bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Relationship Between Population Changes and Logistics Development: An Analysis Based on the Spatiotemporal Evolution Characteristics of Population and Logistics Coupling Coordination
Authors: Zhou Xuan , Hou Jinfeng , Song Qixia , Wang Yong
Published: December 2024

In recent years, China’s population growth rate is slowing, and birth rates are declining. The impact of changes in population size and structure on logistics development has raised important concerns. The coupling coordination between population and logistics has significant implications for the sustainable development of regional economies. This paper analyzes the relationship between population changes and logistics development from the perspective of the spatiotemporal evolution of their coupling coordination. First, based on population and logistics data from 31 provincial-level administrative regions in China from 2003 to 2022, a comprehensive evaluation indicator system is established to assess the population and logistics development levels across these provinces. Second, a coupling coordination degree model is constructed to explore the coupling coordination relationship between population changes and logistics development. Methods such as kernel density estimation and spatial autocorrelation analysis are employed to analyze the temporal evolution characteristics of the coupling coordination degree of the two subsystems. The results indicate that: (1) From 2003 to 2022, the population and logistics development levels in 31 provinces exhibited an upward trend. The growth rate of logistics development level scores exceeds that of population scores; (2) During the study period, the coupling coordination degree between population and logistics in most provinces shows a year-on-year increase, and notable spatial differences exhibit a decreasing trend; (3) There exists a significant positive spatial correlation in the coupling coordination degree between population and logistics across the 31 provinces, and local spatial autocorrelation is primarily characterized by ‘high–high’ and ‘low–low’ clustering distributions. Based on the above results, we propose policy recommendations to promote the coordinated development of population and logistics.
Impact of Tax Reductions on Public–Private Partnership Projects: Evidence from Comprehensive Implementation of China’s Business Tax to Value-Added Tax Reform
Authors: Zhao Jing , Wang Wei
Published: December 2024

This paper evaluates whether and how tax reduction policies affect public–private partnership (PPP) projects in China by using the complete conversion from business tax to value-added tax (BT-to-VAT) as a significant case. This reform enhances overall productivity and intensifies fiscal pressure on local governments through substantial tax reductions. Utilizing a sample of PPP projects from 2014 to 2019 and a difference-in-differences methodology, this paper treats the BT-to-VAT reform’s full rollout as a quasi-natural experiment to estimate its impact on PPPs. The results indicate that the full rollout of this reform results in a 20.93% increase in the number of PPP projects and an 11.43% rise in investment values, notably accelerating project execution. Mechanism tests reveal that this reform exacerbates fiscal disparities among cities while boosting total factor productivity (TFP) at the city level. Consequently, it increases local government demand for PPP initiatives and strengthens social capital’s capacity to engage in such partnerships—ultimately facilitating broader adoption and implementation of the PPP model. Furthermore, the effect is more pronounced for PPPs in the transportation and urban development sectors. Additionally, stronger impacts are observed in cities characterized by larger fiscal gaps, higher infrastructure demands, and greater prior PPP experience, as well as those located in central and western regions. This paper is one of the first to quantitatively assess the effect of fully implementing BT-to-VAT transition on PPPs, which is crucial for sustainable development concerning infrastructure and fiscal sustainability.
Can Big Data Comprehensive Pilot Zone Promote Low-Carbon Urban Development? Evidence from China
Authors: Liu Shenhua , Xiao Deheng
Published: December 2024

Big data, artificial intelligence, and other cutting-edge technologies are combined in a novel way by big data comprehensive pilot zones (BDCPZs) to provide cities with more comprehensive and precise evaluation and management services. However, it is still unclear how this platform will affect cities, especially with regard to carbon emissions. A sample of Chinese prefecture-level cities is used in this study. It examines the impact of BDCPZ buildings on carbon emissions in urban settings using a double-difference model. According to our data, even under rigorous testing, the use of BDCPZ substantially reduces carbon emissions. According to our analysis of the mechanism, the BDCPZ lowers carbon emissions by raising environmental awareness among the general population and strengthening urban green innovation capacities. The effect of BDCPZ in reducing urban carbon emissions is more pronounced in cities that are not dependent on natural resources, and are located in the eastern and western regions, and have greater levels of human capital, according to an examination of heterogeneity. Drawing from the aforementioned findings, this essay makes specific policy recommendations to support the development of low-carbon development in urban areas.
Innovative Pathways for Collaborative Governance in Technology-Driven Smart Communities
Authors: Tian Nailing , Wang Wei
Published: December 2024

