bluuebunny/crossref_metadata_2025 huggingface dataset:
An Overview of the Applications of Earth Observation Satellite Data: Impacts and Future Trends
Authors: Zhao Qiang , Yu Le , Du Zhenrong , Peng Dailiang , Hao Pengyu , Zhang Yongguang , Gong Peng
Published: April 2022

As satellite observation technology develops and the number of Earth observation (EO) satellites increases, satellite observations have become essential to developments in the understanding of the Earth and its environment. However, the current impacts to the remote sensing community of different EO satellite data and possible future trends of EO satellite data applications have not been systematically examined. In this paper, we review the impacts of and future trends in the use of EO satellite data based on an analysis of data from 15 EO satellites whose data are widely used. Articles that reference EO satellite missions included in the Web of Science core collection for 2020 were analyzed using scientometric analysis and meta-analysis. We found the following: (1) the number of publications and citations referencing EO satellites is increasing exponentially; however, the number of articles referencing AVHRR, SPOT, and TerraSAR is tending to decrease; (2) papers related to EO satellites are concentrated in a small number of journals: 43.79% of the articles that were reviewed were published in only 13 journals; and (3) remote sensing impact factor (RSIF), a new impact index, was constructed to measure the impacts of EO satellites and to predict future trends in applications of their data. Landsat, Sentinel, MODIS, Gaofen, and WorldView were found to be the most significant current EO satellite missions and MODIS data to have the widest range of applications. Over the next five years (2021–2025), it is expected that Sentinel will become the satellite mission with the greatest influence.
Spatially Stratified and Multi-Stage Approach for National Land Cover Mapping Based on Sentinel-2 Data and Expert Knowledge
Authors: Costa Hugo , Benevides Pedro , Moreira Francisco D. , Moraes Daniel , Caetano Mário
Published: April 2022

Portugal is building a land cover monitoring system to deliver land cover products annually for its mainland territory. This paper presents the methodology developed to produce a prototype relative to 2018 as the first land cover map of the future annual map series (COSsim). A total of thirteen land cover classes are represented, including the most important tree species in Portugal. The mapping approach developed includes two levels of spatial stratification based on landscape dynamics. Strata are analysed independently at the higher level, while nested sublevels can share data and procedures. Multiple stages of analysis are implemented in which subsequent stages improve the outputs of precedent stages. The goal is to adjust mapping to the local landscape and tackle specific problems or divide complex mapping tasks in several parts. Supervised classification of Sentinel-2 time series and post-classification analysis with expert knowledge were performed throughout four stages. The overall accuracy of the map is estimated at 81.3% (±2.1) at the 95% confidence level. Higher thematic accuracy was achieved in southern Portugal, and expert knowledge significantly improved the quality of the map.
Multi-Sensor Analysis of Snow Seasonality and a Preliminary Assessment of SAR Backscatter Sensitivity to Arctic Vegetation: Limits and Capabilities
Authors: Stendardi Laura , Karlsen Stein Rune , Malnes Eirik , Nilsen Lennart , Tømmervik Hans , Cooper Elisabeth J. , Notarnicola Claudia
Published: April 2022

Snow melt timing and the last day of snow cover have a significant impact on vegetation phenology in the Svalbard archipelago. The aim of this study is to assess the seasonal variations of the snow using a multi-sensor approach and to analyze the sensitivity of the Synthetic Aperture Radar (SAR) backscatter to vegetation growth and soil moisture in an arctic environment. A combined approach using time series data from active remote sensing sensors such as SAR and passive optical sensors is a known technique in snow monitoring, while there is little knowledge of the radar C-band’s response pattern to vegetation dynamics in the arctic. First, we created multi-sensor masks using the HV backscatter coefficients from Sentinel-1 and the Normalized Difference Snow Index (NDSI) time series from Sentinel-2, monitoring the snow dynamics in Adventdalen (Svalbard) for the season from 2017 to 2018. Second, radar sensitivity analysis was performed using the HV polarized channel responses to vegetation growth and soil moisture dynamics. (1) Our results showed that the C-band radar data are capable of monitoring the seasonal variability in timing of snow melting in Adventdalen, revealing an earlier start by approximately 20 days in 2018 compared to 2017. (2) From the sensitivity analyses, the HV channel showed a major response to the vegetation component in areas with drier graminoid dominated vegetation without water-saturated soil (R = 0.69). However, the temperature was strongly correlated with the HV channel (R = 0.74) during the years with delayed snow melting. Areas of frozen tundra with drier vegetation dominated by graminoids had delayed soil thawing processes and therefore this may limit the ability of the radar to follow the vegetation growth pattern and soil moisture.
Soybean EOS Spatiotemporal Characteristics and Their Climate Drivers in Global Major Regions
Authors: Lou Zihang , Peng Dailiang , Zhang Xiaoyang , Yu Le , Wang Fumin , Pan Yuhao , Zheng Shijun , Hu Jinkang , Yang Songlin , Chen Yue , Liu Shengwei
Published: April 2022

