bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Intelligent Design and Visualization of Gas Extraction Drilling Based on PSO–LSTM
Authors: Yin Yongming , Wang Dacang , Zhu Quanjie , Yang Guangyu , Chen Xuexi , Liu Xiaohui , Liu Yongfeng
Published: August 2024

Under the background of intelligent construction of coal mines, gas extraction design is still based on manual design, which is complex, time–consuming, and error–prone, and its automation degree needs to be improved. In order to solve this problem, taking the 1302 working face of a mine in Shanxi Province as the research object, this paper carried out relevant research. Firstly, the influencing factors of gas extraction were determined, and the influence rules of different parameters on the extraction effect were studied by numerical simulation. Secondly, an intelligent optimization method of gas extraction drilling parameters based on deep mining called the PSO–LSTM model, is proposed. This model uses the PSO algorithm to optimize the parameters of the LSTM model, so as to improve the accuracy of the LSTM model results. Finally, a quantitative expression algorithm of 3D spatial information of gas extraction drilling holes based on Python is proposed, which can automatically generate 3D spatial models of bedding or through gas extraction drilling holes using optimized drilling parameters and known 3D information of coal seams. This study shows that the results obtained using the PSO–LSTM model are the same as the drilling parameters obtained using numerical simulation, which verifies the accuracy of the PSO–LSTM model. According to the optimized drilling parameters, a 3D model of gas extraction drilling is quickly generated, which greatly reduces the tedious work of drawing construction drawings for coal mine enterprises and improves the intelligence level of coal gas extraction drilling.
Plant-Based Substrates for the Production of Iron Bionanoparticles (Fe-BNPs) and Application in PCB Degradation with Bacterial Strains
Authors: Tlčíková Marcela , Horváthová Hana , Dercová Katarína , Majčinová Michaela , Hurbanová Mariana , Turanská Katarína , Jurkovič Ľubomír
Published: August 2024

Removing polychlorinated biphenyls (PCBs) from the environment is an important process for the protection of biota. This work examines three different approaches to the degradation of such contaminants. The first involves the use of iron bionanoparticles (Fe-BNPs) prepared through green synthesis from selected plant matrices. The second approach entails the use of the bacteria Stenotrophomonas maltophilia (SM) and Ochrobactrum anthropi (OA) isolated from a PCB-contaminated area, Strážsky canal, located in the Slovak republic, which receives efflux of canal from Chemko Strážske plant, a former producer of PCB mixtures. The third approach combines these two methods, employing a sequential hybrid two-step application of Fe-BNPs from the plant matrix followed by the application of bacterial strains. Fe-BNPs are intended to be an eco-friendly alternative to synthetic nanoscale zero-valent iron (nZVI), which is commonly used in many environmental applications. This work also addresses the optimization parameters for using nZVI in PCB degradation, including the pH of the reaction, oxygen requirements, and dosage of nZVI. Pure standards of polyphenols (gallic acid, GA) and flavonoids (quercetin, Q) were tested to produce Fe-BNPs using green synthesis at different concentrations (0.1, 0.3, 0.5, 0.8, and 1 g.L−1) and were subsequently applied to the PCB degradation experiments. This step monitored the minimum content of bioactive substances needed for the synthesis of Fe-BNPs and their degradation effects. Experimental analysis indicated that among the selected approaches, sequential nanobiodegradation appears to be the most effective for PCB degradation, specifically the combination of Fe-BNPs from sage and bacteria SM (75% degradation of PCBs) and Fe-BNPs from GA (0.3 g.L−1) with bacteria OA (92% degradation of PCBs).
A Diffusion Model to Describe Water Absorption by Red Rice during Soaking: Variable Mass Diffusivity, Variable Volume, Use of Boundary-Fitted Coordinates
Authors: da Silva Wilton Pereira , de Lima Antonio Gilson Barbosa , Pereira Joan Carlos Alves , Gomes Josivanda Palmeira , Queiroz Alexandre José de Melo , de Figueirêdo Rossana Maria Feitosa , Paiva Yaroslávia Ferreira , dos Santos Francislaine Suélia , de Melo Bruno Adelino , Moura Henrique Valentim , Silva Eugênia Teles de Vilela , da Silva Júnior Aluizio Freire , de Souto Leidjane Matos
Published: August 2024

This article aims to carry out experiments on water absorption by husked red rice at constant temperatures of 28, 40, and 50 °C. The description of the absorption kinetics and the analyses of the water distribution and volumetric expansion of each grain, at a given instant, were carried out using a diffusion model. In order for the model to be as close as possible to the real physical situation, the mesh necessary to numerically solve the diffusion equation was generated from the photograph of a grain. Thus, the diffusion equation was written in Boundary-Fitted Coordinates (BFCs). The solution of the diffusion equation written in generalized coordinates was then discretized in space and time, using the Finite Volume method, with a fully implicit formulation, considering the variable volume and variable mass diffusivity as functions of the local moisture content. Optimizations based on the Levenberg–Marquardt algorithm make it possible to determine the parameters of an exponential function relating mass diffusivity and the local moisture content for each temperature. Statistical indicators (chi-square, determination coefficient, and Student’s t-test) allowed us to conclude that the proposed model was very satisfactory for all temperatures, making it possible to simulate the water absorption, water distribution, and volumetric expansion of the grain over time.
Is Minimal Change Disease Associated with Prostate Cancer or Is Age Just a Number?
Authors: Kleinová Patrícia , Vnučák Matej , Graňák Karol , Beliančinová Monika , Blichová Tímea , Dedinská Ivana
Published: August 2024

