bluuebunny/crossref_metadata_2025 huggingface dataset:
Underwater Fish Segmentation Algorithm Based on Improved PSPNet Network
Authors: Han Yanling , Zheng Bowen , Kong Xianghong , Huang Junjie , Wang Xiaotong , Ding Tianhong , Chen Jiaqi
Published: September 2023

With the sustainable development of intelligent fisheries, accurate underwater fish segmentation is a key step toward intelligently obtaining fish morphology data. However, the blurred, distorted and low-contrast features of fish images in underwater scenes affect the improvement in fish segmentation accuracy. To solve these problems, this paper proposes a method of underwater fish segmentation based on an improved PSPNet network (IST-PSPNet). First, in the feature extraction stage, to fully perceive features and context information of different scales, we propose an iterative attention feature fusion mechanism, which realizes the depth mining of fish features of different scales and the full perception of context information. Then, a SoftPool pooling method based on fast index weighted activation is used to reduce the numbers of parameters and computations while retaining more feature information, which improves segmentation accuracy and efficiency. Finally, a triad attention mechanism module, triplet attention (TA), is added to the different scale features in the golden tower pool module so that the space attention can focus more on the specific position of the fish body features in the channel through cross-dimensional interaction to suppress the fuzzy distortion caused by background interference in underwater scenes. Additionally, the parameter-sharing strategy is used in this process to make different scale features share the same learning weight parameters and further reduce the numbers of parameters and calculations. The experimental results show that the method presented in this paper yielded better results for the DeepFish underwater fish image dataset than other methods, with 91.56% for the Miou, 46.68 M for Params and 40.27 G for GFLOPS. In the underwater fish segmentation task, the method improved the segmentation accuracy of fish with similar colors and water quality backgrounds, improved fuzziness and small size and made the edge location of fish clearer.
Automatic Video-Oculography System for Detection of Minimal Hepatic Encephalopathy Using Machine Learning Tools
Authors: Calvo Córdoba Alberto , García Cena Cecilia E. , Montoliu Carmina
Published: September 2023

This article presents an automatic gaze-tracker system to assist in the detection of minimal hepatic encephalopathy by analyzing eye movements with machine learning tools. To record eye movements, we used video-oculography technology and developed automatic feature-extraction software as well as a machine learning algorithm to assist clinicians in the diagnosis. In order to validate the procedure, we selected a sample (n=47) of cirrhotic patients. Approximately half of them were diagnosed with minimal hepatic encephalopathy (MHE), a common neurological impairment in patients with liver disease. By using the actual gold standard, the Psychometric Hepatic Encephalopathy Score battery, PHES, patients were classified into two groups: cirrhotic patients with MHE and those without MHE. Eye movement tests were carried out on all participants. Using classical statistical concepts, we analyzed the significance of 150 eye movement features, and the most relevant (p-values ≤ 0.05) were selected for training machine learning algorithms. To summarize, while the PHES battery is a time-consuming exploration (between 25–40 min per patient), requiring expert training and not amenable to longitudinal analysis, the automatic video oculography is a simple test that takes between 7 and 10 min per patient and has a sensitivity and a specificity of 93%.
YOLO-SS-Large: A Lightweight and High-Performance Model for Defect Detection in Substations
Authors: Wang Qian , Yang Lixin , Zhou Bin , Luan Zhirong , Zhang Jiawei
Published: September 2023

With the development of deep fusion intelligent control technology and the application of low-carbon energy, the number of renewable energy sources connected to the distribution grid has been increasing year by year, gradually replacing traditional distribution grids with active distribution grids. In addition, as an important component of the distribution grid, substations have a complex internal environment and numerous devices. The problems of untimely defect detection and slow response during intelligent inspections are particularly prominent, posing risks and challenges to the safe and stable operation of active distribution grids. To address these issues, this paper proposes a high-performance and lightweight substation defect detection model called YOLO-Substation-large (YOLO-SS-large) based on YOLOv5m. The model improves lightweight performance based upon the FasterNet network structure and obtains the F-YOLOv5m model. Furthermore, in order to enhance the detection performance of the model for small object defects in substations, the normalized Wasserstein distance (NWD) and complete intersection over union (CIoU) loss functions are weighted and fused to design a novel loss function called NWD-CIoU. Lastly, based on the improved model mentioned above, the dynamic head module is introduced to unify the scale-aware, spatial-aware, and task-aware attention of the object detection heads of the model. Compared to the YOLOv5m model, the YOLO-SS-Large model achieves an average precision improvement of 0.3%, FPS enhancement of 43.5%, and parameter reduction of 41.0%. This improved model demonstrates significantly enhanced comprehensive performance, better meeting the requirements of the speed and precision for substation defect detection, and plays an important role in promoting the informatization and intelligent construction of active distribution grids.
Optimal Frequency and Wireless Power Budget for Miniature Receivers in Obese People
Authors: Van de Steene Tom , Tanghe Emmeric , Martens Luc , Garripoli Carmine , Stanzione Stefano , Joseph Wout
Published: September 2023

