bluuebunny/crossref_metadata_2025 huggingface dataset:
Results from Developments in the Use of a Scanning Sonar to Support Diving Operations from a Rescue Ship
Authors: Grządziel Artur
Published: February 2020

In recent years, widespread use of scanning sonars for acoustic imaging of the seabed surface can be observed. These types of sonars are mainly used with tripods or special booms, or are mounted onboard remotely operated or unmanned vehicles. Typical scanning sonar applications include search and recovery operations, imaging of underwater infrastructure, and scour monitoring. The use of these sonars is often limited to shallow waters. Diver teams or underwater remotely operated vehicles (ROV) are commonly used to inspect shipwrecks, port wharfs, and ship hulls. However, reduced underwater visibility, submerged debris, and extreme water depths can limit divers’ capabilities. In this paper, a novel, nonstandard technique for use of a scanning sonar is proposed. The new application for scanning sonar technology is a practical solution developed on the Polish Navy’s search and rescue ship “Lech.” To verify the effectiveness of the proposed technique, the author took part in four different studies carried out in the southeastern Baltic Sea. The tests were performed using the MS 1000 scanning sonar. The results demonstrate that the proposed technique has the potential to provide detailed sonar images of the seabed and underwater objects before the descent of divers. The divers get acquainted with the underwater situation, which undoubtedly increases the safety of the entire operation. Scanning sonars are unlikely to completely replace the work of divers but may reduce the number and duration of dives. The sonar use technique turned out to be useful when rescuing a crew of a submarine that crashed and settled on the sea bottom as part of a naval exercise. The sonar data obtained during four experimental tests performed in the Baltic Sea prove the validity, usefulness, and significance of the proposed technique, especially from the standpoint of safety of underwater work.
Angle Distance-Based Hierarchical Background Separation Method for Hyperspectral Imagery Target Detection
Authors: Hao Xiaohui , Wu Yiquan , Wang Peng
Published: February 2020

Traditional detectors for hyperspectral imagery (HSI) target detection (TD) output the result after processing the HSI only once. However, using the prior target information only once is not sufficient, as it causes the inaccuracy of target extraction or the unclean separation of the background. In this paper, the target pixels are located by a hierarchical background separation method, which explores the relationship between the target and the background for making better use of the prior target information more than one time. In each layer, there is an angle distance (AD) between each pixel spectrum in HSI and the given prior target spectrum. The AD between the prior target spectrum and candidate target ones is smaller than that of the background pixels. The AD metric is utilized to adjust the values of pixels in each layer to gradually increase the separability of the background and the target. For making better discrimination, the AD is calculated through the whitened data rather than the original data. Besides, an elegant and ingenious smoothing processing operation is employed to mitigate the influence of spectral variability, which is beneficial for the detection accuracy. The experimental results of three real hyperspectral images show that the proposed method outperforms other classical and recently proposed HSI target detection algorithms.
Compositing the Minimum NDVI for Daily Water Surface Mapping
Authors: Fan Xingwang , Liu Yuanbo , Wu Guiping , Zhao Xiaosong
Published: February 2020

Capturing high frequency water surface dynamics via optical remote sensing is important for understanding hydro-ecological processes over seasonally flooded wetlands. However, it is a difficult task due to the presence of clouds on satellite images. This study proposed the MODerate-resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) Minimum Value Composite (MinVC) algorithm to generate daily water surface data at a 250-m resolution. The algorithm selected pixelwise minimum values from the combined daily Terra and Aqua MODIS NDVI data within a 15-day moving window. Consisting mainly of cloud and water surface information, the MinVC NDVI data were segmented for water surfaces over the Poyang Lake, China (2000–2017) by using an edge detection model. The water surface mapping result was strongly correlated with the Landsat based result (R2 = 0.914, root mean square error, RMSE = 223.7 km2), the cloud free MODIS image based result (R2 = 0.824, RMSE = 356.7 km2), the recent Landsat-MODIS image fusion based result (R2 = 0.765, RMSE = 403 km2), and the hydrodynamic modeling result (R2 = 0.799). Compared to the equivalent eight-day MOD13 NDVI based on the Constraint View-Angle Maximum Value Composite (CV-MVC) algorithm, the daily MinVC NDVI highlighted water bodies by generating spatially homogenous water surface information. Consequently, the algorithm provided spatially and temporally continuous data for calculating water submersion times and trends in water surface area, which contribute to a better understanding of hydro-ecological processes over seasonally flooded wetlands. Within the framework of sensor intercalibration, the algorithm can be extended to incorporate multiple sensor data for improved water surface mapping.
Global and Local Tensor Sparse Approximation Models for Hyperspectral Image Destriping
Authors: Kong Xiangyang , Zhao Yongqiang , Xue Jize , Chan Jonathan Cheung-Wai , Kong Seong G.
Published: February 2020

