bluuebunny/crossref_metadata_2025 huggingface dataset:
Rupture Kinematics and Coseismic Slip Model of the 2021 Mw 7.3 Maduo (China) Earthquake: Implications for the Seismic Hazard of the Kunlun Fault
Authors: Chen Han , Qu Chunyan , Zhao Dezheng , Ma Chao , Shan Xinjian
Published: August 2021

The 21 May 2021 Maduo earthquake was the largest event to occur on a secondary fault in the interior of the active Bayanhar block on the north-central Tibetan plateau in the last twenty years. A detailed kinematic study of the Maduo earthquake helps us to better understand the seismogenic environments of the secondary faults within the block, and its relationship with the block-bounding faults. In this study, firstly, SAR images are used to obtain the coseismic deformation fields. Secondly, we use a strain model-based method and steepest descent method (SDM) to resolve the three-dimensional displacement components and to invert the coseismic slip distribution constrained by coseismic displacement fields, respectively. The three-dimensional displacement fields reveal a dominant left-lateral strike-slip motion, local horizontal displacement variations and widely distributed near-fault subsidence/uplift deformation. We prefer a five-segment fault slip model, with well constrained fault geometry featuring different dip angles and striking, constrained by InSAR observations. The peak coseismic slip is estimated to be ~5 m near longitude 98.9°E at a depth of ~4–7 km. Overall, the distribution of the coseismic slip on the fault is highly correlated to the measured surface displacement offsets along the entire rupture. We observe the moderate shallow slip deficit and limited afterslip deformation following the Maduo earthquake, it may indicate the effects of off-fault deformation during the earthquake and stable interseismic creep on the fault. The occurrence of the Maduo earthquake on a subsidiary fault updates the importance and the traditional estimate of the seismic hazards for the Kunlun fault.
A New Multi-Scale Sliding Window LSTM Framework (MSSW-LSTM): A Case Study for GNSS Time-Series Prediction
Authors: Wang Jian , Jiang Weiping , Li Zhao , Lu Yang
Published: August 2021

GNSS time-series prediction plays an important role in the monitoring of crustal plate movement, and dam or bridge deformation, and the maintenance of global or regional coordinate frames. Deep learning is a state-of-the-art approach for extracting high-level abstract features from big data without any prior knowledge. Moreover, long short-term memory (LSTM) networks are a form of recurrent neural networks that have significant potential for processing time series. In this study, a novel prediction framework was proposed by combining a multi-scale sliding window (MSSW) with LSTM. Specifically, MSSW was applied for data preprocessing to effectively extract the feature relationship at different scales and simultaneously mine the deep characteristics of the dataset. Then, multiple LSTM neural networks were used to predict and obtain the final result by weighting. To verify the performance of MSSW-LSTM, 1000 daily solutions of the XJSS station in the Up component were selected for prediction experiments. Compared with the traditional LSTM method, our results of three groups of controlled experiments showed that the RMSE value was reduced by 2.1%, 23.7%, and 20.1%, and MAE was decreased by 1.6%, 21.1%, and 22.2%, respectively. Our results showed that the MSSW-LSTM algorithm can achieve higher prediction accuracy and smaller error, and can be applied to GNSS time-series prediction.
High Speed Maneuvering Platform Squint TOPS SAR Imaging Based on Local Polar Coordinate and Angular Division
Authors: Bie Bowen , Quan Yinghui , Xu Kaijie , Sun Guangcai , Xing Mengdao
Published: August 2021

This paper proposes an imaging algorithm for synthetic aperture radar (SAR) mounted on a high-speed maneuvering platform with squint terrain observation by progressive scan mode. To overcome the mismatch between range model and the signal after range walk correction, the range history is calculated in local polar format. The Doppler ambiguity is resolved by nonlinear derotation and zero-padding. The recovered signal is divided into several blocks in Doppler according to the angular division. Keystone transform is used to remove the space-variant range cell migration (RCM) components. Thus, the residual RCM terms can be compensated by a unified phase function. Frequency domain perturbation terms are introduced to correct the space-variant Doppler chirp rate term. The focusing parameters are calculated according to the scene center of each angular block and the signal of each block can be processed in parallel. The image of each block is focused in range-Doppler domain. After the geometric correction, the final focused image can be obtained by directly combined the images of all angular blocks. Simulated SAR data has verified the effectiveness of the proposed algorithm.
Understanding Spatio-Temporal Patterns of Land Use/Land Cover Change under Urbanization in Wuhan, China, 2000–2019
Authors: Zhai Han , Lv Chaoqun , Liu Wanzeng , Yang Chao , Fan Dasheng , Wang Zikun , Guan Qingfeng
Published: August 2021