This study investigates wireless power transfer for deep in-body receivers, determining the optimal frequency, power budget, and design for the transmitter and receiver. In particular, the focus is on small, in-body receivers at large depths up to 20 cm for obese patients. This enables long-term monitoring of the gastrointestinal tract for all body types. Numerical simulations are used to investigate power transfer and losses as a function of frequency and to find the optimal design at the selected frequency for an obese body model. From all ISM-frequencies in the investigated range (1 kHz–10 GHz), the value of 13.56 MHz yields the best performance. This optimum corresponds to the transition from dominant copper losses in conductors to dominant losses in conductive tissue. At this frequency, a transmitting and receiving coil are designed consisting of 12 and 23 windings, respectively. With a power transfer efficiency of 2.70×10−5, 18 µW can be received for an input power of 0.68 W while still satisfying exposure guidelines. The power transfer is validated by measurements. For the first time, efficiency values and the power budget are reported for WPT through 20 cm of tissue to mm sized receivers. Compared to WPT at higher frequencies, as commonly used for small receivers, the proposed system is more suitable for WPT to large depths in-body and comes with the advantage that no focusing is required, which can accommodate multiple receivers and uncertainty about receiver location more easily. The received power allows long-term sensing in the gastrointestinal tract by, e.g., temperature, pressure, and pH sensors, motility sensing, or even gastric stimulation.
Using DWS Optical Readout to Improve the Sensitivity of Torsion Pendulum
Authors: Wang Shaoxin , Liu Heshan , Dai Lei , Luo Ziren , Xu Peng , Li Pan , Gao Ruihong , Li Dayu , Qi Keqi
Published: September 2023

In space gravitational wave detection missions, a drag-free system is used to keep the test mass (TM) free-falling in an ultralow-noise environment. Ground verification experiments should be carried out to clarify the shielding and compensating capabilities of the system for multiple stray force noises. A hybrid apparatus was designed and analyzed based on the traditional torsion pendulum, and a technique for enhancing the sensitivity of the torsion pendulum system by employing the differential wavefront sensing (DWS) optical readout was proposed. The readout resolution experiment was then carried out on an optical bench that was designed and established. The results indicate that the angular resolution of the DWS signal in optical readout mode can reach the level of 10 nrad/Hz1/2 over the full measurement band. Compared with the autocollimator, the sensitivity of the torsional pendulum is noticeably improved, and the background noise is expected to reach 4.5 × 10−15 Nm/Hz1/2@10 mHz. This method could also be applied to future upgrades of similar systems.
Synergistic Evolution of China’s Green Economy and Digital Economy Based on LSTM-GM and Grey Absolute Correlation
Authors: Xu Guoteng , Peng Shuai , Li Chengjiang , Chen Xia
Published: September 2023

This study aims to understand the synergistic evolution of the green and digital economies towards sustainable development. Previous research lacked quantitative analysis, which hindered the development of a comprehensive understanding. An evaluation index system is established using the CRITIC and entropy weight combination methods. The TOPSIS model is utilized to evaluate indicators and derive a comprehensive development index for both economies. The LSTM-GM model is employed to predict the evolutionary trends for the next five years. The absolute grey correlation model is applied to analyze historical and future synergistic evolutionary trends. Findings show increasing levels of green and digital economic development. The digital economy promotes green economic development by enhancing efficiency through innovation and upgrades. The green economy facilitates the structural adjustment of the digital economy by reducing emissions and enhancing resource utilization. Predictions indicate a steady growth in both economies and an increasing synergistic evolution. Based on the analysis, policy recommendations are proposed to promote the integration and development of the digital and green economies, facilitating high-quality synergistic growth.
Rural Tourism Households Adapting to Seasonality: An Exploratory Sequential Mixed-Methods Study
Authors: Su Zhen , Xian Kun , Lu Dandan , Wang Wenhui , Zheng Yinghong , Khotphat Tanaporn
Published: September 2023

The inherent vulnerability of tourism poses a substantial challenge to maintaining the productivity and stability of livelihoods among rural tourism households. Although tourism seasonality significantly influences the livelihood activities of rural tourism households, research exploring how they adapt their livelihood strategies to achieve optimal outcomes is limited. Employing an exploratory sequential mixed-methods design that combines thematic analysis and fuzzy-set Qualitative Comparative Analysis (fsQCA), we investigated the relationship between the livelihood strategies and outcomes of rural tourism households under the influence of tourism seasonality in the Lijiang scenic spot of China. The results indicate that livelihood strategies adopted by rural tourism households include “Tourism Persistence”, “Seasonal Employment”, and “Seasonal Farming” during the off-season and “Extending Working Hours”, “Increasing Staffing Input”, and “Increasing Capital Input” during the peak season. Furthermore, these strategies form flexible combinations to realize livelihood outcomes, with “Extending Working Hours” being a necessary condition. The findings also revealed that the four configurations of seasonal livelihood strategies in the two patterns significantly contributed to high livelihood outcomes. One is named “Peak-Season Driven Pattern”; the other is named “Peak-Off Blend-Driven Pattern”. These findings provide theoretical and practical insights for sustainable livelihood research.
Nexus between Environmental Degradation, Clean Energy, Financial Inclusion, and Poverty: Evidence with DSUR, CUP-FM, and CUP-BC Estimation
Authors: Li Zhengxin , Qamruzzaman Md.
Published: September 2023

