bluuebunny/crossref_metadata_2025 huggingface dataset:
Bioaccumulation of Trace Metals in Groenlandia densa Plant Reintroduced in Western Pomerania
Authors: Podlasińska Joanna , Wróbel Mariola , Szpikowski Józef , Szpikowska Grażyna
Published: May 2021

The phytoremediation role of aquatic plants in situ is extremely important today when, due to repeated droughts and periodical shrinkage of surface water resources, the load of biogenic and toxic substances in these waters is increasing dramatically. The aim of the study was to assess the bioaccumulation of heavy metals (Cd, Cr, Cu, Hg, Mn and Zn) by the Groenlandia densa reintroduced in the area of its historical occurrence in the habitat of rivers characterized by Ranunculion fluitantis vegetation. Research material was collected from 3 sites in the Natura 2000 area in Western Pomerania on areas differing in anthropogenic load, from sites on streams in agricultural, urbanized and forested catchments. The study showed varying content of trace metals in Groenlandia densa. Plants and sediments collected from the site with the highest anthropogenic load, located in an urbanized catchment, contained more metals. The tolerance of Groenlandia densa to elevated Mn levels in water/sediment was confirmed.
CO2 Emission and Energy Consumption from Automobile Industry in China: Decomposition and Analyses of Driving Forces
Authors: Hu Shaohua , Yang Jie , Jiang Zhigang , Ma Minda , Cai Wei
Published: May 2021

Despite the increasing contribution of the automotive industry to China’s national economy, CO2 emissions have become a challenge. However, the research about its energy consumption and carbon emissions is lacking. The significance of this study is to fill the research gap and provide suggestions for China’s automotive industry to reduce its carbon emissions. In this paper, the extended logarithmic Division index (LMDI) method is adopted to decompose the factors affecting carbon emissions and determine the key driving forces. According to provincial statistical data in China in 2017, the annual emissions of six provinces exceeded five million tons, accounting for 55.44% of the total emissions in China. The largest source of emissions in China is in Jilin Province, followed by Jiangsu, Shandong, Shanghai, Hubei and Henan. The decomposition results show that investment intensity effect is the greatest factor for CO2 emissions, while R&D intensity and energy intensity are the two principal factors for emission reduction. After the identification of driving factors, mitigation measures are proposed considering the current state of affairs and real situation, including improving energy structure, accelerating product structure transformation, stimulating sound R&D investment activities, promoting energy conservation and new energy automobile industry development and boosting industrial cluster development.
Kinetics on Chromium-Bearing Vanadia-Titania Magnetite Smelting with High-Basicity Pellet
Authors: Song Hanlin , Zhang Jinpeng , Xue Xiangxin
Published: May 2021

The effects of high-basicity pellet on smelting chromium-bearing vanadia-titania magnetite are investigated via thermodynamic smelting and non-isothermal kinetics experiments. The thermodynamic results indicated that the high-basicity pellet significantly affects and ameliorates the softening-melting-dripping behaviors during the smelting process. As the high-basicity pellet ratio increased from 0 wt.% to 52 wt.%, the range of softening temperature [T40–T4] decreased from 121 °C to 84 °C and the melting-dripping temperature [Td–Ts] decreased from 224 °C to 169 °C. Moreover, the apparent activation energy of non-isothermal kinetics also decreased from 99.91 kJ·mol−1 to 66.74 kJ·mol−1. Additionally, the reaction mechanism of high-basicity pellet on smelting chromium-bearing vanadia-titania magnetite was investigated via thermodynamic calculations of Gibbs free energy and characterizations of the titanium slag. Therefore, combined with the lowest permeability index, the fastest non-isothermal reduction rate, the highest recovery of valuable elements and the minimum content of titanium carbonitride, the preferable high-basicity pellet ratio was considered to be 11~23 wt.%.
Mechanical Behaviour of Large Strain Capacitive Sensor with Barium Titanate Ecoflex Composite Used to Detect Human Motion
Authors: Cholleti Eshwar Reddy , Stringer Jonathan , Kelly Piaras , Bowen Chris , Aw Kean
Published: May 2021

In this paper, the effect of strain rate on the output signal of highly stretchable interdigitated capacitive (IDC) strain sensors is studied. IDC sensors fabricated with pristine Ecoflex and a composite based on 40 wt% of 200 nm barium titanate (BTO) dispersed in a silicone elastomer (Ecoflex 00-30TM) were subjected to 1000 stretch and relax cycles to study the effect of dynamic loading conditions on the output signal of the IDC sensor. It was observed that the strain rate has no effect on the output signal of IDC sensor. To study the non-linear elastic behaviour of pristine Ecoflex and composites based on 10, 20, 30, 40 wt% of 200 nm BTO filler dispersed in a silicone elastomer, we conducted uniaxial tensile testing to failure at strain rates of ~5, ~50, and ~500 mm/min. An Ogden second-order model was used to fit the uniaxial tensile test data to understand the non-linearity in the stress-strain responses of BTO-Ecoflex composite at different strain rates. The decrease in Ogden parameters (α1 and α2) indicates the decrease in non-linearity of the stress-strain response of the composite with an increase in filler loading. Scanning electronic microscopy analysis was performed on the cryo-fractured pristine Ecoflex and 10, 20, 30, and 40 wt% of BTO-Ecoflex composites, where it was found that 200 nm BTO is more uniformly distributed in Ecoflex at a higher filler loading levels (40 wt% 200 nm BTO). Therefore, an IDC sensor was fabricated based on a 40 wt% 200 nm BTO-Ecoflex composite and mounted on an elastic elbow sleeve with supporting electronics, and successfully functioned as a reliable and robust flexible sensor, demonstrating an application to measure the bending angle of an elbow at slow and fast movement of the arm. A linear relationship with respect to the elbow bending angle was observed between the IDC sensor output signal under a 50% strain and the deflection of the elbow of hand indicating its potential as a stretchable, flexible, and wearable sensor.
Covariation of Passive–Active Microwave Measurements over Vegetated Surfaces: Case Studies at L-Band Passive and L-, C- and X-Band Active
Authors: Albanesi Erica , Bernoldi Silvia , Dell’Acqua Fabio , Entekhabi Dara
Published: May 2021

