bluuebunny/crossref_metadata_2025 huggingface dataset:
Impedimetric Determination of Kanamycin in Milk with Aptasensor Based on Carbon Black-Oligolactide Composite
Authors: Kulikova Tatiana , Gorbatchuk Vladimir , Stoikov Ivan , Rogov Alexey , Evtugyn Gennady , Hianik Tibor
Published: August 2020

The determination of antibiotics in food is important due to their negative effect on human health related to antimicrobial resistance problem, renal toxicity, and allergic effects. We propose an impedimetric aptasensor for the determination of kanamycin A (KANA), which was assembled on the glassy carbon electrode by the deposition of carbon black in a chitosan matrix followed by carbodiimide binding of aminated aptamer mixed with oligolactide derivative of thiacalix[4]arene in a cone configuration. The assembling was monitored by cyclic voltammetry, electrochemical impedance spectroscopy, and scanning electron microscopy. In the presence of the KANA, the charge transfer resistance of the inner interface surprisingly decreased with the analyte concentration within 0.7 and 50 nM (limit of detection 0.3 nM). This was attributed to the partial shielding of the negative charge of the aptamer and of its support, a highly porous 3D structure of the surface layer caused by a macrocyclic core of the carrier. The use of electrostatic assembling in the presence of cationic polyelectrolyte decreased tenfold the detectable concentration of KANA. The aptasensor was successfully tested in the determination of KANA in spiked milk and yogurt with recoveries within 95% and 115%.
Three-Dimensional Chipless RFID Tags: Fabrication through Additive Manufacturing
Authors: Terranova Sergio , Costa Filippo , Manara Giuliano , Genovesi Simone
Published: August 2020

A new class of Radio Frequency IDentification (RFID) tags, namely the three-dimensional (3D)-printed chipless RFID one, is proposed, and their performance is assessed. These tags can be realized by low-cost materials, inexpensive manufacturing processes and can be mounted on metallic surfaces. The tag consists of a solid dielectric cylinder, which externally appears as homogeneous. However, the information is hidden in the inner structure of the object, where voids are created to encrypt information in the object. The proposed chipless tag represents a promising solution for anti-counterfeiting or security applications, since it avoids an unwanted eavesdropping during the reading process or information retrieval from a visual inspection that may affect other chipless systems. The adopted data-encoding algorithm does not rely on On–Off or amplitude schemes that are commonly adopted in the chipless RFID implementations but it is based on the maximization of available states or the maximization of non-overlapping regions of uncertainty. The performance of such class of chipless RFID tags are finally assessed by measurements on real prototypes.
Prediction of Sweet Corn Seed Germination Based on Hyperspectral Image Technology and Multivariate Data Regression
Authors: Cui Huawei , Cheng Zhishang , Li Peng , Miao Aimin
Published: August 2020

Vigor identification in sweet corn seeds is important for seed germination, crop yield, and quality. In this study, hyperspectral image (HSI) technology integrated with germination tests was applied for feature association analysis and germination performance prediction of sweet corn seeds. In this study, 89 sweet corn seeds (73 for training and the other 16 for testing) were studied and hyperspectral imaging at the spectral range of 400–1000 nm was applied as a nondestructive and accurate technique to identify seed vigor. The root length and seedling length which represent the seed vigor were measured, and principal component regression (PCR), partial least squares (PLS), and kernel principal component regression (KPCR) were used to establish the regression relationship between the hyperspectral feature of seeds and the germination results. Specifically, the relevant characteristic band associated with seed vigor based on the highest correlation coefficient (HCC) was constructed for optimal wavelength selection. The hyperspectral data features were selected by genetic algorithm (GA), successive projections algorithm (SPA), and HCC. The results indicated that the hyperspectral data features obtained based on the HCC method have better prediction results on the seedling length and root length than SPA and GA. By comparing the regression results of KPCR, PCR, and PLS, it can be concluded that the hyperspectral method can predict the root length with a correlation coefficient of 0.7805. The prediction results of different feature selection and regression algorithms for the seedling length were up to 0.6074. The results indicated that, based on hyperspectral technology, the prediction of seedling root length was better than that of seed length.
Fully Automated Lab-On-A-Disc Platform for Loop-Mediated Isothermal Amplification Using Micro-Carbon-Activated Cell Lysis
Authors: Seo Moo-Jung , Yoo Jae-Chern
Published: August 2020

Fast and fully automated deoxyribonucleic acid (DNA) amplification methods are of interest in the research on lab-on-a-disc (LOD) platforms because of their full compatibility with the spin-column mechanism using centrifugal force. However, the standard procedures followed in DNA amplification require accurate noncontact temperature control as well as cell lysis at a low temperature to prevent damage to the LOD platform. This requirement makes it challenging to achieve full automation of DNA amplification on an LOD. In this paper, a fully automated LOD capable of performing cell lysis and amplification on a single compact disc of DNA samples is proposed. The proposed system uses micro-carbon to heat DNA samples without damaging the LOD as well as a noncontact heating system and an infrared camera sensor to remotely measure the real temperature of the amplification chamber. Compared with conventional DNA amplification systems, the proposed system has the advantage of full automation of the LOD platform. Experimental results demonstrated that the proposed system offers a stable heating method for DNA amplification and cell lysis.
The CSP-Based New Features Plus Non-Convex Log Sparse Feature Selection for Motor Imagery EEG Classification
Authors: Zhang Shaorong , Zhu Zhibin , Zhang Benxin , Feng Bao , Yu Tianyou , Li Zhi
Published: August 2020

