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Article ; Online: Measuring the macroeconomic determinants of agricultural price volatility

Hang Liu

Frontiers in Public Health, Vol

Implications for natural resource commodity prices for green recovery

2022 Volume 10

Abstract: With rapid growth, green economic recovery has been a key agenda for the globe. However, the price volatility for natural resources plays a significant role in reshaping the green recovery. Therefore, the current study investigates the impact of green ... ...

Abstract	With rapid growth, green economic recovery has been a key agenda for the globe. However, the price volatility for natural resources plays a significant role in reshaping the green recovery. Therefore, the current study investigates the impact of green recovery, hum, a capital index, GDP growth, foreign direct investment and inflation on natural resource volatility in China from 1995 to 2020. In order to investigate the long-term association among selected variables, this study employs the Autoregressive Distributive Lag (ARDL) model. In addition, the current research uses the Aikaik information (AIC) criteria for the model selections. Obtained outcomes show the significant contribution of green recovery, human capital, GDP growth, FDI and inflation increase the natural resource price volatility level. However, to validate the results of ARDL, this study also used the ECM approach and validated the prior findings. On behalf of outcomes, the current study implies some imperative policies to attain the desired objective for green growth.
Keywords	natural resources prices volatility ; FDI ; inflation ; human capital index ; gross domestic product ; Public aspects of medicine ; RA1-1270
Subject code	339
Language	English
Publishing date	2022-12-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Research on the capacity cost allocation and the electricity capacity price optimization method for a power system based on the BARY‐GA algorithm

Hang Liu / Qing Liu / Rui He / Feng Li / Kaiyan Luo

Energy Science & Engineering, Vol 12, Iss 1, Pp 168-

2024 Volume 180

Abstract: Abstract Under the new power system, a high proportion of new energy is widely connected to the power grid, and it is necessary to increase investment in centralized and distributed energy storage, flexible resource regulation, and transmission and ... ...

Abstract	Abstract Under the new power system, a high proportion of new energy is widely connected to the power grid, and it is necessary to increase investment in centralized and distributed energy storage, flexible resource regulation, and transmission and distribution grids, resulting in an increase in power system costs. The current electricity capacity price does not reflect the economic value of the added system adequately, and flexible capacity is needed to ensure the safety of the power grid under the new power system. In the context of the transformation of the new power system and investment function, it is increasingly difficult to recover the costs according to the traditional electricity price. It is necessary to establish a coordinated development mechanism for the electricity capacity price and the electricity price that recovers the fixed costs according to the investment function to ensure a reasonable return on investment in flexible resources and to provide effective investment signals. Therefore, this work first studied and proposed a mechanism for the formation of capacity and electricity prices based on the proportion of allowed income and fixed costs at different voltage levels and calculates the level of electricity capacity (demand) prices and electricity consumption prices. Then, using the BARY curve, genetic algorithm, and clustering of user load rates, a collaborative mechanism between the electricity capacity price and the electricity price was designed. With the goal of optimizing the electricity capacity price and considering constraints such as the flexibility and reliability of the new power system, the ratio of the capacity cost allocated to the electricity capacity price by voltage level users to the capacity cost allocated to the electricity price was calculated, and the optimal combination of electricity capacity price and electricity price for different load‐rate intervals was determined. Finally, the effectiveness of the model was verified through numerical simulations. On the basis ...
Keywords	BARY‐GA ; capacity pricing mechanism ; electricity capacity synergy ; new power system ; Technology ; T ; Science ; Q
Subject code	338
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Wiley
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Regenerated Cellulose Fibers (RCFs) for Future Apparel Sustainability

Ting Chi / Anastasia Frattali / Hang Liu / Yini Chen

Sustainability, Vol 15, Iss 5404, p

Insights from the U.S. Consumers

2023 Volume 5404

Abstract: An increasing number of apparel companies are inventing novel green technologies to produce regenerated cellulose fibers (RCFs) out of textile waste. RCF can significantly reduce virgin cotton production and decrease textile waste in incinerators or ... ...

