bluuebunny/crossref_metadata_2025 huggingface dataset:
Fabrication and Underwater Testing of a Vector Hydrophone Comprising a Triaxial Piezoelectric Accelerometer and Spherical Hydrophone
Authors: Roh Taehoun , Yeo Hong Goo , Joh Cheeyoung , Roh Yongrae , Kim Kyungseop , Seo Hee-seon , Choi Hongsoo
Published: December 2022

A vector hydrophone is an underwater acoustic sensor that can detect the direction of a sound source. Wide-band characteristics and high sensitivity enhance the performance of underwater surveillance systems in complex environments. A vector hydrophone comprising a triaxial piezoelectric accelerometer and spherical hydrophone was fabricated and tested in the air and underwater. The vector hydrophone was designed to exceed the quantitative figures of merit (i.e., receiving voltage sensitivity and bandwidth) of commercially available hydrophones. Accelerometer performance was enhanced by placing a pair of piezoelectric single crystals on each axis and modifying the seismic mass material. The receiving voltage sensitivity of the omnidirectional hydrophone was approximately −160 dB relative to 1 V/μPa with the amplifier in water; the sensitivity of the accelerometer exceeded 300 mV/g in air and −215 dB relative to 1 V/μPa underwater over the frequency range of interest. The receiving directivity of the vector hydrophone was validated underwater, which confirmed that it could detect the direction of a sound source.
Adaptive Approach to Time-Frequency Analysis of AE Signals of Rocks
Authors: Lukovenkova Olga , Marapulets Yuri , Solodchuk Alexandra
Published: December 2022

The paper describes a new adaptive approach to the investigation of acoustic emission of rocks, the anomalies of which may serve as short-term precursors of strong earthquakes. The basis of the approach is complex methods for monitoring acoustic emission and for analysis of its time-frequency content. Piezoceramic hydrophones and vector receivers, installed at the bottom of natural and artificial water bodies, as well as in boreholes with water, are used as acoustic emission sensors. To perform a time-frequency analysis of geoacoustic signals, we use a sparse approximation based on the developed Adaptive Matching Pursuit algorithm. The application of this algorithm in the analysis makes it possible to adapt to the concrete characteristics of each geoacoustic pulse. Results of the application of the developed approach for the investigation of acoustic emission anomalies, occurring before earthquakes, are presented. We analyzed the earthquakes, that occurred from 2011 to 2016 in the seismically active region of the Kamchatka peninsula, which is a part of the circum-Pacific orogenic belt also known as the “Ring of Fire”. It was discovered that geoacoustic pulse frequency content changes before a seismic event and returns to the initial state after an earthquake. That allows us to make a conclusion on the transformation of acoustic emission source scales before earthquakes. The obtained results may be useful for the development of the systems for environmental monitoring and detection of earthquake occurrences.
A Tiled Ultrasound Matrix Transducer for Volumetric Imaging of the Carotid Artery
Authors: dos Santos Djalma Simões , Fool Fabian , Mozaffarzadeh Moein , Shabanimotlagh Maysam , Noothout Emile , Kim Taehoon , Rozsa Nuriel , Vos Hendrik J. , Bosch Johan G. , Pertijs Michiel A. P. , Verweij Martin D. , de Jong Nico
Published: December 2022

High frame rate three-dimensional (3D) ultrasound imaging would offer excellent possibilities for the accurate assessment of carotid artery diseases. This calls for a matrix transducer with a large aperture and a vast number of elements. Such a matrix transducer should be interfaced with an application-specific integrated circuit (ASIC) for channel reduction. However, the fabrication of such a transducer integrated with one very large ASIC is very challenging and expensive. In this study, we develop a prototype matrix transducer mounted on top of multiple identical ASICs in a tiled configuration. The matrix was designed to have 7680 piezoelectric elements with a pitch of 300 μm × 150 μm integrated with an array of 8 × 1 tiled ASICs. The performance of the prototype is characterized by a series of measurements. The transducer exhibits a uniform behavior with the majority of the elements working within the −6 dB sensitivity range. In transmit, the individual elements show a center frequency of 7.5 MHz, a −6 dB bandwidth of 45%, and a transmit efficiency of 30 Pa/V at 200 mm. In receive, the dynamic range is 81 dB, and the minimum detectable pressure is 60 Pa per element. To demonstrate the imaging capabilities, we acquired 3D images using a commercial wire phantom.
Optimal Geometries for AOA Localization in the Bayesian Sense
Authors: Dogancay Kutluyil
Published: December 2022

