bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluations of Machine Learning-Based CYGNSS Soil Moisture Estimates against SMAP Observations
Authors: Senyurek Volkan , Lei Fangni , Boyd Dylan , Gurbuz Ali Cafer , Kurum Mehmet , Moorhead Robert
Published: October 2020

This paper presents a machine learning (ML) framework to derive a quasi-global soil moisture (SM) product by direct use of the Cyclone Global Navigation Satellite System (CYGNSS)’s high spatio-temporal resolution observations over the tropics (within ±38° latitudes) at L-band. The learning model is trained by using in-situ SM data from the International Soil Moisture Network (ISMN) sites and various space-borne ancillary data. The approach produces daily SM retrievals that are gridded to 3 km and 9 km within the CYGNSS spatial coverage. The performance of the model is independently evaluated at various temporal scales (daily, 3-day, weekly, and monthly) against Soil Moisture Active Passive (SMAP) mission’s enhanced SM products at a resolution of 9 km × 9 km. The mean unbiased root-mean-square difference (ubRMSD) between concurrent (same calendar day) CYGNSS and SMAP SM retrievals for about three years (from 2017 to 2019) is 0.044 cm3 cm−3 with a correlation coefficient of 0.66 over SMAP recommended grids. The performance gradually improves with temporal averaging and degrades over regions regularly flagged by SMAP such as dense forest, high topography, and coastlines. Furthermore, CYGNSS and SMAP retrievals are evaluated against 170 ISMN in-situ observations that result in mean unbiased root-mean-square errors (ubRMSE) of 0.055 cm3 cm−3 and 0.054 cm3 cm−3, respectively, and a higher correlation coefficient with CYGNSS retrievals. It is important to note that the proposed approach is trained over limited in-situ observations and is independent of SMAP observations in its training. The retrieval performance indicates current applicability and future growth potential of GNSS-R-based, directly measured spaceborne SM products that can provide improved spatio-temporal resolution than currently available datasets.
Meta-analysis of Unmanned Aerial Vehicle (UAV) Imagery for Agro-environmental Monitoring Using Machine Learning and Statistical Models
Authors: Eskandari Roghieh , Mahdianpari Masoud , Mohammadimanesh Fariba , Salehi Bahram , Brisco Brian , Homayouni Saeid
Published: October 2020

Unmanned Aerial Vehicle (UAV) imaging systems have recently gained significant attention from researchers and practitioners as a cost-effective means for agro-environmental applications. In particular, machine learning algorithms have been applied to UAV-based remote sensing data for enhancing the UAV capabilities of various applications. This systematic review was performed on studies through a statistical meta-analysis of UAV applications along with machine learning algorithms in agro-environmental monitoring. For this purpose, a total number of 163 peer-reviewed articles published in 13 high-impact remote sensing journals over the past 20 years were reviewed focusing on several features, including study area, application, sensor type, platform type, and spatial resolution. The meta-analysis revealed that 62% and 38% of the studies applied regression and classification models, respectively. Visible sensor technology was the most frequently used sensor with the highest overall accuracy among classification articles. Regarding regression models, linear regression and random forest were the most frequently applied models in UAV remote sensing imagery processing. Finally, the results of this study confirm that applying machine learning approaches on UAV imagery produces fast and reliable results. Agriculture, forestry, and grassland mapping were found as the top three UAV applications in this review, in 42%, 22%, and 8% of the studies, respectively.
Forecasting Spatio-Temporal Dynamics on the Land Surface Using Earth Observation Data—A Review
Authors: Koehler Jonas , Kuenzer Claudia
Published: October 2020

Reliable forecasts on the impacts of global change on the land surface are vital to inform the actions of policy and decision makers to mitigate consequences and secure livelihoods. Geospatial Earth Observation (EO) data from remote sensing satellites has been collected continuously for 40 years and has the potential to facilitate the spatio-temporal forecasting of land surface dynamics. In this review we compiled 143 papers on EO-based forecasting of all aspects of the land surface published in 16 high-ranking remote sensing journals within the past decade. We analyzed the literature regarding research focus, the spatial scope of the study, the forecasting method applied, as well as the temporal and technical properties of the input data. We categorized the identified forecasting methods according to their temporal forecasting mechanism and the type of input data. Time-lagged regressions which are predominantly used for crop yield forecasting and approaches based on Markov Chains for future land use and land cover simulation are the most established methods. The use of external climate projections allows the forecasting of numerical land surface parameters up to one hundred years into the future, while auto-regressive time series modeling can account for intra-annual variances. Machine learning methods have been increasingly used in all categories and multivariate modeling that integrates multiple data sources appears to be more popular than univariate auto-regressive modeling despite the availability of continuously expanding time series data. Regardless of the method, reliable EO-based forecasting requires high-level remote sensing data products and the resulting computational demand appears to be the main reason that most forecasts are conducted only on a local scale. In the upcoming years, however, we expect this to change with further advances in the field of machine learning, the publication of new global datasets, and the further establishment of cloud computing for data processing.
A Novel Ambiguity Parameter Estimation and Elimination Strategy for GNSS/INS Tightly Coupled Integration
Authors: Ma Chun , Zhang Qiuzhao , Meng Xiaolin , Zheng Nanshan , Pan Shuguo
Published: October 2020