The analysis of soil and land cover scattering properties and their connection with the parameters of microwave scattering is a longstanding research topic. Recently, the advent of modern space-borne microwave radiometers like SMAP in addition to the trend towards open data for scientific use fostered the development of enhanced models based on data fusion from different platforms permitting more accurate assessments. SMAP was designed to operate on an integrated combination of a radiometer and a radar, both operating in L-band. Unexpected failure of the radar component encouraged scientists to experiment various combination of data from the surviving radiometer with other sources of radar data, notably C-band Sentinel-1 data. In this work, we present a case study on a possible combination of SMAP radiometer data with X-band radar data from TerraSAR-X and COSMO-SkyMed, comparing results with those provided by NASA from their standard production procedures. The study was performed on two test sites, one at an agricultural site in Germany and one in the Brazilian Amazon, to explore very different vegetation conditions. This work is a part of a broader research effort addressing the combination of multiple sources of passive and active microwave sensing data. The research question defining this research effort is whether the use of data from multiple active sources affords either obtaining more accurate estimates of active–passive co-variation parameters for a given observation period, or shortening the minimum observation period by increasing the temporal density of active samples. In this framework, this paper addresses a preliminary comparison of fresh and past results obtained from C-, X-, and L-band active sensing data. The observed relations offer interesting clues on the impact of band selection on soil vegetation analysis.
A Novel Method to Mitigate the Multipath Error for BDS-2 Dam Deformation Monitoring
Authors: Zou Xuan , Li Zhiyuan , Li Yangyang , Wang Yawei , Tang Weiming , Deng Chenlong , Cui Jianhui , Fu Ruinan
Published: May 2021

The multipath effect on carrier-phase observations is related to the observational environment of the station, and cannot be eliminated or attenuated by the differential method. In the actual dam environment of deformation monitoring, multipath is very complicated. It is the main error source of BDS-2 for high precision data processing. In this paper, a new method called the multi-point hemispherical grid model (MHGM) is studied and evaluated. This method uses the hemispheric grid model to attenuate the influence of multipath errors. The effectiveness and improvement of the new method with respect to the popular sidereal filter (SF) method were assessed and verified by the actual dam monitoring data with only the BDS-2. The MHGM and SF approach calculates the multipath corrections from multi-days historical data, and then corrects the multipath error from the observations on the day of interest. Compared with the SF method, the MHGM can also effectively provide a graphical display of multipath error interference around the stations, which matches the surrounding observation environment. The results show that the double-differenced (DD) residuals of the MHGM for GEO/IGSO and MEO satellites are slightly better than those of SF, but the RMS of MHGM for GEO/IGSO+MEO DD residuals is improved by about 17.0%. The performance of the MHGM method for different satellite constellations is consistent and not affected by the different orbital repeat times, which could solve the “zero mean” assumption problem of the SF method. Meanwhile, the RMS of static with a 2 h interval and kinematic positioning errors of the MHGM method in the horizontal and vertical direction can be up to 1.7, 3.6 and 2.4, 8.1 mm, respectively. The MHGM model could avoid the multipath reference problem caused by different orbital repetition periods, making it more suitable for the combined multipath modeling of BDS-2 and BDS-3.
Sentinel-2 Exposed Soil Composite for Soil Organic Carbon Prediction
Authors: Dvorakova Klara , Heiden Uta , van Wesemael Bas
Published: May 2021

