bluuebunny/crossref_metadata_2025 huggingface dataset:
Water Body Extraction in Remote Sensing Imagery Using Domain Adaptation-Based Network Embedding Selective Self-Attention and Multi-Scale Feature Fusion
Authors: Liu Jiahang , Wang Yue
Published: July 2022

A water body is a common object in remote sensing images and high-quality water body extraction is important for some further applications. With the development of deep learning (DL) in recent years, semantic segmentation technology based on deep convolution neural network (DCNN) brings a new way for automatic and high-quality body extraction from remote sensing images. Although several methods have been proposed, there exist two major problems in water body extraction, especially for high resolution remote sensing images. One is that it is difficult to effectively detect both large and small water bodies simultaneously and accurately predict the edge position of water bodies with DCNN-based methods, and the other is that DL methods need a large number of labeled samples which are often insufficient in practical application. In this paper, a novel SFnet-DA network based on the domain adaptation (DA) embedding selective self-attention (SSA) mechanism and multi-scale feature fusion (MFF) module is proposed to deal with these problems. Specially, the SSA mechanism is used to increase or decrease the space detail and semantic information, respectively, in the bottom-up branches of the network by selective feature enhancement, thus it can improve the detection capability of water bodies with drastic scale change and can prevent the prediction from being affected by other factors, such as roads and green algae. Furthermore, the MFF module is used to accurately acquire edge information by changing the number of the channel of advanced feature branches with a unique fusion method. To skip the labeling work, SFnet-DA reduces the difference in feature distribution between labeled and unlabeled datasets by building an adversarial relationship between the feature extractor and the domain classifier, so that the trained parameters of the labeled datasets can be directly used to predict the unlabeled images. Experimental results demonstrate that the proposed SFnet-DA has better performance on water body segmentation than state-of-the-art methods.
Ensemble Machine Learning of Random Forest, AdaBoost and XGBoost for Vertical Total Electron Content Forecasting
Authors: Natras Randa , Soja Benedikt , Schmidt Michael
Published: July 2022

Space weather describes varying conditions between the Sun and Earth that can degrade Global Navigation Satellite Systems (GNSS) operations. Thus, these effects should be precisely and timely corrected for accurate and reliable GNSS applications. That can be modeled with the Vertical Total Electron Content (VTEC) in the Earth’s ionosphere. This study investigates different learning algorithms to approximate nonlinear space weather processes and forecast VTEC for 1 h and 24 h in the future for low-, mid- and high-latitude ionospheric grid points along the same longitude. VTEC models are developed using learning algorithms of Decision Tree and ensemble learning of Random Forest, Adaptive Boosting (AdaBoost), and eXtreme Gradient Boosting (XGBoost). Furthermore, ensemble models are combined into a single meta-model Voting Regressor. Models were trained, optimized, and validated with the time series cross-validation technique. Moreover, the relative importance of input variables to the VTEC forecast is estimated. The results show that the developed models perform well in both quiet and storm conditions, where multi-tree ensemble learning outperforms the single Decision Tree. In particular, the meta-estimator Voting Regressor provides mostly the lowest RMSE and the highest correlation coefficients as it averages predictions from different well-performing models. Furthermore, expanding the input dataset with time derivatives, moving averages, and daily differences, as well as modifying data, such as differencing, enhances the learning of space weather features, especially over a longer forecast horizon.
Shuffle-CDNet: A Lightweight Network for Change Detection of Bitemporal Remote-Sensing Images
Authors: Cui Fengzhi , Jiang Jie
Published: July 2022

Change detection is an important task in remote-sensing image analysis. With the widespread development of deep learning in change detection, most of the current methods improve detection performance by making the network deeper and wider, but ignore the inference time and computational costs of the network. Therefore, this paper proposes a lightweight change-detection network called Shuffle-CDNet. It accepts the six-channel image that concatenates the bitemporal images by channel as the input, and it adopts the backbone network with channel shuffle operation and depthwise separable convolution layers. The classifier uses a lightweight atrous spatial pyramid pooling (Light-ASPP) module to reduce computational costs. The edge-information feature extracted by a lightweight branch is integrated with the shallow and deep features extracted by the backbone network, and the spatial and channel attention mechanisms are introduced to enhance the expression of features. At the same time, logit knowledge distillation and data augmentation techniques are used in the training phase to improve detection performance. Experimental results showed that the proposed method achieves a better balance in computational efficiency and detection performance compared with other advanced methods.
On the Use of NDVI to Estimate LAI in Field Crops: Implementing a Conversion Equation Library
Authors: Bajocco Sofia , Ginaldi Fabrizio , Savian Francesco , Morelli Danilo , Scaglione Massimo , Fanchini Davide , Raparelli Elisabetta , Bregaglio Simone Ugo Maria
Published: July 2022

