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Article ; Online: Enhancing economic competitiveness analysis through machine learning

Xiaofeng Xu / Zhaoyuan Chen / Shixiang Chen

PLoS ONE, Vol 18, Iss

Exploring complex urban features

2023 Volume 11

Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Enhancing economic competitiveness analysis through machine learning

Xiaofeng Xu / Zhaoyuan Chen / Shixiang Chen

PLoS ONE, Vol 18, Iss 11, p e

Exploring complex urban features.

2023 Volume 0293303

Abstract: Urban economic competitiveness is a fundamental indicator for assessing the level of urban development and serves as an effective approach for understanding regional disparities. Traditional economic competitiveness research that relies solely on ... ...

Abstract	Urban economic competitiveness is a fundamental indicator for assessing the level of urban development and serves as an effective approach for understanding regional disparities. Traditional economic competitiveness research that relies solely on traditional regression models and assumes feature relationship theory tends to fall short in fully exploring the intricate interrelationships and nonlinear associations among features. As a result, the study of urban economic disparities remains limited to a narrow range of urban features, which is insufficient for comprehending cities as complex systems. The ability of deep learning neural networks to automatically construct models of nonlinear relationships among complex features provides a new approach to research in this issue. In this study, a complex urban feature dataset comprising 1008 features was constructed based on statistical data from 283 prefecture-level cities in China. Employing a machine learning approach based on convolutional neural network (CNN), a novel analytical model is constructed to capture the interrelationships among urban features, which is applied to achieve accurate classification of urban economic competitiveness. In addition, considering the limited number of samples in the dataset owing to the fixed number of cities, this study developed a data augmentation approach based on deep convolutional generative adversarial network (DCGAN) to further enhance the accuracy and generalization ability of the model. The performance of the CNN classification model was effectively improved by adding the generated samples to the original sample dataset. This study provides a precise and stable analytical model for investigating disparities in regional development. In the meantime, it offers a feasible solution to the limited sample size issue in the application of deep learning in urban research.
Keywords	Medicine ; R ; Science ; Q
Subject code	910
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Drainage Pattern Recognition of River Network Based on Graph Convolutional Neural Network

Xiaofeng Xu / Pengcheng Liu / Mingwu Guo

ISPRS International Journal of Geo-Information, Vol 12, Iss 7, p

2023 Volume 253

Abstract: Drainage network pattern recognition is a significant task with wide applications in geographic information mining, map cartography, water resources management, and urban planning. Accurate identification of spatial patterns in river networks can help us ...

Abstract	Drainage network pattern recognition is a significant task with wide applications in geographic information mining, map cartography, water resources management, and urban planning. Accurate identification of spatial patterns in river networks can help us understand geographic phenomena, optimize map cartographic quality, assess water resource potential, and provide a scientific basis for urban development planning. However, river network pattern recognition still faces challenges due to the complexity and diversity of river networks. To address this issue, this study proposes a river network pattern recognition method based on graph convolutional networks (GCNs), aiming to achieve accurate classification of different river network patterns. We utilize binary trees to construct a hierarchical tree structure based on river reaches and progressively determine the tree hierarchy by identifying the upstream and downstream relationships among river reaches. Based on this representation, input features for the graph convolutional model are extracted from both spatial and geometric perspectives. The effectiveness of the proposed method is validated through classification experiments on four types of vector river network data (dendritic, fan-shaped, trellis, and fan-shaped). The experimental results demonstrate that the proposed method can effectively classify vector river networks, providing strong support for research and applications in related fields.
Keywords	drainage patterns ; pattern recognition ; river network ; binary tree ; graph convolution ; Geography (General) ; G1-922
Subject code	006
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Value of Combined Application of Oxycodone Hydrochloride Injection and Dexmedetomidine in Anesthesia for LC for Patients with Gallbladder Lesions

Zhantian Wang / Xiaofeng Xu

Journal of Healthcare Engineering, Vol

2021 Volume 2021

Abstract: Objective. To analyze the effect of combined application of oxycodone hydrochloride injection and dexmedetomidine in anesthesia for laparoscopic cholecystectomy (LC) for patients with gallbladder lesions. Method. 93 patients with gallbladder lesions in ... ...

