bluuebunny/crossref_metadata_2025 huggingface dataset:
Retrieval and Uncertainty Analysis of Land Surface Reflectance Using a Geostationary Ocean Color Imager
Authors: Lee Kyeong-Sang , Lee Eunkyung , Jin Donghyun , Seong Noh-Hun , Jung Daeseong , Sim Suyoung , Han Kyung-Soo
Published: January 2022

Land surface reflectance (LSR) is well known as an essential variable to understand land surface properties. The Geostationary Ocean Color Imager (GOCI) be able to observe not only the ocean but also the land with the high temporal and spatial resolution thanks to its channel specification. In this study, we describe the land atmospheric correction algorithm and present the quality of results through comparison with Moderate Resolution Imaging Spectroradiometer (MODIS) and in-situ data for GOCI-II. The GOCI LSR shows similar spatial distribution and quantity with MODIS LSR for both healthy and unhealthy vegetation cover. Our results agreed well with in-situ-based reference LSR with a high correlation coefficient (>0.9) and low root mean square error (<0.02) in all 8 GOCI channels. In addition, seasonal variation according to the solar zenith angle and phenological dynamics in time-series was well presented in both reference and GOCI LSR. As the results of uncertainty analysis, the estimated uncertainty in GOCI LSR shows a reasonable range (<0.04) even under a high solar zenith angle over 70°. The proposed method in this study can be applied to GOCI-II and can provide continuous satellite-based LSR products having a high temporal and spatial resolution for analyzing land surface properties.
Forest Canopy Height Mapping by Synergizing ICESat-2, Sentinel-1, Sentinel-2 and Topographic Information Based on Machine Learning Methods
Authors: Xi Zhilong , Xu Huadong , Xing Yanqiu , Gong Weishu , Chen Guizhen , Yang Shuhang
Published: January 2022

Spaceborne LiDAR has been widely used to obtain forest canopy heights over large areas, but it is still a challenge to obtain spatio-continuous forest canopy heights with this technology. In order to make up for this deficiency and take advantage of the complementary for multi-source remote sensing data in forest canopy height mapping, a new method to estimate forest canopy height was proposed by synergizing the spaceborne LiDAR (ICESat-2) data, Synthetic Aperture Radar (SAR) data, multi-spectral images, and topographic data considering forest types. In this study, National Geographical Condition Monitoring (NGCM) data was used to extract the distributions of coniferous forest (CF), broadleaf forest (BF), and mixed forest (MF) in Hua’ nan forest area in Heilongjiang Province, China. Accordingly, the forest canopy height estimation models for whole forest (all forests together without distinguishing types, WF), CF, BF, and MF were established, respectively, by Radom Forest (RF) and Gradient Boosting Decision Tree (GBDT). The accuracy for established models and the forest canopy height obtained based on estimation models were validated consequently. The results showed that the forest canopy height estimation models considering forest types had better performance than the model grouping all types of forest together. Compared with GBDT, RF with optimal variables had better performance in forest canopy height estimation with Pearson’s correlation coefficient (R) and the root-mean-squared error (RMSE) values for CF, BF, and MF of 0.72, 0.59, 0.62, and 3.15, 3.37, 3.26 m, respectively. It has been validated that a synergy of ICESat-2 with other remote sensing data can make a crucial contribution to spatio-continuous forest canopy height mapping, especially for areas covered by different types of forest.
Spatiotemporal Evolution of the Carbon Fluxes from Bamboo Forests and their Response to Climate Change Based on a BEPS Model in China
Authors: Kang Fangfang , Li Xuejian , Du Huaqiang , Mao Fangjie , Zhou Guomo , Xu Yanxin , Huang Zihao , Ji Jiayi , Wang Jingyi
Published: January 2022

Carbon flux is the main basis for judging the carbon source/sink of forest ecosystems. Bamboo forests have gained much attention because of their high carbon sequestration capacity. In this study, we used a boreal ecosystem productivity simulator (BEPS) model to simulate the gross primary productivity (GPP) and net primary productivity (NPP) of bamboo forests in China during 2001–2018, and then explored the spatiotemporal evolution of the carbon fluxes and their response to climatic factors. The results showed that: (1) The simulated and observed GPP values exhibited a good correlation with the determination coefficient (R2), root mean square error (RMSE), and absolute bias (aBIAS) of 0.58, 1.43 g C m−2 day−1, and 1.21 g C m−2 day−1, respectively. (2) During 2001–2018, GPP and NPP showed fluctuating increasing trends with growth rates of 5.20 g C m−2 yr−1 and 3.88 g C m−2 yr−1, respectively. The spatial distribution characteristics of GPP and NPP were stronger in the south and east than in the north and west. Additionally, the trend slope results showed that GPP and NPP mainly increased, and approximately 30% of the area showed a significant increasing trend. (3) Our study showed that more than half of the area exhibited the fact that the influence of the average annual precipitation had positive effects on GPP and NPP, while the average annual minimum and maximum temperatures had negative effects on GPP and NPP. On a monthly scale, our study also demonstrated that the influence of precipitation on GPP and NPP was higher than that of the influence of temperature on them.
Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System
Authors: Voshtani Sina , Ménard Richard , Walker Thomas W. , Hakami Amir
Published: January 2022