Currently, analyses related the status of soybeans, a major oil crop, as well as the related climate drivers, are based on on-site data and are generally focused on a particular country or region. This study used remote sensing, meteorological, and statistical data products to analyze spatiotemporal variations at the end of the growing season (EOS) for soybeans in the world’s major soybean-growing areas. The ridge regression estimation model calculates the average annual temperature, precipitation, and total radiation contributions to phenological changes. A systematic analysis of the spatiotemporal changes in the EOS and the associated climate drivers since the beginning of the 21st century shows the following: (1) in India, soybean EOS is later than in China and the United States. The main soybean-growing areas in the southern hemisphere are concentrated in South America, where two crops are planted yearly. (2) In most of the world’s soybean-growing regions, the rate change of the EOS is ±2 days/year. In the Mississippi River Valley, India, and South America (the first quarter), the soybean EOS is generally occurring earlier, whereas, in northeast China, it is generally occurring later. (3) The relative contributions of different meteorological factors to the soybean EOS vary between soybean-growing areas; there are also differences within the individual areas. This study provides a solid foundation for understanding the spatiotemporal changes in soybean crops in the world’s major soybean-growing areas and spatiotemporal variations in the effects of climate change on soybean EOS.
Relationship between the Intraseasonal Oscillation over Mid-High-Latitude Eurasia and the Stratospheric Sudden Warming Event in February 2018
Authors: Fan Linjie , Yang Shuangyan , Hu Jinggao , Li Tim
Published: April 2022

Taking the stratospheric sudden warming (SSW) event in February 2018 as an example, the relationship between the SSW event and the intraseasonal oscillation (ISO) mode over mid-high-latitude Eurasia is investigated by daily reanalysis data. First, the 2018 SSW event and mid-high-latitude ISO are reviewed. The 2018 SSW event is a typical vortex-split event defined by the NCEP-DOE dataset, and the ISO mode features a southeastward propagation. Along with the ISO propagation, temperature anomalies developed from troposphere to stratosphere in the 2018 wintertime. It is also found that a strong ISO event occurred before the onset of SSW in this wintertime. Our analysis reveals that the correlation is significant when mid-high-latitude ISO leads the 2018 SSW event by 9–13 days. Occurrence of strong ISO 9–13 days before the SSW event is found to be conducive to its onset. The diagnosis of planetary wave activity indicates that stronger ISO leads to strengthened wavenumber-2 geopotential height anomalies; then, its in-phase superposition of climatological geopotential height makes up for the upward-propagating tropospheric planetary waves, which is in favor of the onset of the 2018 SSW event. The outcome of energy conversion equations also reveals that ISO perturbation contributes to the onset of SSW. Lastly, the contribution of the vertical component of Plumb wave activity flux propagated upward from the region of mid-high-latitude ISO is estimated at approximately 69%.
High-Resolution Mapping of Paddy Rice Extent and Growth Stages across Peninsular Malaysia Using a Fusion of Sentinel-1 and 2 Time Series Data in Google Earth Engine
Authors: Fatchurrachman  , Rudiyanto  , Soh Norhidayah Che , Shah Ramisah Mohd , Giap Sunny Goh Eng , Setiawan Budi Indra , Minasny Budiman
Published: April 2022

Rice is the staple crop for more than half the world’s population, but there is a lack of high-resolution maps outlining rice areas and their growth stages. Most remote sensing studies map the rice extent; however, in tropical regions, rice is grown throughout the year with variable planting dates and cropping frequency. Thus, mapping rice growth stages is more useful than mapping only the extent. This study addressed this challenge by developing a phenology-based method. The hypothesis was that the unsupervised classification (k-means clustering) of Sentinel-1 and 2 time-series data could identify rice fields and growth stages, because (1) the presence of flooding during transplanting can be identified by Sentinel-1 VH backscatter; and (2) changes in the canopy of rice fields during growth stages (vegetative, generative, and ripening phases) up to the point of harvesting can be identified by Normalized Difference Vegetation Index (NDVI) time series. Using the proposed method, this study mapped rice field extent and cropping calendars across Peninsular Malaysia (131,598 km2) on the Google Earth Engine (GEE) platform. The Sentinel-1 and 2 monthly time series data from January 2019 to December 2020 were classified using k-means clustering to identify areas with similar phenological patterns. This approach resulted in 10-meter resolution maps of rice field extent, intensity, and cropping calendars. Validation using very high-resolution street view images from Google Earth showed that the predicted map had an overall accuracy of 95.95%, with a kappa coefficient of 0.92. In addition, the predicted crop calendars agreed well with the local government’s granary data. The results show that the proposed phenology-based method is cost-effective and can accurately map rice fields and growth stages over large areas. The information will be helpful in measuring the achievement of self-sufficiency in rice production and estimates of methane emissions from rice cultivation.
Open Source IIoT Solution for Gas Waste Monitoring in Smart Factory
Authors: Waters Mark , Waszczuk Pawel , Ayre Rodney , Dreze Alain , McGlinchey Don , Alkali Babakalli , Morison Gordon
Published: April 2022