Exploring land use structure and dynamics is critical for urban planning and management. This study attempts to understand the Wuhan development mode since the beginning of the 21st century by profoundly investigating the spatio-temporal patterns of land use/land cover (LULC) change under urbanization in Wuhan, China, from 2000 to 2019, based on continuous time series mapping using Landsat observations with a support vector machine. The results indicated rapid urbanization, with large LULC changes triggered. The built-up area increased by 982.66 km2 (228%) at the expense of a reduction of 717.14 km2 (12%) for cropland, which threatens food security to some degree. In addition, the natural habitat shrank to some extent, with reductions of 182.52 km2, 23.92 km2 and 64.95 km2 for water, forest and grassland, respectively. Generally, Wuhan experienced a typical urbanization course that first sped up, then slowed down and then accelerated again, with an obvious internal imbalance between the 13 administrative districts. Hanyang, Hongshan and Dongxihu specifically presented more significant land dynamicity, with Hanyang being the active center. Over the past 19 years, Wuhan mainly developed toward the east and south, with the urban gravity center transferred from the northwest to the southeast of Jiang’an district. Lastly, based on the predicted land allocation of Wuhan in 2029 by the patch-generating land use simulation (PLUS) model, the future landscape dynamic pattern was further explored, and the result shows a rise in the northern suburbs, which provides meaningful guidance for urban planners and managers to promote urban sustainability.
Estimating Rainfall with Multi-Resource Data over East Asia Based on Machine Learning
Authors: Zhang Yushan , Wu Kun , Zhang Jinglin , Zhang Feng , Xiao Haixia , Wang Fuchang , Zhou Jianyin , Song Yi , Peng Liang
Published: August 2021

The lack of accurate estimation of intense precipitation is a universal limitation in precipitation retrieval. Therefore, a new rainfall retrieval technique based on the Random Forest (RF) algorithm is presented using the Advanced Himawari Imager-8 (Himawari-8/AHI) infrared spectrum data and the NCEP operational Global Forecast System (GFS) forecast information. And the gauge-calibrated rainfall estimates from the Global Precipitation Measurement (GPM) product served as the ground truth to train the model. The two-step RF classification model was established for (1) rain area delineation and (2) precipitation grades’ estimation to improve the accuracy of moderate rain and heavy rain. In view of the imbalance categories’ distribution in the datasets, the resampling technique including the Random Under-sampling algorithm and Synthetic Minority Over-sampling Technique (SMOTE) was implemented throughout the whole training process to fully learn the characteristics among the samples. Among the features used, the contributions of meteorological variables to the trained models were generally greater than those of infrared information; in particular, the contribution of precipitable water was the largest, indicating the sufficient necessity of water vapor conditions in rainfall forecasting. The simulation results by the RF model were compared with the GPM product pixel-by-pixel. To prove the universality of the model, we used independent validation sets which are not used for training and two independent testing sets with different periods from the training set. In addition, the algorithm was validated against independent rain gauge data and compared with GFS model rainfall. Consequently, the RF model identified rainfall areas with a Probability Of Detection (POD) of around 0.77 and a False-Alarm Ratio (FAR) of around 0.23 for validation, as well as a POD of 0.60–0.70 and a FAR of around 0.30 for testing. To estimate precipitation grades, the value of classification was 0.70 in validation and in testing the accuracy was 0.60 despite a certain overestimation. In summary, the performance on the validation and test data indicated the great adaptability and superiority of the RF algorithm in rainfall retrieval in East Asia. To a certain extent, our study provides a meaningful range division and powerful guidance for quantitative precipitation estimation.
Interseismic Slip and Coupling along the Haiyuan Fault Zone Constrained by InSAR and GPS Measurements
Authors: Qiao Xin , Qu Chunyan , Shan Xinjian , Zhao Dezheng , Liu Lian
Published: August 2021

The Haiyuan fault zone is an important tectonic boundary and strong seismic activity belt in northeastern Tibet, but no major earthquake has occurred in the past ∼100 years, since the Haiyuan M8.5 event in 1920. The current state of strain accumulation and seismic potential along the fault zone have attracted significant attention. In this study, we obtained the interseismic deformation field along the Haiyuan fault zone using Envisat/ASAR data in the period 2003–2010, and inverted fault kinematic parameters including the long-term slip rate, locking degree and slip deficit distribution based on InSAR and GPS individually and jointly. The results show that there is near-surface creep in the Laohushan segment of about 19 km. The locking degree changes significantly along the strike with the western part reaching 17 km and the eastern part of 3–7 km. The long-term slip rate gradually decreases from west 4.7 mm/yr to east 2.0 mm/yr. As such, there is large strain accumulation along the western part of the fault and shallow creep along the Laohushan segment; while in the eastern section, the degree of strain accumulation is low, which suggests the rupture segments of the 1920 earthquake may have been not completely relocked.
Diurnal Cycle Model of Lake Ice Surface Albedo: A Case Study of Wuliangsuhai Lake
Authors: Li Zhijun , Wang Qingkai , Tang Mingguang , Lu Peng , Li Guoyu , Leppäranta Matti , Huotari Jussi , Arvola Lauri , Shi Lijuan
Published: August 2021

