bluuebunny/crossref_metadata_2025 huggingface dataset:
Unsupervised Image-to-Image Translation: A Review
Authors: Hoyez Henri , Schockaert Cédric , Rambach Jason , Mirbach Bruno , Stricker Didier
Published: November 2022

Supervised image-to-image translation has been proven to generate realistic images with sharp details and to have good quantitative performance. Such methods are trained on a paired dataset, where an image from the source domain already has a corresponding translated image in the target domain. However, this paired dataset requirement imposes a huge practical constraint, requires domain knowledge or is even impossible to obtain in certain cases. Due to these problems, unsupervised image-to-image translation has been proposed, which does not require domain expertise and can take advantage of a large unlabeled dataset. Although such models perform well, they are hard to train due to the major constraints induced in their loss functions, which make training unstable. Since CycleGAN has been released, numerous methods have been proposed which try to address various problems from different perspectives. In this review, we firstly describe the general image-to-image translation framework and discuss the datasets and metrics involved in the topic. Furthermore, we revise the current state-of-the-art with a classification of existing works. This part is followed by a small quantitative evaluation, for which results were taken from papers.
Monocular Pose Estimation of an Uncooperative Spacecraft Using Convexity Defect Features
Authors: Han Haeyoon , Kim Hanik , Bang Hyochoong
Published: November 2022

Spacecraft relative pose estimation for an uncooperative spacecraft is challenging because the target spacecraft neither provides sensor information to a chaser spacecraft nor contains markers that assist vision-based navigation. Moreover, the chaser does not have prior pose estimates when initiating the pose estimation. This paper proposes a new monocular pose estimation algorithm that addresses these issues in pose initialization situations for a known but uncooperative target spacecraft. The proposed algorithm finds convexity defect features from a target image and uses them as cues for matching feature points on the image to the points on the known target model. Based on this novel method for model matching, it estimates a pose by solving the PnP problem. Pose estimation simulations are carried out in three test scenarios, and each assesses the estimation accuracy and initialization performance by varying relative attitudes and distances. The simulation results show that the algorithm can estimate the poses of spacecraft models when a solar panel length and the number of solar panels are changed. Furthermore, a scenario considering the surface property of the spacecraft emphasizes that robust feature detection is essential for accurate pose estimation. This algorithm can be used for proximity operations with a known but uncooperative target spacecraft. Specifically, one of the main applications is relative navigation for on-orbit servicing.
SCA: Search-Based Computing Hardware Architecture with Precision Scalable and Computation Reconfigurable Scheme
Authors: Chang Liang , Zhao Xin , Zhou Jun
Published: November 2022

Deep neural networks have been deployed in various hardware accelerators, such as graph process units (GPUs), field-program gate arrays (FPGAs), and application specific integrated circuit (ASIC) chips. Normally, a huge amount of computation is required in the inference process, creating significant logic resource overheads. In addition, frequent data accessions between off-chip memory and hardware accelerators create bottlenecks, leading to decline in hardware efficiency. Many solutions have been proposed to reduce hardware overhead and data movements. For example, specific lookup-table (LUT)-based hardware architecture can be used to mitigate computing operation demands. However, typical LUT-based accelerators are affected by computational precision limitation and poor scalability issues. In this paper, we propose a search-based computing scheme based on an LUT solution, which improves computation efficiency by replacing traditional multiplication with a search operation. In addition, the proposed scheme supports different precision multiple-bit widths to meet the needs of different DNN-based applications. We design a reconfigurable computing strategy, which can efficiently adapt to the convolution of different kernel sizes to improve hardware scalability. We implement a search-based architecture, namely SCA, which adopts an on-chip storage mechanism, thus greatly reducing interactions with off-chip memory and alleviating bandwidth pressure. Based on experimental evaluation, the proposed SCA architecture can achieve 92%, 96% and 98% computational utilization for computational precision of 4 bit, 8 bit and 16 bit, respectively. Compared with state-of-the-art LUT-based architecture, the efficiency can be improved four-fold.
Research on Trajectory Recognition and Control Technology of Real-Time Tracking Welding
Authors: Zhao Xiaohui , Zhang Yaowen , Wang Hao , Liu Yu , Zhang Bao , Hu Shaoyang
Published: November 2022

Real-time tracking welding with the assistance of structured light vision enhances the intelligence of robotic welding, which significantly shortens teaching time and guarantees accuracy for user-customized product welding. However, the robustness of most image processing algorithms is deficient during welding practice, and the security regime for tracking welding is not considered in most trajectory recognition and control algorithms. For these two problems, an adaptive feature extraction algorithm was proposed, which can accurately extract the seam center from the continuous, discontinuous or fluctuating laser stripes identified and located by the CNN model, while the prior model can quickly remove a large amount of noise and interference except the stripes, greatly improving the extraction accuracy and processing speed of the algorithm. Additionally, the embedded Pauta criterion was used to segmentally process the center point data stream and to cyclically eliminate outliers and further ensure the accuracy of the welding reference point. Experimental results showed that under the guarantee of the above-mentioned seam center point extraction and correction algorithms, the tracking average error was 0.1 mm, and even if abnormal trajectory points existed, they did not cause welding torch shaking, system interruption or other accidents.
Reflection-Aware Generation and Identification of Square Marker Dictionaries
Authors: Garrido-Jurado Sergio , Garrido Juan , Jurado-Rodríguez David , Vázquez Francisco , Muñoz-Salinas Rafael
Published: November 2022