The common spatial pattern (CSP) is a very effective feature extraction method in motor imagery based brain computer interface (BCI), but its performance depends on the selection of the optimal frequency band. Although a lot of research works have been proposed to improve CSP, most of these works have the problems of large computation costs and long feature extraction time. To this end, three new feature extraction methods based on CSP and a new feature selection method based on non-convex log regularization are proposed in this paper. Firstly, EEG signals are spatially filtered by CSP, and then three new feature extraction methods are proposed. We called them CSP-wavelet, CSP-WPD and CSP-FB, respectively. For CSP-Wavelet and CSP-WPD, the discrete wavelet transform (DWT) or wavelet packet decomposition (WPD) is used to decompose the spatially filtered signals, and then the energy and standard deviation of the wavelet coefficients are extracted as features. For CSP-FB, the spatially filtered signals are filtered into multiple bands by a filter bank (FB), and then the logarithm of variances of each band are extracted as features. Secondly, a sparse optimization method regularized with a non-convex log function is proposed for the feature selection, which we called LOG, and an optimization algorithm for LOG is given. Finally, ensemble learning is used for secondary feature selection and classification model construction. Combing feature extraction and feature selection methods, a total of three new EEG decoding methods are obtained, namely CSP-Wavelet+LOG, CSP-WPD+LOG, and CSP-FB+LOG. Four public motor imagery datasets are used to verify the performance of the proposed methods. Compared to existing methods, the proposed methods achieved the highest average classification accuracy of 88.86, 83.40, 81.53, and 80.83 in datasets 1–4, respectively. The feature extraction time of CSP-FB is the shortest. The experimental results show that the proposed methods can effectively improve the classification accuracy and reduce the feature extraction time. With comprehensive consideration of classification accuracy and feature extraction time, CSP-FB+LOG has the best performance and can be used for the real-time BCI system.
NH3 Sensor Based on 3D Hierarchical Flower-Shaped n-ZnO/p-NiO Heterostructures Yields Outstanding Sensing Capabilities at ppb Level
Authors: Zhao Zhenting , Yang Haoyue , Wei Zihan , Xue Yan , Sun Yongjiao , Zhang Wenlei , Li Pengwei , Gong Weiping , Zhuiykov Serge , Hu Jie
Published: August 2020

Hierarchical three-dimensional (3D) flower-like n-ZnO/p-NiO heterostructures with various ZnxNiy molar ratios (Zn5Ni1, Zn2Ni1, Zn1Ni1, Zn1Ni2 and Zn1Ni5) were synthesized by a facile hydrothermal method. Their crystal phase, surface morphology, elemental composition and chemical state were comprehensively investigated by XRD, SEM, EDS, TEM and XPS techniques. Gas sensing measurements were conducted on all the as-developed ZnxNiy-based sensors toward ammonia (NH3) detection under various working temperatures from 160 to 340 °C. In particular, the as-prepared Zn1Ni2 sensor exhibited superior NH3 sensing performance under optimum working temperature (280 °C) including high response (25 toward 100 ppm), fast response/recovery time (16 s/7 s), low detection limit (50 ppb), good selectivity and long-term stability. The enhanced NH3 sensing capabilities of Zn1Ni2 sensor could be attributed to both the specific hierarchical structure which facilitates the adsorption of NH3 molecules and produces much more contact sites, and the improved gas response characteristics of p-n heterojunctions. The obtained results clear demonstrated that the optimum n-ZnO/p-NiO heterostructure is indeed very promising sensing material toward NH3 detection for different applications.
WiGAN: A WiFi Based Gesture Recognition System with GANs
Authors: Jiang Dehao , Li Mingqi , Xu Chunling
Published: August 2020

In recent years, a series of research experiments have been conducted on WiFi-based gesture recognition. However, current recognition systems are still facing the challenge of small samples and environmental dependence. To deal with the problem of performance degradation caused by these factors, we propose a WiFi-based gesture recognition system, WiGAN, which uses Generative Adversarial Network (GAN) to extract and generate gesture features. With GAN, WiGAN expands the data capacity to reduce time cost and increase sample diversity. The proposed system extracts and fuses multiple convolutional layer feature maps as gesture features before gesture recognition. After fusing features, Support Vector Machine (SVM) is exploited for human activity classification because of its accuracy and convenience. The key insight of WiGAN is to generate samples and merge multi-grained feature maps in our designed GAN, which not only enhances the data but also allows the neural network to select different grained features for gesture recognition. According to the result of experiments conducted on two existing datasets, the average recognition accuracy of WiGAN reaches 98% and 95.6%, respectively, outperforming the existing system. Moreover, the recognition accuracy under different experimental environments and different users shows the robustness of WiGAN.
Deep Learning-Based Real-Time Multiple-Person Action Recognition System
Authors: Tsai Jen-Kai , Hsu Chen-Chien , Wang Wei-Yen , Huang Shao-Kang
Published: August 2020