Ice surface albedo is an important factor in various optical remote sensing technologies used to determine the distribution of snow or melt water on the ice, and to judge the formation or melting of lake ice in winter, especially in cold and arid areas. In this study, field measurements were conducted at Wuliangsuhai Lake, a typical lake in the semi-arid cold area of China, to investigate the diurnal variation of the ice surface albedo. Observations showed that the diurnal variations of the ice surface albedo exhibit bimodal characteristics with peaks occurring after sunrise and before sunset. The curve of ice surface albedo with time is affected by weather conditions. The first peak occurs later on cloudy days compared with sunny days, whereas the second peak appears earlier on cloudy days. Four probability density distribution functions—Laplace, Gauss, Gumbel, and Cauchy—were combined linearly to model the daily variation of the lake ice albedo on a sunny day. The simulations of diurnal variation in the albedo during the period from sunrise to sunset with a solar altitude angle higher than 5° indicate that the Laplace combination is the optimal statistical model. The Laplace combination can not only describe the bimodal characteristic of the diurnal albedo cycle when the solar altitude angle is higher than 5°, but also reflect the U-shaped distribution of the diurnal albedo as the solar altitude angle exceeds 15°. The scale of the model is about half the length of the day, and the position of the two peaks is closely related to the moment of sunrise, which reflects the asymmetry of the two peaks of the ice surface albedo. This study provides a basis for the development of parameterization schemes of diurnal variation of lake ice albedo in semi-arid cold regions.
Using Privacy Respecting Sound Analysis to Improve Bluetooth Based Proximity Detection for COVID-19 Exposure Tracing and Social Distancing
Authors: Bahle Gernot , Fortes Rey Vitor , Bian Sizhen , Bello Hymalai , Lukowicz Paul
Published: August 2021

We propose to use ambient sound as a privacy-aware source of information for COVID-19-related social distance monitoring and contact tracing. The aim is to complement currently dominant Bluetooth Low Energy Received Signal Strength Indicator (BLE RSSI) approaches. These often struggle with the complexity of Radio Frequency (RF) signal attenuation, which is strongly influenced by specific surrounding characteristics. This in turn renders the relationship between signal strength and the distance between transmitter and receiver highly non-deterministic. We analyze spatio-temporal variations in what we call “ambient sound fingerprints”. We leverage the fact that ambient sound received by a mobile device is a superposition of sounds from sources at many different locations in the environment. Such a superposition is determined by the relative position of those sources with respect to the receiver. We present a method for using the above general idea to classify proximity between pairs of users based on Kullback–Leibler distance between sound intensity histograms. The method is based on intensity analysis only, and does not require the collection of any privacy sensitive signals. Further, we show how this information can be fused with BLE RSSI features using adaptive weighted voting. We also take into account that sound is not available in all windows. Our approach is evaluated in elaborate experiments in real-world settings. The results show that both Bluetooth and sound can be used to differentiate users within and out of critical distance (1.5 m) with high accuracies of 77% and 80% respectively. Their fusion, however, improves this to 86%, making evident the merit of augmenting BLE RSSI with sound. We conclude by discussing strengths and limitations of our approach and highlighting directions for future work.
Development of an Inexpensive Harnessing System Allowing Independent Gardening for Balance Training for Mobility Impaired Individuals
Authors: Newell McPherson , Reinthal Ann , Espy Debbie , Ekelman Beth
Published: August 2021

Balance is key to independent mobility, and poor balance leads to a risk of falling and subsequent injury that can cause self-restriction of activity for older adults. Balance and mobility can be improved through training programs, but many programs are not intensive or engaging enough to sufficiently improve balance while maintaining adherence. As an alternative to traditional balance training, harnessed gardening sessions were conducted in an urban greenhouse as an example of a community activity through which balance and mobility can be trained and/or maintained. An inexpensive multidirectional harness system was developed that can be used as an assistive or rehabilitative device in community, private, and senior center gardens to allow balance or mobility-impaired adults to participate in programming. Two wearable sensor systems were used to measure responses to the system: the Polhemus G4 system measured gardeners’ positions and center of mass relative to the base of support, and ActiGraph activity monitors measured the frequency and intensity of arm movements in garden as compared to home environments. The harnessed gardening system provides a safe environment for intense movement activity and can be used as a rehabilitation device along with wearable sensor systems to monitor ongoing changes.
A Multichannel Strain Measurement Technique for Nanomodified Smart Cement-Based Sensors in Reinforced Concrete Structures
Authors: Meoni Andrea , D’Alessandro Antonella , Mancinelli Massimo , Ubertini Filippo
Published: August 2021