The leaf area index (LAI) is a direct indicator of vegetation activity, and its relationship with the normalized difference vegetation index (NDVI) has been investigated in many research studies. Remote sensing makes available NDVI data over large areas, and researchers developed specific equations to derive the LAI from the NDVI, using empirical relationships grounded in field data collection. We conducted a literature search using “NDVI” AND “LAI” AND “crop” as the search string, focusing on the period 2017–2021. We reviewed the available equations to convert the NDVI into the LAI, aiming at (i) exploring the fields of application of an NDVI-based LAI, (ii) characterizing the mathematical relationships between the NDVI and LAI in the available equations, (iii) creating a software library with the retrieved methods, and (iv) releasing a publicly available software as a service, implementing these equations to foster their reuse by third parties. The literature search yielded 92 articles since 2017, where 139 equations were proposed. We analyzed the mathematical form of both the single equations and ensembles of the NDVI to LAI conversion methods, specific for crop, sensor, and biome. The characterization of the functions highlighted two main constraints when developing an NDVI-LAI conversion function: environmental conditions (i.e., water and light resource, land cover, and climate) and the availability of recurring data during the growing season. We found that the trend of an NDVI-LAI function is usually driven by the ecosystem water availability for the crop rather than by the crop type itself, as well as by the data availability; the data should be adequate in terms of the sample size and temporal resolution for reliably representing the phenomenon under investigation. Our study demonstrated that the choice of the NDVI-LAI equation (or ensemble of equations) should be driven by the trade-off between the scale of the investigation and data availability. The implementation of an extensible and reusable software library publicly queryable via API represents a valid mean to assist researchers in choosing the most suitable equations to perform an NDVI-LAI conversion.
Realtime Monitoring of Local Sweat Rate Kinetics during Constant-Load Exercise Using Perspiration-Meter with Airflow Compensation System
Authors: Okawara Hiroki , Sawada Tomonori , Nakashima Daisuke , Maeda Yuta , Minoji Shunsuke , Morisue Takashi , Katsumata Yoshinori , Matsumoto Morio , Nakamura Masaya , Nagura Takeo
Published: July 2022

Epidermal wearable sweat biomarker sensing technologies are likely affected by sweat rate because of the dilution effect and limited measurement methods. However, there is a dearth of reports on the local sweat rate (LSR) monitored in real-time during exercise. This explorative study investigated the feasibility of real-time LSR monitoring and clarified LSR kinetics on the forehead and upper arm during constant-load exercise using a perspiration meter with an airflow compensation system. This observational cross-sectional study included 18 recreationally trained males (mean age, 20.6 ± 0.8 years). LSR on the forehead and upper arm (mg/cm2/min) were measured during a constant-load exercise test at 25% of their pre-evaluated peak power until exhaustion. The LSR kinetics had two inflection points, with a gradual decrease in the incremental slope for each section. After the second flexion point, the LSR slope slightly decreased and was maintained until exhaustion. However, the degree of change varied among the participants. Although the ratio of forehead LSR to upper arm LSR tended to decrease gradually over time, there was little change in this ratio after a second flexion point of LSR in both. These findings suggest possible differences in LSR control between the forehead and upper arm during constant-load exercise to prolonged exhaustion.
MODECP: A Multi-Objective Based Approach for Solving Distributed Controller Placement Problem in Software Defined Network
Authors: Liao Chenxi , Chen Jia , Guo Kuo , Liu Shang , Chen Jing , Gao Deyun
Published: July 2022

Software-Defined Network is an emerging networking paradigm that enables intelligent and flexible network management. Specifically, the design of the control plane is crucial. Therefore, in order to avoid a single point of failure, multiple controllers are deployed constantly in a distributed manner on the control plane. In this paper, we propose a controller placement approach based on multiple objectives (MODECP), including network delay, network security, load-balancing rate, and link occupancy. In the controller placement stage, an improved multi-objective differential evolution algorithm is proposed to search for controllers’ positions and assign switches to controllers reasonably. Furthermore, an improved affinity propagation algorithm is proposed to obtain the number of controllers placed in the network partition stage, comprehensively considering the delay, node security, and load. Simulations are performed based on several topologies from Internet Topology Zoo. Extensive results show that the proposed algorithm can realize trade-offs among multiple objectives and improve network performance in delay, security, controller load, and link occupancy compared to the single-objective based approach. Moreover, compared with the genetic algorithm and random placement algorithm, the proposed algorithm performs better with low latency, high security, low load rate, and low link overhead.
Flexible Mechanoluminescent SrAl2O4:Eu Film with Tracking Performance of CFRP Fracture Phenomena
Authors: Fujio Yuki , Xu Chao-Nan , Terasaki Nao
Published: July 2022