Rapid development of smart manufacturing techniques in recent years is influencing production facilities. Factories must both keep up with smart technologies as well as upskill their workforce to remain competitive. One of the recent concerns is how businesses can contribute to environmental sustainability and how to reduce operating costs. In this article authors present a method of measuring gas waste using Industrial Internet of Things (IIoT) sensors and open-source solutions utilised on a brownfield production asset. The article provides a result of an applied research initiative in a live manufacturing facility. The design followed the Reference Architectural Model for Industry 4.0 (RAMI 4.0) model to provide a coherent smart factory system. The presented solution’s goal is to provide factory supervisors with information about gas waste which is generated during the production process. To achieve this an operational technology (OT) network was installed and Key Performance Indicators (KPIs) dashboards were designed. Based on the information provided by the system, the business can be more aware of the production environment and can improve its efficiency.
Color Demosaicing of RGBW Color Filter Array Based on Laplacian Pyramid
Authors: Jeong Kyeonghoon , Kim Jonghyun , Kang Moon Gi
Published: April 2022

In recent years, red, green, blue, and white (RGBW) color filter arrays (CFAs) have been developed to solve the problem of low-light conditions. In this paper, we propose a new color demosaicing algorithm for RGBW CFAs using a Laplacian pyramid. Because the white channel has a high correlation to the red, green, and blue channels, the white channel is interpolated first using each color difference channel. After we estimate the white channel, the red, green, and blue channels are interpolated using the Laplacian pyramid decomposition of the estimated white channel. Our proposed method using Laplacian pyramid restoration works with Canon-RGBW CFAs and any other periodic CFAs. The experimental results demonstrated that the proposed method shows superior performance compared with other conventional methods in terms of the color peak signal-to-noise ratio, structural similarity index measure, and average execution time.
NIKE BLUETRACK: Blue Force Tracking in GNSS-Denied Environments Based on the Fusion of UWB, IMUs and 3D Models
Authors: Mascher Karin , Watzko Markus , Koppert Axel , Eder Julian , Hofer Peter , Wieser Manfred
Published: April 2022

Blue force tracking represents an essential task in the field of military applications. A blue force tracking system provides the location information of their own forces on a map to commanders. For the command post, this results in more efficient operation control with increasing safety. In underground structures (e.g., tunnels or subways), the localisation is challenging due to the lack of GNSS signals. This paper presents a localisation system for military or emergency forces tailored to usage in complex underground structures. In a particle filter, position changes from a dual foot-mounted INS are fused with opportunistic UWB ranges and data from a 3D tunnel model to derive position information. A concept to deal with the absence of UWB infrastructure or 3D tunnel models is illustrated. Recurrent neural network methodologies are applied to cope with different motion types of the operators. The evaluation of the positioning algorithm took place in a street tunnel. If a fully installed infrastructure was available, positioning errors under one metre were reached. The results also showed that the INS can bridge UWB outages. A particle-filter-based approach to UWB anchor mapping is presented, and the first simulation results showed its viability.
Analysis of Privacy-Enhancing Technologies in Open-Source Federated Learning Frameworks for Driver Activity Recognition
Authors: Novikova Evgenia , Fomichov Dmitry , Kholod Ivan , Filippov Evgeny
Published: April 2022

Wearable devices and smartphones that are used to monitor the activity and the state of the driver collect a lot of sensitive data such as audio, video, location and even health data. The analysis and processing of such data require observing the strict legal requirements for personal data security and privacy. The federated learning (FL) computation paradigm has been proposed as a privacy-preserving computational model that allows securing the privacy of the data owner. However, it still has no formal proof of privacy guarantees, and recent research showed that the attacks targeted both the model integrity and privacy of the data owners could be performed at all stages of the FL process. This paper focuses on the analysis of the privacy-preserving techniques adopted for FL and presents a comparative review and analysis of their implementations in the open-source FL frameworks. The authors evaluated their impact on the overall training process in terms of global model accuracy, training time and network traffic generated during the training process in order to assess their applicability to driver’s state and behaviour monitoring. As the usage scenario, the authors considered the case of the driver’s activity monitoring using the data from smartphone sensors. The experiments showed that the current implementation of the privacy-preserving techniques in open-source FL frameworks limits the practical application of FL to cross-silo settings.
An SHA-3 Hardware Architecture against Failures Based on Hamming Codes and Triple Modular Redundancy
Authors: Torres-Alvarado Alan , Morales-Rosales Luis Alberto , Algredo-Badillo Ignacio , López-Huerta Francisco , Lobato-Báez Mariana , López-Pimentel Juan Carlos
Published: April 2022