This paper presents a global and local tensor sparse approximation (GLTSA) model for removing the stripes in hyperspectral images (HSIs). HSIs can easily be degraded by unwanted stripes. Two intrinsic characteristics of the stripes are (1) global sparse distribution and (2) local smoothness along the stripe direction. Stripe-free hyperspectral images are smooth in spatial domain, with strong spectral correlation. Existing destriping approaches often do not fully investigate such intrinsic characteristics of the stripes in spatial and spectral domains simultaneously. Those methods may generate new artifacts in extreme areas, causing spectral distortion. The proposed GLTSA model applies two ℓ 0 -norm regularizers to the stripe components and along-stripe gradient to improve the destriping performance. Two ℓ 1 -norm regularizers are applied to the gradients of clean image in spatial and spectral domains. The double non-convex functions in GLTSA are converted to single non-convex function by mathematical program with equilibrium constraints (MPEC). Experiment results demonstrate that GLTSA is effective and outperforms existing competitive matrix-based and tensor-based destriping methods in visual, as well as quantitative, evaluation measures.
Quantifying Flood Water Levels Using Image-Based Volunteered Geographic Information
Authors: Lin Yan-Ting , Yang Ming-Der , Han Jen-Yu , Su Yuan-Fong , Jang Jiun-Huei
Published: February 2020

Many people use smartphone cameras to record their living environments through captured images, and share aspects of their daily lives on social networks, such as Facebook, Instagram, and Twitter. These platforms provide volunteered geographic information (VGI), which enables the public to know where and when events occur. At the same time, image-based VGI can also indicate environmental changes and disaster conditions, such as flooding ranges and relative water levels. However, little image-based VGI has been applied for the quantification of flooding water levels because of the difficulty of identifying water lines in image-based VGI and linking them to detailed terrain models. In this study, flood detection has been achieved through image-based VGI obtained by smartphone cameras. Digital image processing and a photogrammetric method were presented to determine the water levels. In digital image processing, the random forest classification was applied to simplify ambient complexity and highlight certain aspects of flooding regions, and the HT-Canny method was used to detect the flooding line of the classified image-based VGI. Through the photogrammetric method and a fine-resolution digital elevation model based on the unmanned aerial vehicle mapping technique, the detected flooding lines were employed to determine water levels. Based on the results of image-based VGI experiments, the proposed approach identified water levels during an urban flood event in Taipei City for demonstration. Notably, classified images were produced using random forest supervised classification for a total of three classes with an average overall accuracy of 88.05%. The quantified water levels with a resolution of centimeters (<3-cm difference on average) can validate flood modeling so as to extend point-basis observations to area-basis estimations. Therefore, the limited performance of image-based VGI quantification has been improved to help in flood disasters. Consequently, the proposed approach using VGI images provides a reliable and effective flood-monitoring technique for disaster management authorities.
Joint Inversion of GPS, Leveling, and InSAR Data for The 2013 Lushan (China) Earthquake and Its Seismic Hazard Implications
Authors: Li Zhicai , Wen Yangmao , Zhang Peng , Liu Yang , Zhang Yong
Published: February 2020

On 20 April 2013, a moment magnitude (Mw) 6.6 earthquake occurred in the Lushan region of southwestern China and caused more than 190 fatalities. In this study, we use geodetic data from nearly 30 continuously operating global positioning system (GPS) stations, two periods of leveling data, and interferometric synthetic aperture radar (InSAR) observations to image the coseismic deformation of the Lushan earthquake. By using the Helmert variance component estimation method, a joint inversion is performed to estimate source parameters by using these GPS, leveling, and InSAR data sets. The results indicate that the 2013 Lushan earthquake occurred on a blind thrust fault. The event was dominated by thrust faulting with a minor left-lateral strike–slip component. The dip angle of the seismogenic fault was approximately 45.0°, and the fault strike was 208°, which is similar to the strike of the southern Longmenshan fault. Our finite fault model reveals that the peak slip of 0.71 m occurred at a depth of ~12 km, with substantial slip at depths of 6–20 km. The estimated magnitude was approximately Mw 6.6, consistent with seismological results. Furthermore, the calculated static Coulomb stress changes indicate that the 2013 Lushan earthquake may have been statically triggered by the 2008 Wenchuan earthquake.
Distributed Multi-Antenna Positioning for Automatic-Guided Vehicle
Authors: An Xinyuan , Zhao Sihao , Cui Xiaowei , Shi Qin , Lu Mingquan
Published: February 2020