Non-destructive testing of carbon-fiber-reinforced plastic (CFRP) laminates with bidirectional fiber bundles (twill-weave) using a mechanoluminescence (ML) technique was proposed. The dynamic strain distributions and fracture phenomena of the CFRP laminates in the tensile testing were evaluated by the fabricated ML sensor consisting of SrAl2O4:Eu (SAOE) powder and epoxy resin. The ML images for the ML sensor attached to the CFRP laminates with bidirectional fiber bundles gave a net-like ML intensity distribution similar to the original twill weave pattern. Specifically, it was found that the ML intensity on the longitudinal fiber bundle, which is the same as the tensile direction, is higher than that on the transverse fiber bundle. This indicates that the ML sensor can visualize the load share between fiber bundles in different directions of the CFRP laminate with high spatial resolution. Meanwhile, the ML sensor could also visualize the ultrafast discontinuous fracture process of the CFRP laminates and its stress distribution. The amount of SAOE powder in the ML sensor affects the tracking performance of the crack propagation. A higher SAOE amount leads to a fracture of the ML sensor itself, and a lower SAOE amount leads to poor ML characteristics.
A Study on the Applicability of the Impact-Echo Test Using Semi-Supervised Learning Based on Dynamic Preconditions
Authors: Yoon Young-Geun , Kim Chung-Min , Oh Tae-Keun
Published: July 2022

The Impact-Echo (IE) test is an effective method for determining the presence, depth, and area of cracks in concrete as well as the dimensions of the sound concrete without defects. In addition, shallow delamination can be measured by confirming a flexural mode in the low-frequency region. Owing to the advancement of non-contact sensors and automated measurement equipment, the IE test can be measured at multiple points in a short period. To analyze and distinguish a large volume of data, applying supervised learning (SL) associated with various contemporary algorithms is necessary. However, SL has limitations due to the difficulty in accurate labeling for increased volumes of test data, and reflection of new specimen characteristics, and it is necessary to apply semi-supervised learning (SSL) to overcome them. This study analyzes the accuracy and evaluates the applicability of a model trained with SSL rather than SL using the data from the air-coupled IE test based on dynamic preconditions. For the detection of delamination defects, the dynamic behavior-based flexural mode was identified, and 21 features were extracted in the time and frequency domains. Three principal components (PCs) such as the real moment, real RMS, and imaginary moment were derived through principal component analysis (PCA). PCs were identical in slab, pavement, and deck. In the case of SSL considering a dynamic behavior, the accuracy increased by 7–8% compared with SL, and it could categorize good, fair, and poor status to a higher level for actual structures. The applicability of SSL to the IE test was confirmed, and because the crack progress varies under field conditions, other parameters must be considered in the future to reflect this.
A Novel Circularly Polarized Folded Transmitarray Antenna with Integrated Radiation and Scattering Performance
Authors: Guo Zexu , Cao Xiangyu , Liu Tao , Gao Jun , Li Sijia , Yang Huanhuan , Li Tong
Published: July 2022

In this paper, a novel design method of circularly polarized folded transmitarray antenna (CPFTA) is presented by applying sequential rotation technology. Compared with the general design method, the novel design method can reduce the design difficulty and improve the axis ratio (AR) bandwidth significantly without adding any additional structure. To verify the proposed method, both a general CPFTA (GCPFTA) and a novel CPFTA (NCPFTA) are designed, fabricated, measured and compared. Good agreements between simulated and measured results are obtained. Thanks to the creative design, the integrated radiation and scattering control of the CPFTA is realized for the first time. The proposed NCPFTA has the advantages of broadband, high gain, planar structure, low profile, convenience in installation and low radar cross section (RCS), which has potential application in mobile satellite communication.
Novel Deep-Water Tidal Meter for Offshore Aquaculture Infrastructures
Authors: Sosa Javier , Montiel-Nelson Juan-A.
Published: July 2022

This paper presents a tidal current meter that is based on the inertial acceleration principle for offshore infrastructures in deep water. Focusing on the marine installations of the aquaculture industry, we studied the forces of tides at a depth of 15 m by measuring the acceleration. In addition, we used a commercial MEMS triaxial accelerometer to record the acceleration values. A prototype of the tidal measurement unit was developed and tested at a real offshore aquaculture infrastructure in Gran Canaria, which is one of the Canary Islands in the Atlantic Ocean. The proposed tidal measurement unit was used as a recorder to assess the complexity of measuring the frequency of tidal currents in the short (10 min), medium (one day) and long term (one week). The acquired data were studied in detail, in both the time and frequency domains, to determine the frequency of the forces that were involved. Finally, the complexity of the frequency measurements from the captured data was analyzed in terms of sampling ratio and recording duration, from the point of view of using our proposed measurement unit as an ultra-low-power embedded system. The proposed device was tested for more than 180 days using a lithium-ion battery. This working period was three times greater than the best alternative in the literature because of the ultra-low-power design of the on-board embedded system. The measurement accuracy error was lower than 1% and the resolution was 0.01 cm/s for the 0.8 m/s velocity scale. This performance was similar to the best Doppler solution that was found in the literature.
Prospect of Internet of Medical Things: A Review on Security Requirements and Solutions
Authors: Sadhu Pintu Kumar , Yanambaka Venkata P. , Abdelgawad Ahmed , Yelamarthi Kumar
Published: July 2022