Background: Prostate cancer is the most common malignancy in men. Secondary nephrotic syndrome, a feature of paraneoplastic syndrome, occurs in 11% of cases and is mainly caused by membranous glomerulopathy. The association between minimal change disease and prostate cancer is rare. Only one cause has been described in the available literature. Case presentation: We present the case of a 77-year-old patient who was admitted to our department with stage 3 acute kidney injury and with nephrotic syndrome with anasarca (creatinine: 168 µmol/L, eGFR: 33 mL/min/1.73 m2, albumin: 18.5 g/L, total cholesterol: 6.86 mmol/L, urine albumin creatinine ratio: 812.7 mg/mmol). In the differential diagnosis of nephrotic syndrome, looking for a secondary cause is essential, so the parainfectious causes of nephrotic syndrome were excluded. An elevated prostate-specific antigen (10.69 ng/L) was found when screening for oncological causes, and prostate adenocarcinoma was identified on biopsy. A renal biopsy was then performed with a finding of minimal change disease. Despite the generally accepted guidelines of prostate carcinoma in that stage and age of the patient being watchful waiting, antiandrogen therapy was started with the cooperation of a urologist. There was a significant improvement in renal parameters in the patient (creatinine: 87 µmol/L, eGFR: 73 mL/min/1.73 m2, albumin: 33.4 g/L, urine albumin creatinine ratio: 27.6 mg/mmol). Conclusion: This case shows the importance of multidisciplinary cooperation in the treatment of secondary causes of nephrotic syndrome. In the case of proven paraneoplastic syndrome, it is necessary to start treating the malignancy; however, in general, a conservative approach without treatment is recommended.
SAR Temporal Shifting: A New Approach for Optical-to-SAR Translation with Consistent Viewing Geometry
Authors: Rangzan Moien , Attarchi Sara , Gloaguen Richard , Alavipanah Seyed Kazem
Published: August 2024

In contrast to the well-investigated field of Synthetic Aperture Radar (SAR)-to-Optical translation, this study explores the lesser-investigated domain of Optical-to-SAR translation, which is a challenging field due to the ill-posed nature of this translation. The complexity arises as single optical data can have multiple SAR representations based on the SAR viewing geometry. To generate an SAR image with a specific viewing geometry, we propose a novel approach, which is termed SAR Temporal Shifting. Our model takes an optical image from the target timestamp and an SAR image from a different temporal point but with a consistent viewing geometry as the expected SAR image. Both of these inputs are complemented with a change map derived from optical images during the intervening period. This model then modifies the SAR data based on the changes observed in the optical data to generate the SAR data for the desired timestamp. Although similar strategies have been explored in the opposite SAR-to-Optical translation, our approach innovates by introducing new spatial evaluation metrics and cost functions. These metrics reveal that simply adding same-domain data as model input, without accounting for the distribution changes in the dataset, can result in model overfitting—even if traditional metrics suggest positive outcomes. To address this issue, we have introduced a change-weighted loss function that discourages the model from merely replicating input data by assigning greater cost to changes in the areas of interest. Our approach surpasses traditional translation methods by eliminating the Generative Adversarial Network’s (GAN’s) fiction phenomenon by learning to change the SAR data based on the optical data instead of solely relying on translation. Furthering the field, we have introduced a novel automated framework to build a despeckled multitemporal SAR–Optical dataset with consistent viewing geometry. We provide the code and the dataset used in our study.
TMP-Net: Terrain Matching and Positioning Network by Highly Reliable Airborne Synthetic Aperture Radar Altimeter
Authors: Lu Yanxi , Song Anna , Liu Gaozheng , Tan Longlong , Xu Yushi , Li Fang , Wang Yao , Jiang Ge , Yang Lei
Published: August 2024

