scholarly journals Estimating the Methane Potential of Energy Crops: An Overview on Types of Data Sources and Their Limitations

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1565
Author(s):  
Yue Zhang ◽  
Sigrid Kusch-Brandt ◽  
Andrew M. Salter ◽  
Sonia Heaven
Keyword(s):  
Crop Residues ◽  
Energy Crops ◽  
Data Sources ◽  
Methane Yield ◽  
Testing Methods ◽  
Crop Type ◽  
Risk Approach ◽  
Biogas Plants ◽  
Methane Potential ◽  
Data Source

As the anaerobic digestion of energy crops and crop residues becomes more widely applied for bioenergy production, planners and operators of biogas plants, and farmers who consider growing such crops, have a need for information on potential biogas and methane yields. A rich body of literature reports methane yields for a variety of such materials. These data have been obtained with different testing methods. This work elaborates an overview on the types of data source available and the methods that are commonly applied to determine the methane yield of an agricultural biomass, with a focus on European crops. Limitations regarding the transferability and generalisation of data are explored, and crop methane values presented across the literature are compared. Large variations were found for reported values, which can only partially be explained by the methods applied. Most notably, the intra-crop variation of methane yield (reported values for a single crop type) was higher than the inter-crop variation (variation between different crops). The pronounced differences in reported methane yields indicate that relying on results from individual assays of candidate materials is a high-risk approach for planning biogas operations, and the ranges of values such as those presented here are essential to provide a robust basis for estimation.

scholarly journals Biomethane Potential Test: Influence of Inoculum and the Digestion System

2020 ◽  
Vol 10 (7) ◽  
pp. 2589 ◽  
Author(s):  
Benedikt Hülsemann ◽  
Lijun Zhou ◽  
Wolfgang Merkle ◽  
Juli Hassa ◽  
Joachim Müller ◽  
...  
Keyword(s):  
Laboratory Tests ◽  
Methane Yield ◽  
Biochemical Methane Potential ◽  
Measurement Variability ◽  
Biogas Yield ◽  
Yield Test ◽  
Biogas Plants ◽  
Methane Potential ◽  
Bmp Test

High precision of measurement of methane potential is important for the economic operation of biogas plants in the future. The biochemical methane potential (BMP) test based on the VDI 4630 protocol is the state-of-the-art method to determine the methane potential in Germany. The coefficient of variation (CV) of methane yield was >10% in several previous inter-laboratory tests. The aim of this work was to investigate the effects of inoculum and the digestion system on the measurement variability. Methane yield and methane percentage of five substrates were investigated in a Hohenheim biogas yield test (D-HBT) by using five inocula, which were used several times in inter- laboratory tests. The same substrates and inocula were also tested in other digestion systems. To control the quality of the inocula, the effect of adding trace elements (TE) and the microbial community was investigated. Adding TE had no influence for the selected, well- supplied inocula and the community composition depended on the source of the inocula. The CV of the specific methane yield was <4.8% by using different inocula in one D-HBT (D-HBT1) and <12.8% by using different digestion systems compared to D-HBT1. Incubation time between 7 and 14 days resulted in a deviation in CV of <4.8%.

scholarly journals A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration

Epidemiologia ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 315-324
Author(s):  
Juan M. Banda ◽  
Ramya Tekumalla ◽  
Guanyu Wang ◽  
Jingyuan Yu ◽  
Tuo Liu ◽  
...  
Keyword(s):  
Large Scale ◽  
Social Dynamics ◽  
Additional Data ◽  
Open Data ◽  
Data Sources ◽  
Research Projects ◽  
Research Groups ◽  
The World ◽  
Data Source

As the COVID-19 pandemic continues to spread worldwide, an unprecedented amount of open data is being generated for medical, genetics, and epidemiological research. The unparalleled rate at which many research groups around the world are releasing data and publications on the ongoing pandemic is allowing other scientists to learn from local experiences and data generated on the front lines of the COVID-19 pandemic. However, there is a need to integrate additional data sources that map and measure the role of social dynamics of such a unique worldwide event in biomedical, biological, and epidemiological analyses. For this purpose, we present a large-scale curated dataset of over 1.12 billion tweets, growing daily, related to COVID-19 chatter generated from 1 January 2020 to 27 June 2021 at the time of writing. This data source provides a freely available additional data source for researchers worldwide to conduct a wide and diverse number of research projects, such as epidemiological analyses, emotional and mental responses to social distancing measures, the identification of sources of misinformation, stratified measurement of sentiment towards the pandemic in near real time, among many others.

