bluuebunny/crossref_metadata_2025 huggingface dataset:
Applying Fully Convolutional Architectures for Semantic Segmentation of a Single Tree Species in Urban Environment on High Resolution UAV Optical Imagery
Authors: Lobo Torres Daliana , Queiroz Feitosa Raul , Nigri Happ Patrick , Elena Cué La Rosa Laura , Marcato Junior José , Martins José , Olã Bressan Patrik , Gonçalves Wesley Nunes , Liesenberg Veraldo
Published: January 2020

This study proposes and evaluates five deep fully convolutional networks (FCNs) for the semantic segmentation of a single tree species: SegNet, U-Net, FC-DenseNet, and two DeepLabv3+ variants. The performance of the FCN designs is evaluated experimentally in terms of classification accuracy and computational load. We also verify the benefits of fully connected conditional random fields (CRFs) as a post-processing step to improve the segmentation maps. The analysis is conducted on a set of images captured by an RGB camera aboard a UAV flying over an urban area. The dataset also contains a mask that indicates the occurrence of an endangered species called Dipteryx alata Vogel, also known as cumbaru, taken as the species to be identified. The experimental analysis shows the effectiveness of each design and reports average overall accuracy ranging from 88.9% to 96.7%, an F1-score between 87.0% and 96.1%, and IoU from 77.1% to 92.5%. We also realize that CRF consistently improves the performance, but at a high computational cost.
A Comparison of Different Methods to Estimate the Effective Spatial Resolution of FO-DTS Measurements Achieved during Sandbox Experiments
Authors: Simon Nataline , Bour Olivier , Lavenant Nicolas , Porel Gilles , Nauleau Benoît , Pouladi Behzad , Longuevergne Laurent
Published: January 2020

For many environmental applications, the interpretation of fiber-optic Raman distributed temperature sensing (FO-DTS) measurements is strongly dependent on the spatial resolution of measurements, especially when the objective is to detect temperature variations over small scales. Here, we propose to compare three different and complementary methods to estimate, in practice, the “effective” spatial resolution of DTS measurements: The classical “90% step change” method, the correlation length estimated from experimental semivariograms, and the derivative method. The three methods were applied using FO-DTS measurements achieved during sandbox experiments using two DTS units having different spatial resolutions. Results show that the value of the spatial resolution estimated using a step change depends on both the effective spatial resolution of the DTS unit and on heat conduction induced by the high thermal conductivity of the cable. The correlation length method provides an estimate much closer to the value provided by the manufacturers, representative of the effective spatial resolutions along cable sections where temperature gradients are small or negligible. Thirdly, the application of the derivative method allows for verifying the representativeness of DTS measurements all along the cable, by localizing sections where measurements are representative of the effective temperature. We finally show that DTS measurements could be validated in sandbox experiments, when using devices with finer spatial resolution.
Predictive Maintenance of Boiler Feed Water Pumps Using SCADA Data
Authors: Moleda Marek , Momot Alina , Mrozek Dariusz
Published: January 2020

IoT enabled predictive maintenance allows companies in the energy sector to identify potential problems in the production devices far before the failure occurs. In this paper, we propose a method for early detection of faults in boiler feed pumps using existing measurements currently captured by control devices. In the experimental part, we work on real measurement data and events from a coal fired power plant. The main research objective is to implement a model that detects deviations from the normal operation state based on regression and to check which events or failures can be detected by it. The presented technique allows the creation of a predictive system working on the basis of the available data with a minimal requirement of expert knowledge, in particular the knowledge related to the categorization of failures and the exact time of their occurrence, which is sometimes difficult to identify. The paper shows that with modern technologies, such as the Internet of Things, big data, and cloud computing, it is possible to integrate automation systems, designed in the past only to control the production process, with IT systems that make all processes more efficient through the use of advanced analytic tools.
Microseismic Event Location by Considering the Influence of the Empty Area in an Excavated Tunnel
Authors: Peng Pingan , Jiang Yuanjian , Wang Liguan , He Zhengxiang
Published: January 2020

The velocity model is a key factor that affects the accuracy of microseismic event location around tunnels. In this paper, we consider the effect of the empty area on the microseismic event location and present a 3D heterogeneous velocity model for excavated tunnels. The grid-based heterogeneous velocity model can describe a 3D arbitrarily complex velocity model, where the microseismic monitoring areas are divided into many blocks. The residual between the theoretical arrival time calculated by the fast marching method (FMM) and the observed arrival time is used to identify the block with the smallest residual. Particle swarm optimization (PSO) is used to improve the location accuracy in this block. Synthetic tests show that the accuracy of the microseismic event location based on the heterogeneous velocity model was higher than that based on the single velocity model, independent of whether an arrival time error was considered. We used the heterogeneous velocity model to locate 7 blasting events and 44 microseismic events with a good waveform quality in the Qinling No. 4 tunnel of the Yinhanjiwei project from 6 June 2017 to 13 June 2017 and compared the location results of the heterogeneous-velocity model with those of the single-velocity model. The results of this case study show that the events located by the heterogeneous velocity model were concentrated around the working face, which matched the actual conditions of the project, while the events located by the single-velocity model were scattered and far from the working face.
Iterative Analog–Digital Multi-User Equalizer for Wideband Millimeter Wave Massive MIMO Systems
Authors: Magueta Roberto , Castanheira Daniel , Pedrosa Pedro , Silva Adão , Dinis Rui , Gameiro Atílio
Published: January 2020