Abstract	Objective. To analyze the effect of combined application of oxycodone hydrochloride injection and dexmedetomidine in anesthesia for laparoscopic cholecystectomy (LC) for patients with gallbladder lesions. Method. 93 patients with gallbladder lesions in our hospital were divided into 2 groups by the random number table method. 46 patients in the control group applied oxycodone hydrochloride injection in anesthesia, and 47 patients in the observation group applied oxycodone hydrochloride injection combined with dexmedetomidine in anesthesia. Result. The T1 and T2 MAP levels in the observation group were lower than those in the control group (P<0.05), and the difference between T3 and the control group was not significantly significant (P>0.05). The T1 to T3 HR level in the observation group were lower than those in the control group (P<0.05). The rate of excessive sedation (10.64%) and sedation inefficiency (12.77%) in the observation group was lower than that in the control group (28.26% and 30.43%), and the rate of satisfactory sedation (76.60%) was higher than that in the control group (41.30%) (P<0.05). The postoperative awakening, tracheal tube removal, and first anal venting time were shorter in the observation group than in the control group (P<0.05). The WHO scores of incisional pain at 6, 12, 24, and 48 hours after the operation were lower in the observation group than in the control group (P<0.05). The T2 SOD level in the observation group was higher than that in the control group, and the ROS and MDA levels were lower than those in the control group (P<0.05). The incidence of side effects of anesthetic in the observation group was 17.02%, which was not statistically different from the control group of 13.04% (P>0.05). Conclusion. The combined application of oxycodone hydrochloride injection and dexmedetomidine in anesthesia for LC for patients with gallbladder lesions can achieve better sedation and analgesia effect, accelerate postoperative awakening and recovery, and control ...
Keywords	Medicine (General) ; R5-920 ; Medical technology ; R855-855.5
Subject code	630
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Hindawi Limited
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Characteristics of Optical Properties and Heating Rates of Dust Aerosol over Taklimakan Desert and Tibetan Plateau in China Based on CALIPSO and SBDART

Xiaofeng Xu / Shixian Pan / Tianyang Luo / Yudi Yang / Zixu Xiong

Remote Sensing, Vol 15, Iss 607, p

2023 Volume 607

Abstract: The spatial and temporal distributions of dust aerosol and its radiative heating effect over Taklimakan Desert (TD) and Tibetan Plateau (TP) were analyzed using the CALIPSO aerosol products and the SBDART model during 2007–2020. The annual dust aerosol ... ...

Abstract	The spatial and temporal distributions of dust aerosol and its radiative heating effect over Taklimakan Desert (TD) and Tibetan Plateau (TP) were analyzed using the CALIPSO aerosol products and the SBDART model during 2007–2020. The annual dust aerosol optical depths (DAOD at 532 nm) ranged from 0.266 to 0.318 over TD and 0.086 to 0.108 over TP, with means of 0.286 ± 0.015 and 0.097 ± 0.006, respectively. The regional mean DAODs of TD (TP) from spring to winter were 0.375 ± 0.020 (0.107 ± 0.010), 0.334 ± 0.028 (0.110 ± 0.010), 0.235 ± 0.026 (0.071 ± 0.008), and 0.212 ± 0.045 (0.083 ± 0.011), respectively. The maximal (minimal) seasonal DAOD of TD appeared in spring (winter), while that of TP appeared in summer (autumn). Although neither the annual nor the seasonal DAODs showed a statistically significant trend over both TD and TP, their yearly fluctuations were apparent, showing coefficients of variation of 0.053 and 0.065 over TD and TP, respectively. The profile of dust extinction coefficient ( σ D ) showed the maximum in spring and summer over TD and TP, respectively. It showed a weak increasing trend of σ D over both TD and TP in spring, but a decreasing trend in autumn. The dust of TD is concentrated within 1–4 km, where the annual averaged shortwave (SW) dust heating rates (DHRs) were larger than 2 K·day −1 from March to September. Over TP, the dust heating layer with SW DHR > 2 K·day −1 ranged from 3 to 4 km during March to June. The SW DHR was much larger in spring and summer than in the other two seasons over both regions, with the maximum in spring. A relatively strong dust heating layer with top >5 km appeared along the north slope of the TP, indicating an important energy transport channel from TD to TP, especially in spring and summer. It showed an increasing trend of the SW DHR over both TD and TP in spring and winter, but a decreasing trend in summer and autumn. Over TD, the most powerful heating appeared within 2–4 km, but the strength and the area of high-value DHR reduced from spring to ...
Keywords	dust ; aerosol optical depth ; heating rate ; Tibetan Plateau ; Taklimakan Desert ; Science ; Q
Subject code	333
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Three-Dimensional Distribution and Transport Features of Dust and Polluted Dust over China and Surrounding Areas from CALIPSO

Xiaofeng Xu / Yudi Yang / Zixu Xiong / Jianming Gong / Tianyang Luo

Remote Sensing, Vol 15, Iss 24, p

2023 Volume 5734

Abstract: Dust plays a very important role in the Earth’s climate system by its direct and indirect effects. Deserts in northwestern China contribute a large amount of dust particles, both inland and outside, while the vertical distribution and transport mechanism ...