Pilot studies have demonstrated the potential of remote sensing for soil organic carbon (SOC) mapping in exposed croplands. However, the use of remote sensing for SOC prediction is often hindered by disturbing factors at the soil surface, such as photosynthetic active and non-photosynthetic active vegetation, variation in soil moisture or surface roughness. With the increasing amount of freely available satellite data, recent studies have focused on stabilizing the soil reflectance by building image composites. These composites tend to minimize the disturbing effects by applying sets of criteria. Here, we aim to develop a robust method that allows selecting Sentinel-2 (S-2) pixels with minimal influence of the following disturbing factors: crop residues, surface roughness and soil moisture. We selected all S-2 cloud-free images covering the Belgian Loam Belt from January 2019 to December 2020 (in total 36 images). We then built nine exposed soil composites based on four sets of criteria: (1) lowest Normalized Burn Ratio (NBR2), (2) Normalized Difference Vegetation Index (NDVI) < 0.25, (3–5) NDVI < 0.25 and NBR2 < threshold, (6) the ‘greening-up’ period of a crop and (7–9) the ‘greening-up’ period of a crop and NBR2 < threshold. The ‘greening-up’ period was selected based on the NDVI timeline, where ‘greening-up’ is considered as the last date of acquisition where the soil is exposed (NDVI < 0.25) before the crop develops (NDVI > 0.25). We then built a partial least square regression (PLSR) model with 10-fold cross-validation to estimate the SOC content based on 137 georeferenced calibration samples on the nine composites. We obtained non-satisfactory results (R2 < 0.30, RMSE > 2.50 g C kg–1, and RPD < 1.4, n > 68) for all composites except for the composite in the ‘greening-up’ stage with a NBR2 < 0.07 (R2 = 0.54 ± 0.12, RPD = 1.68 ± 0.45 and RMSE = 2.09 ± 0.39 g C kg–1, n = 49). Hence, the ‘greening-up’ method combined with a strict NBR2 threshold allows selecting the purest exposed soil pixels suitable for SOC prediction. The limit of this method might be its coverage of the total cropland area, which in a two-year period reached 62%, compared to 95% coverage if only the NDVI threshold is applied.
Inventory and GLOF Susceptibility of Glacial Lakes in Hunza River Basin, Western Karakorum
Authors: Muneeb Fakhra , Baig Siddique Ullah , Khan Junaid Aziz , Khokhar Muhammad Fahim
Published: May 2021

Northern latitudes of Pakistan are warming at faster rate as compared to the rest of the country. It has induced irregular and sudden glacier fluctuations leading to the progression of glacial lakes, and thus enhancing the risk of Glacier Lake Outbursts Floods (GLOF) in the mountain systems of Pakistan. Lack of up-to-date inventory, classification, and susceptibility profiles of glacier lakes and newly formed GLOFs, are few factors which pose huge hindrance towards disaster preparedness and risk reduction strategies in Pakistan. This study aims to bridge the existing gap in data and knowledge by exploiting satellite observations, and efforts are made to compile and update glacier lake inventories. GLOF susceptibility assessment is evaluated by using Analytical Hierarchy Process (AHP), a multicriteria structured technique based on three susceptibility contributing factors: Geographic, topographic, and climatic. A total of 294 glacial lakes are delineated with a total area of 7.85 ± 0.31 km2 for the year 2018. Analysis has identified six glacier lakes as potential GLOF and met the pre-established criteria of damaging GLOFs. The historical background of earlier GLOF events is utilized to validate the anticipated approach and found this method appropriate for first order detection and prioritization of potential GLOFs in Northern Pakistan.
Quantifying Contributions of Local Emissions and Regional Transport to NOX in Beijing Using TROPOMI Constrained WRF-Chem Simulation
Authors: Zhu Yizhi , Hu Qihou , Gao Meng , Zhao Chun , Zhang Chengxin , Liu Ting , Tian Yuan , Yan Liu , Su Wenjing , Hong Xinhua , Liu Cheng
Published: May 2021

Air quality is strongly influenced by both local emissions and regional transport. Atmospheric chemical transport models can distinguish between emissions and regional transport sources in air pollutant concentrations. However, quantifying model inventories is challenging due to emission changes caused by the recent strict control measures taken by the Chinese government. In this study, we use NO2 column observations from the Tropospheric Monitoring Instrument to retrieve top-down nitrogen oxide (NOX) emissions and quantify the contributions of local emissions and regional transport to NOx in Beijing (BJ), from 1 November 2018 to 28 February 2019 (W_2018) and 1 November 2019 to 29 February 2020 (W_2019). In W_2018 and W_2019, the BJ bottom-up NOX emissions from the multi-resolution emission inventory for China in 2017 were overestimated by 11.8% and 40.5%, respectively, and the input of NOX from other cities to BJ was overestimated by 10.9% and 51.6%, respectively. The simulation using our adjusted inventory exhibited a much higher spatial agreement (slope = 1.0, R2 = 0.79) and reduced a mean relative error by 45% compared to those of bottom-up NOX emissions. The top-down inventory indicated that (1) city boundary transport contributes approximately 40% of the NOX concentration in BJ; (2) in W_2019, NOX emissions and transport in BJ decreased by 20.4% and 17.2%, respectively, compared to those of W_2018; (3) in W_2019, NOX influx substantially decreased (−699 g/s) in BJ compared to that of W_2018 despite negative meteorological conditions that should have increased NOx influx by +503 g/s. Overall, the contribution of intercity input to NOx in BJ has declined with decreasing emissions in the surrounding cities due to regional cooperative control measures, and the role of local emissions in BJ NOx levels was more prominent. Our findings indicate that local emissions may play vital roles in regional center city air quality.
Delineation of Urban Agglomeration Boundary Based on Multisource Big Data Fusion—A Case Study of Guangdong–Hong Kong–Macao Greater Bay Area (GBA)
Authors: He Xiong , Yuan Xiaodie , Zhang Dahao , Zhang Rongrong , Li Ming , Zhou Chunshan
Published: May 2021

