Impact of input data resolution and extent of harvested areas on crop yield estimates in large-scale agricultural modeling for maize in the USA

Abstract Can corrective information change citizens’ misperceptions about immigrants and subsequently lead to favorable immigration opinions? While prior studies from the USA document how corrections about the size of minority populations fail to change citizens’ immigration-related opinions, they do not examine how other facts that speak to immigrants’ cultural or economic dependency rates can influence immigration policy opinions. To extend earlier work, we conducted a large-scale survey experiment fielded to a nationally representative sample of Danes. We randomly expose participants to information about non-Western immigrants’ (1) welfare dependency rate, (2) crime rate, and (3) proportion of the total population. We find that participants update their factual beliefs in light of correct information, but reinterpret the information in a highly selective fashion, ultimately failing to change their policy preferences.

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Are Climate Factors Driving the Contemporary Wildfire Occurrence in China?

Forests ◽

10.3390/f12040392 ◽

2021 ◽

Vol 12 (4) ◽

pp. 392

Author(s):

Zige Lan ◽

Zhangwen Su ◽

Meng Guo ◽

Ernesto C. Alvarado ◽

Futao Guo ◽

...

Keyword(s):

Human Factors ◽

Large Scale ◽

Fire Occurrence ◽

Climate Factors ◽

Wildfire Occurrence ◽

Prediction And Prevention ◽

Data Resolution ◽

Main Driver ◽

Landscape Factors ◽

Modelling Approach

Understanding the drivers of wildfire occurrence is of great value for fire prevention and management, but due to the variation in research methods, data sources, and data resolution of those studies, it is challenging to conduct a large-scale comprehensive comparative qualitative analysis on the topic. China has diverse vegetation types and topography, and has undergone rapid economic and social development, but experiences a high frequency of wildfires, making it one of the ideal locations for wildfire research. We applied the Random Forests modelling approach to explore the main types of wildfire drivers (climate factors, landscape factors and human factors) in three high wildfire density regions (Northeast (NE), Southwest (SW), and Southeast (SE)) of China. The results indicate that climate factors were the main driver of wildfire occurrence in the three regions. Precipitation and temperature significantly impacted the fire occurrence in the three regions due to the direct influence on the moisture content of forest fuel. However, wind speed had important influence on fire occurrence in the SE and SW. The explanation power of the landscape and human factors varied significantly between regions. Human factors explained 40% of the fire occurrence in the SE but only explained less than 10% of the fire occurrence in the NE and SW. The density of roads was identified as the most important human factor driving fires in all three regions, but railway density had more explanation power on fire occurrence in the SE than in the other regions. The landscape factors showed nearly no influence on fire occurrence in the NE but explained 46.4% and 20.6% in the SE and SW regions, respectively. Amongst landscape factors, elevation had the highest average explanation power on fire occurrence in the three regions, particularly in the SW. In conclusion, this study provides useful insights into targeted fire prediction and prevention, which should be more precise and effective under climate change and socio-economic development.

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The utility of self-rated health in population surveys: the role of bodyweight

Population Health Metrics ◽

10.1186/s12963-021-00255-2 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Robert Bozick

Keyword(s):

Treatment Group ◽

Large Scale ◽

Well Being ◽

Control Group ◽

Self Rated Health ◽

Risk Of Mortality ◽

Highly Sensitive ◽

The Usa ◽

Group Members ◽

Nationally Representative

Abstract Background Self-rated health (SRH) is one of the most commonly used summary measures of overall health and well-being available to population scientists due to its ease of administration in large-scale surveys and to its efficacy in predicting mortality. This paper assesses the extent to which SRH is affected by its placement before or after questions about bodyweight on a survey, and whether differences in placement on the questionnaire affects SRH’s predictive validity. Methods I assessed the validity of SRH in predicting the risk of mortality by comparing outcomes of sample members who were asked to rate their health before reporting on their bodyweight (the control group) and sample members who were asked to rate their health after reporting on their bodyweight (the treatment group). Both the control and treatment group were randomly assigned via an experiment administered as a module in a nationally representative sample of adults in the USA in 2019 (N = 2523). Results The odds of reporting a more favorable appraisal of health are 30% lower for sample members who were in the treatment group when compared with the control group. Additionally, the SRH of treatment group members is significantly associated with their risk of mortality, while the SRH of control group members is not. Conclusion The findings from this study suggest that for researchers to maximize the utility of SRH, closer attention needs to be paid to the context of the survey within which it asked. SRH is highly sensitive to the questions that precede it, and this sensitivity may in turn mischaracterize the true health of the population that the survey is intending to measure.

