bluuebunny/crossref_metadata_2025 huggingface dataset:
Annual and Seasonal Patterns of Burned Area Products in Arctic-Boreal North America and Russia for 2001–2020
Authors: Clelland Andrew A. , Marshall Gareth J. , Baxter Robert , Potter Stefano , Talucci Anna C. , Rady Joshua M. , Genet Hélène , Rogers Brendan M. , Natali Susan M.
Published: September 2024

Boreal and Arctic regions have warmed up to four times quicker than the rest of the planet since the 1970s. As a result, boreal and tundra ecosystems are experiencing more frequent and higher intensity extreme weather events and disturbances, such as wildfires. Yet limitations in ground and satellite data across the Arctic and boreal regions have challenged efforts to track these disturbances at regional scales. In order to effectively monitor the progression and extent of wildfires in the Arctic-boreal zone, it is essential to determine whether burned area (BA) products are accurate representations of BA. Here, we use 12 different datasets together with MODIS active fire data to determine the total yearly BA and seasonal patterns of fires in Arctic-boreal North America and Russia for the years 2001–2020. We found relatively little variability between the datasets in North America, both in terms of total BA and seasonality, with an average BA of 2.55 ± 1.24 (standard deviation) Mha/year for our analysis period, the majority (ca. 41%) of which occurs in July. In contrast, in Russia, there are large disparities between the products—GFED5 produces over four times more BA than GFED4s in southern Siberia. These disparities occur due to the different methodologies used; dNBR (differenced Normalized Burn Ratio) of short-term composites from Landsat images used alongside hotspot data was the most consistently successful in representing BA. We stress caution using GABAM in these regions, especially for the years 2001–2013, as Landsat-7 ETM+ scan lines are mistaken as burnt patches, increasing errors of commission. On the other hand, we highlight using regional products where possible, such as ABoVE-FED or ABBA in North America, and the Talucci et al. fire perimeter product in Russia, due to their detection of smaller fires which are often missed by global products.
Target Motion Parameters Estimation by Full-Plane Hyperbola-Warping Transform with a Single Hydrophone
Authors: Li Yuzheng , Gao Bo , Chen Zhuo , Yu Yueqi , Wang Zhennan , Gao Dazhi
Published: September 2024

In this paper, to counteract the sensitivity of the traditional Hough transform to noise and the fluctuations in parameter estimation, we propose a hyperbolic warping transform that integrates all interference fringes in the time–frequency domain to accurately estimate the motion parameters of a single hydrophone. This method can accurately estimate the target motion parameters, including the time of closest point of approach (tCPA), the ratio of the nearest distance to the speed (b=rCPA/v), and the waveguide invariant (β). The two algorithms are compared by simulation and sea trial experiments. Hyperbola-warping improves the noise immunity performance by 10 dB in simulation experiments, increases the detection range by 20% in sea trial experiments, and demonstrates that the method proposed in this paper has better noise resistance and practicality.
Feasibility Study on the Use of NO2 and PM2.5 Sensors for Exposure Assessment and Indoor Source Apportionment at Fixed Locations
Authors: Chacón-Mateos Miriam , Remy Erika , Liebers Uta , Heimann Frank , Witt Christian , Vogt Ulrich
Published: September 2024

Recent advances in sensor technology for air pollution monitoring open new possibilities in the field of environmental epidemiology. The low spatial resolution of fixed outdoor measurement stations and modelling uncertainties currently limit the understanding of personal exposure. In this context, air quality sensor systems (AQSSs) offer significant potential to enhance personal exposure assessment. A pilot study was conducted to investigate the feasibility of the NO2 sensor model B43F and the particulate matter (PM) sensor model OPC-R1, both from Alphasense (UK), for use in epidemiological studies. Seven patients with chronic obstructive pulmonary disease (COPD) or asthma had built-for-purpose sensor systems placed inside and outside of their homes at fixed locations for one month. Participants documented their indoor activities, presence in the house, window status, and symptom severity and performed a peak expiratory flow test. The potential inhaled doses of PM2.5 and NO2 were calculated using different data sources such as outdoor data from air quality monitoring stations, indoor data from AQSSs, and generic inhalation rates (IR) or activity-specific IR. Moreover, the relation between indoor and outdoor air quality obtained with AQSSs, an indoor source apportionment study, and an evaluation of the suitability of the AQSS data for studying the relationship between air quality and health were investigated. The results highlight the value of the sensor data and the importance of monitoring indoor air quality and activity patterns to avoid exposure misclassification. The use of AQSSs at fixed locations shows promise for larger-scale and/or long-term epidemiological studies.
Enhanced Harmonic Partitioned Scheduling of Periodic Real-Time Tasks Based on Slack Analysis
Authors: Ren Jiankang , Zhang Jun , Li Xu , Cao Wei , Li Shengyu , Chu Wenxin , Song Chengzhang
Published: September 2024