Action recognition has gained great attention in automatic video analysis, greatly reducing the cost of human resources for smart surveillance. Most methods, however, focus on the detection of only one action event for a single person in a well-segmented video, rather than the recognition of multiple actions performed by more than one person at the same time for an untrimmed video. In this paper, we propose a deep learning-based multiple-person action recognition system for use in various real-time smart surveillance applications. By capturing a video stream of the scene, the proposed system can detect and track multiple people appearing in the scene and subsequently recognize their actions. Thanks to high resolution of the video frames, we establish a zoom-in function to obtain more satisfactory action recognition results when people in the scene become too far from the camera. To further improve the accuracy, recognition results from inflated 3D ConvNet (I3D) with multiple sliding windows are processed by a nonmaximum suppression (NMS) approach to obtain a more robust decision. Experimental results show that the proposed method can perform multiple-person action recognition in real time suitable for applications such as long-term care environments.
Smart Wireless Acoustic Sensor Network Design for Noise Monitoring in Smart Cities
Authors: Alsina-Pagès Rosa Ma , Bellucci Patrizia , Zambon Giovanni
Published: August 2020

This Special Issue is focused on all the technologies necessary for the development of an efficient wireless acoustic sensor network, from the first stages of its design to the tests conducted during deployment; its final performance; and possible subsequent implications for authorities in terms of the definition of policies. This Special Issue collects the contributions of several LIFE and H2020 projects aimed at the design and implementation of intelligent acoustic sensor networks, with a focus on the publication of good practices for the design and deployment of intelligent networks in any locations.
An Improved Partial Discharge Detection System Based on UV Pulses Detection
Authors: Shen Zeliang , Wang Jingang , Wei Gang
Published: August 2020

Partial discharge (PD) usually reflects failures and potential hazards of equipment, so PD detection is important to protect the power system. The most reliable method now is the pulse current method (PCM), but the device of PCM is large and hard to carry. Ultraviolet (UV) pulse detection is another method to detect PD, which has a high precision, strong anti-interference ability, and a long effective distance. However, the existing detection system does not work well when the PD is weak and can hardly reflect the hidden trouble of equipment. This paper introduces an improved PD detection system, based on the UV Pulse Method, which is of high precision and can reflect early discharge. In this study, a corresponding detection device was also built. This device is handheld, non-contact, easy to use, and of high precision.
A Red Emissive Fluorescent Turn-on Sensor for the Rapid Detection of Selenocysteine and Its Application in Living Cells Imaging
Authors: Wang Zongcheng , Zheng Huihuang , Zhang Chengliang , Tang Dongfang , Wu Qiyao , Dessie Wubliker , Jiang Yuren
Published: August 2020

The content of selenocysteine in cells has an important effect on a variety of human diseases, and the detection of selenocysteine by fluorescent sensors in vivo has shown many advantages. In order to further develop fast-reaction-time, good-selectivity, and high-sensitivity long-wavelength selenocysteine fluorescent sensors, we designed and synthesized the compound YZ-A4 as a turn-on fluorescent sensor to detect the content of selenocysteine. The quantitative detection range of the sensor YZ-A4 to selenocysteine was from 0 to 32 μM, and the detection limit was as low as 11.2 nM. The sensor displayed a rapid turn-on response, good selectivity, and high sensitivity to selenocysteine. Finally, we have demonstrated that YZ-A4 could be used for fluorescence imaging of selenocysteine in living cells.
Scan-Chain-Fault Diagnosis Using Regressions in Cryptographic Chips for Wireless Sensor Networks
Authors: Lim Hyunyul , Cheong Minho , Kang Sungho
Published: August 2020

Scan structures, which are widely used in cryptographic circuits for wireless sensor networks applications, are essential for testing very-large-scale integration (VLSI) circuits. Faults in cryptographic circuits can be effectively screened out by improving testability and test coverage using a scan structure. Additionally, scan testing contributes to yield improvement by identifying fault locations. However, faults in circuits cannot be tested when a fault occurs in the scan structure. Moreover, various defects occurring early in the manufacturing process are expressed as faults of scan chains. Therefore, scan-chain diagnosis is crucial. However, it is difficult to obtain a sufficiently high diagnosis resolution and accuracy through the conventional scan-chain diagnosis. Therefore, this article proposes a novel scan-chain diagnosis method using regression and fan-in and fan-out filters that require shorter training and diagnosis times than existing scan-chain diagnoses do. The fan-in and fan-out filters, generated using a circuit logic structure, can highlight important features and remove unnecessary features from raw failure vectors, thereby converting the raw failure vectors to fan-in and fan-out vectors without compromising the diagnosis accuracy. Experimental results confirm that the proposed scan-chain-diagnosis method can efficiently provide higher resolutions and accuracies with shorter training and diagnosis times.
An Ultra-Sensitive Modular Hybrid EMG–FMG Sensor with Floating Electrodes
Authors: Ke Ang , Huang Jian , Chen Luyao , Gao Zhaolong , He Jiping
Published: August 2020