Most of the previous work on hybrid transmit and receive beamforming focused on narrowband channels. Because the millimeter wave channels are expected to be wideband, it is crucial to propose efficient solutions for frequency-selective channels. In this regard, this paper proposes an iterative analog–digital multi-user equalizer scheme for the uplink of wideband millimeter-wave massive multiple-input-multiple-output (MIMO) systems. By iterative equalizer we mean that both analog and digital parts are updated using as input the estimates obtained at the previous iteration. The proposed iterative analog–digital multi-user equalizer is designed by minimizing the sum of the mean square error of the data estimates over the subcarriers. We assume that the analog part is fixed for all subcarriers while the digital part is computed on a per subcarrier basis. Due to the complexity of the resulting optimization problem, a sequential approach is proposed to compute the analog phase shifters values for each radio frequency (RF) chain. We also derive an accurate, semi-analytical approach for obtaining the bit error rate (BER) of the proposed hybrid system. The proposed solution is compared with other hybrid equalizer schemes, recently designed for wideband millimeter-wave (mmWave) massive MIMO systems. The simulation results show that the performance of the developed analog–digital multi-user equalizer is close to full-digital counterpart and outperforms the previous hybrid approach.
The Coefficient of Variation of Step Time Can Overestimate Gait Abnormality: Test-Retest Reliability of Gait-Related Parameters Obtained with a Tri-Axial Accelerometer in Healthy Subjects
Authors: Fujiwara Shunrou , Sato Shinpei , Sugawara Atsushi , Nishikawa Yasumasa , Koji Takahiro , Nishimura Yukihide , Ogasawara Kuniaki
Published: January 2020

The aim of this study was to investigate whether variation in gait-related parameters among healthy participants could help detect gait abnormalities. In total, 36 participants (21 men, 15 women; mean age, 35.7 ± 9.9 years) performed a 10-m walk six times while wearing a tri-axial accelerometer fixed at the L3 level. A second walk was performed ≥1 month after the first (mean interval, 49.6 ± 7.6 days). From each 10-m data set, the following nine gait-related parameters were automatically calculated: assessment time, number of steps, stride time, cadence, ground force reaction, step time, coefficient of variation (CV) of step time, velocity, and step length. Six repeated measurement values were averaged for each gait parameter. In addition, for each gait parameter, the difference between the first and second assessments was statistically examined, and the intraclass correlation coefficient (ICC) was calculated with the level of significance set at p < 0.05. Only the CV of step time showed a significant difference between the first and second assessments (p = 0.0188). The CV of step time also showed the lowest ICC, at <0.50 (0.425), among all parameters. Test–retest results of gait assessment using a tri-axial accelerometer showed sufficient reproducibility in terms of the clinical evaluation of all parameters except the CV of step time.
Assessing the Response of Ecosystem Water Use Efficiency to Drought During and after Drought Events across Central Asia
Authors: Zou Jie , Ding Jianli , Welp Martin , Huang Shuai , Liu Bohua
Published: January 2020

The frequency and intensity of drought are expected to increase worldwide in the future. However, it is still unclear how ecosystems respond to drought. Ecosystem water use efficiency (WUE) is an essential ecological index used to measure the global carbon–water cycles, and is defined as the carbon absorbed per unit of water lost by the ecosystem. In this study, we applied gross primary productivity (GPP), evapotranspiration (ET), land surface temperature (LST), and normalized difference vegetation index (NDVI) data to calculate the WUE and drought index (temperature vegetation dryness index (TVDI)), all of which were retrieved from moderate resolution imaging spectroradiometer (MODIS) data. We compared the mean WUE across different vegetation types, drought classifications, and countries. The temporal and spatial changes in WUE and drought were analyzed. The correlation between drought and WUE was calculated and compared across different vegetation types, and the differences in WUE between drought and post-drought periods were compared. The results showed that (1) ecosystems with a low (high) productivity had a high (low) WUE, and the mean ecosystem WUE of Central Asia showed vast differences across various drought levels, countries, and vegetation types. (2) The WUE in Central Asia exhibited an increasing trend from 2000 to 2014, and Central Asia experienced both drought (from 2000 to 2010) and post-drought (from 2011 to 2014) periods. (3) The WUE showed a negative correlation with drought during the drought period, and an obvious drought legacy effect was found, in which severe drought affected the ecosystem WUE over the following two years, while a positive correlation between WUE and drought was found in the post-drought period. (4) A significant increase in ecosystem WUE was found after drought, which revealed that arid ecosystems exhibit high resilience to drought stress. Our results can provide a specific reference for understanding how ecosystems will respond to climate change.
Recognizing New Classes with Synthetic Data in the Loop: Application to Traffic Sign Recognition
Authors: Villalonga Gabriel , Van de Weijer Joost , López Antonio M.
Published: January 2020