The accurate delineation of urban agglomeration boundary is conductive to not only the better understanding of the development relationship between cities in urban agglomeration but also to the guidance of regional functions as well as the formulation of regional management policies. At the same time, the fusion of land relations and urban internal relations can greatly improve the accuracy of the delineation of urban agglomeration boundary. Still, for all that, previous studies delineated the boundary only from the perspective of land relations. In this study, firstly, wavelet transform is used to fuse Night-time Light data (NTL), POI (Point of Interest) data and Tencent Migration data, respectively. Then, the image is segmented by multiresolution segmentation to delineate the urban agglomeration boundary of GBA. Finally, the results are verified. The results show that the accuracy of urban agglomeration boundary delineated by NTL data is 85.57%, with the Kappa value as 0.6256, respectively. While, after fusing POI data, the accuracy is 88.97%, with the Kappa value as 0.7011, respectively. What is more, the accuracy of delineating urban agglomeration boundary by continuous fusion of population movement data reaches 93.60%, and that of Kappa value as 0.8155. Therefore, it can be concluded that compared with delineating the boundary of urban agglomeration only based on land relations, the fusion of population movement data of urban agglomerations by wavelet transform strengthens the interconnection between cities in urban agglomeration and contributes to the accurate division of urban agglomeration boundaries. What is more, such accurate delineation not only has important practical value for optimizing the spatial structure of urban agglomerations, but also assists in the formulation of regional management and development planning policies.
Seasonal Precipitation Variability and Non-Stationarity Based on the Evolution Pattern of the Indian Ocean Dipole over the East Asia Region
Authors: Kim Jong-Suk , Yoon Sun-Kwon , Oh Sang-Myeong , Chen Hua
Published: May 2021

Non-linear behavioral links with atmospheric teleconnections were identified between the Indian Ocean Dipole (IOD) mode and seasonal precipitation over East Asia (EA) using statistical models. The analysis showed that the lower the lag time, the higher the correlation; more than a two-fold correlation for non-linear regression with a kernel density estimator than for the linear regression method. When the IOD peaked, a pattern of significant reductions in seasonal precipitation during the negative IOD period occurred throughout the Korean Peninsula (KP). The occurrence of the positive IOD was in line with the El Niño phenomenon and generated greater seasonal precipitation than only the positive IOD, which takes place from March to May. This change occurred more in the cold tongue El Niño than the warm pool El Niño, inducing much higher spring precipitation throughout the KP. When negative IODs and La Niña coincided, there was slightly greater precipitation from March to May compared to the sole occurrence of negative IODs. In positive (negative) IOD years, there was anti-cyclonic (cyclonic) circulation in the South China Sea (SCS), helping to transport moisture to EA. The composite precipitation anomalies in the positive (negative) IOD years show above (below) normal precipitation in southern China. In contrast, other parts of the EA experienced drier (humid) signals than normal years. In positive IOD years, the anti-cyclonic circulation strength of the Bay of Bengal and the SCS continued until autumn and spring of the following year. This shows possible remote connections between climate events related to the tropical Indian Ocean and variations in precipitation over EA.
UAV-Based Remote Sensing Applications for Bridge Condition Assessment
Authors: Feroz Sainab , Abu Dabous Saleh
Published: May 2021

Deterioration of bridge infrastructure is a serious concern to transport and government agencies as it declines serviceability and reliability of bridges and jeopardizes public safety. Maintenance and rehabilitation needs of bridge infrastructure are periodically monitored and assessed, typically every two years. Existing inspection techniques, such as visual inspection, are time-consuming, subjective, and often incomplete. Non-destructive testing (NDT) using Unmanned Aerial Vehicles (UAVs) have been gaining momentum for bridge monitoring in the recent years, particularly due to enhanced accessibility and cost efficiency, deterrence of traffic closure, and improved safety during inspection. The primary objective of this study is to conduct a comprehensive review of the application of UAVs in bridge condition monitoring, used in conjunction with remote sensing technologies. Remote sensing technologies such as visual imagery, infrared thermography, LiDAR, and other sensors, integrated with UAVs for data acquisition are analyzed in depth. This study compiled sixty-five journal and conference papers published in the last two decades scrutinizing NDT-based UAV systems. In addition to comparison of stand-alone and integrated NDT-UAV methods, the facilitation of bridge inspection using UAVs is thoroughly discussed in the present article in terms of ease of use, accuracy, cost-efficiency, employed data collection tools, and simulation platforms. Additionally, challenges and future perspectives of the reviewed UAV-NDT technologies are highlighted.
Non-Contact Monitoring and Classification of Breathing Pattern for the Supervision of People Infected by COVID-19
Authors: Purnomo Ariana Tulus , Lin Ding-Bing , Adiprabowo Tjahjo , Hendria Willy Fitra
Published: May 2021