Airborne aircrafts are dependent on the Global Navigation Satellite System (GNSS), which is susceptible to interference due to the satellite base-station and cooperative communication. Synthetic aperture radar altimeter (SARAL) provides the ability to measure the topographic terrain for matching with Digital Elevation Model (DEM) to achieve positioning without relying on GNSS. However, due to the near-vertical coupling in the delay-Doppler map (DDM), the similarity of DDMs of adjacent apertures is high, and the probability of successful matching is low. To this end, a novel neural network of terrain matching and aircraft positioning is proposed based on the airborne SARAL imagery. The model-driven terrain matching and aircraft positioning network (TMP-Net) is capable of realizing aircraft positioning by utilizing the real-time DDMs to match with the DEM-based DDM references, which are generated by a point-by-point coupling mechanism between the airborne routine and ground terrain DEM. Specifically, the training dataset is established by a numerical simulation method based on a semi-analytical model. Therefore, DEM-based DDM references can be generated by forward deduction when only regional DEM can be obtained. In addition to the model-based DDM generation, feature extraction, and similarity measurement, an aircraft positioning module is added. Three different positioning methods are designed to achieve the aircraft positioning, where three-point weighting exhibits the best performance in terms of positioning accuracy. Due to the fact that both the weighted triplet loss and softmax loss are employed in a cooperative manner, the matching accuracy can be improved and the positioning error can be reduced. Finally, both simulated and measured airborne datasets are used to validate the effectiveness of the proposed algorithm. Quantitative and qualitative evaluations show the superiority.
Off-Axis Integral Cavity Carbon Dioxide Gas Sensor Based on Machine-Learning-Based Optimization
Authors: Li Pengbo , Lin Guanyu , Chen Jianbo , Wang Jianing
Published: August 2024

Accurately detecting atmospheric carbon dioxide is a vital part of responding to the global greenhouse effect. Conventional off-axis integral cavity detection systems are computationally intensive and susceptible to environmental factors. This study deploys an Extreme Learning Machine model incorporating a cascaded integrator comb (CIC) filter into the off-axis integrating cavity. It is shown that appropriate parameters can effectively improve the performance of the instrument in terms of lower detection limit, accuracy, and root mean square deviation. The proposed method is incorporated successfully into a monitoring station situated near an industrial area for detecting atmospheric carbon dioxide (CO2) concentration daily.
NMC3D: Non-Overlapping Multi-Camera Calibration Based on Sparse 3D Map
Authors: Dai Changshuai , Han Ting , Luo Yang , Wang Mengyi , Cai Guorong , Su Jinhe , Gong Zheng , Liu Niansheng
Published: August 2024

With the advancement of computer vision and sensor technologies, many multi-camera systems are being developed for the control, planning, and other functionalities of unmanned systems or robots. The calibration of multi-camera systems determines the accuracy of their operation. However, calibration of multi-camera systems without overlapping parts is inaccurate. Furthermore, the potential of feature matching points and their spatial extent in calculating the extrinsic parameters of multi-camera systems has not yet been fully realized. To this end, we propose a multi-camera calibration algorithm to solve the problem of the high-precision calibration of multi-camera systems without overlapping parts. The calibration of multi-camera systems is simplified to the problem of solving the transformation relationship of extrinsic parameters using a map constructed by multiple cameras. Firstly, the calibration environment map is constructed by running the SLAM algorithm separately for each camera in the multi-camera system in closed-loop motion. Secondly, uniformly distributed matching points are selected among the similar feature points between the maps. Then, these matching points are used to solve the transformation relationship between the multi-camera external parameters. Finally, the reprojection error is minimized to optimize the extrinsic parameter transformation relationship. We conduct comprehensive experiments in multiple scenarios and provide results of the extrinsic parameters for multiple cameras. The results demonstrate that the proposed method accurately calibrates the extrinsic parameters for multiple cameras, even under conditions where the main camera and auxiliary cameras rotate 180°.
Automatic Path-Planning Techniques for Minimally Invasive Stereotactic Neurosurgical Procedures—A Systematic Review
Authors: Monfaredi Reza , Concepcion-Gonzalez Alondra , Acosta Julbe Jose , Fischer Elizabeth , Hernandez-Herrera Gabriel , Cleary Kevin , Oluigbo Chima
Published: August 2024

This review systematically examines the recent research from the past decade on diverse path-planning algorithms tailored for stereotactic neurosurgery applications. Our comprehensive investigation involved a thorough search of scholarly papers from Google Scholar, PubMed, IEEE Xplore, and Scopus, utilizing stringent inclusion and exclusion criteria. The screening and selection process was meticulously conducted by a multidisciplinary team comprising three medical students, robotic experts with specialized knowledge in path-planning techniques and medical robotics, and a board-certified neurosurgeon. Each selected paper was reviewed in detail, and the findings were synthesized and reported in this review. The paper is organized around three different types of intervention tools: straight needles, steerable needles, and concentric tube robots. We provide an in-depth analysis of various path-planning algorithms applicable to both single and multi-target scenarios. Multi-target planning techniques are only discussed for straight tools as there is no published work on multi-target planning for steerable needles and concentric tube robots. Additionally, we discuss the imaging modalities employed, the critical anatomical structures considered during path planning, and the current status of research regarding its translation to clinical human studies. To the best of our knowledge and as a conclusion from this systematic review, this is the first review paper published in the last decade that reports various path-planning techniques for different types of tools for minimally invasive neurosurgical applications. Furthermore, this review outlines future trends and identifies existing technology gaps within the field. By highlighting these aspects, we aim to provide a comprehensive overview that can guide future research and development in path planning for stereotactic neurosurgery, ultimately contributing to the advancement of safer and more effective neurosurgical procedures.
Specifics of Data Collection and Data Processing during Formation of RailVista Dataset for Machine Learning- and Deep Learning-Based Applications
Authors: Abisheva Gulsipat , Goranin Nikolaj , Razakhova Bibigul , Aidynov Tolegen , Satybaldina Dina
Published: August 2024