With the widespread and increasing use of Internet-of-Things (IoT) devices in all aspects of daily life, a hopeful future for people, data, and processes is emerging. Extensive spans allow for an integrated life cycle to be created from home to enterprise. The Internet of Medical Things (IoMT) forms a flourishing surface that incorporates the sensitive information of human life being sent to doctors or hospitals. These open an enormous space for hackers to utilize flaws of the IoMT network to make a profit. This creates a demand for standardizing regulations and a secure system. Though many authorities are making standards, there are some lacking in the system which makes the product vulnerable. Although many established mechanisms are present for the IoT network, there are a number of obstacles preventing its general implementation in the IoMT network. One of the adoption challenges is the IoMT devices itself, because many IoMT networks consist of battery-powered devices with constrained processing capability. A general overview of the different security integrations with IoT applications has been presented in several papers. Therefore, this paper aims to provide an overview of the IoMT ecosystem, regulations, challenges of standards, security mechanisms using cryptographic solutions, physical unclonable functions (PUF)-based solutions, blockchain, and named data networking (NDN) as well, with pros and cons.
Reliable Aerial Mobile Communications with RSRP & RSRQ Prediction Models for the Internet of Drones: A Machine Learning Approach
Authors: Behjati Mehran , Zulkifley Muhammad Aidiel , Alobaidy Haider A. H. , Nordin Rosdiadee , Abdullah Nor Fadzilah
Published: July 2022

The unmanned aerial vehicle (UAV) industry is moving toward beyond visual line of sight (BVLOS) operations to unlock future internet of drones applications, including unmanned environmental monitoring and long-range delivery services. A reliable and ubiquitous mobile communication link plays a vital role in ensuring flight safety. Cellular networks are considered one of the main enablers of BVLOS operations. However, the existing cellular networks are designed and optimized for terrestrial use cases. To investigate the reliability of provided aerial coverage by the terrestrial cellular base stations (BSs), this article proposes six machine learning-based models to predict reference signal received power (RSRP) and reference signal received quality (RSRQ) based on the multiple linear regression, polynomial, and logarithmic methods. In this regard, first, a UAV-to-BS measurement campaign was conducted in a 4G LTE network within a suburban environment. Then, the aerial coverage was statistically analyzed and the prediction methods were developed as a function of distance and elevation angle. The results reveal the capability of terrestrial BSs in providing aerial coverage under some circumstances, which mainly depends on the distance between the UAV and BS and flight height. The performance evaluation shows that the proposed RSRP and RSRQ models achieved RMSE of 4.37 dBm and 2.71 dB for testing samples, respectively.
A Novel Method to Measure the Static Coefficient of Friction for Socks
Authors: Eun Jinsu , Ryue Jaejin , Park Sangsoo , Lee Kikwang
Published: July 2022

Mechanical testers have commonly been used to measure the frictional properties of socks. However, the friction values may be susceptible to the level of stretchiness of tested fabrics or human variability. Thus, the aim of this study was to propose a novel method that enables friction measurement of socks in a sock-wearing condition with less human variability effects. Five socks with different frictional properties were chosen. Three experimental ramp tests were performed with an artificial structure shaped like the foot-ankle complex (last) and a ramp tester to quantify the static coefficient of friction (COF) at the foot against sock, at the sock against an insole, and the foot wearing socks against the insole, respectively. The angle where the last slipped while the ramp surface was gradually inclined was used to compute the static COF values for each sock. The reliability was 0.99, and COF values ranged from 0.271 to 0.861 at the foot-sock interface, 0.342 to 0.639 at the sock-insole interface, and 0.310 to 0.614 in the third test. Socks with different frictional properties were successfully distinguished each other. Thus, the suggested protocol could be a reliable option for measuring the static COF values in the tension similar with it found in a sock-waring condition with reduced effects of human variability.
Polyphenols from Plants: Phytochemical Characterization, Antioxidant Capacity, and Antimicrobial Activity of Some Plants from Different Sites of Greece
Authors: Papastavropoulou Konstantina , Oz Emel , Oz Fatih , Proestos Charalampos
Published: July 2022

