bluuebunny/crossref_metadata_2025 huggingface dataset:
Uncertainty Assessment of Differential Absorption Lidar Measurements of Industrial Emissions Concentrations
Authors: Innocenti Fabrizio , Gardiner Tom , Robinson Rod
Published: September 2022

Differential absorption lidar (DIAL) has been shown to be a very effective technique for the location and quantification of emissions of pollutants and greenhouse gases at industrial facilities. Several field trials have demonstrated the DIAL system performances and contributed to the development of the DIAL methodology, which is the basis of the protocols described in the European Standard EN 17628. While numerous papers have focused on different aspects of DIAL uncertainties, a rigorous propagation of the uncertainties in the DIAL equation has not been found. In this study, all the uncertainty sources contributing to a DIAL concentration measurement are assessed and the impact they have on the calculation of the mass emission rate. We derive the equations for both a DIAL system path-concentration integral and concentration uncertainties. The results from a methane measurement are presented, showing that for a signal to noise ratio on the backscattered lidar signals of 500, the path-concentration integral standard uncertainty is 2.3 ppb km and the concentration standard uncertainty is 92 ppb over a sampling spacing of 45 m. An equation is also presented enabling calculation of the contribution of the concentration uncertainty to the mass emission rate uncertainty.
Contributions of Climate Change, Vegetation Growth, and Elevated Atmospheric CO2 Concentration to Variation in Water Use Efficiency in Subtropical China
Authors: Xiao Jianyong , Xie Binggeng , Zhou Kaichun , Li Junhan , Xie Jing , Liang Chao
Published: September 2022

Ecosystem water use efficiency (WUE) plays an important role in maintaining the carbon assimilation–water transpiration balance in ecosystems. However, spatiotemporal changes in WUE in the subtropical region of China (STC) and the impact of driving forces remain unclear. In this study, we analyzed the spatiotemporal variation in WUE in the STC and used ridge regression combined with path analysis to identify direct and indirect effects of climate change, vegetation growth, and elevated atmospheric CO2 concentration (Ca) on the interannual trend in WUE. We then quantified the actual and relative contributions of these drivers to WUE change based on the sensitivity of these variables on WUE and the trends of the variables themselves. Results reveal a mean WUE of 1.57 g C/m2/mm in the STC. The annual WUE series showed a descending trend with a decline rate of 0.0006 g C/m2/mm/year. The annual average temperature (MAT) and leaf area index (LAI) had strong positive direct effects on the WUE, while the vapor pressure deficit (VPD) had a strong negative direct effect. Opposite direct and indirect effects offset each other, but overall there was a total positive effect of Ca and VPD on WUE. In terms of actual contribution, LAI, Ca, and VPD were the main driving factors; LAI caused WUE to increase by 0.0026 g C/m2/mm/year, while Ca and VPD caused WUE to decrease by 0.0021 and 0.0012 g C/m2/mm/year, respectively. In terms of relative contribution, LAI dominated the WUE trend, although Ca and VPD were also important factors. Other drivers contributed less to the WUE trend. The results of this study have implications for ecological management and restoration under environmental climate change conditions in subtropical regions worldwide.
A Novel Method for Improving Quality of Oblique Incidence Sounding Ionograms Based on Eigenspace-Based Beamforming Technology and Capon High-Resolution Range Profile
Authors: Zhang Wuyong , Liu Tongxin , Yang Guobin , Jiang Chunhua , Hu Yaogai , Lan Ting , Zhao Zhengyu
Published: September 2022

Ground-based oblique incidence sounding (OIS) is an important means to investigate the ionosphere. As the OIS ionogram is a visual representation of the OIS parameters, such as group distance and maximum usable frequency (MUF), it is of great significance for improving the quality and the range resolution. This will facilitate the automatic interpretation and inversion of OIS ionograms to obtain the fine structure and spatial–temporal evolutions of the ionosphere. In this paper, a novel OIS signal processing scheme is proposed based on the Eigenspace-based (ESB) beamforming technology and Capon high-resolution range profile (HRRP). First, by applying the ESB beamformer to a compact L-shaped antenna array, the energy of the OIS signals received by multiple antennas can be added, while the interference and noise will be suppressed. Subsequently, the Capon HRRP algorithm is used to improve the range resolution. This is achieved due to the slow variation in the characteristics of the ionosphere resulting in good short-term coherence of the narrowband signals. The experimental results show that the two-stage signal-processing method significantly improves the imaging quality of OIS ionograms. In particular, the structure inside the ionosphere and its temporal and spatial evolution can be observed more precisely after the range resolution of the OIS ionogram is improved; therefore, it has great application potential.
Machine Learning-Based Rockfalls Detection with 3D Point Clouds, Example in the Montserrat Massif (Spain)
Authors: Blanco Laura , García-Sellés David , Guinau Marta , Zoumpekas Thanasis , Puig Anna , Salamó Maria , Gratacós Oscar , Muñoz Josep Anton , Janeras Marc , Pedraza Oriol
Published: September 2022