To improve the reliability and safety of myoelectric prosthetic control, many researchers tend to use multi-modal signals. The combination of electromyography (EMG) and forcemyography (FMG) has been proved to be a practical choice. However, an integrative and compact design of this hybrid sensor is lacking. This paper presents a novel modular EMG–FMG sensor; the sensing module has a novel design that consists of floating electrodes, which act as the sensing probe of both the EMG and FMG. This design improves the integration of the sensor. The whole system contains one data acquisition unit and eight identical sensor modules. Experiments were conducted to evaluate the performance of the sensor system. The results show that the EMG and FMG signals have good consistency under standard conditions; the FMG signal shows a better and more robust performance than the EMG. The average accuracy is 99.07% while using both the EMG and FMG signals for recognition of six hand gestures under standard conditions. Even with two layers of gauze isolated between the sensor and the skin, the average accuracy reaches 90.9% while using only the EMG signal; if we use both the EMG and FMG signals for classification, the average accuracy is 99.42%.
A Point-of-Care Based on Label-Free Interferometric Optical Detection Method to Evaluate Interferon Gamma (IFN-γ): A Correlation with the ELISA Technique
Authors: Heras María Fe Laguna , Ramirez Yolanda , Fernández Martín Celia , L. Espinosa Rocío , Lavín Alvaro , Holgado Miguel
Published: August 2020

Interferon-gamma (IFN-γ) is a cytokine associated with inflammatory diseases, virus, infection, etc. The quantification of interferon-gamma concentration levels is studied to relate the immune system response to the progression of disease. In this work, we used a label-free point-of-care device based on the increase relative optical power (IROP) and a biosensor based on photonic transducers called BICELLs (Biophotonic Sensing Cells) to evaluate interferon-gamma concentrations. The BICELLs’ sensing surface size used is 100 μm in diameter. The bioreceptor is attached to the surface by streptavidin-biotin affinity. This label-free IROP-based device can work with a low concentration of reagents and a low sample volume for measurements. Furthermore, this new device was compared with an ELISA technique in the same conditions. A good correlation was achieved between both techniques. This device is easy to use, and it is a cost-effective tool for monitoring an analyte in a disease.
Instrumented Four Square Step Test in Adults with Transfemoral Amputation: Test-Retest Reliability and Discriminant Validity between Two Types of Microprocessor Knees
Authors: Gouelle Arnaud , Highsmith Michael Jason
Published: August 2020

Technology-based outcomes have recently been proposed to complement the standard Four Square Step Test (FSST) by providing a decomposition of the sequences and information about the stepping pattern. A test-retest study and a randomized crossover design have been used to determine immediate test-retest reliability and to assess discriminant validity, in persons with a unilateral transfemoral amputation, for the parameters computed by an instrumented version of the Four Square Step Test. Twenty adults, independent and unlimited community ambulators, with a unilateral transfemoral amputation, performed two Four Square Step Tests on a pressure mat first with a microprocessor knee, then, a few weeks later with another one. One of these prosthetic knees was acknowledged to be superior and to provide functional improvement. Test-retest, intraclass correlation coefficients and minimal detectable change at 95% confidence level were calculated for each variable. Paired samples t-tests were then used to identify differences between the two microprocessor knee systems. The test-retest reliability of most outcome measures was good to excellent. Few variables showed a systematic difference and a trend to improve between test 1 and test 2. When comparing both microprocessor knees, significant differences in the expected direction were observed, with interpretation in accordance with a functional improvement. Importantly, we highlighted that various strategies to improve the performance in the test might complexify the interpretation of the most detailed measurement. The instrumented Four Square Step test provides reliable measures with satisfactory test-retest reliability and discriminant validity in persons with unilateral transfemoral amputation.
Adsorption, Desorption and Bioavailability of Tungstate in Mediterranean Soils
Authors: Petruzzelli Gianniantonio , Pedron Francesca
Published: August 2020

The adsorption and desorption process of the tungstate ion was studied in three soils characteristic of the Mediterranean area, with particularly reference to bioavailability pathways. In the three soils examined, the tungstate adsorption was described by a Langmuir-type equation, while the desorption process showed that not all the adsorbed tungstate was released, probably due to the formation of different bonds with the adsorbing soil surfaces. The pH was found to be the main soil property that regulates the adsorption/desorption: The maximum adsorption occurred in the soil with the acidic pH, and the maximum desorption in the most basic soil. In addition, the organic matter content played a fundamental role in the adsorption of tungstate by soils, being positively correlated with the maximum of adsorption. These results indicate that the lowest bioavailability should be expected in the acidic soil characterized by the highest adsorption capacity. This is confirmed by the trend of the maximum buffer capacity (MBC) of soils which is inversely related to bioavailability, and was the highest in the acidic soil and the lowest in the most basic soil. Our data could contribute in drafting environmental regulations for tungsten that are currently lacking for Mediterranean soils.
Secondary-School-Based Interventions to Improve Muscular Strength in Adolescents: A Systematic Review
Authors: García-Baños Carmelo , Rubio-Arias Jacobo Ángel , Martínez-Aranda Luis Manuel , Ramos-Campo Domingo Jesús
Published: August 2020