The estimation of ambiguity in the global navigation satellite system/inertial navigation system (GNSS/INS) tightly coupled system is a key issue for GNSS/INS precise navigation positioning. Only when the ambiguity is solved correctly can the integrated navigation system obtain high-precision positioning results. Aiming at the problem of ambiguity parameter estimation in GNSS/INS tightly coupled system, a new strategy for ambiguity parameter estimation and elimination is proposed in this paper. Here, the ambiguity parameter is first added to the state equations of GNSS/INS in the estimation process. Then, the strategy of eliminating the parameter is used to improve efficiency. A residual test is carried out based on introducing the ambiguity parameter, thereby reducing or avoiding its influence on the filtering estimation process. Two groups of experiments were carried out and compared with GNSS positioning results. The results showed that, in the open sky observation environment, the positioning accuracy of the GNSS/INS tightly coupled method proposed in this paper was within 5 cm, and the ambiguity fixed rate was more than 97%, which is basically consistent. In a GNSS-denied environment, the positioning accuracy of the GNSS/INS tightly coupled method proposed in this paper was obviously better than that of GNSS, and the positioning accuracy in X, Y, and Z directions was improved by 82.46%, 78.87%, and 79.67%, respectively. The fixed rate of ambiguity increased from 73% to 78.57%. Therefore, in a GNSS-challenged environment, the novel strategy of the GNSS/INS tightly coupled system has higher ambiguity fixed rate and significantly improves positioning accuracy and continuity.
One-Dimensional Multi-Scale Domain Adaptive Network for Bearing-Fault Diagnosis under Varying Working Conditions
Authors: Wang Kai , Zhao Wei , Xu Aidong , Zeng Peng , Yang Shunkun
Published: October 2020

Data-driven bearing-fault diagnosis methods have become a research hotspot recently. These methods have to meet two premises: (1) the distributions of the data to be tested and the training data are the same; (2) there are a large number of high-quality labeled data. However, machines usually work under different working conditions in practice, which challenges these prerequisites due to the fact that the data distributions under different working conditions are different. In this paper, the one-dimensional Multi-Scale Domain Adaptive Network (1D-MSDAN) is proposed to address this issue. The 1D-MSDAN is a kind of deep transfer model, which uses both feature adaptation and classifier adaptation to guide the multi-scale convolutional neural network to perform bearing-fault diagnosis under varying working conditions. Feature adaptation is performed by both multi-scale feature adaptation and multi-level feature adaptation, which helps in finding domain-invariant features by minimizing the distribution discrepancy between different working conditions by using the Multi-kernel Maximum Mean Discrepancy (MK-MMD). Furthermore, classifier adaptation is performed by entropy minimization in the target domain to bridge the source classifier and target classifier to further eliminate domain discrepancy. The Case Western Reserve University (CWRU) bearing database is used to validate the proposed 1D-MSDAN. The experimental results show that the diagnostic accuracy for the 12 transfer tasks performed by 1D-MSDAN was superior to that of the mainstream transfer learning models for bearing-fault diagnosis under variable working conditions. In addition, the transfer learning performance of 1D-MSDAN for multi-target domain adaptation and real industrial scenarios was also verified.
A Survey on Trust Management for WBAN: Investigations and Future Directions
Authors: Ayed Samiha , Chaari Lamia , Fares Amina
Published: October 2020

The rapid uptake of the Wireless Body Area Networks (WBAN) and their services poses unprecedented security requirements. WBAN are evolving to support these requirements. Fulfilling these tasks is challenging as their mobile context is increasingly complex, heterogeneous, and evolving. One potential solution to meet the WBAN security requirements is trust management that helps to reach a more secure and adaptable WBAN environment. Accordingly, this article aims to serve as a brief survey of trust management approaches within intra-WBAN and inter-WBAN. For that, we first summarize trust management concepts, discuss WBAN challenges and classify the attacks on WBAN trust management models. Subsequently, we detail and compare the existing trust based approaches in a WBAN context. We pinpoint their limitations and provide a new classification of these different approaches. We also propose a set of best practices that may help the reader to build a robust and an efficient trust management framework. We complete this survey by highlighting the open future directions and perspectives for research.
Flexible Virtual Reality System for Neurorehabilitation and Quality of Life Improvement
Authors: Stanica Iulia-Cristina , Moldoveanu Florica , Portelli Giovanni-Paul , Dascalu Maria-Iuliana , Moldoveanu Alin , Ristea Mariana Georgiana
Published: October 2020