The adoption of multiprocessor platforms is growing commonplace in Internet of Things (IoT) applications to handle large volumes of sensor data while maintaining real-time performance at a reasonable cost and with low power consumption. Partitioned scheduling is a competitive approach to ensure the temporal constraints of real-time sensor data processing tasks on multiprocessor platforms. However, the problem of partitioning real-time sensor data processing tasks to individual processors is strongly NP-hard, making it crucial to develop efficient partitioning heuristics to achieve high real-time performance. This paper presents an enhanced harmonic partitioned multiprocessor scheduling method for periodic real-time sensor data processing tasks to improve system utilization over the state of the art. Specifically, we introduce a general harmonic index to effectively quantify the harmonicity of a periodic real-time task set. This index is derived by analyzing the variance between the worst-case slack time and the best-case slack time for the lowest-priority task in the task set. Leveraging this harmonic index, we propose two efficient partitioned scheduling methods to optimize the system utilization via strategically allocating the workload among processors by leveraging the task harmonic relationship. Experiments with randomly synthesized task sets demonstrate that our methods significantly surpass existing approaches in terms of schedulability.
Selection of X-ray Tube Settings for Relative Bone Density Quantification in the Knee Joint of Cats Using Computed Digital Absorptiometry
Authors: Bonecka Joanna , Turek Bernard , Jankowski Krzysztof , Borowska Marta , Jasiński Tomasz , Skierbiszewska Katarzyna , Domino Małgorzata
Published: September 2024

Bone mineral density (BMD) varies with aging and both systemic and local diseases; however, such evidence is lacking in feline medicine. This may be due to the need for general anesthesia in cats for direct BMD measurements using dual-energy X-ray absorptiometry (DXA) or quantitative computed tomography (QCT). In this study, computed digital absorptiometry (CDA), an indirect relative BMD-measuring method, was optimized to select an X-ray tube setting for the quantitative assessment of the feline knee joint. The knee joints of nine cats were radiographically imaged and processed using the CDA method with an aluminum density standard and five X-ray tube settings (from 50 to 80 kV; between 1.2 and 12 mAs). The reference attenuation of the X-ray beam for ten steps (S1–S10) of the density standard was recorded in Hounsfield units (HU), compared between X-ray tube settings, and used to determine the ranges of relative density applied for radiograph decomposition. The relative density decreased (p < 0.0001) with an increase in kV and dispersed with an increase in mAs. Then, the percentage of color pixels (%color pixels), representing ranges of relative density, was compared among S1–S10 and used for the recognition of background artifacts. The %color pixels was the highest for low steps and the lowest for high steps (p < 0.0001), regardless of X-ray tube settings. The X-ray tube setting was considered the most beneficial when it effectively covered the lowest possible HU ranges without inducing background artifacts. In conclusion, for further clinical application of the CDA method for quantitative research on knee joint OA in cats, 60 kV and 1.2 mAs settings are recommended.
Evaluation of Fracturing Effect of Tight Reservoirs Based on Deep Learning
Authors: Feng Ankang , Ke Yuxin , Hei Chuang
Published: September 2024

The utilization of hydraulic fracturing technology is indispensable for unlocking the potential of tight oil and gas reservoirs. Understanding and accurately evaluating the impact of fracturing is pivotal in maximizing oil and gas production and optimizing wellbore performance. Currently, evaluation methods based on acoustic logging, such as orthogonal dipole anisotropy and radial tomography imaging, are widely used. However, when the fractures generated by hydraulic fracturing form a network-like pattern, orthogonal dipole anisotropy fails to accurately assess the fracturing effects. Radial tomography imaging can address this issue, but it is challenged by high manpower and time costs. This study aims to develop a more efficient and accurate method for evaluating fracturing effects in tight reservoirs using deep learning techniques. Specifically, the method utilizes dipole array acoustic logging curves recorded before and after fracturing. Manual labeling was conducted by integrating logging data interpretation results. An improved WGAN-GP was employed to generate adversarial samples for data augmentation, and fracturing effect evaluation was implemented using SE-ResNet, ResNet, and DenseNet. The experimental results demonstrated that ResNet with residual connections is more suitable for the dataset in this study, achieving higher accuracy in fracturing effect evaluation. The inclusion of the SE module further enhanced model accuracy by adaptively adjusting the weights of feature map channels, with the highest accuracy reaching 99.75%.
A Surface-Enhanced Raman Scattering Substrate with Tunable Localized Surface Plasmon Resonance Absorption Based on AgNPs
Authors: Lin Guanzhou , Wu Meizhang , Tang Rui , Wu Bo , Wang Yang , Zhu Jia , Zhang Jinwen , Wu Wengang
Published: September 2024