Physical education is considered an ideal environment for improving physical fitness and muscle strength through exercise and training. This systematic review aimed to analyze studies where an intervention was implemented in Secondary School Physical Education classes to improve muscle strength. The literature search was carried out in the SPORTDiscus, PubMed, Web of Science and ScienceDirect databases. We selected randomized and nonrandomized interventions conducted in Physical Education with adolescents aged 13–18 years, where muscle strength was evaluated, comparing a control group with one or more experimental groups. From the identified works after applying the levels of screening and eligibility, eight articles were chosen for the final analysis. Data collection and risk of bias assessment were performed independently by a single reviewer. The interventions of the included studies employed varied training loads, materials, and exercises. Significant improvements were achieved in all interventions for different strength measurement tests such as the Countermovement Jump (CMJ), Standing Long Jump (SLJ) and Squat Jump (SJ) tests, medicine ball throwing test, maximum isometric strength, manual dynamometry, push-up and curl-up tests, and maximum repetition tests. Strength training can be applied safely and effectively in Secondary Education. However, methodological differences in interventions have been identified; therefore, further research is needed.
Soil Quality Changes within a (Nothofagus obliqua) Forest Under Silvopastoral Management in the Andes Mountain Range, South Central Chile
Authors: Ortiz Juan , Dube Francis , Neira Pablo , Panichini Marcelo , Stolpe Neal B. , Zagal Erick , Martínez-Hernández Pedro A.
Published: August 2020

In Chile, 49.1% of the national territory is affected by soil degradation (including erosion and loss of soil organic matter), whereby of the 51.7 Mha that have been historically associated with agricultural-livestock and forestry activities, only 35.5 Mha are being used at the present. Consequently, soil degradation has resulted in the release of about 11.8 Gg yr−1 of carbon (C) equivalent (CO2eq) to the atmosphere. Silvopastoral systems (SPS), however, can increase soil organic C (SOC) through sequestration (C→SOC), improve ecosystem services, and have been internationally recommended for sustainable land use. Therefore, it was proposed to determine the effects of SPS on soils, over five years, in degraded sites that were located in the Ranchillo Alto (SPS-RA) (37°04′52″ S, 71°39′14″ W), Ñuble region. The sites were rated according to previous canopy disturbance levels (+) as follows: open (Op)+++, semi open (SOp)++, and semi closed (SC)+. The analysis was performed on different physical and chemical soil properties (0–5 and 5–20 cm depths), that were expressed as soil indicators (SIND) for chemical and physical properties, which were used to calculate a soil quality (SQ) index (SQI). The results indicated overall SQI values of 37.6 (SC) > 29.8 (Op) > 28.8 (SOp), but there were no significant variations (p < 0.05) in physical SQ, whereas chemical SQ varied in all conditions, mostly at 0–5 cm in Op and SOp. Increases of SOC were also observed (2015–2018 period) of 22.5, 14.5, and 4.8 Mg ha−1 for SOp, Op, and SC, respectively, showing that SPS promote the reclamation of Ranchillo Alto soils.
The Effect of a Nature-Based Environmental Education Program on Children’s Environmental Attitudes and Behaviors: A Randomized Experiment with Primary Schools
Authors: Collado Silvia , Rosa Claudio D. , Corraliza José A.
Published: August 2020

The evidence about the effects of nature-based instruction on pro-environmentalism is uncompelling, mainly due to a lack of controlled experiments. This hinders causal claims and the provision of intervention guidelines. We present an experiment examining the impact of a nature-based environmental education (NBEE) program included in the school curriculum on children’s environmental attitudes (EA) and behaviors (EB). Children who followed the program through traditional instruction were used as a control group. Seven Spanish primary schools participated in the program and school classes were randomly assigned to the NBEE program (experimental group, N = 516) or the environmental education (EE) through traditional instruction (control group, N = 218). Our results indicate that children’s EA increased more in the NBEE group than in the control group. On average, EB remained virtually the same in both groups of children across time. In light of our findings, we encourage the promotion of a nature-based pedagogy in formal education to enhance children’s environmental attitudes.
Simulating Soybean–Rice Rotation and Irrigation Strategies in Arkansas, USA Using APEX
Authors: Carroll Sam R. , Le Kieu Ngoc , Moreno-García Beatriz , Runkle Benjamin R. K.
Published: August 2020