On-board vision systems may need to increase the number of classes that can be recognized in a relatively short period. For instance, a traffic sign recognition system may suddenly be required to recognize new signs. Since collecting and annotating samples of such new classes may need more time than we wish, especially for uncommon signs, we propose a method to generate these samples by combining synthetic images and Generative Adversarial Network (GAN) technology. In particular, the GAN is trained on synthetic and real-world samples from known classes to perform synthetic-to-real domain adaptation, but applied to synthetic samples of the new classes. Using the Tsinghua dataset with a synthetic counterpart, SYNTHIA-TS, we have run an extensive set of experiments. The results show that the proposed method is indeed effective, provided that we use a proper Convolutional Neural Network (CNN) to perform the traffic sign recognition (classification) task as well as a proper GAN to transform the synthetic images. Here, a ResNet101-based classifier and domain adaptation based on CycleGAN performed extremely well for a ratio ∼ 1 / 4 for new/known classes; even for more challenging ratios such as ∼ 4 / 1 , the results are also very positive.
Review on Smart Electro-Clothing Systems (SeCSs)
Authors: Muhammad Sayem Abu Sadat , Hon Teay Siew , Shahariar Hasan , Luise Fink Paula , Albarbar Alhussein
Published: January 2020

This review paper presents an overview of the smart electro-clothing systems (SeCSs) targeted at health monitoring, sports benefits, fitness tracking, and social activities. Technical features of the available SeCSs, covering both textile and electronic components, are thoroughly discussed and their applications in the industry and research purposes are highlighted. In addition, it also presents the developments in the associated areas of wearable sensor systems and textile-based dry sensors. As became evident during the literature research, such a review on SeCSs covering all relevant issues has not been presented before. This paper will be particularly helpful for new generation researchers who are and will be investigating the design, development, function, and comforts of the sensor integrated clothing materials.
Using Accelerometer and GPS Data for Real-Life Physical Activity Type Detection
Authors: Allahbakhshi Hoda , Conrow Lindsey , Naimi Babak , Weibel Robert
Published: January 2020

This paper aims to examine the role of global positioning system (GPS) sensor data in real-life physical activity (PA) type detection. Thirty-three young participants wore devices including GPS and accelerometer sensors on five body positions and performed daily PAs in two protocols, namely semi-structured and real-life. One general random forest (RF) model integrating data from all sensors and five individual RF models using data from each sensor position were trained using semi-structured (Scenario 1) and combined (semi-structured + real-life) data (Scenario 2). The results showed that in general, adding GPS features (speed and elevation difference) to accelerometer data improves classification performance particularly for detecting non-level and level walking. Assessing the transferability of the models on real-life data showed that models from Scenario 2 are strongly transferable, particularly when adding GPS data to the training data. Comparing individual models indicated that knee-models provide comparable classification performance (above 80%) to general models in both scenarios. In conclusion, adding GPS data improves real-life PA type classification performance if combined data are used for training the model. Moreover, the knee-model provides the minimal device configuration with reliable accuracy for detecting real-life PA types.
Auto-Correction of 3D-Orientation of IMUs on Electric Bicycles
Authors: Schnee Jan , Stegmaier Jürgen , Lipowsky Tobias , Li Pu
Published: January 2020

The application of inertial measurement units (IMU) in electronically power-assisted cycles (EPACs) has become increasingly important for improving their functionalities. One central issue of such an application is to calibrate the orientation of the IMU on the EPAC. The approach presented in this paper utilizes common bicycling motions to calibrate the 2D- and 3D-mounting orientation of a micro-electro-mechanical system (MEMS) IMU on an electric bicycle. The method is independent of sensor biases and requires only a very low computation expense and, thus, the estimation can be realized in real-time. In addition, the acceleration biases are estimated using a barometric pressure sensor. The experimental results show high accuracy of the calibrated orientation and estimated sensor biases.
On the Calibration of GNSS-Based Vehicle Speed Meters
Authors: Martucci Adolfo , Cerasuolo Giovanni , Petrella Orsola , Laracca Marco
Published: January 2020