In this paper, a three-layer structure of silver particle (AgNP)-dielectric-metal is proposed and constructed based on the characteristics of AgNPs that can excite LSPR (Localized Surface Plasmon Resonance) in free space. In order to overcome the problem of AgNPs easily oxidizing in the air, this paper synthesizes AgNPs using the improved Tollens method and effectively suppresses the coffee-ring effect by changing the solution evaporation conditions, so that the distribution of AgNPs in the deposition area is relatively uniform. The structure proposed in this paper takes advantage of the flexibility of nanoparticle application. The AgNPs deposited on the dielectric layer can effectively localize energy and regulate the LSPR of the device well. The structure can not only achieve precise regulation of the LSPR resonance peak of AgNPs but also can be used as a SERS substrate.
Fresnel Diffraction Model for Laser Dazzling Spots of Complementary Metal Oxide Semiconductor Cameras
Authors: Wang Xinyu , Xu Zhongjie , Zhong Hairong , Cheng Xiang’ai , Xing Zhongyang , Zhang Jiangbin
Published: September 2024

Laser dazzling on complementary metal oxide semiconductor (CMOS) image sensors is an effective method in optoelectronic countermeasures. However, previous research mainly focused on the laser dazzling under far fields, with limited studies on situations that the far-field conditions were not satisfied. In this paper, we established a Fresnel diffraction model of laser dazzling on a CMOS by combining experiments and simulations. We calculated that the laser power density and the area of saturated pixels on the detector exhibit a linear relationship with a slope of 0.64 in a log-log plot. In the experiment, we found that the back side illumination (BSI-CMOS) matched the simulations, with an error margin of 3%, while the front side illumination (FSI-CMOS) slightly mismatched the simulations, with an error margin of 14%. We also found that the full-screen saturation threshold for the BSI-CMOS was 25% higher than the FSI-CMOS. Our work demonstrates the applicability of the Fresnel diffraction model for BSI-CMOS, which provides a valuable reference for studying laser dazzling.
Penetrating Barriers: Noncontact Measurement of Vital Bio Signs Using Radio Frequency Technology
Authors: Aflalo Kobi , Zalevsky Zeev
Published: September 2024

The noninvasive measurement and sensing of vital bio signs, such as respiration and cardiopulmonary parameters, has become an essential part of the evaluation of a patient’s physiological condition. The demand for new technologies that facilitate remote and noninvasive techniques for such measurements continues to grow. While previous research has made strides in the continuous monitoring of vital bio signs using lasers, this paper introduces a novel technique for remote noncontact measurements based on radio frequencies. Unlike laser-based methods, this innovative approach offers the advantage of penetrating through walls and tissues, enabling the measurement of respiration and heart rate. Our method, diverging from traditional radar systems, introduces a unique sensing concept that enables the detection of micro-movements in all directions, including those parallel to the antenna surface. The main goal of this work is to present a novel, simple, and cost-effective measurement tool capable of indicating changes in a subject’s condition. By leveraging the unique properties of radio frequencies, this technique allows for the noninvasive monitoring of vital bio signs without the need for physical contact or invasive procedures. Moreover, the ability to penetrate barriers such as walls and tissues opens new possibilities for remote monitoring in various settings, including home healthcare, hospital environments, and even search and rescue operations. In order to validate the effectiveness of this technique, a series of experiments were conducted using a prototype device. The results demonstrated the feasibility of accurately measuring respiration patterns and heart rate remotely, showcasing the potential for real-time monitoring of a patient’s physiological parameters. Furthermore, the simplicity and low-cost nature of the proposed measurement tool make it accessible to a wide range of users, including healthcare professionals, caregivers, and individuals seeking to monitor their own health.
The Impact of Light Rail Transit on Urban Development in Dubai, UAE
Authors: Alefari Dhabia , Dar Saleh Abeer , Haggag Mahmoud
Published: September 2024

Over the last two decades, the United Arab Emirates (UAE) has experienced significant urban growth, prompting the Dubai Roads and Transport Authority (RTA) to advocate for sustainable transport solutions. This led to the implementation of the Light Rail Transit (LRT) to address urban mobility, environmental sustainability, and energy efficiency. Dubai has strategically prioritized infrastructure and transportation network expansion to support its rapid development. This paper aims to examine the critical role of the LRT system, particularly the metro and tramway, in steering Dubai towards sustainability. Metro and tramway systems offer crucial high-capacity public transport, enhance connectivity, stimulate economic growth, and contribute to a sustainable environment. The study assesses the transformative impact of the Dubai Metro on urban development, focusing on key stations like Jabal Ali, Al-Barsha First, and Business Bay. Using qualitative research methods, including GIS, spatial maps, interviews, case studies, and land use investigations, the research analyzes population density, connectivity, accessibility, and urban land use patterns around these stations. Results indicate a positive impact of the Dubai Metro on both commercial and residential land use, improved connectivity, and enhanced accessibility, reinforcing its role in cultivating a sustainable urban environment.
Skillful Seasonal Prediction of Global Onshore Wind Resources in SIDRI-ESS V1.0
Authors: Yan Zixiang , Zhou Wen , Li Jinxiao , Zhu Xuedan , Zang Yuxin , Zhang Liuyi
Published: September 2024