Cryptography has become one of the vital disciplines for information technology such as IoT (Internet Of Things), IIoT (Industrial Internet Of Things), I4.0 (Industry 4.0), and automotive applications. Some fundamental characteristics required for these applications are confidentiality, authentication, integrity, and nonrepudiation, which can be achieved using hash functions. A cryptographic hash function that provides a higher level of security is SHA-3. However, in real and modern applications, hardware implementations based on FPGA for hash functions are prone to errors due to noise and radiation since a change in the state of a bit can trigger a completely different hash output than the expected one, due to the avalanche effect or diffusion, meaning that modifying a single bit changes most of the desired bits of the hash; thus, it is vital to detect and correct any error during the algorithm execution. Current hardware solutions mainly seek to detect errors but not correct them (e.g., using parity checking or scrambling). To the best of our knowledge, there are no solutions that detect and correct errors for SHA-3 hardware implementations. This article presents the design and a comparative analysis of four FPGA architectures: two without fault tolerance and two with fault tolerance, which employ Hamming Codes to detect and correct faults for SHA-3 using an Encoder and a Decoder at the step-mapping functions level. Results show that the two hardware architectures with fault tolerance can detect up to a maximum of 120 and 240 errors, respectively, for every run of KECCAK-p, which is considered the worst case. Additionally, the paper provides a comparative analysis of these architectures with other works in the literature in terms of experimental results such as frequency, resources, throughput, and efficiency.
The Middleware for an Exoskeleton Assisting Upper Limb Movement
Authors: Strzelczyk Przemyslaw , Tomczewski Krzysztof , Wrobel Krzysztof
Published: April 2022

This article presents the possibilities of newly developed middleware dedicated for distributed and modular control systems. The software enables the exchange of information locally, within one control module, and globally, between many modules. The executed information exchange system speed tests confirmed the correct operation of the software. The middleware was used in the control system of the active upper-limb exoskeleton. The upper-limb rehabilitation exoskeleton structure with six degrees of mechanical freedom is presented. The tests were performed using the prototype with three joints. The drives’ models of individual joints were developed and simulated. As a result, the courses of the motion trajectory were shown for different kinds of pressure on the force sensors, and different methods of signal filtering. The tests confirmed a correct operation of middleware and drives control system.
Fine-Tuned DenseNet-169 for Breast Cancer Metastasis Prediction Using FastAI and 1-Cycle Policy
Authors: Vulli Adarsh , Srinivasu Parvathaneni Naga , Sashank Madipally Sai Krishna , Shafi Jana , Choi Jaeyoung , Ijaz Muhammad Fazal
Published: April 2022

Lymph node metastasis in breast cancer may be accurately predicted using a DenseNet-169 model. However, the current system for identifying metastases in a lymph node is manual and tedious. A pathologist well-versed with the process of detection and characterization of lymph nodes goes through hours investigating histological slides. Furthermore, because of the massive size of most whole-slide images (WSI), it is wise to divide a slide into batches of small image patches and apply methods independently on each patch. The present work introduces a novel method for the automated diagnosis and detection of metastases from whole slide images using the Fast AI framework and the 1-cycle policy. Additionally, it compares this new approach to previous methods. The proposed model has surpassed other state-of-art methods with more than 97.4% accuracy. In addition, a mobile application is developed for prompt and quick response. It collects user information and models to diagnose metastases present in the early stages of cancer. These results indicate that the suggested model may assist general practitioners in accurately analyzing breast cancer situations, hence preventing future complications and mortality. With digital image processing, histopathologic interpretation and diagnostic accuracy have improved considerably.
Using Robot-Based Variables during Upper Limb Robot-Assisted Training in Subacute Stroke Patients to Quantify Treatment Dose
Authors: Jamin Pascal , Duret Christophe , Hutin Emilie , Bayle Nicolas , Koeppel Typhaine , Gracies Jean-Michel , Pila Ophélie
Published: April 2022

In post-stroke motor rehabilitation, treatment dose description is estimated approximately. The aim of this retrospective study was to quantify the treatment dose using robot-measured variables during robot-assisted training in patients with subacute stroke. Thirty-six patients performed fifteen 60 min sessions (Session 1–Session 15) of planar, target-directed movements in addition to occupational therapy over 4 (SD 2) weeks. Fugl–Meyer Assessment (FMA) was carried out pre- and post-treatment. The actual time practiced (percentage of a 60 min session), the number of repeated movements, and the total distance traveled were analyzed across sessions for each training modality: assist as needed, unassisted, and against resistance. The FMA score improved post-treatment by 11 (10) points (Session 1 vs. Session 15, p < 0.001). In Session 6, all modalities pooled, the number of repeated movements increased by 129 (252) (vs. Session 1, p = 0.043), the total distance traveled increased by 1743 (3345) cm (vs. Session 1, p = 0.045), and the actual time practiced remained unchanged. In Session 15, the actual time practiced showed changes only in the assist-as-needed modality: −13 (23) % (vs. Session 1, p = 0.013). This description of changes in quantitative-practice-related variables when using different robotic training modalities provides comprehensive information related to the treatment dose in rehabilitation. The treatment dose intensity may be enhanced by increasing both the number of movements and the motor difficulty of performing each movement.
A Survey on Artificial Intelligence Aided Internet-of-Things Technologies in Emerging Smart Libraries
Authors: Bi Siguo , Wang Cong , Zhang Jilong , Huang Wutao , Wu Bochun , Gong Yi , Ni Wei
Published: April 2022