This research delves into the intricate interconnections among financial inclusion, the adoption of renewable energy, environmental resilience, and poverty reduction in low-income countries (LICs), lower-middle-income countries (LMICs), and sub-Saharan Africa (SSA), in light of complex issues such as poverty, environmental degradation, and sustainable development. This work comprehensively understands the interaction between these crucial factors by utilizing a dynamic panel model, specifically Dynamic Seemingly Unrelated Regression (DSUR), CUP-FM, and CUP-BC. The empirical analysis conducted in our study has produced findings that are both significant and noteworthy. Financial inclusion pertains to facilitating formal financial services for demographic segments that have historically been marginalized or excluded. A negative relationship between financial inclusion and poverty levels in low-income countries (LICs), lower-middle-income countries (LMICs), and sub-Saharan Africa (SSA) has been observed. Moreover, there is an inverse correlation between the utilization of renewable energy sources and poverty, indicating that the utilization of renewable energy sources possesses the potential to catalyze the enhancement of economic conditions and overall welfare. However, it is important to note that the correlation between environmental deterioration and poverty underscores the urgent necessity for implementing comprehensive policies that address sustainability and poverty reduction. The results above shed light on the potential for governmental interventions to promote positive transformations. Improving endeavors to achieve financial inclusion holds the capacity to empower individuals and businesses alike, fostering economic progress and alleviating poverty. Renewable energy technology is progressively acknowledged as a viable strategy to promote economic advancement and tackle environmental issues simultaneously. It is of utmost importance to establish comprehensive policy frameworks that effectively tackle the intricate interplay between environmental degradation and poverty to create a future that is both sustainable and egalitarian.
The Nitrate Fate Tool: A Decision Support System for the Assessment of the Groundwater Vulnerability to Nitrate in Support of Sustainable Development Goals
Authors: Bancheri Marialaura , Basile Angelo , Botta Marco , Langella Giuliano , Cavaliere Federica , Bonfante Antonello , Ferraro Giuliano , Acutis Marco , Perego Alessia
Published: September 2023

This article introduces a new web-based and freely accessible tool, the Nitrate Fate tool (NFt), for the assessment of groundwater vulnerability to nitrate pollution in a variety of pedoclimatic conditions. The contamination of water resources by nitrate, in fact, represents a growing and persistent global environmental problem, and the utilization of practical tools to assist personnel working in the agricultural sector is key for mitigating the impact on land use, while maintaining farmers’ incomes. The (NFt) has been developed and integrated into the geospatial decision support system, LandSupport, as a way to support multiple stakeholders in conducting the so-called what-if scenario analysis (e.g., what would happen to the crop production if I substitute a quote of inorganic fertilizer with the same quote of an organic one?). The tool couples a state-of-art crop-growth model—which simulates crop growth dynamics, the nitrogen and carbon cycles—with a novel transfer function model in order to assess the transport of nitrate through the unsaturated zone to the groundwater table. Within the LandSupport platform, the results are shown both as coloured maps and as cumulative charts representing the travel times and the concentrations of root leachate to groundwater table depths. This work details the tool’s rationale, the coupling of the models, and their implementation. Moreover, this article shows examples of applications supporting several public authorities and end-users, underlining that, by combining all of the information on soils, groundwater table depths, management and climates, it is possible to obtain a comprehensive understanding of nitrogen transport dynamics. Two case studies are presented: the Piana del Sele and the eastern plain of Naples, both located in the Campania region of Italy. The results of the tool’s applications reveal significant groundwater vulnerability in both plains, mainly due to the shallow groundwater table depths, resulting in remarkably fast mean nitrate travel times ranging from 0 to 6 years. Finally, the tool provides a reproducible and replicable solution, and future implementation is foreseen for additional case studies all over the world.
Spatiotemporal Distribution and Driving Force Analysis of the Ecosystem Service Value: A Typical Case Study of the Coastal Zone, Eastern China
Authors: Zhang Xiaoyan , Shen Juqin , Sun Fuhua , Wang Shou , Wan Yu
Published: September 2023