With population growth and resource depletion, maximizing the efficiency of soybean (Glycine max [L.] Merr.) and rice (Oryza sativa L.) cropping systems is urgently needed. The goal of this study was to shed light on precise irrigation amounts and optimal agronomic practices via simulating rice–rice and soybean–rice crop rotations in the Agricultural Policy/Environmental eXtender (APEX) model. The APEX model was calibrated using observations from five fields under soybean–rice rotation in Arkansas from 2017 to 2019 and remote sensing leaf area index (LAI) values to assess modeled vegetation growth. Different irrigation practices were assessed, including conventional flooding (CVF), known as cascade, multiple inlet rice irrigation with polypipe (MIRI), and furrow irrigation (FIR). The amount of water used differed between fields, following each field’s measured or estimated input. Moreover, fields were managed with either continuous flooding (CF) or alternate wetting and drying (AWD) irrigation. Two 20-year scenarios were simulated to test yield changes: (1) between rice–rice and soybean–rice rotation and (2) under reduced irrigation amounts. After calibration with crop yield and LAI, the modeled LAI correlated to the observations with R2 values greater than 0.66, and the percent bias (PBIAS) values were within 32%. The PBIAS and percent difference for modeled versus observed yield were within 2.5% for rice and 15% for soybean. Contrary to expectation, the rice–rice and soybean–rice rotation yields were not statistically significant. The results of the reduced irrigation scenario differed by field, but reducing irrigation beyond 20% from the original amount input by the farmers significantly reduced yields in all fields, except for one field that was over-irrigated.
Best–Worst Method for Modelling Mobility Choice after COVID-19: Evidence from Italy
Authors: Moslem Sarbast , Campisi Tiziana , Szmelter-Jarosz Agnieszka , Duleba Szabolcs , Nahiduzzaman Kh Md , Tesoriere Giovanni
Published: August 2020

All countries have suffered from the COVID-19 crisis; the pandemic has adversely impacted all sectors. In this study, we examine the transport sector with a specific focus on the problem of commuting mode choice and propose a new decision-making approach for the alternative modes after synthesizing expert opinions. As a methodology, a customized model of the recently developed best–worst method (BWM) is used to evaluate mobility choice alternatives. The survey reflects citizens’ opinions toward mobility choices in two Italian cities, Palermo and Catania, before and during the pandemic. BWM is a useful tool for examining mobility choice in big cities. The adopted model is easy to apply and capable of providing effective solutions for sustainable mode choice. The urban context is analyzed considering the importance of transport choices, evaluating the variation of resilience to the changing opinions of users.
Analyzing Pathways of Nurturing Informal Seed Production into Formal Private Ventures for Sustainable Seed Delivery and Crop Productivity: Experiences from Ethiopia
Authors: Akpo Essegbemon , Feleke Gebrekidan , Fikre Asnake , Chichaybelu Mekasha , Ojiewo Chris O. , Varshney Rajeev K.
Published: August 2020

Sustaining crop production and productivity in sub-Saharan Africa requires the availability and use of quality seed of improved varieties by smallholder farmers. The private sector has been considered as the best way to sustain seed supply and crop productivity. Unfortunately, the private sector’s share in the seed production and delivery in sub-Saharan Africa countries has not been very substantial for decades. As a consequence, farmer access to quality seed of recently released varieties remains very low. This manuscript analyzes the experiences of informal seed producers who graduated to formal private seed enterprises to understand the effectiveness of the support they receive to become viable seed ventures. We used comparative research methods to analyze the qualitative and quantitative data collected to understand the underlying mechanisms. The findings showed that the analyzed seed enterprises started with as little as about USD 300 and have already multiplied over tenfold their initial capital. They benefited from a wide variety of supports, e.g., quality seed production, marketing, partnerships, and value chain development trainings and infrastructures, from extension workers, research centers, national and international NGOs, and the other private seed enterprise operators like large public seed enterprises and agro-dealers. The seed enterprises are producing pre-basic, basic, and certified seed of cereals and self-pollinated legume crops delivered directly to farmers, institutional markets, and agro-dealers. The seed production data have been increasing for the past three years with an area expanding from about 30 ha to over 150 ha per year for chickpea. The seed production and delivery practices being employed are smallholder farmer-based practices that are environmentally friendly. For sustainable and reliable seed production and delivery systems in sub-Saharan Africa, a bold step is needed whereby the informal seed production entities are nurtured and upgraded into formal certified seed production ventures that deliver social and economic benefits to the promotors and the communities.
Insecurity, Resource Scarcity, and Migration to Camps of Internally Displaced Persons in Northeast Nigeria
Authors: Kamta Frederic Noel , Schilling Janpeter , Scheffran Jürgen
Published: August 2020

For almost two decades, the Lake Chad Basin (LCB) in general and northeast Nigeria in particular have been subject to the insurgency of the Islamist terrorist group Boko Haram. This region is also known for its poor environmental conditions that mostly manifest in land desertification and water scarcity. We analyze the impact of the insecurity and conflict on migration from the most affected rural areas of northeast Nigeria to Maiduguri. We also explore the role that water scarcity and land desertification play in the decision of local people to migrate. Data were collected by interviewing 204 internally displaced persons (IDPs) at the Bakassi IDP camp in Maiduguri between March and May 2019. Experts were also interviewed at various governmental, non-governmental, and international institutions in Abuja. Respondents at the Bakassi IDP camp came from Guzamala, Gwoza, Marte, Monguno, and Nganzai. Though insecurity created by the conflict between Boko Haram insurgents and government forces was mentioned by all respondents as the main factor that triggered migration, this study shows that the decision to migrate was also a function of other factors that differ between communities. These factors include the geographical location of the community, land ownership, the socioeconomic status of the migrants, access to water and land, and wealth. This study reveals that in some communities, it was possible for people to live with conflict if they were still able to practice farming or if they had additional sources of income such as small businesses. The decision to migrate was only taken when the practice of such activities was no longer possible and they had nothing to hold on to.
Analysis on Decoupling between Urbanization Level and Urbanization Quality in China
Authors: Zhang Xueru , Song Wei , Wang Jingtao , Wen Bo , Yang Dazhi , Jiang Shiliang , Wu Yanbin
Published: August 2020