With the boom in artificial intelligence (AI) and Internet-of-Things (IoT), thousands of smart devices are interconnected with each other and deeply applied into human society. This prosperity has significantly improved public service and management, which were traditionally based on manual work. As a notable scenario, librarianship has embraced an era of “Smart Libraries” enabled by AI and IoT. Unlike existing surveys, our work comprehensively overviews the AI- and IoT-based technologies in three fundamental aspects: smart service, smart sustainability, and smart security. We then further highlight the trend towards future smart libraries.
An Effective Approach for Controller Placement in Software-Defined Internet-of-Things (SD-IoT)
Authors: Ali Jehad , Roh Byeong-hee
Published: April 2022

The Software-Defined Networking (SDN) paradigm has transferred network intelligence from network devices to a centralized controller. Controllers are distributed in a network to eliminate a single point of failure (SPOF) and improve reliability and balance load. In Software-Defined Internet of Things (SD-IoT), sensors exchange data with a controller on a regular basis. If the controllers are not appropriately located in SD-IoT, the E2E latency between the switches, to which the sensors are connected, and the controller increases. However, examining the placement of controllers in relation to the whole network is not an efficient technique since applying the objective function to the entire network is a difficult operation. As a result, segmenting the network into clusters improves the efficiency with which switches are assigned to the controller. As a result, in this research, we offer an effective clustering strategy for controller placement in SDN that leverages the Analytical Network Process (ANP), a multi-criteria decision-making (MCDM) scheme. The simulation results demonstrated on real Internet topologies suggest that our proposed method outperforms the standard k-means approach in terms of E2E delay, controller-to-controller (C2C) delay, the fair allocation of switches in the network, and the communication overhead.
Fast Adaptation of Manipulator Trajectories to Task Perturbation by Differentiating through the Optimal Solution
Authors: Srikanth Shashank , Babu Mithun , Masnavi Houman , Kumar Singh Arun , Kruusamäe Karl , Krishna Krishnan Madhava
Published: April 2022

Joint space trajectory optimization under end-effector task constraints leads to a challenging non-convex problem. Thus, a real-time adaptation of prior computed trajectories to perturbation in task constraints often becomes intractable. Existing works use the so-called warm-starting of trajectory optimization to improve computational performance. We present a fundamentally different approach that relies on deriving analytical gradients of the optimal solution with respect to the task constraint parameters. This gradient map characterizes the direction in which the prior computed joint trajectories need to be deformed to comply with the new task constraints. Subsequently, we develop an iterative line-search algorithm for computing the scale of deformation. Our algorithm provides near real-time adaptation of joint trajectories for a diverse class of task perturbations, such as (i) changes in initial and final joint configurations of end-effector orientation-constrained trajectories and (ii) changes in end-effector goal or way-points under end-effector orientation constraints. We relate each of these examples to real-world applications ranging from learning from demonstration to obstacle avoidance. We also show that our algorithm produces trajectories with quality similar to what one would obtain by solving the trajectory optimization from scratch with warm-start initialization. Most importantly, however, our algorithm achieves a worst-case speed-up of 160x over the latter approach.
Innovative Practice of Sustainable Landscape Architecture Education—Parametric-Aided Design and Application
Authors: Hsu Che-Yu , Ou Sheng-Jung
Published: April 2022

The traditional teaching model of landscape architecture education is teacher-centered classroom lectures, which cannot effectively satisfy students’ curiosity and stimulate their creative thinking and computational thinking skills, resulting in students’ low willingness to learn, inattentiveness, and lack of participation in discussions and interactions. This study attempts to combine the BOPPPS teaching structure and Design-Based Learning model to innovate the teaching design, construct the knowledge chain of landscape architecture design modeling and inspire the logic of thinking, with visual programming language, virtual reality parametric modeling and 3D printing hands-on activities while integrating sustainable development goals and related thematic issues to develop practical skills and problem-solving abilities. Through collecting students’ learning performance, examining the quality and effectiveness of teaching and learning, reflecting on the revised teaching content and methods and establishing a practical teaching plan for sustainable landscape architecture education. The results of the study show that the combination of innovative teaching and learning models with SDG-related thematic issues and collaborative group discussions with teaching activities helps to enhance students’ learning effectiveness and bring the learning performances of different learners closer together. In addition, the analysis of learning satisfaction shows that it enhances students’ interest and motivation in learning.
Impact of Assistive Technologies to Inclusive Education and Independent Life of Down Syndrome Persons: A Systematic Literature Review and Research Agenda
Authors: Krasniqi Venera , Zdravkova Katerina , Dalipi Fisnik
Published: April 2022