Radio-based positioning systems are typically utilized to provide high-precision position information for automatic-guided vehicles (AGVs). However, the presence of obstacles in harsh environments, as well as carried cargoes on the AGV, will degrade the localization performance, since they block the propagation of radio signals. In this paper, a distributed multi-antenna positioning system is proposed, where multiple synchronous antennas are equipped on corners of an AGV to improve the availability and accuracy of positioning. An estimator based on the Levenberg–Marquardt algorithm is introduced to solve the nonlinear pseudo-range equations. To obtain the global optimal solutions, we propose a coarse estimator that utilizes the displacement knowledge of the antennas to provide a rough initial guess. Simulation results show a better availability of our system compared with the single antenna positioning system. Decimeter accuracy can be obtained under a Gaussian measurement noise with a standard deviation of 0.2 m. The results also demonstrate that the proposed algorithm can achieve positioning accuracy close to the theoretical Cramer–Rao lower bound. Furthermore, given prior information of the yaw angle, the same level of accuracy can be obtained by the proposed algorithm without the coarse estimation step.
Accuracy of CAD/CAM Digital Impressions with Different Intraoral Scanner Parameters
Authors: Chiu Asher , Chen Yen-Wei , Hayashi Juri , Sadr Alireza
Published: February 2020

The advancement of intraoral scanners has allowed for more efficient workflow in the dental clinical setting. However, limited data exist regarding the accuracy of the digital impressions produced with various scanner settings and scanning approaches. The purpose of this in vitro study was to compare the accuracy of digital impressions at the crown preparation margin using different scanning resolutions of a specific intraoral scanner system. An all-ceramic crown preparation of a mandibular first molar was constructed in a typodont, and a scan (n = 3) was created with an industrial-grade laboratory scanner (3Shape D2000) as the control. Digital impressions were obtained with an intraoral scanner (3Shape TRIOS 3) under three settings—high resolution (HR), standard resolution (SR), and combined resolution (SHR). Comparative 3D analysis of scans was performed with Geomagic Control X software to measure the discrepancy between intraoral scans and the control scan along the preparation finish line. The scan time and number of images captured per scan were recorded. Statistical analysis was performed by one-way ANOVA, two-way repeated measures ANOVA, Pearson’s correlation, and Dunnett’s T3 test (α = 0.05). Significant differences were observed for scan time and for number of images captured among scan resolution settings (α < 0.05). The scan time for the SR group was, on average, 34.2 s less than the SHR group and 46.5 s less than the HR group. For discrepancy on the finish line, no significant differences were observed among scanning resolutions (HR: 31.5 ± 5.5 μm, SHR: 33.2 ± 3.7 μm, SR: 33.6 ± 3.1 μm). Significant differences in discrepancy were observed among tooth surfaces, with the distal surface showing the highest discrepancies. In conclusion, the resolution of the intra-oral scanner is primarily defined by the system hardware and optimized for default scans. A software high-resolution mode that obtains more data over a longer time may not necessarily benefit the scan accuracy, while the tooth preparation and surface parameters do affect the accuracy.
Hybrid RSS/AOA Localization using Approximated Weighted Least Square in Wireless Sensor Networks
Authors: Kang SeYoung , Kim TaeHyun , Chung WonZoo
Published: February 2020

We present a target localization method using an approximated error covariance matrix based weighted least squares (WLS) solution, which integrates received signal strength (RSS) and angle of arrival (AOA) data for wireless sensor networks. We approximated linear WLS errors via second-order Taylor approximation, and further approximated the error covariance matrix using a least-squares solution and the variance in measurement noise over the sensor nodes. The algorithm does not require any prior knowledge of the true target position or noise variance. Simulations validated the superior performance of our new method.
Innovative Optical-Sensing Technology for the Online Fouling Characterization of Silicon Carbide Membranes during the Treatment of Oily Water
Authors: Ebrahimi Mehrdad , Schmidt Axel A. , Kaplan Cagatay , Schmitz Oliver , Czermak Peter
Published: February 2020

The oil and gas industry generates a large volume of contaminated water (produced water) which must be processed to recover oil before discharge. Here, we evaluated the performance and fouling behavior of commercial ceramic silicon carbide membranes in the treatment of oily wastewaters. In this context, microfiltration and ultrafiltration ceramic membranes were used for the separation of oil during the treatment of tank dewatering produced water and oily model solutions, respectively. We also tested a new online oil-in-water sensor (OMD-32) based on the principle of light scattering for the continuous measurement of oil concentrations in order to optimize the main filtration process parameters that determine membrane performance: the transmembrane pressure and cross-flow velocity. Using the OMD-32 sensor, the oil content of the feed, concentrate and permeate streams was measured continuously and fell within the range 0.0–200 parts per million (ppm) with a resolution of 1.0 ppm. The ceramic membranes achieved an oil-recovery efficiency of up to 98% with less than 1.0 ppm residual oil in the permeate stream, meeting environmental regulations for discharge in most areas.
Correction: Osman, M., et al. A Novel Online Approach for Drift Covariance Estimation of Odometries Used in Intelligent Vehicle Localization. Sensors 2019, 19, 5178
Authors: Osman Mostafa , Hussein Ahmed , Al-Kaff Abdulla , Garcia Fernando , Cao Dongpu
Published: February 2020

The authors wish to make the following corrections to this paper [...]
Accuracy Analysis of Measuring X-Y-Z Coordinates with Regard to the Investigation of the Tombolo Effect
Authors: Masnicki Romuald , Specht Cezary , Mindykowski Janusz , Dąbrowski Paweł , Specht Mariusz
Published: February 2020