Polyphenols are present in many plants and herbs, and the scientific community and consumers are aware of their health-promoting effects. Plants of Greek origin were studied for their polyphenol content and their antioxidant and antimicrobial activities. Gas chromatography–mass spectrometry (GC–MS) and high-performance liquid chromatography coupled to a diode array detector (HPLC–DAD) were used for the identification and characterization of plant polyphenols. For GC–MS, a silylation procedure was employed. Ferulic acid, quercetin, and catechin were the most abundant polyphenols. The Rancimat test, FRAP (Ferric-reducing Antioxidant power) assay, and DPPH (2,2-Diphenyl-1-picrylhydrazyl) assay were used to study the antioxidant capacity, which was proven for all studied plants. The antimicrobial activity was studied against specific pathogenic microorganisms. Pelargonium purpureum and Sideritis scardica plant extracts inhibited most microorganisms such as L. monocytogenes and E. coli. Extracts of studied plants showed both antioxidant and antimicrobial activities; hence, they can be considered to be used by the food industry.
Higher Leg and Trunk Muscle Activation during Balance Control in Copers versus People with Chronic Ankle Instability and Healthy Female Athletes
Authors: Karbalaeimahdi Mina , Alizadeh Mohammad Hossein , Minoonejad Hooman , Behm David G. , Alizadeh Shahab
Published: July 2022

More than 70% of people with ankle sprain experience chronic ankle instability. However, some people are well adapted to this damage (copers) and do not suffer from chronic ankle instability (CAI). This cross-sectional study involved 34 female athletes, who were classified into three groups (athletes with CAI, copers, and healthy athletes) and tested on a Biodex Balance System. Surface electromyography (EMG) and balance scores were monitored. The coper and healthy group exhibited higher medial gastrocnemius (MG) EMG activity during unstable balance conditions. The rectus abdominus (RA) in the coper group and rectus femoris (RF) in the healthy group showed greater EMG activity compared to CAI during unstable conditions. During stable conditions, the coper group showed greater RA EMG activity compared to CAI, as well as higher tibialis anterior (TA) EMG activity compared to the healthy group. Additionally, balance error scores were higher in the CAI group than those in the healthy group under unstable conditions. In conclusion, decreased EMG activity of the MG, RF, and RA in CAI athletes may contribute to impaired balance in these individuals. The increased EMG activity of the MG, TA, and RA in copers might result in more trunk and ankle stability.
Urbanization and Habitat Characteristics Associated with the Occurrence of Peste des Petits Ruminants in Africa
Authors: Zhang Shanyong , Li Ning , Xu Mingshuai , Huang Zheng Y. X. , Gu Zhujun , Yin Shenglai
Published: July 2022

As a highly contagious viral disease, peste des petits ruminants (PPR) can cause severe socio-economic impacts in developing countries due to its threat to sheep and goat production. Previous studies have identified several risk factors for PPR at the individual or herd level. However, only a few studies explored the impacts of landscape factors on PPR risk, particularly at a regional scale. Moreover, risk factor analyses in Africa usually focused on sub-Saharan Africa while neglecting northern Africa. Based on regional occurrence data during 2006–2018, we here explored and compared the risk factors, with a focus on factors related to ruminant habitats, for the occurrence of PPR in sub-Saharan and northern Africa. Our results demonstrated different risk factors in the two regions. Specifically, habitat fragmentation was negatively correlated with PPR occurrence in sub-Saharan Africa, while positively correlated with PPR occurrence in northern Africa. Moreover, urbanization showed a positive association with PPR occurrence in sub-Saharan Africa. Our study is among the first, to our knowledge, to compare the risk factors for PPR in sub-Saharan and northern Africa and contributes to a better understanding of the effects of habitat characteristics on PPR occurrence at a regional scale.
The Effect of International Diversification on Sustainable Development: The Mediating Role of Dynamic Capabilities
Authors: Wu Hang , Qu Yiying , Ye Yong
Published: July 2022

International diversification has become a crucial measure for firms to realize sustainable development. However, previous studies have drawn inconsistent conclusions on the sustainable performance impact of international expansion. This paper examines the relationships among international diversification, capabilities, and sustainable performance. We provide a theoretical perspective of dynamic capabilities to uncover the impact mechanism of international diversification on firms’ economic and environmental performance. Based on data from Chinese listed manufacturing firms operating overseas, the findings show that international diversification is significant for firms’ sustainable development, and its effect on economic performance and environmental performance is mediated by adaptive capability and innovation capability. The implications for theoretical development and operating practice are discussed.
The Climate Characteristics of the Northeast China Cold Vortex against the Background of Global Warming
Authors: Fang Yihe , Hua Jingjing , Yu Yiqiu , Lin Yitong , Zhao Chunyu
Published: July 2022