After the first industrial revolution, urbanization level worldwide has increased rapidly. As the largest developing country in the world, China has witnessed a rapid improvement in its urbanization level in recent years. Nevertheless, the quality of urbanization has not been improved simultaneously. The relationship between the level and the quality of urbanization has thus become a hot topic for researchers. By introducing the concept and model of decoupling in the field of resources and environment into the analysis of urbanization level and quality, this study evaluated the relationship between urbanization level and urbanization quality of 285 prefecture-level cities in China from 2005 to 2014. It was found that: (1) The urbanization level and urbanization quality in China are unbalanced because the former is growing in a faster rate than the latter. The average urbanization level of China has increased by 27.40% from 42.99% in 2005 to 54.77% in 2014, while the increase of urbanization quality, however, is much slower with only 11.21% for the same period. It can be concluded that China has paid more attention to urbanization level than urbanization quality. (2) From 2005 to 2014, the relationship between China’s urbanization level and quality showed a total of eight decoupling states, of which the main ones were strong negative decoupling (non-ideal state) and growth negative decoupling (close to ideal state), accounting for 38.32% and 33.49% of the total number of samples in China, respectively. (3) The change of urbanization level and urbanization quality in China can be divided into two stages: for the first stage from 2005 to 2010, with rapid improvement in urbanization level, and the other from 2011 to 2014, with rapid improvement in urbanization quality. (4) Spatially, the areas with significant decoupling between urbanization level and urbanization quality are mainly distributed in underdeveloped areas such as the west; and the decoupling presents the spatial pattern of the highest in the west, the second in the middle, and the lowest in the east.
Green Infrastructures in the Peri-Urban Landscape: Exploring Local Perception of Well-Being through ‘Go-Alongs’ and ‘Semi-Structured Interviews’
Authors: Santo-Tomás Muro Rocío , Sáenz de Tejada Granados Carlota , Rodríguez Romero Eva J.
Published: August 2020

Providing conditions for health and well-being, especially for those most exposed to social and environmental inequalities, is a precondition for sustainable development. Green infrastructures in peri-urban areas have the potential to improve the quality of life of locals by fostering healthy practices, providing views, or bringing nature closer to the city. This work explores the local perception of well-being within urban green infrastructures (UGI) in the peri-urban fringe of Madrid (Spain) through a combination of qualitative methods: “go-alongs” and “semi-structured static interviews”. The grounded-theory based codification of the data using NVivo software and their subsequent analysis results in the identification of social, natural, and perceptual elements that prove to play a relevant role in locals’ perception of well-being. Among these, connectivity with other green spaces, panoramic views and place-based memories are aspects that seem to make UGI serve the community at its full potential, including perceived physical and psychological well-being. We identify in each case study both positive characteristics of UGI and dysfunctional aspects and areas of opportunity. Lastly, a methodological, geographical, and theoretical discussion is made on the relevance of the case studies and pertinence of the two interview methods as valuable tools for analysis and intervention in the peri-urban landscape.
The Impact of Environmental Regulation on Technological Innovation of Resource-Based Industries
Authors: Li Weiqing , Sun Huaping , Tran Dang Khoa , Taghizadeh-Hesary Farhad
Published: August 2020

The development of the resource-based industry has obvious negative externality, and the government’s environmental regulation on the resource-based industry will force the technological innovation of the resource-based industry. This paper selects the panel data of 12 resource-based industries in China from 2003 to 2019 and tests the impact of environmental regulation on technological innovation of resource-based industries by constructing the econometric model. The results show that environmental regulation can promote the technological innovation of resource-based industries. Specifically, environmental regulation has no significant positive impact on the immediate product innovation of 12 resource-based industries in China, but it has a significant positive impact on the product innovation lagging behind one period and two periods. Environmental regulation has no significant impact on the process innovation of current period, but has a significant positive impact on the process innovation of lagging one period. Industrial scale has a significant positive impact on product innovation of resource-based industries. The input of scientific and technological activity personnel has a significant positive impact on the product innovation of current period, and in the long run, it promotes both product innovation and process innovation. On this basis, this paper puts forward the relevant measures and suggestions for the formulation of environmental regulation policies. The government departments should subdivide the resource-based industries, formulate environmental rules and policies by classification, encourage industrial enterprises to carry out technological innovation, reasonably implement fiscal and taxation policy tools and increase the investment in R&D funds, and improve the training mechanism of scientific and technological personnel.
Strengthening Professional Efficacy Due to Sustainable Development of Social and Individual Competences—Empirical Research Study among Polish and Slovak Employees of the Aviation Sector
Authors: Dobrowolska Małgorzata , Flakus Maria , Ślazyk-Sobol Magdalena , Wawoczny Adam
Published: August 2020