During the pandemic of coronavirus disease-2019 (COVID-19), medical practitioners need non-contact devices to reduce the risk of spreading the virus. People with COVID-19 usually experience fever and have difficulty breathing. Unsupervised care to patients with respiratory problems will be the main reason for the rising death rate. Periodic linearly increasing frequency chirp, known as frequency-modulated continuous wave (FMCW), is one of the radar technologies with a low-power operation and high-resolution detection which can detect any tiny movement. In this study, we use FMCW to develop a non-contact medical device that monitors and classifies the breathing pattern in real time. Patients with a breathing disorder have an unusual breathing characteristic that cannot be represented using the breathing rate. Thus, we created an Xtreme Gradient Boosting (XGBoost) classification model and adopted Mel-frequency cepstral coefficient (MFCC) feature extraction to classify the breathing pattern behavior. XGBoost is an ensemble machine-learning technique with a fast execution time and good scalability for predictions. In this study, MFCC feature extraction assists machine learning in extracting the features of the breathing signal. Based on the results, the system obtained an acceptable accuracy. Thus, our proposed system could potentially be used to detect and monitor the presence of respiratory problems in patients with COVID-19, asthma, etc.
Miniature Optical Particle Counter and Analyzer Involving a Fluidic-Optronic CMOS Chip Coupled with a Millimeter-Sized Glass Optical System
Authors: Jobert Gabriel , Barritault Pierre , Fournier Maryse , Monpeurt Cyrielle , Boutami Salim , Jamois Cécile , Bernasconi Pietro , Lovera Andrea , Braga Daniele , Seassal Christian
Published: May 2021

Our latest advances in the field of miniaturized optical PM sensors are presented. This sensor combines a hybrid fluidic-optronic CMOS (holed retina) that is able to record a specific irradiance pattern scattered by an illuminated particle (scattering signature), while enabling the circulation of particles toward the sensing area. The holed retina is optically coupled with a monolithic, millimeter-sized, refracto-reflective optical system. The latter notably performs an optical pre-processing of signatures, with a very wide field of view of scattering angles. This improves the sensitivity of the sensors, and simplifies image processing. We report the precise design methodology for such a sensor, as well as its fabrication and characterization using calibrated polystyrene beads. Finally, we discuss its ability to characterize particles and its potential for further miniaturization and integration.
Frequency Response of Pressure-Sensitive Paints under Low-Pressure Conditions
Authors: Kasai Miku , Sasaki Daisuke , Nagata Takayuki , Nonomura Taku , Asai Keisuke
Published: May 2021

The characteristics of fast-response pressure-sensitive paints (PSPs) in low-pressure conditions were evaluated. Three representative porous binders were investigated: polymer-ceramic PSP (PC-PSP), anodized-aluminum PSP (AA-PSP), and thin-layer chromatography PSP (TLC-PSP). For each PSP, two types of luminophores, Pt(II) meso-tetra (pentafluorophenyl) porphine (PtTFPP) and tris(bathophenanthroline) ruthenium dichloride (Ru(dpp)3), were used as sensor molecules. Pressure sensitivities, temperature sensitivities, and photodegradation rates were measured and evaluated using a pressure chamber. The effect of ambient pressure on the frequency response was investigated using an acoustic resonance tube. The diffusivity coefficients of PSPs were estimated from the measured frequency response and luminescent lifetime, and the governing factor of the frequency response under low-pressure conditions was identified. The results of static calibration show that PC-PSP/PtTFPP, AA-PSP/Ru(dpp)3, and TLC-PSP/PtTFPP have high pressure sensitivities that exceed 4%/kPa under low-pressure conditions and that temperature sensitivity and photodegradation rates become lower as the ambient pressure decreases. Dynamic calibration results show that the dynamic characteristics of PSPs with PtTFPP are dependent on the ambient pressure, whereas those of PSPs with Ru(dpp)3 are not influenced by the ambient pressure. This observation indicates that the governing factor in the frequency response under low-pressure conditions is the lifetime for PC-PSP and TLC-PSP, whereas the governing factor for AA-PSP is diffusion.
From a Low-Cost Air Quality Sensor Network to Decision Support Services: Steps towards Data Calibration and Service Development
Authors: Veiga Tiago , Munch-Ellingsen Arne , Papastergiopoulos Christoforos , Tzovaras Dimitrios , Kalamaras Ilias , Bach Kerstin , Votis Konstantinos , Akselsen Sigmund
Published: May 2021

Air pollution is a widespread problem due to its impact on both humans and the environment. Providing decision makers with artificial intelligence based solutions requires to monitor the ambient air quality accurately and in a timely manner, as AI models highly depend on the underlying data used to justify the predictions. Unfortunately, in urban contexts, the hyper-locality of air quality, varying from street to street, makes it difficult to monitor using high-end sensors, as the cost of the amount of sensors needed for such local measurements is too high. In addition, development of pollution dispersion models is challenging. The deployment of a low-cost sensor network allows a more dense cover of a region but at the cost of noisier sensing. This paper describes the development and deployment of a low-cost sensor network, discussing its challenges and applications, and is highly motivated by talks with the local municipality and the exploration of new technologies to improve air quality related services. However, before using data from these sources, calibration procedures are needed to ensure that the quality of the data is at a good level. We describe our steps towards developing calibration models and how they benefit the applications identified as important in the talks with the municipality.
Biosensing Applications Using Nanostructure-Based Localized Surface Plasmon Resonance Sensors
Authors: Kim Dong Min , Park Jong Seong , Jung Seung-Woon , Yeom Jinho , Yoo Seung Min
Published: May 2021