Identifying and assessing the drivers of change in ecosystem service value (ESV) is critical for integrated management and human well-being in coastal zone areas. This paper took a typical coastal zone in eastern China as the research object. Based on five periods of remote sensing monitoring data of land use status from 2000 to 2020, the ESV of Yancheng was estimated by adopting the equivalence factor method. Spatial statistical analysis and GeoDetector were applied to reveal the heterogeneous features of ESV and its driving mechanism. The results suggested that: (1) From 2000–2020, each land use type in the study area changed to different degrees, among which the most drastic change was in the construction land, which increased continuously by 962.69 km2, the cultivated land area decreased continuously by 784.1 km2, and the area of water body decreased by 163.34 km2. (2) ESV experienced a process of increasing and then decreasing, from 547.84 × 108 yuan to 570.86 × 108 yuan and then decreasing to 507.62 × 108 yuan, with farmland ecosystems having the largest ESV, accounting for more than 60%. Regulatory services were the core function of ecosystem services, accounting for more than 60%. (3) There was significant spatial-temporal differentiation in ESV, with extremely low ESV expanding in rapidly developing urbanized areas. The ESV distribution exhibited significant spatial autocorrelation and local spatial clustering, with the gravity center showing a general trend from north to southwest. (4) The ESV spatial and temporal evolutionary characteristics were the result of a multifactorial integration of land use, topography, socio-economics, and climate factors. The explanatory power of each factor in descending order was LDI > DEM > POP > GDP > RAI > TEM, and any two-factor interaction had higher explanatory power than the single factor.
A Global Analysis of Emissions, Decarbonization, and Alternative Fuels in Inland Navigation—A Systematic Literature Review
Authors: Christodoulou Raftis Charilaos , Vanelslander Thierry , van Hassel Edwin
Published: September 2023

In response to the pressing need for transportation decarbonization, this paper examines the often overlooked domain of inland waterway transport and seeks to answer which alternative fuel or power source is the most promising for that sector. As the shipping industry significantly contributes to global carbon emissions, it has been shifting towards alternative fuels and decarbonization measures in the effort to reduce them, whereas the inland waterways, operating predominantly on diesel engines, have not achieved equivalent substantial progress. Employing a systematic literature review and regional analysis, this study identifies notable trends. LNG initially emerged as a favored alternative fuel, but recent studies emphasize a shift towards “greener” solutions like batteries and hydrogen. Europe and Asia lead in these developments. This investigation uncovers critical gaps in research and development, particularly in the Northern European countries that have extensive inland waterway networks. It also calls for future studies to explore the performance of vessels that have adopted LNG compared to other emerging alternatives and emphasizes the importance of considering the time lag between technology development and research publication.
Study of the Ecological and Reclamation Condition of Abandoned Saline Lands and Their Development for Sustainable Development Goals
Authors: Laiskhanov Shakhislam , Smanov Zhassulan , Kaimuldinova Kulyash , Aliaskarov Duman , Myrzaly Nazira
Published: September 2023

To provide the population with food, it is very important to re-cultivate “abandoned lands” that have been retired from agricultural use. The conversion of arable land into agricultural abandoned lands in the south of Kazakhstan is, first of all, primarily associated with salinity. For the purposes of sustainable development, there is a need to develop proposals for re-mastering by studying their current state and reviewing world studies on the reclamation of salt-affected soils. Therefore, this study is devoted to the study of the current environmental and reclamation conditions of the abandoned areas of the Otyrar region in southern Kazakhstan. The proposed directions of changes in their development were also presented. In the course of the research, the historical method is used in the study of the emergence and formation of abandoned lands; the method of geographical analysis during the territorial analysis of the research object; the statistical and comparison methods in showing the complexity and intensity of the problems; the cartographic, geo-informational and field research (reconnaissance) methods in the study of the condition of the abandoned lands in the research object and methods of grouping and analysis were used in the work with scientific data on the topic of research. Using Sentinel-2 images, the GIS program created phenological dynamics of crops based on NDVI vegetation indices during the vegetation period of the irrigated range. By classifying them, abandoned lands due to salinization were separated from fields. By deciphering space images with the help of geoinformation technologies, it was revealed that the area of abandoned lands in the research object is 13,688.9 ha, including the area of non-saline soils—83.9 ha, weakly saline soils—984.4 ha, medium saline soils—2398.3 ha, and highly saline soils—10,222.1 ha. A review of the methods and technologies proposed by scientists for the development and amelioration of salt-affected lands was made. Taking into account the ecological and reclamation state of the object of research along with the material and technical capabilities of farms, two methods of developing abandoned lands (organic and agro-innovative) in the research object are proposed and the need for their use in case of soil salinization has been scientifically justified.
Novelty and Sustainability: The Generation Process of Original Business Model Innovation
Authors: Jiang Guihuang , Ji Xuehong , Zhang Aonan
Published: September 2023