Rock slope monitoring using 3D point cloud data allows the creation of rockfall inventories, provided that an efficient methodology is available to quantify the activity. However, monitoring with high temporal and spatial resolution entails the processing of a great volume of data, which can become a problem for the processing system. The standard methodology for monitoring includes the steps of data capture, point cloud alignment, the measure of differences, clustering differences, and identification of rockfalls. In this article, we propose a new methodology adapted from existing algorithms (multiscale model to model cloud comparison and density-based spatial clustering of applications with noise algorithm) and machine learning techniques to facilitate the identification of rockfalls from compared temporary 3D point clouds, possibly the step with most user interpretation. Point clouds are processed to generate 33 new features related to the rock cliff differences, predominant differences, or orientation for classification with 11 machine learning models, combined with 2 undersampling and 13 oversampling methods. The proposed methodology is divided into two software packages: point cloud monitoring and cluster classification. The prediction model applied in two study cases in the Montserrat conglomeratic massif (Barcelona, Spain) reveal that a reduction of 98% in the initial number of clusters is sufficient to identify the totality of rockfalls in the first case study. The second case study requires a 96% reduction to identify 90% of the rockfalls, suggesting that the homogeneity of the rockfall characteristics is a key factor for the correct prediction of the machine learning models.
Advances in InSAR Imaging and Data Processing
Authors: Zhang Lei , Lu Zhong
Published: September 2022

Through different phases of synthetic aperture radar (SAR) data acquired on different dates and/or at different satellite imaging locations, the interferometric SAR (InSAR) technique has long been used to map ground deformation or generate global digital elevation model (DEM) (e [...]
Homemade Pipette Tip Solid-Phase Extraction for the Simultaneous Determination of 40 Drugs of Abuse in Urine by Liquid Chromatography–Tandem Mass Spectrometry
Authors: Pascual-Caro Sergi , Borrull Francesc , Calull Marta , Aguilar Carme
Published: September 2022

Pipette tip solid-phase extraction facilitates the handling of low-volume samples and organic solvents in order to achieve more environmentally friendly pre-treatment sample techniques. The use of pipette tip extraction was examined for the quick and simple determination of a heterogeneous group of 40 drugs of abuse and some of their metabolites in urine by liquid chromatography coupled to tandem mass spectrometry. Several parameters were studied and optimized, including those which can affect extraction efficiencies, such as the amount of sorbent and the volumes and number of aspirating/dispensing cycles of the sample and organic solvents. The linear range of this method was between the quantification limit and 75 or 100 ng mL−1. Detection limits between 0.025 and 0.500 ng mL−1 and quantification limits from 0.100 to 1.500 ng mL−1 were achieved, which are adequate to determine the studied compounds in urine from drug users. Finally, in order to prove its suitability in toxicological and forensic analyses, the method was successfully applied to 22 urine specimens from women who were starting a detoxification program. Cocaine was the most frequently detected substance, as its presence or the presence of its main metabolite was found in 86% of the analyzed samples.
Materialism and Immorality: More Urban than Rural?
Authors: Okulicz-Kozaryn Adam
Published: September 2022

Metropolitan areas tend to be materialistic/consumerist, and materialism/consumerism is usually considered immoral. Some literature argues that in cities, in general, there is more vice and immorality. In this study, we empirically explore the relationship between urbanness and materialism/immorality using 1972–2018 US General Social Survey. We find much support for a hypothesis that urbanness is associated with higher materialism and immorality. Seven out of eight measures show some evidence of more materialism/immorality in large cities, and four measures remain significant even in the most oversaturated models. However, we caution, as it is one of the first quantitative studies in the area, that the evidence is provisional. While there is a lot of theory, more empirical quantitative research is needed. The study is associative, not causal, and results may not generalize outside of the US.
Fatigue-Free Force-Velocity and Power-Velocity Profiles for Elite Track Sprint Cyclists: The Influence of Duration, Gear Ratio and Pedalling Rates
Authors: Dunst Anna Katharina , Hesse Clemens , Ueberschär Olaf , Holmberg Hans-Christer
Published: September 2022

Background: Maximal force-velocity (F/v) profiles for track cyclists are commonly derived from ergometer sprints using an isovelocity or isoinertial approach. Previously, an attempt was made to derive maximal F/v profiles from a single maximal 65-m sprint on the cycling track. Hypothesising that this approach may not accurately reflect the fatigue-free F/v profile, we propose an alternative procedure and compare it to the previous method. Moreover, we test for the impact of gear ratio on diagnostic results. Methods: Twelve elite track cyclists completed a high-cadence low-resistance pedalling test on a freestanding roller (motoric test) and two series of three maximal 65-m sprints on a cycling track with different gear ratios. F/v profiles were calculated based on the measured crank force and cadence either during the first 6–7 revolutions (≤6 s) on the track (model I) or were derived from the first 3–4 revolutions (≤3 s) on the track combined with 1 or 2 fatigue-free cycles at cadences above 160 rpm from the motoric test (model II). Results: Although both models exhibit high-to-excellent linearity between force and velocity, the extrapolated isometric force was higher (1507.51 ± 257.60 N and 1384.35 ± 276.84 N; p < 0.002; d = 2.555) and the slope steeper (−6.78 ± 1.17 and −5.24 ± 1.11; p < 0.003, d = −2.401) with model I. An ICC of 1.00 indicates excellent model consistency when comparing the F/v profiles (model II) derived from the different geared sprints. Conclusions: Assuring fatigue-free measurements and including high-cadence data points in the calculations provide valid maximal F/v and P/v profiles from a single acceleration-sprint independent of gear ratio.
Antibiotic Therapy and Athletes: Is the Mitochondrial Dysfunction the Real Achilles’ Heel?
Authors: Puccini Valentina
Published: September 2022