Nanomodified smart cement-based sensors are an emerging self-sensing technology for the structural health monitoring (SHM) of reinforced concrete (RC) structures. To date, several literature works demonstrated their strain-sensing capabilities, which make them suited for damage detection and localization. Despite the most recent technological improvements, a tailored measurement technique allowing feasible field implementations of smart cement-based sensors to concrete structures is still missing. In this regard, this paper proposes a multichannel measurement technique for retrieving strains from smart cement-based sensors embedded in RC structures using a distributed biphasic input. The experiments performed for its validation include the investigation on an RC beam with seven embedded sensors subjected to different types of static loading and a long-term monitoring application on an RC plate. Results demonstrate that the proposed technique is effective for retrieving time-stable simultaneous strain measurements from smart cement-based sensors, as well as for aiding the identification of the changes in their electrical outputs due to the influence of environmental effects variable over time. Accordingly, the proposed multichannel strain measurement technique represents a promising approach for performing feasible field implementations of smart cement-based sensors to concrete structures.
Calderón’s Method with a Spatial Prior for 2-D EIT Imaging of Ventilation and Perfusion
Authors: Shin Kwancheol , Mueller Jennifer L.
Published: August 2021

Bedside imaging of ventilation and perfusion is a leading application of 2-D medical electrical impedance tomography (EIT), in which dynamic cross-sectional images of the torso are created by numerically solving the inverse problem of computing the conductivity from voltage measurements arising on electrodes due to currents applied on electrodes on the surface. Methods of reconstruction may be direct or iterative. Calderón’s method is a direct reconstruction method based on complex geometrical optics solutions to Laplace’s equation capable of providing real-time reconstructions in a region of interest. In this paper, the importance of accurate modeling of the electrode location on the body is demonstrated on simulated and experimental data, and a method of including a priori spatial information in dynamic human subject data is presented. The results of accurate electrode modeling and a spatial prior are shown to improve detection of inhomogeneities not included in the prior and to improve the resolution of ventilation and perfusion images in a human subject.
A Data Analytics/Big Data Framework for Advanced Metering Infrastructure Data
Authors: Guerrero-Prado Jenniffer S. , Alfonso-Morales Wilfredo , Caicedo-Bravo Eduardo F.
Published: August 2021

The Advanced Metering Infrastructure (AMI) data represent a source of information in real time not only about electricity consumption but also as an indicator of other social, demographic, and economic dynamics within a city. This paper presents a Data Analytics/Big Data framework applied to AMI data as a tool to leverage the potential of this data within the applications in a Smart City. The framework includes three fundamental aspects. First, the architectural view places AMI within the Smart Grids Architecture Model-SGAM. Second, the methodological view describes the transformation of raw data into knowledge represented by the DIKW hierarchy and the NIST Big Data interoperability model. Finally, a binding element between the two views is represented by human expertise and skills to obtain a deeper understanding of the results and transform knowledge into wisdom. Our new view faces the challenges arriving in energy markets by adding a binding element that gives support for optimal and efficient decision-making. To show how our framework works, we developed a case study. The case implements each component of the framework for a load forecasting application in a Colombian Retail Electricity Provider (REP). The MAPE for some of the REP’s markets was less than 5%. In addition, the case shows the effect of the binding element as it raises new development alternatives and becomes a feedback mechanism for more assertive decision making.
Evaluation of the Uniformity of Protective Coatings on Concrete Structure Surfaces Based on Cluster Analysis
Authors: Liu Dunwen , Zhang Wanmao , Tang Yu , Jian Yinghua , Gong Chun , Qiu Fengkai
Published: August 2021

With the continuous development of urbanization and industrialization in the world, concrete is widely used in various engineering constructions as an engineering material. However, the consequent problem of durability of concrete structures is also becoming increasingly prominent. As an important additional measure, a protective coating can effectively improve the durability of concrete performance. Moreover, the uniformity of the concrete surface coating will directly affect its protective effect. Therefore, we propose a nondestructive inspection and evaluation method of coating uniformity based on infrared imaging and cluster analysis for concrete surface coating uniformity detection and evaluation. Based on the obtained infrared images, a series of processing and analysis of the images were carried out using MATLAB software to obtain the characteristics of the infrared images of the concrete surface. Finally, by extracting the temperature distribution data of the pixel points on the concrete surface, an evaluation method of concrete surface coating uniformity based on a combination of cluster analysis and hierarchical analysis was established. The evaluation results show that the determination results obtained by this method are consistent with the actual situation. This study has a positive contribution to the testing of concrete surface coating uniformity and its evaluation.
IoT Sensor Networks in Smart Buildings: A Performance Assessment Using Queuing Models
Authors: Santos Brena , Soares André , Nguyen Tuan-Anh , Min Dug-Ki , Lee Jae-Woo , Silva Francisco-Airton
Published: August 2021