This paper presents the methodology and outcomes of creating the Rail Vista dataset, designed for detecting defects on railway tracks using machine and deep learning techniques. The dataset comprises 200,000 high-resolution images categorized into 19 distinct classes covering various railway infrastructure defects. The data collection involved a meticulous process including complex image capture methods, distortion techniques for data enrichment, and secure storage in a data warehouse using efficient binary file formats. This structured dataset facilitates effective training of machine/deep learning models, enhancing automated defect detection systems in railway safety and maintenance applications. The study underscores the critical role of high-quality datasets in advancing machine learning applications within the railway domain, highlighting future prospects for improving safety and reliability through automated recognition technologies.
Generation and Evaluation of an Efficient Femtosecond Green Laser
Authors: Teng Mingyang , Meng Xianghao
Published: August 2024

We demonstrate femtosecond ultra-stable green laser generation by an ytterbium-doped polarization-maintaining fiber laser with a 2.4 mm long lithium triborate (LBO) crystal. We generated 5.6 W of femtosecond green light at 520 nm for a fundamental power of 12 W, which corresponds to a conversion efficiency of 46.7%. The fiber chirped-pulse amplifier, which has an environmentally immune front end, delivered 170 fs pulses at a 75 MHz repetition rate centered at 1040 nm. According to the dispersion of the optical material in a double-frequency setup, the introduced dispersion had a negligible effect for the green laser, and the pulse duration of the generated green laser was calculated to be 171 fs, resulting in an excellent power stability, with fluctuation as low as 0.16% of the generated green light. This system could be of great interest in ultrafast optical and photobiology research.
Patents and Public Health: State Responsibility to Opt for a Balanced Approach
Authors: Butt Saima , Shaukat Kamran , Alam Talha Mahboob , Jan Tony
Published: August 2024

The topic of public health is indispensable to talk about. It is essential to discuss new inventions, new and improved treatments, and their efficiencies with different combinations, but one thing that is important to remember is whether these inventions are available for those in need. Availability concerns are linked with affordability, as the affordability of a drug determines its consumption; furthermore, affordability can lead to overconsumption. The Trade-Related Aspects of Intellectual Property Rights (TRIPS) Agreement provides flexibility to control the misuse of patent monopolies. The object of this research is twofold: one is to investigate whether and how Pakistan incorporates TRIPS flexibilities in its national patent legislation, and the second is to find out the reason for unaffordable cancer treatment in Pakistan. This research highlights that the use of TRIPS flexibilities in Pakistan will help the state authorities to provide better health facilities to the public generally as well as particularly in cancer cases, as cancer treatment in Pakistan is unaffordable. The methodology applied for this research is primarily comparative and bears the qualitative aspect of the issue. This research concludes that Pakistan’s legal system fails to incorporate effective legal provisions related to TRIPS flexibilities, and it also highlights that the ever-greening of patents results in the high prices of cancer medicines in Pakistan. This research further recommended that there is a dire need to incorporate and use TRIPS flexibilities in the country to control the high prices of cancer treatment and cancer mortality rate in the country.
Adverse Consequences of Crime Victimization for School-Aged Girls in South Korea
Authors: Han Sungil , O Min-Suk , Choi Jaeyong
Published: August 2024

Crime victimization is one of the most stressful negative events and brings numerous adverse outcomes to victims. Victims suffer from physical damage, property loss, psychological trauma, and behavioral problems. Many studies have examined these adverse consequences of crime victimization, but a comprehensive approach for victims who are school-aged girls has been relatively under-documented. To fill the gap in the literature, this study analyzes data from a nationally representative sample of Korean school-aged girls (N = 3762). The results of the regression analyses indicate that previous victimization is associated with lower life satisfaction, increased negative emotions, and a fear of crime, and appears to elevate the risk of revictimization and delinquent behavior. It is concluded that victims should be treated with appropriate resources and support to reduce future adverse outcomes.
Assessing Urban Ventilation in Common Street Morphologies for Climate-Responsive Design toward Effective Outdoor Space Regeneration
Authors: Ruda Sarria Francisco , Guerrero Delgado MCarmen , Sánchez Ramos José , Palomo Amores Teresa , Molina Félix José Luis , Álvarez Domínguez Servando
Published: August 2024