Tombolo is a narrow belt connecting the mainland with an island lying near the shore. It is formed as a result of sand and gravel being deposited by sea currents. In consequence, the seabed constantly rises and the shoreline moves towards the sea. This paper deals with accuracy analysis of the undertaken tombolo effect investigation, namely estimation of uncertainty of the measurement results. The aforementioned analysis concerns two methods used for creating a 3D beach model: Firstly, based on geodetic laser scanning (TLS—terrestrial laser scanning) and secondly, using images from unmanned aerial vehicles (UAV). The presented exemplary estimation of uncertainty of the measurement of coordinates X-Y-Z is based on the Polish case study.
Carbon Nanotube Yarn Microelectrodes Promote High Temporal Measurements of Serotonin Using Fast Scan Cyclic Voltammetry
Authors: Mendoza Alexander , Asrat Thomas , Liu Favian , Wonnenberg Pauline , Zestos Alexander G.
Published: February 2020

Carbon fiber-microelectrodes (CFMEs) have been the standard for neurotransmitter detection for over forty years. However, in recent years, there have been many advances of utilizing alternative nanomaterials for neurotransmitter detection with fast scan cyclic voltammetry (FSCV). Recently, carbon nanotube (CNT) yarns have been developed as the working electrode materials for neurotransmitter sensing capabilities with fast scan cyclic voltammetry. Carbon nanotubes are ideal for neurotransmitter detection because they have higher aspect ratios enabling monoamine adsorption and lower limits of detection, faster electron transfer kinetics, and a resistance to surface fouling. Several methods to modify CFMEs with CNTs have resulted in increases in sensitivity, but have also increased noise and led to irreproducible results. In this study, we utilize commercially available CNT-yarns to make microelectrodes as enhanced neurotransmitter sensors for neurotransmitters such as serotonin. CNT-yarn microelectrodes have significantly higher sensitivities (peak oxidative currents of the cyclic voltammograms) than CFMEs and faster electron transfer kinetics as measured by peak separation (ΔEP) values. Moreover, both serotonin and dopamine are adsorption controlled to the surface of the electrode as measured by scan rate and concentration experiments. CNT yarn microelectrodes also resisted surface fouling of serotonin onto the surface of the electrode over thirty minutes and had a wave application frequency independent response to sensitivity at the surface of the electrode.
Automated Home Oxygen Delivery for Patients with COPD and Respiratory Failure: A New Approach
Authors: Sanchez-Morillo Daniel , Muñoz-Zara Pilar , Lara-Doña Alejandro , Leon-Jimenez Antonio
Published: February 2020

Long-term oxygen therapy (LTOT) has become standard care for the treatment of patients with chronic obstructive pulmonary disease (COPD) and other severe hypoxemic lung diseases. The use of new portable O2 concentrators (POC) in LTOT is being expanded. However, the issue of oxygen titration is not always properly addressed, since POCs rely on proper use by patients. The robustness of algorithms and the limited reliability of current oximetry sensors are hindering the effectiveness of new approaches to closed-loop POCs based on the feedback of blood oxygen saturation. In this study, a novel intelligent portable oxygen concentrator (iPOC) is described. The presented iPOC is capable of adjusting the O2 flow automatically by real-time classifying the intensity of a patient’s physical activity (PA). It was designed with a group of patients with COPD and stable chronic respiratory failure. The technical pilot test showed a weighted accuracy of 91.1% in updating the O2 flow automatically according to medical prescriptions, and a general improvement in oxygenation compared to conventional POCs. In addition, the usability achieved was high, which indicated a significant degree of user satisfaction. This iPOC may have important benefits, including improved oxygenation, increased compliance with therapy recommendations, and the promotion of PA.
Attack Detection Using Network Coding in IoT Environment
Authors: Lee Yong , Lee Goo Yeon
Published: February 2020

Network coding is a reasonable way to increase network efficiency in response to an increase of sensed data in the Internet of Things (IoT). In network coding, intermediate nodes combine packets received from neighboring nodes, transform, and transmit encoded packets that can be decoded at the destination. This scheme is based on trust among nodes. If any malicious node joins the network, it can act as an intermediate node that could fabricate encoded packets. It might be more difficult to identify the authenticity of such encoded packets since packets that are received at the destination might not originate from a single source, but be combined with several other packets originating from multiple sources. In this paper, we propose a scheme on how to detect attacked packets among the received packets at a destination and how to recover the original message from the packets including the attacked “look-like-valid” packets. This scheme shows that a destination could recover the valid message with just the received packets including some attacked packets and will result in a quite efficient performance in network coding.
Determining the Online Measurable Input Variables in Human Joint Moment Intelligent Prediction Based on the Hill Muscle Model
Authors: Xiong Baoping , Zeng Nianyin , Li Yurong , Du Min , Huang Meilan , Shi Wuxiang , Mao Guojun , Yang Yuan
Published: February 2020