Smart buildings in big cities are now equipped with an internet of things (IoT) infrastructure to constantly monitor different aspects of people’s daily lives via IoT devices and sensor networks. The malfunction and low quality of service (QoS) of such devices and networks can severely cause property damage and perhaps loss of life. Therefore, it is important to quantify different metrics related to the operational performance of the systems that make up such computational architecture even in advance of the building construction. Previous studies used analytical models considering different aspects to assess the performance of building monitoring systems. However, some critical points are still missing in the literature, such as (i) analyzing the capacity of computational resources adequate to the data demand, (ii) representing the number of cores per machine, and (iii) the clustering of sensors by location. This work proposes a queuing network based message exchange architecture to evaluate the performance of an intelligent building infrastructure associated with multiple processing layers: edge and fog. We consider an architecture of a building that has several floors and several rooms in each of them, where all rooms are equipped with sensors and an edge device. A comprehensive sensitivity analysis of the model was performed using the Design of Experiments (DoE) method to identify bottlenecks in the proposal. A series of case studies were conducted based on the DoE results. The DoE results allowed us to conclude, for example, that the number of cores can have more impact on the response time than the number of nodes. Simulations of scenarios defined through DoE allow observing the behavior of the following metrics: average response time, resource utilization rate, flow rate, discard rate, and the number of messages in the system. Three scenarios were explored: (i) scenario A (varying the number of cores), (ii) scenario B (varying the number of fog nodes), and (iii) scenario C (varying the nodes and cores simultaneously). Depending on the number of resources (nodes or cores), the system can become so overloaded that no new requests are supported. The queuing network based message exchange architecture and the analyses carried out can help system designers optimize their computational architectures before building construction.
Removal of ECG Artifacts Affects Respiratory Muscle Fatigue Detection—A Simulation Study
Authors: Kahl Lorenz , Hofmann Ulrich
Published: August 2021

This work investigates elimination methods for cardiogenic artifacts in respiratory surface electromyographic (sEMG) signals and compares their performance with respect to subsequent fatigue detection with different fatigue algorithms. The analysis is based on artificially constructed test signals featuring a clearly defined expected fatigue level. Test signals are additively constructed with different proportions from sEMG and electrocardiographic (ECG) signals. Cardiogenic artifacts are eliminated by high-pass filtering (HP), template subtraction (TS), a newly introduced two-step approach (TSWD) consisting of template subtraction and a wavelet-based damping step and a pure wavelet-based damping (DSO). Each method is additionally combined with the exclusion of QRS segments (gating). Fatigue is subsequently quantified with mean frequency (MNF), spectral moments ratio of order five (SMR5) and fuzzy approximate entropy (fApEn). Different combinations of artifact elimination methods and fatigue detection algorithms are tested with respect to their ability to deliver invariant results despite increasing ECG contamination. Both DSO and TSWD artifact elimination methods displayed promising results regarding the intermediate, “cleaned” EMG signal. However, only the TSWD method enabled superior results in the subsequent fatigue detection across different levels of artifact contamination and evaluation criteria. SMR5 could be determined as the best fatigue detection algorithm. This study proposes a signal processing chain to determine neuromuscular fatigue despite the presence of cardiogenic artifacts. The results furthermore underline the importance of selecting a combination of algorithms that play well together to remove cardiogenic artifacts and to detect fatigue. This investigation provides guidance for clinical studies to select optimal signal processing to detect fatigue from respiratory sEMG signals.
An Analysis of Android Malware Classification Services
Authors: Rashed Mohammed , Suarez-Tangil Guillermo
Published: August 2021

The increasing number of Android malware forced antivirus (AV) companies to rely on automated classification techniques to determine the family and class of suspicious samples. The research community relies heavily on such labels to carry out prevalence studies of the threat ecosystem and to build datasets that are used to validate and benchmark novel detection and classification methods. In this work, we carry out an extensive study of the Android malware ecosystem by surveying white papers and reports from 6 key players in the industry, as well as 81 papers from 8 top security conferences, to understand how malware datasets are used by both. We, then, explore the limitations associated with the use of available malware classification services, namely VirusTotal (VT) engines, for determining the family of an Android sample. Using a dataset of 2.47 M Android malware samples, we find that the detection coverage of VT’s AVs is generally very low, that the percentage of samples flagged by any 2 AV engines does not go beyond 52%, and that common families between any pair of AV engines is at best 29%. We rely on clustering to determine the extent to which different AV engine pairs agree upon which samples belong to the same family (regardless of the actual family name) and find that there are discrepancies that can introduce noise in automatic label unification schemes. We also observe the usage of generic labels and inconsistencies within the labels of top AV engines, suggesting that their efforts are directed towards accurate detection rather than classification. Our results contribute to a better understanding of the limitations of using Android malware family labels as supplied by common AV engines.
Multi-Objective Optimisation of Biodiesel Synthesis in Simulated Moving Bed Reactor
Authors: Ray Nillohit , Ray Ajay
Published: August 2021