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Untapped research opportunities in China: promising future avenues and potential concerns for aging companion animals

GeroScience ◽

10.1007/s11357-021-00433-y ◽

2021 ◽

Author(s):

Jessica M. Hoffman ◽

Shanshan Song ◽

Katharina Brugger ◽

Teresa G. Valencak

Keyword(s):

Large Scale ◽

Companion Animals ◽

Companion Animal ◽

The European Union ◽

Pet Ownership ◽

Ethical Considerations ◽

Aging Research ◽

Agricultural Animal ◽

The Usa ◽

Laboratory Models

AbstractCompanion animals have recently been proposed as ideal translational models of human aging due to their shared susceptibility for certain diseases, similar environments, and sophisticated veterinary medicine diagnostics, all of which are not possible in rodent laboratory models. Here, we introduce and propose the study of companion animals in China as a largely untapped resource in academic and veterinary aging research. Pet ownership rates along with economic gains in the pet industry have skyrocketed over the last decade in China. Yet, the majority of research institutions still focus on agricultural animal research, not companion animals. In this perspective, we compare available pet ownership rates between the USA, the European Union, and China before focusing on the potential of companion animal aging research in China. In addition, we highlight some ethical considerations that must be addressed before large-scale companion animal aging research can be completed.

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Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques

Electronics ◽

10.3390/electronics10141648 ◽

2021 ◽

Vol 10 (14) ◽

pp. 1648

Author(s):

Marinko Barukčić ◽

Toni Varga ◽

Vedrana Jerković Jerković Štil ◽

Tin Benšić

Keyword(s):

Power System ◽

Power Management ◽

Computational Intelligence ◽

Input Data ◽

Optimization Problem ◽

Optimal Allocation ◽

Distribution Networks ◽

Distributed Generations ◽

Data Resolution ◽

The Impact

The paper researches the impact of the input data resolution on the solution of optimal allocation and power management of controllable and non-controllable renewable energy sources distributed generation in the distribution power system. Computational intelligence techniques and co-simulation approach are used, aiming at more realistic system modeling and solving the complex optimization problem. The optimization problem considers the optimal allocation of all distributed generations and the optimal power control of controllable distributed generations. The co-simulation setup employs a tool for power system analysis and a metaheuristic optimizer to solve the optimization problem. Three different resolutions of input data (generation and load profiles) are used: hourly, daily, and monthly averages over one year. An artificial neural network is used to estimate the optimal output of controllable distributed generations and thus significantly decrease the dimensionality of the optimization problem. The proposed procedure is applied on a 13 node test feeder proposed by the Institute of Electrical and Electronics Engineers. The obtained results show a huge impact of the input data resolution on the optimal allocation of distributed generations. Applying the proposed approach, the energy losses are decreased by over 50–70% by the optimal allocation and control of distributed generations depending on the tested network.

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Solar Thermochemical Hydrogen Production in the USA

Sustainability ◽

10.3390/su13147804 ◽

2021 ◽

Vol 13 (14) ◽

pp. 7804

Author(s):

Christoph Falter ◽

Andreas Sizmann

Keyword(s):