This study constructs an analytical framework to assess the effectiveness of collaborative governance in smart communities, focusing on six key elements: collaborative subjects, funding sources, community participants’ literacy, community-specific systems, community culture, and supporting facilities. Using fuzzy set qualitative comparative analysis (QCA) on 20 typical cases of community governance, the study identifies that collaborative subjects and supporting facilities are necessary conditions for achieving effective community governance. Community culture and community participants’ literacy are recognized as sufficient conditions for effective collaborative governance involving multiple subjects in smart communities. The study also identifies several pathways to enhance the effectiveness of collaborative governance in smart communities, including the subject-–culture-embedded pathway, technology–resource-driven pathway, and system–talent-led pathway. These pathways highlight the integration of community-specific cultural elements and the leveraging of modern technologies to foster stakeholder engagement, enhance decision-making processes, and improve service delivery. The findings suggest that robust community culture and literacy, combined with advanced technological infrastructure and diverse funding sources, significantly contribute to the success of collaborative governance initiatives. By providing a comprehensive analysis of the interplay between these factors, the study offers valuable insights into the construction of smart communities and proposes strategies for enhancing the effectiveness of collaborative governance. This research contributes to the broader discourse on sustainable urban development and the knowledge economy, emphasizing the crucial role of innovation, technology, and community engagement in shaping the future of smart cities.
Simplified Multi-Hazard Assessment to Foster Resilience for Sustainable Energy Infrastructure on Santa Cruz Island, Galapagos
Authors: Haro-Baez Ana Gabriela , Posso Eduardo , Rojas Santiago , Arcos-Aviles Diego
Published: December 2024

This study analyzes the clean energy infrastructure resilience on Santa Cruz Island, located in the Galapagos archipelago, facing identified multi-natural hazard scenarios such as earthquakes, tsunamis, volcanic eruptions, and extreme weather events. Although Santa Cruz Island has a relatively modern energy infrastructure, its geographic location and lack of clear emergency management actions would significantly affect its performance. Risk assessment components, such as exposure and vulnerability, are also analyzed, highlighting the need for strategic interventions to ensure the continuity of energy supply and other essential services. Proved methodologies are used to propose action plans, including structural and non-structural solutions and simulations based on disaster scenarios. As a result, a series of strategies are revealed to strengthen the response and adaptation capacity of both critical infrastructure and the local community. These strategies hold the potential to ensure the island’s long-term energy security and sustainability, reducing its carbon footprint and instilling hope for a resilient future.
Comparative Analysis of Asphalt Pavement Condition Prediction Models
Authors: Radwan Mostafa M. , Zahran Elsaid M. M. , Dawoud Osama , Abunada Ziyad , Mousa Ahmad
Published: December 2024

There is a growing global interest in preserving transportation infrastructure. This necessitates routine evaluation and timely maintenance of road networks. The effectiveness of pavement management systems (PMSs) heavily relies on accurate pavement deterioration models. However, there are limited comparative studies on modeling approaches for rural roads in arid climatic conditions using the same datasets for training and testing. This study compares three approaches for developing a pavement condition index (PCI) model as a function of pavement age: classical regression, machine learning, and deep learning. The PCI is a pavement management index widely adopted by many road agencies. A dataset on pavement age and distress was collected over a twenty-year period to develop reliable predictive models. The results demonstrate that the regression model, machine learning model, and the deep learning model achieved a coefficient of determination (R2) of 0.973, 0.975, and 0.978, respectively. While these values are technically equal, the average bias for the deep learning model (1.14) was significantly lower than that of the other two models, signaling its superiority. Additionally, the trend predicted by the deep learning model showed more distinct phases of PCI deterioration with age than the machine learning model. The latter exhibited a wider range of PCI deterioration rates over time compared to the regression model. The deep learning model outperforms a recently developed regression model for a similar region. These findings highlight the potential of using deep learning to estimate pavement surface conditions accurately and its efficacy in capturing the PCI-age relationship.
UK Hydrogen Roadmap: Financial and Strategic Insights into Oil and Gas Industry’s Transition
Authors: Eltweri Ahmed , Al-karaki Wa’el , Zhai Yuan , Abdullah Khadijah , Faccia Alessio
Published: December 2024

Inspired by the announcement of the new Hydrogen Strategy for the UK in 2021, this study aimed to determine how the oil and gas industry responds and adapts to the changes. This paper analyses qualitative and quantitative data from the companies’ annual and energy reports. Four oil and gas companies involved in hydrogen projects in the UK were selected as case studies. The responses from the companies were collected using the content analysis research strategy in 2019–2021. A steady increase was observed based on the code frequency, reflecting the increasing discussions and actions the companies took regarding this hydrogen pathway. Although only one company appears to be at the forefront of this transition progress, with a score of almost 90% based on the strategy management analysis, other companies continue to demonstrate their commitment to supporting the national target.
Effects of Standardized Innovation Management Systems on Innovation Ambidexterity and Innovation Performance
Authors: Arslan Murat , Ince Huseyin , Imamoglu Salih Zeki
Published: December 2024