In this work, multi-objective optimisation study was performed to determine the performance improvement in a simulated moving bed reactor (SMBR) for biodiesel synthesis. The selection of the operating parameters such as switching time, liquid flow rates in various sections, as well as the length and number of columns is not straightforward in an SMBR. In most cases, conflicting requirements and constraints influence the optimal selection of the decision (operating or design) variables. A mathematical model that predicts single-column experimental results well was modified and verified experimentally for multiple-column SMBR system. In this article, a few multi-objective optimisation problems were carried out for both existing set-up as well as at the design stage. A non-dominated sorting genetic algorithm (NSGA) was used as the optimisation tool for the optimisation study. Due to conflicting effect of process parameters, the multi-objective optimisation study resulted in non-dominated Pareto optimal solutions. It was shown that significant increase in yield and purity of biodiesel in SMBR was possible both for operating and at design stage.
Quantification of Histidine-Containing Dipeptides in Dolphin Serum Using a Reversed-Phase Ion-Pair High-Performance Liquid Chromatography Method
Authors: Kumagai Momochika , Kato Sanae , Arakawa Nanami , Otsuka Mika , Hamano Takahisa , Kashiwagi Nobuyuki , Yabuki Akira , Yamato Osamu
Published: August 2021

The quantification of histidine-containing dipeptides (anserine, carnosine, and balenine) in serum might be a diagnostic tool to assess the health condition of animals. In this study, an existing reversed-phase ion-pair high-performance liquid chromatography (HPLC)–ultraviolet detection method was improved and validated to quantify serum anserine, carnosine, and balenine levels in the dolphin. The serum was deproteinized with trichloroacetic acid and directly injected into the HPLC system. Chromatographic separation of the three histidine-containing dipeptides was achieved on a TSK–gel ODS-80Ts (4.6 mm × 150 mm, 5 µm) analytical column using a mobile phase of 50 mmol/L potassium dihydrogen phosphate (pH 3.4) containing 6 mmol/L 1-heptanesulfonic acid and acetonitrile (96:4). The standard curve ranged from 0.1 µmol/L to 250 µmol/L. The average accuracy of the intra- and inter-analysis of anserine, carnosine, and balenine was 97–106%. The relative standard deviations of total precision (RSDr) of anserine, carnosine, and balenine in dolphin serum were 5.9%, 4.1%, and 2.6%, respectively. The lower limit of quantification of these compounds was 0.11–0.21 µmol/L. These results indicate that the improved method is reliable and concise for the simultaneous determination of anserine, carnosine, and balenine in dolphin serum, and may be useful for evaluation of health conditions in dolphins. Furthermore, this method can also be applied to other biological samples.
Modelling Salinity and Sodicity Risks of Long-Term Use of Recycled Water for Irrigation of Horticultural Crops
Authors: Phogat Vinod , Mallants Dirk , Šimůnek Jirka , Cox James W. , Petrie Paul R. , Pitt Timothy
Published: August 2021

Long-term use of recycled water (RW) for irrigation in arid and semiarid regions usually changes the soil solution composition and soil exchange characteristics, enhancing the risk for salinity and sodicity hazards in soils. This modelling study focuses on developing alternative management options that can reduce the potentially harmful impacts of RW use on the irrigation of wine grapes and almonds. The multicomponent UNSATCHEM add-on module for HYDRUS-1D was used to evaluate the impact of long-term (2018–2050) use of irrigation waters of different compositions: good-quality low-salinity (175 mg/L) water (GW), recycled water with 1200 mg/L salinity (RW), blended water of GW and RW in the 1:1 proportion (B), and monthly (Alt1) and half-yearly (Alt6) alternate use of GW and RW. The management options include different levels of annual gypsum applications (0, 1.7, 4.3, and 8.6 t/ha soil) to the calcareous (Cal) and hard red-brown (HRB) soils occurring in the Northern Adelaide Plain (NAP) region, South Australia. Additional management scenarios involve considering different leaching fractions (LF) (0.2, 0.3, 0.4, and 0.5) to reduce the salinity build-up in the soil. A new routine in UNSATCHEM to simulate annual gypsum applications was developed and tested for its applicability for ameliorating irrigation-induced soil sodicity. The 1970–2017 period with GW irrigation was used as a warmup period for the model. The water quality was switched from 2018 onwards to reflect different irrigation water qualities, gypsum applications, and LF levels. The data showed that the GW, B, Alt1, and Alt6 irrigation scenarios resulted in lower soil solution salinity (ECsw) than the RW irrigation scenario, which led to increased ECsw values (4.1–6.6 dS/m) in the soil. Annual gypsum applications of 1.7, 4.3, and 8.6 t/ha reduced pH, SAR, and ESP in both soils and reduced the adverse impacts of irrigation, especially in surface soils. A combination of water blending or cyclic water use with 3.8 t/ha annual gypsum applications showed promise for the SAR and ESP control. Additionally, irrigation with RW, a 0.2 LF, and annual gypsum applications limited the harmful salinity impacts in the soils. However, in the RW irrigation scenario, ECsw and ESP at the bottom of the crop root zone (90–120 cm depth) in the HRB soil were still higher than the wine grape and almond salinity thresholds. Thus, annual amendment applications, combined with the long-term use of blended water or cyclic use of RW and GW, represent a sustainable management option for crop production at the calcareous and hard red-brown soils.
A Unique Unified Wind Speed Approach to Decision-Making for Dispersed Locations
Authors: Mansour Ayman M. , Almutairi Abdulaziz , Alyami Saeed , Obeidat Mohammad A. , Almkahles Dhafer , Sathik Jagabar
Published: August 2021