As life expectancy is mostly increasing, the incidence of many neurological disorders is also constantly growing. For improving the physical functions affected by a neurological disorder, rehabilitation procedures are mandatory, and they must be performed regularly. Unfortunately, neurorehabilitation procedures have disadvantages in terms of costs, accessibility and a lack of therapists. This paper presents Immersive Neurorehabilitation Exercises Using Virtual Reality (INREX-VR), our innovative immersive neurorehabilitation system using virtual reality. The system is based on a thorough research methodology and is able to capture real-time user movements and evaluate joint mobility for both upper and lower limbs, record training sessions and save electromyography data. The use of the first-person perspective increases immersion, and the joint range of motion is calculated with the help of both the HTC Vive system and inverse kinematics principles applied on skeleton rigs. Tutorial exercises are demonstrated by a virtual therapist, as they were recorded with real-life physicians, and sessions can be monitored and configured through tele-medicine. Complex movements are practiced in gamified settings, encouraging self-improvement and competition. Finally, we proposed a training plan and preliminary tests which show promising results in terms of accuracy and user feedback. As future developments, we plan to improve the system’s accuracy and investigate a wireless alternative based on neural networks.
Towards Improving TSCH Energy Efficiency: An Analytical Approach to a Practical Implementation
Authors: Sordi Marcos A. , K. Rayel Ohara , Moritz Guilherme L. , Rebelatto João L.
Published: October 2020

The IEEE 802.15.4-2015 standard defines a number of Medium Access Control (MAC) layer protocols for low power wireless communications, which are desirable for energy-constrained Internet of Things (IoT) devices. Originally defined in the IEEE 802.15.4e amendment, the Time Slotted Channel Hopping (TSCH) has recently been attracting attention from the research community due to its reduced contention (time scheduling) and robustness against fading (channel hopping). However, it requires a certain level of synchronization between the nodes, which can increase the energy consumption. In this work, we implement the Guard Beacon (GB) strategy, aiming at reducing the guard time usually implemented to compensate for imperfect synchronization. Moreover, besides presenting a realistic energy consumption model for a Contiki Operating System-based TSCH network, we show through analytical and practical results that, without the proposed scheme, the power consumption can be more than 13% higher.
Design, Validation and Comparison of Path Following Controllers for Autonomous Vehicles
Authors: Yang Xing , Xiong Lu , Leng Bo , Zeng Dequan , Zhuo Guirong
Published: October 2020

As one of the core issues of autonomous vehicles, vehicle motion control directly affects vehicle safety and user experience. Therefore, it is expected to design a simple, reliable, and robust path following the controller that can handle complex situations. To deal with the longitudinal motion control problem, a speed tracking controller based on sliding mode control with nonlinear conditional integrator is proposed, and its stability is proved by the Lyapunov theory. Then, a linear parameter varying model predictive control (LPV-MPC) based lateral controller is formulated that the optimization problem is solved by CVXGEN. The nonlinear active disturbance rejection control (ADRC) method is applied to the second lateral controller that is easy to be implemented and robust to parametric uncertainties and disturbances, and the pure pursuit algorithm serves as a benchmark. Simulation results in different scenarios demonstrate the effectiveness of the proposed control schemes, and a comparison is made to highlight the advantages and drawbacks. It can be concluded that the LPV-MPC has some trouble to handle uncertainties while the nonlinear ADRC performs slight worse tracking but has strong robustness. With the parallel development of the control theory and computing power, robust MPC may be the future direction.
A Low-Cost 3D Phenotype Measurement Method of Leafy Vegetables Using Video Recordings from Smartphones
Authors: Yang Zishang , Han Yuxing
Published: October 2020

Leafy vegetables are an essential source of the various nutrients that people need in their daily lives. The quantification of vegetable phenotypes and yield estimation are prerequisites for the selection of genetic varieties and for the improvement of planting methods. The traditional method is manual measurement, which is time-consuming and cumbersome. Therefore, there is a need for efficient and convenient in situ vegetable phenotype identification methods to provide data support for breeding research and for crop yield monitoring, thereby increasing vegetable yield. In this paper, a novel approach was developed for the in-situ determination of the three-dimensional (3D) phenotype of vegetables by recording video clips using smartphones. First, a smartphone was used to record the vegetable from different angles, and then the key frame containing the crop area in the video was obtained using an algorithm based on the vegetation index and scale-invariant feature transform algorithm (SIFT) matching. After obtaining the key frame, a dense point cloud of the vegetables was reconstructed using the Structure from Motion (SfM) method, and then the segmented point cloud and a point cloud skeleton were obtained using the clustering algorithm. Finally, the plant height, leaf number, leaf length, leaf angle, and other phenotypic parameters were obtained through the point cloud and point cloud skeleton. Comparing the obtained phenotypic parameters to the manual measurement results, the root-mean-square error (RMSE) of the plant height, leaf number, leaf length, and leaf angle were 1.82, 1.57, 2.43, and 4.7, respectively. The measurement accuracy of each indicators is greater than 80%. The results show that the proposed method provides a convenient, fast, and low-cost 3D phenotype measurement pipeline. Compared to other methods based on photogrammetry, this method does not need a labor-intensive image-capturing process and can reconstruct a high-quality point cloud model by directly recording videos of crops.
Evaluating the Impact of Increased Fuel Cost and Iran’s Currency Devaluation on Road Traffic Volume and Offenses in Iran, 2011–2019
Authors: Delavary Milad , Ghayeninezhad Zahra , Lavallière Martin
Published: October 2020