We present a parametric Kalman filter data assimilation system using GOSAT methane observations within the hemispheric CMAQ model. The assimilation system produces forecasts and analyses of concentrations and explicitly computes its evolving error variance while remaining computationally competitive with other data assimilation schemes such as 4-dimensional variational (4D-Var) and ensemble Kalman filter (EnKF). The error variance in this system is advected using the native advection scheme of the CMAQ model and updated at each analysis while the error correlations are kept fixed. We discuss extensions to the CMAQ model to include methane transport and emissions (both anthropogenic and natural) and perform a bias correction for the GOSAT observations. The results using synthetic observations show that the analysis error and analysis increments follow the advective flow while conserving the information content (i.e., total variance). We also demonstrate that the vertical error correlation contributes to the inference of variables down to the surface. In a companion paper, we use this assimilation system to obtain optimal assimilation of GOSAT observations.
Comparison of the Novel Probabilistic Self-Optimizing Vectorized Earth Observation Retrieval Classifier with Common Machine Learning Algorithms
Authors: Musial Jan Pawel , Bojanowski Jedrzej Stanislaw
Published: January 2022

The Vectorized Earth Observation Retrieval (VEOR) algorithm is a novel algorithm suited to the efficient supervised classification of large Earth Observation (EO) datasets. VEOR addresses shortcomings in well-established machine learning methods with an emphasis on numerical performance. Its characteristics include (1) derivation of classification probability; (2) objective selection of classification features that maximize Cohen’s kappa coefficient (κ) derived from iterative “leave-one-out” cross-validation; (3) reduced sensitivity of the classification results to imbalanced classes; (4) smoothing of the classification probability field to reduce noise/mislabeling; (5) numerically efficient retrieval based on a pre-computed look-up vector (LUV); and (6) separate parametrization of the algorithm for each discrete feature class (e.g., land cover). Within this study, the performance of the VEOR classifier was compared to other commonly used machine learning algorithms: K-nearest neighbors, support vector machines, Gaussian process, decision trees, random forest, artificial neural networks, AdaBoost, Naive Bayes and Quadratic Discriminant Analysis. Firstly, the comparison was performed using synthetic 2D (two-dimensional) datasets featuring different sample sizes, levels of noise (i.e., mislabeling) and class imbalance. Secondly, the same experiments were repeated for 7D datasets consisting of informative, redundant and insignificant features. Ultimately, the benchmarking of the classifiers involved cloud discrimination using MODIS satellite spectral measurements and a reference cloud mask derived from combined CALIOP lidar and CPR radar data. The results revealed that the proposed VEOR algorithm accurately discriminated cloud cover using MODIS data and accurately classified large synthetic datasets with low or moderate levels of noise and class imbalance. On the contrary, VEOR did not feature good classification skills for significantly distorted or for small datasets. Nevertheless, the comparisons performed proved that VEOR was within the 3–4 most accurate classifiers and that it can be applied to large Earth Observation datasets.
Forage Availability and Quality, and Feeding Behaviour of Indigenous Goats Grazing in a Mediterranean Silvopastoral System
Authors: Chebli Youssef , El Otmani Samira , Hornick Jean-Luc , Keli Abdelhafid , Bindelle Jérôme , Cabaraux Jean-François , Chentouf Mouad
Published: January 2022

The aim of this study was to evaluate the feeding behaviour of indigenous goats and the selection drivers of different plant species in a Mediterranean forest rangeland. To achieve this goal, the seasonal variations in terms of forage availability and quality of ingested plant species were studied during three grazing seasons. In the same period, eight indigenous goats of Beni Arouss breed were selected to explore the seasonal changes in their browsing behaviour. Forage quality was determined by the hand-plucking technique. The results showed a wide seasonal variation in forage availability and quality, and feeding behaviour. Woody species were more selected independently of the season (p < 0.001). The crude protein content varied from 53.3 g/kg of dry mater (DM) for Erica arborea in summer to 197 g/kg DM for Calicotome villosa in autumn (p < 0.001). Despite the high condensed tannins content in selected shrubs, they were highly consumed. In vitro organic matter digestibility (IVOMD) and metabolizable energy (ME) had recorded the highest contents in herbaceous during spring. Shrubs and trees contain the lowest levels of IVOMD (<500 g/kg) and ME (<7.2 MJ/kg) during autumn and summer. It is concluded that seasonal changes in forage availability and quality did not necessarily affect the indigenous goats’ preference. These findings could help goat herders to develop feeding and grazing systems while increasing the performance of goats in the Mediterranean silvopastoral system.
Understanding the Influence of Rock Content on Streaming Potential Phenomenon of Soil–Rock Mixture: An Experimental Study
Authors: Zhang Xin , Zhao Mingjie , Wang Kui
Published: January 2022