Urban heat islands are an environmental hazard which degrade people’s lives worldwide, reducing social life and increasing health problems, forcing scientists to design innovative acclimatization methods in public places, such as sheltering. This paper focuses on providing quantitative indicators about airflow rates and qualitative information about airflow patterns in street canyons for typical street canyon morphologies, which is essential when designing outdoor acclimatization strategies to mitigate urban overheating. This is based on CFD simulations using an enhanced numerical domain model, which can reduce computational cost and simulation time. The study is performed for different ARs, from wide (AR = 0.75) to narrow (AR = 4), and wind speed to characterize their effect on street ventilation The results show that air renewal decreases while the AR increases. The reduction is faster for a low AR and then comes to a standstill for a high AR. In addition, the study shows that inside narrow streets, the pattern of airflow is affected by the wind velocity magnitude. These findings provide numerical values of air ventilation for a wide range of typical street canyon configurations, which represent essential data for designing effective climate control strategies, mitigating urban heat islands and conducting outdoor thermal comfort studies. This work contributes valuable knowledge to the multidisciplinary efforts aimed at enhancing urban living environments.
The NYMPHA Algae Extract as a New Consolidant for the Restoration of Cultural Heritage: Studies and Considerations on Its Effectiveness on Painted Marble
Authors: Di Fazio Melania , Fratello Chiara , Paglialunga Giulia , Mignardi Silvano , Vergelli Lisa , Frasca Francesca , Rigon Carolina , Ioele Marcella , Gioventù Eleonora , Antonacci Amina , Favero Gabriele , Medeghini Laura
Published: August 2024

This work aimed to assess the potential efficacy of a novel polysaccharides-based extract as a green consolidant for the pictorial layer on marble substrates. Understanding its properties could lead to determining whether it can ensure the correct conservation and transmission of the cultural heritage. Four different types of marble specimens were prepared with paint based on malachite (egg, tempera grassa, rabbit glue, and linseed oil as binders). Colorimetric analyses, peeling tests, SEM-EDS, and FTIR spectroscopy were used to test the properties of the consolidant. Results reveal that no aesthetic changes occur when using the extract on painted surfaces and that the cohesive properties of most pictorial films increase after its application, confirming the consolidating effect. In conclusion, the use of an innovative green product for the restoration of marble-painted surfaces can be considered a possible good solution for consolidating treatment. Through this initial explorative research, we suggest an innovative approach to the protection of cultural heritage that doesn’t cause harm to both the restorer’s health and the environment.
Effects of Biochar under Different Preparation Conditions on the Growth of Capsicum
Authors: Xie Haiwei , Zhou Xuan , Zhang Yan
Published: August 2024

Biochar return to the field has been widely explored, but there is a problematic disconnect between biochar preparation and biochar return to the field. In this study, soybean straw is used as a raw material and is sieved into two components: 60-mesh (0.250 mm) and 110-mesh (0.130 mm). Four kinds of biochar were obtained by pyrolysis under the condition of no heat preservation and heat preservation for 60 min. The biochar was applied to the soil, and the effects of biochar on soil and capsicum growth were analyzed by Spearman correlation. Compared with the control group, soil pH, soil electrical conductivity, and soil organic matter decomposition were increased by 0.58, 101 μs/cm, and 9.48%, respectively. The fruit quantity, plant height, water, fat, soluble solid, and titrable acidity of capsicum were increased by 1, 0.55, 0.08, 0.62, 0.67, and 0.7 times, respectively. Spearman correlation analysis showed that soil properties and capsicum growth were most affected by biochar’s specific surface area (SSA). Therefore, increasing the biomass mesh number and heat preservation time is beneficial to increasing the SSA of biochar and facilitating the return of biochar to the field and the best preparation conditions are 110-mesh soybean straw biomass pyrolysis and heat preservation for 60 min.
The Influence of Hydrogen Addition on a SI Engine—Theoretical and Experimental Investigations
Authors: Georgescu Rareș , Pană Constantin , Negurescu Niculae , Cernat Alexandru , Nuțu Cristian , Sandu Cristian
Published: August 2024

In a world with severe pollution regulations and restrictions imposed to internal combustion engines, improving efficiency and reducing pollutant emissions and greenhouse gases are important goals for researchers. A highly effective method to achieve the premises written above is to use alternative fuels, which may have a strong influence on combustion processes in spark ignition engines. In order to increase the heat release rate during combustion, the brake thermal efficiency, and to decrease the levels of pollutant emissions and greenhouse gases, the use of sustainable alternative fuels, in parallel with conventional fuels is a great choice. Among alternative fuels, hydrogen is an excellent fuel in terms of its physical-chemical properties, making it an attractive replacement for classic fuels in the combustion process. This article demonstrates AMESim 13.0.0/Rev13 theoretical and experimental investigations conducted on a supercharged spark ignition engine at 55% engine load and 2500 rpm speed, analyzes the effect of 2.15% hydrogen that substitutes gasoline on combustion, implicitly investigates energy and fuel efficiency of the engine and investigates pollutant and greenhouse gas emission levels. These experimental investigations confirm the theoretical study of thermo-gas-dynamic processes of a SI engine fueled with gasoline and hydrogen, and it shows the importance of engine tunings and hydrogen quantity on engine operation. The obtained results indicate the advantages of fueling the engine with both gasoline and hydrogen: the increase of the heat release rate which leads to the increase of maximum pressure and maximum pressure rise rate during combustion, the increase of the brake thermal efficiency, the decrease of the combustion duration, the decrease of the brake specific energetic consumption by 4.8%, the decrease of the levels of pollutant emissions by 11.11% for unburned hydrocarbons HC, by 12.5% for monoxide carbon CO, by 63.23% for nitrogen oxides NOx, and by 33.7% for carbon dioxide CO2 as a greenhouse gas. Further research directions can be developed from this research for other operating regimes and other hydrogen quantities.
Application of Green Management in the Teaching, Research, and Practice of Human Resource Management
Authors: Zhou Chong , Zeng Zeng
Published: August 2024