Trends and underlying patterns should be identified in the timely distribution of road traffic offenses to increase traffic safety. In this study, a time series analysis was used to study the incidence rate of road traffic violations on Iranian rural roads. Road traffic volume and offenses data from March 2011 to October 2019 were aggregated. Interrupted time series were used to evaluate the impact of increasing fuel cost in June of 2013 and July of 2014 and the currency devaluation of Rial vs. US dollars in July of 2017 on trends and patterns, traffic volume, and number of offenses. A change-point detection (CPD) analysis was also used to identify singular changes in the frequency of traffic offenses. Results show a general decline in the number of overtaking and speeding offenses of −24.31% and −13.23%, respectively, due to the first increase in fuel cost. The second increase only reduced overtaking by 20.97%. In addition, Iran’s currency devaluation reduced the number of overtaking offenses by 26.39%. Modeling a change-point detection and a Mann-Kendall Test of traffic offenses in Iran, it was found that the burden of violations was reduced.
Global Perspective on Marital Satisfaction
Authors: Dobrowolska Małgorzata , Groyecka-Bernard Agata , Sorokowski Piotr , Randall Ashley K. , Hilpert Peter , Ahmadi Khodabakhsh , Alghraibeh Ahmad M. , Aryeetey Richmond , Bertoni Anna , Bettache Karim , Błażejewska Marta , Bodenmann Guy , Bortolini Tiago S. , Bosc Carla , Butovskaya Marina , Castro Felipe N. , Cetinkaya Hakan , Cunha Diana , David Daniel , David Oana Alexandra , Dileym Fahd A. , Domínguez Espinosa Alejandra C. , Donato Silvia , Dronova Daria , Dural Seda , Fisher Maryanne , Frackowiak Tomasz , Akkaya Aslıhan Hamamcıoğlu , Hamamura Takeshi , Hansen Karolina , Hattori Wallisen Tadashi , Hromatko Ivana , Gulbetekin Evrim , Iafrate Raffaella , James Bawo , Jiang Feng , Kimamo Charles O. , Koç Fırat , Krasnodębska Anna , Lopes Fívia A. , Martinez Rocio , Meskó Norbert , Molodovskaya Natalya , Qezeli Khadijeh Moradi , Motahari Zahrasadat , Natividade Jean Carlos , Ntayi Joseph , Ojedokun Oluyinka , Omar-Fauzee Mohd S. B. , Onyishi Ike E. , Özener Barış , Paluszak Anna , Portugal Alda , Realo Anu , Relvas Ana Paula , Rizwan Muhammad , Sabiniewicz Agnieszka , Salkičević Svjetlana , Sarmány-Schuller Ivan , Stamkou Eftychia , Stoyanova Stanislava , Šukolová Denisa , Sutresna Nina , Tadinac Meri , Teras Andero , Tinoco Ponciano Edna Lúcia , Tripathi Ritu , Tripathi Nachiketa , Tripathi Mamta , Yamamoto Maria E. , Yoo Gyesook , Sorokowska Agnieszka
Published: October 2020

Across the world, millions of couples get married each year. One of the strongest predictors of whether partners will remain in their relationship is their reported satisfaction. Marital satisfaction is commonly found to be a key predictor of both individual and relational well-being. Despite its importance in predicting relationship longevity, there are relatively few empirical research studies examining predictors of marital satisfaction outside of a Western context. To address this gap in the literature and complete the existing knowledge about global predictors of marital satisfaction, we used an open-access database of self-reported assessments of self-reported marital satisfaction with data from 7178 participants representing 33 different countries. The results showed that sex, age, religiosity, economic status, education, and cultural values were related, to various extents, to marital satisfaction across cultures. However, marriage duration, number of children, and gross domestic product (GDP) were not found to be predictors of marital satisfaction for countries represented in this sample. While 96% of the variance of marital satisfaction was attributed to individual factors, only 4% was associated with countries. Together, the results show that individual differences have a larger influence on marital satisfaction compared to the country of origin. Findings are discussed in terms of the advantages of conducting studies on large cross-cultural samples.
Spatial–Temporal Characteristics and Influencing Factors of Coupled Coordination between Urbanization and Eco-Environment: A Case Study of 13 Urban Agglomerations in China
Authors: Wan Jia , Zhang Liwei , Yan Junping , Wang Xiaomeng , Wang Ting
Published: October 2020