This paper considers the optimal sensor placement problem for angle-of-arrival (AOA) target localization in the 2D plane with a Gaussian prior. Optimal sensor locations are analytically determined for a single AOA sensor using the D- and A-optimality criteria and an approximation of the Bayesian Fisher information matrix (BFIM). Optimal sensor placement is shown to align with the minor axis of the prior covariance error ellipse for both optimality criteria. The approximate BFIM is argued to be valid for a sufficiently small prior covariance compared with the target range. Optimal sensor placement results obtained for Bayesian target localization are extended to manoeuvring target tracking. For sensor trajectory optimization subject to turn-rate constraints, numerical search methods based on the D- and A-optimality criteria as well as a new closed-form projection algorithm that aims to achieve alignment with the minor axis of the prior error ellipse are proposed. It is observed that the two optimality criteria generate significantly different optimal sensor trajectories despite having the same optimal sensor placement for the localization of a stationary target. Analysis results and the performance of the sensor trajectory optimization methods are demonstrated with simulation examples. It is observed that the new closed-form projection algorithm achieves superior tracking performance compared with the two numerical search methods.
The Effect of Freezing and Thawing on Complex Permittivity of Bovine Tissues
Authors: Matković Anđela , Šarolić Antonio
Published: December 2022

The aim of this study was to investigate how the freezing and thawing of biological tissues affect their complex permittivity in the microwave frequency range from 0.5 MHz to 18 GHz. We measured the complex permittivity of ex vivo bovine tissues, including brain white and grey matter, liver, and muscle, using an open-ended coaxial probe. Bovine tissues were chosen for their availability and similarity to human tissue permittivity. The samples were measured at 25 °C, before they were frozen either in a commercial freezer below −18 °C or in liquid nitrogen, nominally at −196 °C. The measured permittivity before freezing was compared to the permittivity measured after freezing and thawing the tissues back to 25 °C. Statistical analysis of the results showed a statistically significant change in permittivity after freezing and thawing by both methods for all the measured tissues, at least in some parts of the measured frequency range. The largest difference was observed for the white matter, while the liver had the smallest percent change.
Simple Millimeter Wave Identification System Based on 60 GHz Van Atta Arrays
Authors: Trzebiatowski Kamil , Rzymowski Mateusz , Kulas Lukasz , Nyka Krzysztof
Published: December 2022

The paper presents a proof-of-concept of a millimeter-wave identification system based on Van Atta array tags in the 60 GHz band. For interrogation of the tags, a vector network analyzer and a measurement transceiver were employed in alternative test configurations. The design, fabrication and measurements of co- and cross-polarized Van Atta arrays are presented in the paper. They can be treated as simple chipless RFID tags with frequency-response-based identification. Tags with various resonance frequencies are designed by scaling an optimized base model. The designed 57–67 GHz co-polarized and cross-polarized tags have small dimensions of approximately 23 mm × 21 mm and 40 mm × 25 mm, and they exhibit radar cross-section (RCS) levels of −16 dBsm and −21 dBsm, respectively. Owing to the retrodirective properties of Van Atta arrays, the RCS can be maintained at a high level within a broad range of angles of incidence. The system was validated in an anechoic chamber where the spectral responses of all the manufactured tags can be clearly distinguished from the environment, enabling their identification. Tests in a reflective environment were also performed, and they have shown that only the cross-polarized tags could be detected and identified in the presence of reflections from the tags’ surroundings.
Reinforcement Learning with Side Information for the Uncertainties
Authors: Yang Janghoon
Published: December 2022

Recently, there has been a growing interest in the consensus of a multi-agent system (MAS) with advances in artificial intelligence and distributed computing. Sliding mode control (SMC) is a well-known method that provides robust control in the presence of uncertainties. While our previous study introduced SMC to the reinforcement learning (RL) based on approximate dynamic programming in the context of optimal control, SMC is introduced to a conventional RL framework in this work. As a specific realization, the modified twin delayed deep deterministic policy gradient (DDPG) for consensus was exploited to develop sliding mode RL. Numerical experiments show that the sliding mode RL outperforms existing state-of-the-art RL methods and model-based methods in terms of the mean square error (MSE) performance.
UV-Light-Tunable p-/n-Type Chemiresistive Gas Sensors Based on Quasi-1D TiS3 Nanoribbons: Detection of Isopropanol at ppm Concentrations
Authors: Sysoev Victor V. , Lashkov Andrey V. , Lipatov Alexey , Plugin Ilya A. , Bruns Michael , Fuchs Dirk , Varezhnikov Alexey S. , Adib Mustahsin , Sommer Martin , Sinitskii Alexander
Published: December 2022

The growing demand of society for gas sensors for energy-efficient environmental sensing stimulates studies of new electronic materials. Here, we investigated quasi-one-dimensional titanium trisulfide (TiS3) crystals for possible applications in chemiresistors and on-chip multisensor arrays. TiS3 nanoribbons were placed as a mat over a multielectrode chip to form an array of chemiresistive gas sensors. These sensors were exposed to isopropanol as a model analyte, which was mixed with air at low concentrations of 1–100 ppm that are below the Occupational Safety and Health Administration (OSHA) permissible exposure limit. The tests were performed at room temperature (RT), as well as with heating up to 110 °C, and under an ultraviolet (UV) radiation at λ = 345 nm. We found that the RT/UV conditions result in a n-type chemiresistive response to isopropanol, which seems to be governed by its redox reactions with chemisorbed oxygen species. In contrast, the RT conditions without a UV exposure produced a p-type response that is possibly caused by the enhancement of the electron transport scattering due to the analyte adsorption. By analyzing the vector signal from the entire on-chip multisensor array, we could distinguish isopropanol from benzene, both of which produced similar responses on individual sensors. We found that the heating up to 110 °C reduces both the sensitivity and selectivity of the sensor array.
Comfort Prediction of Office Chair Surface Material Based on the ISSA-LSSVM
Authors: Zhang Xuyinglong , Cheng Zilian , Zhang Mengyang , Zhu Xiaodong , Zhang Xianquan
Published: December 2022