Introduction: Human joint moment is a critical parameter to rehabilitation assessment and human-robot interaction, which can be predicted using an artificial neural network (ANN) model. However, challenge remains as lack of an effective approach to determining the input variables for the ANN model in joint moment prediction, which determines the number of input sensors and the complexity of prediction. Methods: To address this research gap, this study develops a mathematical model based on the Hill muscle model to determining the online input variables of the ANN for the prediction of joint moments. In this method, the muscle activation, muscle-tendon moment velocity and length in the Hill muscle model and muscle-tendon moment arm are translated to the online measurable variables, i.e., muscle electromyography (EMG), joint angles and angular velocities of the muscle span. To test the predictive ability of these input variables, an ANN model is designed and trained to predict joint moments. The ANN model with the online measurable input variables is tested on the experimental data collected from ten healthy subjects running with the speeds of 2, 3, 4 and 5 m/s on a treadmill. The variance accounted for (VAF) between the predicted and inverse dynamics moment is used to evaluate the prediction accuracy. Results: The results suggested that the method can predict joint moments with a higher accuracy (mean VAF = 89.67±5.56 %) than those obtained by using other joint angles and angular velocities as inputs (mean VAF = 86.27±6.6%) evaluated by jack-knife cross-validation. Conclusions: The proposed method provides us with a powerful tool to predict joint moment based on online measurable variables, which establishes the theoretical basis for optimizing the input sensors and detection complexity of the prediction system. It may facilitate the research on exoskeleton robot control and real-time gait analysis in motor rehabilitation.
Experiment of Structural Geometric Morphology Monitoring for Bridges Using Holographic Visual Sensor
Authors: Shao Shuai , Zhou Zhixiang , Deng Guojun , Du Peng , Jian Chuanyi , Yu Zhongru
Published: February 2020

To further improve the precision and efficiency of structural health monitoring technology and the theory of large-scale structures, full-field non-contact structural geometry morphology monitoring is expected to be a breakthrough technology in structural safety state monitoring and digital twins, owing to its economic, credible, high frequency, and holographic advantages. This study validates a proposed holographic visual sensor and algorithms in a computer-vision-based full-field non-contact displacement and vibration measurement. Using an automatic camera patrol experimental device, original segmental dynamic and static video monitoring data of a model bridge under various damage/activities were collected. According to the temporal and spatial characteristics of the series data, the holographic geometric morphology tracking algorithm was introduced. Additionally, the feature points set of the structural holography geometry and the holography feature contours were established. Experimental results show that the holographic visual sensor and the proposed algorithms can extract an accurate holographic full-field displacement signal, and factually and sensitively accomplish vibration measurement, while accurately reflecting the real change in structural properties under various damage/action conditions. The proposed method can serve as a foundation for further research on digital twins for large-scale structures, structural condition assessment, and intelligent damage identification.
Online Correction Method for the Registration Error between TSMFTIS Detector and Interferogram
Authors: Cao Jun , Yuan Yan , Su Lijuan , Zhu Conghui , Yan Qiangqiang
Published: February 2020

Temporally-spatially modulated Fourier transform imaging spectrometers (TSMFTISs) provide high-throughout-type push-broom spectrometry with both temporal and spatial modulation features. The system requires strict registration between the detector and the interferogram. However, registration errors are unavoidable and directly change the corresponding optical path difference values of the interferogram. As a result, the interferogram should be corrected before restoring the spectrum. In order to obtain the correct optical path difference (OPD) values, an online registration error correction method based on robust least-square linear fitting is presented. The model of the registration error was constructed to analyze its effect on the reconstructed spectra. Fitting methods were used to obtain correct optical path difference information. Simulations based on the proposed method were performed to determine the influence of the registration error on the restored spectra and the effectiveness of the proposed correction method. The simulation results prove that the accuracy of the recovered spectrum can be improved after correcting the interferogram deviation caused by the registration error. The experimental data were also corrected using the proposed methods.
Design of Signal Generators Using Active Elements Developed in I3T25 CMOS Technology Single IC Package for Illuminance to Frequency Conversion
Authors: Sotner Roman , Jerabek Jan , Polak Ladislav , Kledrowetz Vilem , Prokop Roman
Published: February 2020

This paper presents a compact and simple design of adjustable triangular and square wave functional generators employing fundamental cells fabricated on a single integrated circuit (IC) package. Two solutions have electronically tunable repeating frequency. The linear adjustability of repeating frequency was verified in the range between 17 and 264 kHz. The main benefits of the proposed generator are the follows: A simple adjustment of the repeating frequency by DC bias current, Schmitt trigger (threshold voltages) setting by DC driving voltage, and output levels in hundreds of mV when the complementary metal-oxide semiconductor (CMOS) process with limited supply voltage levels is used. These generators are suitable to provide a simple conversion of illuminance to frequency of oscillation that can be employed for illuminance measurement and sensing in the agriculture applications. Experimental measurements proved that the proposed concept is usable for sensing of illuminance in the range from 1 up to 500 lx. The change of illuminance within this range causes driving of bias current between 21 and 52 μA that adjusts repeating frequency between 70 and 154 kHz with an error up to 10% between the expected and real cases.
Fabrication of Anti-HSV-1 Curcumin Stabilized Nanostructured Proniosomal Gel: Molecular Docking Studies on Thymidine Kinase Proteins
Authors: El-Halim Shady M. Abd , Mamdouh Mohamed A. , El-Haddad Alaadin E. , Soliman Sara M.
Published: February 2020