Thanks to their metrological characteristics (accuracy, dimensions, synchronization capability, easy interfacing, and so on), in the last few years, the GNSS (Global Navigation Satellite System) based speed instruments are often used in a wide field of application. The traceability of the measurement results achieved by the GNSS instrument should be made by means of calibration procedures in compliance with the ISO/IEC 17025 standard and ILAC (International Laboratory Accreditation Cooperation) policy on the traceability of measurement results. In this context, some calibration methodologies have been proposed in the literature or used by some calibration centers. In a speed range from 1 to 300 km/h, an analysis on the suitability of the experimental calibration method (based on a couple of photocells placed on the road at a certain distance) for the GNSS speed measurement systems is presented in this paper. An analysis of the measurement setup has allowed for the recognition of both all the uncertainty contributions and defines the variability range of their values. After the formulation of the relationships between the uncertainty contributions and the total calibration uncertainty due to the calibration method, the sensitivity analysis has been made. The analyzed measurement setup, even if considering a careful choice of both instrumentations and methodologies, is suitable for the calibration of high accuracy GNSS based instruments only considering distances between the photocells sufficiently large and for speed values lower than 200 km/h. In any case, the proposed analysis can be a useful tool to allow for the choices on the measurement setup to reach the desired trade-off between calibration costs and compliance with technical requirements and also the calibration of instrumentation different by GNSS.
Human Emotion Recognition: Review of Sensors and Methods
Authors: Dzedzickis Andrius , Kaklauskas Artūras , Bucinskas Vytautas
Published: January 2020

Automated emotion recognition (AEE) is an important issue in various fields of activities which use human emotional reactions as a signal for marketing, technical equipment, or human–robot interaction. This paper analyzes scientific research and technical papers for sensor use analysis, among various methods implemented or researched. This paper covers a few classes of sensors, using contactless methods as well as contact and skin-penetrating electrodes for human emotion detection and the measurement of their intensity. The results of the analysis performed in this paper present applicable methods for each type of emotion and their intensity and propose their classification. The classification of emotion sensors is presented to reveal area of application and expected outcomes from each method, as well as their limitations. This paper should be relevant for researchers using human emotion evaluation and analysis, when there is a need to choose a proper method for their purposes or to find alternative decisions. Based on the analyzed human emotion recognition sensors and methods, we developed some practical applications for humanizing the Internet of Things (IoT) and affective computing systems.
Feasibility of Discriminating UAV Propellers Noise from Distress Signals to Locate People in Enclosed Environments Using MEMS Microphone Arrays
Authors: Izquierdo Alberto , del Val Lara , Villacorta Juan J. , Zhen Weikun , Scherer Sebastian , Fang Zheng
Published: January 2020

Detecting and finding people are complex tasks when visibility is reduced. This happens, for example, if a fire occurs. In these situations, heat sources and large amounts of smoke are generated. Under these circumstances, locating survivors using thermal or conventional cameras is not possible and it is necessary to use alternative techniques. The challenge of this work was to analyze if it is feasible the integration of an acoustic camera, developed at the University of Valladolid, on an unmanned aerial vehicle (UAV) to locate, by sound, people who are calling for help, in enclosed environments with reduced visibility. The acoustic array, based on MEMS (micro-electro-mechanical system) microphones, locates acoustic sources in space, and the UAV navigates autonomously by closed enclosures. This paper presents the first experimental results locating the angles of arrival of multiple sound sources, including the cries for help of a person, in an enclosed environment. The results are promising, as the system proves able to discriminate the noise generated by the propellers of the UAV, at the same time it identifies the angles of arrival of the direct sound signal and its first echoes reflected on the reflective surfaces.
Solid-State Emissive Metallo-Supramolecular Assemblies of Quinoline-Based Acyl Hydrazone
Authors: Cho Hye Jin , Kim TaeWoo , Kim Hyunwoo , Song Changsik
Published: January 2020

Development of fluorescence-based sensory materials for metal elements is currently in the mainstream of research due to the simplicity and usability of fluorescence as a method of detection. Herein, we report a novel “bis”-quinoline-based acyl hydrazone—named bQH that could be synthesized by a facile, low-cost method through simple condensation of hydrazide with an aldehyde. This acyl hydrazone showed emissive properties through Zn selective binding, especially in its solid-state, as shown by experiments such as UV–Vis, photoluminescence (PL), nuclear magnetic resonance (NMR), and inductively-coupled plasma-optical emission spectroscopies (ICP-OES), and energy-dispersive X-ray spectroscopy (EDS) mapping. The binding modes in which bQH coordinates to Zn2+ was proved to consist of two modes, 1:1 and 1:2 (bQH:Zn2+), where the binding mode was controlled by the Zn2+ ion content. Under the 1:1 binding mode, bQH-Zn2+ complexes formed a polymeric array through the metallo-supramolecular assembly. The resulting bQH-Zn2+ complex maintained its fluorescence in solid-state and exhibited excellent fluorescence intensity as compared to the previously reported quinoline-based acyl hydrazone derivative (mQH).
Optimum Water and Fertilizer Management for Better Growth and Resource Use Efficiency of Rapeseed in Rainy and Drought Seasons
Authors: Feng Jun , Hussain Hafiz Athar , Hussain Saddam , Shi Chao , Cholidah Linna , Men Shengnan , Ke Jianhong , Wang Longchang
Published: January 2020