The goal of this research is to investigate the effects of standardized innovation management systems (SIMSs) on innovation ambidexterity and innovation performance and further on innovation capability. A survey was conducted in Türkiye with 178 manufacturing companies. The PLS-SEM method was used to test the hypotheses by using SmartPLS 4.1.0.2 software. The results show that SIMSs have a positive effect on innovation ambidexterity, innovation capability, and innovation performance. In addition, the results confirm a positive relationship between innovation capability and innovation performance, innovation ambidexterity, and innovation performance. According to research results, companies should follow ISO 56002 principles as a standardized innovation management system to achieve innovation ambidexterity, innovation capability, and innovation performance. This is the first known paper investigating the effect of SIMSs on innovation ambidexterity empirically. This research has provided a new link between the newly developing SIMSs and the innovation ambidexterity literature. Therefore, this study contributes to the development of the SIMSs from this perspective.
Integrating Remote Sensing Techniques and Allometric Models for Sustainable Carbon Sequestration Estimation in Prosopis cineraria-Druce Trees
Authors: Al-Jabri Khaled , Al-Mulla Yaseen , Al-Abri Ahmed , Al-Battashi Fathiya , Al-Sulaimani Mohammed , Tabook Ahmed , Al-Raba’Ni Salma , Sulaiman Hameed , Al-Salmi Nasser , Al-Shukaili Talal
Published: December 2024

This study emphasizes the role of Prosopis cineraria (Druce) in promoting sustainability through its contribution to carbon sequestration and climate change mitigation. The accurate quantification of the aboveground biomass (AGB) of Druce trees is essential for assessing their potential in reducing carbon emissions, yet remains a significant challenge. To address this, the study aimed to (1) estimate the AGB using destructive sampling; (2) analyze variability in existing allometric biomass equations; (3) evaluate remote sensing and machine learning techniques for estimating AGB and carbon sequestration; and (4) develop and validate new allometric equations based on field and remote sensing data. The Druce trees, with diameters at breast height ranging from 20.7 to 28.97 cm, exhibited an AGB of 208.3 kg per tree, which corresponds with a carbon sequestration stock of 97.89 kg C/tree. This translates to an annual carbon dioxide sequestration potential of 0.36 t C/tree. The newly developed allometric model (Model-2) was found to demonstrate superior accuracy, with performance metrics including a mean absolute percentage error (MAPE) of 2.6%, relative bias of 5.3%, R2 of 0.906, mean absolute error (MAE) of 0.151, and root mean square error (RMSE) of 0.189. These improvements highlight the significant role of remote sensing technologies in advancing sustainable carbon monitoring and offer a more precise tool for enhancing global carbon sequestration models. By integrating field-based measurements and advanced technologies, this study strengthens our ability to assess the carbon sequestration potential of trees, contributing to more sustainable management and climate resilience strategies.
Development of Collaboration Model for Data Space-Based Open Collaboration Platform in Continuous Process Industries
Authors: Shin Moonsoo
Published: December 2024

This study aims to propose a data space-based collaboration platform targeting continuous process industries such as continuous casting of steel and oil refining. The proposed collaboration platform serves as a basic environment in which supply chain participants share data through a data space, further supporting effective collaboration among the participating companies. Specifically, it implements a collaboration model among supply chain participants that reflects the characteristics of continuous process industries in which the supply chain is centered around the core suppliers. In fact, the key issue of continuous process industries is how to effectively distribute the manufacturing capabilities and production capacities of key suppliers with large-scale equipment to demand companies. In this context, this study (1) examines the results of existing research on data space-based collaboration platforms, (2) derives the differentiating factors and implementation strategies of the collaboration process among supply chain participants in continuous process industries, (3) presents the basic structure and operating framework of the collaboration platform, and (4) validates the proposed collaboration model through a simulation study based on a hypothetical scenario. The experimental results show that the proposed method is not only superior to a conventional distributed approach but also achieves similar performance to a centralized approach.
A Study on Carbon-Reduction Strategies for Rural Residential Buildings Based on Economic Benefits in the Gannan Tibetan Area, China
Authors: Yang Jingjing , Zhang Xilong
Published: December 2024

The building sector contributes approximately half of all carbon emissions. The heating stage accounts for the largest proportion of building carbon emissions. The focus on carbon-reduction strategies in rural areas could not be copied from urban buildings due to different heating modes limited by economic factors. The Gannan region in Gansu province was selected to carry out an on-site survey on heating conditions, including the heating modes, the energy used for heating, heating fees, residents’ satisfaction with heating, and the thermal environment of the typical building. The results showed that local rural residents burnt scattered coal for heating using primitive heating stoves with low efficiency, causing low air temperatures and high heating fees. The carbon emissions generated by heating reached 5743.28 kgCO2e·m−2. Several strategies for reducing carbon emissions were proposed, considering the economic benefits limited by rural economic development. A parameter of reduced carbon emissions per investment input was proposed to evaluate the carbon-reduction strategies. The results showed that biomass was the most economical way to reduce carbon emissions. Reduced carbon emissions per investment input reached 44.19 kgCO2e·CNY−1 with energy efficiency of 50%, followed by thermal insulation design of 32.31 kgCO2e·CNY−1, natural gas furnaces of 26.08 kgCO2e·CNY−1, and air-source heat pumps of 20.27 kgCO2e·CNY−1. In addition, carbon emissions generated by biomass were 12.4% and 24% of those caused by coal and natural gas supplying the same energy. Moreover, building insulation should be increased according to economic benefits. The optimum energy efficiency was 55% in Gannan. The results provided a reference for building low-carbon heating in rural areas, which could help achieve the low-carbon goal with low investments.
Fluctuation Induced Force in the Nagle–Kardar Model in Ensemble with Conserved Magnetization
Authors: Dantchev Daniel , Tonchev Nicholay S. , Rudnick Joseph
Published: December 2024