Urban agglomeration is the core area of not only regional economic development and urbanization but also human–land contradiction. Based on the population–economy–society–spatial model and the pressure–state–response model, this study develops an evaluation index system for the urbanization and eco-environment of 13 urban agglomerations in China. The urbanization index and eco-environment index are determined using the coefficient of variation method. The coupled coordination of the two indices is measured with the coupled coordination model, and the influence of the indicator factors is calculated with a geographical detector. The results reveal the following: (1) The urbanization indices of the 13 urban agglomerations in China increase year by year, and the spatial distribution pattern is high in the east and low in the west. (2) The eco-environment index shows an “S-shaped” variation trend, and the spatial difference between urban agglomerations gradually decreases. (3) The coupled coordination is mainly characterized as a mild imbalance, and the spatial distribution pattern is “balance in the east and imbalance in the west”. (4) The coupled coordination degree between urbanization and eco-environment is affected by many factors. Among such factors, economic urbanization, social urbanization, spatial urbanization, and eco-environment response are the main controlling factors. The impact of population urbanization, eco-environment pressure, and eco-environment state presents a gradual increase.
The Predictive Effect of Teachers’ Perception of School Principals’ Motivating Language on Teachers’ Self-Efficacy via a Cultural Context
Authors: Ozeren Emir , Arslan Aykut , Yener Serdar , Appolloni Andrea
Published: October 2020

The aim of the study is to investigate the relationship between teachers’ perception of school principals’ motivating language and teachers’ self-efficacy mediated by the cultural context. School principals’ linguistic communication skills are critical to sustain the motivation of teachers and their self-efficacy. Motivating language theory (MLT), on which this study is based, provides a model that helps us understand how the language, more precisely, the speech acts, used by school principals have an impact on teachers’ self-efficacy. A survey method was employed with 252 teachers through convenience sampling. The teachers’ mean age was 34.87 (SD = 9.22) years, and the average length of service was 11.72 (SD = 9.42) years. The results showed that school principals’ use of motivating language was significantly and positively associated with teachers’ self-efficacy (b = 0.10, p < 0.000). The low-context culture was found to have a full mediating effect in this relationship (b = 0.04, t = 3.1771, p < 0.000). The findings contribute to leader communication theory by highlighting a particular emphasis on the language school principals use to motivate teachers.
Jump Aggregation, Volatility Prediction, and Nonlinear Estimation of Banks’ Sustainability Risk
Authors: Wang Zhouwei , Zhao Qicheng , Zhu Min , Pang Tao
Published: October 2020

Extreme financial events usually lead to sharp jumps in stock prices and volatilities. In addition, jump clustering and stock price correlations contribute to the risk amplification acceleration mechanism during the crisis. In this paper, four Jump-GARCH models are used to forecast the jump diffusion volatility, which is used as the risk factor. The linear and asymmetric nonlinear effects are considered, and the value at risk of banks is estimated by support vector quantile regression. There are three main findings. First, in terms of the volatility process of bank stock price, the Jump Diffusion GARCH model is better than the Continuous Diffusion GARCH model, and the discrete jump volatility is significant. Secondly, due to the difference of the sensitivity of abnormal information shock, the jump behavior of bank stock price is heterogeneous. Moreover, CJ-GARCH models are suitable for most banks, while ARJI-R2-GARCH models are more suitable for small and medium sized banks. Thirdly, based on the jump diffusion volatility information, the performance of the support vector quantile regression is better than that of the parametric quantile regression and nonparametric quantile regression.
Dismissals and Temporary Leaves in Romanian Companies in the Context of Low Demand and Cash Flow Problems during the COVID-19 Economic Lockdown
Authors: Turnea Elena-Sabina , Neștian Ștefan Andrei , Tiță Silviu Mihail , Vodă Ana Iolanda , Guță Alexandra Luciana
Published: October 2020

The aim of this study is to describe the relations between low demand, cash flow problems, employee dismissals, and temporary leaves experienced by Romanian companies during the economic lockdown in the first two months of the COVID-19 pandemic outbreak in Romania (16 March–16 May 2020). For this purpose, we conducted a quantitative study using descriptive, correlation, and regression analyses applied to data collected from company decision-makers. Our results show that demand for products/services and cash flow in companies has decreased significantly, the workforce being affected by dismissals and temporary leaves/furloughing. Additionally, the average linear revenue of companies has been decreasing due to insufficient cash flow, higher absenteeism of workers, customers having been affected, and the demand going down. Therefore, employee dismissals, employee temporary leaves (furlough), and dismissal intentions have been positively correlated with insufficient cash flow in companies and an extremely low demand.
Sustainability Perceptions in Tourism and Hospitality: A Mixed-Method Bibliometric Approach
Authors: Lima Santos Luís , Cardoso Lucília , Araújo-Vila Noelia , Fraiz-Brea Jose A.
Published: October 2020

In the post-Covid-19 era, tourism impacts and the role played by sustainable planning on the long-term success of destinations have gained renewed importance. Understanding the image and perceptions tourists hold of a destination is vital for tourism planning, as they play a key role in tourists’ decisions. Considering the importance of these two key concepts (perceptions and sustainability), the present paper contributes to the advancement of knowledge on sustainable tourism by characterizing the state of the art of Sustainability Perceptions in Tourism and Hospitality (SPTH). To this end, the scientific literature on the topic was mapped through a combination of three bibliometric analysis techniques, namely: evaluative, relational, and systematic bibliometric analysis. These were based on productivity and impact indicators, including SciVal topic prominence. The results reveal that sustainability perceptions in SPTH focus on tourists’, stakeholders’, and residents’ perceptions. These findings highlight the need for involving local communities in the destination planning process to align the outcomes of tourism development with their expectations. Finally, this paper presents an original methodological contribution, as it is the first to apply the SciVal topic prominence analysis to SPTH.
Sustainable Construction through Industry Self-Regulation: The Development and Role of Building Environmental Assessment Methods in Achieving Green Building
Authors: Leiringer Roine
Published: October 2020