Curcumin is a dietary compound with accrued evidence of antiviral activity. Poor solubility and permeation renders curcumin a good applicant for incorporation into proniosomes. The intent of this study was to formulate curcumin proniosomal gel for topical application and the evaluation of its in-vitro, ex-vivo activities against Herpes Simplex virus type 1 (HSV-1), as well as molecular docking studies on HSV-1 thymidine kinase proteins. Coacervation phase separation tactic, using 23 full factorial design, was used in the preparation of different proniosomes. Cytotoxicity of the selected formulae (F4 and F8) was evaluated on the Vero cell line. Optimal formulae (F4 and F8) showed entrapment efficiency of 97.15 ± 2.47% and 95.85 ± 2.9%, vesicle size of 173.7 ± 2.26 nm and 206.15 ± 4.17 nm and percentages curcumin released after 3 h of 51.9 ± 1.4% and 50.5 ± 1.1%, respectively. Ex-vivo permeation studies demonstrated that the optimal formulae markedly improved the dermal curcumin delivery. Curcumin proniosomal gel formulae exhibited 85.4% reduction of HSV-1 replication. The ability of curcumin to interact with the key amino acids in the enzyme binding sites of 1KI7, 1KI4, and 1E2P, as indicated by its docking pattern, rationalized its observed activity. Therefore, curcumin proniosomes could be considered as a successful topical delivery system for the treatment of HSV-1.
Temporal and Spatial Differences in the Resilience of Smart Cities and Their Influencing Factors: Evidence from Non-Provincial Cities in China
Authors: Dong Xiaojun , Shi Tao , Zhang Wei , Zhou Qian
Published: February 2020

Based on the sample data of 81 non-provincial smart cities in China in 2017, the comprehensive evaluation index of the resilience of sample cities is calculated by using the entropy method, and the spatial differences of different factors on the resiliency are analyzed by using the geographical weighted regression (GWR) model. The conclusions are as follows: Firstly, the comprehensive evaluation index of the resilience of smart cities presents a spatial distribution characteristic of decreasing from the east to the west. At the same time, the resilience comprehensive index, the public infrastructure resilience capacity index, the economic development resilience index, the social security resilience index, and the ecological environment resilience index of smart cities have obvious agglomeration effects on their geographical spaces. Secondly, the public infrastructure resilience capacity index and the ecological environment resilience index are both low with a discrete distribution, while the economic development resilience index and the social security resilience index are both high with a concentrated distribution. Thirdly, different factors have significantly positive effects on the resilience of smart cities. In particular, the public infrastructure capacity resilience index decreases from the north to the south with the spatial distribution pattern of concentration, the economic development resilience index and the ecological environment resilience index of smart cities decrease from the east to the west with a concentrated spatial distribution pattern, and the social security resilience index of smart cities decreases from the southwest to the northeast with a concentrated spatial distribution pattern. Therefore, it is necessary to enhance awareness of smart cities, strengthen the driving force of science and technology innovation, strengthen public infrastructure and service construction, and continuously improve the rapid resilience of smart cities.
Deltas in Crisis: From Systems to Sophisticated Conjunctions
Authors: Jensen Casper Bruun , Morita Atsuro
Published: February 2020

In recent years, threatened deltas have emerged as a significant matter of concern in numerous fields. While Earth System science and social-ecological systems focus on topics like global water circulation and sediment transport, social scientists tend to consider the problems facing particular deltas in the context of modernization or (post)-colonial development. There is nevertheless broad agreement that the delta crisis raises fundamental questions about modern approaches to infrastructure planning. Thus, environmental and sustainability scientists have come to recognize “the social” as integral to the delta crisis. This understanding of “the social,” however, takes two quite different forms. As an object of social-ecological systems research, the social is modeled alongside ecological systems. However, as a context for scientific interventions in environmental policy it appears as an obstacle to achieving sustainable delta policies. Based on a careful examination of Earth System science and associated discourses, we show that this instability of “the social”, combined with the ambition to integrate ‘it’ in an encompassing system poses serious problems for interdisciplinary delta research and for more imaginative and inclusive collaborative efforts to tackle the delta crisis—including, but going considerably beyond, policy and governance. Rather than integrative systems, we argue that the situation requires the creation of sophisticated conjunctions of epistemologies, methods, and practices. Such conjunctions, we suggest, pave the way for a cosmo-ecological approach, where social, environmental and sustainability sciences work together with designers, urban planners, policy-makers, and affected or concerned citizens on solving multi-scalar delta problems by working across their differences.
Strategic Planning and Management Model for the Regeneration of Historic Urban Landscapes: The Case of Historic Center of Novi Pazar in Serbia
Authors: Muminović Esad , Radosavljević Uroš , Beganović Džemila
Published: February 2020