For finite systems the thermodynamic potentials are not equivalent. Thus, in any of them the fluctuations induce different forces: Casimir force (CF) in the grand canonical ensemble (GCE) and Helmholtz force (HF) in the canonical (CE) one with fixed magnetization. Here, we consider the HF within the Nagle–Kardar model with periodic boundary conditions. The model represents a one-dimensional Ising chain with both nearest nearest-neighbor short-ranged and long-ranged interactions present in it. The nearest-neighbor interactions of strength Js could be either ferromagnetic (Js>0), or antiferromagnetic (Js<0). The long-ranged equivalent-neighbor ferromagnetic interactions are of strength Jl/N>0. In the thermodynamic limit the model exhibits in the (Ks=βJs, Kl=βJl) plane a second-order phase transition line 2Kl=exp−2Ks, with Ks>−ln(3)/4, which ends at a tricritical point (Kl=3/2, Ks=−ln(3)/4). The obtained results demonstrate that the temperature behavior of the HF differs essentially from the one of the CF. Furthermore, we show that the CE and GCE are not equivalent, even in the thermodynamic limit. Finally, in the {Ks,Kl,m} phase space we determine the regions of stable states of the system.
Three-Dimensional Numerical Simulation of Controlled-Source Electromagnetic Method Based on Third-Type Boundary Condition
Authors: Guo Hongyu , Li Yong , Gong Shengping , Lin Lujun , Duan Zhuang , Jia Shihao
Published: December 2024

Controlled-source electromagnetic method (CSEM), as a significant geophysical exploration technique, plays a crucial role in imaging subsurface structures. To enhance the accuracy and efficiency of CSEM simulations, this paper introduces a 3D unstructured vector finite element numerical simulation method based on the third-type boundary condition. Vector finite elements are particularly suitable for handling discontinuities in the electric field normal. They automatically satisfy tangential field continuity and zero-divergence requirements, providing a solid foundation for forward modeling in the CSEM. The adoption of the third-type boundary condition aims to reduce computational scale while ensuring higher simulation accuracy. Using this method, we conducted detailed numerical simulations on various models, including layered models, single-anomaly models, composite-anomaly models, and layered-anomaly models. The experimental results demonstrate that the algorithm accurately reproduces the electromagnetic responses of various geological models. It also exhibits superior computational accuracy under low-frequency conditions, outperforming traditional simulation methods. In summary, the 3D unstructured vector finite element numerical simulation method proposed in this study offers an efficient and reliable solution for CSEM, which is of great significance for advancing CSEM technology, especially in inversion techniques and data interpretation. Future work will focus on further optimizing algorithm performance and exploring its application potential in complex geological environments.
A Study of the Symmetry of the Tricomplex Repunit Sequence with Repunit Sequence
Authors: Costa Eudes A. , Catarino Paula M. M. C. , Santos Douglas C.
Published: December 2024

In this paper, we introduce a new family of sequences related to Horadam-type sequences. Specifically, we consider the repunit sequence {rn}n≥0, which is defined by the initial terms r0=0 and r1=1 and follows the Horadam recurrence relation given by rn=11rn−1−10rn−2 for n≥2. Many studies have explored generalizations of integer sequences in different directions: some by preserving the initial terms, some by preserving the recurrence relation, and some by considering different numerical sets beyond positive integers. In this article, we take the third approach. Specifically, we study these sequences in the context of the tricomplex ring T. We define the Tricomplex Repunit sequence {trn}n≥0, with initial terms tr0=(0,1,11) and tr1=(1,11,111), and governed by the recurrence relation trn=11trn−1−10trn−2, for n≥2. This sequence is also a Horadam-type sequence but defined in the tricomplex ring T. In this paper, we establish the properties of the Tricomplex Repunit sequence and establish several new as well as well-known identities associated with it, including Binet’s formula, Tagiuri–Vajda’s identity, d’Ocagne’s identity, and Catalan’s identity. We also derive the generating function for this sequence. Furthermore, we study various additional properties of these generalized sequences and establish results concerning the summation of terms related to the Tricomplex Repunit sequence, and one of our main goals is to determine analogous or symmetrical properties for the Tricomplex Repunit sequence to those we know for the ordinary repunit sequence.
Inertia Support Capability Evaluation for Wind Turbine Generators Based on Symmetrical Operation
Authors: Chen Zaiyu , Li Yang , Zhou Qian
Published: December 2024

With the increasing integration of new energy into the grid, the level of system inertia has been significantly reduced, posing a severe challenge to frequency stability. Consequently, there is an urgent need for wind turbine generators (WTGs) to actively provide inertia support through virtual inertia control. Assessing the inertia support capability of WTGs reasonably and setting appropriate controller parameters based on this assessment is a topic worthy of discussion. As WTGs’ characteristics are mostly ignored in the evaluation of inertia support capability for WTGs, an evaluation method based on symmetrical operation is proposed. The proposed method considers the impact of real inertia and aerodynamic characteristics, thereby helping to determine reasonable virtual inertia coefficients and de-loading reserve capacity for WTGs. With the proposed method, it can be determined that large WTGs can provide inertia support capabilities close to those of synchronous generators to the grid without exceeding a 0.1% reduction in reserve capacity during de-loading operation.
Symmetric Functions and Rings of Multinumbers Associated with Finite Groups
Authors: Chopiuk Yurii , Zagorodnyuk Andriy
Published: December 2024