Characteristics of green management in saving costs and promoting sustainable development have been widely recognized but advanced green management theory has not been well integrated into the curriculum of human resource management majors. This study analyzes the challenges faced by green management practices from the perspective of teachers’ teaching and scientific research, notes the urgency of integrating green management into the teaching and research of human resource management majors, and proposes a methodology and teaching reform ideas for integrating green management theory and green management modes into the practice of human resource management majors’ courses. Comparative and case study research methods are used to analyze and demonstrate the application of green management theories and models in teaching and research in human resource management. Incorporating the green management theory and model into the teaching and research of human resource management can encourage enterprises to become “people-oriented”, value employees, pursue sustainable development, and achieve the organic unity of economic, social, and ecological benefits. Integrating green management into the teaching and research of human resource management enriches course content, promotes the effective combination of professional knowledge and application practice, and provides research methodology and theoretical support for teachers and students to conduct scientific research.
Analysis of the Impact of Urban Infrastructure on Urbanization Processes at Different Levels from a Spatiotemporal Perspective
Authors: Wu Yunjie , Qian Peng , Yang Lei , Tian Zhuang , Luo Jieqiong
Published: August 2024

A comprehensive understanding of the heterogeneity of urbanization development at different levels and its influencing factors is crucial for promoting global urbanization and advancing China’s new urbanization. Using indicators related to urbanization development, a multidimensional index system was constructed based on five dimensions: population, economy, space, society, and ecology. Employing methods such as the Mann–Kendall test, Sen’s trend analysis, multiple linear regression, and spatial autocorrelation analysis, the spatiotemporal evolution characteristics of urbanization from 2000 to 2019 were analyzed comprehensively at national, economic zone, provincial, and prefectural city scales. The results indicate the following. (1) From 2000 to 2019, urbanization levels at all levels showed an overall upward trend, with the national urbanization rate increasing most rapidly at 5.39%. (2) Trend analysis reveals rapid and significant growth trends in urbanization at the national and economic zone scales, while urban-level changes exhibit greater diversity and spatiotemporal heterogeneity. (3) Spatial distribution patterns show that urbanization levels in the eastern coastal economic zones are significantly higher than those in the northeastern economic zones, highlighting pronounced regional disparities in development and agglomeration effects in economically advanced regions and provinces. (4) Regression analysis demonstrates that spatial urbanization significantly influences urbanization development in China, with urban infrastructure playing a crucial role across different levels.
Positive Effect of Biochar Application on Soil Properties: Solubility and Speciation of Heavy Metals in Non-Acidic Contaminated Soils near a Steel Metallurgical Plant in Southeastern Europe
Authors: Stoykova Mariela , Atanassova Irena , Benkova Maya , Simeonova Tsetska , Nenova Lyuba , Harizanova Milena , Atsenova Milchena
Published: August 2024

Neutral and slightly alkaline arable soils from the vicinity of the former and the biggest metallurgical plant in southeastern Europe were analyzed for the status of the water soluble pool of heavy metals in 1–20% w/w biochar (BC)-amended contaminated soils. Heavy metal solubility was monitored over a 6-month period. The metals (Fe, Mn, Cu, Zn, Cd, Pb and Ba) exhibited significant relationships between each other and exceeded the maximum permissible concentrations (MPC) in surface waters for domestic and drinking purposes. In most of the investigated sites and BC treatments, metal concentrations decreased with time due to the transfer to more resistant soil pools. Cation exchange capacity, exchangeable Ca and pH increased after BC application, while electrical conductivity decreased. BC amendment led to the prevalence of humic acids (HAs) over fulvic acids (FAs) and increased the fraction of refractory organic carbon. The share of metal–organic complexes increased for the metals Zn, Cd, Mn and Ba in the BC-amended soils, and the share of free Me2+ species decreased. This trend was especially pronounced in the soils with the lowest pH of 6.4–6.9. In addition to improving soil physicochemical and ecochemical properties, biochar application contributed to metal species in solutions that were less mobile and bioavailable.
Exploring Factors Influencing Consumers’ Willingness to Pay Healthy-Labeled Foods at a Premium Price
Authors: Ghazanfari Sima , Firoozzare Ali , Covino Daniela , Boccia Flavio , Palmieri Nadia
Published: August 2024