Nowadays, taking into account the multidimensionality of the external environment and necessity of the sustainable development of human resources, organizations are obliged to take more care of the psychological resources of their employees, e.g., positive orientation, ego resilience, and emotional stability. Such resources affect how we cope with stress and a sense of threat. The authors of this paper focus on people employed in the aviation sector, who work in the hard-to-cope environment of full automation, demanding working conditions and numerous stressors. The presented study fills a gap in the research on the psychological characteristics of the aviation sector. Moreover, a sense of stress/threat is described in the context of the high specificity of employees representing the 4.0 sector. Therefore, it provides additional insights into the psychological functioning of the employees in the aviation sector. The results show that both positive orientation and ego resilience might be seen as protective factors against a sense of threat and stress, while a type D personality is a risk factor of a higher level of those psychological states. The novelty of the presented research concerns a better understanding of the sense of stress/threat experienced by the employees in this sector, as well as verifying the relationships between psychological variables described in the literature as personal resources.
Evaluation of Water Quality Interaction by Dam and Weir Operation Using SWAT in the Nakdong River Basin of South Korea
Authors: Lee Jiwan , Lee Yonggwan , Woo Soyoung , Kim Wonjin , Kim Seongjoon
Published: August 2020

The purpose of this study was to evaluate the streamflow and water quality (SS, T-N, and T-P) interaction of the Nakdong river basin (23,609.3 km2) by simulating dam and weir operation scenarios using the Soil and Water Assessment Tool (SWAT). The operation scenarios tested were dam control (Scenario 1), dam control and weir gate control (Scenario 2), dam control and sequential release of the weirs with a one-month interval between each weir (Scenario 3), dam control and weir gate full open (Scenario 4), dam control and weir gate sequential full open (Scenario 5), weir gate control (Scenario 6), weir gate full open (Scenario 7), and weir gate sequential full open (Scenario 8). Before evaluation, the SWAT was calibrated and validated using 13 years (2005–2017) of daily multi-purpose dam inflow data from five locations ((Andong Dam (ADD), Imha Dam (IHD), Hapcheon Dam (HCD), Namkang Dam (NKD), and Milyang Dam (MYD))multi-function weir inflow data from seven locations (Sangju Weir (SJW), Gumi Weir (GMW), Chilgok Weir (CGW), Gangjeong-Goryeong Weir (GJW), Dalseong Weir (DSW), Hapcheon-Changnyeong Weir (HCW), and Changnyeong-Haman Weir (HAW)), and monthly water quality monitoring data from six locations (Andong-4 (AD-4), Sangju (SJ-2), Waegwan (WG), Hapcheon (HC), Namkang-4 (NK-4), and Mulgeum (MG). For the dam inflows and dam storage, the Nash-Sutcliffe efficiency (NSE) was 0.59~0.78, and the coefficient of determination (R2) was 0.71~0.90. For water quality, the R2 values of SS, T-N, and T-P were 0.58~0.83, 0.53~0.68, and 0.56~0.79, respectively. For the eight dam and weir release scenarios suggested by the Ministry of Environment, Scenarios 4 and 8 exhibited water quality improvement effects compared to the observed data.
Patterns of the Network of Cross-Border University Research Collaboration in the Guangdong-Hong Kong-Macau Greater Bay Area
Authors: Ma Jinyuan , Jiang Fan , Gu Liujian , Zheng Xiang , Lin Xiao , Wang Chuanyi
Published: August 2020

This study analyzes the patterns of university co-authorship networks in the Guangdong-Hong Kong-Macau Greater Bay Area. It also examines the quality and subject distribution of co-authored articles within these networks. Social network analysis is used to outline the structure and evolution of the networks that have produced co-authored articles at universities in the Greater Bay Area from 2014 to 2018, at both regional and institutional levels. Field-weighted citation impact (FWCI) is used to analyze the quality and citation impact of co-authored articles in different subject fields. The findings of the study reveal that university co-authorship networks in the Greater Bay Area are still dispersed, and their disciplinary development is unbalanced. The study also finds that, while the research areas covered by high-quality co-authored articles fit the strategic needs of technological innovation and industrial distribution in the Greater Bay Area, high-quality research collaboration in the humanities and social sciences is insufficient.
How Much Is One Life Worth? The Right to Equity Healthcare for Improving Older Patients’ Health Infected by COVID-19
Authors: Merodio Guiomar , Ramis-Salas Mimar , Valero Diana , Aubert Adriana
Published: August 2020

Ageism has a tremendous negative impact on elderly persons and society. Discrimination against the elderly is a driver of health and social inequalities. The COVID-19 pandemic has posed new social and health challenges regarding resource scarcity and shortfalls. Under these difficult circumstances, discourses excluding, and discrimination against, older people have aroused. This article gathers evidence on hospital healthcare experiences of older people infected by COVID-19 during the pandemic outbreak in Spain and it analyzes elements that have positively influenced older patients’ perceived health and well-being. We conducted nine qualitative in-depth interviews in Madrid—one of the regions of Spain most affected by COVID-19—with older people that were hospitalized and recovered from COVID-19, family members of old patients infected with COVID-19, and nurses that attended infected older patients. Findings show the challenging experiences faced by older people who were hospitalized due to COVID-19, on the one hand, and the relevance of transformative aspects related to family relationships, solidarity actions, and humanized care that overcame age discrimination, favoring social and equity healthcare for the elderly on the other hand.