Mapping the United Nations Fundamental Principles of Official Statistics against new and big data sources

2021 ◽  
Vol 37 (1) ◽  
pp. 161-169
Author(s):  
Dominik Rozkrut ◽  
Olga Świerkot-Strużewska ◽  
Gemma Van Halderen
Keyword(s):  
Big Data ◽  
Public Information ◽  
Fundamental Principle ◽  
Data Sources ◽  
Official Statistics ◽  
Development Agenda ◽  
Data Gaps ◽  
Data Source ◽  
Exciting Time ◽  
Statistical Systems

Never has there been a more exciting time to be an official statistician. The data revolution is responding to the demands of the CoVID-19 pandemic and a complex sustainable development agenda to improve how data is produced and used, to close data gaps to prevent discrimination, to build capacity and data literacy, to modernize data collection systems and to liberate data to promote transparency and accountability. But can all data be liberated in the production and communication of official statistics? This paper explores the UN Fundamental Principles of Official Statistics in the context of eight new and big data sources. The paper concludes each data source can be used for the production of official statistics in adherence with the Fundamental Principles and argues these data sources should be used if National Statistical Systems are to adhere to the first Fundamental Principle of compiling and making available official statistics that honor citizen’s entitlement to public information.

Event detection of different English data sources based on transfer learning

2021 ◽  
pp. 1-11
Author(s):  
Yanan Huang ◽  
Yuji Miao ◽  
Zhenjing Da
Keyword(s):  
Transfer Learning ◽  
Event Detection ◽  
Visual Analysis ◽  
Learning Algorithm ◽  
Data Sources ◽  
Data Set ◽  
Data Source ◽  
Single Data Source ◽  
The Difference ◽  
Single Data

The methods of multi-modal English event detection under a single data source and isomorphic event detection of different English data sources based on transfer learning still need to be improved. In order to improve the efficiency of English and data source time detection, based on the transfer learning algorithm, this paper proposes multi-modal event detection under a single data source and isomorphic event detection based on transfer learning for different data sources. Moreover, by stacking multiple classification models, this paper makes each feature merge with each other, and conducts confrontation training through the difference between the two classifiers to further make the distribution of different source data similar. In addition, in order to verify the algorithm proposed in this paper, a multi-source English event detection data set is collected through a data collection method. Finally, this paper uses the data set to verify the method proposed in this paper and compare it with the current most mainstream transfer learning methods. Through experimental analysis, convergence analysis, visual analysis and parameter evaluation, the effectiveness of the algorithm proposed in this paper is demonstrated.

Determination of methane yield of cellulose using different experimental setups

2014 ◽  
Vol 70 (4) ◽  
pp. 599-604 ◽  
Author(s):  
Bing Wang ◽  
Ivo Achu Nges ◽  
Mihaela Nistor ◽  
Jing Liu
Keyword(s):  
Water Column ◽  
Test System ◽  
Methane Yield ◽  
Biochemical Methane Potential ◽  
Methane Potential ◽  
Bmp Test ◽  
Potential Test

In this work, biochemical methane potential (BMP) tests with cellulose as a model substrate were performed with the aid of three manually operated or conventional experimental setups (based on manometer, water column and gas bag) and one automated apparatus specially designed for analysis of BMP. The methane yields were 340 ± 18, 354 ± 13, 345 ± 15 and 366 ± 5 ml CH4/g VS obtained from experimental setups with manometer, water column, gas bag, and automatic methane potential test system, which corresponded to a biodegradability of 82, 85, 83 and 88% respectively. The results demonstrated that the methane yields of cellulose obtained from conventional and automatic experimental setups were comparable; however, the methane yield obtained from the automated apparatus showed greater precision. Moreover, conventional setups for the BMP test were more time- and labour-intensive compared with the automated apparatus.