Since the beginning of the 21st century, the lifespan of people born with Down syndrome (DS) has increased. They now outlive their parents and rely on their relatives who usually sacrifice their own families to care for their disabled siblings. To reduce the pressure on families and the wider community, it is crucial to prepare DS people for independent life from early childhood. Emerging technologies can significantly support the process of acquiring the skills that are necessary for solving real-life problems at home and work. To assess their impact and estimate how much they are implemented in inclusive education, a review of 564 papers published after 2015 was done using the PRISMA review model. After gradual exclusion, 24 papers were used for the final review. Thematic analysis resulted in four themes with one common concept: variety. The results of examining the four research questions defined in the paper’s background confirm that the synergy of emerging assistive technologies and inclusive education has the potential of becoming a very effective strategy for creating an independent life for DS individuals. Many questions remain open, mainly related to a DS persons’ specific needs and capabilities. The acceptance of the proposed synergy will depend on them.
The Importance of Community Perspectives on Hotel Community-Related CSR: A Position Paper
Authors: Kasim Azilah , Khuadthong Bussalin , Jailani Noormala , Mokhtar Muhammad , Radha Jasmine , Leong Maebel
Published: April 2022

The purpose of this position paper is to present an opinion on the importance of understanding host community perspectives in any community-based corporate social responsibility initiative. A host community is essentially the consumer of any community-based CSR, yet they each have unique cultures, features, needs, and expectations, which may or may not fit a business’s CSR initiative, unless the community perspectives are accounted for prior to the implementation of the CSR project. Focusing on the hotel sector context, the paper develops its position by reviewing supporting literature and highlighting the outcomes of a qualitative case study that involved face-to face semistructured interviews with 15 local opinion leaders who represented several local communities. The paper concludes with a firmer opinion on its position, and it offers some of the implications of its findings.
Integrating Environmental and Economic Perspectives in Building Design
Authors: Schneider-Marin Patricia , Winkelkotte Anne , Lang Werner
Published: April 2022

With increasing environmental damage and decreasing resource availability, sustainability assessment in the building sector is gaining momentum. A literature review shows that the related methods for environmental and economic performance, Life Cycle Assessment (LCA) and Life Cycle Costing (LCC), show great potential for answering a multitude of questions related to building performance. Prevalent topics are the implications of LCA and LCC for retrofit solutions and the trade-offs between environmental and economic considerations in building design. A detailed review of 30 case studies shows the range of differing result integration methods and sheds light on the use of monetary valuation of environmental indicators for an integrated assessment. While a quasi-dynamic approach, accounting for the changing value of money over time, is common in LCC, such an approach is largely absent from LCA. The analysis of common metrics shows that the studies employ strongly differing system boundaries and input parameters. Moreover, a clear description of the methodological framework is missing in most studies. Therefore, this research develops an “Eco2” framework, integrating LCA and LCC for application in building design. Potential further developments for Eco2 building assessment are related to extending the system boundaries by including mechanical systems and end-of-life phases, data collection and structuring, and streamlining the approach for continuous application to all stages of building design processes. Additionally, the influence on design decisions of employing temporal parameters in both LCA and LCC and of choosing particular result integration methods should be investigated further.
Enhancing Employee Creativity in the Banking Sector: A Transformational Leadership Framework
Authors: Fu Qinghua , Cherian Jacob , Rehman Khalil-ur , Samad Sarminah , Khan Mohammed Arshad , Athar Ali Mohammad , Cismas Laura Mariana , Miculescu Andra
Published: April 2022

Despite the growing academic interest in transformational leadership and employee creativity, the banking sector has not yet received enough consideration. Mostly, the banking sector was assumed to be an inappropriate setting for employee creativity as it is a tightly supervised and controlled segment of an economy. Nevertheless, some research studies in advanced nations emphasized the significance of employee creativity in a banking context. However, the case of developing countries (e.g., Pakistan) has remained an understudied area. Against this background, the objective of this study was to examine the relationships between transformational leadership (TL), perceived organizational support (POS), and employee creativity (EC) through work engagement (WE). Some private banks were selected, situated in a large metropolitan city, with data collected for the present research by a self-administered questionnaire. The structural equation modeling (SEM) technique was employed to analyze data. It was observed that TL and POS induce EC, whereas WE mediated these relationships. These findings may help policymakers of the banking industry to improve employee creativity through WE.
Research Status and Trends of Underwater Photosynthesis
Authors: Guo Jinbo , Xue Jianhui , Hua Jianfeng , Xuan Lei , Yin Yunlong
Published: April 2022