Abstract	An increasing number of apparel companies are inventing novel green technologies to produce regenerated cellulose fibers (RCFs) out of textile waste. RCF can significantly reduce virgin cotton production and decrease textile waste in incinerators or landfills. However, our knowledge on U.S. consumers’ willingness to purchase RCF-made apparel is still limited given its newness. To address the gap in the literature, this study aimed to identify the factors significantly influencing the U.S. consumers’ purchase intention toward RCF-made apparel. Building on the Theory of Planned Behavior (TPB), a research model including attitude, subjective norm, perceived behavioral control, perceived consumer effectiveness, and past environmental behavior as predictors was proposed to investigate the U.S. consumers’ intention to purchase RCF-made apparel. The primary data were collected by a Qualtrics survey of U.S. consumers. A total of 544 eligible responses were gathered for data analysis and hypothesis testing. The multiple regression method was applied for determining the proposed statistical relationships. Attitude, perceived consumer effectiveness, and past environmental behavior positively affect U.S. consumers’ purchase intention toward RCF-made apparel, while the effects of subjective norm and perceived behavior control are insignificant. Attitude plays a partial mediating role between past environmental behavior and purchase intention toward RCF-made apparel. A higher level of consumer environmental behavior leads to a more positive attitude toward and a greater likelihood to purchase RCF-made apparel. The proposed research model exhibits a good explanatory power, accounting for 64.8% of variance in U.S. consumers’ purchase intention toward RCF-made apparel.
Keywords	sustainability ; regenerated cellulose fiber ; apparel ; purchase intention ; U.S. consumers ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Predicting drug adverse effects using a new Gastro-Intestinal Pacemaker Activity Drug Database (GIPADD)

Julia Yuen Hang Liu / John A. Rudd

Scientific Reports, Vol 13, Iss 1, Pp 1-

2023 Volume 10

Abstract: Abstract Electrical data could be a new source of big-data for training artificial intelligence (AI) for drug discovery. A Gastro-Intestinal Pacemaker Activity Drug Database (GIPADD) was built using a standardized methodology to test drug effects on ... ...

Abstract	Abstract Electrical data could be a new source of big-data for training artificial intelligence (AI) for drug discovery. A Gastro-Intestinal Pacemaker Activity Drug Database (GIPADD) was built using a standardized methodology to test drug effects on electrical gastrointestinal (GI) pacemaker activity. The current report used data obtained from 89 drugs with 4867 datasets to evaluate the potential use of the GIPADD for predicting drug adverse effects (AEs) using a machine-learning (ML) approach and to explore correlations between AEs and GI pacemaker activity. Twenty-four “electrical” features (EFs) were extracted using an automated analytical pipeline from the electrical signals recorded before and after acute drug treatment at three concentrations (or more) on four-types of GI tissues (stomach, duodenum, ileum and colon). Extracted features were normalized and merged with an online side-effect resource (SIDER) database. Sixty-six common AEs were selected. Different algorithms of classification ML models, including Naïve Bayes, discriminant analysis, classification tree, k-nearest neighbors, support vector machine and an ensemble model were tested. Separated tissue models were also tested. Averaging experimental repeats and dose adjustment were performed to refine the prediction results. Random datasets were created for model validation. After model validation, nine AEs classification ML model were constructed with accuracy ranging from 67 to 80%. EF can be further grouped into ‘excitatory’ and ‘inhibitory’ types of AEs. This is the first time drugs are being clustered based on EF. Drugs acting on similar receptors share similar EF profile, indicating potential use of the database to predict drug targets too. GIPADD is a growing database, where prediction accuracy is expected to improve. The current approach provides novel insights on how EF may be used as new source of big-data in health and disease.
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Study on co-seismic ionospheric disturbance of Alaska earthquake on July 29, 2021 based on GPS TEC

Qingshan Ruan / Xitun Yuan / Hang Liu / Shuyao Ge

Scientific Reports, Vol 13, Iss 1, Pp 1-

2023 Volume 14

Abstract: Abstract With the rapid development of space geodetic information technology, the Global Positioning System (GPS) has been widely used in seismology and space environmental research. Typically, the occurrence of a large earthquake will lead to some ... ...