Food safety in developing countries has always been a concern, and deciding to purchase foods with a healthy label can be challenging. The goal of this study was to investigate the behavior of consumers for healthy foods by evaluating the factors influencing the prevalence of purchasing them despite having to pay a premium. Required data were collected in 2022 from 359 households in Mashhad, Iran, through an online questionnaire. A Generalized Poisson model was employed for analysis and the results indicate that the consumer’s field of study, the importance of food shape and size, the importance of food healthiness, the level of government supervision, practicing the 5Rs, awareness of the harmful effects of fast food on health (1% level) and variables of trust in a brand of healthy food, and the level of knowledge about the harmful effects of chemical fertilizers and toxins on human health (10% level) have a direct and significant relationship with consumers’ willingness to purchase more healthy foods for which they are willing to pay a premium. On the other hand, the relationship of some other factors, such as the importance of food price (1% level) and household size, household expenses, presence of individuals over 60 years old in the household, and the importance of food taste and flavor (5% level) became negative and significant. Therefore, to promote the consumption of foods with a healthy label for the purpose of reducing environmental issues and human health problems, it is recommended to produce and offer various healthy foods, create local markets, provide discounts and economic incentives to the public, and use attractive packaging with accurate and readable labels.
Assessment of Green Innovation Efficiency in Chinese Industrial Enterprises Based on an Improved Relational Two-Stage DEA Approach: Regional Disparities and Convergence Analysis
Authors: Chen Xiaohong , Xu Ruochen
Published: August 2024

Industrial enterprises are characterized by significant energy consumption and high emissions. Therefore, the implementation of green innovation by these enterprises is beneficial for promoting sustainable economic development and safeguarding the ecological environment. In this study, a relational two-stage DEA model containing shared inputs and undesired outputs is constructed to evaluate and decompose the green innovation efficiency (GIE) of Chinese industrial enterprises across 30 provinces from 2012 to 2021. Since the objective function of this model is nonlinear, a heuristic search method is employed for its resolution. On the basis of efficiency evaluation, the Gini coefficient, kernel density estimation, and convergence analysis are further employed to investigate the regional disparities and convergence properties in the two-stage efficiency of green innovation. Our findings are as follows: (1) The average GIE of Chinese industrial enterprises demonstrates a fluctuating upward trajectory, with significant regional disparities observed between provinces. (2) Regional disparities in R&D efficiency (RDE) and achievement conversion efficiency (ACE) have diminished in all regions. Super-variable density and interregional differences serve as the primary sources of regional disparities in RDE and ACE, respectively. (3) The presence of absolute and conditional convergence in RDE and ACE is observed across all regions. To improve the GIE of Chinese industrial enterprises, it is imperative to emphasize the heterogeneous impact of economic levels, industrial structure, and the degree of openness across various regions and stages of green innovation.
Investigating Polylactic Acid Foam–Plant Fiber Composites for Sound Absorption and Insulation
Authors: Rotini Federico , Fiorineschi Lorenzo , Conti Leonardo , Rossi Giuseppe
Published: August 2024

This study explores the acoustic properties of composite biomaterials using a polylactic acid (PLA) matrix reinforced by plant fibers for sound insulation applications. Acoustic tests evaluated the absorption coefficient, reflection factor, and characteristic impedance, examining various configurations with different thicknesses of the composite biomaterial. The combinations of PLA/grape stem and PLA/wood straw were analyzed for their acoustic behaviors. Grape stems and wood straw were chosen because they are abundant, undervalued waste materials, especially in Italian regions like Tuscany. Therefore, using these materials in composite biomaterials could offer opportunities for valorization. The findings highlight the impact of plant fiber characteristics on acoustic properties, emphasizing the need to optimize these factors for desired acoustic outcomes. The results suggest implications for developing eco-friendly construction materials that balance environmental sustainability with performance requirements. This investigation contributes to the ongoing discourse on sustainable material utilization for acoustic purposes, reinforcing the potential for innovative and environmentally conscious building solutions.
Life Cycle Assessment of Municipal Solid Waste Management within Open Dumping and Landfilling Contexts: A Strategic Analysis and Planning Responses Applicable to Algeria
Authors: Cheniti Hamza , Kerboua Kaouther , Sekiou Omar , Aouissi Hani Amir , Benselhoub Aissa , Mansouri Rachida , Zeriri Ibtissem , Barbari Karima , Gilev Jadranka Blazevska , Bouslama Zihad
Published: August 2024

This paper examines Municipal Solid Waste (MSW) Management with a high organic matter content employing the Waste and Resource Assessment Tool for the Environment (WRATE) and the Ecoinvent database, by conducting a Life Cycle Impact Assessment (LCIA). Four scenarios, aligned with Algeria’s National Waste Management Strategy, are analyzed as case studies. LCA results identify the baseline scenario (current state) as the worst case. Significant improvements (84% reduction in climate change impact) are observed for scenario 2 to 4, which incorporate methane capture and energy recovery. Likewise, acidification potential was reduced, while eutrophication balanced positively for scenario 1 to 3 and negatively for scenario 4, promoting sustainable practices. This study proposes an optimal solution where the MSW service covers the charges and starts generating profit by shifting from a flat rate of 2000 Algerian Dinars (DZD) per household per year to 1% of household income. This change aims for at least 41% cost recovery from citizens at the national level, with minimum recovery targets for composting (50%), recycling (25%), and efficient landfilling (15%), alongside 20% energy recovery. To align with the Waste Hierarchy priorities, the Algerian government should gradually restrict organic waste landfilling (54% of MSW) and promote composting. Additionally, Algeria should establish regulations to encourage recycling programs, such as implementing Extended Producer Responsibility (EPR) regulations and setting recycling targets for various waste streams.
The Influence of Industrial Structure Adjustment on Carbon Emissions: An Analysis Based on the Threshold Effect of Green Innovation
Authors: Zhang Wen-Bo , Xie Zi-Han , Yu Chuan-Jiang
Published: August 2024