Localized surface plasmon resonance (LSPR)-based biosensors have recently garnered increasing attention due to their potential to allow label-free, portable, low-cost, and real-time monitoring of diverse analytes. Recent developments in this technology have focused on biochemical markers in clinical and environmental settings coupled with advances in nanostructure technology. Therefore, this review focuses on the recent advances in LSPR-based biosensor technology for the detection of diverse chemicals and biomolecules. Moreover, we also provide recent examples of sensing strategies based on diverse nanostructure platforms, in addition to their advantages and limitations. Finally, this review discusses potential strategies for the development of biosensors with enhanced sensing performance.
Low-Power Wireless Sensor Network Using Fine-Grain Control of Sensor Module Power Mode
Authors: You Seongwon , Eshraghian Jason K. , Iu Herbert C. , Cho Kyoungrok
Published: May 2021

Wireless sensor nodes are heavily resource-constrained due to their edge form factor, which has motivated increasing battery life through low-power techniques. This paper proposes a power management method that leads to less energy consumption in an idle state than conventional power management systems used in wireless sensor nodes. We analyze and benchmark the power consumption between Sleep, Idle, and Run modes. To reduce sensor node power consumption, we develop fine-grained power modes (FGPM) with five states which modulate energy consumption according to the sensor node’s communication status. We evaluate the proposed method on a test bench Mica2. As a result, the power consumed is 74.2% lower than that of conventional approaches. The proposed method targets the reduction of power consumption in IoT sensor modules with long sleep mode or short packet data in which most networks operate.
Cooperative Fusion Based Passive Multistatic Radar Detection
Authors: Asif Asma , Kandeepan Sithamparanathan
Published: May 2021

Passive multistatic radars have gained a lot of interest in recent years as they offer many benefits contrary to conventional radars. Here in this research, our aim is detection of target in a passive multistatic radar system. The system contains a single transmitter and multiple spatially distributed receivers comprised of both the surveillance and reference antennas. The system consists of two main parts: 1. Local receiver, and 2. Fusion center. Each local receiver detects the signal, processes it, and passes the information to the fusion center for final detection. To take the advantage of spatial diversity, we apply major fusion techniques consisting of hard fusion and soft fusion for the case of multistatic passive radars. Hard fusion techniques are analyzed for the case of different local radar detectors. In terms of soft fusion, a blind technique called equal gain soft fusion technique with random matrix theory-based local detector is analytically and theoretically analyzed under null hypothesis along with the calculation of detection threshold. Furthermore, six novel random matrix theory-based soft fusion techniques are proposed. All the techniques are blind in nature and hence do not require any knowledge of transmitted signal or channel information. Simulation results illustrate that proposed fusion techniques increase detection performance to a reasonable extent compared to other blind fusion techniques.
Detection of Postural Control in Young and Elderly Adults Using Deep and Machine Learning Methods with Joint–Node Plots
Authors: Lee Posen , Chen Tai-Been , Wang Chi-Yuan , Hsu Shih-Yen , Liu Chin-Hsuan
Published: May 2021

Postural control decreases with aging. Thus, an efficient and accurate method of detecting postural control is needed. We enrolled 35 elderly adults (aged 82.06 ± 8.74 years) and 20 healthy young adults (aged 21.60 ± 0.60 years) who performed standing tasks for 40 s, performed six times. The coordinates of 15 joint nodes were captured using a Kinect device (30 Hz). We plotted joint positions into a single 2D figure (named a joint–node plot, JNP) once per second for up to 40 s. A total of 15 methods combining deep and machine learning for postural control classification were investigated. The accuracy, sensitivity, specificity, positive predicted value (PPV), negative predicted value (NPV), and kappa values of the selected methods were assessed. The highest PPV, NPV, accuracy, sensitivity, specificity, and kappa values were higher than 0.9 in validation testing. The presented method using JNPs demonstrated strong performance in detecting the postural control ability of young and elderly adults.
Enhancement of Speed and Accuracy Trade-Off for Sports Ball Detection in Videos—Finding Fast Moving, Small Objects in Real Time
Authors: Hiemann Alexander , Kautz Thomas , Zottmann Tino , Hlawitschka Mario
Published: May 2021

The detection and localization of the ball in sport videos is crucial to better understand events and actions occurring in those sports. Despite recent advances in the field of object detection, the automatic detection of balls remains a challenging task due to the unsteady nature of balls in images. In this paper, we address the detection of small, fast-moving balls in sport video data and introduce a real-time ball detection approach based on the YOLOv3 object detection model. We apply specific adjustments to the network architecture and training process in order to enhance the detection accuracy and speed: We facilitate an efficient integration of motion information, avoiding a complex modification of the network architecture. Furthermore, we present a customized detection approach that is designed to primarily focus on the detection of small objects. We integrate domain-specific knowledge to adapt image pre-processing and a data augmentation strategy that takes advantage of the special features of balls in images in order to improve the generalization ability of the detection network. We demonstrate that the general trade-off between detection speed and accuracy of the YOLOv3 model can be enhanced in consideration of domain-specific prior knowledge.
Are Mothers and Daughters Most Important? How Gender, Childhood Family Dissolution and Parents’ Current Living Arrangements Affect the Personal Care of Parents
Authors: Kridahl Linda , Duvander Ann-Zofie
Published: May 2021