It is widely recognized that athletes consume oral antibiotics almost twice as often as observed in the non-sports population in order to reduce as much as possible the period of inactivity due to bacterial diseases. However, increasing evidences have demonstrated the ability of some classes of antibiotics to induce muscle weakness, pain, and a feeling of fatigue upon resuming physical activity conditions that considerably limit the athletic performance of athletes, ascribable to alterations in the biochemical mechanisms underlying normal musculoskeletal activity, such as mitochondrial respiration. For this reason, tailoring a treatment plan for effective antibiotics that limit an athlete’s risk is paramount to their safety and ability to maintain adequate athletic performance. The present review illustrates and critically analyzes the evidence on the use of antibiotics in sports, deepening the molecular mechanisms underlying the onset and development of muscle–tendon alterations in athletes as well as delineating the pharmacological strategies aimed at counteracting such adverse events.
Implementation of Congestion-Related Controls Improves Runner Density, Flow Rate, Perceived Safety, and Satisfaction during an Australian Running Event
Authors: Peckover Sean , Raineri Aldo , Scanlan Aaron T.
Published: September 2022

This study examined the impact of congestion-related controls on runner density, flow rate, perceived safety, and satisfaction during an Australian running event. Runner congestion was compared between races organized at the Sunshine Coast Marathon and Running Festival in 2019 without controls and in 2021 with added controls, including modifications to the start corral design and use of wave starts. Following a mixed-method design, runner congestion was quantitatively measured via determining runner density and flow rate in the start corrals with video analyses, while post-event surveys were used to gather qualitative evidence regarding the prevalence of congestion and its impact on runner safety and satisfaction. Descriptive analyses for quantitative data showed runner density (1.48–3.01 vs. 0.52–1.20 runners per m2) and flow rate (102–152 vs. 36–59 runners per min per m) were reduced across races with controls. Regarding qualitative data, Wilcoxon–Mann–Whitney rank-sum tests demonstrated a significantly (p < 0.01) lower prevalence of congestion was perceived on course while running, alongside a reduced (p = 0.08) perceived impact of congestion on event satisfaction across races with controls. Furthermore, descriptive analyses for qualitative data showed a reduced proportion of runners indicated the start corrals were “somewhat” to “extremely” (rating of at least 3 on a 5-point scale) congested upon race commencement with controls (64% vs. 75%), and perceived safety (10% vs. 17%) and satisfaction (17% vs. 30%) were “somewhat” to “extremely” impacted by congestion across races with controls. Adopting suitable start corral designs with wave starts may enable race directors to reduce runner congestion to enhance continued participation among the public and viability of their running events.
HEART Hybrid Methods for Assessing Human Reliability in Coal-Fired Thermal Power Plant Process
Authors: Ogmen Akide Cerci , Ekmekci Ismail
Published: September 2022

The assessment of human reliability is crucial in serious processes and operations, such as planned maintenance, unplanned maintenance, and troubleshooting in a coal-fired thermal power plant, as the nature of these processes poses significant threats. When the literature is examined, the evaluation of human reliability in any type of power plant, especially coal-fired thermal power plants, is limited. In order to fill this gap, we systematically assessed human reliability in an accident that occurred during a repair of a tube failure in a boiler in a coal-fired thermal power plant. The HEART (human error assessment and reduction technique) method was used in a hybrid way alongside the fuzzy AHP and SWARA (step weight assessment ratio analysis) methods. Although the HEART method is a practical, understandable, and easy-to-implement human reliability assessment method, the APOE (assessment of the proportion effect) value depends on the decision of a single decision maker. This study aimed to eliminate this deficiency and compare human error possibilities using HEART–fuzzy AHP and HEART–SWARA methods. This hybrid method can be used in the operation of all coal-fired thermal power plants and provides practical contributions to minimize human error.
Biosynthesis of Nanoparticles Using Endophytes: A Novel Approach for Enhancing Plant Growth and Sustainable Agriculture
Authors: Fadiji Ayomide Emmanuel , Mortimer Peter Edward , Xu Jianchu , Ebenso Eno E. , Babalola Olubukola Oluranti
Published: September 2022