The repercussions of high levels of environmental pollution coupled with the low reserves and increased costs of traditional energy sources have led to the widespread adaptation of wind energy worldwide. However, the expanded use of wind energy is accompanied by major challenges for electric grid operators due to the difficulty of controlling and forecasting the production of wind energy. The development of methods for addressing these problems has therefore attracted the interest of numerous researchers. This paper presents an innovative method for assessing wind speed in different and widely spaced locations. The new method uses wind speed data from multiple sites as a single package that preserves the characteristics of the correlations among those sites. Powerful Waikato Environment for Knowledge Analysis (Weka) machine learning software has been employed for supporting data preprocessing, clustering, classification, visualization, and feature selection and for using a standard algorithm to construct decision trees according to a training set. The resultant arrangement of the sites according to likely wind energy productivity facilitates enhanced decisions related to the potential for the effective operation of wind energy farms at the sites. The proposed method is anticipated to provide network operators with an understanding of the possible productivity of each site, thus facilitating their optimal management of network operations. The results are also expected to benefit investors interested in establishing profitable projects at those locations.
Industrial-Scale Hydrothermal Carbonization of Agro-Industrial Digested Sludge: Filterability Enhancement and Phosphorus Recovery
Authors: Lucian Michela , Merzari Fabio , Gubert Michele , Messineo Antonio , Volpe Maurizio
Published: August 2021

Hydrothermal carbonization (HTC) provides an attractive alternative method for the treatment of high-moisture waste and, in particular, digested sludge. HTC could reduce the costs and environmental risks associated with sludge handling and management. Although it is recognized that the dewaterability of hydrochars produced from digested sludge, even at mild temperatures (180–190 °C), is highly improved with respect to the starting material, the filterability of HTC slurries for the recovery of the solid material (hydrochar) still represents a challenge. This study presents the results of an investigation into the filterability of agro-industrial digested sludge HTC slurries produced by a C-700 CarboremTM HTC industrial-scale plant. The filterability of HTC slurries, produced at 190 °C for 1 h, with the use of acid solutions of hydrochloric acid, sulfuric acid or citric acids, was investigated by using a semi-industrial filter press. The use of sulfuric acid or citric acid solutions, in particular, significantly improved the filterability of HTC slurries, reducing the time of filtration and residual moisture content. The acid treatment also promoted the migration of heavy metals and phosphorus (P) in the HTC filtrate solution. This study demonstrates that P can be recovered via the precipitation of struvite in high yields, recovering up to 85 wt% by mass of its initial P content.
Sustainable Urban Development: A Review of Urban Sustainability Indicator Frameworks
Authors: Michalina Denis , Mederly Peter , Diefenbacher Hans , Held Benjamin
Published: August 2021

The issue of urban sustainability is currently exceptionally up to date, and the sustainable development of cities has become an important topic on the political level. Many cities in the world are facing acute challenges concerning growing dangers to the environment and ensuring quality of life for their inhabitants. In connection with cities achieving their individual goals of sustainable development, urban sustainability indicator frameworks (USIFs) are becoming the subjects of attention. Such frameworks enable sustainability to be clearly measured and assessed. In this article, we analysed selected global and European USIFs in terms of their commonalities and differences, sustainability dimensions, thematic categories, and categorised indicators. Based on the analysis of the content of the reviewed frameworks, we compiled a list of generally recognised thematic categories within the four main dimensions of sustainable development, and we identified the key indicators of urban sustainability. Our review showed differences in the existing approaches that substantially contributed to the current inconsistencies in assessing and measuring sustainable development in cities. Our results provide an overview of this issue, e.g., to decision makers, and could concurrently serve as a generally applicable foundation for the creation of new urban sustainability indicator frameworks. We also point out the current trends and challenges in the domain of urban sustainability assessment.
Agricultural Water Management Using Two-Stage Channels: Performance and Policy Recommendations Based on Northern European Experiences
Authors: Västilä Kaisa , Väisänen Sari , Koskiaho Jari , Lehtoranta Virpi , Karttunen Krister , Kuussaari Mikko , Järvelä Juha , Koikkalainen Kauko
Published: August 2021

Conventional dredging of ditches and streams to ensure agricultural drainage and flood mitigation can have severe environmental impacts. The aim of this paper is to investigate the potential benefits of an alternative, nature-based two-stage channel (TSC) design with floodplains excavated along the main channel. Through a literature survey, investigations at Finnish field sites and expert interviews, we assessed the performance, costs, and monetary environmental benefits of TSCs in comparison to conventional dredging, as well as the bottlenecks in their financing and governance. We found evidence supporting the expected longer-term functioning of drainage as well as larger plant and fish biodiversity in TSCs compared to conventional dredging. The TSC design likely improves water quality since the floodplains retain suspended sediment and phosphorus and remove nitrogen. In the investigated case, the additional value of phosphorus retention and conservation of protected species through the TSC design was 2.4 times higher than the total costs. We demonstrate how TSCs can be made eligible for the obligatory vegetated riparian buffer of the European Union agri-environmental subsidy scheme (CAP-AES) by optimising their spatial application with respect to other buffer measures, and recommend to publicly finance their additional costs compared to conventional dredging at priority sites. Further studies on biodiversity impacts and long-term performance of two-stage channels are required.
Policies as Drivers for Circular Economy in the Construction Sector in the Nordics
Authors: zu Castell-Rüdenhausen Malin , Wahlström Margareta , Astrup Thilde Fruergaard , Jensen Carl , Oberender Anke , Johansson Pernilla , Waerner Eirik Rudi
Published: August 2021