In this study, by using the ERA5 data of the atmospheric circulation field that was re-analyzed by the ECMWF (European Centre for Medium-Range Weather Forecasts), we revealed the features of the Northeast China Cold Vortex (NCCV) from 1950 to 2020 (including active days, occurrence time of NCCV processes, and process durations). This study focused on a comparative analysis of the differences in the NCCV’s climate characteristics in the cold and warm periods to help future predictions. The results revealed the following: From 1950 to 2020, the NCCV occurred 2961 times on 9782 days. The average annual occurrence time of NCCV processes, annual average of cold vortex days, and average process duration of the NCCVs were 41.7 times, 137.8 days, and 3.6 days, respectively. These indicators of the NCCVs showed an increasing trend, but the trend was not significant. The NCCVs occurred most frequently in May, followed by June, and were located at the southernmost point in June. Therefore, it had the most active days and a relatively long process duration in May and June, significantly impacting Northeast China. During the cold period (1950–1980), the annual occurrence time of NCCV processes, number of cold vortex days, and the process duration of the NCCVs all showed an increasing trend, while in the warm period, these showed a decreasing trend. In addition, the durations of the NCCVs decreased significantly in the warm period, which indicated that the NCCV processes continued to weaken after climate warming. During the warm period (1981–2020), the frequency and active days of the NCCVs throughout the year and most months increased, and its general location was more southerly than in the cold period. Moreover, the annual average occurrence time of NCCV processes, number of active days, and average duration of the NCCV in the warm period were more than those in the cold period. Finally, the NCCVs continued for longer in autumn and winter than in spring and summer, and the durations of the NCCVs increased in warm periods.
Cycling Tourism: A Literature Review to Assess Implications, Multiple Impacts, Vulnerabilities, and Future Perspectives
Authors: Ciascai Ovidiu R. , Dezsi Ștefan , Rus Karina A.
Published: July 2022

Cycle tourists are increasingly prominent in the profile of world tourism and, in the light of the literature, it is essential, among other things, to examine more closely who they are, what their concerns and motivations are that generate the choice of a cycle tourism product, and, as a priority, the level of economic, social, and environmental impact they cause at destination. In this context, this literature review aims at identifying authors’ and publishers’ interest in cycle tourism, the positive and negative effects of this form of tourism on the economic environment (direct and indirect), as well as effects on the social environment (benefits and potential drawbacks for local communities, along with health benefits for practitioners) and, last but not least, the degree of vulnerability to economic crises generated by travel restrictions. The conclusions reported in this article, as they have been drawn from analyses and examples of best practice, based on natural and anthropogenic geographical conditions, will be prioritised as future research directions. The usefulness of this approach lies in the information with significant applied and novelty aspects, addressed to local, regional, and national authorities, cycling and cycle-tourism associations, and various private interested enterprises, with a view to promoting cycling for recreational purposes and implementing cycling/cycle-tourism infrastructure as a sustainable way of developing small towns and rural areas with tourism potential.
Sustainable Development of Mastery Goals and Innovative Behavior: Evidence from Chinese Faculty Members
Authors: Gao Chao , Han Jiying
Published: July 2022

It is well-acknowledged that organizational sustainability largely depends on employees’ innovative behavior, which is the same case with higher education institutions. This study aimed to explore the characteristics of and relationships between faculty members’ mastery goals and innovative behavior under the framework of achievement goal theory in the research context. Results from an anonymous questionnaire survey of 621 Chinese faculty members revealed a four-dimensional structure of mastery goals (task-approach goals, task-avoidance goals, learning-approach goals, and learning-avoidance goals) and a five-dimensional structure of innovative research behavior (opportunity exploration, generativity, formative investigation, championing, and application). The faculty members reported a high level of mastery goals for research and a moderate level of innovative research behavior respectively. Male faculty scored higher on opportunity exploration, formative investigation, championing, and application than their female counterparts. Innovative research behavior showed significantly positive associations with task-approach goals, negative associations with learning-approach goals, and no significant association with mastery-avoidance goals except the positive link of learning-avoidance goals to championing. These results have implications for understanding faculty research motivations and behaviors and effectively stimulating their innovativeness in research for sustainable development of higher education institutions.
Research Topic Specialization of Universities in Information Science and Library Science and Its Impact on Inter-University Collaboration
Authors: Hou Lei , Luo Jiashan , Pan Xue
Published: July 2022

Universities significantly empower the development of science and technology, and inter-university research collaborations have been one of the major approaches. Considering each university has its expertise regarding research topics in a given discipline, the present paper examines the specialization of university research and its impact on inter-university collaborations. Based on a keyword network constructed via research articles in Information Science and Library Science, 10 research topics are identified. Accordingly, the research topic diversity of a university and the research topic similarity between two universities are quantified. The universities with diverse research topics are found to be more collaborative. A further collaboration network analysis based on the Quadradic Assignment Procedure reveals the important role of research topic similarity on the closeness and impact of collaborations. The different research topic specializations largely prevent close collaborations between two universities, but on the other hand, have the potential to form a complementary combination of knowledge leading to more impactful research output. The analysis and results highlight the important role of research topic specialization and provide insights for the university- or department-level strategy for research collaborations.
The Influence of Arbuscular Mycorrhizal Fungus Rhizophagus irregularis on the Growth and Quality of Processing Tomato (Lycopersicon esculentum Mill.) Seedlings
Authors: Roussis Ioannis , Beslemes Dimitrios , Kosma Chariklia , Triantafyllidis Vassilios , Zotos Anastasios , Tigka Evangelia , Mavroeidis Antonios , Karydogianni Stella , Kouneli Varvara , Travlos Ilias , Kakabouki Ioanna
Published: July 2022