Current strategies for increasing food production rely heavily on the use of agrichemicals to improve plant growth and resistance to disease. However, many of these chemicals have been shown to have negative impacts on human health and the environment. Nanotechnology presents itself as one of the promising technologies that can be employed to overcome these challenges, but, in the same way that agrichemicals can be harmful, so too can nanotechnology production lines cause harm. In an effort to produce nanoparticles (NPs) in an environmentally friendly and sustainable manner, biological synthesis pathways using microbes and plants are being explored and developed. Synthesis of NPs using endophytic microbiomes is one of the biological approaches showing great potential, offering environmentally friendly alternatives to current production lines and adding value to agricultural systems. This review presents the current potential of NPs synthesized using endophytic microbiomes (primarily bacteria and fungi) to enhance plant growth and improve disease resistance, ultimately making agriculture more sustainable. The future focus on the exploration of this important technique is advocated.
The Sustainability of International Trade: The Impact of Ongoing Military Conflicts, Infrastructure, Common Language, and Economic Wellbeing in Post-Soviet Region
Authors: Čábelková Inna , Smutka Luboš , Rotterova Svitlana , Zhytna Olesya , Kluger Vít , Mareš David
Published: September 2022

The sustainability of international trade is subject to immense pressure. Apart from obstructed logistics, disruption of production chains and changes in demand, the sustainability of international trade is heavily affected by the sanctions caused by the Russia–Ukraine conflict. This paper studies the factors predicting sustainable international trade in the post-Soviet region. We hypothesize that ongoing conflicts, infrastructure, language integration, geographical proximity, common border, and economic wellbeing significantly impact international trade. Methodologically we rely on linear and hierarchical regressions estimating a set of gravitation models (N = 15 countries—104 trading pairs; 2010–2020). The results suggest that Russian as a primary language and the average density of road networks positively predict bilateral trade volume. The geographical distance, infrastructure differences, military conflicts, and, surprisingly, the pair-average GDP per capita diminish bilateral trade. Countries’ GDP mediates the effect of GDP per capita. The results are robust over time. The results present an important insight into sustainable international trade within the region affected by the numerous military conflicts in the past and the war conflict between Russia and Ukraine nowadays. The rebuilding of Ukrainian transport infrastructure is one of the essential measures from the country’s point of view and a factor supporting internationally sustainable food supply.
Spatio-Temporal Characteristics of the Indo-Pacific Warm Pool and the Corresponding Rain Pool
Authors: Yin Zi , Dong Qing , Xiang Kunsheng , Bian Min
Published: September 2022

The greatest warm body in the world exists in the tropical oceans, which stimulates deep convection, resulting in abundant water vapor and precipitation in the tropical atmosphere. Using multiple SST datasets and related precipitation and atmospheric parameter data, this study examines multi-scale variabilities of the Indo-Pacific warm pool (IPWP) as well as the associated rain pool (IPRP). The results show that the IPWP and IPRP are spatially analogous and have significant increasing trends of intensity and coverage. Seasonal variations of the IPWP and IPRP are the strongest and almost coincident with each other. Our results also confirm previous findings that the most important interannual variations of the IPWP and IPRP are associated with various types of ENSO. The composite analysis reveals that the IPWP’s SST structure is linked to the ENSO-induced trade wind anomaly and that SST structural changes cause changes in the position and intensity of the ascending branch of the Walker circulation, which in turn drives changes in the position and intensity of the IPRP.
Analytical Enumeration of Redundant Data Anomalies in Energy Consumption Readings of Smart Buildings with a Case Study of Darmstadt Smart City in Germany
Authors: Kasaraneni Purna Prakash , Yellapragada Venkata Pavan Kumar , Moganti Ganesh Lakshmana Kumar , Flah Aymen
Published: September 2022

High-quality data are always desirable for superior decision-making in smart buildings. However, latency issues, communication failures, meter glitches, etc., create data anomalies. Especially, the redundant/duplicate records captured at the same time instants are critical anomalies. Two such cases are the same timestamps with the same energy consumption reading and the same timestamps with different energy consumption readings. This causes data inconsistency that deludes decision-making and analytics. Thus, such anomalies must be properly identified. So, this paper performs an enumeration of redundant data anomalies in smart building energy consumption readings using an analytical approach with 4-phases (sub-dataset extraction, quantification, visualization, and analysis). This provides the count, distribution, type, and correlation of redundancies. Smart buildings’ energy consumption dataset of Darmstadt city, Germany, was used in this study. From this study, the highest count of redundancies is observed as 5060 on 26 January 2012 with the average count of redundancies at the hour level being 211 and the minute level being 7. Similarly, the lowest count of redundancies is observed as 89 on 24 January 2012. Further, out of these 5060 redundancies, 1453 redundancies are found with the same readings and 3607 redundancies are found with different readings. Additionally, it is identified that there are only 14 min out of 1440 min on 26 January 2012 without having any redundancy. This means that almost 99% of the minutes in the day possess some kind of redundancies, where the energy consumption readings were recorded mostly with two occurrences, moderately with three occurrences, and very few with four and five occurrences. Thus, these findings help in enhancing the quality of data for better analytics.
Sentiment Analysis of Consumer Reviews Using Deep Learning
Authors: Iqbal Amjad , Amin Rashid , Iqbal Javed , Alroobaea Roobaea , Binmahfoudh Ahmed , Hussain Mudassar
Published: September 2022

