bluuebunny/crossref_metadata_2025 huggingface dataset:
Satellite-Based Determination of the Water Footprint of Carrots and Onions Grown in the Arid Climate of Saudi Arabia
Authors: Al-Gaadi Khalid A. , Madugundu Rangaswamy , Tola ElKamil , El-Hendawy Salah , Marey Samy
Published: November 2022

Increasing demand for food, climate change, and other human interventions are leading to significant increases in water consumption by the agricultural sector. This requires rationalizing the water used for the production of agricultural crops through improved irrigation management practices. Therefore, this study aimed to estimate the water footprint (WF) of onion (Allium cepa L.) and carrot (Daucus carota) crops using the CROPWAT model and the SSEB (Simplified Surface Energy Balance) algorithm. Experiments were carried out at two center-pivot irrigated fields belonging to Tawdeehiya Commercial Farms in the southeastern region of the Riyadh governorate, Saudi Arabia. Individual bands and vegetation indices (VIs) were retrieved from Sentinel-2 satellite data, including the normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), optimized soil adjusted vegetation index (OSAVI), renormalized difference vegetation index (RDVI), and enhanced vegetation index (EVI), and the land surface temperatures (LST) extracted from Landsat-8 data were used to estimate crop productivity (CP), crop water use (CWU) (i.e., evapotranspiration—ETa), and crop WF. Crop growth/phenology stages and georeferenced biophysical parameters were recorded during the growth period, and crop yield samples were collected randomly from predetermined sampling locations. It was found that the NIR band was appropriate for predicting onion yield (R2 = 0.68; p > F = 0.02) and carrot yield (R2 = 0.77; p > F = 0.02). The results also showed the feasibility of using the RDVI and EVI to estimate the yields of onion and carrot crops, with bias values of 15% and –17%, respectively. The CWU has also been successfully estimated using the SSEB algorithm, with an overall accuracy of 89%. The SSEB-estimated CWU was relatively high compared to the applied amounts by 10.6% (onions) and 12.6% (carrots). Finally, the crop WF was successfully estimated at 312 m3 t−1 and 230 m3 t−1 for carrots and onions, respectively, with an overall accuracy of 71.11%. The outcomes of this study can serve as a reference for crop irrigation management practices in the study region and areas with similar environmental conditions.
Spatiotemporal Assessment of Forest Fire Vulnerability in China Using Automated Machine Learning
Authors: Ren Hongge , Zhang Li , Yan Min , Chen Bowei , Yang Zhenyu , Ruan Linlin
Published: November 2022

Frequent forest fires cause air pollution, threaten biodiversity and spoil forest ecosystems. Forest fire vulnerability assessment is a potential way to improve the ability of forests to resist climate disasters and help formulate appropriate forest management countermeasures. Here, we developed an automated hybrid machine learning algorithm by selecting the optimal model from 24 models to map potential forest fire vulnerability over China during the period 2001–2020. The results showed forest aboveground biomass (AGB) had a vulnerability of 26%, indicating that approximately 2.32 Gt C/year of forest AGB could be affected by fire disturbances. The spatiotemporal patterns of forest fire vulnerability were dominated by both forest characteristics and climate conditions. Hotspot regions for vulnerability were mainly located in arid areas in western China, mountainous areas in southwestern China, and edges of vegetation zones. The overall forest fire vulnerability across China was insignificant. The forest fire vulnerability of boreal and temperate coniferous forests and mixed forests showed obviously decreasing trends, and cultivated forests showed an increasing trend. The results of this study are expected to provide important support for the forest ecosystem management in China.
A Novel Data-Driven Evaluation Framework for Fork after Withholding Attack in Blockchain Systems
Authors: Zhang Yang , Chen Yourong , Miao Kelei , Ren Tiaojuan , Yang Changchun , Han Meng
Published: November 2022

In the blockchain system, mining pools are popular for miners to work collectively and obtain more revenue. Nowadays, there are consensus attacks that threaten the efficiency and security of mining pools. As a new type of consensus attack, the Fork After Withholding (FAW) attack can cause huge economic losses to mining pools. Currently, there are a few evaluation tools for FAW attacks, but it is still difficult to evaluate the FAW attack protection capability of target mining pools. To address the above problem, this paper proposes a novel evaluation framework for FAW attack protection of the target mining pools in blockchain systems. In this framework, we establish the revenue model for mining pools, including honest consensus revenue, block withholding revenue, successful fork revenue, and consensus cost. We also establish the revenue functions of target mining pools and other mining pools, respectively. In particular, we propose an efficient computing power allocation optimization algorithm (CPAOA) for FAW attacks against multiple target mining pools. We propose a model-solving algorithm based on improved Aquila optimization by improving the selection mechanism in different optimization stages, which can increase the convergence speed of the model solution and help find the optimal solution in computing power allocation. Furthermore, to greatly reduce the possibility of falling into local optimal solutions, we propose a solution update mechanism that combines the idea of scout bees in an artificial bee colony optimization algorithm and the constraint of allocating computing power. The experimental results show that the framework can effectively evaluate the revenue of various mining pools. CPAOA can quickly and accurately allocate the computing power of FAW attacks according to the computing power of the target mining pool. Thus, the proposed evaluation framework can effectively help evaluate the FAW attack protection capability of multiple target mining pools and ensure the security of the blockchain system.
Circular Subaperture Stitching Interferometry Based on Polarization Grating and Virtual–Real Combination Interferometer
Authors: Hu Yao , Wang Zhen , Hao Qun
Published: November 2022