Abstract	Abstract With the rapid development of space geodetic information technology, the Global Positioning System (GPS) has been widely used in seismology and space environmental research. Typically, the occurrence of a large earthquake will lead to some changes in the ionosphere, this phenomenon is called coseismic ionospheric disturbances (CIDs). In this contribution, differential slant total electron content (dSTEC) is used to study the anomalous characteristics of the ionosphere. First, based on the ionospheric dSTEC time series and two-dimensional disturbance detection, the temporal and spatial characteristics of ionospheric disturbances can be accurately analysed. Secondly, using wavelet transform spectrum analysis and disturbance propagation velocity, it can be determined that the disturbance sources of this earthquake can be identified as acoustic wave, gravity wave and Rayleigh wave. Finally, in order to further clarify the direction of the earthquake disturbance, this study focuses on proposing an innovative method for the disturbance propagation direction, and determines that there are two directions of the propagation of the CIDs of the Alaski earthquake.
Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2023-07-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Renting than Buying Apparel

Ting Chi / Olabisi Adesanya / Hang Liu / Rebecca Anderson / Zihui Zhao

Sustainability, Vol 15, Iss 4926, p

U.S. Consumer Collaborative Consumption for Sustainability

2023 Volume 4926

Abstract: Apparel rental service is a business model that is becoming increasingly popular in recent years as consumers become more conscious of their environmental impact and look for ways to reduce waste and save money. However, our knowledge on this changing ... ...

Abstract	Apparel rental service is a business model that is becoming increasingly popular in recent years as consumers become more conscious of their environmental impact and look for ways to reduce waste and save money. However, our knowledge on this changing consumer behavior is scant. To address the gap in the literature, this study aimed to identify the determinants driving U.S. consumers’ intention to use apparel rental services. Building on the Theory of Planned Behavior (TPB), a research model was proposed. The primary data were gathered by an online survey of U.S. consumers through Qualtrics. A total of 338 eligible responses were obtained for data analysis and hypothesis testing. The results show that attitude, subjective norms, perceived consumer effectiveness, environmental knowledge, perceived personal relevance, and past environmental behavior significantly influence U.S. consumers’ intention to adopt apparel rental services. In addition, attitude plays a partial mediating role in the effects of environmental knowledge and perceived personal relevance on U.S. consumers’ intent to use apparel rental services. The demographic variables including age, gender, education level, and income level do not significantly influence U.S. consumer intention to rent apparel. The proposed research model exhibits a high explanatory power, collectively accounting for 74.7% of the variance in U.S. consumers’ intention to adopt apparel rental services.
Keywords	sustainability ; collaborative consumption ; apparel rental ; adoption ; U.S. consumers ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	690
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Comparison of the similarity between two quantum images

You-hang Liu / Zai-dong Qi / Qiang Liu

Scientific Reports, Vol 12, Iss 1, Pp 1-

2022 Volume 10

Abstract: Abstract Comparing the similarity between digital images is an important subroutine in various image processing algorithms. In this study, we present three quantum algorithms for comparing the similarity between two quantum images. These algorithms are ... ...

Abstract	Abstract Comparing the similarity between digital images is an important subroutine in various image processing algorithms. In this study, we present three quantum algorithms for comparing the similarity between two quantum images. These algorithms are applied to binary, grey and color images for the first time. Without considering the image preparation, the proposed algorithms achieve exponential acceleration than the existing quantum and classical methods in all three cases. At the end of this paper, an experiment based on the real quantum computer of IBMQ and simulations verify the effectiveness of the algorithms.
Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Study on Module Selection Method for Customized Products

Hang Liu

Intelligent Control and Automation , Vol 05, Iss 04, Pp 245-

2014 Volume 252

Abstract: Modularization is the key technique for modern manufacturing system, which resolves the conflict between flexibility and productivity. The challenge of deciding which modules should choose under resource limitation from a large amount of available ... ...