This study serves the purpose of assisting users in selecting a comfortable seat surface material for office chairs and enhancing users’ comfort while using office chairs. To address the issue that the selection of traditional seat surface material is too subjective and that the prediction effect is poor, an improved sparrow search algorithm (ISSA) optimized least squares support vector machine (LSSVM) method for office chair seat surface material comfort prediction has been proposed. Sparrow Search Algorithm (SSA) was optimized with Sobol sequences, nonlinear inertial weights, and a crisscross optimization algorithm to produce the Improved Sparrow Search Algorithm (ISSA), and then the relevant parameters of the LSSVM algorithm were optimized with the modified algorithm to improve its prediction performance. The prediction accuracy of the ISSA-LSSVM model is as high as 95.75% by combining the body pressure distribution experiments; the root mean square error (RMSE) is 0.29; the goodness of fit (R2) is 0.92; the mean absolute error (MAE) is 0.24; the standard deviation (RSD) is 5.99%. The ISSA-LSSVM model predicts seat surface material comfort more accurately and reliably. This strategy can assist consumers to narrow down their seat surface material choices and even suggest an optimal selection. In this way, it can boost users’ pleasure with office chairs, which has great potential for wide application.
Non-Destructive Detection of Abnormal Chicken Eggs by Using an Optimized Spectral Analysis System
Authors: Kim Juntae , Semyalo Dennis , Rho Tae-Gyun , Bae Hyungjin , Cho Byoung-Kwan
Published: December 2022

Environmental pressures, such as temperature and light intensity, food, and genetic factors, can cause chicken eggs to develop abnormalities. The common types of internal egg abnormalities include bloody and damaged egg yolk. Spectrometers have been recently used in real-time abnormal egg detection research. However, there are very few studies on the optimization of measurement systems. This study aimed to establish optimum parameters for detecting of internal egg abnormalities (bloody and damaged-yolk eggs) using visible and near-infrared (Vis/NIR) spectrometry (192–1110 nm range) and multivariate data analysis. The detection performance using various system parameters, such as the types of light sources, the configuration of the light, and sensor positions, was investigated. With the help of collected data, a partial least-squares discriminant analysis (PLS-DA) model was developed to classify normal and abnormal eggs. The highest classification accuracy for the various system parameters was 98.7%. Three band selection methods, such as weighted regression coefficient (WRC), sequential feature selection (SFS), and successive projection algorithm (SPA) were used for further model optimization, to reduce the spectral bands from 1028 to less than 7. In conclusion the results indicate that the types of light sources and the configuration design of the sensor and illumination affect the detection accuracy for abnormal eggs.
Surrogate-Model-Based Interval Analysis of Spherical Conformal Array Antenna with Power Pattern Tolerance
Authors: Ding Guangda , Li Peng , Rocca Paolo , Chang Jiantao , Xu Wanye
Published: December 2022

A method based on an interval arithmetic is proposed to analyze uncertain factors such as the curvature radii, excitation amplitude, and excitation phase of a spherical conformal array antenna. An interval description of element factors under different curvature radii of spherical substrates is established using the surrogate model based on the data obtained through a full-wave analysis method. The interval formula of the spherical curvature radius and array element position error is derived and the effects of the spherical radius tolerance, excitation amplitude tolerance, and excitation phase tolerance on the antenna power pattern are studied. To evaluate the effectiveness and reliability of the proposed method, a set of representative numerical results are reported and discussed and a comparison with the Monte Carlo methods and full-wave simulation is described. This method can be widely used during the antenna design and before the antenna prototyping/manufacturing to predict the effects, on the radiation performance, of possible errors/tolerances in the antenna structure to guarantee the antenna working ‘in operation’.
Landscape Pattern Consistency Assessment of 10 m Land Cover Products in Different Ecological Zoning Contexts of Sichuan Province, China
Authors: Ma Miaomiao , Zou Youfeng , Zhang Wenzhi , Chen Chunhui
Published: December 2022