Hydrogen Production ◽

Large Scale ◽

Low Cost ◽

The United States ◽

Solar Irradiation ◽

Transport Sector ◽

Fossil Energy ◽

The Us ◽

The Usa ◽

Solar Thermochemical

Hydrogen produced from renewable energy has the potential to decarbonize parts of the transport sector and many other industries. For a sustainable replacement of fossil energy carriers, both the environmental and economic performance of its production are important. Here, the solar thermochemical hydrogen pathway is characterized with a techno-economic and life-cycle analysis. Assuming a further increase of conversion efficiency and a reduction of investment costs, it is found that hydrogen can be produced in the United States of America at costs of 2.1–3.2 EUR/kg (2.4–3.6 USD/kg) at specific greenhouse gas emissions of 1.4 kg CO2-eq/kg. A geographical potential analysis shows that a maximum of 8.4 × 1011 kg per year can be produced, which corresponds to about twelve times the current global and about 80 times the current US hydrogen production. The best locations are found in the Southwest of the US, which have a high solar irradiation and short distances to the sea, which is beneficial for access to desalinated water. Unlike for petrochemical products, the transport of hydrogen could potentially present an obstacle in terms of cost and emissions under unfavorable circumstances. Given a large-scale deployment, low-cost transport seems, however, feasible.

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Events in Northern Africa and Middle East: Causes and Consequences

World Economy and International Relations ◽

10.20542/0131-2227-2011-7-11-25 ◽

2011 ◽

pp. 11-25

Author(s):

I. Labinskaya

Keyword(s):

Middle East ◽

North Africa ◽

Large Scale ◽

Arab Countries ◽

Northern Africa ◽

External Factors ◽

Wide Range ◽

The Usa ◽

Oriental Studies

Political developments in North Africa and the Middle East that have begun in January 2011 are gaining strength and involve an increasing number of Arab countries. The participants of the Roundtable – experts from IMEMO, Institute of Oriental Studies (RAS), Institute of the USA and Canada (RAS) and Mrs. E. Suponina from “Moscow News” newspaper analyzed a wide range of issues associated with these events. Among them are: 1) the reasons for such a large-scale explosion, 2) the nature of the discussed developments (revolutions, riots?) and who are the subjects of the current “Arab drama”, 3) the role of Islam and political Islamism, 4) the role of external factors.

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Research and industrialisation of Hermetia illucens L. in China

Journal of Insects as Food and Feed ◽

10.3920/jiff2019.0020 ◽

2020 ◽

Vol 6 (1) ◽

pp. 5-12

Author(s):

J.B. Zhang ◽

J.K. Tomberlin ◽

M.M. Cai ◽

X.P. Xiao ◽

L.Y. Zheng ◽

...

Keyword(s):

Large Scale ◽

Organic Waste ◽

Animal Feed ◽

Egg Laying ◽

Breeding Method ◽

Hermetia Illucens ◽

Cold Temperatures ◽

The Usa ◽

The Government ◽

Future Work

The larvae of the black soldier fly (BSF), Hermetia illucens L., are commonly associated with decaying organic wastes. Over the past 15 years, investigators in China have conducted extensive research exploring the use of BSF larvae to recycle organic materials as a means to protect the environment, while producing products of value, such as protein and bioenergy. Initial efforts were based on a BSF strain from the USA. However, since then, H. illucens strains from specimens collected in Hubei and Guangdong Provinces have been established and used as models to explore the use of this species in sustainable agriculture. China has played an instrumental role in developing an in-door breeding method using a quartz-iodine lamp rather than depend on natural sunlight. This discovery has allowed the establishment of in-door BSF colonies in regions throughout the world where abiotic conditions (i.e. cold temperatures) are preventative. Researchers in China paved the way for using microbes as a means to enhance BSF production including, enhancing BSF egg-laying as well as waste reduction. Furthermore, bacteria from BSF gut or waste can be cultured and used to promote BSF growth, shorten conversion time, and enhanced conversion efficacy. Recent efforts have demonstrated BSF larvae can degrade antibiotics as well as suppress noxious odours in livestock manure. Due to the efforts of research on BSF in China, numerous companies that recycle organic waste at a large scale (>20 tonnes waste digested/day), have been established. Resulting products include insect powder, and live BSFL that can be used as animal feed ingredients for livestock (e.g. eels and frogs), while protecting the environment. Future work will decipher the mechanisms regulating BSF larval conversion of organic waste so that the system can be optimised. However, efforts are still needed at the government level to establish quality assurance standards if this process is truly to become established as an industry in China.

