimate. While we focus on the designing and analysis of algorithms for counting 4-cliques, we present a method which allows generalizing Tiered Sampling to obtain high-quality estimates for the number of occurrence of any sub-graph of interest, while reducing the analysis effort due to specific properties of the pattern of interest. We present a complete analytical analysis and extensive experimental evaluation of our proposed method using both synthetic and real-world data. Our results demonstrate the advantage of our method in obtaining high-quality approximations for the number of 4 and 5-cliques for large graphs using a very limited amount of memory, significantly outperforming the single edge sample approach for counting sparse motifs in large scale graphs.

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