Square markers are a widespread tool to find correspondences for camera localization because of their robustness, accuracy, and detection speed. Their identification is usually based on a binary encoding that accounts for the different rotations of the marker; however, most systems do not consider the possibility of observing reflected markers. This case is possible in environments containing mirrors or reflective surfaces, and its lack of consideration is a source of detection errors, which is contrary to the robustness expected from square markers. This is the first work in the literature that focuses on reflection-aware square marker dictionaries. We present the derivation of the inter-marker distance of a reflection-aware dictionary and propose new algorithms for generating and identifying such dictionaries. Additionally, part of the proposed method can be used to optimize preexisting dictionaries to take reflection into account. The experimentation carried out demonstrates how our proposal greatly outperforms the most popular predefined dictionaries in terms of inter-marker distance and how the optimization process significantly improves them.
Using Statistical Parametric Mapping to Compare the Propulsion of Age-Group Swimmers in Front Crawl Acquired with the Aquanex System
Authors: Morais Jorge E. , Marinho Daniel A. , Oliveira João P. , Sampaio Tatiana , Lopes Tiago , Barbosa Tiago M.
Published: November 2022

Understanding the difference in each upper limb between age groups can provide deeper insights into swimmers’ propulsion. This study aimed to: (1) compare swimming velocity and a set of kinematical variables between junior and juvenile swimmers and (2) compare the propulsion outputs through discrete and continuous analyses (Statistical Parametric Mapping—SPM) between junior and juvenile swimmers for each upper limb (i.e., dominant and non-dominant). The sample was composed of 22 male swimmers (12 juniors with 16.35 ± 0.74 years; 10 juveniles with 15.40 ± 0.32 years). A set of kinematic and propulsion variables was measured at maximum swimming velocity. Statistical Parametric Mapping was used as a continuous analysis approach to identify differences in the propulsion of both upper limbs between junior and juvenile swimmers. Junior swimmers were significantly faster than juveniles (p = 0.04, d = 0.86). Although juniors showed higher propulsion values, the SPM did not reveal significant differences (p < 0.05) for dominant and non-dominant upper limbs between the two age groups. This indicates that other factors (such as drag) may be responsible for the difference in swimming velocity. Coaches and swimmers should be aware that an increase in propulsion alone may not immediately lead to an increase in swimming velocity.
EEG-Based Emotion Classification Using Stacking Ensemble Approach
Authors: Chatterjee Subhajit , Byun Yung-Cheol
Published: November 2022

Rapid advancements in the medical field have drawn much attention to automatic emotion classification from EEG data. People’s emotional states are crucial factors in how they behave and interact physiologically. The diagnosis of patients’ mental disorders is one potential medical use. When feeling well, people work and communicate more effectively. Negative emotions can be detrimental to both physical and mental health. Many earlier studies that investigated the use of the electroencephalogram (EEG) for emotion classification have focused on collecting data from the whole brain because of the rapidly developing science of machine learning. However, researchers cannot understand how various emotional states and EEG traits are related. This work seeks to classify EEG signals’ positive, negative, and neutral emotional states by using a stacking-ensemble-based classification model that boosts accuracy to increase the efficacy of emotion classification using EEG. The selected features are used to train a model that was created using a random forest, light gradient boosting machine, and gradient-boosting-based stacking ensemble classifier (RLGB-SE), where the base classifiers random forest (RF), light gradient boosting machine (LightGBM), and gradient boosting classifier (GBC) were used at level 0. The meta classifier (RF) at level 1 is trained using the results from each base classifier to acquire the final predictions. The suggested ensemble model achieves a greater classification accuracy of 99.55%. Additionally, while comparing performance indices, the suggested technique outperforms as compared with the base classifiers. Comparing the proposed stacking strategy to state-of-the-art techniques, it can be seen that the performance for emotion categorization is promising.
Research on the Application of Multi-Source Information Fusion in Multiple Gait Pattern Transition Recognition
Authors: Guo Chaoyue , Song Qiuzhi , Liu Yali
Published: November 2022