Optimum water–fertilizer management in rainfed agriculture is an important factor in improving crop productivity and the ecological environment under fluctuating climate conditions, especially in Southwest China, where seasonal drought and waterlogging occur frequently. In order to investigate the effects of different cultivation technologies on growth and the water and fertilizer use efficiency of rapeseed (Brassica napus L.), a two-year field study was conducted in rainy (2016–2017) and drought (2017–2018) seasons which included three cultivation patterns: (1) conventional flat planting (FP); (2) straw mulching (SM); (3) ridge-furrow rainfall harvesting system (RF), and three fertilization patterns: (1) conventional fertilization (CF); (2) reduced slow-release fertilizer (SR); and (3) no fertilizer as a control treatment. The results indicated that the yield and its composition values were lower in the rainy year than in the seasonal dry year. The single water-saving technology had no significant effect on yield increase when seasonal drought occurred. The two technologies (SM + SR and RF + SR) improved the height, leaf SPAD value and dry matter of the rapeseed and adjusted the root–shoot ratio under two different climate conditions. In the rainy season, these technologies reduced the loss of nutrients, while in the seasonal drought year, it increased the soil moisture. The SM + SR and RF + SR increased the yield of rapeseed by 7.71% and 29.93% and enhanced oil content by 4.64% and 7.91%, respectively, compared with the local cultivation pattern. Meanwhile, these treatments decreased the total water consumption during whole growth stages and promoted water use efficiency by 14.84% and 28.71%, respectively. The combination of SM + SR and RF + SR also increased the accumulation of N, P, and K and significantly promoted the utilization efficiency of fertilizer. In the future, the adverse effects of environmental factors could be relieved, and the goal of cost savings and increasing efficiency could be achieved by adopting the optimal cultivation technologies in rapeseed production of Southwest China.
Anthropogenic Influences on Environmental Changes of Lake Bosten, the Largest Inland Freshwater Lake in China
Authors: Liu Wen , Ma Long , Abuduwaili Jilili
Published: January 2020

A short lacustrine sediment core (41 cm) from Lake Bosten in arid central Asia was used to investigate the environmental changes that occurred in the past ≈150 years based on the superposition of climate and anthropogenic factors. Geochemical elements, total organic carbon (TOC) and nitrogen (TN), and stable isotope data (δ13Corg and δ15N) were used to identify abnormal environmental changes. The average C/N ratio in the sediments of Lake Bosten suggested that the organic matter in lake sediments was mainly from aquatic plants. The δ13Corg and δ15N in the lake sediments mainly reflect changes in the structure of the lake’s ecosystem. Before the 1960s, the primary productivity of the lake was relatively low with a relatively stable lake water environment. From the 1960s to the mid-1980s, the lake’s ecosystem was closely related to a significant decline in water levels caused by human activities and an increase in salinity. From the late 1980s to ≈2000, the aquatic plant structure of Lake Bosten did not change significantly. After 2000, the upper part of the sedimentary record suggested enhanced productivity due to urban and industrial development in the catchment area. However, sedimentary perspectives of the responses of different environmental proxies in sediments to human activities were anisochronous, and the increasing heavy metal (Pb and Cu) and P accumulations appeared in 1970, reflecting heightened human impacts. Through the comparison between the Aral Sea and Lake Bosten, it was inferred that, under the intervention of human activities, the lake experienced a completely different evolution trend. Humans, as geological agents, should protect our living environment while satisfying social development. The results will provide an important supplement to a large spatial scale study of the influences of human activities on the environment in Central Asia, which also has some significant implications for the protection of the ecological environment and the realization of sustainable development in arid regions.
Assessment of the DRT System Based on an Optimal Routing Strategy
Authors: Kim Jooyoung
Published: January 2020

Demand responsive transport (DRT) is operated according to flexible routes, dispatch intervals, and dynamic demand, is attracting a lot of attention. The biggest characteristic of the DRT service is that the vehicle routes and schedules are operated optimally based on real-time travel requests of using passengers without fixed operating schedules. This study analyzed the feasibility of implementing the DRT service by analyzing the benefits for the users and cost of the operator from the effects of increasing public transportation use and providing personalized mobility service based on DRT implementation by the introduction of DRT using multi-agent transport simulation (MATSim). Through the simulation, the DRT is expected to provide convenient, fast, and cost-effective mobility services to customers; provide an optimal vehicle scale to providers; and, ultimately, achieve a safe and efficient transportation system.
The Social Metabolism of Quiet Sustainability in the Faroe Islands
Authors: Bogadóttir Ragnheiður
Published: January 2020

This paper investigates the interrelations between social metabolism and socio-ecological sustainability in the Faroe Islands in a long-term perspective. It traces the trajectory and changes in socio-metabolic configurations from the time of settlement until today and shows how social metabolism has increased to very high per capita levels during the past century. The analysis departs from the recognition that a decrease in social metabolism, i.e., a net reduction in throughput of natural resources in human economies, is necessary in order to curb the impending ecological crisis. It is argued that parallel to the growth oriented formal Faroese economy, economic food-provisioning practices rooted in the traditional, and ecologically sustainable, land management system continue to be practiced by Faroese people. These practices can be conceptualized as practices of so-called “quiet sustainability” and their contribution is estimated in bio-physical metrics of weight. The analysis shows that practices of “quiet sustainability” contribute significant quantities of certain food items to the local population thereby enhancing food security and food sovereignty. Moreover, these practices are an integral element in the biocultural diversity, which has constituted the Faroe Islands for close to two millennia. Therefore, they should be considered real alternatives to import-based consumption and taken into account in sustainability discourse and policy to a higher degree than is currently the case.
Analysis of Tail Dependence between Sovereign Debt Distress and Bank Non-Performing Loans
Authors: Liu Li , Liu Yu-Min , Kim Jong-Min , Zhong Rui , Ren Guang-Qian
Published: January 2020