The seasonal variation in wind resources has a great impact on wind energy generation, affecting the maintenance planning, operational strategies, and economic benefits of wind farms. Therefore, effective seasonal prediction of wind resources is crucial for the wind power industry. This study evaluates the seasonal prediction skill for global onshore wind resources using the SIDRI-ESS V1.0 dynamic prediction system. High prediction skill for 10 m wind speed (ws10m) is observed mainly in six regions: southern North America, northern South America, western and eastern Europe, and South and East Asia. These regions already have a substantial wind power industry or possess rich wind resources and will need wind power industry deployment in the future. Prediction skill is the highest at a 1-month lead time for most regions and decays as the lead time increases. The highest skill emerges in East Asia, with a temporal correlation coefficient (TCC) reaching 0.7, and persists with a 1-month to 5-month lead time. However, the highest skill for southern North America is at a 6-month lead time. Additionally, ensemble prediction effectively reduces uncertainty, such that a multi-member ensemble mean always matches or even exceeds the individual ensemble member with the best performance. Ensemble size analysis shows that increasing the number of ensemble members generally enhances the prediction skill, with 24 members being sufficient for most regions and lead times. However, further increasing the ensemble size is essential to improve the prediction skill at a 6-month lead time. Meanwhile, we also indicate that ws10m can be used as a proxy in evaluating seasonal prediction of wind resources over most regions, while direct seasonal prediction of wind power density is more effective for northern South America. The high seasonal prediction skill of SIDRI-ESS V1.0 highlights its potential for providing valuable seasonal climate prediction services to the wind power industry.
Procurement of Artificial Intelligence Systems in UAE Public Sectors: An Interpretive Structural Modeling of Critical Success Factors
Authors: Alshehhi Khalid , Cheaitou Ali , Rashid Hamad
Published: September 2024

This study investigates the critical success factors (CSFs) influencing the procurement of artificial intelligence (AI) systems within the United Arab Emirates (UAE) public sector. While AI holds immense potential to enhance public service delivery, its successful integration hinges on critical factors. This research utilizes Interpretive Structural Modeling (ISM) to analyze the CSFs impacting AI procurement within the UAE public sector. Through ISM, a structural model is developed to highlight the interrelationships between these CSFs and their influence on the procurement process, outlining the key elements for successful AI procurement within the UAE public sector. Based on the literature review and expert validation from the UAE public sector, ten CSFs were identified. This study found that clear needs assessment is the most influential CSF, while the long-term value of AI systems or services is the least influential. This study provides policymakers and public sector leaders with valuable insights, enabling them to formulate effective strategies to optimize the procurement process and establish a strong foundation for AI adoption. Finally, this will lead to an improved and more efficient public service delivery in the UAE.
Efficacy of the Simplex-Centroid Method for Optimization of Mixtures of Soil, Ladle Furnace Slag and Fly Ash Applied in Pavement Construction
Authors: Rodrigues Mateus Henrique Ribeiro , Silva Taciano Oliveira da , Pitanga Heraldo Nunes , Pedroti Leonardo Gonçalves , Rodrigues Klaus Henrique de Paula , Lopes Emerson Cordeiro , Nalon Gustavo Henrique
Published: September 2024

Integrating industrial wastes into soils to enhance their properties is a potential solution to current waste management challenges. Since the current literature lacks systematic studies on the mechanical performance of mixtures of soil, ladle furnace slag (LFS) and fly ash (FA), this research investigated the chemical stabilization of two different soils (clayey or sandy soil) using a concomitant mix of distinct types of industrial wastes: LFS and FA. A design of experiments (DoE) methodology was employed to systematically generate distinct mixtures for each soil sample, utilizing a simplex-centroid design. The mixtures were subjected to unconfined compressive strength (UCS), California Bearing Ratio (CBR) and resilient modulus (RM) tests. The industrial by-products improved the mechanical properties of the soils, providing UCS, CBR index and RM increases up to 130.5%, 324.4% and 132.6%, respectively. Synergistic and antagonistic effects related to the combination of different wastes were discussed, based on mathematical models with coefficients of determination ranging from 0.760 to 0.998, in addition to response surfaces generated for each response variable. The desirability function was applied to identify the optimal component proportions. The best mixture proportion was 80% soil, 20% LFS and 0% FA, which improved the formation of cemented compounds that contributed to the enhanced mechanical strength. The use of industrial waste for soil stabilization has therefore proven to be technically feasible and environmentally friendly.
A Comparative Study on the Spatial Structure Characteristics of National-Level Traditional Villages in Liaoning, China
Authors: Feng Le , Fan Lei , Wang Na , Li Le , Zhang Ruohan , Deng Ge
Published: September 2024