Multi-source information fusion technology is a kind of information processing technology which comprehensively processes and utilizes multi-source uncertain information. It is an effective scheme to solve complex pattern recognition and improve classification performance. This study aims to improve the accuracy and robustness of exoskeleton gait pattern transition recognition in complex environments. Based on the theory of multi-source information fusion, this paper explored a multi-source information fusion model for exoskeleton gait pattern transition recognition in terms of two aspects of multi-source information fusion strategy and multi-classifier fusion. For eight common gait pattern transitions (between level and stair walking and between level and ramp walking), we proposed a hybrid fusion strategy of multi-source information at the feature level and decision level. We first selected an optimal feature subset through correlation feature extraction and feature selection algorithm, followed by the feature fusion through the classifier. We then studied the construction of a multi-classifier fusion model with a focus on the selection of base classifier and multi-classifier fusion algorithm. By analyzing the classification performance and robustness of the multi-classifier fusion model integrating multiple classifier combinations with a number of multi-classifier fusion algorithms, we finally constructed a multi-classifier fusion model based on D-S evidence theory and the combination of three SVM classifiers with different kernel functions (linear, RBF, polynomial). Such multi-source information fusion model improved the anti-interference and fault tolerance of the model through the hybrid fusion strategy of feature level and decision level and had higher accuracy and robustness in the gait pattern transition recognition, whose average recognition accuracy for eight gait pattern transitions reached 99.70%, which increased by 0.15% compared with the highest average recognition accuracy of the single classifier. Moreover, the average recognition accuracy in the absence of different feature data reached 97.47% with good robustness.
From Sensor Data to Educational Insights
Authors: Ruipérez-Valiente José A. , Martínez-Maldonado Roberto , Di Mitri Daniele , Schneider Jan
Published: November 2022

Technology is gradually becoming an integral part of learning at all levels of educational [...]
Sagnac with Double-Sense Twisted Low-Birefringence Standard Fiber as Vibration Sensor
Authors: Santiago-Hernández Héctor , Beltrán-González Anuar Benjamín , Mora-Nuñez Azael , Bravo-Medina Beethoven , Pottiez Olivier
Published: November 2022

In this work, we study a double-sense twisted low-birefringence Sagnac loop structure as a sound/vibration sensing device. We study the relation between the adjustments of a wave retarder inside the loop (which allows controlling the transmission characteristic to deliver 10, 100, and 300 μW average power at the output of the system) and the response of the Sagnac sensor to vibration frequencies ranging from 0 to 22 kHz. For a 300 m loop Sagnac, two sets of experiments were carried out, playing at the same time all the sound frequencies mixed for ∼1 s, and playing a sweep of frequencies for 30 s. In both cases, the time- and frequency-domain transmission amplitudes are larger for an average power of 10 μW, and smaller for an average power of 300 μW. For mixed frequencies, the Fourier analysis shows that the Sagnac response is larger for low frequencies (from 0 to ∼5 kHz) than for high frequencies (from ∼5 kHz to ∼22 kHz). For a sweep of frequencies, the results reveal that the interferometer perceives all frequencies. However, beyond ∼2.5 kHz, harmonics are present each ∼50 Hz, revealing that some resonances are present. The results about the influence of the power transmission through the polarizer and power emission of laser diode (LD) on the Sagnac interferometer response at high frequencies reveal that our system is robust, and the results are highly reproducible, and harmonics do not depend on the state of polarization at the input of the Sagnac interferometer. Furthermore, increasing the LD output power from 5 mW to 67.5 mW allows us to eliminate noisy signals at the system output. in our setup, the minimum sound level detected was 56 dB. On the other hand, the experimental results of a 10 m loop OFSI reveal that the response at low frequencies (1.5 kHz to 5 kHz) is minor compared with the 300 m loop OFSI. However, the response at high frequencies is low but still enables the detection of these frequencies, yielding the possibility of tuning the response of the vibration sensor by varying the length of the Sagnac loop.
Design and Implementation of Embedded-Based Vein Image Processing System with Enhanced Denoising Capabilities
Authors: Lee Jongwon , Jeong Incheol , Kim Kapyol , Cho Jinsoo
Published: November 2022

In general, it is very difficult to visually locate blood vessels for intravenous injection or surgery. In addition, if vein detection fails, physical and mental pain occurs to the patient and leads to financial loss in the hospital. In order to prevent this problem, NIR-based vein detection technology is developing. The proposed study combines vein detection and digital hair removal to eliminate body hair, a noise that hinders the accuracy of detection, improving the performance of the entire algorithm by about 10.38% over existing systems. In addition, as a result of performing venous detection of patients without body hair, 5.04% higher performance than the existing system was detected, and the proposed study results were verified. It is expected that the use of devices to which the proposed study is applied will provide more accurate vascular maps in general situations.
A Fissure-Aided Registration Approach for Automatic Pulmonary Lobe Segmentation Using Deep Learning
Authors: Xue Mengfan , Han Lu , Song Yiran , Rao Fan , Peng Dongliang
Published: November 2022