This paper presents a polarization grating based circular subaperture stitching interferometer. The system can be used for small F/# concave surface tests with a large F/# transmission sphere, where F/# is the ratio of focal length to aperture. A polarization grating was employed to deflect the incident beam for subaperture scanning by its axial rotation instead of a multi-axis motion-control system. Compared with the traditional subaperture stitching interferometric system, the system proposed in this paper is smaller in size and reduces the measurement error introduced by mechanical adjustment. Using a virtual interferometer model and a virtual–real combination algorithm to remove the retrace error, the full-aperture figure error can be directly obtained without the need for a complex stitching algorithm. The feasibility of the algorithm was verified, and the measurement error caused by the modeling error was analyzed by simulation. The capability of the polarization grating to scan subapertures was experimentally confirmed, and possible solutions to some engineering challenges were pointed out. The research in this paper has pioneering and guiding significance for the application of polarization grating in interferometry.
Ship Berthing and Unberthing Monitoring System in the Ferry Terminal
Authors: Abramowicz-Gerigk Teresa , Jachowski Jacek
Published: November 2022

This paper presents a monitoring system designed to increase the safety of the quay structure in ferry terminals, in which, during berthing and unberthing maneuvers, propeller and thruster-generated jets may damage the seabed protection, threatening the stability of the berth structure. Direct measurement of flow velocity on the seabed is not possible due to the possibility of its damage, therefore dynamic pressure measurement of the quay wall was used within the system. The relationship between the pressure on the quay wall and flow velocity on the seabed was determined using real-scale CFD simulation of the flow field generated during berthing and unberthing maneuvers. The paper focuses on the computations of the pressure distribution generated by bow thrusters. These computations made it possible to determine the velocity field in the time domain. Their results, verified using real-scale measurements, are in line with generally accepted empirical methods.
Statistical Analysis of Silicon Photomultiplier Output Signals
Authors: Kolka Zdenek , Barcik Peter , Biolkova Viera
Published: November 2022

Silicon photomultipliers are relatively new devices designed as a matrix of single-photon avalanche detectors, which have become popular for their miniature dimensions and low operating voltage. Their superior sensitivity allows detecting low-photon-count optical pulses, e.g., in ranging and LIDAR applications. The output signal of the photomultiplier is a non-stationary stochastic process, from which a weak periodic pulse can be extracted by means of statistical processing. Using the double-exponential approximation of output avalanche pulses the paper presents a simple analytical solution to the mean and variance of the stochastic process. It is shown that even for an ideal square optical pulse the rising edge of the statistically detected signal is longer than the edge of individual avalanche pulses. The knowledge of the detected waveform can be used to design an optimum laser pulse waveform or algorithms for estimating the time of arrival. The experimental section demonstrates the proposed procedure.
Learning with Weak Annotations for Robust Maritime Obstacle Detection
Authors: Žust Lojze , Kristan Matej
Published: November 2022

Robust maritime obstacle detection is critical for safe navigation of autonomous boats and timely collision avoidance. The current state-of-the-art is based on deep segmentation networks trained on large datasets. However, per-pixel ground truth labeling of such datasets is labor-intensive and expensive. We propose a new scaffolding learning regime (SLR) that leverages weak annotations consisting of water edges, the horizon location, and obstacle bounding boxes to train segmentation-based obstacle detection networks, thereby reducing the required ground truth labeling effort by a factor of twenty. SLR trains an initial model from weak annotations and then alternates between re-estimating the segmentation pseudo-labels and improving the network parameters. Experiments show that maritime obstacle segmentation networks trained using SLR on weak annotations not only match but outperform the same networks trained with dense ground truth labels, which is a remarkable result. In addition to the increased accuracy, SLR also increases domain generalization and can be used for domain adaptation with a low manual annotation load. The SLR code and pre-trained models are freely available online.
The 1,3-Dioctadecyl-1H-imidazol-3-ium Based Potentiometric Surfactant Sensor for Detecting Cationic Surfactants in Commercial Products
Authors: Sakač Nikola , Madunić-Čačić Dubravka , Marković Dean , Ventura Bartolomeo Della , Velotta Raffaele , Ptiček Siročić Anita , Matasović Brunislav , Sermek Nikolina , Đurin Bojan , Šarkanj Bojan , Jozanović Marija
Published: November 2022