Abstract	Modularization is the key technique for modern manufacturing system, which resolves the conflict between flexibility and productivity. The challenge of deciding which modules should choose under resource limitation from a large amount of available alternative modules has been well recognized in academia and industry correspondingly in producing customized production. For this reason, this paper proposes a new module selection method to deal with the problem, which combines rough set theory into total quality development (QFD) framework. First of all, a decision table is build up and then be modified through examining the importance of each attribute. Afterwards, the basic importance rating vector is calculated and the modifying index of the importance will be determined to get the final result. Finally, the feasibility and efficiency of the proposed method is manifested by a case study.
Keywords	Module Selection ; Rough Set Theory ; QFD ; Resource Limitation ; Electronic computers. Computer science ; QA75.5-76.95 ; Instruments and machines ; QA71-90 ; Mathematics ; QA1-939 ; Science ; Q
Subject code	670
Language	English
Publishing date	2014-10-01T00:00:00Z
Publisher	Scientific Research Publishing
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Spatio-Temporal Characteristics and Influencing Factors of Urban Spatial Quality in Northeast China Based on DMSP-OLS and NPP-VIIRS Nighttime Light Data

Hang Liu / Xiaohong Chen / Ying Wang / Xiaoqing Xu / Mingxuan Zhang

Sustainability, Vol 14, Iss 15668, p

2022 Volume 15668

Abstract: The quality of urban spaces is a pivotal part of high-quality spatial development. It is directly connected to the comprehensive, coordinated and sustainable development of a region. In recent years, Northeast China has characterized urban space ... ...

Abstract	The quality of urban spaces is a pivotal part of high-quality spatial development. It is directly connected to the comprehensive, coordinated and sustainable development of a region. In recent years, Northeast China has characterized urban space contraction and development. To study the quality of urban space in Northeast China, this paper fitted the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data with 11 indicators related to high-quality urban development for the period 1992–2018. The feasibility of nighttime light data reflecting urban spatial quality was verified by a linear equation, and the temporal characteristics of urban spatial quality in Northeast China were obtained. The Exploratory Spatial Data Analysis Geographically and Temporally Weighted Regression (ESDA-GTWR) explores the spatial relevance and possible influencing factors of this kind of development. The results suggest that the overall trend of spatial quality in the three northeastern provinces is “initial slow growth and significantly weakened after”. The fast developing cities include Panjin, Liaoyang, Shenyang, and Dalian in the Liaoning Province. On the other hand, cities such as Heihe and Yichun in the Heilongjiang Province have relatively slow development speeds. Furthermore, the spatial quality development in the three northeastern provinces exhibits a trend of continuous concentration. The cities with high spatial qualities are concentrated near the Liaoning Province, with low spatial qualities in the north and high spatial qualities in the southern parts of the three provinces. As there is a notable gap between the northern and the southern regions, the central region represents an area in partial transition. The spatial quality of each city in the three northeastern provinces is the result of a number of intertwined factors, with significant differences in the degree of their ...
Keywords	Northeast China ; spatial quality ; nighttime light ; ESDA-GTWR ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	910
Language	English
Publishing date	2022-11-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Areal Interpolation Using Parcel and Census Data in Highly Developed Urban Environments

XiaoHang Liu / Alexis Martinez

ISPRS International Journal of Geo-Information, Vol 8, Iss 7, p

2019 Volume 302

Abstract: Areal interpolation is routinely used when spatial data are unavailable at desired geographical units. While many methods are available, few of them were developed specifically for and tested in highly developed urban cores. Even fewer studied ... ...

Abstract	Areal interpolation is routinely used when spatial data are unavailable at desired geographical units. While many methods are available, few of them were developed specifically for and tested in highly developed urban cores. Even fewer studied subpopulation or population characteristics. This paper explores both issues using parcel map and decennial census data as ancillary information. Using census blocks as intermediate zones, the method first disaggregates source-zone data to intermediate zones, then disaggregates data to parcel level in intermediate zones intersecting target zones, and finally aggregates intermediate-zone and parcel-level estimates to obtain target-zone estimates. Compared to areal weighting and residential proportion, the proposed method is significantly more accurate. All three methods perform the best on population count, and worst on spatially clustered subpopulations such as black/African American population. Quotient variables are more difficult to interpolate than count variables. The research demonstrates the utility of parcel and decennial census data for areal interpolation in highly developed urban cores, and calls for future research on subpopulation and population characteristics.
Keywords	areal interpolation ; dasymetric mapping ; parcel data ; cadastral data ; census ; population ; subpopulation ; Geography (General) ; G1-922
Subject code	310
Language	English
Publishing date	2019-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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