Knowing the spatial structure of traditional villages is required to promote and preserve these villages. These traditional villages are an essential part of China’s farming legacy and hold substantial historical and cultural significance. Therefore, this article analyzed 30 nationally recognized traditional villages in Liaoning Province, selected from the 6819 traditional villages in the province, as samples. These were divided into three types based on elevation: plain-type (below 200 m above sea level), hilly-type (200–500 m), and mountain-type (above 500 m) villages. Two villages of each type were selected for a total of six villages as the study objects; for these, quantitative comparative research on the spatial structure of these villages was carried out. The results of the study show that: (1) plain-type traditional villages are little affected by the terrain, the overall presentation of the surface space, the village traffic is well developed, able to form a commercial street as the core of the road interruptions in the head of the road more; (2) hilly-type traditional villages are influenced by mountains and water systems, forming a linear space with main roads as the core and crossroads, their core areas are more remote and lack space for public activities, and the villages rely on religious venues or the former residences of celebrities to attract tourists; (3) mountain-type villages are greatly influenced by the mountains, making it difficult to form a commercial area, the distribution of each natural town is relatively scattered and forms a point-like space, each point is developed with public space as the core, and there is a lack of characteristics within the village. The above quantitative characteristics are compared and three targeted conservation strategies for national-level traditional villages in Liaoning are proposed.
Sustainable Solutions for Energy Production from Biomass Materials
Authors: Zlateva Penka , Terziev Angel , Mileva Nevena Milcheva
Published: September 2024

This study reveals the possibilities of the sustainable usage of pellets produced from waste biomass based on the thermal properties of processed raw materials. For this study, a thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and differential thermal analysis (DTA) were performed to better understand the thermal properties of the pellets. This study covered two types of wood pellets with different ratios of waste material: a kind of pellet made from a combination of wood and sunflower residues, and two types of pellets made from sunflower husks. The analysis revealed that the wood pellets offered the best thermal stability and high energy values, making them the preferred choice for heating systems. Mixed pellets showed a lower thermal capacity and combustion efficiency, showing possibilities for further optimization. Sunflower-husk pellets demonstrated a high calorific value, but their application was restricted by a significantly higher ash content and worse environmental impact compared with the first two types of pellets. In addition, the outputs from this study revealed that pellets composed of wood reduced their mass the most at temperatures in the range of 310 to 323 °C. In comparison, the mass loss of sunflower husk pellets was 35.6%/°C (at a 5 °C/min temperature gradient) lower than wood pellets and about 42%/°C lower at a 10 °C/min temperature gradient. These findings highlight the importance of pellet production and technology usage to achieve better sustainability and better thermal properties of the pellets.
An Assessment of the Production Potential and Food Self-Sufficiency of Ukraine against the Background of the European Union and Poland
Authors: Szajner Piotr , Szczepaniak Iwona , Łopaciuk Wiesław
Published: September 2024

Rapidly changing external conditions, such as the COVID-19 pandemic and the war in Ukraine, which are pure crisis phenomena, not only determine the geopolitical and geoeconomic situation in the global markets but also cause structural changes in individual countries. Under these conditions, the level of food self-sufficiency becomes particularly important, as it is one of the factors determining the food security of any country. The aim of this research is to assess Ukraine’s food self-sufficiency compared to the European Union and Poland. The self-sufficiency ratio (SSR) index was used to assess food self-sufficiency. This is the ratio of the volume of production of the most important products of plant and animal origin to the volume of domestic consumption. Domestic consumption was defined as the volume of domestic production plus the volume of imports minus the volume of exports, and it also included changes in domestic stock levels. The surveyed time frame is 2019–2021. The analyzed data were taken from the State Statistics Service of Ukraine, FAOSTAT, USDA, and Statistics Poland. A comparative analysis of self-sufficiency for the main agri-food sectors of Ukraine, the EU, and Poland showed significant differences. Taking into account the production potential and food self-sufficiency indicators of Ukraine, Ukraine’s possible accession to the EU can be expected to have a major impact on the EU’s supply and demand situation, as it may pose a threat to many EU agri-food sectors.
Single-Person Households among the Socially Vulnerable Elderly Population: A Comparative Study of Housing, Living Habits, and Social Environments in Selected Neighborhoods of Seoul for the Prevention of Solitary Deaths
Authors: Kim Ho-Jeong , Park Joo-Ho , Park Na-Yeon , Moon Hyeun Jun
Published: September 2024

Solitary deaths, where individuals die alone and are isolated from the society, have emerged as a major social issue in South Korea. This study aimed to analyze the characteristics, perceptions, and living environments of socially vulnerable groups at risk of solitary deaths, focusing on comparing two neighborhood areas with different housing types to understand regional differences. In-depth interviews were conducted with 100 single-person households in the low-rise residential area of Sadang 4-dong and the public rental apartment area of the Gayang 5 apartment complex. The survey analysis revealed significant regional differences in factors that could influence the prevention of solitary deaths, including the connectivity between units within buildings, visual isolation, the control of appropriate indoor environments, and the frequency of social interactions. Although the Gayang 5 apartment complex, a public rental housing which is over 30 years old, offers advantages in residential safety and building maintenance compared to the low-rise residential area, this positively impacts aspects like housing satisfaction and increased social interactions. Single-person households living in multi-family and multi-household housing in low-rise residential areas generally experience poorer living environments, highlighting the need for more detailed services. These services should include enhanced support for heating and cooling costs, strengthened care services, and improved social networks. For preventing solitary deaths, region-specific strategies and screening tools are required to tailor interventions more effectively.
Corporate Financial Performance vs. Corporate Sustainability Performance, between Earnings Management and Process Improvement
Authors: Burcă Valentin , Bogdan Oana , Bunget Ovidiu-Constantin , Dumitrescu Alin-Constantin
Published: September 2024