To applicate streaming potential phenomenon to study the seepage feature in the soil–rock mixture (SRM), research on the variation in the streaming potential phenomenon of SRM is the precondition. This paper deals, in assistance with the streaming potential test apparatus, with the streaming potential effect response of SRM subjected to different rock contents. The test results show that when the rock content increases from 10% to 30%, the streaming potential coupling coefficient increases with the increases in rock content at 85% compactness and 0.01 mol L−1 salinity. When the rock content is more than 30%, the streaming potential coupling coefficient decreases with the increases in rock content. As the rock content increases, the permeability coefficient has a negative correlation with the streaming potential coupling coefficient. The streaming potential increases first and then goes down with the increases in rock content, and the streaming potential decreases significantly when the rock content exceeds 50%. The findings indicate that the rock content is the key structural factor that restricts the streaming potential phenomenon of the SRM.
Optimal Sensor Placement in Reduced-Order Models Using Modal Constraint Conditions
Authors: Lee Eun-Taik , Eun Hee-Chang
Published: January 2022

Sensor measurements of civil structures provide basic information on their performance. However, it is impossible to install sensors at every location owing to the limited number of sensors available. Therefore, in this study, we propose an optimal sensor placement (OSP) algorithm while reducing the system order by using the constraint condition between the master and slave modes from the target modes. The existing OSP methods are modified in this study, and an OSP approach using a constrained dynamic equation is presented. The validity and comparison of the proposed methods are illustrated by utilizing a numerical example that predicts the OSPs of the truss structure. It is observed that the proposed methods lead to different sensor layouts depending on the algorithm criteria. Thus, it can be concluded that the OSP algorithm meets the measurement requirements for various methods, such as structural damage detection, system identification, and vibration control.
A 65 nm Duplex Transconductance Path Up-Conversion Mixer for 24 GHz Automotive Short-Range Radar Sensor Applications
Authors: Delwar Tahesin Samira , Siddique Abrar , Biswal Manas Ranjan , Behera Prangyadarsini , Choi Yeji , Ryu Jee-Youl
Published: January 2022

A 24 GHz highly-linear upconversion mixer, based on a duplex transconductance path (DTP), is proposed for automotive short-range radar sensor applications using the 65-nm CMOS process. A mixer with an enhanced transconductance stage consisting of a DTP is presented to improve linearity. The main transconductance path (MTP) of the DTP includes a common source (CS) amplifier, while the secondary transconductance path (STP) of the DTP is implemented as an improved cross-quad transconductor (ICQT). Two inductors with a bypass capacitor are connected at the common nodes of the transconductance stage and switching stage of the mixer, which acts as a resonator and helps to improve the gain and isolation of the designed mixer. According to the measured results, at 24 GHz the proposed mixer shows that the linearity of output 1-dB compression point (OP1dB) is 3.9 dBm. And the input 1-dB compression point (IP1dB) is 0.9 dBm. Moreover, a maximum conversion gain (CG) of 2.49 dB and a noise figure (NF) of 3.9 dB is achieved in the designed mixer. When the supply voltage is 1.2 V, the power dissipation of the mixer is 3.24 mW. The mixer chip occupies an area of 0.42 mm2.
Machine Learning-Based Heavy Metal Ion Detection Using Surface-Enhanced Raman Spectroscopy
Authors: Park Seongyong , Lee Jaeseok , Khan Shujaat , Wahab Abdul , Kim Minseok
Published: January 2022

Surface-Enhanced Raman Spectroscopy (SERS) is often used for heavy metal ion detection. However, large variations in signal strength, spectral profile, and nonlinearity of measurements often cause problems that produce varying results. It raises concerns about the reproducibility of the results. Consequently, the manual classification of the SERS spectrum requires carefully controlled experimentation that further hinders the large-scale adaptation. Recent advances in machine learning offer decent opportunities to address these issues. However, well-documented procedures for model development and evaluation, as well as benchmark datasets, are missing. Towards this end, we provide the SERS spectral benchmark dataset of lead(II) nitride (Pb(NO3)2) for a heavy metal ion detection task and evaluate the classification performance of several machine learning models. We also perform a comparative study to find the best combination between the preprocessing methods and the machine learning models. The proposed model can successfully identify the Pb(NO3)2 molecule from SERS measurements of independent test experiments. In particular, the proposed model shows an 84.6% balanced accuracy for the cross-batch testing task.
Autonomous Instrumentation for Measuring Electromagnetic Radiation from Rocks in Mine Conditions—A Functional Analysis
Authors: Maniak Krzysztof , Mydlikowski Remigiusz
Published: January 2022

This paper analyses the function of an innovative integrated receiver for the measurement of electromagnetic field emissions. The autonomous receiver measures and registers the elevated emission levels of both components of the EM field originating from rocks subjected to increased mechanical stress. The receiver’s sensitivity of 60 µV/m, its dynamic range of 98 dB, and its impulse response of 0.23 V/µs were determined in laboratory conditions. Real EM field signals from hard coal samples subjected to crushing force were recorded using an autonomous receiver. The observed and recorded results confirm that the receiver operates in the full range of amplitudes of the EM field signal emitted from the rock. The results determine the band of characteristic signals for EM field emission from hard coal. The system created on the basis of autonomous EM receivers can support the existing seismic safety systems in real mine conditions by predicting the possibility of mine collapse hazards.
Effective TCP Flow Management Based on Hierarchical Feedback Learning in Complex Data Center Network
Authors: Mizutani Kimihiro
Published: January 2022