In this paper, we introduce ωn-symmetric polynomials associated with the finite group ωn, which consists of roots of unity, and groups of permutations acting on the Cartesian product of Banach spaces ℓ1. These polynomials extend the classical notions of symmetric and supersymmetric polynomials on ℓ1. We explore algebraic bases in the algebra of ωn-symmetric polynomials and derive corresponding generating functions. Building on this foundation, we construct rings of multisets (multinumbers), defined as equivalence classes on the underlying space under the action of ωn-symmetric polynomials, and investigate their fundamental properties. Furthermore, we examine the ring of integer multinumbers associated with the group ωn, proving that it forms an integral domain when n is prime or n=4.
Enhancing Early Breast Cancer Detection with Infrared Thermography: A Comparative Evaluation of Deep Learning and Machine Learning Models
Authors: Jalloul Reem , Krishnappa Chethan Hasigala , Agughasi Victor Ikechukwu , Alkhatib Ramez
Published: December 2024

Breast cancer remains one of the most prevalent and deadly cancers affecting women worldwide. Early detection is crucial, particularly for younger women, as traditional screening methods like mammography often struggle with accuracy in cases of dense breast tissue. Infrared thermography offers a non-invasive imaging alternative that enhances early detection by capturing subtle thermal variations indicative of breast abnormalities. This study investigates and compares the performance of various deep learning and machine learning models in analyzing thermographic data to classify breast tissue as healthy, benign, or malignant. To maximize detection accuracy, data preprocessing, feature extraction, and dimensionality reduction were implemented to isolate distinguishing characteristics across tissue types. Leveraging advanced feature extraction and visualization techniques inspired by geospatial data methodologies, we evaluated several deep learning architectures and classical classifiers using the DRM-IR and Breast Thermography Mendeley thermal datasets. Among the tested models, the ResNet152 architecture combined with a Support Vector Machine (SVM) classifier delivered the highest performance, achieving 97.62% accuracy, 95.79% precision, 98.53% recall, 94.52% specificity, an F1 score of 97.16%, an area under the curve (AUC) of 99%, a latency of 0.06 s, and CPU utilization of 88.66%. These findings underscore the potential of integrating infrared thermography with advanced deep learning and machine learning approaches to significantly improve the accuracy and efficiency of breast cancer detection, supporting its role as a valuable tool for early diagnosis.
Children’s Perceived Ease of Use of a Projected Augmented Reality Game Designed for Balance and Coordination Training
Authors: Liu Yishi , Achterbosch Leigh , Meredith Grant , Dekker Evan , Lim Suryani , Lavender Andrew P.
Published: December 2024

Developing balance and coordination skills is essential for children, especially those aged 4–8, but limited Health and Physical Education (HPE) programs in schools hinder effective training. Game-based learning and Augmented Reality (AR) technologies offer promising ways to enhance these skills by providing immersive HPE experiences. An AR exercise-game prototype was developed to train children’s balance and coordination, with 19 children aged 4 to 9 testing the prototype. Post-activity surveys revealed high engagement and interactivity ratings. The difficultly of the current prototype was found to be appropriately challenging for 4- to 6-year-olds. Feedback emphasized a preference for interactive, challenging elements, suggesting improvements in difficulty customization, visuals, and technical stability. Competitive play between multiple children testing the prototype encouraged repeated attempts, but also highlighted the need for improved tracking solutions and lab setup. Overall, the innovative design shows educational potential but requires further large-scale testing on a refined version to assess its effectiveness in balance and coordination training.
Firefighting with Conductive Aerosol-Assisted Vortex Rings
Authors: LaRocco John , Tahmina Qudsia , Essel Stanley , Simonis John
Published: December 2024

Conventional firefighting tools and methods can strain water sources, require toxic foams, or rely on pre-installed countermeasures. A low-cost, non-toxic, and portable option was previously overlooked in portable devices: electrically assisted “ionic wind” fire suppression. Conductive aerosols, carried by vortex rings, can potentially extend the length of an electric arc and suppress fires. After the simulation, two prototype vortex ring launchers were compared, one using compressed air and another using an elastic diaphragm. The efficiency of each test case was assessed with a purpose-built automated image analysis system. The compressed air vortex launcher had a significantly higher efficiency than the elastic diaphragm prototype, with a p-value of 0.0006. Regardless of the prototype or the use of conductive aerosols, the device had an effective range of up to 1.98 m. The highest reliability of 90 ± 4.1% was achieved at 1.52 m from the launcher. The observations with compressed air launcher results saw no significant difference regarding the use of the conductive aerosol. Further investigation of the concept requires a systematic examination of other types of fires, electronic optimization, permutations of chemicals and concentrations, other types of vortex generation, and human factors. The computer vision system could also be used to further detect and target active fires. Beyond firefighting, the device can be adapted to applications ranging from manufacturing to aerospace. Regardless of the use of conductive aerosols, handheld vortex ring generators are a versatile, potential firefighting tool.
Behavior and Mechanisms of Antimony Precipitation from Wastewater by Sulfate-Reducing Bacteria Desulfovibrio desulfuricans
Authors: Zhuang Fan , Xiang Xiaowu , Hu Jin , Xiong Jing , Zhang Teng , Zhou Lei , Jiang Guoping , Zhang Min , Liu Zhenghua , Yin Huaqun , Xia Ling , Mahmoud Ibrahim Ahmed Ibrahim , Meng Delong
Published: December 2024