The purpose of this paper is to identify the role of strategic planning as a sustainable tool for regulating both the protection and development of historic urban landscapes, as well as developing an adequate and effective strategic model and management instruments for implementation. The role and importance of strategic planning are examined in the context of global transformative actions in the urban governance of community and private sector engagement and sustainable development on the local level. We argue that a specific—tailor-made—integrated strategic urban planning approach could be a useful model, both for development and urban regeneration and for the preservation of protected valuable historic urban landscapes, thus contributing to a sustainable urban revival of wider surrounding territories including cultural, social and economic development. We stand on the position that the sustainable approach to the protection and revitalization of the historic urban landscapes has to be in line with the acknowledgment of specific local community values, contemporary needs, their involvement, and, eventually, their satisfaction. The case study method was based on the example of a protected historic center of Novi Pazar in Serbia to test the possibilities of applying strategic planning model and management for the implementation tailored to the local context. Eventually, the scenario method was applied to test the possibilities of a simulation of the strategic planning model and management instruments for a protected historic center. We found that the appropriate combination and utilization of regulatory, economic and informational management instruments have to be in place in the specific context. We conclude and draw out theoretical and practical remarks from our research that integrated strategic urban planning model should consider the logic and the functioning of the competitive real estate markets, and the sustainable environmental, economic and social effects, potentials and benefits for the locality where they originate, in order to be utilized as the new generative value both for the protection and for the revival of historic city centers. The paper develops a conceptual strategic planning and management model for the regeneration of historic urban landscapes that capture the physical, environmental, economic, and social effects and indicators of a given space. Based on this input, an adequate initial stage of the conceptual strategy by the authors of the paper was developed for the regeneration of the historic urban city center.
Decoupling Elasticity and Driving Factors of Energy Consumption and Economic Development in the Qinghai-Tibet Plateau
Authors: Fan Weiguo , Meng Mengmeng , Lu Jianchang , Dong Xiaobin , Wei Hejie , Wang Xuechao , Zhang Qing
Published: February 2020

Decoupling of energy consumption and economic development is a key factor in achieving sustainable regional development. The decoupling relationship between energy consumption and economic development in the Qinghai-Tibet Plateau region is still unclear. This paper uses the logarithmic mean Divisia index (LMDI) decomposition method and Tapio elastic index model to analyze the decoupling degree and driving factors of energy consumption and economic development, and evaluates the decoupling effort level in Qinghai-Tibet Plateau from 2006 to 2016. The results indicate that the Qinghai-Tibet Plateau region showed a weak decoupling as a whole, and that only Tibet experienced expanding negative decoupling in 2006–2007 and an expansion link in 2007–2008. Economic scale is a primary factor that hinders the decoupling of energy consumption, followed by investment intensity and industrial energy structure. The cumulative promotion effect of research and development (R&D) efficiency and intensity and the inhibition effect of investment intensity cancel each other out. With the exception of Tibet and Xinjiang, all provinces in the Qinghai-Tibet plateau have made decoupling efforts. Decoupling efforts made by R&D efficiency contributed the most, followed by energy intensity and R&D intensity. This paper provides policy recommendations for the decoupling of energy consumption experience for underdeveloped regions.
Benchmarking Energy Use at University of Almeria (Spain)
Authors: Chihib Mehdi , Salmerón-Manzano Esther , Manzano-Agugliaro Francisco
Published: February 2020

Several factors impact the energy use of university campus buildings. This study aims to benchmark the energy use in universities with Mediterranean climates. The University of Almeria campus was used as a case study, and different types of buildings were analyzed. The second goal was to model the electricity consumption and determinate which parameter correlate strongly with energy use. Macro-scale energy consumption data during a period of seven years were gathered alongside cross-sectional buildings information. Eight years of daily outdoor temperature data were recorded and stored for every half hour. This dataset was eventually used to calculate heating and cooling degree-days. The weather factor was recognized as the variable with the greatest impact on campus energy consumption, and as the coefficient indicated a strong correlation, a linear regression model was established to forecast future energy use. A threshold of 8 GWh has been estimated as the energy consumption limit to be achieved despite the growth of the university. Finally, it is based on the results to inform the recommendations for decision making in order to act effectively to optimize and achieve a return on investment.
A Study on the Potential Fertilization Effects of Microgranule Fertilizer Based on the Protein and Calcined Bones in Maize Cultivation
Authors: Balawejder Maciej , Szostek Małgorzata , Gorzelany Józef , Antos Piotr , Witek Grzegorz , Matłok Natalia
Published: February 2020