This study examines adult children’s propensity to provide personal care to older mothers and fathers. The theory of intergenerational solidarity facilitates the understanding of commitment and support between adult children and parents. Solidarity may depend on childhood events as well as the current situation, and we therefore focus on whether there was a parental breakup in childhood and the parent’s current living arrangements. We also focus on the gendered aspects of the relations as earlier research has found stronger matrilinear relationships. The propensity for personal care was analyzed with regression analysis using the 2012 Swedish Generations and Gender Survey. The results show that daughters are more likely than sons to provide personal care to both parents. Parental breakup in childhood does not change the propensity of personal care to any parent. The probability of receiving care is higher for lone mothers than for mothers living with the father, but not for repartnered mothers. Adult children’s care provision does not differ for lone fathers and fathers living with the mother, but children are more likely to provide care to lone fathers than to repartnered fathers. We interpret this to indicate that repartnering weakens ties to fathers but not mothers. The results indicate that the child’s gender and the parent’s living arrangements operate differently with regard to care for mothers and fathers. The most common pattern is care provided from daughters to mothers. For example, daughters of lone mothers are more likely to provide care than sons in the same situation. We conclude that intergenerational solidarity is not affected by parental breakup in childhood but that present living arrangements affect such solidarity in gendered ways.
Reviewing the Impact of Vehicular Pollution on Road-Side Plants—Future Perspectives
Authors: Muthu Manikandan , Gopal Judy , Kim Doo-Hwan , Sivanesan Iyyakkannu
Published: May 2021

With population explosion, automobiles have also exploded and so has pollution due to vehicular emissions. Road-side plants and highway vegetation are the first targets of these vehicular emissions. This review briefly presents a snapshot of how vehicular emission can affect plants. On the contrary, the positive perspective of how road-side plants may be able to affect and influence the harmful effects of vehicular emissions has also been discussed. Ways and means by which plants can become potential bio indicators of air pollution have also been speculated. The fact that the nanocarbon particulate aspect of automobile pollutants and their interactions with road-side plants and more so on road-side agricultural crops, has not been appropriately investigated has been raised as a key concern. The need to arrive at mitigation methods to identify permanent solutions to these rising concerns has been highlighted.
Evaluation of Coal Fly Ash for Modulating the Plant Growth, Yield, and Antioxidant Properties of Daucus carota (L.): A Sustainable Approach to Coal Waste Recycling
Authors: Shakeel Adnan , Khan Abrar Ahmad , Alharby Hesham F. , Bamagoos Atif A. , Tombuloglu Huseyin , Hakeem Khalid Rehman
Published: May 2021

In search of a safe, cost-effective, and sustainable method for the disposal and management of coal fly ash (CFA), seeds of carrot were sown in earthen pots containing growth substrate consisting of field soil amended with different concentrations of weathered CFA at w/w % ratios. Results suggested that CFA added many essential plant nutrients to the growth substrate and improved some important soil characteristics such as pH, electric conductivity, porosity, and water holding capacity. The growth substrate containing 15% of CFA proved most suitable for growing carrots. Plants grown in 15% CFA amended soil had significantly (p ≤ 0.05) enhanced plant growth, yield, photosynthetic pigments, nitrate reductase activity, protein, and carbohydrate contents as compared to the control. The activity of antioxidant enzymes such as SOD and CAT was significantly upregulated in 15% CFA amended soil as compared to the control. The biomineralization of various elements in the edible part of the carrot was well under the limits and no toxic metal was detected in the edible part of the carrot. The present study, therefore, attempts to delineate the application of weathered CFA as a soil amendment in agroecosystems to improve the productivity of lands through a cost-effective and an ecofriendly manner.
Difference in the Attitude of Students and Employees of the University of Ljubljana towards Work from Home and Online Education: Lessons from COVID-19 Pandemic
Authors: Drašler Varineja , Bertoncelj Jasna , Korošec Mojca , Pajk Žontar Tanja , Poklar Ulrih Nataša , Cigić Blaž
Published: May 2021

The COVID-19 pandemic caused a large and involuntary shift to work from home (WFH) or teleworking, and widespread adoption of web-based platforms. This study aims to uncover the attitude and perception of WFH and online education among students and employees of the University of Ljubljana. A web-based questionnaire survey was conducted in November 2020, and more than 1300 valid responses were received. The lack of daily commuting, improved eating habits, and more time available for a family were the main reported advantages of WFH. The main issues, highlighted by respondents, were higher stress levels, lower study/work efficiency, and poorer working environment at home. When comparing the online educational process with the traditional one, the absence of traditional laboratory work, inadequate social interactions, and limitations of online knowledge assessment were identified as drawbacks by both students and educators. A significant difference between students and educators was observed in their opinion on the efficiency of online lectures compared to traditional ones, with the former being significantly more favored by students than educators. Overall, the majority of the respondents from all groups wish for the pre-COVID-19 study/work mode to be established as soon as possible. This implies that the perceived drawbacks of online education outweigh its advantages.
Does Income Inequality Exist among Urban Farmers? A Demonstration of Lorenz Curves from Northern Thailand
Authors: Jaitiang Daranrat , Huang Wen-Chi , Yang Shang-Ho
Published: May 2021