Compared to incremental business model innovation, the impact of original business model innovation on both enterprises and societal development is more significant. The process of its emergence has attracted considerable attention. This article defines the concept of original business model and divides the process of its formation into two steps: achieving novelty and sustainability. Employing an exploratory multiple case study method, the research and analysis are conducted on six startup enterprises with characteristics of original business model innovation. The study reveals that achieving novelty involves three stages, i.e., heterogeneous knowledge accumulation, pain point perception, and opportunity identification, as well as cross-domain thinking application and creative formation. Achieving sustainability entails three stages: concept definition, business model development, and business model validation. Throughout this process, the effective integration of cross-domain knowledge is achieved through iterative experimentation, garnering support and recognition from stakeholders. The attainment of sustainability is pivotal to the success of original business models.
Experimental Investigation and Proposal of Artificial Neural Network Models of Lead and Cadmium Heavy Metal Ion Removal from Water Using Porous Nanomaterials
Authors: Jery Atef El , Aldrdery Moutaz , Ghoudi Naoufel , Moradi Mohammadreza , Ali Ismat Hassan , Tizkam Hussam H. , Sammen Saad Sh.
Published: September 2023

This study used porous nanomaterials MCM-41 and SBA-15, as well as their modified species, to remove lead and cadmium ions from water. We used X-ray diffraction (XRD), a scanning electron microscope (SEM), the Brunauer–Emmett–Teller (BET), and the Fourier transform infrared (FT-IR) method to investigate the characteristics of porous nanomaterials. Additionally, atomic absorption spectroscopy (AAS) measured the concentration of lead and cadmium ions. The stratigraphic analysis showed the samples’ isothermal shape to be type IV. This study investigated the amount, absorbent, pH changes, and adsorption time parameters. We observed that the adsorption efficiency of lead by the synthesized samples was higher than that of the adsorption of cadmium. Mesoporous structures also displayed increased adsorption efficiency due to the amino group. Four testing stages were conducted to determine the reproducibility of the adsorption by the synthesized samples, with the results showing no significant changes. As a result of the adsorption process, the structure of the recycled sample NH2-MCM-41 was preserved. We also used artificial neural networks (ANN) to propose predictive models based on the experimental results. The ANN models were very accurate, such that the mean absolute error (MAE) was less than 2% and the R2 was higher than 0.98.
Role of Experimental, Modeling, and Simulation Studies of Plasma in Sustainable Green Energy
Authors: Arshad Muhammad Yousaf , Saeed Muhammad Azam , Tahir Muhammad Wasim , Raza Ahsan , Ahmad Anam Suhail , Tahir Fasiha , Borkowski Bartłomiej , Mączka Tadeusz , Niedzwiecki Lukasz
Published: September 2023

This comprehensive review paper offers a multifaceted examination of non-thermal plasma applications in addressing the complex challenge of tar removal within biomass-oriented technologies. It begins with a concise introduction to the research background, setting the context for our exploration. The research framework is then unveiled, providing a structured foundation for understanding the intricate dynamics of plasma–tar interactions. As we delve deeper into the subject, we elucidate the reactivity of tar compounds and the transformation of alkali metals through plasma-based methodologies, essential factors in enhancing product gas quality. Through an array of empirical studies, we investigated the nuanced interactions between plasma and diverse materials, yielding crucial insights into plasma kinetics, modeling techniques, and the optimization of plasma reactors and processes. Our critical review also underscores the indispensable role of kinetic modeling and simulation in advancing sustainable green energy technologies. By harnessing these analytical tools, researchers can elevate system efficiency, reduce emissions, and diversify the spectrum of available renewable energy sources. Furthermore, we delve into the intricate realm of modeling plasma behavior and its intricate interplay with various constituents, illuminating a path toward innovative plasma-driven solutions. This comprehensive review highlights the significance of holistic research efforts that encompass empirical investigations and intricate theoretical modeling, collectively advancing the frontiers of plasma-based technologies within the dynamic landscape of sustainable energy. The insights gained from this review contribute to the overall understanding of plasma technologies and their role in achieving a greener energy landscape.
A Study on Modifying Campus Buildings to Improve Habitat Comfort—A Case Study of Tianjin University Campus
Authors: Du Xinge , Gao Guoyao , Gao Feng , Zhou Zhihua
Published: September 2023