The main objective of the paper is to assess the relationship between firms’ financial resilience and firms’ strategic sustainable development vulnerabilities, in the context of implications of the COVID-19 pandemic on firms’ business environment. Background: The last decade has emphasized an increase in business models’ uncertainty and risk exposure. The COVID-19 pandemic has highlighted the awareness in this direction, especially in a changing context, that looks more and more for corporate sector operations’ orientation towards sustainable development. The question we would address in this paper is how the nexus between corporate sustainability performance and corporate financial resilience is affected by management decision through process improvements, product quality assurance, or managers’ preference to improve corporate financials by earnings management practice instead, especially in the context of specific corporate financial risk management. Methods: The data are extracted from the Refinitiv database. The sample is limited to 275 European Union listed firms, selected based on data availability. The empirical analysis consists of an OLS multiple regression. For robustness purposes, a quantile regression model is estimated as well. Results: The approach considers implications of the pandemic on firms’ business environment and earnings management accounting based policies and strategies as well. The result suggests that alignment to sustainability frameworks lead to the deterioration of firms’ financial resilience. Similar results show the negative impact of firms’ financial vulnerability (credit default risk) on firms’ financial resilience. Instead, the risk of bankruptcy, firms’ liquidity, or high product quality and business process improvement determine the positive impact on firms’ financial resilience. Conclusions: The study highlights several insights both for management and policy makers. First, the results underline the relevance of management’s choice for earnings management on ensuring firms’ financial resilience, which ask for better corporate governance and high-quality and effective institutional regulatory and enforcement mechanisms. Second, the paper brings evidence on the impact of the COVID-19 pandemic on firms’ financial sustainable development. Third, the study emphasizes the importance of the efforts of corporate process improvements and high-quality products on generating value-add, by looking on the relevance of those drivers on the level of corporate economic value-add, a measure that limits the impact of discretionary management accrual-based accounting choices on our discussion.
Equity and Inclusion in Climate Action and Adaptation Plans of Michigan Cities
Authors: Lioubimtseva Elena , Zylman Hannah , Carron Katherine , Poynter Kaytlin , Rashrash Bushra Mohamed-Elmabruk
Published: September 2024

Community engagement in climate action and adaptation planning is an essential prerequisite for overcoming existing and projected environmental injustices associated with the negative impacts of climate change. The diversity and inclusion of stakeholders are crucial for addressing equity in both the development and implementation of local climate plans. Our study attempts to evaluate and compare consideration of equity in climate action and climate adaptation plans of Michigan cities and its association with the diversity of stakeholders involved in the planning process. Data analysis is based on the content of eight municipal climate action and/or climate adaptation plans, related documents, and interviews with city planners along with community activists. Data derived from the climate action and adaptation plans were also compared to the strategies outlined in the Tribal Climate Adaptation Menu, which integrates climate science and indigenous knowledge. The study concludes that municipalities that engage more diverse groups of stakeholders appear to be more attentive to social equity and more likely to offer specific climate action and adaptation measures focusing on vulnerable groups. The integration of indigenous knowledge could provide valuable insights for municipalities through collaboration with tribal communities and climate adaptation experts.
Automorphism Groups in Polyhedral Graphs
Authors: Ghorbani Modjtaba , Alidehi-Ravandi Razie , Dehmer Matthias
Published: September 2024

The study delves into the relationship between symmetry groups and automorphism groups in polyhedral graphs, emphasizing their interconnected nature and their significance in understanding the symmetries and structural properties of fullerenes. It highlights the visual importance of symmetry and its applications in architecture, as well as the mathematical structure of the automorphism group, which captures all of the symmetries of a graph. The paper also discusses the significance of groups in Abstract Algebra and their relevance to understanding the behavior of mathematical systems. Overall, the findings offer an inclusive understanding of the relationship between symmetry groups and automorphism groups, paving the way for further research in this area.
Interval-Valued Linguistic q-Rung Orthopair Fuzzy TODIM with Unknown Attribute Weight Information
Authors: Zhang Yushu , Tang Fangcheng , Song Zeyuan , Wang Jun
Published: September 2024

It is widely known that symmetry does exist in management systems, such as economics, management, and even daily life. In addition, effective and qualified decision-making methods can enhance the performance and symmetry of management systems. Hence, this paper focuses on a decision-making method. Linguistic interval-valued q-rung orthopair fuzzy sets (LIVq-ROFSs) have recently been proposed as being effective in describing decision-makers’ evaluation values in complex situations. This paper proposes a novel multi-attribute group decision-making (MAGDM) method with LIVq-ROFSs to handle realistic decision-making problems. The main contributions of this study are three-fold. First, a new method for determining the weight information of attributes based on decision makers’ evaluation values is proposed. Second, the classical TODIM is extended into LIVq-ROFSs and a new decision-making method is proposed. Third, our proposed MAGDM method is applied to a real decision-making problem to reveal its effectiveness.
Probing the Equation of State of Dense Nuclear Matter by Heavy Ion Collision Experiments
Authors: Senger Peter
Published: September 2024