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The long-term development of Russian biotech sector

foresight ◽

10.1108/fs-06-2016-0024 ◽

2017 ◽

Vol 19 (5) ◽

pp. 491-500 ◽

Cited By ~ 1

Author(s):

Anna Grebenyuk ◽

Nikolai Ravin

Keyword(s):

High Performance ◽

Large Scale ◽

Technological Development ◽

Science And Technology ◽

Plant Biotechnology ◽

High Tech ◽

Content Type ◽

Research Areas ◽

Research Activities ◽

The Usa

Purpose To define strategic directions for the Russia’s social, economic, scientific and technological development in 2011-2013, a large-scale foresight study including the deep analysis of prospects of biotechnology development there was undertaken (Russia 2030: Science and Technology Foresight). This paper aims to present results of this research. Design/methodology/approach The study was based on a combination of technology-push and market-pull approaches that aimed not only to identify most promising science and technology (S&T) areas but also to understand how they can be realized in practice. Representatives from federal authorities, science and business were involved in the project to create future visions of technological directions; analyze grand challenges, weak signals and wild cards; and set research and development (R&D) priorities. Findings According to results of the study, Russia has a potential for biotech sector development, although the level of R&D in the majority of areas is lagging behind that in the USA and leading EU countries. However, there are several advanced applied research areas where efforts can be focused. Among them are high-performance genomics and post-genomics research platforms, systems and structural biology, microbial metabolic engineering, plant biotechnology and microbial strains and consortia for development of symbiotic plant–microbial communities. Originality/value Concentration of available resources of government and business on biotechnological sector development can help to find answers for challenges that Russia faces today or will face tomorrow. It will help to pick up on the current level of research activities, improve the quality of personnel training, make this area the engine of the economy and carry out the so-called new industrialization of the country, building a new, high-tech device industry.

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The effect of input data resolution and complexity on the uncertainty of hydrological predictions in a humid vegetated watershed

Hydrology and Earth System Sciences ◽

10.5194/hess-22-5947-2018 ◽

2018 ◽

Vol 22 (11) ◽

pp. 5947-5965 ◽

Cited By ~ 1

Author(s):

Linh Hoang ◽

Rajith Mukundan ◽

Karen E. B. Moore ◽

Emmet M. Owens ◽

Tammo S. Steenhuis

Keyword(s):

Land Use ◽

Parameter Uncertainty ◽

Input Data ◽

Hydrological Modeling ◽

Assessment Tool ◽

Model Performance ◽

Data Complexity ◽

Delaware River ◽

Output Uncertainty ◽

Data Resolution

Abstract. Uncertainty in hydrological modeling is of significant concern due to its effects on prediction and subsequent application in watershed management. Similar to other distributed hydrological models, model uncertainty is an issue in applying the Soil and Water Assessment Tool (SWAT). Previous research has shown how SWAT predictions are affected by uncertainty in parameter estimation and input data resolution. Nevertheless, little information is available on how parameter uncertainty and output uncertainty are affected by input data of varying complexity. In this study, SWAT-Hillslope (SWAT-HS), a modified version of SWAT capable of predicting saturation-excess runoff, was applied to assess the effects of input data with varying degrees of complexity on parameter uncertainty and output uncertainty. Four digital elevation model (DEM) resolutions (1, 3, 10 and 30 m) were tested for their ability to predict streamflow and saturated areas. In a second analysis, three soil maps and three land use maps were used to build nine SWAT-HS setups from simple to complex (fewer to more soil types/land use classes), which were then compared to study the effect of input data complexity on model prediction/output uncertainty. The case study was the Town Brook watershed in the upper reaches of the West Branch Delaware River in the Catskill region, New York, USA. Results show that DEM resolution did not impact parameter uncertainty or affect the simulation of streamflow at the watershed outlet but significantly affected the spatial pattern of saturated areas, with 10m being the most appropriate grid size to use for our application. The comparison of nine model setups revealed that input data complexity did not affect parameter uncertainty. Model setups using intermediate soil/land use specifications were slightly better than the ones using simple information, while the most complex setup did not show any improvement from the intermediate ones. We conclude that improving input resolution and complexity may not necessarily improve model performance or reduce parameter and output uncertainty, but using multiple temporal and spatial observations can aid in finding the appropriate parameter sets and in reducing prediction/output uncertainty.

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