A low-cost and fast potentiometric surfactant sensor for cationic surfactants, based on the new ion-pair 1,3-dioctadecyl-1H-imidazol-3-ium-tetraphenylborate (DODI-TPB), is presented. The new cationic surfactant DODI-Br was synthesized and characterized by NMR, LC-MS, and elemental analysis, and was used for synthesis of the DODI-TPB ionophore. The DODI-TPB surfactant sensor was obtained by implementation of the ionophore in PVC. The sensor showed excellent response characteristics with near-Nernstian slopes to the cationic surfactants DMIC, CPC, CTAB, and Hyamine 1622. The highest voltage responses were obtained for DMIC and CPC (58.7 mV/decade of activity). DMIC had the lowest detection limit (0.9 × 10−6 M) and the broadest useful linear concentration range (1.8 × 10−6 to 1.0 × 10−4 M). An interference study showed remarkable stability. Potentiometric titration curves for the titration of cationic surfactants (DMIC, CPC, CTAB, and Hyamine 1622), with DDS and TPB used as titrants, showed sigmoidal curves with well-defined inflexion points and a broad signal change. The standard addition method was successfully applied with recovery rates from 98.9 to 101.2 at two concentrations. The amount of cationic surfactant found in disinfectants and antiseptics was in good agreement with the referent two-phase titration method and the surfactant sensor on the market. This new surfactant sensor represents a low-cost alternative to existing methods for cationic surfactant detection.
Feasibility of Ultra-Short-Term Analysis of Heart Rate and Systolic Arterial Pressure Variability at Rest and during Stress via Time-Domain and Entropy-Based Measures
Authors: Volpes Gabriele , Barà Chiara , Busacca Alessandro , Stivala Salvatore , Javorka Michal , Faes Luca , Pernice Riccardo
Published: November 2022

Heart Rate Variability (HRV) and Blood Pressure Variability (BPV) are widely employed tools for characterizing the complex behavior of cardiovascular dynamics. Usually, HRV and BPV analyses are carried out through short-term (ST) measurements, which exploit ~five-minute-long recordings. Recent research efforts are focused on reducing the time series length, assessing whether and to what extent Ultra-Short-Term (UST) analysis is capable of extracting information about cardiovascular variability from very short recordings. In this work, we compare ST and UST measures computed on electrocardiographic R-R intervals and systolic arterial pressure time series obtained at rest and during both postural and mental stress. Standard time–domain indices are computed, together with entropy-based measures able to assess the regularity and complexity of cardiovascular dynamics, on time series lasting down to 60 samples, employing either a faster linear parametric estimator or a more reliable but time-consuming model-free method based on nearest neighbor estimates. Our results are evidence that shorter time series down to 120 samples still exhibit an acceptable agreement with the ST reference and can also be exploited to discriminate between stress and rest. Moreover, despite neglecting nonlinearities inherent to short-term cardiovascular dynamics, the faster linear estimator is still capable of detecting differences among the conditions, thus resulting in its suitability to be implemented on wearable devices.
A Mechanism-Based Automatic Fault Diagnosis Method for Gearboxes
Authors: Xu Lei , Wang Tiantian , Xie Jingsong , Yang Jinsong , Gao Guangjun
Published: November 2022

Convenient and fast fault diagnosis is the key to improving the service safety and maintenance efficiency of gearboxes. However, the environment and working conditions under complex service conditions are variable, and there is a lack of fault samples in engineering applications. These factors lead to difficulties in intelligent diagnosis methods based on machine learning, while traditional mechanism-based fault diagnosis requires high expertise and long time periods for the manual analysis of data. For the requirements of diagnostic convenience, an automatic fault diagnosis method for gearboxes is proposed in this paper. The method achieves accurate acquisition of rotational speed by constructing a rotational frequency search algorithm. The self-referencing characteristic frequency identification method is proposed to avoid manual signal analysis. On this basis, a framework of anti-interference automatic diagnosis is constructed to realize automatic diagnosis of gear faults. Finally, a gear fault experiment is carried out based on a high-fidelity experimental bench of bogie to verify the effectiveness of the proposed method. The proposed automatic diagnosis method does not rely on a large number of fault samples and avoids the need for diagnosis through professional knowledge, thus saving time for data analysis and promoting the application of fault diagnosis methods.
Relationship of Training Factors and Resilience with Injuries in Ski Mountaineers
Authors: Etayo-Urtasun Paula , León-Guereño Patxi , Sáez Iker , Castañeda-Babarro Arkaitz
Published: November 2022

Ski mountaineering is an increasingly popular sport with a relatively high risk of injury. Therefore, several studies have analyzed factors related to the likelihood of injury, including athlete characteristics, training, resilience and equipment. Thus, the aim of this study was to identify factors that may influence injury risk. A 15-minute online survey was sent to various ski mountaineering groups of different ages and levels. Both the Mann–Whitney U test and odds ratio analysis were performed in order to analyze the data. Results from 104 skiers showed that most injuries occurred in the lower extremities, especially in the knee (29.6%). The findings indicated that skiers who had suffered an injury performed in more competitions per year (p = 0.046), more ski mountaineering sessions per week (p = 0.022) and fewer core training sessions per week (0.029), although core training and competition were not statistically significant factors. Likewise, non-injured athletes had fewer pairs of skis (p = 0.019), which were also wider (p = 0.04). However, no difference was found for warm up and resilience between both groups (p = 0.275). In conclusion, it is important to implement preventive measures based on these factors, even if more research is needed.
The Nexus of Industry 4.0 and Circular Procurement: A Systematic Literature Review and Research Agenda
Authors: Rejeb Abderahman , Appolloni Andrea
Published: November 2022