The investigation of the nuclear matter equation of state (EOS) beyond saturation density has been a fundamental goal of heavy ion collision experiments for more than 40 years. First constraints on the EOS of symmetric nuclear matter at high densities were extracted from heavy ion data measured at AGS and GSI. At GSI, symmetry energy has also been investigated in nuclear collisions. These results of laboratory measurements are complemented by the analysis of recent astrophysical observations regarding the mass and radius of neutron stars and gravitational waves from neutron star merger events. The research programs of upcoming laboratory experiments include the study of the EOS at neutron star core densities and will also shed light on the elementary degrees of freedom of dense QCD matter. The status of the CBM experiment at FAIR and the perspective regarding the studies of the EOS of symmetric and asymmetric dense nuclear matter will be presented.
Using Task Support Requirements during Socio-Technical Systems Design
Authors: Gregoriades Andreas , Sutcliffe Alistair
Published: September 2024

Socio-technical systems (STSs) are systems of systems, synthesising human and IT components that jointly operate to achieve specific goals. Such systems are overly complex but, if designed optimally, they can significantly improve STS performance. Critical phases in STS design are defining the functional requirements for automated or software-supported human activities and addressing social and human interaction issues. To define automation support for human operations, STS designers need to ensure that specifications will satisfy not only the non-functional requirements (NFR) of the system but also of its human actors such as human reliability/workload. However, such human factors aspects are not addressed sufficiently with traditional STS design approaches, which could lead to STS failure or rejection. This paper proposes a new STS design method that addresses this problem and introduces a novel type of requirements, namely, Task Support Requirements (TSR) that assists in specifying the functionality that IT systems should have to support human agents in undertaking their tasks by addressing human limitations. The proposed method synthesises a requirements/software engineering approach to STS design with functional allocation and an HCI perspective, which facilitates the application of human factors knowledge in conceptual models and evaluation through VR simulation. A case study methodology is employed in this work that allows in-depth, multi-faceted explorations of the complex issues that characterise STSs. Two case studies are presented in this work; the first is a detailed illustration of how the method is applied during the design of an in-vehicle information system to enhance drivers’ situation awareness. The second is an empirical evaluation of the method using participants that apply it to design a mobile application to minimise the risk of pedestrian travellers conceiving a contagious disease while commuting in public space. The results from the empirical evaluation showed that the method positively contributes to STS design by addressing human factors issues effectively.
Comparison of Neural Recovery Effects of Botulinum Toxin Based on Administration Timing in Sciatic Nerve-Injured Rats
Authors: Seo Minsu , Hwang Seokjoon , Lee Tae Heon , Nam Kiyeun
Published: September 2024

This study aimed to assess the effects of the timing of administering botulinum neurotoxin A (BoNT/A) on nerve regeneration in rats. Sixty 6-week-old rats with a sciatic nerve injury were randomly divided into four groups: the immediately treated (IT) group (BoNT/A injection administered immediately post-injury), the delay-treated (DT) group (BoNT/A injection administered one week post-injury), the control group (saline administered one week post-injury), and the sham group (only skin and muscle incisions made). Nerve regeneration was assessed 3, 6, and 9 weeks post-injury using various techniques. The levels of glial fibrillary acid protein (GFAP), astroglial calcium-binding protein S100β (S100β), growth-associated protein 43 (GAP43), neurofilament 200 (NF200), and brain-derived neurotrophic factor (BDNF) in the IT and DT groups were higher. ELISA revealed the highest levels of these proteins in the IT group, followed by the DT and control groups. Toluidine blue staining revealed that the average area and myelin thickness were higher in the IT group. Electrophysiological studies revealed that the CMAP in the IT group was significantly higher than that in the control group, with the DT group exhibiting significant differences starting from week 8. The findings of the sciatic functional index analysis mirrored these results. Thus, administering BoNT/A injections immediately after a nerve injury is most effective for neural recovery. However, injections administered one week post-injury also significantly enhanced recovery. BoNT/A should be administered promptly after nerve damage; however, its administration during the non-acute phase is also beneficial.
Research on Responsible Innovation Performance Evaluation in the Blue Economic Zone of Marine Industry
Authors: Jiang Daokui , Wang Su , Chen Zhuo
Published: September 2024