EdgeDIPN

2020 ◽  
Vol 14 (3) ◽  
pp. 320-328
Author(s):  
Long Guo ◽  
Lifeng Hua ◽  
Rongfei Jia ◽  
Fei Fang ◽  
Binqiang Zhao ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Attention Mechanism ◽  
Data Sources ◽  
User Intent ◽  
Multiple User ◽  
Shopping Experience ◽  
Data Source ◽  
Intent Prediction ◽  
The Right

With the rapid growth of e-commerce in recent years, e-commerce platforms are becoming a primary place for people to find, compare and ultimately purchase products. To improve online shopping experience for consumers and increase sales for sellers, it is important to understand user intent accurately and be notified of its change timely. In this way, the right information could be offered to the right person at the right time. To achieve this goal, we propose a unified deep intent prediction network, named EdgeDIPN, which is deployed at the edge, i.e., mobile device, and able to monitor multiple user intent with different granularity simultaneously in real-time. We propose to train EdgeDIPN with multi-task learning, by which EdgeDIPN can share representations between different tasks for better performance and saving edge resources in the meantime. In particular, we propose a novel task-specific attention mechanism which enables different tasks to pick out the most relevant features from different data sources. To extract the shared representations more effectively, we utilize two kinds of attention mechanisms, where the multi-level attention mechanism tries to identify the important actions within each data source and the inter-view attention mechanism learns the interactions between different data sources. In the experiments conducted on a large-scale industrial dataset, EdgeDIPN significantly outperforms the baseline solutions. Moreover, EdgeDIPN has been deployed in the operational system of Alibaba. Online A/B testing results in several business scenarios reveal the potential of monitoring user intent in real-time. To the best of our knowledge, EdgeDIPN is the first full-fledged real-time user intent understanding center deployed at the edge and serving hundreds of millions of users in a large-scale e-commerce platform.

Operational results of an agricultural biogas plant equipped with modern instrumentation and automation

2008 ◽  
Vol 57 (6) ◽  
pp. 803-808 ◽  
Author(s):  
J. Wiese ◽  
O. Kujawski
Keyword(s):  
Energy Crops ◽  
Full Scale ◽  
Biogas Plant ◽  
Biogas Plants ◽  
Technical Details ◽  
Modern Instrumentation

Agricultural biogas plants based on energy crops gain more and more importance because of numerous energetic, environmental and agricultural benefits. In contrast to older biogas plants, the newest generation of biogas plants is equipped with modern ICA equipment and reliable machines/engines. In this paper, the authors present technical details and operational results of a modern full-scale agricultural biogas plant using energy crops.

scholarly journals Comparison of the Effect of Perennial Energy Crops and Arable Crops on Earthworm Populations

Agronomy ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 675 ◽  
Author(s):  
Feledyn-Szewczyk ◽  
Radzikowski ◽  
Stalenga ◽  
Matyka
Keyword(s):  
Winter Wheat ◽  
Crop Production ◽  
Crop Residues ◽  
Production Systems ◽  
Arable Land ◽  
Energy Crops ◽  
Integrated System ◽  
Species Number ◽  
Organic System ◽  
Perennial Energy Crops

The purpose of the study was to compare earthworm communities under winter wheat in different crop production systems on arable land—organic (ORG), integrated (INT), conventional (CON), monoculture (MON)—and under perennial crops cultivated for energy purposes—willow (WIL), Virginia mallow (VIR), and miscanthus (MIS). Earthworm abundance, biomass, and species composition were assessed each spring and autumn in the years 2014–2016 using the method of soil blocks. The mean species number of earthworms was ordered in the following way: ORG > VIR > WIL > CON > INT > MIS > MON. Mean abundance of earthworms decreased in the following order: ORG > WIL > CON > VIR > INT > MIS > MON. There were significantly more species under winter wheat cultivated organically than under the integrated system (p = 0.045), miscanthus (p = 0.039), and wheat monoculture (p = 0.002). Earthworm abundance was significantly higher in the organic system compared to wheat monoculture (p = 0.001) and to miscanthus (p = 0.008). Among the tested energy crops, Virginia mallow created the best habitat for species richness and biomass due to the high amount of crop residues suitable for earthworms and was similar to the organic system. Differences in the composition of earthworm species in the soil under the compared agricultural systems were proven. Energy crops, except miscanthus, have been found to increase earthworm diversity, as they are good crops for landscape diversification.