At present, the design and planning of teaching and living areas on university campuses are relatively straightforward but encounter problems, such as poor ventilation, low indoor air quality, and poor sound insulation. In this study, the teaching building and living area cluster at the Tianjin University campus were selected as the research objects. We verified the effectiveness of the simulation results before and after renovation through onsite testing. To improve ventilation, an atrium and patio were added to the teaching building, and the ventilation of the renovated building was studied. The indoor thermal environment intelligent control system regulates carbon dioxide (CO2) concentration and humidity in the teaching building and changes the thermal comfort of the teaching building. Limiting vehicle speeds near the teaching building and the living area cluster, using muffling materials and muffling equipment, and increasing greenery to reduce noise were factors we studied, considering whether they had a noise-reduction effect. It was found that the average number of air changes in the overall functional space of the first teaching building reaches 6.49 times/h, and the wind speed in the human activity region is below 1 m/s. When using a thermal environment intelligent control system, the indoor temperature throughout the year was within the thermal comfort range 81% of the time. The maximum noise around the teaching building during the daytime was 51.0 dB, the maximum noise at nighttime was 41.5 dB, and the maximum sound level on the facade of the living area cluster was 53 dB. The average noise-reduction rate was 22.63%, which exceeds the noise-reduction rate given in the above research literature.
The Design of a Posture Instruction Atlas and the Prevention of Construction Workers’ Work-Related Musculoskeletal Disorders (WMSDs): A Study on Attention Allocation and Cognitive Load Based on Eye Tracking
Authors: Ouyang Yewei , Cheng Cheng , Wang Dan , He Shiyi , Zheng Lan
Published: September 2023

Training construction workers in safe postures for their tasks could help them avoid unsafe postures and reduce work-related musculoskeletal disorders (WMSDs). This study compared two forms of atlas design in facilitating workers’ learning postures, including their differences in guiding workers’ attention allocation and cognitive load during the learning process. One kind of atlas graphically shows the correct postures to perform construction tasks, and the other adds wrong demonstrations alongside the right ones. Eye-tracking technology was utilized to measure attention allocation and cognitive load. An experimental study was conducted, with 52 construction workers being invited as participants. The results indicated that workers significantly distributed more attention to diagrams than texts and more attention to diagrams showing execution postures than preparatory postures. Moreover, the workers had significantly longer fixation durations on the key body parts when there were wrong demonstrations, which ultimately improved their learning outcomes. There were no significant differences in cognitive load. Suggestions for designing an instructional atlas to enhance construction workers’ occupational health education can be obtained from the findings, including applying diagrams more instead of texts to describe how to correctly perform construction tasks, emphasizing the importance of preparation posture when performing construction tasks, and adding wrong demonstrations showing consequences, with visual cues being positioned on the key body parts.
The Impact of COVID-19 and War in Ukraine on Energy Prices of Oil and Natural Gas
Authors: Xing Xiufeng , Cong Yingjia , Wang Yu , Wang Xueqing
Published: September 2023

The oil and gas sector remains pivotal in supplying energy globally. The COVID-19 pandemic and the Russia–Ukraine crisis intertwined the energy supply and demand, incurred the volatility of energy prices and disrupted the world economic order with profound effects on global political and economic paths in the long run. To investigate the impact of global COVID-19 on the energy prices of oil and natural gas for the period 2020–2022, a type of vector autoregressive (VAR) model, the vector error correction (VEC) model and the ordinary least squared (OLS) method were used for empirical analysis, producing the following main results. (i) COVID-19 significantly Granger caused both oil prices and natural gas prices to fluctuate at the 5% level. (ii) Oil prices significantly Granger caused natural gas prices to fluctuate at the 1% level because of the relations of substitutes for each other. (iii) OLS estimation validated that the cumulative number of COVID-19 confirmed cases was positively correlated with both oil prices and natural gas prices. However, the effect diminished in the long term as the pandemic was eventually brought under effective control. Exploring the effects of global issues including the pandemic and the war in Ukraine on the energy market is crucial to understanding the relationship between the supply shock and the energy sector green transitions and the global economy recovery.
An Overview of the Increasing Ornamental Plant Business in Indonesia Post-COVID-19 Pandemic as a Result of Social Media and Its Future Perspective
Authors: Mubarok Syariful , Suminar Erni , Karyani Tuti , Rufaidah Fathi , Sari Dwi Novanda , Rahmat Bayu Pradana Nur
Published: September 2023

The ornamental plant is one of the important horticultural commodities in Indonesia, but its development differs from that of other horticultural commodities, such as vegetable and fruit plants. The COVID-19 pandemic, which has been ongoing since early 2020, apart from having an impact on health, has also positively impacted the ornamental plant business in Indonesia. Home confinement caused certain physiological problems that could be solved by indoor gardening activity, leading to an increase in the demand for ornamental plants, especially for leafy ornamental plants. This review provides a comprehensive overview of the growth of the ornamental production business in Indonesia in terms of psychological needs and the power of social media. There was an increase in ornamental prices due to the impact of the COVID-19 pandemic in Indonesia. Consumer preferences and behaviors were also altered by the pandemic, as indicated by consumers’ new motivations, perceptions, learning, and belief systems regarding ornamental plants. The government has launched several strategies to gain domestic competitiveness and maintain its sustainability in the environment. Digital transformation has been applied by ornamental plant businesses in Indonesia. The digital marketing of ornamental plants relies on social media concepts such as entertainment, customization, interactions, electronic word of mouth (EWOM), and trendiness.
A Learning Progression for Understanding Interdependent Relationships in Ecosystems
Authors: Dozier Sara J. , MacPherson Anna , Morell Linda , Gochyyev Perman , Wilson Mark
Published: September 2023