We investigate the tail dependence between sovereign debt distress and bank non-performing loans (NPLs) using a large sample of developed and emerging countries in recent decades. Considering the feedback loop of sovereign debt and bank loan distress, we use three copula models to analyze the asymmetry of tail dependence structure between sovereign debt exposure and bank NPLs. We use the Gaussian copula marginal regression to control the concurrent impact of other macroeconomic variables. We provide evidence that sovereign debt indicates an important determinant of NPLs. We also find that there is tail dependence between sovereign debt distress and bank NPLs, whereas the tail dependence coefficients vary across countries. Our findings shed light on the influence of fiscal distress on bank loan distress and provide immediate implications for the design of macro prudential and financial policy.
Encouraging Pro-Environmental Behaviors Through Children-Based Appeals: A Kin Selection Perspective
Authors: Palomo-Vélez Gonzalo , Buczny Jacek , Van Vugt Mark
Published: January 2020

Environmental problems are due to the fact of humans prioritizing their narrow personal interests over collective interests. How can pro-environmental behavior be promoted without requiring people to behave in ways that go against their selfish tendencies? Kin selection theory asserts that humans are predisposed to ensure the survival and replication of their genes which they share with their offspring. We hypothesized that appeals to the welfare of their children would foster pro-environmental decision-making through activating a parental care motivation. Four studies examined the impact of messages about the welfare of (potential) children on environmental intentions. Overall, the results show that children-based appeals indirectly fostered ecological intentions through an increased parental care motivation. Furthermore, meta-analyses triangulated these findings by showing that people with children show greater parental care and pro-environmental intentions. These results are discussed in light of the kin selection theory, and its implications for environmental policymaking are addressed.
Drought Risk to Agricultural Systems in Zimbabwe: A Spatial Analysis of Hazard, Exposure, and Vulnerability
Authors: Frischen Janna , Meza Isabel , Rupp Daniel , Wietler Katharina , Hagenlocher Michael
Published: January 2020

The devastating impacts of drought are fast becoming a global concern. Zimbabwe is among the countries more severely affected, where drought impacts have led to water shortages, declining yields, and periods of food insecurity, accompanied by economic downturns. In particular, the country’s agricultural sector, mostly comprised of smallholder rainfed systems, is at great risk of drought. In this study, a multimethod approach is applied, including a remote sensing-based analysis of vegetation health data from 1989–2019 to assess the drought hazard, as well as a spatial analysis combined with expert consultations to determine drought vulnerability and exposure of agricultural systems. The results show that droughts frequently occur with changing patterns across Zimbabwe. Every district has been affected by drought during the past thirty years, with varying levels of severity and frequency. Severe drought episodes have been observed in 1991–1992, 1994–1995, 2002–2003, 2015–2016, and 2018–2019. Drought vulnerability and exposure vary substantially in the country, with the south-western provinces of Matabeleland North and South showing particularly high levels. Assessments of high-risk areas, combined with an analysis of the drivers of risk, set the path towards tailor-made adaptation strategies that consider drought frequency and severity, exposure, and vulnerability.
Proximal Cities: Does Walkability Drive Informal Settlements?
Authors: Cutini Valerio , Di Pinto Valerio , Rinaldi Antonio Maria , Rossini Francesco
Published: January 2020

The uncontrolled growth of urban areas worldwide is pushing a substantial part of the urban population to the fringes of society, confining them to the unsecure and unhygienic settlements that we call “informal.” These settlements lack in intelligible layout and essential services and infrastructures, thus representing a challenging issue for policy makers and urban designers in the development of renewal programs and strategies. In order to support the facing of these issues through an on-site upgrade approach, this paper argues that walkability deeply affects the functioning of informal settlements, so as to propose that they can be identified as “proximal cities,” which expresses the idea that the vital space in informal settlements has soft boundaries and follows a fuzzy logic. A quantitative analysis, based on a configurational approach, and a qualitative analysis, focused on the morphologic features of the settlements, have been implemented. A comparison of the results shows that this approach is suitable to provide a deeper knowledge on informal settlement and informal society under the assumption of their strict mutual connection. A primal definition of proximal cities, suitable for describing some properties of autopoietic urban systems, emerges from the evidence-based relationships between their spatial and social features. In this respect, a case study has been proposed and discussed.
Identification of Heracleum sosnowskyi-Invaded Land Using Earth Remote Sensing Data
Authors: Sužiedelytė Visockienė Jūratė , Tumelienė Eglė , Maliene Vida
Published: January 2020