The development of the non-ferrous metal industry is generating increasingly large quantities of wastewater containing heavy metals (e.g., Sb). The precipitation of heavy metals by microorganisms involves complex mechanisms that require further investigation to optimize bioremediation technologies. In this study, we employed a sulfate-reducing bacteria (SRB) strain Desulfovibrio desulfuricans CSU_dl to treat the antimony (Sb)-containing wastewater; the behavior of Sb and mechanisms underlying precipitation were investigated by characterizing the precipitates. The results showed that the abiotic factors constraining SRB bacterial growth greatly affect Sb forms and precipitation. For instance, Sb precipitation maximumly occurred at pH 6 and 7, or C:N ratio of 10:1 and 40:3 for Sb(III) and Sb(V), respectively, resulting in a maximum Sb removal rate of 94%. Interestingly, we found that substantial antimonate and antimonite were adsorbed on the SRB cell surface, indicating that cell surface is a critical reaction site of Sb transformation and precipitation. Sb was adsorbed to the cell surface by C-C and C=O groups, and was further precipitated by forming Sb2S3 and Sb2S5 or was coprecipitated with the P-containing group. Partial Sb(V) reduction was also observed on the SRB cell surface. These results provided a deep insight into the Sb bio-transformation and were an advancement with respect to understanding bioremediation of Sb-contaminated wastewater.
Diversity of Mycotoxins in Stored Paddy Rice: Contamination Patterns in the Mekong Delta, Vietnam
Authors: Phan Lien Thi Kim , Nguyen Thuy Thi Ngoc , Tran Thien Thi Thanh , De Saeger Sarah
Published: December 2024

Rice (Oryza sativa L.) is the most important food in Vietnam. However, rice is often lost in post-harvest due to fungal growth and mycotoxins contamination. This study aimed to evaluate mycotoxin contamination in stored paddy rice collected in 2018, 2019, and 2022 in six provinces in Mekong Delta, Vietnam, using LC-MS/MS. The results revealed that 47% of the samples were contaminated with 12 types of mycotoxins. The prevalence of these mycotoxins was 30% (ZEN), 10% (FUS/MON), 6% (BEA/AFB2), 2–4% (AFG1, AFB1, AFG2), 2% (FB1), and 1% (OTA/AME/ENB). Among the provinces, stored paddy rice from Kien Giang had the highest contamination, followed by Ben Tre, Long An, An Giang, Dong Thap, and Can Tho. Remarkably, paddy rice collected in 2022 was usually contaminated with emerging mycotoxins with a higher incidence of co-occurrence ranging from 2–6% of the samples. Additionally, five stored paddy rice samples were contaminated with levels of AFB1, OTA, and ZEN exceeding Vietnamese regulatory limits for unprocessed rice. Our findings provide valuable insights into mycotoxin contamination across different years and growing regions in the Mekong Delta, Vietnam. This study could give essential information to stakeholders, including policy-makers or food safety authorities, etc., to inform strategies to mitigate these toxins in the near future and underscores the importance of monitoring rice production.
Spatial Analysis and Socio-Environmental Determinants of Canine Visceral Leishmaniasis in an Urban Area in Northeastern Brazil
Authors: de Freitas Natan Diego Alves , Freire Lucas José Macedo , Silva Suely Ruth , do Nascimento Nilton Guedes , Cordeiro-Estrela Pedro
Published: December 2024

The urbanization process has led to significant changes in the landscape, shifting the epidemiological profile of the visceral leishmaniasis (VL) in Brazil. Dogs are considered the main urban reservoir of VL, whose infections precede cases in humans. In order to understand the socio-environmental determinants associated with canine visceral leishmaniasis (CVL), we conducted a spatial analysis of CVL cases in northeastern Brazil from 2013 to 2015, georeferencing 3288 domiciled dogs. We used linear mixed models to understand the ecoepidemiological determinants of CVL spatial relative risk (CVL SRR). Our findings indicate heterogeneity in CVL distribution, with 1 km diameter clusters potentially connected within an estimated 4.9 km diameter by the Ripley-K statistic. In our best-fit model, the CVL SRR was positively correlated with the proportion of households with literate heads, with trees, and with open sewage, but negatively correlated with vegetation phenology and mean income of the census sector. Here, we discuss the potential maintenance source of urban CVL clusters on a One Health framework. These findings highlight the complex interplay of socioeconomic and environmental factors in shaping the spatial distribution of CVL.
Posterior Positivity Distribution Analysis of Subclinical Bluetongue in the Eastern and North-Eastern States of India: A Wakeup Call for Outbreak Preparedness
Authors: Joardar Siddhartha Narayan , Sanyal Aritra , Abd El Wahed Ahmed , Ray Saibal
Published: December 2024