The segmentation of pulmonary lobes is important in clinical assessment, lesion location, and surgical planning. Automatic lobe segmentation is challenging, mainly due to the incomplete fissures or the morphological variation resulting from lung disease. In this work, we propose a learning-based approach that incorporates information from the local fissures, the whole lung, and priori pulmonary anatomy knowledge to separate the lobes robustly and accurately. The prior pulmonary atlas is registered to the test CT images with the aid of the detected fissures. The result of the lobe segmentation is obtained by mapping the deformation function on the lobes-annotated atlas. The proposed method is evaluated in a custom dataset with COPD. Twenty-four CT scans randomly selected from the custom dataset were segmented manually and are available to the public. The experiments showed that the average dice coefficients were 0.95, 0.90, 0.97, 0.97, and 0.97, respectively, for the right upper, right middle, right lower, left upper, and left lower lobes. Moreover, the comparison of the performance with a former learning-based segmentation approach suggests that the presented method could achieve comparable segmentation accuracy and behave more robustly in cases with morphological specificity.
Development of a Chemiluminescent Method in a Microfluidic Device for Ultrasensitive Determination of Okadaic Acid with Highly Efficient Aptamer-Based Isolation
Authors: Mao Libing , Zhao Qi , Yang Yan , Wang Sai , Dong Yiyang
Published: November 2022

Rapid detection of okadaic acid (OA) in shellfish is crucial for practical application in food safety analysis. In order to establish a rapid, delicate detection scheme, an OA aptamer was utilized to quickly capture OA from the sample solution with polystyrene microspheres as solid phase carriers, and an inner-microchannel dam structure was designed to intercept the aptamer-functionalized microspheres to achieve the separation of OA for detection. Horseradish peroxidase (HRP) is utilized to catalyze the luminescence reaction of luminol-H2O2 solution. Through the direct competition for the aptamer between OA and OA-HRP, the rapid detection of OA can be achieved. The dynamic range of this detection method is 41.3–4.02 ng/mL, and the limit of detection (LOD) and lowest limit of quantitation (LOQ) are 12.4 pg/mL and 41.3 pg/mL, respectively. This miniaturized device enables rapid, ultrasensitive detection of OA, and demonstrates the merits of its field portability and low reagent consumption. The device can be deployed for on-site detection and analysis of marine biotoxins thereof.
The Interplay between Digitalization and Competitiveness: Evidence from European Countries
Authors: Hurduzeu Gheorghe , Lupu Iulia , Lupu Radu , Filip Radu Ion
Published: November 2022

In modern societies, digitalization plays a tremendously important role for people and businesses. Apart from an economic representation, competitiveness characterizes a society from political, cultural, or human points of view. In this article, we aim to highlight the role of digital development from a competitiveness perspective, as there are few studies related to this relationship. The empirical investigation is based on panel data analysis for European Union countries for 2017–2022, considering the digital economy and society index (DESI) and the index developed by International Institute for Management Development (IMD), respectively IMD world competitiveness index. The results obtained are reported both for general indices and for the components of DESI, presented separately for the groups of Central and Eastern European countries and Western European countries. They indicate different influences for the two groups of countries, with only a few common aspects. The most obvious is the case of skilled labor. This aspect demonstrates the link between the various dimensions of digitalization and changes in human capital development strategies, as they appear in the specialized literature.
Changes in the Regional Development of Romania (2000–2019), Measured with a Multidimensional PEESH Index
Authors: Veres Valér , Benedek József , Török Ibolya
Published: November 2022

Measuring development is a long-standing challenge in the social sciences. Although multidimensional and multivariate approaches to development present several conceptual and/or methodological problems, some studies have pointed out that the unidimensional view of economic progress has failed on a large scale. The main purpose of our article is to elaborate a multidimensional composite index called the PEESH (population, economic, education, social, and health) Development Index, for measuring socio-economic development in Romania with a territorial profile. The PEESH DI index presented in this paper contains five sub-dimensions: population dynamics, economy and labor force, education, social conditions and housing, and health and life conditions, including 22 core indicators. The components of the resulting multidimensional index were weighted using factor analysis and then aggregated transversely into a composite index. Our results show that the differentiated increase of the indicators composing the PEESH DI resulted in a certain restructuring of the development hierarchy of Romania’s counties between 2000 and 2019. These empirical facts strengthen the idea that development cannot be reduced to only economic growth, it comprises an important social dimension as well. Finally, we have strongly argued in this paper that it is time to switch from a single-sided and reductionist perspective of the measurement of regional disparities, within the framework of the Cohesion Policy in the European Union, to a wider and multidimensional perspective, reflecting the complex character of the development process.
Satellite-Based Discrimination of Urban Dynamics-Induced Local Bias from Day/Night Temperature Trends across the Nile Delta, Egypt: A Basis for Climate Change Impacts Assessment
Authors: Abbas Waleed , Hamdi Islam
Published: November 2022