H. sosnowskyi (Heracleum sosnowskyi) is a plant that is widespread both in Lithuania and other countries and causes abundant problems. The damage caused by the population of the plant is many-sided: it menaces the biodiversity of the land, poses risk to human health, and causes considerable economic losses. In order to find effective and complex measures against this invasive plant, it is very important to identify places and areas where H. sosnowskyi grows, carry out a detailed analysis, and monitor its spread to avoid leaving this process to chance. In this paper, the remote sensing methodology was proposed to identify territories covered with H. sosnowskyi plants (land classification). Two categories of land cover classification were used: supervised (human-guided) and unsupervised (calculated by software). In the application of the supervised method, the average wavelength of the spectrum of H. sosnowskyi was calculated for the classification of the RGB image and according to this, the unsupervised classification by the program was accomplished. The combination of both classification methods, performed in steps, allowed obtaining better results than using one. The application of authors’ proposed methodology was demonstrated in a Lithuanian case study discussed in this paper.
Decision-Making in the Transport Sector: A Sustainable Evaluation Method for Road Infrastructure
Authors: Henke Ilaria , Cartenì Armando , Molitierno Clorinda , Errico Assunta
Published: January 2020

The transport sector is often the center of political and scientific debate on sustainability due to negative externalities produced by the daily movement of goods and people which impact both on the environment and on quality of life. Great interest has therefore focused on impact estimation of transport infrastructures/services with respect to social, economic, and environmental sustainability. Among the consolidated assessment methods, the cost–benefit analysis (CBA) is one of the quantitative tools representing the final stage (decision) in decision-making processes, which compares design alternatives and verifies the sustainability of a transport project. Recently the Italian Government proposed the national “Guidelines for Assessment of Investment Projects” based on CBA. The aim of this research is twofold: a) from a research point of view, to propose a sustainable evaluating method for impact assessment of the new transportation infrastructure aimed in performing both rational and shared decisions with the territories; b) for a practical point of view, to propose a first application of the CBA Italian guideline useful for the professional practice in the field of public investment evaluation. A quantitative impacts assessment of social, economic and environmental sustainability was performed for a revamping project of a new “greenway” in the south of Italy. Furthermore, also the social equity impacts produced by the new road infrastructure was also quantified, estimating the GINI indexes variation as a measure of effectiveness.
Purchase Intention in the Online Open Market: Do Concerns for E-Commerce Really Matter?
Authors: Kim Sang Soo
Published: January 2020

This study aims to investigate motivational factors and motivation hindering factors of online shopping via online open market platforms. For a comprehensive exploration, the response data were collected from a total of 417 Korean consumers before conducting a hierarchical regression analysis. The results showed that the effects of motivation factors on purchasing intention were all supported. As for moderating effects of concerns for e-commerce, privacy concerns by time saving, perceived ease of use, and security concerns by cost saving were found to be statistically significant. Privacy concerns by cost saving and business integrity concerns by time saving were also found to be statistically significant, but had a positive effect as opposed to an initial prediction. The finding denotes that, in order to reduce concerns for e-commerce, consumers may prefer using the online shops they can trust based on their previous shopping experience. Various concerns identified and analyzed in this study are clues to better understanding what potentially motivates or obstructs consumers to shop online, thereby helping businesses thrive in the online open market.
Soliton Solutions of Mathematical Physics Models Using the Exponential Function Technique
Authors: Javeed Shumaila , Saleem Alimgeer Khurram , Nawaz Sidra , Waheed Asif , Suleman Muhammad , Baleanu Dumitru , Atif M.
Published: January 2020

This paper is based on finding the exact solutions for Burger’s equation, Zakharov-Kuznetsov (ZK) equation and Kortewegde vries (KdV) equation by utilizing exponential function method that depends on the series of exponential functions. The exponential function method utilizes the homogeneous balancing principle to find the solutions of nonlinear equations. This method is simple, wide-reaching and helpful for finding the exact solution of nonlinear conformable PDEs.
A Method of L1-Norm Principal Component Analysis for Functional Data
Authors: Yu Fengmin , Liu Liming , Yu Nanxiang , Ji Lianghao , Qiu Dong
Published: January 2020

Recently, with the popularization of intelligent terminals, research on intelligent big data has been paid more attention. Among these data, a kind of intelligent big data with functional characteristics, which is called functional data, has attracted attention. Functional data principal component analysis (FPCA), as an unsupervised machine learning method, plays a vital role in the analysis of functional data. FPCA is the primary step for functional data exploration, and the reliability of FPCA plays an important role in subsequent analysis. However, classical L2-norm functional data principal component analysis (L2-norm FPCA) is sensitive to outliers. Inspired by the multivariate data L1-norm principal component analysis methods, we propose an L1-norm functional data principal component analysis method (L1-norm FPCA). Because the proposed method utilizes L1-norm, the L1-norm FPCs are less sensitive to the outliers than L2-norm FPCs which are the characteristic functions of symmetric covariance operator. A corresponding algorithm for solving the L1-norm maximized optimization model is extended to functional data based on the idea of the multivariate data L1-norm principal component analysis method. Numerical experiments show that L1-norm FPCA proposed in this paper has a better robustness than L2-norm FPCA, and the reconstruction ability of the L1-norm principal component analysis to the original uncontaminated functional data is as good as that of the L2-norm principal component analysis.
Bilateral and Unilateral Asymmetries of Strength and Flexibility in Young Elite Sailors: Windsurfing, Optimist and Laser Classes
Authors: Caraballo Israel , González-Montesinos José Luis , Alías Antonio
Published: January 2020