Tomato (Lycopersicon esculentum Mill.) is one of the most valuable horticultural crops, not only for its economic importance but also for its high nutritional value and sensory qualities. The arbuscular mycorrhiza (AM) fungus Rhizophagus irregularis can improve plant nutrient uptake and decrease seedling transplanting shock. Although R. irregularis is one of the most extensively studied AMF species, there is a paucity of data on the effects of this species on processing tomato seedlings produced in an aerated hydroponic float system. A greenhouse experiment with four treatments and three replications was established in a completely randomized design. The treatments contained the addition of 0, 40, 80, and 120 fungal spores per L of nutrient solution (control, AMF1, AMF2, and AMF3, respectively). Root colonization analysis proved that the maximum dose of applied AMF (AMF3) supported colonization to a large extent, succeeding 36.74%. In addition, the highest values of total dry weight (1.386 g), survival rate (94.79%), N content (3.376 mg per 100 g DW) and P content (0.497 mg per 100 g DW) were also observed under AMF3 treatment. In conclusion, the application of high doses of the AM fungus R. irregularis in nutrient solutions of float system leads to a substantial improvement in the quality and growth of processing tomato seedlings.
Energy Saving with Zero Hot Spots: A Novel Power Control Approach for Sustainable and Stable Data Centers
Authors: Li Danyang , Zhang Yuqi , Song Jie , Liu Hui , Jiang Jingqing
Published: July 2022

Data centers with high energy consumption have become a threat to urban sustainability on electric energy. In contrast, hot spots in a data center are another threat to server stability, which leads to unsafe data storage and service provisioning to urban lives. However, state-of-the-art works cannot ensure sustainability and stability together because they fail to consider them holistically. For example, some existing works eliminate the hot spots by increasing cooling power, which results in lower sustainability. In contrast, others reduce energy consumption by saving the cooling power, which harms stability. Therefore, to balance the hot spot elimination and energy saving through power control remains challenging, this paper proposes a novel power control approach for energy saving with zero hot spots in data centers. Power control works when hot spots appear, or consumed energy is excess. Specifically, we formulated a total consumption minimization problem to characterize and analyze the optimal set points for power control, where the number of hot spots is zero and the energy consumption is low. Adding the interactional penalty models can determine the power control approach when the objective function obtains the optimal solution. We propose a Modified Differential Evolution algorithm (MDE) to solve the function quickly and accurately. It adopts adaptive parameters to reduce the computing time. Meanwhile, it avoids optimal local solutions by changing mutation operations. Further, simulation experiments using our optimal solution demonstrate that energy consumption saves about 13% on average with zero hot spots, compared with three typical approaches.
Factors Influencing Hospitality Employees’ Pro-Environmental Behaviours toward Food Waste
Authors: Chawla Gaurav , Lugosi Peter , Hawkins Rebecca
Published: July 2022

Food waste remains an ongoing problem in hotel operations, and changing employees’ behaviour is key to tackling this issue. Analysing the influences on employees’ working practices can help to drive pro-environmental behaviour changes that reduce food waste, thus supporting the UN’s SDG 12: ensuring responsible consumption and production patterns. This study used the theory of planned behaviour as its theoretical framework and empirical data generated through participant observation, analysis of organisational documents, and semi-structured interviews in luxury hotels to examine waste drivers among employees. The findings suggest that hotel workers adopt a rational rather than moral lens toward food waste. Moreover, attitudes, subjective norms, and perceived behavioural control strongly influence intentions to perform pro-environmental behaviours. Positive attitudes and strong subjective norms propel employees toward pro-environmental behaviours while a lack of perceived control acts as a constraining force.
Solar Typologies: A Comparative Analysis of Urban Form and Solar Potential
Authors: Giostra Simone , Masera Gabriele , Monteiro Rafaella
Published: July 2022

Efficient use of energy in the construction sector is a pillar of the European Union’s 2050 climate protection goals, yet legislation makes no explicit reference to urban morphology or building form, which are recognized as key to energy performance in buildings. Rapidly changing energy standards and new requirements for on-site energy production demand a vigorous scrutiny of established urban typologies that are largely the product of an older energy regime. The research explores a set of 312 building shapes with floor-to-area ratio (FAR) of 3 within a given plot to identify emerging trends, ranges, and correlations between geometric variables, visual comfort, and energy indicators. Cases are grouped and evaluated in relation to three main urban typologies to highlight unique features related to each typology. The paper also compares two groups of results related to passive and active solar potential, respectively, to identify formal traits that are specific to each of these two design strategies. Finally, the research ranks design options based on total energy use taking into account the energy need for artificial lighting as well as contributions from both passive energy savings and active energy production. Results show that energy demand across cases varies by a factor 2 for passive strategies and a factor 5 when active potential is considered based on shape alone. Best results are clearly positioned at the two extremes of the geometric and proportional range. On the one hand, low-rise compact bar and courtyard buildings that are perhaps most prevalent in our cities today may be effectively retrofitted to meet active energy targets. On the other hand, extremely tall and slim towers appear to be the only typology in the study with the potential to achieve zero-energy status by virtue of their form alone. The work sheds light on the formal implications of EU energy mandates and offers a glimpse of how buildings may adapt to the combined selective pressures of high on-site energy fraction and low energy use to shape our future cities.
Real-Time Human Fault Detection in Assembly Tasks, Based on Human Action Prediction Using a Spatio-Temporal Learning Model
Authors: Zhang Zhujun , Peng Gaoliang , Wang Weitian , Chen Yi
Published: July 2022