The research on land cover and its changing value to the ecology environment and ecosystem service is of great importance. Understanding the landscape patterns and accuracy in remote sensing land cover data from multiple sources under eco-regionalization is important for relevant research under eco-regionalization. Land cover and land use in different ecological regionalization contexts influence massive ecosystem processes on a global scale, and many ecosystem models are dependent on accurate land cover information. It is, therefore, important to assess the available global land cover products based on different ecological zoning contexts and to understand the differences between them so that different researchers can apply them in a rational way. This study took Sichuan Province as an experimental case. Based on the three methods of spatial superposition, landscape index, and validation sample, we discussed and then analyzed the consistency of landscape patterns for the three 10 m global land cover data under different ecogeographic zones. The results showed that the spatial consistency of FROM-GLC, ESA, and ESRI land cover data were high under the ecological zoning of Palearctic0518 (PA0518) and PA1017, while the spatial pattern was less consistent for the three land cover data under the ecological zoning of PA0509 and PA0437. The fully consistent areas for the three data were 44,420.9 km2 and 53,368.9 km2, respectively. The results of the quantitative analysis of the landscape index showed significant differences in the degree of landscape fragmentation, landscape shape complexity, and the connectivity among landscape patches of several land cover data were significantly different under different ecological zones. Based on the three kinds of independent validation samples to achieve the absolute accuracy of evaluation, the overall accuracy of the FROM-GLC, ESA, and ESRI land cover data was less than 60%, and future drawing still needs to further improve the regional land cover data mapping accuracy under different ecological zones in order to carry out ecological environment monitoring, land ecological security evaluation, and related research to provide a reference.
Optimum Fluid Content in Pavement Cold In-Place Recycling Containing Waste Materials
Authors: Kopić Miloš , Milović Tiana , Matić Bojan , Jovanović Stanislav , Marinković Milan
Published: December 2022

The planning of road infrastructure undergoes major changes, especially in terms of sustainable development. Recycling of pavement structures involves the reuse of materials from existing pavement structures due to its timesaving and environmental benefits, as well as cost reduction. According to the recycling temperature, recycling can be hot and cold. This paper deals with cold in-place recycling and the determination of the optimum fluid content for by-product materials in mixtures compared with one containing natural zeolite. The content of bitumen emulsion and cement—which are the most used materials so far in cold recycling along with foam bitumen—was replaced with fly ash, slag or natural zeolite, and bakelite, respectively, while recycled asphalt pavement from Serbia (Žabalj) was used. Six different mixtures were made. The mixture with the addition of fly ash had the highest optimum fluid content (7.6%) compared with all test mixtures. Mixtures with slag, natural zeolite, and bakelite were in the range of a mixture containing 2% cement. Furthermore, the mixture with 3% cement had the lowest optimum fluid content (5.7%) in comparison to all the mixtures that were tested.
Landslide Susceptibility Prediction: Improving the Quality of Landslide Samples by Isolation Forests
Authors: Zhang Qinghua , Liang Zhu , Liu Wei , Peng Weiping , Huang Houzan , Zhang Shouwen , Chen Lingwei , Jiang Kaihua , Liu Lixing
Published: December 2022

Landslide susceptibility prediction (LSP) is the first step to ease landslide disasters with the application of various machine learning methods. A complete landslide inventory, which is essential but difficult to obtain, should include high-quality landslide and non-landslide samples. The insufficient number of landslide samples and the low purity of non-landslide samples limit the performance of the machine learning models. In response, this study aims to explore the effectiveness of isolated forest (IF) to solve the problem of insufficient landslide samples. IF belongs to unsupervised learning, and only a small share of landslide samples in the study area were required for modeling, while the remaining samples were used for testing. Its performance was compared to another advanced integration model, adaptive boosting integrated with decision tree (Ada-DT), which belongs to two-class classifiers (TCC) and needs a sufficient number of samples. Huangpu District, Guangzhou City, Guangdong Province in China, was selected as the study area, and 13 predisposing factors were prepared for the modeling. Results showed that the IF proved its effectiveness with an AUC value of 0.875, although the Ada-DT model performed better (AUC = 0.921). IF outperformed the Ada-DT model in terms of recognizing landslides, and the sensitivity values of IF and the Ada-DT model were 90.00% and 86.67%, respectively, while the Ada-DT model performed better in terms of specificity. Two susceptibility maps obtained by the models were basically consistent with the field investigation, while the areas predicted by IF tended to be conservative as higher risk areas were presented, and the Ada-DT model was likely to be risky. It is suggested to select non-landslide samples from the very low susceptibility areas predicted by the IF model to form a more reliable sample set for Ada-DT modeling. The conclusion confirms the practicality and advancement of the idea of anomaly detection in LSP and improves the application potential of machine learning algorithms for geohazards.
Dimensionality-Transformed Remote Sensing Data Application to Map Soil Salinization at Lowlands of the Syr Darya River
Authors: Samarkhanov Kanat , Abuduwaili Jilili , Samat Alim , Ge Yongxiao , Liu Wen , Ma Long , Smanov Zhassulan , Adamin Gabit , Yershibul Azamat , Sadykov Zhassulan
Published: December 2022