Internet and social media platforms such as Twitter, Facebook, and several blogs provide various types of helpful information worldwide. The increased usage of social media and e-commerce websites is constantly generating a massive volume of data about image/video, sound, text, etc. The text among these is the most significant type of unstructured data, requiring special attention from researchers to acquire meaningful information. Recently, many techniques have been proposed to obtain insights from these data. However, there are still challenges in dealing with the text of enormous size; therefore, accurate polarity detection of consumer reviews is an ongoing and exciting problem. Due to this, it is challenging to derive exact meanings from the textual data from consumer reviews, comments, tweets, posts, etc. Previously, a reasonable amount of work has been conducted to simplify the extraction of exact meanings from these data. A unique technique that includes data gathering, preprocessing, feature encoding, and classification utilizing three long short-term memory variations is presented to address sentiment analysis problems. Analysing appropriate data collection, preprocessing, and classification is crucial when interpreting such data. Different textual datasets were used in the studies to gauge the importance of the suggested models. The proposed technique of predicting sentiments shows better, or at least comparable, results with less computational complexity. The outcome of this work shows the significant importance of sentiment analysis of consumer reviews and social media content to obtain meaningful insights.
Electric Vehicle Owners’ Perception of Remanufactured Batteries: An Empirical Study in China
Authors: Chinen Kenichiro , Matsumoto Mitsutaka , Tong Pingsheng , Han Yongliang Stanley , Niu Kuei-Hsien Jeff
Published: September 2022

The proliferation of electric vehicles (EVs) globally is remarkable progress in strides toward a low carbon society. However, the volume of end-of-life EV batteries will hit a critical mass in the future. Widespread adoption of EV battery remanufacturing is essential in achieving higher resource efficiency. The current study investigated Chinese EV owners’ perceptions of remanufactured EV batteries: 420 respondents in China who own and drive EVs participated in the survey. This study modeled respondents’ acceptance, purchase intention, and willingness-to-pay for remanufactured EV batteries by adapting the structural equation model (SEM). The results showed that consumers’ price consciousness and perceived benefits both directly influence their purchase intention of remanufactured batteries. Unlike previous studies, this study found that consumers’ perceived risks on remanufactured batteries do not directly influence their purchase intention. Instead, the influence of perceived risks on purchasing behavior is mediated by perceived benefits. The study also found that purchase intention affects willingness to pay and acceptance of remanufactured batteries. Drawing on our study results, this research suggests measures to promote markets for remanufactured EV batteries and provides corporate marketing options to accelerate proliferation of remanufactured batteries.
Towards a Decision-Making Approach of Sustainable Water Resources Management Based on Hydrological Modeling: A Case Study in Central Morocco
Authors: Alitane Abdennabi , Essahlaoui Ali , Van Griensven Ann , Yimer Estifanos Addisu , Essahlaoui Narjisse , Mohajane Meriame , Chawanda Celray James , Van Rompaey Anton
Published: September 2022

Water is one of the fundamental resources of economic prosperity, food security, human habitats, and the driver of many global phenomena, such as droughts, floods, contaminated water, disease, poverty, and hunger. Therefore, its deterioration and its inadequate use lead to heavy impacts on environmental resources and humans. Thus, we argue that to address these challenges, one can rely on hydrological management strategies. The objective of this study is to simulate and quantify water balance components based on a hydrologic model with available data at the R’Dom watershed in Morocco. For this purpose, the hydrologic model used is the Soil and Water Assessment Tool + (SWAT+) model. The streamflow model simulations were run at the monthly time step (from 2002 to 2016), during the calibration period 2002–2009, the coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) values were 0.84 and 0.70, respectively, and 0.81 and 0.65, respectively, during the validation period 2010–2016. The results of the water balance modeling in the watershed during the validation period revealed that the average annual precipitation was about 484 mm, and out of this, 5.75 mm came from the development of irrigation in agricultural lands. The evapotranspiration accounted for about 72.28% of the input water of the watershed, while surface runoff (surq_gen) accounted for 12.04%, 11.90% was lost by lateral flow (latq), and 4.14% was lost by groundwater recharge (perco). Our approach is designed to capture a real image of a case study; zooming into other case studies with similar environments to uncover the situation of water resources is highly recommended. Moreover, the outcomes of this study will be helpful for policy and decision-makers, and it can be a good path for researchers for further directions based on the SWAT model to simulate water balance to achieve adequate management of water resources.
Optimization of Ultrasonic-Assisted Enzymatic Extraction of Freeze-Dried Sea Buckthorn (Hippophae rhamnoides L.) Berry Oil Using Response Surface Methodology
Authors: Kumar T. Ashrith , Pareek Sunil , Kaur Ramanpreet , Sagar Narashans Alok , Singh Lochan , Sami Rokayya , Aljuraide N. I. , Elhakem Abeer , Alsharari Zayed D. , Alruwais Raja Saad , Aljabri Mahmood D. , Rahman Mohammed M.
Published: September 2022