In the wake of Industry 4.0, circular supply chain management has undergone radical transformations. Organizations have been able to boost their efficiency thanks to incorporating Industry 4.0 technologies such as big data analytics, the internet of things (IoT), blockchain, cloud computing, artificial intelligence, etc., into various supply chain functions. Since circular procurement (CP) is an essential part of circular supply chain management, it can provide fresh chances for organizations to become more efficient and sustainable. With the support of Industry 4.0 technologies, CP can provide extra opportunities for accelerating the shift to the circular economy. Although research into the intersection of procurement and Industry 4.0 continues to advance, no review study has examined the implications of Industry 4.0 in CP. Therefore, this research aims to address this knowledge gap by systematically reviewing the existing literature about the applications of Industry 4.0 technologies in CP. A total of 89 journal articles were selected from Scopus and Web of Science databases to identify the themes discussed and set an agenda for future research. A conceptual framework is also developed to evaluate the antecedents, enablers, and performance outcomes of Industry-4.0-enabled CP. Finally, the review concludes by highlighting the theoretical and practical implications.
Mutual Interaction of Daylight and Overheating in the Attic Space in Summer Time
Authors: Katunský Dušan , Vertaľ Marián , Dolníková Erika , Zozuláková Silvia , Hutkai Kristián , Dická Zuzana
Published: November 2022

The classroom space located in the attic of an old building is the subject of this study. The building was renovated and new spaces were created in the unused attic to expand classrooms. The original space under the sloping roof was not used because its internal headroom was not suitable. During the restoration, the entire original truss was raised gradually (in parts) by 1.2 m. This created a space with an entire area that can be used for classrooms. Continuous strips of vertical windows measuring 860/600 mm were installed in the space which enable a visual connection between the interior space and the exterior. At roof level, there are also two rows of skylights above each other which ensure enough daylight is present but create unpleasant overheating in the summer. The purpose of this study is to find a way to optimize the shading of transparent surfaces and the heat accumulation of building structures in order to achieve suitable interior conditions in the attic. This task was achieved by shading the windows in the attic. Shaded windows decrease illumination by 82% compared to unshaded ones. The percentage decrease in illumination is more significant than the decrease in the maximum temperature due to overheating. Additionally, the maximum temperature in the attic drops by only 31% if vertical and skylight windows are shaded with external blinds compared to unshaded windows. The minimum air temperature reached in the attic also drops by 26%. In order for users in the attic space to feel comfortable, it is necessary to use HVAC equipment in addition to the design of suitably built structures and window shading.
Selected Differences and Relationships of Consumers’ Online Brand-Related Activities and Their Motives
Authors: Nastišin Ľudovít , Bačík Radovan , Tomášová Mária , Pavlinský Marek
Published: November 2022

The main goal of the paper is to assess the statistical significance of the differences in the motives and activities of COBRAs in the context of the frequency of use of these platforms and also the driving forces and motivations behind the brand-related activities. The importance of consumers’ online brand-related activities (COBRAs) as relevant factors in managerial and marketing practice is undeniable. In addition, this area is only at the beginning of research coverage, and thus defines a research gap for us. The dataset used hereunder is based on data acquired from a standardized questionnaire discussing the above-mentioned activities and motives. In total, the questionnaire was filled in by 401 respondents. The analysis made use of the Kruskal–Wallis H test to detect differences and the Spearman’s rho coefficient to detect relationships. Based on this, several statistically significant differences and relationships were identified in all cases. The most important implications drawn pertain to differences in the social-interaction motives on all platforms studied, the highest rate of concurrence, at the level of 3–4 h, spent on these platforms, as well as relationships with a strong correlation coefficient in content-creation activities and content-contribution activities on all social media platforms. Even though these findings require further analysis, they prove a valuable insight into the topic.
Isolation of Biosurfactant-Producing Bacteria and Their Co-Culture Application in Microbial Fuel Cell for Simultaneous Hydrocarbon Degradation and Power Generation
Authors: Sharma Kalpana , Singh Vandana , Pandit Soumya , Thapa Bhim Sen , Pant Kumud , Tusher Tanmoy Roy
Published: November 2022