The problem of saving soil resources and their reclamation measures under current climate change conditions attracts the world community’s close attention. It is relevant in the Syr Darya River’s lowlands, where the secondary soil salinization processes have intensified. The demand for robust methods to assess soil salinity is high, and the primary purpose of this study was to develop a quantitative analysis method for soil salinity estimation. We found a correspondence between the sum of salts in a topsoil layer to the Landsat 8 data in the Tasseled cap transformation of the image values. After testing several methods, we built a prediction model. The K-nearest neighborhood (KNN) model with a coefficient of determination equal to 0.96 using selected predictors proved to be the most appropriate for soil salinity assessment. We also performed a quantitative assessment of soil salinity. A significant increase in a salt-affected area and the mean soil sum expressing an intensification of secondary soil salinization from 2018 to 2021 was found. The increasing temperature values, decreasing soil moisture, and agricultural use affect the extension of salt-affected ground areas in the study area. Thus, the soil moisture trend in the Qazaly irrigation zone is negative and declining, with the highest peaks in early spring. The maximum temperature has a mean value of 15.6 °C (minimum = −15.1 °C, maximum = 37.4 °C) with an increasing trend. These parameters are evidence of climate change that also affects soil salinization. PCA transformation of the Landsat-8 satellite images helped to remove redundant spectral information from multiband datasets and map soil salinity more precisely. This approach simultaneously extends mapping opportunities involving visible and invisible bands and results in a smaller dataset.
R&D Investment, Internal Control and Enterprise Performance—An Empirical Study Based on the Listed Companies in China of the Core Industry of the Digital Economy
Authors: Wu Xinyue , Zeng Shaolun
Published: December 2022

Based on the financial data of listed companies in the core industries of the digital economy from 2010 to 2021, the moderating effect was used to analyze R&D investment, internal control, and enterprise performance. The empirical results show that for listed companies in the core industries of the digital economy, increasing R&D investment can help companies improve their performance. In addition, internal control positively impacts enterprise performance. Internal control acts as a moderating variable, negatively moderating R&D investment and enterprise performance. At low levels of internal control, an increase in R&D investment is associated with a more significant increase in firm performance than at high levels of internal control. Increasing investment in R&D is associated with a slower performance increase at high internal control levels. For companies in the core industries of the digital economy, there is no significant inverted ‘U’-shaped relationship between R&D investment and enterprise performance.
Establishment of a City-Based Index to Communicate Air Pollution-Related Health Risks to the Public in Bangkok, Thailand
Authors: Onchang Rattapon , Hirunkasi Kannigar , Janchay Siriwan
Published: December 2022

An Air Quality Health Index (AQHI), a health risk-based air pollution index, was constructed to communicate to the public their health risks due to exposure to air pollution in Bangkok, Thailand. This AQHI was built by analyzing the association between total excess respiratory disease-related deaths and individual air pollutants, using a time-series analysis of daily data from 2010 to 2019. We used Poisson regression in a generalized additive model, with natural cubic smooth splines to analyze the data and controls for other common variables (time, temperature, relative humidity, day of the week, and public holidays). The regression coefficients of these variables were then employed to establish the suitability of this AQHI for Bangkok. The results indicated that a 10-unit increase in particulate matter (PM10), fine particulate matter (PM2.5), ozone (O3), or nitrogen dioxide (NO2) was statistically associated with increased respiratory disease mortality. The coefficients of these four pollutants were then adopted in the construction of an AQHI for Bangkok. Compared with the currently used Air Quality Index (AQI), the AQHI was a more effective indicator in communicating multiple air pollution-related health risks to the public in Bangkok.
Mobility Patterns of Scholar Communities in Southwestern European Countries
Authors: Lage Joana , d’Espiney Ana , Canha Nuno , Manteigas Vítor , Alexandre José Luís , Gonçalves Karla , Chacartegui Ricardo , Lizana Jesus , Lechón Yolanda , Gamarra Ana Rosa , Fernandez Amaia , Blondeau Patrice , Gomes Margarida , Almeida Susana Marta
Published: December 2022

The present study aimed to provide an in-depth assessment of the commuting patterns of scholar communities of southwestern European countries and to identify measures to improve their sustainable performance regarding mobility. The adopted methodology characterised the mobility pattern of students as a sustainability indicator and the availability of related infrastructures and local public transport network. Data were gathered by qualitative (behavioural questionnaires) and quantitative (technical audits) approaches, based on measurable indicators (key performance indicators and scores (ranging between 0–5)). Overall, French schools showed the best sustainable performance regarding mobility (2.0) and Gibraltar had the lowest (1.2). The existence of bike parking and electric car charging points were the main weaknesses founds (with their related mean scores being 0.6 and 0.2, respectively). The score associated with annual CO2 emissions due to students’ mobility had the best performance, where all countries managed to obtain an average of 3.1. The global score, which assessed the sustainable performance of scholar communities regarding mobility, had a mean value of 1.5 for all studied countries, which highlights the potential for improvement of the studied schools, mainly targeting the public transport network optimisation and the enhancement of scholar infrastructures concerning bicycle parking and electric cars.
(Re)Defining Restorative and Regenerative Urban Design and Their Relation to UNSDGs—A Systematic Review
Authors: He Qingchang , Reith Andras
Published: December 2022