Many studies focusing on improving Transmission Control Protocol (TCP) flow control realize a more effective use of bandwidth in data center networks. They are excellent ways to more effectively use the bandwidth between clients and back-end servers. However, these schemes cannot achieve the total optimization of bandwidth use for data center networks as they do not take into account the path design of TCP flows against a hierarchical complex structure of data center networks. To address this issue, this paper proposes a TCP flow management scheme specified a hierarchical complex data center network for effective bandwidth use. The proposed scheme dynamically controls the paths of TCP flows by reinforcement learning based on a hierarchical feedback model, which obtains an optimal TCP flow establishment policy even if both the network topology and link states are more complicated. In evaluation, the proposed scheme achieved more effective bandwidth use and reduced the probability of TCP incast up to 30% than the conventional TCP flow management schemes: Variant Load Balancing (VLB), Equal Cost Multi Path (ECMP), and Intelligent Forwarding Strategy Based on Reinforcement Learning (IFS-RL) in the complex data center network.
Generosity and Environmental Protection: How Strong Is the Relationship between Giving and Sustainability?
Authors: Lazăr Adela , Sîrbu Ioana , Barth Karla , Bacter Claudia , Hatos Adrian
Published: January 2022

(1) Background: Sustainability is a crucial priority and a critical part of the modern world. Promoting pro-social values to the younger generation is an issue addressed throughout this paper. The present study aims to answer the question of whether generosity, as a positive attitude towards others, and sustainability, as a positive attitude towards the environment, are related. (2) Methods: The current research includes a sample of 4333 adolescents, ages 14 and 15, who attend schools in Bihor County, Romania. (3) Results: The regression analysis indicates a significant correlation between sustainable values, operationalized through adolescent involvement in environmental organisations, and generosity. (4) Conclusions: Sustainable behaviour can be considered a form of giving that contributes to the collective good. Our research outlines a significant need for a new set of competencies provided through a newly designed curriculum and/or through focused training, in order to cultivate generosity across cultures, ecologies, and generations; at the same time, we also highlight the significant role that the joint efforts of the school-family-library trifecta in supporting this goal.
Dynamic Flood Resilience Typology: A Systemic Transitional Adaptation from Peitou Plateau, Taiwan
Authors: Ling Tzen-Ying
Published: January 2022

Resilience practice is a place-based activity. This study incorporates the notion of “Transitional Progress” as an available scoping tool pin-pointing the human-habitat domain; the critical human resilience build-up can be identified by the site-specific and locally adapted practice as the residents’ perception and interaction within the local geographical character are examined. The assessment framework is proposed as a measurable process, followed by an adaptive cycle valuation performed for each of the scales at the different transitional stages. This resilience varies from the degree and time exposed to flood and the resident’s respective responses regarding people, community, and place; accordingly, the semi-structured interview documented respondents’ self-evaluation from the Peitou Plateau in Taipei. The study ascertained that in the face of climate risks: (1) adaptive measures aided and enhanced the information gathered for risk impact is based on the residents’ perception of the habitat and human domain (2) adaptive capacity assessment is an effective mean in understanding residents’ mitigation will and confidence, and (3) community ability to reflect on past actual time scenario. Most importantly, the assessment framework contributes to understanding local adaptation practice and contributes toward the sustainability of the urbanity.
Online Learning Platforms and Covenant University Students’ Academic Performance in Practical Related Courses during COVID-19 Pandemic
Authors: Adeyeye Babatunde , Ojih Success Emmanuel , Bello Damilola , Adesina Evaristus , Yartey Darlynton , Ben-Enukora Charity , Adeyeye Queen
Published: January 2022

This study examines the effectiveness of online learning platforms (Zoom and Moodle) and their effect on the academic performance of Covenant University, Ota, Nigeria, students studying practical-related courses during COVID-19. This study specifically seeks to determine students’ attitudes towards online learning platforms, investigate the effectiveness of these platforms on practical-related courses as well as ascertain the effect of Zoom and Moodle platforms on the students’ academic performance during the Pandemic. Data were gathered through a survey of 380 CU students through the purposive sampling technique to pick students offering practical related courses. Results show that due to the effectiveness of the platforms (Zoom and Moodle) and the positive communication between lecturers and students via these platforms, students would like to see online learning continually adopted after the COVID-19 pandemic. Findings further show that students had no difficulties using these platforms. Due to the sheer adaptability of the online learning platforms used during the pandemic, the usage of Zoom and Moodle had a favorable impact on student’s academic achievement in practical-related courses. The study concludes that distance learning is a future direction in teaching practical-related courses because of the flexible nature of the platforms. Thus, universities in this part of the world should invest more in online education platforms to maintain academic continuity, especially during times of emergency.
Heritage and Diversity: Values in European Heritage Management Reflected in Award-Winning Best Practices
Authors: van den Dries Monique H. , Kerkhof Miyuki J. H. , Homme Sunniva T.
Published: January 2022