Biosurfactant-producing microorganisms improve the efficacy of hydrocarbon biodegradation as the biosurfactant is essential in making hydrocarbons available for breakdown. The present study reports the isolation of biosurfactant-producing bacteria that can be used for crude oil remediation and to characterize the biosurfactant generated during the breakdown of crude oil. This study also reports evaluating the synergism and potentiality of biosurfactant-producing bacteria for simultaneous hydrocarbon biodegradation and power generation. Two bacterial strains (Bacillus subtilis strain B1 and Pseudomonas aeruginosa strain B2) were isolated from petroleum-contaminated soils, which are found effective in producing biosurfactants and degrading crude oil as the sole carbon source. B. subtilis B1 exhibited a higher potential for biosurfactant production and crude oil degradation than P. aeruginosa B2. The FTIR and GC-MS analysis were conducted for further characterization of the biosurfactant, which revealed that the surfactant produced by strain B1 and B2 was surfactin and rhamnolipid, respectively. The application of the B1 and B2 co-culture in microbial fuel cells (MFCs) showed synergism among them and resulted in a maximum power density production of 6.3 W/m3 with an open circuit voltage of 970 mV while degrading 2.5% v/v crude oil containing anolyte. The findings indicate that the co-culture of isolated crude oil-degrading strains has great potential for enhanced power generation and the bioremediation of hydrocarbon-contaminated environments. Moreover, the synergism of isolated strains in MFCs suggested their potent applicability in environmental, energy, and industrial sectors as an economical and feasible alternative to the existing technologies.
Simulation Study on the Size Effect of Secant Modulus of Rocks Containing Rough Joints
Authors: Sun Mingzhi , Hu Gaojian , Hu Jianli , Zhang Huanqing , Li Yu , Wang Weiping , Zhang Guangbin
Published: November 2022

The secant modulus reflects the ability of rocks to resist deformation, and it is mostly used to evaluate rock strength and deformation evolution. Due to the existence of rough joints in rocks, the secant modulus changes according to rock size. Therefore, it is very important to effectively obtain the secant modulus to evaluate rough-jointed rock deformation. In this paper, the regression analysis method is used, and 25 sets of simulation models are set up to discuss the influence of joint roughness and rock size on the rock secant modulus. The research shows that the secant modulus increases exponentially with the increase in rock size, and it increases as a power function with the increase in joint roughness. The characteristic size of the secant modulus increases exponentially with the increase in joint roughness, also as a power function. This paper gives the specific forms of these four relationships. The establishment of these relationships enables the prediction and calculation of the secant modulus and provides guidance for rock deformation analysis.
Experimental Research on Seismic Behavior of Haunched Concrete Beam–Column Joint Based on the Bolt Connection
Authors: Zhang Yang , Ma Wei , Li Xin , Li Kai
Published: November 2022

Studying the seismic performance of assembled beam–column joints is essential for the development of assembled frame structures. In this paper, a novel dry connection beam–column joint with a high degree of modularity and a simple structure is proposed and tested using a pseudostatic test. The joint is composed of a precast concrete beam with a steel axillary plate at the end and a precast concrete column connected by long bolts. By analyzing the characteristics of the hysteresis curve, skeleton curve, and stiffness degradation curve, we were able to investigate the seismic performance of this novel new joint under low circumferential reciprocating load as well as the impact of bolts of various strength grades on the joint’s seismic performance. The results illustrated the robust overall bearing performance of the newly assembled beam–column joint. However, when connected with common bolts, the joint deforms more, exhibits good ductility, clearly displays semi-rigid characteristics, and performs better in terms of energy dissipation. This contrasts with connecting with low-strength bolts, which cause the joint to deform little and have poor energy dissipation capacity. The prefabricated columns and beams remain undamaged, making it possible to quickly repair the assembled building structure after an earthquake; however, the joints are harmed due to the bending and fracture of the connection bolts. It has been suggested that researchers add damping energy dissipation devices to the new joint to increase its energy dissipation capacity and control the joint’s overall deformation because the joint’s energy dissipation capacity is insufficient under the low circumferential reciprocating load.
Thermal Comfort Assessment of the Perimeter Zones by Using CFD Simulation
Authors: Lim Taesub , Kim Daeung Danny
Published: November 2022

Most perimeter zones are thermally susceptible to the variation of outdoor conditions, especially due to a large amount of heat gain through glazing. To reduce heat gain, spandrel panels are generally installed in curtain walls of commercial buildings. For the present study, thermal performance in an office located in the perimeter zone was investigated using Computational Fluid Dynamics (CFD) simulation. By varying the spandrel panel heights, thermal comfort was assessed quantitatively. The findings suggest that when the spandrel panel height was 0 m, the highest temperature was observed in all cases. As the height of the spandrel panel was increased, the temperature decreased. For thermal comfort evaluation, Predicted Mean Vote (PMV) values at 1.5 m from the floor in all cases were larger than zero. PMV values in all cases were within the range of slightly cool to warm. When the spandrel panel height was 0 m, the highest thermal sensation (warm) among the cases was observed, which may cause thermal dissatisfaction for occupants. In addition, thermal comfort was deemed satisfactory based on the criteria of ASHRAE standard 55, when the height of the spandrel panel was higher than 0.6 m.
Impact of Soil Amendment with Biochar on Greenhouse Gases Emissions, Metals Availability and Microbial Activity: A Meta-Analysis
Authors: Atilano-Camino Marina M. , Canizales Laborin Ana P. , Ortega Juarez Angelita M. , Valenzuela Cantú Ana K. , Pat-Espadas Aurora M.
Published: November 2022