As climate change has become a common challenge to global sustainable development, China has also proposed carbon peaking and carbon neutrality goals to cope with it. To achieve the dual-carbon goal, it has released a series of specific measures, like controlling both the amount and intensity of carbon emissions. It has also put in place a “1+N” policy framework for carbon peak and carbon neutrality, among which the industrial structure adjustment and technological progress are the most direct and effective ways to achieve climate-friendly sustainable development. So, it is of great benefit to examine the industrial structure adjustment and corresponding carbon emissions effect for the formulation of reasonable industrial adjustment policies. Based on the provincial panel data of China from 2005 to 2019, this paper adopts the panel threshold model to investigate the influence of industrial structure adjustment on carbon emissions at different levels of green innovation. Its findings show that there exists a nonlinear relationship between the industrial structure adjustment and carbon emissions and the influence of the former on the latter has the threshold effect of green innovation. Specifically, when green innovation capacity falls below a certain threshold value, the industry structure adjustment has no significant correlation with carbon emissions; when the threshold value is exceeded, changing industrial structure can dramatically reduce carbon emissions. According to the findings, it is suggested that in the process of attaining the dual-carbon goal, the government should highly promote industrial restructuring and technological advancement, especially supporting low-carbon and green technological innovation and ensuring the continuity and consistency of green innovation policy to enhance the carbon emission reduction effect of industrial optimization.
Improved Multi-Objective Beluga Whale Optimization Algorithm for Truck Scheduling in Open-Pit Mines
Authors: Zhang Pengchao , Liu Xiang , Yi Zebang , He Qiuzhi
Published: August 2024

Big data and artificial intelligence have promoted mining innovation and sustainable development, and the transportation used in open-pit mining has increasingly incorporated unmanned driving, real-time information sharing, and intelligent algorithm applications. However, the traditional manual scheduling used for mining transportation often prioritizes output over efficiency and quality, resulting in high operational expenses, traffic jams, and long lines. In this study, a novel scheduling model with multi-objective optimization was created to overcome these problems. Production, demand, ore grade, and vehicle count were the model’s constraints. The optimization goals were to minimize the shipping cost, total waiting time, and ore grade deviation. An enhanced multi-objective beluga whale optimization (IMOBWO) algorithm was implemented in the model. The algorithm’s superior performance was demonstrated in ten test functions, as well as the IEEE 30-bus system. It was enhanced by optimizing the population initialization, improving the adaptive factor, and adding dynamic domain perturbation. The case analysis showed that, in comparison to the other three conventional multi-objective algorithms, IMOBWO reduced the shipping cost from 7.65 to 0.84%, the total waiting time from 35.7 to 7.54%, and the ore grade deviation from 14.8 to 3.73%. The implementation of this algorithm for truck scheduling in open-pit mines increased operational efficiency, decreased operating costs, and advanced intelligent mine construction and transportation systems. These factors play a significant role in the safety, profitability, and sustainability of open-pit mines.
Using Light as a Medium to Convey Its Dark Side—A Light Festival Case Study
Authors: Breukel Klaasz , Cieraad Ellen
Published: August 2024

The pervasive use of anthropogenic light at night has significantly increased the brightness of the night sky, which negatively affects human wellbeing, the ecology of plants and animals, night sky aesthetics, and astronomical observations. However, public awareness of light pollution remains limited. This study evaluates the effectiveness of an ‘eco-art installation’ in raising awareness about the impacts of anthropogenic light at night (ALAN). The installation, ‘Scope’, used light as a medium to convey the adverse effects of anthropogenic light at the Te Ramaroa festival in Nelson, New Zealand, which is held to celebrate light in the depths of winter. An online survey assessed the awareness of Nelson region residents, comparing responses between those who experienced the installation and those who did not, and assessing the self-reported knowledge increase after engagement with the installation. The findings indicated that eco-art installations can significantly enhance the public’s understanding of ALAN’s environmental and health impacts. The installation successfully increased self-reported specific knowledge about ALAN, with 92% of visitors reporting learning something new; however, overarching knowledge and levels of concern were largely similar between the groups. Emotional engagement was high, with 62% of viewers stating that the installation invoked an emotional response. While the study did not measure beha-vioural changes, 94% of festival participants found it at least ‘somewhat appropriate’ and 64% found it ‘very’ or ‘entirely appropriate’ to raise awareness of these issues at such events, suggesting a potential foundation for future action. This research underscores the promise of art–science collaborations in environmental education and public engagement.