In the presented manuscript, the method of production, mechanism of action and the potential fertilizing effect of fertilizer soil microgranules, characterized by a controlled release of ingredients, that were produced from thermally processed bone waste and protein were described. The prepared fertilizer was tested in 3 doses in a pot experiment and thereafter the selected dose of 30 kg ha−1 was utilized in field conditions. The applied dose of fertilizer caused an average increase of maize yield of 620 kg ha−1 (grain moisture 14%). It was found that the obtained increase of maize did not result from the amount of supplied micro and macro elements to the soil, but it was a consequence of the fertilizer’s mechanism of action. It was shown that the release of nitrogen in ammonium form from protein degradation due to the influence of fertilizer components and water had impact on the intensive growth and development of plant root system. This resulted in an increase in plant resistance to water stress during the growing season and consequently, greater yield. The developed soil fertilizer (produced mainly from the processed waste) with the proposed mechanism of action should be successfully applied in fertilizing plants that are grown in areas characterized by cyclical water shortages during the growing season
What Causes Different Sentiment Classification on Social Network Services? Evidence from Weibo with Genetically Modified Food in China
Authors: Li Youzhu , Gao Xianghui , Du Mingying , He Rui , Yang Shanshan , Xiong Jason
Published: February 2020

(1) Background Genetic Modification (GM) refers to the transfer of genes with known functional traits into the target organism, and ultimately the acquisition of individuals with specific genetic traits. GM technology in China has developed rapidly. However, the process is controversial; thus, future development may be hindered. China has become the world’s largest importer of GM products. Research on the attitudes towards GM food in China will help the government achieve sustainable development by better understanding and applications of the technology. (2) Methods This research utilizes data from Sina Weibo (microblog), one of the biggest social network services (SNS) in China. By using the self-created Python crawler program, comments related to the genetically modified food in the People’s Daily account are analyzed. Sentiment classifications are analyzed via multivariate logistic regression. (3) Results Based on the factor analysis, theme type characteristics, the propagation characteristics, the body information characteristics, and the comment characteristics have different degrees of influence on the user’s emotional distribution. (4) Conclusion Practical implications and conclusions are provided based on the results at the end.
Trade Agreements and Global Value Chains: New Evidence from China’s Belt and Road Initiative
Authors: Peng Fei , Kang Lili , Liu Taoxiong , Cheng Jia , Ren Luxiao
Published: February 2020

This paper investigates the relationship between China’s trade agreements (TAs) and partner countries’ upgrade in global value chains (GVCs). We focus on the experience of China and relate China’s TAs with one belt and one road (OBOR) initiative. A structural equation model (SEM) is applied on a dataset including 216 countries and regions to identify the direct and indirect effects of China’s TAs and OBOR initiative on its export, outwards foreign direct investment (OFDI) and partner economy’ GVCs upgrade over the period 2010–2015. We find that China’s TA partner countries are more likely to be included in the OBOR initiative than those non-TA partner countries. The positive effects of China’s TAs and OBOR initiative on China’s export, outwards foreign direct investment (OFDI) and partner countries’ upgrade in GVCs differ across country groups at the different locations of GVCs. Both vertical and horizontal spillover effects exist in China’s TAs. Therefore, the partner countries at low end and middle of GVCs might benefit more from TAs with China than those richer countries at the high end of GVCs.
Impact of Innovation Culture, Organization Size and Technological Capability on the Performance of SMEs: The Case of China
Authors: Tang GuoXiang , Park Kwangtae , Agarwal Anurag , Liu Feng
Published: February 2020

Small and medium-sized enterprises (SMEs) in both the manufacturing and service sectors have been viewed as an important driving force behind the rapid economic growth in China. There are multiple factors that drive the success of SMEs. In this paper, we study the effect of innovation culture, technological capability, and organization size on the performance of SMEs in China. We hypothesize that firm performance is positively affected by each of these factors. We use data from 1124 SMEs in China and apply regression analysis to test our hypotheses. We find that technological capability and organization size have a statistically positive effect on the performance of SMEs. Because manufacturing and service industries have distinct characteristics, we also compare the effects of these factors on firm performance within these industries. We find that technological capability is positively and statistically significantly related to firm performance in the manufacturing industry but not in the service industry, while innovation culture is positively and statistically significantly related to firm performance in the service industry but not in the manufacturing industry.
Malmquist Indexes of Productivity Change in Tunisian Manufacturing Industries
Authors: Zrelli Houyem , Alsharif Abdullah H. , Tlili Iskander
Published: February 2020

This research aims to investigate the extent and nature of productivity growth in manufacturing industries using nonparametric frontier techniques. In order to decompose the total factor productivity (TFP) into technical efficiency change and technological change we use the output-oriented Malmquist productivity index method for 34 Tunisian manufacturing industries over the period 2002–2016. The results indicated that TFP has witnessed an average growth of two percent over the period 2002–2016. The productivity growth identified was attributed to the improvements in the technology (or frontier-shift) rather than improvements or changes in the efficiency.