The effect of soil amendment with biochar has been widely evaluated for its effects in mitigating greenhouse gas emissions (GHG) and remediating polluted soils with metals; however, a synergic understanding of the system, including biochar, soil, and microbial activity, is lacking. In this study, a meta-analysis of 854 paired data from 73 studies demonstrate that biochar application in soil affects GHG emissions and soil metal availability. First, several properties of biochar, soil, and microbial activity were considered as parameters in the meta-analysis. Then, the size effect was evaluated using the percentage of change (Pc) as obtained by the meta-analyzed data. Several parameters were related as influencer factors in GHG emissions and soil metal availability. Notably, biochar addition in soil resulted in a significant CO2 increase in emissions, whereas N2O emissions decreased; these results were directly correlated with microbial activity. Although this trend, demonstrated by the data analysis, differs from results of other studies found in the literature, it also emphasized the need for a deep understanding of the effect of biochar addition to soil (properties, nutrients, gas exchange, etc.) and to microorganisms (activity, diversity, etc.). Furthermore, it was also proved, that soil metal concentration decreases significantly when biochar was added (Cd > Zn > Pb > Cu > Fe). According to the results, biochar addition in soils contaminated with Cd and Cu was related to an increase in the microbial activity; while, soils amended with biochar but polluted with Pb, Zn, and Fe presented a higher inhibition effect on microorganisms. To improve the interpretation of soil amendment with biochar, it would be necessary to standardize the form for reporting results, particularly of the microbial activity and GHG emissions, in order to be used for future comparative studies.
Estimation of the Mean Trace Length of Discontinuities in an Underground Drift Using Laser Scanning Point Cloud Data
Authors: Xiao Yigai , Yang Chengye , Li Jielin , Zhou Keping , Lin Yun , Sun Guoquan
Published: November 2022

In the drifts of underground metal mines, the extraction of rock mass discontinuity characteristics from point cloud models generated with laser scanning has become the main approach. However, the exposure of discontinuities is restricted in drifts, and the size of discontinuities cannot be measured directly. Therefore, it is necessary to use a reasonable sampling tool to estimate the mean trace length of the discontinuities that are mapped in the point cloud model. In this paper, a method to estimate the mean trace length of discontinuities using a three-dimensional (3D) model of a drift (3DM) is proposed. Through the point cloud data of a drift obtained using 3D laser scanning, the information on discontinuities in the surrounding rock was extracted; then, the mean trace length was estimated using 3DEC to set sampling windows on the roof and sidewall in the 3DM. By analyzing the difference between the circular sampling window and the rectangular sampling window using simulated cases, the estimation results showed that the mean trace length obtained using circular measuring windows in the 3DM was closer to the true trace length. Finally, the method was used in a practical engineering case in Jianshan Iron Mine, Panzhihua, Sichuan, China.
Computational Investigation of Wind Loads on Tilted Roof-Mounted Solar Array
Authors: Tu Zhibin , Zheng Gensheng , Yao Jianfeng , Shen Guohui , Lou Wenjuan
Published: November 2022

A detailed computational investigation of the wind field around tilted solar modules mounted on a large building roof has been undertaken, utilizing the Reynolds-Averaged Navier-Stokesv (RANS) approach supplied with the SST k − ω turbulence model. The study investigated the flow field for various tilt angle of modules at normal wind directions relative to the wall. Then the shape factors and moment coefficients of modules were explored. The results show that the recirculation vortex generated by the building edge is disintegrated to smaller local vortices. With the increasing of the tilt angle, an increasing number of local vortices emerged at the leading rows, leading to a relatively large wind pressure and shape factor at the corner of the array. In most tilt angles at 0° and 180° wind direction the shape factors are negative. However, for the 40° and 55° tilt angles at 180° wind direction, the shape factors on the lower surfaces are positive, due to the dominating of approaching flow rather than the local vortices. The array is divided into six zones based on the distribution of shape factors. As the shape factors on upper and lower are similar, the shape factors in most zones for tilt angles from 5° to 55° are quite small. However, shape factors in the leading row for 30°, 40° and 55° are relatively large. This indicates that the shading effect of front rows can significantly reduce the shape factors of the rear rows. Compared to the values calculated by Chinese, American and Japanese standards, the shape factors by simulation are quite small. The moment induced by nonuniform wind pressure, which is often ignored in the literature and standards, is quite large at the leading zones, with a maximum of 0.28 for 55° tilt angle. Ignoring the wind induced moment on the leading zones may make the wind resistance design of the solar module support structure unsafe.
Forest Degradation Index: A Tool for Forest Vulnerability Assessment in Indian Western Himalaya
Authors: Jha Shashidhar Kumar , Negi Ajeet Kumar , Alatalo Juha Mikael , Prabhu Vignesh , Jha Mani Bhushan , Kumar Hemant
Published: November 2022