Underwater photosynthesis is the most important metabolic activity for submerged plants since it could utilize carbon fixation to replenish lost carbohydrates and improve internal aeration by producing O2. The present study used bibliometric methods to quantify the annual number of publications related to underwater photosynthesis. CiteSpace, as a visual analytic software for the literature, was employed to analyze the distribution of the subject categories, author collaborations, institution collaborations, international (regional) collaborations, and cocitation and keyword burst. The results show the basic characteristics of the literature, the main intellectual base, and the main research powers of underwater photosynthesis. Meanwhile, this paper revealed the research hotspots and trends of this field. This study provides an objective and comprehensive analysis of underwater photosynthesis from a bibliometric perspective. It is expected to provide reference information for scholars in related fields to refine the research direction, solve specific scientific problems, and assist scholars in seeking/establishing relevant collaborations in their areas of interest.
Long-Term Fertilizer Reduction in Greenhouse Tomato-Cucumber Rotation System to Assess N Utilization, Leaching, and Cost Efficiency
Authors: Geng Yucong , Bashir Muhammad Amjad , Zhao Ying , Luo Jianhang , Liu Xiaotong , Li Feng , Wang Hongyuan , Raza Qurat-Ul-Ain , Rehim Abdur , Zhang Xuejun , Liu Hongbin
Published: April 2022

Technology-oriented approaches to reduce chemical fertilization in agroecosystems without influencing the vegetable yield is a proficient method for sustainable agriculture and environmental safety. However, short-term studies are not capable to indicate the effects of various inputs in a long run; therefore, a six-year experiment was conducted in Ningxia, China. The experimental units were: no fertilizer control (CK: 0 kg N ha−1), chicken manure (M: organic N 362 kg ha−1), reduced chemical fertilizer (RCF: chemical N 992 kg ha−1 + organic N 362 kg ha−1), and conventional fertilizer (CF: chemical N 1515 kg ha−1 + organic N 362 kg ha−1). The study aimed to assess the effects of reduced fertilization on yield, nitrogen (N) use efficiency (NUE), N leaching, and the economic benefits. The results achieved herein indicate that RCF has significantly improved the NUE, reduced N leaching (23.7%), and improved the N economic benefit (NEB, 41.8%) as compared to the CF. Based on yield, net benefit, and NUE conditions, the optimum N application range was 634–821 kg N ha−1 for tomato and 556–778 kg N ha−1 for cucumber. The study concluded that reduced chemical application of N is an important factor to control environmental pollution and improve fertilizer use efficiency. Further experiments are suggested to examine the optimum N rate provision from chemical fertilizer and its ratio with organic fertilization.
Research on the Impact of Digital Innovation Driving the High-Quality Development of the Shipping Industry
Authors: Jian Lingxiang , Guo Jia , Ma Hui
Published: April 2022

Based on the evaluation index system of high-quality development of the shipping industry and digital innovation, this paper uses the “VHSD-EM” model to evaluate the high-quality development of the shipping industry and digital innovation in 11 coastal provinces of China from 2010 to 2019 and the fixed effect model to study the impact of digital innovation on the high-quality development of the shipping industry. The results show the following: (1) Both the index of the high-quality development of the shipping industry and the index of digital innovation generally show a slow growth trend, but there are obvious differences in regional development, among which the Yangtze River Delta and Pearl River Delta have prominent advantages; (2) Digital innovation plays a significant role in promoting high-quality development of the shipping industry. When the index of digital innovation increases by 1 unit, the index of the high-quality development of the shipping industry increases by 1.233 units on average. However, the potential of digital innovation driving the high-quality development of the shipping industry has not been fully utilized; (3) Investment in education and technology and other transportation industries have an important impact on the high-quality development of the shipping industry. It is necessary to increase the investment in education and science, improve the level of shipping technology, and exert the function of transportation to form a complete traffic and transport network. In general, the paper verifies the role of digital innovation in promoting the high-quality development of the shipping industry, as well as the impact of related factors on the high-quality development of the shipping industry, putting forward targeted suggestions for promoting the high-quality development of the shipping industry.
Mainstreaming the Gender: Measuring the Job Attributes and Gender Differences across Selected EU Member States
Authors: Mihálik Jaroslav , Matejková Alexandra
Published: April 2022

In our research article, we expect that the job attitudes of men and women should converge, and their declared different preferences for job attributes should decrease. We also expect that the preference for job attributes aimed at comfortable working conditions should be closer between men and women due to the growing balance of men’s and women’s role distribution within the household. Therefore, the main goal of the research, using quantitative research methods and using data from the European Values Study (EVS), is to identify the gender differences, if any, in the preferences for external and internal job attributes across selected EU member states. In particular, we focus on the importance of work for men and women; gender differences in job attributes; the preference for external and internal job attributes; the inclination of gender stereotypes and attitudes toward gender roles division; and the comparison of gender equality and job attribute preference in the selected EU countries. Our conclusions confirmed parallels between gender stereotypes and equality among the Western, Eastern, and Southern EU member states.
Effects of Railway Market Liberalisation: European Union Perspective
Authors: Solina Kristijan , Abramović Borna
Published: April 2022