A circular economy (CE) represents the key alternative to the linear ‘take-make-consume-dispose’ economic model, that still predominates in the construction sector. This study investigates how policies support CE-focused businesses in the construction sector in the Nordics. A literature review, the creation of a database, a review of Nordic actors with a CE focus, and targeted interviews with actors across the value chain of the construction sector in Denmark, Finland, Norway, and Sweden enabled us to benchmark the CE policy landscape and assess how CE policies at different levels support CE business models in the construction sector. The results show that the construction sector is well represented in the CE policy frameworks and that many business opportunities are created when national and local policies are put into practice. The implementation of policies is mainly done via three key concepts, i.e., planning, requirements for sustainable constructions, and requirements for public procurement. It can be concluded that policies are drivers for the implementation of a CE and support CE business models in the Nordics.
A Public Bad Game Method to Study Dynamics in Socio-Ecological Systems (Part II): Results of Testing Musa-Game in Rwanda and Adding Emergence and Spatiality to the Analysis
Authors: Galarza-Villamar Julissa Alexandra , McCampbell Mariette , Galarza-Villamar Andres , Leeuwis Cees , Cecchi Francesco , Galarza-Rodrigo John
Published: August 2021

This article is the second in a series of two and presented findings from field-testing an experimental boardgame (Musa-game) with banana farmers in four villages in Eastern Rwanda. The conceptualization and design of the Musa-game were described in Part I. Musa-game gives insights into how farmers’ individual and collective decision-making and actions regarding management of a public bad interplay with other factors and characteristics of the socio-ecological system (SES). A public bad is a non-rivalrous, non-excludable issue that causes loss of social-welfare of individuals and communities. The method contributes contextual understanding about the emergence of phenomena that arise from the interactions between human and non-human actors. Musa-game was framed to study one public bad challenge in particular: the infectious crop disease Banana Xanthomonas Wilt disease (BXW). Findings increased the knowhow about the emergence and governance of conditions that hinder or enhance the spread of infectious diseases like BXW. Analysis of qualitative and quantitative data suggested that individual farmers’ actions were influenced by perceptions of risk, affecting both individual and collective disease management. Additionally, the used experimental treatments allowed us to evaluate the influence of communication on risk-governance strategies. It appears that a combination of possession of technical knowledge about the disease, opportunities to communicate about the disease, and a collective disease management strategy enables the best individual actions and collective performance.
Sustainable Behavior among Romanian Students: A Perspective on Electricity Consumption in Households
Authors: Gherheș Vasile , Fărcașiu Marcela Alina
Published: August 2021

The Organization for Economic Co-operation and Development (OECD) estimates that the environmental pressure from households will increase significantly by 2030. Sustainable consumption means making consumers aware of the social and environmental impacts of the goods and services they use. In this respect, special attention must be paid to electricity consumption since its generation affects the environment. The present research aims at capturing electricity consumption behaviors among students, after having applied an online questionnaire between March and April 2021, recording 816 responses. The results of this research highlighted the fact that for seven out of fourteen statements, percentages of over 50% for the “always” and “often” answer variants were recorded, but cases when the highest percentages were for the “rarely” and “never” answer variants (e.g., “You read the hours on the light bulb packs before purchasing them”, “You put your mobile phone in the power saving mode so that you don’t have to charge it so often” and “You unplug the electrical and electronic equipment that you do not use”) were also observed. Decrypting consumer behaviors is a key point for building strategies that will lead to consumers’ awareness of conserving electricity in households and, thus, to a reduction in their environmental impact.
The Women* Who Made It: Experiences from Being a Woman* at a Maker Festival
Authors: Campreguer França Nathalia , Smit Dorothé , Wuschitz Stefanie , Fuchsberger Verena
Published: August 2021

This paper examines the profile of 10 women* makers attending Schmiede, a 10-day maker festival, which is unique not least due to its almost equal gender distribution. Drawing on interviews with women* attendees, we describe general struggles in fitting in the culture of spaces for making, the role of mentorship in childhood and adulthood, motivations and different approaches for engaging in making, limiting factors in (art-)making, and the consequences of sexism for making practice. We then discuss the characteristics of these women* makers in relation to existing literature about the culture in maker spaces and festivals and conclude by highlighting characteristics of the observed festival that may have resulted in more inclusive access for women* and other underrepresented groups.