The global climate is showing altered temperatures and precipitation levels. Forests can be a stabilizing force in climate change. They regulate the nutrient cycle, protect species and diversity, and support livelihoods that drive holistic growth. Presently, the forest ecosystem’s capacity to withstand change is being undermined by the rate of change, along with anthropogenic pressures and the specificities of mountainous regions. Here, we attempted to design a ‘forest vulnerability index’ using field measurements and household surveys. A total of 71 quadrants were laid out, and 545 respondents were interviewed in 91 villages along the altitudinal gradient (altitude < 1200 m asl (Zone A), 1200–1800 m asl (Zone B), and >1800 m asl (Zone C)) of the Pauri district of Uttarakhand, India. The village-level data were normalized and combined to represent climate change impacts and the dimension of vulnerability. The IPCC (2014) protocol was used to assess forest vulnerability. The highest vulnerability was recorded in Zone ‘B’, and higher sensitivity, higher climate change impacts, and lower adaptive capacities were recorded in Zone ‘B’ and ‘C’. The approach is comparable within the district and between the states. In enhancing our shared understanding of forest degradation, the results are of value to policy/decision-makers, implementers, and adaptation funding agencies, who can use them to assess the scale, cause, and actions for adaptation.
Experimental Study on Mechanical Properties and Stability Analysis of Structural Plane under Unloading Normal Stress
Authors: Jiao Feng , Xu Jiang , Peng Shoujian , He Meixin , Zhang Xinrui
Published: November 2022

Excavation in rock induces the unloading of stress in excavation-disturbed zones and can cause the structural plane to reach shear failure due to the unloading of normal stress. Unloading normal stress tests of a regular sawtooth structural plane were conducted in this study to investigate the influence of the unloading velocities (v) and asperity angles (θ) on mechanical properties and the stability of the structural plane. The average value of normal displacement (Du1) and the shear displacement of unloading (Dsu) gradually increases with an increase in θ and Du1 accounts for 59.70%, 31.81%, and 18.60% of the height of a single asperity under different θ. However, Du2, Ds, and the unloading capacity (Δσn) gradually decreased. Moreover, Ds account for 24.52%, 11.61%, and 7.4% of the length of a single asperity, respectively. With an increase in θ and v, three-dimensional (3D) morphology parameters and normal deformation energy (Un) decreased gradually, indicating that the damage degree of the structural plane increases. The analysis of the evolution of the gap width of the structural plane at the initial point, unloading point, and instability point indicates that the greater the θ or the smaller the v, the lower would be the likelihood for the structural plane to be damaged. Concurrently, its instability is more sudden and the impact tendency is stronger.
A Microsimulation Modelling Approach to Quantify Environmental Footprint of Autonomous Buses
Authors: Hasan Umair , Whyte Andrew , AlJassmi Hamad
Published: November 2022

In this study a novel microsimulation-based methodology for environmental assessment of urban systems is developed to address the performance of autonomous mass-mobility against conventional approaches. Traffic growth and microsimulation models, calibrated using real data, are utilised to assess four traffic management scenarios: business-as-usual; public bus transport case; public-bus rapid transit (BRT) case; and, a traffic-demand-responsive-autonomous-BRT case, focusing on fuel energy efficiency, headways, fleet control and platooning for lifecycle analysis (2015–2045) of a case study 3.5 km long 5-lane dual-carriageway section. Results showed that both energy consumption and exhaust emission rates depend upon traffic volume and flow rate factors of vehicle speed-time curves; acceleration-deceleration; and braking rate. The results measured over-reliance of private cars utilising fossil fuel that cause congestions and high environmental footprint on urban roads worsen causing excessive travel times. Public transport promotion was found to be an effective and easy-to-implement environmental burden reduction strategy. Results showed significant potential of autonomous mass-mobility systems to reduce environmental footprint of urban traffic, provided adequate mode-shift can be achieved. The study showed utility of microsimulations for energy and emissions assessment, it linked bus network performance assessment with environmental policies and provided empirical models for headway and service frequency comparisons at vehicle levels. The developed traffic fleet operation prediction methodology for long-term policy implications and tracking models for accurate yearly simulation of real-world vehicle operation profiles are applicable for other sustainability-oriented urban traffic management studies.
Blockchain for Internet of Underwater Things: State-of-the-Art, Applications, Challenges, and Future Directions
Authors: Bhattacharya Sweta , Victor Nancy , Chengoden Rajeswari , Ramalingam Murugan , Selvi Govardanan , Maddikunta Praveen , Donta Praveen , Dustdar Schahram , Jhaveri Rutvij , Gadekallu Thippa
Published: November 2022

The Internet of Underwater Things (IoUT) has become widely popular in the past decade as it has huge prospects for the economy due to its applicability in various use cases such as environmental monitoring, disaster management, localization, defense, underwater exploration, and so on. However, each of these use cases poses specific challenges with respect to security, privacy, transparency, and traceability, which can be addressed by the integration of blockchain with the IoUT. Blockchain is a Distributed Ledger Technology (DLT) that consists of series of blocks chained up in chronological order in a distributed network. In this paper, we present a first-of-its-kind survey on the integration of blockchain with the IoUT. This paper initially discusses the blockchain technology and the IoUT and points out the benefits of integrating blockchain technology with IoUT systems. An overview of various applications, the respective challenges, and the possible future directions of blockchain-enabled IoUT systems is also presented in this survey, and finally, the work sheds light on the critical aspects of IoUT systems and will enable researchers to address the challenges using blockchain technology.
Online English Learning Engagement among Digital Natives: The Mediating Role of Self-Regulation
Authors: Wang Xiaoqi , Hui Lianghong , Jiang Xin , Chen Yuhan
Published: November 2022