Human fault detection plays an important role in the industrial assembly process. In the current unstructured industrial workspace, the definition of human faults may vary over a long sequence, and this vagueness introduces multiple issues when using traditional detection methods. A method which could learn the correct action sequence from humans, as well as detect the fault actions based on prior knowledge, would be more appropriate and effective. To this end, we propose an end-to-end learning model to predict future human actions and extend it to detect human faults. We combined the auto-encoder framework and recurrent neural network (RNN) method to predict and generate intuitive future human motions. The convolutional long short-term memory (ConvLSTM) layer was applied to extract spatio-temporal features from video sequences. A score function was implemented to indicate the difference between the correct human action sequence and the fault actions. The proposed model was evaluated on a model vehicle seat assembly task. The experimental results showed that the model could effectively capture the necessary historical details to predict future human actions. The results of several fault scenarios demonstrated that the model could detect the faults in human actions based on corresponding future behaviors through prediction features.
Optimal Environmental Policy in a Dynamic Transboundary Pollution Game: Emission Standards, Taxes, and Permit Trading
Authors: Xu Hao , Luo Ming
Published: July 2022

Global environmental problems such as transboundary pollution and global warming have been recognized as major issues around the world. In practice, governments of all countries are actively exploring various environmental policies to control pollution. The government needs to consider the impact of neighboring regions when formulating environmental policies, especially in the context of transboundary pollution. However, the above problems are less studied, to bridge this gap and aim at solving problems in existing practices, we consider a differential game model of transboundary pollution control to examine which policy is more effective in promoting environmental quality and social welfare in a dynamic and accumulative global pollution context. Three alternative policy instruments, namely emission standards, emission taxes, and emission permit trading, are considered and compared. The results show that the social welfare of each region is the lowest and the total pollution stock is the highest under the emission tax policy due to the “rent-shifting,” “policy-leakage,” and “free-riding” effects. Moreover, the realized level of the environmental policy in the Nash equilibrium of the policy game is distorted away from the socially optimal level. The emission standards policy is found to be better than the emission tax policy and characterized by initiating the rent-shifting effect without the policy-leakage effect. Moreover, the pollution stock of two regions is found to be the lowest and the social welfare is found to be the highest under the emission permit trading policy, which is not associated with any of the three effects. Finally, a numerical example is used to illustrate the results, and a sensitivity analysis is performed in the steady state.
The Determinants of Consumers’ E-Waste Recycling Behavior through the Lens of Extended Theory of Planned Behavior
Authors: Mohamad Nur Shafeera , Thoo Ai Chin , Huam Hon Tat
Published: July 2022

Cutting-edge technological advancements have turned many electronic devices into waste within a short time of usage. Electronic waste (e-waste) has become a global problem. Due to the adverse impact of e-waste on the environment and human health, a regulatory system for effective collection and treatment of e-waste disposed of by the community and business sectors is in dire need. In an attempt to address the setbacks and cope with e-waste issues, this study determined factors that influence e-waste recycling intentions (ERIs) and e-waste recycling behavior (ERB) among consumers in Malaysia through the lens of an extended theory of planned behavior (TPB) model. Via an online survey, 159 questionnaires were collected from targeted respondents in Malaysia aged 18 years and above identified using the purposive sampling method. The structural equation modeling (SEM) approach was deployed for data analysis. As a result, moral obligation (MO) emerged as the most significant factor toward ERI, followed by perceived convenience (PC). Next, ERI displayed a significant effect on ERB. The multi-group analysis (MGA) outcomes revealed significant group differences in education variables, signifying that the lower/middle education group was more easily influenced to perform ERB than the higher education group. Essentially, this study contributes to many aspects especially in enhancing the awareness of e-waste issues and emphasizing the broad knowledge about e-waste recycling. This study provides practical implications for the government, the policymakers and all stakeholders, including consumers, non-government agencies, collectors, retailers, and recycling facilities. The study outcomes may be considered when formulating laws and regulations to enhance e-waste recycling efforts that guarantee a sustainable ecosystem in the future.