Abstract	Dust plays a very important role in the Earth’s climate system by its direct and indirect effects. Deserts in northwestern China contribute a large amount of dust particles, both inland and outside, while the vertical distribution and transport mechanism of dust still have many uncertainties. Using Level 3 cloud-free monthly aerosol products of the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) system from 2007 to 2020, we analyzed the spatial and temporal variations and transport features for dust and polluted dust aerosols over China and the surrounding areas. The results show that the Taklimakan Desert (TD) and the Thar Desert (TRD) always act as the high-value centers of dust optical depth (DOD), while the centers of polluted dust optical depth (PDOD) are located in eastern China, the Sichuan Basin and the Indian subcontinent. The DOD shows an increasing trend in most areas, while the PDOD presents a significant decrease and increase in eastern China and central India, respectively. The largest DOD appears in spring over the TD and the Gobi Desert (GD), while the largest DOD in summer is over the TRD. Although most dusts in the TD and TRD are concentrated below 4 km, they may be higher over the TD. Most of the polluted dusts are confined to under 2 km. The dust input to the Tibetan Plateau (TP) could come from both the TD and TRD and occurs mostly in spring and summer, respectively. The polluted dusts of South Asia and the Indian subcontinent are mostly contained in the boundary layer in winter, but they could extend much higher in spring and summer, which favors their transport into southwestern China. The dust layer shows apparent seasonality. Its top reaches a higher level in spring and summer, while the base stays at a similar height in all seasons. The dust layer appears to be the thickest in spring over most areas, while the thickest layer in summer is over the TD and TRD. The polluted dust layer is thickest in the Indian subcontinent in spring. The overlapping of dust and ...
Keywords	dust ; polluted dust ; distribution ; transport ; CALIPSO ; Science ; Q
Subject code	950
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Neural Network-Based Output Feedback Fault Tolerant Tracking Control for Nonlinear Systems with Unknown Control Directions

Kun Yan / Chaobo Chen / Xiaofeng Xu / Qingxian Wu

Complexity, Vol

2022 Volume 2022

Abstract: In this study, an adaptive output feedback fault tolerant control (FTC) scheme is proposed for a class of multi-input and multioutput (MIMO) nonlinear systems with multiple constraints. The neural network (NN) is adopted to handle the unknown ... ...

Abstract	In this study, an adaptive output feedback fault tolerant control (FTC) scheme is proposed for a class of multi-input and multioutput (MIMO) nonlinear systems with multiple constraints. The neural network (NN) is adopted to handle the unknown nonlinearity by means of its superior approximation capability. Based on it, the state observer is designed to estimate the unmeasured states, and the nonlinear disturbance observer is constructed to tackle the external disturbances. In addition, the Nussbaum function is utilized to cope with the actuator faults, which are coupled with the unknown control directions. Combining with the Lyapunov theory, a NN-based output feedback FTC law is developed for the MIMO nonlinear systems, and the boundedness of all closed-loop system error signals is proved. Simulation results on the unmanned helicopter are performed to demonstrate the effectiveness of the proposed controller.
Keywords	Electronic computers. Computer science ; QA75.5-76.95
Subject code	629
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Hindawi-Wiley
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Simulation and experimental investigation of a multi-temperature insulation box with phase change materials for cold storage

Xiaofeng, Xu / Xuelai, Zhang

Journal of food engineering. 2021 Mar., v. 292

2021

Abstract: In terms of cold chain logistics, China is less developed with most refrigerated transport being mechanical compression refrigeration. To improve the economy of logistics and ensure the quality of fruits and vegetables in refrigerated transportation, a ... ...