The EU_CUL research network project, which is a collaboration of academics in heritage studies and in pedagogy, explored the use of cultural heritage for fostering social responsibility in higher education (Erasmus + project. In this context, research was conducted on inspirational examples and best practices in heritage management that include social and other societal values of heritage. This included award winning heritage practices in Europe. Heritage awards have, as a good practice assessment methodology, the potential to promote particular implemented practices. They can therefore help us find out what is considered ‘best practices’ in heritage management. An analysis of these practices also enables us to identify patterns, trends and potential biases. Sub-questions posed were: what is considered a ‘best practice’ in heritage awards? What kind of practices get these prizes and recognitions? What kinds of heritage are included and get the most attention? To what extent is the diversity of heritage, values and individuals in Europe represented? This chapter will discuss the results of this analysis of heritage awards and critically discuss the patterns that emerge and how this relates to governance and leadership in heritage management. The research is limited to Europe, it focuses on EAA and Europa Nostra, thus national prizes were not included.
GIS-Based Decision Support System for Safe and Sustainable Building Construction Site in a Mountainous Region
Authors: Mallick Javed , Ibnatiq Abdulaziz Awad , Kahla Nabil Ben , Alqadhi Saeed , Singh Vijay P. , Hoa Pham Viet , Hang Hoang Thi , Hong Nguyen Van , Le Hoang Anh
Published: January 2022

The site selection process for a building entails evaluating a variety of factors with varying degrees of importance or percentage influence. In order to ensure that critical site selection factors are not overlooked, a methodology for calculating a building’s safe site selection must be developed. The study identified three broad aspects widely considered in site selection, namely environmental, physical, and socioeconomic criteria. To assess the safest site selection of residential building construction for sustainable urban growth, we used GIS-based multi-criteria decision-making approach that combined Fuzzy-AHP and weighted linear combination (WLC) aggregation method used to calculate the SSPZ. The final safe site suitability map was generated by aggregating all aspects such as geophysical, socio-economic and Geo-environmental thematic layers and their associated Fuzzy-AHP weights using the weighted linear combination method. The sites potential index’s mean value of 0.513 with standard deviation of 0.340, minimum and maximum GeoPhySSSI are 0.0 and 0.91, respectively, SSS index is classified into zones by histogram profile using natural breaks (jenks)” Subsequently, safe sites identified and divided into six classes namely no construction, very low suitable site low suitable site, moderate suitable site, high suitable site, and very high suitable site.“ According to the statistical analysis, 3.64% and 32.12% of the total area were under very high and high SSSZ, while 26.40% and 6.22% accounted to the moderate and low suitable potential, respectively” Our findings suggest that integrating the fuzzy collection with AHP is highly desirable in terms of alternative and decision-making effectiveness. The study reveals that the areas of high and moderate suitability are located near existing habitant area, major roads, and educational and health services; they are not located in restricted/protected areas or are vulnerable to natural hazards. The findings indicate that unsuitable and less-suitable land uses such as vegetation, protected areas, and agriculture lands cover nearly one-third area of Abha-Khamis Mushyet regions, implying that using Fuzzy-AHP and GIS techniques will significantly aid in the conservation of the environment. This would significantly mitigate adverse effects on the ecosystem and climate.
The Differences in Physical Activity Preferences and Practices among High versus Low Active Adolescents in Secondary Schools
Authors: Frömel Karel , Groffik Dorota , Kudláček Michal , Šafář Michal , Zwierzchowska Anna , Mitáš Josef
Published: January 2022

This study aimed to (a) identify the differences in the preferred, practiced, and organized physical activity (PA) between high and low physically active Czech and Polish boys and girls and to (b) identify which types of PA are likely to be recommended by low active boys and girls. The research was carried out between 2010 and 2019 in the Czech Republic and Poland and included 6619 participants aged 15 to 19 years. The preferences and practices of the different types of PA and participation in organized PA were identified using a PA preference questionnaire and weekly PA was identified using the International Physical Activity Questionnaire-long form. Czech and Polish boys and girls who were low active preferred less physically demanding and more health-oriented PA compared with high active individuals. Power exercises and participation in organized PA are the most significant predictors of achieving at least 3 × 20 min of vigorous PA per week among low active individuals in both countries. Monitoring the trends in the preferred and practiced types of PA among boys and girls is crucial for the effective promotion of PA to low active boys and girls and positive changes in physical education and school health policy.
Innovation and Patenting within Containerized Liner Shipping
Authors: Chlomoudis Constantinos , Styliadis Theodore
Published: January 2022