The Nile Delta is the most vital region of the desert-dominated country of Egypt. Due to its prominent level of vulnerability to climate change’s negative impacts and its low capacity for adaptation and mitigation, the current study aims to provide accurate quantification of temperature change across the Nile Delta as an integral basis for sustainability and climate change impacts assessment studies. This was achieved through monitoring urban dynamics and detecting LST trends in 91 cities and their rural surroundings. The relevant local urban bias was discriminated from regional/background changes present in diurnal/nocturnal temperature records. The temperature records were then corrected/adjusted by removing this urban bias. Owing to the insufficiency of ground-based meteorological observatories, the investigation utilized moderate resolution imaging spectroradiometer (MODIS) land surface temperatures (LSTs) and Landsat-based datasets (2000–2021). The widely used Mann–Kendall test (MKT) and Theil–Sen estimator (TSE) were employed to assess trends in urban sprawl, LST time series, and the implied association. The analysis revealed that the region has experienced dramatic urbanization, where the total urban expansion was greater than two-thirds (69.1%) of the original urban area in 2000. This was accompanied by a notable warming trend in the day/night and urban/rural LST records. The nocturnal LST exhibited a warming tendency (0.072 °C year−1) larger than the diurnal equivalent (0.065 °C year−1). The urban dynamics were positively correlated with LST trends, whereas the Mediterranean Sea appeared as a significant anti-urbanization moderator, in addition to the Nile River and the prevailing northerly/northwesterly winds. The urban–rural comparison approach disclosed that the urbanization process caused a warming bias in the nighttime LST trend by 0.017 °C year−1 (21.8%) and a cooling bias in the daytime by −0.002 °C year−1 (4.4%). All results were statistically significant at a confidence level of 99%. It is recommended that studies of climate-related sustainability and climate change impact assessment in the Nile Delta should apply a distinction of urban-induced local effect when quantifying the actual regional temperature change.
Prediction of the Remaining Useful Life of a Switch Machine, Based on Multi-Source Data
Authors: Zheng Yunshui , Chen Weimin , Zhang Yaning , Bai Dengyu
Published: November 2022

Aimed at the shortcomings of a single feature to characterize the health status and accurately predict the remaining life span of the equipment, a prediction method for a switch machine, based on the weighted Mahalanobis distance (WDMD), is proposed. The method consists of two parts: the construction of a health indicator, based on the weighted Markov distance and the prediction of the remaining useful life, based on the hidden Markov model (HMM). Firstly, a kernel principal component analysis (KPCA) is used to extract the characteristics of the power curve data of the switch machine, and the characteristics with a high correlation with the degradation process are screened, according to the trend indicators. Secondly, the resulting features are combined with multi-source information, as the input, and a comprehensive health indicator (HI) is constructed by the weighted fusion of the WDMD algorithm, to characterize the degradation process of the switch machine. The degradation model of this HI is established and trained by the HMM, so as to predict the remaining life span of the equipment. Finally, the actual operation data of the railway field is selected to verify the prediction method proposed in the paper. The results show that the state recognition and the life prediction accuracy of the proposed method is higher, which can provide effective opinions for the predictive maintenance of the switch machine equipment.
A Reliability-Based Stochastic Traffic Assignment Model for Signalized Traffic Network with Consideration of Link Travel Time Correlations
Authors: Shen Liang , Wang Feiran , Chen Yueyuan , Lv Xinyi , Wen Zongliang
Published: November 2022

Traffic assignment model (TAM) is an important research issue of urban traffic design and planning. Most of the existing studies are conducted under deterministic conditions. In reality, the link travel time and waiting time at signalized intersections are stochastic due to many uncertain factors in transportation networks. Under this circumstance, this paper proposes a new travel time reliability-based user equilibrium (TRUE) traffic assignment model with consideration of link travel time correlations and waiting time at signalized intersections in stochastic traffic networks. Under the assumption that link travel times and waiting times at signalized intersections follow normal distributions, the proposed model is transformed into a variational inequality (VI) model. It is rigorously proven that there is at least one solution for the VI problem, and the method of successive average (MSA) is employed to solve the proposed model. The numerical experiments are used to illustrate the applications and effectiveness of the proposed model.
Studies on the Utilization of Marble Dust, Bagasse Ash, and Paddy Straw Wastes to Improve the Mechanical Characteristics of Unfired Soil Blocks
Authors: Sharma Tarun , Singh Sandeep , Sharma Shubham , Sharma Aman , Shukla Anand Kumar , Li Changhe , Zhang Yanbin , Eldin Elsayed Mohamed Tag
Published: November 2022

Earthen materials are the world’s oldest and cheapest construction materials. Compacted soil stabilised blocks are unfired admixed soil blocks made up of soil plus stabilisers such as binders, fibres, or a combination of both. The manufacturing and usage of cement and cement blocks raises a number of environmental and economic challenges. As a result, researchers are attempting to develop an alternative to cement blocks, and various tests on unfired admixed soil blocks have been performed. This investigation undertakes use of agricultural waste (i.e., paddy straw fiber and sugarcane bagasse ash) and industrial waste (i.e., marble dust) in manufacturing unfired admixed soil blocks. The applicability of unfired soil blocks admixed with marble dust, paddy straw fiber, and bagasse ash were studied. The marble dust level ranged from 25% to 35%, the bagasse ash content ranged from 7.5% to 12.5%, and the content of paddy straw fibre ranged from 0.8% to 1.2% by soil dry weight. Various tests were conducted on 81 mix designs of the prepared unfired admixed soil blocks to determine the mechanical properties of the blocks, followed by modeling and optimization. The characterization of the materials using XRD and XRF and of the specimens using SEM and EDS were performed for the mineral constituents and microstructural analysis. The findings demonstrate that the suggested method is a superior alternative to burned bricks for improving the mechanical properties of unfired admixed soil blocks.
Simulation Assessment of Inlet Parameters and Membrane-Surface-Structure Effects on CO2 Absorption Flux in Membrane Contactors
Authors: Garehbagh Amin Mojarad , Rajabzadeh Saeid , Shouman Mahmoud A. , Elmarghany Mohamed R. , Salem Mohamed S. , Arahman Nasrul , Mohammadi Toraj , Matsuyama Hideto
Published: November 2022