This paper describes a hypothesized learning progression for how secondary students understand interdependent relationships in ecosystems, a key concept in the field of ecology and for public understanding of science. In this study, a hypothetical learning progression was developed and empirically investigated using Rasch modeling of data from 1366 students in a large, diverse, urban school district. We found that the empirical evidence supported the general structure of the hypothesized learning progression for relationships in ecosystems. There were notable exceptions, and we describe the ways in which we altered the items and the learning progression to address empirical inconsistencies with our a priori conceptions. The assessment items developed through this study are immediately available online for formative assessment purposes, and the learning progression can support teachers’ thinking about students’ understanding of ecosystems. In particular, the upper reach of the learning progression offers a more complete description of the ways in which students might develop their understanding of complex interactions in ecosystems, beyond what is currently offered in the literature and standards documents about students’ understanding.
The Degree of Environmental Risk and Attractiveness as a Criterion for Visiting a Tourist Destination
Authors: Petrović Marko D. , Milovanović Ilija , Gajić Tamara , Kholina Veronika N. , Vujičić Miroslav , Blešić Ivana , Đoković Filip , Radovanović Milan M. , Ćurčić Nina B. , Rahmat Al Fauzi , Muzdybayeva Karlygash , Kubesova Gulnar , Koshkimbayeva Umyt , Dávid Lóránt Dénes
Published: September 2023

In recent years, more and more attention has been paid to the behavior of tourists and their intention to choose a destination based on various factors. The goal of this research was to determine to what extent environmental risks and the attractiveness of the destination influence the choice of destination and the behavior of tourists. Furthermore, the goal was to determine the influence of psychological groups of tourists on their decision to choose a tourist destination using three psychographic techniques: BFI-10 (Big Five Inventories), AIO (Activities, Interests, and Opinions), and VALS 2 (Values and Lifestyle), and a freely determined six-level scale of risk and tourist attractiveness of imagined destinations. Analyzing the results obtained through the structural modeling-path analysis model, it was determined that tourists grouped in almost all psychographic orientations, resulting from lifestyles, negatively perceive destinations with a high degree of risk and attractiveness, while, with the VALS 2 technique, only members of the action orientation tend to accept ecologically risky destinations. Despite the fact that many studies have looked at how tourists perceive various risks and behave, it is still uncommon to use an integrated approach that considers the simultaneous application of several psychological tests and a unique method of gathering responses from travelers by presenting them with descriptively imagined destinations that differ in their levels of environmental risk and tourist appeal. As a result, this study can provide a conceptual framework for theoretical and practical implications for improved risk management strategies in a specific travel destination and in areas vulnerable to environmental hazards, as well as for completing knowledge about traveler behavior in risky destinations.
Valorizing Community Identity and Social Places to Implement Participatory Processes in San Giovanni a Teduccio (Naples, Italy)
Authors: Procentese Fortuna , Gatti Flora
Published: September 2023

This paper addresses the implementation of an intervention aimed at promoting participatory processes in San Giovanni a Teduccio—a neighborhood on the eastern outskirts of Naples—to foster the acknowledgment and valorization of local social, cultural, and identity resources by citizens. Former industrial and marine area, today disused and run-down industrial establishments in the neighborhood and obscure and pollute the sea, weakening local identity and cultural heritages. Interviews were carried out to address citizens’ and stakeholders’ social identity, their civic and social engagement in the community, and the potential and critical issues they identified in it. A split community emerged from their words, with a minority civically and socially engaged in the regeneration of community places and relationships—even though through a fragmented multiplicity of projects—and a “dormant” majority, passive and anesthetized by the nostalgia of the industrial and marine past. Participants were also asked to share pictures about meaningful community places; these showed abandoned and run-down urban spaces, but also places where citizens could meet, share, and identify. An exhibition was organized to share these materials with the broader community, opening up a space for thinking about the need to involve citizens in acknowledging and valorizing local cultural, social, and identity resources through participatory processes.
Fostering Employees’ Job Performance through Sustainable Human Resources Management and Trust in Leaders—A Mediation Analysis
Authors: Farmanesh Panteha , Mostepaniuk Alla , Khoshkar Parisa Gharibi , Alhamdan Riham
Published: September 2023