Increasingly, in many industries, companies commercialize their technology and innovations through patenting to gain an edge over competition. Within the maritime sector, while literature on innovation is expanding, issues related to the importance of intangible assets, such as patenting, for the participant firms of the industry remain unaddressed. Utilizing innovational frameworks and patent data withdrawn from European Patent Organization’s (EPO’s) database, the aim of this paper is to investigate the innovative level, in terms of patents granted, of incumbent market actors in liner shipping. Apart from patent counts, this exercise sheds light on the areas to which these patents apply, providing a classification while also investigating additional attributes which relate to patent citations, investors and applicants. Although results indicate a varying degree of utilization of the patenting system amongst liner carriers, they nonetheless affirm to some extent that knowledge creation is a valuable tool in the arsenal of some liner carriers, and that patenting is one of the various means utilized to enhance their market position and achieve a sustained competitive advantage. In addition, findings suggest that liner carriers’ innovative efforts have, based on the forward citations received, some significance, while they focus primarily the development of patented technologies which enhance the operational efficiency of their vessels. In this respect, the investigation undertaken sheds some light and provides a novel perspective on understanding the behaviour and innovative propensity of liner shipping companies.
Reliability as a Key Driver for a Sustainable Design of Adaptive Load-Bearing Structures
Authors: Efinger Dshamil , Ostertag Andreas , Dazer Martin , Borschewski David , Albrecht Stefan , Bertsche Bernd
Published: January 2022

The consumption of construction materials and the pollution caused by their production can be reduced by the use of reliable adaptive load-bearing structures. Adaptive load-bearing structures are able to adapt to different load cases by specifically manipulating internal stresses using actuators installed in the structure. One main aspect of quality is reliability. A verification of reliability, and thus the safety of conventional structures, was a design issue. When it comes to adaptive load-bearing structures, the material savings reduce the stiffness of the structure, whereby integrated actuators with sensors and a control take over the stiffening. This article explains why the conventional design process is not sufficient for adaptive load-bearing structures and proposes a method for demonstrating improved reliability and environmental sustainability. For this purpose, an exemplary adaptive load-bearing structure is introduced. A linear elastic model, simulating tension in the elements of the adaptive load-bearing structure, supports the analysis. By means of a representative local load-spectrum, the operating life is estimated based on Woehler curves given by the Eurocode for the critical notches. Environmental sustainability is increased by including reliability and sustainability in design. For an exemplary high-rise adaptive load-bearing structure, this increase is more than 50%.
Systematic Observation of Corner Kick Strategies in Portuguese Football Players
Authors: Gouveia Vítor , Duarte João P. , Sarmento Hugo , Freitas José , Rebelo-Gonçalves Ricardo , Amaro Nuno , Matos Rui , Antunes Raúl , Field Adam , Monteiro Diogo
Published: January 2022

Set pieces are important for the success of football teams, with the corner kick being one of the most game defining events. The aim of this research was twofold: (1) to analyze the corner kicks of a senior football amateur team, and (2) to compare the corner kicks of successful and unsuccessful teams (of the 2020/21 sporting season). In total, 500 corners were observed using a bespoke notational analysis tool, using a specific observational instrument tool (8 criteria; 25 categories). Out of the 500 corner kicks, 6% resulted in a goal. A greater number of direct corners using inswing trajectories were performed (n = 54%). Corners were delivered to central and front post areas most frequently (n = 79%). Five attackers were most predominantly used for offensive corners (n = 58%), but defenders won the ball more frequently (n = 44%). Attempts at goal occurred following a corner most commonly from outside of the box (n = 7%). Goals were scored most frequently with the foot (n = 16%) and head (n = 15%). Successful teams are more effective at reaching the attackers and score more goals directly from corners. Unsuccessful teams deliver more corner kicks out of play, the first touch is more frequently from the opposition defenders, and fewe goals are scored from corner kicks. The study provides an insight into the determining factors and patterns that influence corner kicks and success in football matches. This information should be used by coaches to prepare teams for both offensive and defensive corner kicks to increase team success and match outcomes.
People’s Perception of Experimental Installations for Sustainable Energy: The Case of IFMIF-DONES
Authors: Troya Zaida , Esteban Rafael , Herrera-Viedma Enrique , Peña-García Antonio
Published: January 2022

Nuclear facilities are a main milestone in the long way to sustainable energy. Beyond the well-known fission centrals, the necessity of cleaner, more efficient and almost unlimited energy reducing waste to almost zero is a major challenge in the next decades. This is the case with nuclear fusion. Different experimental installations to definitively control this nuclear power are proliferating in different countries. However, citizens in the surroundings of cities and villages where these installations are going to be settled are frequently reluctant because of doubts about the expected benefits and the potential hazards. In this framework, knowing the opinion of people and their perception of experimental fusion facilities is essential for researchers, administrations and rulemaking bodies planning future fusion plants. This is the case for IFMIF-DONES, a neutron irradiation facility to determine the most suitable materials for the future fusion reactors. The construction of this installation is starting in Escúzar (Granada, Spain), and this work presents a large survey among 311 people living or working in the village. Their perception, fears, hopes and other variables are analyzed, and the conclusions for future installations and their impact on the energy policy are presented.
Valuing the Impact of Forest Disturbances on the Climate Regulation Service of Western U.S. Forests
Authors: Marcos-Martinez Raymundo , Sánchez José J. , Srivastava Lorie , Soonsawad Natthanij , Bachelet Dominique
Published: January 2022