The ultrasound-assisted extraction (UAE) of oil has received immense importance nowadays because of the enormous benefits the process offers. However, the literature evaluating this process is scarce for sea buckthorn oil. Furthermore, to date, to the best of our knowledge, a study evaluating the combined use of enzymes and UAE for this oil is lacking. In this study, oil from freeze-dried sea buckthorn berries was extracted using ultrasound-assisted enzymatic extraction (UAEE) and the effect of variables (time, enzyme concentration, and solvent to sample ratio) was evaluated on oil yield and its physiochemical properties (acid value, peroxide value, iodine value, density, and color). The optimum conditions were determined using the response surface methodology. The optimum conditions established were 5.08 mL/g, 14.65 min, and 3.13 U/g for a solvent to sample ratio, ultra-sonication time, and enzyme units, respectively. The oil yield was 18.32%. Physicochemical parameters were found better in UAEE oil than in the Soxhlet-extracted oil. Gas chromatography detected relatively higher levels of fatty acids, including palmitic, palmitoleic, and oleic acids in UAEE oil. The optimum conditions were also verified for adequacy by validation and results were matched with predicted values with 0.8 to 1.5 error %, which states that the model can be utilized to predict oil yield percentage.
The Limited Responses of Provincial Expressway Network Operation Quality to the Impact of COVID-19: Taking Shaanxi Province as an Example
Authors: Ma Yongji , Xu Jinliang , Gao Chao , Gu Chenwei , Tong Xiaohui
Published: September 2022

Recent research indicates that the coronavirus disease 2019 (COVID-19) pandemic has impacted road traffic operation quality. From the perspective of service level, safety level, and operation orderliness, this study attempts to analyze the limited responses of the operation quality of the provincial expressway network (PEN) to the impact of COVID-19. The traffic operation data of the PEN in Shaanxi Province were collected for three consecutive years (from 2019 to 2021) before and after the COVID-19 outbreak, including weekly average daily traffic, weekly traffic interruption times, weekly traffic control time, weekly traffic accidents, weekly traffic injuries, and weekly traffic deaths. Through descriptive statistics and dynamic analysis, we studied the limited responses of the safety and service levels of the PEN to the impact of COVID-19. An evaluation model of operation orderliness of the PEN was established by using dissipative structure theory and entropy theory. Results show that in 2020, the service level, safety level, and operation orderliness of the PEN dropped to their lowest. With the gradual control of pandemic, its negative impacts on the service level and operation orderliness of the PEN gradually decreased but did not recover to the pre-pandemic level. In terms of the safety level, the number of traffic accidents, traffic injuries, and traffic deaths decreased, whereas the traffic accident rate and accident casualty rate remained high. In summary, the operation quality of the PEN in Shaanxi Province has had a limited response to the impact of COVID-19.
Adsorption of Copper and Lead Ions in a Binary System onto Orange Peels: Optimization, Equilibrium, and Kinetic Study
Authors: Afolabi Felicia Omolara , Musonge Paul , Bakare Babatunde Femi
Published: September 2022

Agricultural waste materials have been proven to be efficient for heavy metal sequestration from wastewater. In this paper, the interactive effects of initial concentration, adsorbent dosage, and particle size on the removal of copper and lead ions in a binary system onto orange peels were investigated using a central composite design. The pHpzc of orange peels was determined to be 3.85. The Fourier transform infrared (FTIR) and energy dispersive x-ray (EDX) revealed the functional groups and elemental composition present on the surface of the bio-sorbent, respectively, before and after adsorption. The ANOVA showed a good fit with a coefficient of determination (R2) of 0.973 and 0.993 for Cu and Pb, respectively. The bio-sorption of Cu and Pb increased with increasing adsorbent dosage while the percentage removal of Pb was consistently higher than Cu. The highest percentage removal of Cu and Pb gave 86.27% and 98.85%, respectively. The kinetic and isotherm studies showed that pseudo-second-order and Langmuir isotherm models fitted the experimental data suggesting chemisorption and monolayer adsorption, respectively. The treatment of wastewater is very essential to avoid water scarcity and to achieve the Sustainable Development Goals (SDGs). This study demonstrates the potential of utilizing orange peels as bio-sorbent for the treatment of wastewater containing Cu and Pb ions.
Evolution and Prediction of the Coupling Coordination Degree of Production–Living–Ecological Space Based on Land Use Dynamics in the Daqing River Basin, China
Authors: Liu Qing , Yang Dongdong , Cao Lei
Published: September 2022