Bluetongue (BT) is considered endemic in the southern states of India, with sporadic incidences reported from the northern, western and central parts of India. However, the eastern and north-eastern states of India have not experienced active disease so far. In the recent past, an extensive sero-epidemiological investigation was carried out in the eastern and north-eastern Indian states. With the aim of getting updated and refined estimates of positivity rates, the sero-surveillance data were analyzed using the Markov chain Monte Carlo (MCMC) method to calculate the positivity rates of various species across different states and agro-climatic zones. The posterior positivity distribution helped in accurately estimating the seroprevalence of bluetongue virus (BTV) among different species and regions. The MCMC method was applied for the first time in a BTV seroprevalence analysis that enhanced our understanding of infection dynamics, guided targeted interventions and supported better decision-making in bluetongue disease control, prevention and disease preparedness. This exercise is quite pertinent in the context of the recent upsurge of newer BTV strains, e.g., BTV-3 and BTV-8, in the western world. In short, as a powerful computational tool, MCMC could be used for accurate seroprevalence estimation, species-specific insights, regional analysis, enhanced decision-making and epidemiological insights for bluetongue.
Impact of Age and Sex on Viral Load in Hepatitis C Virus Infection
Authors: Magri Andrea , Manfredi Giulia Francesca , Smirne Carlo , Pigni Silvia , Burlone Michela Emma , Bellan Mattia , Vercellino Nicole , Minisini Rosalba , Pirisi Mario
Published: December 2024

The determinants of hepatitis C virus (HCV) viral load remain incompletely understood and may differ in females, who are relatively protected from the consequences of HCV infection during their reproductive years. We aimed to evaluate how age affects the relationship between sex and viral load. n = 922 patients (males n = 497, median age 62 years), all naïve to direct antiviral agents, were studied. Females were older (median age 68 vs. 57, p < 0.001) and had a higher prevalence of genotype 2 (33% vs. 20%, p < 0.001) than males; there was no difference between sexes regarding the METAVIR stage. The median HCV RNA concentration was 1.017 × 106 IU/mL (interquartile range, 0.286–2.400). Among males, the METAVIR stage was the strongest independent predictor of a high viral load (defined as the highest two quartiles), with advanced stages inversely associated with viral load (p = 0.008). In females, age was the only independent predictor, with women aged ≥55 years exhibiting higher loads (p = 0.009). These findings are consistent with data showing that estrogens exert an antiviral effect in in vitro models of HCV. Their declining levels after the menopause may explain the “catch-up” phase of HCV-related liver disease, observed in older women.
Geographic Distribution of Vaccinia Virus, Diagnosis and Demographic Aspects of Affected Populations, Minas Gerais, Brazil, 2000–2023
Authors: e Silva Pedro H. B. , de Oliveira Maycon D. , de Almeida Iara M. , Domingos Iago J. S. , Stoffella-Dutra Ana G. , Barbosa Costa Galileu , de Oliveira Jaqueline S. , Iani Felipe C. M. , de Castro Márcio R. , Abrahão Jonatas S. , Kroon Erna G. , Trindade Giliane de S.
Published: December 2024

Since its first report in Brazil in 1999, outbreaks of exanthematous diseases caused by vaccinia virus (VACV) have been a recurring concern, particularly impacting rural regions. Minas Gerais (MG) State, Brazil, has emerged as the epicenter of bovine vaccinia (BV) outbreaks. This study presents a comprehensive overview of VACV circulation in MG State over the past two decades, examining the occurrence and distribution of poxvirus cases and outbreaks and the demographic characteristics of affected populations. Analysis of secondary databases from 2000 to 2023 revealed VACV circulation in at least 149 municipalities, particularly expanding in dairy regions. The study underscores BV as an occupational disease, predominantly affecting rural men involved in dairy cattle activities. Laboratory findings indicate high levels of anti-OPXV antibodies in most individuals, with some showing acute infections confirmed by qPCR testing. This analysis informs public health policies, emphasizing the need for enhanced surveillance of and preventive measures for dairy farming communities.
Reflections on COVID-19: A Literature Review of SARS-CoV-2 Testing
Authors: Lau Chin Shern , Oh Helen M. L. , Aw Tar Choon
Published: December 2024