The management of global carbon dioxide (CO2) emissions is considered one of the main environmental problems facing the modern world. One of the potential techniques for CO2 capture is absorption, using membrane contactor modules. Most of the previous research that dealt with membrane contactor simulations considered the whole membrane surface as the active reaction surface. However, in this paper, a more realistic model of the membrane-contactor module is presented, taking into account the effects of the pore size and surface porosity. CO2 absorption into the monoethanolamine (MEA) solution in hollow fiber membrane-contactor modules was numerically investigated. A computational fluid dynamics simulation was established using essential basic fluid dynamics and mass transfer equations in reactive mode. An algorithmic function was used to present the relations between the CO2 absorption flux and the hollow fiber length, membrane surface pore size, and porosity. The simulation results were compared to previously obtained experimental results without using any fitting parameters, and a good agreement was found with an average error of 8.5%. The validated simulation was then used to predict the effects of the MEA inlet velocity and concentration, the membrane surface pore size, and porosity on the total CO2 absorption flux. A maximum absorption flux of about 1.8 mol/m2·s was achieved at an MEA concentration of 4 M with a pore size of 0.2 microns, a surface porosity of 1%, and an inlet velocity of 0.25 m/s. The extrapolation technique was then used to predict the values of the absorption flux at longer fiber lengths. The concentration profiles around the pores at the gas–liquid contact surface of the membrane were obtained and presented. The proposed model exhibited excellent potential to evaluate the effective reaction surface in hollow fiber membrane contactors. This model could be considered the first step to obtaining accurate predictions of the membrane contactor gas absorption performance based on its surface structure.
Knowledge or Responsibility? The Role of Media Use on Citizens’ Willingness to Pay for Environment Governance
Authors: Wang Huan
Published: November 2022

It is not that the public is unwilling to participate in environmental protection, but rather that they lack the appropriate information. The media offers an alternative explanatory pathway to understanding citizens’ willingness to pay (WTP) for environmental governance, but the existing literature still lacks empirical studies on this topic and the intermediate mechanisms. Adopting an environmental communication perspective, this paper divided the environmental effects of media into two dimensions: knowledge growth and responsibility cultivation, and conducted an empirical analysis on whether, and how, media use affected citizens’ WTP, based on data from the China General Social Survey 2018 (hereafter, CGSS2018). The findings found that the frequency of media use significantly increased citizen’s WTP, in which individual environmental responsibility rather than environmental knowledge played a mediating effect; i.e., media use increased individuals’ WTP by increasing the public’s environmental responsibility. Furthermore, this study discovered that traditional media use had a significant effect on the citizens’ WTP, again verifying the mediating effect of individual environmental responsibility, while new media use did not have such a communication effect. This study extends the theories related to pro-environmental behaviors, and provides practical implications for the government to promote environmental governance and sustainability.
Wildlife Knowledge and Attitudes toward Hunting: A Comparative Hunter–Non-Hunter Analysis
Authors: Raftogianni Georgia , Kontsiotis Vasileios J. , Liordos Vasilios
Published: November 2022

Assessing the public’s attitudes toward hunting and knowledge about wildlife is critical for successfully managing and conserving resources. This need is further emphasized by the increase in urbanization, resulting in decreasing participation in outdoor activities, such as hunting. This study aimed at investigating the attitudes toward hunting and the wildlife knowledge of Greek residents and at understanding the variation among hunters and non-hunters. Respondents to on-site, face-to-face surveys (n = 461; hunters, 146; non-hunters, 315) were asked to rate their acceptance of the motives for hunting and of hunting as a management tool and their knowledge about the ecology, biology, and behavior of wildlife. The hunters were highly motivated for hunting and supported it as a management tool. The non-hunters’ attitudes were, however, neutral to negative. The hunters had greater knowledge about wildlife species, both game and non-game, than the non-hunters. The more experienced hunters with greater knowledge about wildlife were generally more positive toward hunting. Older, male, non-hunters who have a greater knowledge about wildlife and who consume game meat and have hunters in the family or among their friends were generally more positive toward hunting. The findings suggested that hunting is a controversial social issue. Policies aimed at informing public groups about good hunting practices and at increasing the public’s engagement in outdoor activities would reduce such controversies, improve human health and well-being, and reinforce nature and wildlife stewardship and support for biodiversity conservation.
Sport Event Tourism in Bucharest. UEFA EURO 2020 Case Study
Authors: Lequeux-Dincă Ana-Irina , Sava Amira-Andreea , Teodorescu Camelia , Gheorghilaş Aurel , Clius Mioara
Published: November 2022