The 1992, the Rio Declaration on Environment and Development highlighted that human impacts on the environment should be reduced. Against this backdrop, publications on restorative and regenerative urban design first appeared in the mid-1990s, and both disciplines have developed rapidly up to the present time. However, there is still some uncertainty regarding the interrelationships and differences between these two terms, and their association with the United Nations Sustainable Development Goals. Based on a search of the Web of Science database, a total of 117 papers were studied with the help of VOS viewer and R studio. The differences between the two disciplines and their respective associations with the United Nations Sustainable Development Goals were analyzed using key performance indicators. Detailed analysis was used to explore their current development status. Scientific publication and citation network analyses were used to examine the historical developments and interrelationships between two disciplines. The review revealed that both disciplines are closely related to the United Nations Sustainable Development Goals, especially regenerative urban design, but they have developed independently in the field of urban design. Unlike the descriptions found in many of the identified papers, restorative urban design not only focuses on ecological aspects but also attempts to create a built environment that allows its users to thrive both physically and mentally. Regenerative urban design is more inclined to restore or create an “ability”. Further, both disciplines are in their infancy but have evolved from internal conceptual development to the stage of exploring external relationships and frameworks as well as mechanisms. This review found that although many frameworks and models are used to support and evaluate these two disciplines, almost all of them fail to integrate necessary aspects of the ecosystem, e.g., elements, relationships, processes, etc. Moreover, future work should examine the design patterns that are closely related to restorative and regenerative urban design to better guide the concrete practice.
Influence of Recycling Agents Addition Methods on Asphalt Mixtures Properties Containing Reclaimed Asphalt Pavement (RAP)
Authors: Ziari Hassan , Hajiloo Mojtaba , Ayar Pooyan
Published: December 2022

Recycling agents (RAs) are used to restore the physicochemical properties of the aged asphalt binder existing in the reclaimed asphalt pavement (RAP) material. The best location for adding the RAs in the manufacturing process of the asphalt mixtures containing RAP has always been of concern to asphalt mixture researchers. In this study, vegetable, paraffinic and aromatic extract oils were used as RAs. The effect of RA location on the performance properties of the asphalt mixtures containing different percentages of the RAP material was investigated by adding the RAs in three different locations, including in the virgin binder, in the hot RAP material, and in the final mixture. For this aim, the rutting, cracking, and moisture sensitivity of the mixtures containing different RAs at different locations was investigated. The results showed that the best location for adding the RAs is different for various RAs. The best place for adding the paraffinic, aromatic extract, and vegetable oils in terms are in the virgin binder, in the RAP, and the final mixture, respectively. Therefore, using RAs in their appropriate location can improve the mechanical properties of asphalt mixtures containing RAP.
Screening of Rhizosphere Microbes of Salt-Tolerant Plants and Developed Composite Materials of Biochar Micro-Coated Soil Beneficial Microorganisms
Authors: Lee Shih-Chi , Kitamura Yutaka , Tsai Shu-Hsien , Chien Chuan-Chi , Cheng Chun-Shen , Hsieh Chin-Cheng
Published: December 2022

To develop composite materials of biochar micro-coated soil beneficial microorganisms, soil samples were collected from the saline-alkali land of the Penghu in Taiwan. After isolation, purification and identification, a total of one Bacillus amyloliquefaciens and two Bacillus megaterium were identified as the source of beneficial microorganisms. The agricultural waste is collected and initially crushed, and then made into biochar through a series of thermal cracking processes. The specific surface area of biochar is more than 100 m2/g, the fixed carbon is more than 80%, the proportion of medium and large pores is more than 30%, the pH after adjustment is 7.3 ± 0.2, and the pore size of beneficial microorganisms grows inward, which is one of the beneficial microorganisms. The biochar micro-coated soil-beneficial microorganism composite material developed in this experiment can indeed help crops to overcome the stress of salt damage to a certain extent, and Bacillus amyloliquefaciens can indeed promote plant growth and help crops effects of over-salting adversity.
Cyclic True Triaxial Tests on Aeolian Sand Considering Initial Shear Effect
Authors: Xu Wendong , Li Xuefeng , Lü Xilin , Yang Wenwei
Published: December 2022

Under traffic loading, the soil elements in subgrade are subjected to a complex 3D stress path. To investigate the cyclic behavior of desert subgrade under initial shear stress conditions, the number of cyclic true triaxial tests were implemented on aeolian sand from the Tengger Desert. A large range of initial shear stress levels and different cyclic stress paths (various combinations of cyclic major and intermediate principal stresses) were designed in the experiments. The results show that the initial shear stress level significantly influences the cyclic response, and the response mode of aeolian sand under initial shear stress is incremental failure and elastic shakedown, while it is critical failure without initial shear stress. With the increase in initial shear stress, the permanent strain increases first and then decreases, with the maximum permanent strain occurring at q0 = 50 kPa. Moreover, by comparing the test data under different cyclic stress paths, it is found that the cyclic resistance decreases with the increase in the coefficient of cyclic intermediate principal stress bcyc. Compared to the limiting pore pressure criterion, the conventional 5% axial strain failure criterion may overestimate the cyclic resistance, leading to unsafe evaluation and design. Therefore, by using the pore pressure criterion, the relationship between the limit pore pressure ratio and the initial stress condition was investigated and it was found that the limit pore pressure ratio decreased linearly when the initial shear stress increased.
Oxidation Ditches for Recycling and Reusing Wastewater Are Critical for Long-Term Sustainability—A Case Study
Authors: Alramthi Saad M. , Ali Gamila H. , Elthagafi Atiah M. , Eldosari Saad H. , Zhu Bao-Ku , Safaa Hosam M.
Published: December 2022