Abstract	In terms of cold chain logistics, China is less developed with most refrigerated transport being mechanical compression refrigeration. To improve the economy of logistics and ensure the quality of fruits and vegetables in refrigerated transportation, a multi-temperature insulation box with different phase change materials (PCMs) was designed for cold storage in this work. The efficiency of PCMs was evaluated using a differential scanning calorimeter (DSC) and thermal conductivity tester. The experimental results reveal phase transition temperatures of 7.1 and −2.5 °C, latent heats of 146.1 and 256.2 J/g, and thermal conductivities of 0.2832 and 0.9427 W/(m·K) of PCM1 (n-octanoic acid-myristic acid composite) and PCM2 (potassium sorbate-water composite), respectively. Combined with vacuum insulation technology, a multi-temperature zone insulation box for cold storage was constructed. A three-dimensional unsteady model was established, and the temperature and velocity fields in different parts of the box were analyzed, especially the melting process of PCMs. An insulation box temperature test system was established using good supply practice (GSP). The experimental results reveal that temperature zones 2 (medium zone) and 3 (low zone) of the insulation box can be kept cold at 7–9 °C for about 13 h and at −2–0 °C for about 14 h, respectively. The results suggest that the designed multi-temperature storage insulation box is an effective transportation equipment for cold chain logistics.
Keywords	calorimeters ; cold ; cold chain ; cold storage ; insulating materials ; models ; potassium ; refrigeration ; temperature ; thermal conductivity ; transportation ; China
Language	English
Dates of publication	2021-03
Publishing place	Elsevier Ltd
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	622518-4
ISSN	0260-8774
ISSN	0260-8774
DOI	10.1016/j.jfoodeng.2020.110286
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Data Analysis and Decision on Navigation Safety of Yangshan Port Channel

Xiang’en Bai / Tian Guan / Xiaofeng Xu / Yingjie Xiao

Sustainability, Vol 14, Iss 7968, p

2022 Volume 7968

Abstract: Aiming at the problem of pilotage disruption under high wind control, this paper provides statistics on wind direction and wind levels during high wind control days, measures pilotage disruption at Yangshan Port for a total of ten years (from 2011 to ... ...

Abstract	Aiming at the problem of pilotage disruption under high wind control, this paper provides statistics on wind direction and wind levels during high wind control days, measures pilotage disruption at Yangshan Port for a total of ten years (from 2011 to 2020), notes the wind direction and wind levels that trigger pilotage disruption, and models and analyzes the effects of different wind directions and wind-level coupling on pilotage disruption. In addition, the difference of traffic flow in the alert area under normal and interrupted conditions of pilotage is analyzed by combining pilotage interruption data and the observation data of the alert area. The law of traffic volume and speed of container ships of different lengths is also analyzed. Based on the data of each observation line, the speed and time of ships in the warning area were evaluated by combining the speed, heading, and time from the records. The traffic law of different types of ships are summarized; that is, the ship’s speed in the caution area is roughly positively correlated with its length: the longer the ship’s length, the faster the ship’s speed, and the less the sailing time. The article provides a basis for the research of pilotage safety operations.
Keywords	pilotage interrupted ; wind level and wind direction ; modeling analysis ; traffic flow ; sailing law ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	551
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Improving the Innovative Performance of Renewable Energy Enterprises in China

Xiaofeng Xu / Xiangyu Chen / Yi Xu / Tao Wang / Yifan Zhang

Sustainability, Vol 14, Iss 8169, p

Effects of Subsidy Policy and Intellectual Property Legislation

2022 Volume 8169

Abstract: Energy efficiency and emissions reductions are effective initiatives to address climate change and energy security. China has increased government subsidies and intellectual property protection (IPP) intensity to promote technological innovation in the ... ...

Abstract	Energy efficiency and emissions reductions are effective initiatives to address climate change and energy security. China has increased government subsidies and intellectual property protection (IPP) intensity to promote technological innovation in the renewable energy sector. This paper selects samples of geothermal, wind, and solar energy companies and examines whether the two initiatives mentioned above can improve company innovation, and assesses their action pathways. The results reveal that: (i) government subsidies can directly facilitate renewable energy enterprises’ innovative performance, and research and development (R&D) input served as a medium; and (ii) the intensity of IPP moderation needed for geothermal and solar enterprises to utilize the government subsidy to enhance innovation. The government should consider the differences of different sub-sectors of renewable energy when increasing subsidies. Better laws and policies are needed to strengthen the protection of intellectual property rights and stimulate innovation in renewable energy enterprises.
Keywords	government subsidy ; renewable energy industry ; intellectual property protection ; innovative performance ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	690
Language	English
Publishing date	2022-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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