Although the Coronavirus disease 2019 (COVID-19) pandemic has ended, there are still many important lessons we can learn, as the pandemic profoundly affected every area of laboratory practice. During the pandemic, extensive changes to laboratory staffing had to be implemented, as many healthcare institutions required regular screening of all healthcare staff. Several studies examined the effectiveness of different screening regimens and concluded that repeated testing, even with lower sensitivity tests, could rival the performance of gold-standard RT-PCR testing in the detection of new cases. Many assay evaluations were performed both in the earlier and later periods of the pandemic. They included both nucleocapsid/spike antibodies and automated antigen assays. Early in the pandemic, it was generally agreed that the initial nucleocapsid antibody assays had poor sensitivity when used before 14 days of disease onset, with total or IgG antibodies being preferred over the use of IgM. Spike antibody assays gradually replaced nucleocapsid antibody assays, as most people were vaccinated. Spike antibodies tracked the rise in antibodies after vaccination with mRNA vaccines and became invaluable in the assessment of vaccine response. Studies demonstrated robust antibody secretion with each vaccine dose and could last for several months post-vaccination. When antigen testing was introduced, they became effective tools to identify affected patients when used serially or in an orthogonal fashion with RT-PCR testing. Despite the numerous findings during the pandemic period, research in COVID-19 has slowed. To this day it is difficult to identify a true neutralizing antibody test for the virus. An appropriate antibody level that would confer protective immunity against the plethora of new variants remains elusive. We hope that a summary of events during the pandemic could provide important insights to consider in planning for the next viral pandemic.
Knowledge and Attitudes Regarding Human Papillomavirus Vaccination Among Future Healthcare Workers in Serbia
Authors: Maletin Nemanja , Denda Nikola , Ljubičić Ana , Velicki Radmila , Patić Aleksandra , Golušin Zoran , Dugandžija Tihomir , Petrović Vladimir , Ristić Mioljub , Vuković Vladimir
Published: December 2024

Background/Objectives: Adequate knowledge and correct attitudes about the HPV vaccine influence awareness of the importance of preventing HPV-related diseases, which is particularly important for future healthcare professionals. We aim to examine the share of correct answers and the prevalence of different attitudes about the HPV vaccine among active regular students of the Faculty of Medicine in Novi Sad. Methods: A cross-sectional study was conducted from 1 to 30 November 2023 using a structured survey questionnaire. Results: A total of 1760 students were included, of which 78% were female, with an average age of 21 years. Students who participated in prior HPV education) demonstrated significantly higher knowledge (81.92% vs. 65.60%, p < 0.001) and were more likely to recommend the vaccine to patients (89.91% vs. 82.99%, p < 0.001). Almost all vaccinated students (99.41%) would recommend the vaccine, compared to 82.91% of unvaccinated students (p < 0.001). Students who actively sought HPV information also showed a higher likelihood of recommending the vaccine (93.05% vs. 83.02%, p < 0.001). Moreover, those with sufficient self-assessed knowledge were more inclined to recommend the vaccine (89.88%) than those with insufficient knowledge (81.66%, p < 0.001). The analysis demonstrated that an increase in the number of correct answers in the knowledge evaluation corresponds to higher odds of recommending the HPV vaccine to patients (OR = 1.23, 95% CI 1.17–1.28). Positive attitudes prevailed, with 68.89% supporting more education on HPV vaccination. Conclusions: Students who previously attended education on HPV infection/vaccination and those who would recommend the vaccine have significantly higher levels of knowledge. The study highlights the importance of HPV-related education in shaping future healthcare professionals’ attitudes and knowledge.
Risk and Pollutant Protective Concentration Levels of Drilling Waste Used to Pave Oil and Gas Field Well Sites
Authors: Yang Jinzhong , Yang Yufei , Tian Lu , Zhou Jinliang , Wang Yiou
Published: December 2024

Paving oil and gas field well sites of drilling waste allow us to reuse solid waste. However, to keep the risk within acceptable limits, some questions need to be answered: what is the dilution effect that soil and groundwater have on the transport of pollutants? What is the minimum concentration of pollutants leached from drill wastes? In this study, we focus on the paving of well sites using drilling wastes, and we analyze the pollutant migration pattern in the soil vadose zone and groundwater mixing zone after rainwater leaching. The drilling waste pollutant protective concentration level (PCL) and the corresponding dilution attenuation factor (DAF) were then proposed. In addition, the PCL’s accessibility, uncertainty, and environmental significance were further analyzed. It was found that the pollutant dilution factor (DF) of the groundwater mixed zone was strongly influenced by the thickness of the mixed zone, the groundwater Darcy rate, the length of the contaminant source, and the permeability, and each contributed approximately 25%. The soil vadose zone attenuation factor (AF) was primarily influenced by the soil vadose zone (i.e., groundwater depth) thickness that contributed approximately 53%. The contaminant DAF values of the well site drilling waste paving (e.g., the soil vadose zone thickness ranged from 5 to 30 m) ranged from 12 to 84. Additionally, the PCL values of the contaminants ranged from 12 to 84 times of the acceptable concentration (e.g., the Class III permissible limits of the Groundwater Quality Standards GB/T 14848-2017) at the groundwater compliance point. The expression for the exponential relationship between the DAF or PLC and the depth of the soil vadose zone was also provided in this study. The study results provide a reference for the actual process of the use of drilling wastes to pave well sites and for solid waste treatment or soil remediation decision-making and the associated risk assessment procedures.