Because the cost of operation and maintenance is lower than those of chemical treatments, the aerobic biological oxidation method used to treat wastewater is very effective. An oxidation ditch can be classified as progressive aeration-activated sludge capable of removing organic pollutants and also nitrogen and phosphorus. The overall goal of this research is to analyse influent, effluent, and operating data over a seven-year period (2014–2020) to better understand process performance, identify knowledge gaps, and suggest potential improvements for the operating efficiency of the wastewater treatment plant (WWTP) in Bishah Governorate, which works with oxidation ditch technology. An examination of historical influent, effluent, and operational data shows that the Bishah WWTP has consistently met the national and international guidelines for wastewater reuse in restricted and unrestricted irrigation. The effluent ratio of the biodegradable organic material (BOD5)/chemical oxygen demand (COD) values ranged from 0.3 to 0.51 with an average of 0.41. Significant Pearson correlation coefficients (bivariate) between physico-chemicals merit, especially in total coliforms form, BOD5 and ammonia. It could be concluded that the operational performance of a wastewater treatment plant with an oxidation ditch in Bishah is working well according to national and international standards.
Hydrogeotechnical Predictive Approach for Rockfall Mountain Hazard Using Elastic Modulus and Peak Shear Stress at Soil–Rock Interface in Dry and Wet Phases at KKH Pakistan
Authors: Mehmood Ehtesham , Rashid Imtiaz , Ahmed Farooq , Farooq Khalid , Tufail Akbar , Ebid Ahmed M.
Published: December 2022

Predicting the susceptibility of rockfall mountain hazards for block-in-matrix soils is challenging for critical steep cuts. This research illustrates a hydrogeotechnical approach for the prediction of rockfall triggering by performing laboratory tests on low-cohesive-matrix soil collected from steep slopes with 85° to 88° angles at the Tatta Pani site, Karakorum Highway (KKH), and then real-scale moisture-induced rockfall was conducted on site for the validation of laboratory data. Laboratory data of forty quick direct shear tests on samples collected from the field depicted a 3-fold drop in peak shear stress (PS) at the soil–soil interface and a 9.3-fold drop at the soil–rock interface by varying the moisture content from 1% (taken as dry phase) to a critical laboratory moisture content (MC)LC of 21% (taken as wet phase). Similarly, a drop in the elastic modulus (ES) was observed to be 5.7-fold at the soil–soil interface and 10-fold at the soil–rock interface for a variation of moisture content from 1 % to 21% for the matrix with a permeability (k) range of 3 × 10−4 to 5.6 × 10−4 m/s, which depicts the criticality of moisture content for the rockfall phenomenon. The critical moisture content evaluated in laboratory is validated by an innovative field-inundation method for thirty-two moisture-induced real-scale forced rockfall cases, which showed the rock-block triggering at field dry density (γd)f and the critical field moisture content (MC)FC of the matrix ranging from 1.78 g/cm3 to 1.92 g/cm3, and 1.3% to 25.4%, respectively. Hydrogeotechnical relations, i.e., MC versus PS and ES, at the soil–rock interface are developed for the prediction of rockfall triggering. The proposed correlations may be helpful in the prediction of rockfall hazards by using expected rainfall in the field for disaster warning and landslide disaster prevention at ecological geotechnical engineering projects. The results revealed that the critical (MC)FC and (MC)LC are within 20%, depicting a good confidence level of the outcomes of this research.
Modelling of Metaheuristics with Machine Learning-Enabled Cybersecurity in Unmanned Aerial Vehicles
Authors: Rizwanullah Mohammed , Mengash Hanan Abdullah , Alamgeer Mohammad , Tarmissi Khaled , Aziz Amira Sayed A. , Abdelmageed Amgad Atta , Alsaid Mohamed Ibrahim , Eldesouki Mohamed I.
Published: December 2022

The adoption and recent development of Unmanned Aerial Vehicles (UAVs) are because of their widespread applications in the private and public sectors, from logistics to environment monitoring. The incorporation of 5G technologies, satellites, and UAVs has provoked telecommunication networks to advance to provide more stable and high-quality services to remote areas. However, UAVs are vulnerable to cyberattacks because of the rapidly expanding volume and poor inbuilt security. Cyber security and the detection of cyber threats might considerably benefit from the development of artificial intelligence. A machine learning algorithm can be trained to search for attacks that may be similar to other types of attacks. This study proposes a new approach: metaheuristics with machine learning-enabled cybersecurity in unmanned aerial vehicles (MMLCS-UAVs). The presented MMLCS-UAV technique mainly focuses on the recognition and classification of intrusions in the UAV network. To obtain this, the presented MMLCS-UAV technique designed a quantum invasive weed optimization-based feature selection (QIWO-FS) method to select the optimal feature subsets. For intrusion detection, the MMLCS-UAV technique applied a weighted regularized extreme learning machine (WRELM) algorithm with swallow swarm optimization (SSO) as a parameter tuning model. The experimental validation of the MMLCS-UAV method was tested using benchmark datasets. This widespread comparison study reports the superiority of the MMLCS-UAV technique over other existing approaches.
Community and Cultural Entrepreneurship and Value Co-Creation in the Local Food Marketscape
Authors: Mars Matthew M.
Published: December 2022