The protection and expansion of forest carbon sinks are critical to achieving climate-change mitigation targets. Yet, the increasing frequency and severity of forest disturbances challenge the sustainable provision of forest services. We investigated patterns of forest disturbances’ impacts on carbon sinks by combining spatial datasets of forest carbon sequestration from biomass growth and emissions from fire and bark beetle damage in the western United States (U.S.) and valued the social costs of forest carbon losses. We also examined potential future trends of forest carbon sinks under two climate-change projections using a global vegetation model. We found that forest carbon losses from bark-beetle damage were larger than emissions from fires between 2003 and 2012. The cumulative social costs of forest carbon losses ranged from USD 7 billion to USD 72 billion, depending on the severity of global warming and the discount rate. Forest carbon stocks could increase around 5% under Representative Concentration Pathway (RCP) 4.5 or 7% under RCP 8.5 by 2091 relative to 2011 levels, mostly in forests with high net primary productivity. These results indicate that spatially explicit management of forest disturbances may increase forest carbon sinks, thereby improving opportunities to achieve critical climate-change mitigation goals.
A Statistical Framework for Evaluating the Effectiveness of Vegetation Management in Reducing Power Outages Caused during Storms in Distribution Networks
Authors: Taylor William O. , Watson Peter L. , Cerrai Diego , Anagnostou Emmanouil
Published: January 2022

This paper develops a statistical framework to analyze the effectiveness of vegetation management at reducing power outages during storms of varying severity levels. The framework was applied on the Eversource Energy distribution grid in Connecticut, USA based on 173 rain and wind events from 2005–2020, including Hurricane Irene, Hurricane Sandy, and Tropical Storm Isaias. The data were binned by storm severity (high/low) and vegetation management levels, where a maximum applicable length of vegetation management for each circuit was determined, and the data were divided into four bins based on the actual length of vegetation management performed divided by the maximum applicable value (0–25%, 25–50%, 50–75%, and 75–100%). Then, weather and overhead line length normalized outage statistics were taken for each group. The statistics were used to determine the effectiveness of vegetation management and its dependence on storm severity. The results demonstrate a higher reduction in damages for lower-severity storms, with a reduction in normalized outages between 45.8% and 63.8%. For high-severity events, there is a large increase in effectiveness between the highest level of vegetation management and the two lower levels, with 75–100% vegetation management leading to a 37.3% reduction in trouble spots. Yet, when evaluating system reliability, it is important to look at all storms combined, and the results of this study provide useful information on total annual trouble spots and allow for analysis of how various vegetation management scenarios would impact trouble spots in the electric grid. This framework can also be used to better understand how more rigorous vegetation management standards (applying ETT) help reduce outages at an individual event level. In future work, a similar framework may be used to evaluate other resilience improvements.
Trends in Emission Inventory of Marine Traffic for Port of Haifa
Authors: Ben-Hakoun Elyakim , Van De Voorde Eddy , Shiftan Yoram
Published: January 2022

Located in the Middle East, Haifa Port serves both local and international trade interests (from Asia, Europe, America, Africa, etc.). Due to its strategic location, the port is part of the Belt and Road initiative. This research investigates Haifa Port’s emissions contribution to the existing daily emission inventory level in the area. This research is based on a developed full bottom-up model framework that looks at the single vessel daily voyage through its port call stages. The main data sources for vessel movements used in this research are the Israel Navy’s movements log and the Israel Administration of Shipping and Ports’ (ASP) operational vessel movements and cargo log. The Fuel Consumption (FC) data and Sulfur Content (SC) levels are based on official Israel ASP survey data. The observation years in this research are 2010–2018, with a focus on the Ocean-Going Vessel (OGV) type only. The results show that the vessel fleet calling at Israel ports mainly comprises vessels that have a lower engine tier grade (i.e., Tier 0 and 1), which is considered a heavy contributor to nitrogen oxide (NOx) pollution. The study recommends an additional cost charged (selective tariff) to reflect the external social cost linked to the single vessel air pollution combined with supportive technological infrastructure and economic incentive tools (e.g., electric subsidy) to attract or influence vessel owners to assign vessels equipped with new engine tier grades for calls at Israeli ports.
Operation Zone Analysis of the Voltage Source Converter Based on the Influence of Different Grid Strengths
Authors: Wang Wenning , Li Kejun , Sun Kaiqi , Wang Jianjian
Published: January 2022