The role of industry self-regulation in facilitating sustainable development has gained increasing recognition over the past two decades. As a result, voluntary certification standards have become ever more common and have been portrayed as effective means of enforcing more environmentally beneficial practices across a range of industries. In this paper, we consider the role of one such type of standard, building environmental assessment methods (BEAMs), and the role they have played in the transition towards green building in the construction industry. Drawing on the theory of strategic action fields, and using the case of HK BEAM in Hong Kong, we investigate the origins, development and impact of BEAMs in what is a highly de-centralised and fragmented industry. The paper concludes with reflections on the need to extend focus from the contents of the BEAMs in terms of categories, criteria and weightings, to instead more actively consider the “taken-for-granted” assumptions around sustainability and the dominant institutionalised practices in construction.
Pricing Decisions and Innovation Strategies Choice in Supply Chain with Competing Manufacturers and Common Supplier
Authors: Liu Bin , Yang Guohua , Zhang Qi
Published: October 2020

This paper evaluates efficacy of supplier and manufacturer innovation under an asymmetric competing supply chain consisting of one supplier and two manufacturers. We depict pricing decisions and innovation strategies under three models, namely, benchmark model, supplier-led, and manufacturer-led innovation models. It is shown that although the supplier is motivated to innovate, all innovation strategies have more profits than single innovation strategies. In addition, when no manufacturer creates the product, one manufacturer will obtain a good profit from the innovation, while facing the competitor, the other manufacturer will have incentive to innovate. Moreover, we also evaluate implications of innovation strategy for consumer welfare and overall supply chain efficiency.
Martial Arts Tourism of the “Europe—Far East” Direction, in the Opinion of Grand Masters
Authors: Figueiredo Abel A. , Błach Wiesław , Bujak Zbigniew , Maroteaux Roland J. , Cynarski Wojciech J.
Published: October 2020

Martial arts tourism is a form of cultural, sports and educational tourism that requires special recognition; particularly important is knowledge about martial arts. The sources of this practical knowledge are especially high-ranking masters. The scientific problem raised here involves the issue of high-ranking martial arts teachers taking trips for their own studies (to acquire knowledge and skills) and teaching others. Some of the questions addressed include how often the trips occur (single, sporadic, or multiple, regular), what their effects are, and what their meaning is—in the opinion of these experts. The “Martial Arts Tourism” questionnaire was addressed to N = 12 people, masters/teachers of high-rank in martial arts (level 7–10 dan/toan) who live and teach in Europe and the USA, but come from Europe. They are the holders of the highest degrees in Chinese, Japanese and Korean styles. Further questions were asked through direct correspondence. The collected statements were usedby means of qualitative analysis—as in the method of ‘expert courts’/’competent judges’. The respondents in most cases undertook trips from Europe to East Asia for their own learning. They teach themselves mainly in their own countries and in Europe. Stays rarely lasted over two weeks. The respondents are convinced of the legitimacy of this type of trip, and believe that the trips are very helpful on the way to mastery. None of the respondents mentioned the material forms of cultural heritage pertaining to martial arts as motives for the trips. Therefore, the ability to visit historic places is a marginal concern. The trips were directly linked to a career path and self-improvement in martial arts, learning or teaching.
STEM Education in Secondary Schools: Teachers’ Perspective towards Sustainable Development
Authors: Nguyen Thi Phuoc Lai , Nguyen Thi Huy , Tran Thanh Khiet
Published: October 2020

Young people are the future of society and agents for social change, and so it is crucial to provide education that not only equips them with knowledge and skills but also changes their attitudes and behavior towards sustainable development. This study provides a review on how pedagogical approaches in science, technology, engineering, and mathematics (STEM) education can be deployed to teach concepts of sustainability. It also shows how secondary school teachers perceived STEM education and how they applied integrated STEM disciplines in designing projects to address development issues in Vietnam. Seventy-seven STEM teaching projects of teachers across the country were analysed, and interviews were conducted with 635 teachers who participated in the STEM program. Teachers valued STEM education and were willing to apply constructivist pedagogical methods to help solve the real-world problems. It is hoped that an integrated STEM approach can transform education into an innovative and inclusive education for social equity and sustainable development.
Integrating Intellectual Property and Sustainable Business Models: The SBM-IP Canvas
Authors: Hernández-Chea Roberto , Vimalnath Pratheeba , Bocken Nancy , Tietze Frank , Eppinger Elisabeth
Published: October 2020