Located in China’s Beijing–Tianjin–Hebei region, the Daqing River Basin has a high economic development level. The natural and social conditions within the basin vary greatly, and the spatial configuration of the Production–Living–Ecological Space (PLES) between different sub-regions is unbalanced, with problems and contradictions in the functions of PLES becoming increasingly prominent. This study constructs a PLES classification system for the Daqing River Basin based on multi-period land use data, simulates the future land use evolution of the basin using the Patch-Generating Land Use Simulation (PLUS) model, calculates the coupling degree (CD) coupling coordination degree (CCD) of PLES from 1992 to 2020, and, under the natural trend development scenario (NT), cropland preservation development scenario (CP), and ecological preservation development scenario (EP) of 2030, quantitatively analyses the historical evolution and future direction of the three-life spatial. The results show that: (1) From 1992 to 2020, the area of living space in the Daqing River Basin has increased significantly, while the area of production space and ecological space has decreased significantly. Compared to NT, CP is beneficial to the maintenance of production space, while the EP is beneficial to the maintenance of ecological space. (2) Globally, the CD and the CCD of PLES in the Daqing River Basin show an increasing trend from 1992 to 2010 and a decreasing trend from 2010 to 2020. In 2030, the CD and the CCD of PLES of the three development scenarios decrease significantly compared to 2020; however, the decrease in CP is slight. (3) By region, from 1992 to 2020, the CCD of PLES in the western and eastern parts of the Daqing River Basin increases relatively more, while the central part increases slightly. Compared to 2020, the CCD of PLES in the central part of the Daqing River Basin is predicted to decrease significantly under NT and EP in 2030, while the decrease is slightly less under CP. In all three scenarios, there are some areas where the CCD of PLES increases in the western areas. This study highlights the internal variability of the spatial evolution of PLES in the basin and focuses on the impact of different future development scenarios on the spatial changes of PLES, which can offer an enlightenment for high-quality development and sustainable territorial spatial planning in the Daqing River Basin.
All-Sky Soil Moisture Estimation over Agriculture Areas from the Full Polarimetric SAR GF-3 Data
Authors: Luo Dayou , Wen Xingping , Xu Junlong
Published: September 2022

This study aims to estimate the soil moisture (SM) in all-sky agriculture areas using fully polarimetric synthetic aperture radar (SAR) Gaofen-3 (GF-3) data. The radar vegetation index (RVI) is obtained using the radar SAR data, which overcomes the difficulty that the optical data cannot construct the vegetation index in cloud-covered areas. The RVI is introduced into the water cloud model (WCM) to remove the contribution of vegetation to the total radar backscatter σ0 and obtain the soil backscattering coefficients σsoil0 with HH and VV polarization. Subsequently, σsoil0 and radar frequency data are introduced into the Chen model, and a semi-empirical model of SM estimation is established. The main findings of this study are as follows: (1) Compared with the σ0, the σsoil0 obtained by the WCM has a stronger correlation with the SM. (2) In the cloud covered area, the accuracy of the estimated SM by synergistically using the WCM and the Chen model is ideal. An RMSE of 0.05 and a correlation coefficient (r) of 0.69 are achieved. In this study, the SM estimation method is not affected by clouds, and it shows many advantages for sustainable development, monitoring soil drought degree, and other related research.
Research on Integrated Customer-Side Energy System Planning Method Considering Carbon Emission Reduction
Authors: Liu Cong , Zhang Yongjie
Published: September 2022

With the improvement of the urbanization level, the energy demand of users continues to increase, which also brings a series of problems. Therefore, in order to effectively solve these problems, energy transformation has begun, and the traditional energy supply model is gradually changing to a diversified and coordinated supply of cold, heat, electricity, and gas. The integrated energy system is not only one of the important means for China to realize the energy revolution, but also one of the important carriers to realize China’s dual carbon goal, because it can realize the coupling and synergy between different energy subsystems and reduce carbon, while also saving costs. Integrated energy system planning is one of the core technologies of integrated energy. Because the load demand of the community will change with time, as a result, this paper studies the typical scenario use frequency of different types of equipment, combined with the energy-pricing method, considering the energy factors such as carbon and energy prices and investment capacity; building area, power supply; equipment operation; and construction-cost factors such as natural gas network and reliability. In order to minimize the total life-cycle cost and total carbon emissions, a dual-objective expansion planning optimization model of integrated energy system was established, and an energy pricing model was added to the capacity optimization of equipment planning. Finally, through the determination of typical scenarios, the economic performance and environmental performance of the three scenarios were compared and analyzed to verify the effectiveness and superiority of the planning model.
Can Complete-Novice E-Bike Riders Be Trained to Detect Unmaterialized Traffic Hazards in the Urban Environment? An Exploratory Study
Authors: Meir Anat
Published: September 2022

Although hazard perception is an important skill found to be crucial for negotiating traffic among various types of road users, few studies have systematically investigated e-bike riders’ ability to perceive potential unmaterialized hazardous situations or aimed to enhance these abilities through training. The present study explored the formation of two hazard perception training interventions based upon exposing young complete-novice e-bike riders to a vast array of materialized traffic hazards, with the aim of evaluating their effectiveness in enriching the ability to anticipate unmaterialized hazards. Young complete-novice e-bike riders were allocated into one of two intervention modes (‘Act and Anticipate Training’ or ‘Predictive and Commentary Training’) or a control group (ten in each group). AAT members underwent a theoretical tutorial, then observed clips depicting real-time hazardous situations footage taken from an e-bike rider’s perspective and were asked to perform a hazard detection task. PCT members underwent a theoretical tutorial, then a ‘what might happen next?’ task, followed by observation of video footage with expert commentary. A week later, participants were requested to complete a hazard perception test, during which they viewed ten videos and pressed a response button whenever they identified a hazardous situation. Overall, participants in both interventions were more aware of potential unmaterialized hazards compared to the control in both their response sensitivity and verbal descriptions. Trainees were responsive to the developed training interventions. Thus, actively detecting materialized hazards may produce effective training that enriches these road users’ hazard perception skills and allows them to safely negotiate traffic. Advantages of each of the training methodologies along with implications for intervention strategies, licensing, and policy development are discussed.
Indicators of Geographic Potential and Business Opportunities for the Development of Active Tourism: Kayaking in Poland
Authors: Lewandowicz Elżbieta
Published: September 2022