With the increasing penetration of renewable energy into the power system, the voltage source converter (VSC) for integrating renewable energy has become the most common device in the electric network. However, the operating stability of the VSC is strongly dependent on its operating control strategy, which is also highly related to the strength of the AC system. Choosing the control strategy of VSC for different strengths of AC systems becomes an essential issue for maintaining the symmetry between high proportion of renewable energy integration and stable operation of AC system. In order to obtain the operation zones of the control strategies of the VSC under different strengths of AC system, in this paper, the two common VSC control strategies, vector current control (VCC) and power synchronization control (PSC), are compared. Firstly, the principle of VCC and PSC are introduced. Then, based on the short circuit ratio (SCR) and the power limit calculation under steady-state conditions of the VSC, the operation zones of the vector current control and power synchronization control are proposed. Finally, a medium voltage modular multilevel converter (MMC) system was built in PSCAD/EMTDC and the proposed operation zones of the VCC and PSC were tested by changing the SCR of the modified IEEE 33 bus system and analyzed via the critical short circuit ratio (CSCR) analysis, the small-signal stability analysis, and transient stability analysis. The results indicate that, as the SCR decreases, the VSC based on VCC is gradually worked into unstable conditions, while the stability of VSC based on PSC gradually increases. The analysis results provide a criterion for the converter operation strategy change that could significantly improve the operating stability of the VSC in the power system and realize the symmetry of the stability of the converter and the change of the strength of the AC system.
Capturing a Change in the Covariance Structure of a Multivariate Process
Authors: Bekker Andriette , Ferreira Johannes T. , Human Schalk W. , Adamski Karien
Published: January 2022

This research is inspired from monitoring the process covariance structure of q attributes where samples are independent, having been collected from a multivariate normal distribution with known mean vector and unknown covariance matrix. The focus is on two matrix random variables, constructed from different Wishart ratios, that describe the process for the two consecutive time periods before and immediately after the change in the covariance structure took place. The product moments of these constructed random variables are highlighted and set the scene for a proposed measure to enable the practitioner to calculate the run-length probability to detect a shift immediately after a change in the covariance matrix occurs. Our results open a new approach and provides insight for detecting the change in the parameter structure as soon as possible once the underlying process, described by a multivariate normal process, encounters a permanent/sustained upward or downward shift.
An Efficient Hyperparameter Control Method for a Network Intrusion Detection System Based on Proximal Policy Optimization
Authors: Han Hyojoon , Kim Hyukho , Kim Yangwoo
Published: January 2022

The complexity of network intrusion detection systems (IDSs) is increasing due to the continuous increases in network traffic, various attacks and the ever-changing network environment. In addition, network traffic is asymmetric with few attack data, but the attack data are so complex that it is difficult to detect one. Many studies on improving intrusion detection performance using feature engineering have been conducted. These studies work well in the dataset environment; however, it is challenging to cope with a changing network environment. This paper proposes an intrusion detection hyperparameter control system (IDHCS) that controls and trains a deep neural network (DNN) feature extractor and k-means clustering module as a reinforcement learning model based on proximal policy optimization (PPO). An IDHCS controls the DNN feature extractor to extract the most valuable features in the network environment, and identifies intrusion through k-means clustering. Through iterative learning using the PPO-based reinforcement learning model, the system is optimized to improve performance automatically according to the network environment, where the IDHCS is used. Experiments were conducted to evaluate the system performance using the CICIDS2017 and UNSW-NB15 datasets. In CICIDS2017, an F1-score of 0.96552 was achieved and UNSW-NB15 achieved an F1-score of 0.94268. An experiment was conducted by merging the two datasets to build a more extensive and complex test environment. By merging datasets, the attack types in the experiment became more diverse and their patterns became more complex. An F1-score of 0.93567 was achieved in the merged dataset, indicating 97% to 99% performance compared with CICIDS2017 and UNSW-NB15. The results reveal that the proposed IDHCS improved the performance of the IDS by automating learning new types of attacks by managing intrusion detection features regardless of the network environment changes through continuous learning.
An Integrative Analysis of Transcriptomics and Proteomics Reveals Novel Insights into the Response in the Midgut of Spodoptera frugiperda Larvae to Vip3Aa
Authors: Jin Minghui , Shan Yinxue , Peng Yan , Wang Ping , Li Qi , Yu Songmiao , Zhang Lei , Xiao Yutao
Published: January 2022

The insecticidal Vip3 proteins, secreted by Bacillus thuringiensis (Bt) during its vegetative growth phase, are currently used in Bt crops to control insect pests, and are genetically distinct from known insecticidal Cry proteins. Compared with Cry toxins, the mechanisms of Vip3 toxins are still poorly understood. Here, the responses of Spodoptera frugiperda larvae after Vip3Aa challenge are characterized. Using an integrative analysis of transcriptomics and proteomics, we found that Vip3Aa has enormous implications for various pathways. The downregulated genes and proteins were mainly enriched in metabolic pathways, including the insect hormone synthesis pathway, whereas the upregulated genes and proteins were mainly involved in the caspase-mediated apoptosis pathway, along with the MAPK signaling and endocytosis pathways. Moreover, we also identified some important candidate genes involved in apoptosis and MAPKs. The present study shows that exposure of S. frugiperda larvae to Vip3Aa activates apoptosis pathways, leading to cell death. The results will promote our understanding of the host response process to the Vip3Aa, and help us to better understand the mode of action of Vip3A toxins.