scholarly journals Characterization and selection of Japanese electronic health record databases used as data sources for non-interventional observational studies

2021 ◽  
Author(s):  
Yumi Wakabayashi ◽  
Masamitsu Eitoku ◽  
Narufumi Suganuma
Keyword(s):  
Electronic Health Record ◽  
Observational Studies ◽  
Large Scale ◽  
Data Sources ◽  
Flow Diagram ◽  
Health Record ◽  
Medical Institutions ◽  
Data Source ◽  
Electronic Health ◽  
Using Data

Abstract Background Interventional studies are the fundamental method for obtaining answers to clinical question. However, these studies are sometimes difficult to conduct because of insufficient financial or human resources or the rarity of the disease in question. One means of addressing these issues is to conduct a non-interventional observational study using electronic health record (EHR) databases as the data source, although how best to evaluate the suitability of an EHR database when planning a study remains to be clarified. The aim of the present study is to identify and characterize the data sources that have been used for conducting non-interventional observational studies in Japan and propose a flow diagram to help researchers determine the most appropriate EHR database for their study goals. Methods We compiled a list of published articles reporting observational studies conducted in Japan by searching PubMed for relevant articles published in the last 3 years and by searching database providers’ publication lists related to studies using their databases. For each article, we reviewed the abstract and/or full text to obtain information about data source, target disease or therapeutic area, number of patients, and study design (prospective or retrospective). We then characterized the identified EHR databases. Results In Japan, non-interventional observational studies have been mostly conducted using data stored locally at individual medical institutions (713/1463) or collected from several collaborating medical institutions (351/1463). Whereas the studies conducted with large-scale integrated databases (195/1463) were mostly retrospective (68.2%), 27.2% of the single-center studies, 46.2% of the multi-center studies, and 74.4% of the post-marketing surveillance studies, identified in the present study, were conducted prospectively. Conclusions Our analysis revealed that the non-interventional observational studies were conducted using data stored local at individual medical institutions or collected from collaborating medical institutions in Japan. Disease registries, disease databases, and large-scale databases would enable researchers to conduct studies with large sample sizes to provide robust data from which strong inferences could be drawn. Using our flow diagram, researchers planning non-interventional observational studies should consider the strengths and limitations of each available database and choose the most appropriate one for their study goals. Trial registration Not applicable.

scholarly journals Modelling Representative Population Mobility for COVID-19 Spatial Transmission in South Africa

2021 ◽  
Vol 4 ◽  
Author(s):  
A. Potgieter ◽  
I. N. Fabris-Rotelli ◽  
Z. Kimmie ◽  
N. Dudeni-Tlhone ◽  
J. P. Holloway ◽  
...  
Keyword(s):  
Human Mobility ◽  
Data Sources ◽  
Population Mobility ◽  
Mobility Patterns ◽  
Mobility Data ◽  
The World ◽  
Spatial Weight ◽  
Data Source ◽  
Reduced Mobility ◽  
Spatial Transmission

The COVID-19 pandemic starting in the first half of 2020 has changed the lives of everyone across the world. Reduced mobility was essential due to it being the largest impact possible against the spread of the little understood SARS-CoV-2 virus. To understand the spread, a comprehension of human mobility patterns is needed. The use of mobility data in modelling is thus essential to capture the intrinsic spread through the population. It is necessary to determine to what extent mobility data sources convey the same message of mobility within a region. This paper compares different mobility data sources by constructing spatial weight matrices at a variety of spatial resolutions and further compares the results through hierarchical clustering. We consider four methods for constructing spatial weight matrices representing mobility between spatial units, taking into account distance between spatial units as well as spatial covariates. This provides insight for the user into which data provides what type of information and in what situations a particular data source is most useful.

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