Poland’s natural and geographical features, including an abundance of rivers and lakes, create favorable conditions for the development of kayaking tourism. Poland is one of the leading European countries in terms of the number of kayaking trails. The aim of this study was to propose indicators for assessing the potential of Poland’s water resources for the development of kayaking activities. This research was pursued in several stages. The number of rivers where kayaking tours are organized was determined in the first stage of the study. Indicators describing the potential of the existing water bodies for the promotion of kayaking tourism were proposed in the second stage. The study produced surprising results. The number of kayaking tour operators has increased considerably in recent years, and new water tourism centers have been established in the vicinity of large urban areas. The popularity of well-established kayaking destinations in Warmia-Masuria, Podlasie and Western Pomerania, i.e., Polish regions with considerable potential for the development of water tourism, has declined. The study revealed that the success of kayaking businesses is presently determined by other factors, and further research is needed to identify these determinants.
Slope Deformation Prediction Based on MT-InSAR and Fbprophet for Deep Excavation Section of South–North Water Transfer Project
Authors: Ding Laizhong , Li Chunyi , Wei Lei , Guo Zengzhang , Jia Pengzhen , Wang Wenjie , Gao Yantao
Published: September 2022

In the operation and maintenance of the South–North Water Transfer Project, monitoring and predicting the canal slope deformation quickly and efficiently is one of the urgent problems to be solved. To predict the slope deformation of the deep excavated canal section at the head of the canal. We propose a new idea of adopting the joint prediction of MT-InSAR and Fbprophet. Firstly, MT-InSAR monitoring technology was used to invert channel deformation using 88 Sentinel-1A orbit-raising image data with a time baseline from 2017 to 2019. The time-series deformation of nine monitoring points was also extracted, and it was found that the time-series curves of the cumulative deformation of the channel slope showed fluctuations. The Fbprophet algorithm was then used to train the prediction model in Python to predict the channel slope deformation over the next 365 days. Finally, the prediction results were compared with the MT-InSAR monitoring values to analyze the prediction accuracy and applicability of the Fbprophet algorithm for the slope deformation monitoring of the South–North Water Transfer Project. The results show that: the deformation rate of the slope of the deep excavation section is in the range of 10 mm/a to 25 mm/a, the maximum accumulated deformation is about 60 mm, and the slope of the excavation canal shows a lifting phenomenon; among the nine monitoring points, the minimum and maximum predicted values of deformation using the machine learning prediction model trained in this paper were 56 mm and 73 mm, respectively; comparing the predicted and monitored values, their correlation coefficients were 0.998 at the highest and 0.988 at the lowest, and the minimum and maximum values of RMSE (RootMean Square Error) were 0.72 mm and 2.87 mm, respectively. It shows that the prediction model trained by the Fbprophet algorithm in this paper applies to the prediction of slope deformation in the deep excavation section, and our prediction results can provide a data reference for disaster prevention and the sustainable development of the South–North Water Transfer Project.
Temporal and Spatial Variation of Vegetation in Net Primary Productivity of the Shendong Coal Mining Area, Inner Mongolia Autonomous Region
Authors: Ke Jia , Zhou Dandan , Hai Chunxing , Yu Yanhua , Jun Hao , Li Bingzi
Published: September 2022

Coal mining can cause significant local environmental damage while driving the regional economy of an area. The key index of net primary productivity (NPP) measures the amount of energy made available in an ecosystem and serves as a useful metric for understanding vegetation restoration in mining areas. This study used a CASA model to estimate the vegetation NPP of the Ordos area of the Shendong coal fields from 2000 to 2019. Model output, human factors, and regional meteorological data were subjected to trend analysis, significance testing, partial correlation analysis, and residual analysis. The NPP data generated by a CASA model inversion approximated measured data to a reasonable degree. The average annual NPP of the vegetation in the study area from 2000 to 2019 was 44.51 g C/m2 a. In general, NPP showed a fluctuating upward trend, with slower increases before 2011 and more rapid increases after 2011. The trend exhibited considerable spatial heterogeneity. Areas with increasing NPP accounted for 21.54% of the study area and occurred mainly in the Dongsheng District, the Kangbashi District, and areas bordering the Ejin Horo Banner. Analysis detected consistent spatial variation between NPP and each factor in the study area. NPP is positively correlated with precipitation and human activities and negatively correlated with air temperature. The change in vegetation cover depended on both human activity and meteorological conditions. In terms of the strength of influence on vegetation NPP, human activity exceeded climate, followed by temperature and precipitation. Although the NPP of vegetation in the region directly affected by coal mining shows a trend of improvement, it is still lower than that in the natural growing region. In the next step, the ecological restoration of vegetation should be further strengthened to achieve regional ecological balance.