This study was motivated by the profound disparity of farmers’ income in northern Thailand. We aimed to investigate the inequalities in the distribution of estimated income among urban farmers in the Mueang district area of Nan province using the Lorenz curves and Gini indices. Approximations of farmers’ incomes were calculated and the Tobit model was applied to identify the determinants of farm income diversification in each sub-district. Results showed that urban farmers had high inequality scores, and there was a wide range of income among farmers. Ownership, land entitlement, and farmland size positively contributed to farmers’ estimated income. Agricultural activities further showed that rice farming significantly raised income disparity, while maize cultivation negatively affected it in nearly all sub-districts. Therefore, this study contributes an important indication that leads farmers to a sustainable livelihood while simultaneously adjusting relevant institutional policies.
Understanding Pro-Environmental Behavior of Citizen Science: An Exploratory Study of the Bird Survey in Taoyuan’s Farm Ponds Project
Authors: Chao Shan-Hui , Jiang Jin-Zhang , Wei Kuan-Chu , Ng Eric , Hsu Chia-Hsuan , Chiang Yi-Te , Fang Wei-Ta
Published: May 2021

This exploratory study aims to fill the gap by adopting Hirose’s two-phase decision-making model with the theory of social networks to explore the environmentally friendly attitudes and environmental behavioral intentions toward pro-environmental behaviors of the citizen scientists who participated in the Bird Survey in Taoyuan’s Farm Ponds Project. The Bird Survey in Taoyuan’s Farm Ponds Project is a systematic citizen science project founded in 2003 with the aim to identify existing and potential irrigation ponds that are important to creating waterbird refuges to secure habitats for wintering waterbirds in anthropogenically influenced areas. The participation in this project itself can be considered as a form of pro-environmental behavior. A total of 24 in-depth semi-structured interviews were conducted with participants of the Bird Survey in Taoyuan’s Farm Ponds Project. Qualitative data showed that participants mentioned six variables (i.e., perceived seriousness, ascription of responsibility, belief in the effectiveness, feasibility evaluation, cost–benefit evaluation, and social norms evaluation) of the two-phase decision-making model in relation to environmentally friendly attitudes and environmental behavioral intention. Findings also revealed three key variables (i.e., social networks, learning and growth, and belonging and contribution) in the theory of social networks that are associated with environmentally friendly attitudes and environmental behavioral intention. Based on the findings, it is proposed that the social needs variables are incorporated as an extension to the two-phase decision-making model to offer a more comprehensive explanation of pro-environmental behavior.
Consumers’ and Farmers’ Perceptions in Europe Regarding the Use of Composted Bedding Material from Cattle
Authors: Klopčič Marija , Erjavec Karmen , Waldrop Megan , Roosen Jutta , Engel Petra , Galama Paul , Kuipers Abele
Published: May 2021

By-products like sawdust and straw are applied in compost bedded-pack barns (CBP) for cattle. These materials, which are gradually mixed with excreta and undergo a composting process, serve as a lying bed for the cattle. This study aims to assess the perception of consumers and farmers regarding the use of CBP during the grazing season of cattle for raising other animals or for growing food crops. This was examined by combining surveys with consumers from eight European countries and cattle farmers, focus groups with consumers, and in-depth interviews with individual farmers who implemented alternative uses of compost. The results showed that farmers preferred the compost bedded-pack system to the cubicle system in terms of sustainability and market aspects, although the cost of the bedding material required for CBP was seen as a significant negative aspect. Around half of all consumers indicated that the compost can be used for non-edible products and 26% indicated the compost can be used for raising other animals. Furthermore, 5% of consumers felt that compost should not be used for any other purpose. There were statistically significant differences between countries; therefore, regional specificities should be taken into account when marketing products from compost in CBP barns.
Effect of Acetic Acid on Compressive Strength and Geometric Texture of the Surface of C20/25 Class Concrete
Authors: Witkowska-Dobrev Joanna , Szlachetka Olga , Dohojda Marek , Wiśniewski Krzysztof
Published: May 2021

Concrete is a highly alkaline material; therefore, the presence of organic acids (acetic, butyric, lactic) from agricultural sewage constitutes a threat to the concrete and the environment. The investigations were aimed at simulating the influence of highly concentrated organic acids on concrete elements of livestock buildings. Cubic samples 100 × 100 × 100 mm of the ordinary concrete were immersed in 10% acetic acid for 270 days. Then, the compressive strength and mass decrement of the samples were determined as well as using SEM images and a 3D-profilograph to profile the surface roughness and depth of changes evoked in the structure of the samples by penetrating acid. The results were compared with those for a control sample (not subjected to the effects of aggressive agents) as well as for samples placed in a neutral and alkaline environment. The compressive strength of the samples stored in the acidic environment was 22.23% lower than that of the control sample, whereas the compressive strength of those samples stored in an alkaline environment were 44.27% higher. Conclusions from these investigations can be of innovative importance in the preparation of environmental impact reports, which are necessary for obtaining permission for the construction and use of livestock buildings, and afterward in the reduction of the impact of these buildings on the environment and surface and underground water resources.