Mega sport events were among the very few types of events still attracting tourists during the 2020 COVID-19 pandemic and represented an exceptionally attractive tourism opportunity for Bucharest through the matches scheduled for the UEFA 2020 championship. Motivated by the novelty of the event which was organized for the first time in the Romanian capital city and motivated by the exceptionally restrictive context imposed by the sanitary crisis, the aim of this study was to analyze domestic tourist participation in and satisfaction with this event. An extended survey focusing on the autochthonous participants was applied to gather data and then further computed using SPSS software through crosstabulations and associated statistical analysis adapted for nominal and ordinal variables. The main results emphasize a large participation of Romanian football supporters who came specifically for the event. Most of them expressed dissatisfaction with souvenir, food and drink products sold within the stadium area but were satisfied with the COVID-19 measures and their costs. Supporters coming from rural areas opted for VFR accommodations while retirees and elderly supporters preferred hotels. Occupation and age were the main variables determining accommodation preferences as well as satisfaction with souvenir prices. These options may be valuable input for future adapted marketing strategies for sport event tourism in Romania. Lacking important urban tourist attractions and competing with other mature European urban destinations, mega sport events may represent an opportunity for autochthonous large cities to increase tourist attractiveness and maintain leisure travel even during periods of travel restrictions.
Adoption of Sustainability Innovations and Environmental Opinion Leadership: A Way to Foster Environmental Sustainability through Diffusion of Innovation Theory
Authors: Khan Ali Junaid , Ul Hameed Waseem , Iqbal Jawad , Shah Ashfaq Ahmad , Tariq Muhammad Atiq Ur Rehman , Ahmed Saira
Published: November 2022

Environmental sustainability is a major challenge for the governments of various countries. The industrial sector and the growth of startups have created a challenge for sustainable development, with little concept of innovativeness for environment sustainability. The current research aims to foster environmental sustainability by adopting sustainability innovation and environmental opinion leadership in the hospital industry. The adoption of sustainability innovation along with environmental opinion leadership in the hospital industry is rarely studied in the literature. Particularly, this concept is completely ignored in the context of Pakistan. Quantitative research approach is employed in this study. A survey instrument in form of a questionnaire was used to collect data from respondents. Respondents of the study were the employees working in public hospitals of Pakistan. Simple random sampling was employed for data collection. The data analysis was carried out by using partial least square-structural equation modeling (PLS-SEM). The findings of this study concluded that the role of trialability, innovativeness, compatibility, simplicity, and relative advantage must be considered when adopting sustainable innovation in hospitals. The practical and theoretical implications of this study are significant for the improvement of environmental sustainability in Pakistan.
Sustainable Tourism in Protected Area—A Case of Fruška Gora National Park, Vojvodina (Northern Serbia)
Authors: Trišić Igor , Privitera Donatella , Štetić Snežana , Genov Georgi , Stanić Jovanović Sara
Published: November 2022

Sustainable development can be an element of tourism success if its principles are included in the process of strategic tourism development planning, and if such a concept is one of the strategic development goals. The paper analyzes the impact of the perception of the local population and visitors and their satisfaction with the development of tourism in the protected mountain area of Fruška Gora National Park, which has an abundance of natural, cultural, and social tourism resources that are directly included in the tourism offer. Maintaining natural and social values within this sensitive tourist destination, eliminating negative effects of tourism, strengthening the role of residents and visitors in tourism planning and development, and initiating special and other forms of tourism should be the basis of tourism development in this preserved area. The purpose of the research was to obtain important results on the residents’ attitudes and visitors’ satisfaction with the state of sustainable tourism within this national park, using quantitative methodology and an SPSS analysis of the conducted questionnaire. The respondents’ attitudes referred to environmental, economic, sociocultural, and institutional sustainability as being significant foundations of sustainable tourism development. The results revealed not only that tourism in Fruška Gora National Park was partially sustainable, but also that there was a need to improve all dimensions of sustainability. Such results could be used to transform tourism development strategies by emphasizing the growth of sustainable forms of tourism activities. The construction of tourist facilities and infrastructures must be based on environmental protection and residents must be directly involved in tourism development planning.
Socio-Economic Constraints of Adopting New Cowpea Varieties in Three Agro-Ecological Zones in the Senegalese Peanut Basin
Authors: Beye Assane , Diakhate Pape Bilal , Diouf Omar , Faye Aliou , Obour Augustine K. , Stewart Zachary P. , Assefa Yared , Min Doohong , Prasad Pagadala V. V.
Published: November 2022