Organizations are encouraged to integrate sustainability into their HRM practices to enhance their attractiveness as employers to prospective employees and to motivate employees to excel, which allows them to recognize the contribution they make to society and the lasting impact they create. Establishing a trusting relationship between employees and leaders emerges as a crucial factor when organizations opt to implement sustainable HRM practices across diverse contexts. Thus, this study examines the role of trust in leaders on the relationship between sustainable HRM practices and employee job performance. Consequently, we employed a quantitative approach in which a simple random sampling technique was used to collect data from 156 academic staffs of three private universities across Kyrenia in Northern Cyprus. The research hypotheses were examined through the application of Smart PLS 3.0. Our results indicated a significant impact of sustainable HRM practices on employees’ job performance, emphasizing the importance of judiciously selecting these practices while fostering a trusting relationship between leaders and employees. These findings offer organizations the opportunity to not only enhance their comprehension and awareness of strategic resource allocation but also to tailor their policies in congruence with the company’s objectives and strategies, thereby ensuring the efficient utilization of resources to enhance employee satisfaction and well-being, ultimately leading to an improvement in job performance.
Factors Affecting the Bidding Decision in Sustainable Construction
Authors: Binshakir Omar , AlGhanim Lulwa , Fathaq Afreen , AlHarith Alsharif Mohamed , Ahmed Salma , El-Sayegh Sameh
Published: September 2023

The environmental harms that the construction industry has caused are significantly detrimental and apparent. These harms include the emittance of a substantial amount of carbon dioxide and inducing ground and water contamination. Fortunately, these adverse environmental impacts can be minimized and counteracted by carrying out sustainable construction projects. As sustainable construction projects gain more popularity and are increasingly in demand, it is crucial for those who will execute these projects to be knowledgeable about the nature of sustainable construction projects and be able to determine whether to bid for these projects. The bidding decision is one of the critical decisions that contractors have to make due to the complexity and uncertainty surrounding this choice. Given the above challenge, this research aims to identify the most significant factors that affect the bidding decision in sustainable construction. The methodology adopted in this research is a mix of qualitative and quantitative analysis. An extensive literature review was first conducted to determine the bidding decision factors. After that, a survey was distributed to United Arab Emirates (UAE) construction professionals, where they were asked to rank the significance of the 40 extracted factors. The weighted average approach was then used to prioritize the most significant factors of the bidding decision in sustainable construction. The results showed that the top 10 ranking factors were as follows: client’s financial capabilities, client’s payment history, client’s reputation, project risks, contractor’s financial capabilities, project complexity, experience in similar projects, project type, contractor’s access to technologies required to execute sustainable projects, and material availability. The findings of this research can benefit contractors and subcontractors by increasing their understanding of the major factors affecting the bidding decision in sustainable construction. Contractors armed with such invaluable information will be better equipped to reach more effective better bidding decisions.
A Quantitative Approach of Measuring Sustainability Risk in Pipeline Infrastructure Systems
Authors: Asha Labiba Noshin , Huang Ying , Yodo Nita , Liao Haitao
Published: September 2023

The secure and dependable functioning of pipeline infrastructure systems is pivotal for transporting vital energy resources during this transition era towards a more sustainable energy future. This paper presents a novel quantitative approach for assessing sustainability risk in pipeline infrastructure systems and provides insights for holistic sustainability design in pipeline operations. The proposed methodology introduces a comprehensive framework for quantifying sustainability risk by integrating probabilities of failure and cumulative consequences from social, environmental, and economic dimensions that impact pipeline integrity. Real-world pipeline incident data were employed to identify the main causes of pipeline incidents like corrosion failure, equipment malfunction, and excavation damage. The consequences arising from these incidents are categorized to measure the cumulative consequences of sustainability risk. By quantifying sustainability risk, operators of pipeline infrastructure systems can strategically mitigate and manage potential disruptions affecting long-term sustainability incentives. In doing so, the proposed approach significantly bolsters the vital role of pipeline infrastructure systems in fostering sustainable energy transportation, yielding substantial benefits for global communities and economies.
Automating Assessment and Providing Personalized Feedback in E-Learning: The Power of Template Matching
Authors: Alhalalmeh Zainab R. , Fouda Yasser M. , Rushdi Muhammad A. , El-Mikkawy Moawwad
Published: September 2023

This research addressed the need to enhance template-matching performance in e-learning and automated assessments within Egypt’s evolving educational landscape, marked by the importance of e-learning during the COVID-19 pandemic. Despite the widespread adoption of e-learning, robust template-matching feedback mechanisms should still be developed for personalization, engagement, and learning outcomes. This study augmented the conventional best-buddies similarity (BBS) approach with four feature descriptors, Harris, scale-invariant feature transform (SIFT), speeded-up robust features (SURF), and maximally stable extremal regions (MSER), to enhance template-matching performance in e-learning. We systematically selected algorithms, integrated them into enhanced BBS schemes, and assessed their effectiveness against a baseline BBS approach using challenging data samples. A systematic algorithm selection process involving multiple reviewers was employed. Chosen algorithms were integrated into enhanced BBS schemes and rigorously evaluated. The results showed that the proposed schemes exhibited enhanced template-matching performance, suggesting potential improvements in personalization, engagement, and learning outcomes. Further, the study highlights the importance of robust template-matching feedback in e-learning, offering insights into improving educational quality. The findings enrich e-learning experiences, suggesting avenues for refining e-learning platforms and positively impacting the Egyptian education sector.