Local food entrepreneurs are confronted with unique challenges when it comes to sustaining their firms and scaling their pro-community impact within geographically confined marketspaces. Yet, the strategies for overcoming these challenges remain under-studied within the community development and local food literatures. The current study addresses this scholarly gap through a qualitative case study of a southern Arizona artisan baker who follows a community-supported business model that strategically engages customers as value co-creators and stewards of a sustainable and scalable local consumption space. The study is conceptually framed by a set of principles that span community entrepreneurship, cultural entrepreneurship, and value co-creation. Data include semi-structured interviews with the baker and a sample of customers (n = 31), 20+ h of direct observations, and 3419 posts made within the bakery’s social media environment. The findings inform the theoretical development of a novel local food value co-creation model.
Impact of Institutional Pressure on Cleaner Production and Sustainable Firm Performance
Authors: Habib Md. Ahashan , Karim Md. Rezaul , Dulal Marzia , Munir Mohammad Shayekh
Published: December 2022

This study aspires to investigate the influence of institutional pressure (IP) on cleaner production (CLP) practices and sustainable firm performances in the clothing industry of Bangladesh. Moreover, the research work explores the mediating role of cleaner production between institutional pressure and firms’ environmental performance. It also analyzes environmental performance as a mediator between cleaner production and firms’ economic performance. Data were collected from 246 textile and garments manufacturing units and analyzed using structural equation modeling (SEM) with the partial least square (PLS) method. The study findings unveiled a direct and positive relationship between institutional pressure and cleaner production, environmental performance and cleaner production, and firms’ environmental and economic performance. The study’s results also reveals that cleaner production partially mediate the relationship between institutional pressure and environmental performance while environmental performance is also partially mediate between cleaner production and firm’s economic performance. The research outcomes recommend that the clothing manufacturing sector welcome institutional pressures and employ cleaner production practices, leading to sustainable performance. Finally, the study highlights the managerial and theoretical implications.
Enabling Risk Management and Adaptation to Climate Change through a Network of Peruvian Universities
Authors: Espinoza-Molina Jorge , Paucar-Cáceres Alberto , Silva-Cornejo Maria del Carmen , Quispe-Prieto Silvia , Acosta-Caipa Karina , Chambe-Vega Esther , Osco-Mamani Erbert , Cordova-Buiza Franklin , Burrowes-Cromwell Toni , Huerta-Tantalean Lucero Nicole
Published: December 2022

In recent decades, Latin America (LA) has been frequently and severely affected by floods and landslides. There is an urgency for adopting Comprehensive Disaster and Climate Risk Management (CRM). In 2016, a group of Peruvian universities established a network (Gestión Integral del Riesgo de Desastres y Adaptación al Cambio Climático (GIRD-ACC)) committed to the principles of CRM. This article compiles and evaluates the network results/plans and actions. A qualitative study and a methodological strategy are reported featuring: a bibliographic/network documentary review; an account of the events that led to the start and development of the network; and a case study of a three-university network. Results show that the network can help in deepening knowledge and forging a culture of risk prevention. This is by incorporating risk management and climate change awareness in professional training and intensive activity to meet the UN Sustainable Development Goals (SDGs -11, 13, and 17). Results indicate the importance of gaining consensus (a notoriously difficult task in LA) between the authorities and the operational departments; the role of universities’ social responsibilities; incorporating sustainability and risk management themes in the mainstream curricula; and developing a network by learning from similar groupings across LA to improve CRM within universities.
Application of Seismic Fragility of Buried Piping Systems with Bellows Expansion Joints
Authors: Ryu Joon-Il , Jeon Bub-Gyu , Son Ho-Young , Ju Bu-Seog
Published: December 2022

Bellows expansion joints are known to have a large displacement capacity and can thus be potentially used to improve the seismic performance of buried piping systems. However, there are no guidelines on the installation of bellows expansion joints for the seismic performance improvement of buried piping systems. Furthermore, there are very few studies on the seismic performance of buried piping systems with bellows expansion joints. In this study, therefore, we performed seismic fragility analysis according to the installation conditions to obtain basic data for the installation guidelines of bellows expansion joints. Therefore, in this study, an experimental test was performed on bellows expansion joints considering the characteristics of earthquake loading conditions, and a 3D finite element (FE) model using the ABAQUS platform was developed and validated based on the experimental results. This model was verified by comparing the force-displacement relationship and energy dissipation. Leakage occurred at a displacement of 113.6 mm in the experiment, and the FE analysis result was also applied up to the same displacement. In the case of energy dissipation, an error between the FE model and experimental result was determined not to be significant. However, the appearance of such physical performance errors is due to the manufacturing errors resulting from the bellows forming process and the variability of material properties. Finally, seismic fragility analysis of buried pipeline systems with bellows expansion joints was performed. In addition, the following cases were used for analysis according to whether bellows were applied or not: (1) without a bellows expansion joints; (2) with a single bellows expansion joint; and (3) with two bellows expansion joints. In conclusion, it was found that the seismic performance of the buried pipeline system was improved when bellows were applied. However, the effect of the seismic fragility curve according to the increase in the number of bellows was insignificant.