Socio-economic constraints like gender, education, age, and income significantly affect the adoption of improved agricultural technologies. The objective of this study was to determine socio-economic factors that affect the adoption of improved cowpea varieties in the Senegalese peanut basin. The study was conducted in three (Bambey, Kebemer, and Kaffrine) of six regions of the peanut basin based on regional importance of cowpea production and rainfall gradient. In each study region, ten villages were selected, and random sampling was used to select eight heads of agricultural households within each village. The questionnaires were administered to 240 randomly selected farmers across the three study regions, 7 communes, and 30 villages. Results showed most heads of households were middle-aged (52–54 years old), married (95–100%), illiterate (84%), and men (95–100%). Households were mostly agriculture dependent (87%), low literacy rates (26% least primary school), and large family sizes (average of 15 members). The median cowpea yields across the study area varied from 35–100 kg ha−1, well below the ~300–400 kg ha−1 average yields reported for Senegal and Sub-Saharan Africa. The majority of farmers (67%) in the study regions did not use improved varieties, and the main reasons were low seed availability (78.8%) and limited access to technical knowledge and information (76.3%), but only 5.8% indicated seed price as a barrier to improved variety adoption. Major uses of cowpea in the study area were for marketing, livestock feed, and human consumption. In Kaffrine, fodder production was the major (85%) criterion for cowpea variety selection, whereas in the north (Bambey and Kebemer), taste, maturity date, and grain yield were major selection criteria. Factors that had positive effect on the likelihood of using improved cowpea varieties include; access to extension services, membership in farmers’ organization, cowpea being the main crop of production, organic farming, market, and livestock-oriented production systems, access to farmland and credit, dependence on agriculture as the main source of household income, and education of head of household. We conclude that there is a critical need for training, access to improved seeds, awareness, and financial support to producers to increase the adoption of new improved cowpea varieties, yields, profitability, and nutritional security among smallholder farmers in the Senegalese peanut basin.
Effect Evaluation of Filling Medium Parameters on Operating and Mechanical Performances of Liquid Heavy Metal Heat Storage Tank
Authors: Wang Gang , Wang Tong
Published: November 2022

In order to evaluate the feasibility and performance of liquid lead-bismuth eutectic as the heat transfer fluid for thermocline heat storage tanks in solar power systems, we conducted an effect evaluation of filling medium parameters on the integrated operating and mechanical performances of a thermocline tank using liquid lead-bismuth eutectic using the computational fluid dynamics simulation method. Four parameters were evaluated: the porosity, thermal conductivity, specific heat capacity, and equivalent diameter of the filling medium. The results show that the liquid lead-bismuth eutectic tank operated stably. The total charging and total discharging durations were 5.7 h and 5.3 h, respectively, and the discharging efficiency was 91.94%. The effect evaluation results reveal that the discharging thermocline thickness of the liquid heavy metal tank can be decreased by increasing the specific heat capacity of the filling particles, or by decreasing the porosity, thermal conductivity, and equivalent diameter of the filling medium. The total discharging quantity of the tank increased from 2.19 × 1010 J to 3.34 × 1010 J when the specific heat capacity of the filling particles increased from 610.0 J/(kg∙K) to 1010.0 J/(kg∙K), while the other three filling medium parameters had no obvious effect on the total discharging quantity of the tank. The mechanical performance of the tank wall could be improved by decreasing any one of the four evaluated parameters of the filling medium. The results of this paper may serve as a reference for the design of actual liquid heavy metal heat storage tanks in solar power plants.
Connecting Future Environmental Trends and Assessments of Fish and Wildlife Resources of Concern: A Case Study of Big Pine Key, Florida
Authors: Miller Lori A. , Harwell Matthew C.
Published: November 2022

Changes in hydrologic and climatic trends will influence the ecology of Florida, and climate scenarios agree that many areas of Florida are susceptible to sea-level rise impacts. The U.S. Fish and Wildlife Service’s Climate Change Action Program focuses on a framework to examine climate change effects on fish, wildlife, plants, and habitats of all three. To follow the program, this study examines how to incorporate current scientific knowledge about regional climate projections in U.S. Fish and Wildlife Service analyses. It provides climate change and sea-level rise projections based on 2017 projections, information on changes in tropical cyclones, temperatures, and precipitation. This study also examines future effects of sea-level rise on existing habitat from saltwater intrusion of the freshwater lens below Big Pine Key. Projections of future sea-water elevations will periodically be reached or exceeded well before 2040 from short-term, stochastic, and extreme events (e.g., king tides and storm surge), and will increasingly inundate the root zone before complete saltwater intrusion. Future trends were connected to 2017 stakeholder-driven conversations about adaptation strategies to develop a suite of actions for creating temporary or permanent freshwater resources. However, beyond 3 ft (0.9 m) of sea-level rise, there are few adaptation options available for the Florida Key deer beyond relocations outside of the Florida Keys. Overall, the approach of connecting future environmental trends to assessments of fish and wildlife resources of concern can be transferred to other situations. Additionally, this approach can be used to update these analyses, such as with the recent 2022 sea-level rise updates by the National Oceanic and Atmospheric Administration, released after this work was conducted.