Responsible innovation is attracting theoretical and practical research attention worldwide due to global climatic changes, severe resource shortages and intensifying environmental deterioration. However, there are still no studies concerning the performance evaluation of responsible innovation in the marine industry. Based on the practices of blue economic zones in China, a responsible innovation performance evaluation system for the marine industry was developed. Based on the data from 2013 to 2018, the responsible innovation performance of the blue economic zone of the marine industry in Shandong Province was evaluated by principal component analysis. The results demonstrated that (1) There was a rank of regions in terms of the comprehensive responsible innovation performance from high to low: Qingdao > Yantai > Weifang > Weihai > Dongying > Binzhou > Rizhao. (2) Considering annual variations, the comprehensive performance of responsible innovation of different regions exhibited slight fluctuations; however, Weihai had demonstrated significant improvement since 2016. (3) The performance trends across various regions indicated that regions exhibiting high performance consistently expanded their advantage over the six-year period. There was a “Matthew effect” in regional development, particularly evident in the disparities between Qingdao and other regions. (4) In regions that rank at the lower end, such as Rizhao, Binzhou, and Dongying, the development of responsible innovation progressed slowly. Finally, some management suggestions to improve innovation performance in the blue economic zone of the marine industry were proposed.
A Review on Recent Developments in the Extraction and Identification of Polycyclic Aromatic Hydrocarbons from Environmental Samples
Authors: Mogashane Tumelo Monty , Mokoena Lebohang , Tshilongo James
Published: September 2024

A class of hazardous chemical molecules known as polycyclic aromatic hydrocarbons (PAHs) are frequently detected in environmental samples such as soil, water, and air. Because of their carcinogenic and mutagenic qualities, PAHs pose a significant threat to both human health and the environment. Therefore, the identification and extraction of PAHs from environmental samples is crucial for monitoring and assessing their presence and potential risks. An overview of these recent advancements is given in this review, which includes the use of sophisticated analytical methods for the identification and measurement of PAHs in environmental samples, such as high-performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS). The limitations of conventional extraction techniques such as Soxhlet extraction and liquid-liquid extraction, which are frequently labour-intensive, solvent-intensive, and prone to low selectivity, are highlighted in this review. In contrast, modern techniques such as Solid-Phase Microextraction (SPME) and Accelerated Solvent Extraction (ASE) offer significant advantages, including reduced solvent use, faster processing times, and enhanced sensitivity and selectivity for PAHs. This review highlights the benefits of these advancements in facilitating faster, more accurate, and environmentally friendly PAH extraction and identification processes, focusing on overcoming the limitations of traditional methods such as chromatographic separation and detection. To improve our comprehension of PAH contamination and provide practical mitigation methods for their effects on the environment and human health, this field needs ongoing research and development.
Synthesis and Characterization of Potassium Bicarbonate and Urea-Modified Biochar from Rape Straw: Application in the Removal of Tetracycline from Aqueous Solution
Authors: Zhang Zhipeng , Tang Chenghan , Wang Hongbin , Zhong Ming , Ge Pengchao , Xu Wenlai , Chen Yiyang
Published: September 2024

Using rapeseed straw as a raw material and potassium bicarbonate (KHCO3) and urea (CO(NH2)2) as modification reagents, the pyrolysis raw materials were mixed in a certain proportion, and the unmodified biochar GBC800, KHCO3-modified biochar KGBC800, and (KHCO3)/(CO(NH2)2) co-modified biochar N-KGBC800 were, respectively, prepared using the one-pot method at 800 °C. The physicochemical properties, such as surface morphology, pore characteristics, functional group distribution, and elemental composition of the three biochars, were characterized, and the adsorption performance and mechanism of the typical antibiotic tetracycline (TC) in water were studied. The results showed that the surface of GBC800 was smooth and dense, with no obvious pore structure, and both the specific surface area and total pore volume were small; the surface of KGBC800 showed an obvious coral-like three-dimensional carbon skeleton, the number of micropores and the specific surface area were significantly improved, and the degree of carbonization and aromatization was enhanced; N-KGBC800 had a coral-like three-dimensional carbon skeleton similar to KGBC800, and there were also many clustered carbon groups. The carbon layer changed significantly with interlayer gaps, presenting a multi-level porous structure. After N doping, the content of N increased, and new nitrogen-containing functional groups were formed. When the initial TC concentration was 100 mg/L, pH ≈ 3.4, the temperature was 25 °C, and the dosage of the three biochars was 0.15 g/L, the adsorption equilibrium was reached before 720 min. The adsorption capacities of GBC800, KGBC800, and N-KGBC800 for TC were 16.97 mg/g, 294.86 mg/g, and 604.71 mg/g, respectively. Fitting the kinetic model to the experimental data, the adsorption of TC by the three biochars was more in line with the pseudo-second-order adsorption kinetic model, and the adsorption isotherm was more in line with the Langmuir model. This adsorption process was a spontaneous endothermic reaction, mainly chemical adsorption, specifically involving multiple adsorption mechanisms such as pore filling, electrostatic attraction, hydrogen bonds, n−π interaction, Lewis acid–base interaction, π−π stacking, or cation −π interaction between the aromatic ring structure of the carbon itself and TC. A biochar-adsorption column was built to investigate the dynamic adsorption process of tetracycline using the three biochars against the background of laboratory pure water and salt water. The adsorption results show that the Thomas model and the Yoon–Nelson model both provide better predictions for dynamic adsorption processes. The modified biochars KGBC800 and N-KGBC800 can be used as preferred materials for the efficient adsorption of TC in water.