Network activities are an essential part of the economy. They represent services of general economic interest and include electronic communication, electricity, postal and railway services. At the end of the 1980s, the European Commission brought forward legislative proposals to open the monopolistic service markets of general economic interest. In that way, states would prepare the legislation to liberalise services, and state-owned monopolistic enterprises would adapt to the new conditions in the market. State-owned railway companies were megalomanic, exerting a triple role of managing the railway infrastructure and service facilities and providing railway transport services. In the early 1990s, the European Union (EU) adopted new legislation that would open the railway freight transport market. This initiated a new era of the railway. Separation of the functions within state own monopolistic companies into infrastructure management and railway undertakings quickly became a reality, paving the way for new railway freight operators. EU directives are implemented differently throughout the EU, which leads to various solutions. We have analysed various scientific and professional sources to understand better different correlations between the traffic parameters of the railway freight transport market. The key parameters were: (1) number of new undertakings, (2) ton-kilometres, (3) infrastructure charges and (4) quantity of transported goods. This paper researches the current state of the railway freight transport market and aims to define the shortcomings in the analyses of the impact of railway liberalisation on freight transport. Our research pointed out the need for seeing a broader picture of state interventions and infrastructure manager independence in the context of preventing market marginalisation. In addition, we have concluded that a number of the new undertakings is not a crucial parameter for understanding the railway freight transport market.
Building and Sustaining a Group of Chinese EFL Learners’ Imagined Identities and Agency
Authors: Xu Guanglin , Kim Jungyin
Published: April 2022

This study explores the imagined identities of three EFL undergraduates at a local public university in China, and how these identities relate to their commitment to language learning. Data were gathered through classroom observations, interviews, course documents, and student artefacts for two academic semesters. The data showed that the students’ imagined identities with regards to their professional development, academic pursuits, and corresponding social roles developed throughout their language learning trajectories. In turn, their imagined professional and social identities informed their current EFL learning agency in terms of their initiative to learn English at the university. The findings suggest that a focused imagined identity assists students in building self-discipline and choosing appropriate learning skills. As the current study presents a limited group of students that may not fully represent EFL students’ imagined identities in China, a longitudinal study may further reveal other factors that could contribute to this topic in the future. Although the construction and development of one’s imagined identity are complex and dynamic, the data show that the earlier one sets a clear professional or academic imagined identity, the more motivated a student is to learn the target language.
The Impact of Perceived Support and Barriers on the Sustainable Orientation of Turkish Startups
Authors: Eroglu Yasemin , Rashid Lubna
Published: April 2022

Sustainable entrepreneurship is a critical component of the solutions to the global challenges of our time. Yet to stimulate sustainable entrepreneurship orientation (SEO), creating supportive environmental conditions is key. While the impact of various external conditions on entrepreneurship orientation is highly studied, the impact of such factors on sustainable orientation of startup founders is not yet well-researched, particularly outside of the western hemisphere. This quantitative study sheds light on the impact of perceived support and barriers on SEO in Turkey, drawing on the theory of planned behavior, extending entrepreneurship literature, and providing novel insights to practitioners. Findings of linear regression analysis reveal that perceived support has a significant and positive impact on SEO, while barriers are found to not have an effect. Those results may indicate that founders are able to circumvent perceived barriers when enough support is received, promoting their ability to behave sustainably despite contextual challenges. Young founder age is also found to positively and significantly influence sustainable orientation. Implications of those results are discussed with researchers and practitioners in mind.
Innovation and Strategic Management for the Development of Tourist Destinations: Development of Nightlife and Residents’ Attitudes in Punta del Este (Uruguay)
Authors: Ramón-Cardona José , Sánchez-Fernández María Dolores
Published: April 2022

Nightlife is a controversial offer for its possible negative social impacts, but it is also important for its media impact and as an element of differentiation of the tourist destination. In the coastal resorts it is a very important offer as it complements the main offer. This paper seeks to determine the background of residents’ attitudes towards the offer of nightlife. To do this, the responses of a sample of 420 residents of the Maldonado-Punta del Este conurbation (Uruguay) who responded to a questionnaire with items measured with Likert scales are analyzed using Structural Equation Models. A first analysis, which presents costs and benefits of three types (economic, social and cultural) as a possible background of the degree of acceptance of this offer, did not detect significant relationships. In a second analysis, the mediation of the overall attitude towards tourism and the degree of acceptance of sun and beach tourism were proposed. In this second analysis it was found that: only economic benefits and cultural costs have significant effects on the overall attitude; the overall attitude has a significant effect on the acceptance of sun and beach tourism, but not on the acceptance of nightlife; and the acceptance of sun and beach tourism has a significant effect on the acceptance of nightlife. The acceptance of nightlife follows the same guidelines as its business development (it is a consequence of sun and beach tourism).