Because of the recent pandemic, students have needed to become skilled, adaptable, self-regulating, and flexible toward online learning. However, few researchers considered digital nativity (DN) when studying self-regulation and learning engagement. This study explored how Chinese digital natives regulated themselves in English learning. A total of 408 college English students volunteered, and partial least squares structural equation modeling (PLS–SEM) was used to process the questionnaire’s tested four hypotheses. The results showed that: (1) DN is related to online self-regulated English learning (OSEL); (2) OSEL is related to online student engagement (OSE); (3) DN is not related to OSE; and (4) OSEL is the mediator between DN and OSE. As such, the current findings should encourage e-learning designers and educators to equip students with both computer literacy and self-regulated competence for sustainable English learning development.
Operating Range, Performance and Emissions of an HCCI Engine Fueled with Fusel Oil/Diethyl Ether: An Experimental Study
Authors: Polat Seyfi , Calam Alper , Ardebili Seyed , Şahin Fatih , Boroiu Alexandru , Solmaz Hamit
Published: November 2022

The main disadvantages of HCCI engines are the knocking tendency at high engine loads, the challenge of the start of the combustion, control of the combustion phase, and the narrow operating range. In this study, we aimed to control the combustion processes in HCCI engines and to expand their working range by improving the fuel properties of fusel oil by the addition of diethyl ether. Thus, the variations in the in-cylinder pressure, rate of heat release, indicated mean effective pressure, start of combustion, combustion duration, CA50, indicated thermal efficiency, mean pressure rise rate, hydrocarbon and carbon monoxide emissions were investigated. It was observed that the in-cylinder pressure and rate of heat release were taken into advance and the test engine could be operated for a wider range by increasing the diethyl ether ratio in the blend. The indicated mean effective pressure increased by 67.5% with DEE40 fuel compared to the DEE80. Under the same operating conditions, HC and CO emissions decreased by 41.6% and 56.2%, in use of DEE40. Furthermore, the highest indicated thermal efficiency was obtained as 42.5% with DEE60 fuel. Maximum hydrocarbon and carbon monoxide emissions were observed with DEE80 fuel as 0.532% and 549 ppm, respectively.
A Model Proposal for Occupational Health and Safety Performance Measurement in Geothermal Drilling Areas
Authors: Tonka Şebnem Karul , Ekmekci Ismail
Published: November 2022

The energy sources required for general development and maintenance cause environmental pollution due to the carbon emissions released into the atmosphere. For these reasons, countries have turned to renewable energy sources. Energy production methods also cause serious problems in terms of the health and safety of employees. This study aimed to create an occupational health and safety performance model in geothermal energy fields, which generate renewable energy sources, using multi-criteria decision-making methods. A two-stage model was created for OHS performance index measurement. In the first stage, a literature screening was performed, risk analysis criteria were examined, and performance measurement criteria were determined with geophysical engineers and OHS experts. Seven main criteria and forty-seven subcriteria were set. An analytical hierarchy process method (AHP) and a fuzzy analytical hierarchy process (F-AHP) using the main criteria and subcriteria were determined. In the second stage, exposure rates were obtained using the Promethee method in three geothermal wells. The risks in these three wells are listed according to their importance. A performance model was created. The Results section includes conclusions and suggestions. This study, by creating an OHS performance model, can be used by managers and OHS professionals working in geothermal energy production fields to solve problems.
Design and Testing of a Remote Control-Based Integrated Flow Regulation and Measurement Device
Authors: Liu Mengyang , Zhu Delan , Nie Xinxin , Shi Changyang , Tu Hongbin , Jing Bo , Fan Huiyi , Zhao Hang
Published: November 2022

In order to maintain sustainable agriculture, the flow in irrigation systems needs to be managed remotely and finely to achieve efficient use of water resources. This research develops a flow measuring device that integrates measurement and control to achieve precise flow regulation under remote control. The device chooses the angular regulating valve as the actuation component to control the flow. By the experimental study of the valve body working characteristics, this paper (1) establishes the relationships among the pressure in front of the valve, the valve body opening and the pipeline flow; (2) establishes the relationship between the valve opening degree and the number of driving pulses of the stepper motor, and (3) designs the opening decision and flow measurement software. The experiment shows that the flow coefficient of the valve body is 84.61, and there is no leakage loss when closed. It also shows that the regulation curve matches the law of fast-opening features. The established relationship and the correlation coefficient between the performance parameters and the measured value are both greater than 0.99, indicating a decent performance of fitness. In a test where the pipeline pressures were 0.10, 0.20, and 0.30 MPa, the average duration of flow regulation was 62.48 s, with a maximum overshoot of 5%, and a maximum steady-state error of 6%. The experiment also showed that the higher the pressure is, the better the regulation effect is. The flow measurement error under varied pressure is below 3%. With its simple structure, fast flow regulation time, and high accuracy, this device meets the requirements of flow management in irrigation systems. It can be used in a variety of flow rate remote monitoring and control scenarios.