Companies attempt to address global sustainability challenges through innovating products, services, and business models. This paper focuses on sustainable business model (SBM) innovations as a way to systemically transform businesses towards sustainability. It has been widely recognized that strategic approaches to using intellectual property (IP) need to be aligned with business model innovation for commercial success. Here we suggest that IP, aligned with SBMs, can also be used to create not only commercial, but also societal and environmental impact. Knowledge about how to best align IP with SBMs to drive sustainability transitions remains limited. We address this gap by developing an SBM-IP canvas that integrates IP considerations into each of the SBM canvas building blocks. We do this by employing relevant theoretical concepts from three literature streams, namely the business model (including SBM), IP, and innovation literature. We use case examples to illustrate different IP considerations that are relevant for the SBM-IP building blocks. These examples show that different IP types (e.g., patents, trademarks) and ways of using them (e.g., more or less restrictive licensing) are applied by companies in relation to the different building blocks. While covering new theoretical ground, the proposed SBM-IP canvas can help decision makers understand how they can use different IP types strategically to propose, create, deliver, and capture sustainable value for society, environment, and the business.
Physical Fitness Predicts Subsequent Improvement in Academic Achievement: Differential Patterns Depending on Pupils’ Age
Authors: Gouveia Élvio Rúbio , Gouveia Bruna Raquel , Marques Adilson , Lopes Helder , Rodrigues Ana , Peralta Miguel , Kliegel Matthias , Ihle Andreas
Published: October 2020

We investigated the longitudinal relationship between physical fitness (flexibility, functional strength, and running speed-agility components) and subsequent change in academic achievement across one school year. We also examined whether this longitudinal relationship differed as a function of pupils’ age, controlling for sex, body mass index, and socioeconomic status. Academic achievement in terms of marks in Portuguese and mathematics was recorded from 142 pupils (M = 14.59 years; SD = 1.99, range 11–18), between autumn 2017 and summer 2018. The physical fitness components, including flexibility, functional strength, and running speed-agility, were assessed at the baseline (i.e., at the beginning of the school year). Latent change score modelling revealed that higher physical fitness level at baseline significantly predicted a subsequent improvement in academic achievement across the school year. This longitudinal relationship was significantly stronger in younger compared to older pupils. Physical fitness and its interaction with age predicted 45.7% of the variance in the change in academic achievement. In conclusion, a better physical fitness profile including flexibility, functional strength, and running speed-agility explains a subsequent improvement in academic achievement. This longitudinal relationship seems to be age-dependent.
Cost-Minimizing System Design for Surveillance of Large, Inaccessible Agricultural Areas Using Drones of Limited Range
Authors: Vargas Tamayo Luis , Thron Christopher , Fendji Jean Louis Kedieng Ebongue , Thomas Shauna-Kay , Förster Anna
Published: October 2020

Drones are used increasingly for agricultural surveillance. The limited flight range of drones poses a problem for surveillance of large, inaccessible areas. One possible solution is to place autonomous, solar-powered charging stations within the area of interest, where the drone can recharge during its mission. This paper designs and implements a software system for planning low-cost drone coverage of large areas. The software produces a feasible, cost-minimizing charging station placement, as well as a drone path specification. Multiple optimizations are required, which are formulated as integer linear programs. In extensive simulations, the resulting drone paths achieved 70–90 percent of theoretical optimal performance in terms of minimizing mission time for a given number of charging stations, for a variety of field configurations.
Factors Affecting Organizations’ Resistance to the Adoption of Blockchain Technology in Supply Networks
Authors: Choi Daeheon , Chung Chune Young , Seyha Thou , Young Jason
Published: October 2020

From a supply chain perspective, new technologies such as blockchain can improve the efficiency and competitiveness of logistics and increase customer satisfaction. Although blockchain technology has been lauded as a way for firms to build sustainable supply chain networks, the rate of acceptance of this technology remains low. Therefore, this study seeks to identify the factors that discourage firms from merging blockchain with the supply chain. Instead of providing further reasons for adopting blockchain technology, we try to understand what deters firms from adding blockchain to their operations. Following the deductive approach, a confirmatory factor analysis is conducted on pre-test questionnaires to test, improve, and verify the constructs (questions) to measure the hypothesized factors. A theoretical model is proposed based on the hypotheses, and structural equation modeling is applied. The results are estimated using the partial least squares approach and a sample of 83 respondents. Our findings based on our empirical data support most of our hypotheses. We find that various factors impede the adoption of blockchain technologies, including technological barriers, constraints rooted in organizations and the environment, and system-related governmental barriers. In addition, various factors are critical determinants of resistance to blockchain in the technological, organizational, and environmental dimensions.
First Captive Breeding Program for the Endangered Pyrenean Sculpin (Cottus hispaniolensis Bacescu-Master, 1964)
Authors: Manubens Joan , Comas Oriol , Valls Núria , Benejam Lluís
Published: October 2020