In sport sailing, performance is related to the sailor’s ability to maintain the stability of the boat, and the boat class determines the variables involved in such ability. In monohull-type vessels, such as the Optimist and Laser classes, the flexibility of the hip joint is a key performance factor. In the Windsurfing class, performance is determined by the strength of the flexors of the fingers and elbows. The performance of the sailor may be affected by asymmetries in the strength and flexibility of the muscles and joints involved in technical actions. The objective of this study was to evaluate asymmetries in strength and flexibility in young sailors. Thirty-three young sailors (ten girls) from the Windsurfing, Optimist and Laser classes were assessed for manual strength and flexibility, by dynamometry and straight leg lift tests, respectively. The symmetry index and the functional asymmetry of compression force were calculated. The results showed no differences between sailors according to gender. The sailors of the Laser class obtained the highest levels of manual strength, whereas those of the Windsurfing class showed the highest flexibility levels. The girls’ group and Windsurfing class had the highest percentage of sailors with strength asymmetry, whereas, the sailors of the Optimist class presented a greater percentage of asymmetry in flexibility. There were no differences in upper limb strength and lower limb flexibility between the dominant and non-dominant sides.
Modeling Quality of Urban Life Using a Geospatial Approach
Authors: Merschdorf Helena , Hodgson Michael E. , Blaschke Thomas
Published: January 2020

The rapid global urbanization of the past century poses several challenges for planners and policy makers. In particular, the conflation of social and urban issues must be understood to create sustainable and livable urban places. In this regard, it was our aim to model and understand the relationship between urban characteristics and peoples’ perceived quality of urban life (QoUL) using statistical analysis and geospatial modeling. We selected objective variables representing urban characteristics based on literature and used principal components analysis to develop uncorrelated components. These components served as the independent variables in a multiple linear regression analysis. The subjective, dependent variables were extracted from a QoUL survey. Results indicated that only the Education/Income component is related to QoUL (R2 of 0.46). Using only single independent variables in a linear model explained 46% of the total variance—over 10% higher than any previously determined relationship between objective variables and subjective QoUL. Furthermore, we found that subjective high QoUL and subjective low QoUL were not strongly correlated, indicating that they are affected by different objective variables, respectively. This suggests that future efforts of increasing QoUL need to define their goals more precisely, as measures for increasing perceptions of high QoUL are likely different from measures for decreasing perceptions of low QoUL.
Effects of Water Stress on Fluorescence Parameters and Photosynthetic Characteristics of Drip Irrigation in Rice
Authors: Xu Qiang , Ma Xiaopeng , Lv Tingbo , Bai Meng , Wang Zelin , Niu Jingran
Published: January 2020

To study the effects of water stress on the fluorescence parameters and photosynthetic characteristics of rice under drip irrigation and mulching, so as to determine the response mechanisms to water stress during the tillering stage. A two-year trial was carried out at Shihezi University, China. Three water gradients were investigated. The results showed that the chlorophyll content (a + b), photosynthetic rate (Pn), and leaf area index (LAI) decreased with decreasing soil moisture content at the tillering stage. The chlorophyll content (a + b) and Pn in the flooding irrigation (CK) treatment were significantly higher than those in the stress treatments, and the chlorophyll content (a + b) and Pn in the W1 and W2 treatments were significantly lower than those in the other treatments. The maximum LAI of the CK, W1, and W2 treatments were similar, while the W3 produced lower values; stress treatment improved the ability of tillering in the early and middle stages, while the decrease in soil water content in the tillering stage resulted in a decrease in the final tillering rate; drought stress in the tillering stage resulted in decreased rice yields. The yield of the W1 and W2 treatments were similar, while that of the W3 treatment was seriously reduced. The main reasons for the reduction in yield was the significant decrease in the number of effective panicles, the seed setting rate, and a decrease in the 1000-grains weight. Water consumption in the stress treatments decreased by 51.69%–58.78% compared to the CK treatment; water-use efficiency in the CK treatment was only 0.25 kg·m−3, and the water-use efficiency of the stress treatments increased by 40%–72%. We should make full use of the compensation effect of drought stress in the water regulation of drip irrigation in covered rice and adopt the water control measure of the W2 treatment in the tillering stage. These measures are conducive to improving water-use efficiency and achieving the goal of high quality, high yield, and high efficiency.