The strong decline of freshwater fish species in Europe implies that further ex-situ conservation plans should be implemented in the near future. The present study reflects our experience with the Pyrenean sculpin (Cottus hispaniolensis Bacescu-Mester, 1964)—a small cottid endemic to the Hispano-French Garona River basin. In recent years, the Spanish Pyrenean sculpin population has reached a limit situation. Because of that, the non-profit association ADEFFA—with support from the public administration—started the first captive breeding program for this species in 2006. Fourteen years later, this study presents the results and evaluates the different steps of the program, with the aim of discussing and improving the ex-situ conservation plans for this and other cold freshwater species. There is a description and a comparison between six consecutive phases during the captive breeding process: nesting behaviour, courtship, egg fixation, parental care (incubation), hatching and survival during juvenile development. The purposes of this project are to: (1) identify the most determining phases for a successful captive breeding; (2) identify the factors that had a major influence to the success of the critical phases; and (3) increase the number of the offspring. This study is based on thirty-three wild individuals collected from Garona River (Val d’Aran, Spanish Pyrenees). During the program, twelve couples spawned in captive conditions, with around 2300 eggs laid. Eight couples bred successfully, with 751 hatched individuals and 608 juveniles reared. The analysis of each step of the captive breeding does not reveal significant differences between phases, so it can be concluded that they are all critical at the same level. In the literature, similar study-cases of captive breeding programs identify incubation and survival phases as the most critical. Consequently, the management made for this project has probably allowed to overcome in part the main impediments described in other similar programs.
Investigation of Thermal Effects in Different Lightweight Constructions for Vehicular Wireless Power Transfer Modules
Authors: Zimmer Steve , Helwig Martin , Lucas Peter , Winkler Anja , Modler Niels
Published: October 2020

This paper presents a thermal investigation of lightweight on-board receiver modules of wireless power transfer systems for electric vehicles. The studied modules are capable of receiving up to 11 kW at a resonance frequency of 85 kHz over a distance of 110–160 mm. The receiver modules were built as sandwich and space–frame concept to design stiff and lightweight structures. The high transmission power of automotive wireless power transfer systems combined with the multi-part assembly of receiver modules led to challenges in heat management. To address this, the physical behaviour of the proposed lightweight concepts were studied on component and system level using a hardware-in-the-loop testing facility for wireless power transfer systems. Special emphasis was laid on the validation of a thermal simulation model, which uses analytical calculated power losses taking into account their temperature dependency. The proposed simulation model is consistent with the experimental validation of the critical active components. The performed systematic studies build the basis for a more sophisticated thermal dimensioning of various constructions for wireless power transfer modules.
Distribution of root rot in grain crop rotation depending on the elements of cultivation technology
Authors:   National Grain Center named after P.P. Lukyanenko, Permyakova T.B.
Published: October 2020

Species composition and pathogenicity of winter wheat rot in the grain crop rotation is given. The influence of the main tillage systems and preceding crops on the level of accumulation and spread of the root rots is given. The advantages of traditional cultivation technology are demonstrated.
Evaluation of the effectiveness of the European corn borer monitoring using bisexual lure based on tests results in the Kuban and the Central Black Earth Zone of Russia
Authors:   All-Russian Research Institute of Plant Protection, Frolov A.N. , Grushevaya I.V. ,   All-Russian Research Institute of Plant Protection, Kononchuk A.G. ,   All-Russian Research Institute of Plant Protection, Ryabchinskaya T.A. ,   All-Russian Research Institute for Plant Protection of the Ministry of Agriculture of the Russian Federation, Kolesnikov V.B. ,   All-Russian Research Institute for Plant Protection of the Ministry of Agriculture of the Russian Federation, Miklós Tóth ,   Plant Protection Institute (Budapest, Hungary)
Published: October 2020

During summer 2019, pilot tests were conducted in the Eastern part of the Krasnodar Krai and in the North of the Voronezh Region on two volatile semiochemicals of maize (phenylacetaldehyde and 4-methoxy-2-phenethyl alcohol) to monitor the European corn borer Ostrinia nubilalis number in comparison with sex pheromones. Traps with semiochemical lure caught significantly more pest adults than traps with sex pheromone – in the Voronezh Region by 16.5 times, and in the Krasnodar Krai by 2.4 times. At the same time, about half of the moths attracted by semiochemical lure were females, whose information value for forecasting is significantly higher than that of males. The results obtained indicate that semiochemical lure can be used for monitoring pests, especially in the Northern foci of its harm, where traps with sex pheromones cannot provide reliable monitoring of the insect
The effectiveness of fungicides in vitro against some species of the genus Fusarium Link – pathogens causing core rot of apple
Authors:   North Caucasian Regional Research Institute of Horticulture and Viticulture, Yakuba G.V. , Astapchuk I.L. ,   North Caucasian Regional Research Institute of Horticulture and Viticulture, Nasonov A.I. ,   North Caucasian Regional Research Institute of Horticulture and Viticulture
Published: October 2020

The research aimed to determine in vitro effectiveness of fungicides of chemical origin against some species of the genus Fusarium Link – pathogens causing core rot of apple. The study showed low biological effectiveness of four fungicides against F. sporotrichioides and F. semitectum. The effect, with one exception, did not exceed 50%; some fungicides were ineffective. Species-specific reactions of relative sensitivity to chemical preparations for various in vitro indices were noted. Thus, F. semitectum showed a higher relative sensitivity in terms of the number of colonies; F. sporotrichioides – in the degree of development of aerial mycelium.