bluuebunny/crossref_metadata_2025 huggingface dataset:
The Geological Investigation of the Lunar Reiner Gamma Magnetic Anomaly Region
Authors: Hu Junhao , Liu Jingwen , Liu Jianzhong , Deng Jiayin , Zhang Sheng , Lei Danhong , Zeng Xuejin , Huang Weidong
Published: November 2024

Reiner Gamma is a potential target for low-orbiting spacecraft or even surface-landed missions in the near future. Unfortunately, thus far, no comprehensive low-altitude (below 20 km) or surface measurements of the magnetic field, magnetic source and plasma environment have been made post-Apollo to complement and complete our understanding of the solar wind interaction with lunar magnetic anomalies and swirl formation. Acquiring the detailed geological knowledge of the Reiner Gamma region is significant for the above scientific targets. In this study, the following research work in the lunar Reiner Gamma magnetic anomaly region was carried out for the regional geological investigation: (1) topographic and geomorphologic analysis; (2) element, mineral, and sequence analysis; and (3) a 1:10,000 regional geological map analysis. Our work helps define measurement requirements for possible future low-orbiting or surface-landed missions to the Reiner Gamma area or similarly magnetized regions of the lunar surface.
A Planar Feature-Preserving Texture Defragmentation Method for 3D Urban Building Models
Authors: Liu Beining , Liu Wenxuan , Lei Zhen , Zhang Fan , Huang Xianfeng , Awwad Tarek M.
Published: November 2024

Oblique photogrammetry-based 3D modeling is widely used for large-scale urban reconstruction. However, textures generated with photogrammetric techniques often exhibit scattered and irregular characteristics, which lead to significant challenges with texture seams and UV map discontinuities, increasing storage requirements and affecting rendering quality. In this paper, we propose a planar feature-preserving texture defragmentation method designed specifically for urban building models. Our approach leverages the multi-planar topology of buildings to optimize texture merging and reduce fragmentation. The proposed approach is composed of three main stages: the extraction of planar features from texture fragments; the employment of these planar elements as guiding constraints for merging adjacent texture fragments within a two-dimensional texture space; and an enhanced texture-packing algorithm designed for more regular texture charts to systematically generate refined texture atlas. Experiments on various urban building models demonstrate that our method significantly improves texture continuity and storage efficiency compared to traditional approaches, with both quantitative and qualitative validation.
Evaluation of Fengyun-4B Satellite Temperature Profile Products Using Radiosonde Observations and ERA5 Reanalysis over Eastern Tibetan Plateau
Authors: Wang Yuhao , Wu Xiaofei , Zhang Haoxin , Ren Hong-Li , Yang Kaiqing
Published: November 2024

The latest-generation geostationary meteorological satellite, Fengyun-4B (FY-4B), equipped with the Geostationary Interferometric Infrared Sounder (GIIRS), offers high-spatiotemporal-resolution three-dimensional temperature structures. Its deployment serves as a critical complement to atmospheric temperature profile (ATP) observation in the Tibetan Plateau (TP). Based on radiosonde observation (RAOB) and the fifth-generation ECMWF global climate atmospheric reanalysis (ERA5), this study validates the availability and representativeness of FY-4B/GIIRS ATP products in the eastern TP region. Due to the issue of satellite zenith, this study focuses solely on examining the eastern TP region. Under a clear sky, FY-4B/GIIRS ATP exhibits good consistency with RAOB compared to cloudy conditions, with an average root mean square error (RMSE) of 2.57 K. FY-4B/GIIRS tends to underestimate temperatures in the lower layers while overestimating temperatures in the upper layers. The bias varies across seasons. Except for summer, the horizontal and vertical bias distribution patterns are similar, though there are slight differences in values. Despite the presence of bias, FY-4B/GIIRS ATP maintains a good consistency with observations and reanalysis data, indicating commendable product quality. These results demonstrate that it can play a vital role in augmenting the ATP observation network limited by sparse radiosonde stations in the eastern TP, offering crucial data support for numerical weather prediction, weather monitoring, and related meteorological research in this region.
Vegetation Greening Promoted the Precipitation Recycling Process in Xinjiang
Authors: Li Xuewei , Hao Xingming , Zhang Sen , Hou Guanyu , Zhang Jingjing , Fan Xue , Zhao Zhuoyi
Published: November 2024

Under the combined influences of climate and vegetation change, land–atmosphere interactions have enhanced, and precipitation recycling is an important part of this. Previous studies of the precipitation recycling process have focused on calculating the precipitation recycling rate (PRR) and analyzing the influencing factors. However, the climate-driven and vegetation-induced precipitation recycling process variations were not quantified. This study has systematically examined the precipitation recycling process in a typical arid region using the Eltahir and Bras model, random forest algorithm, and partial least-squares structural equation modeling. During 1982–2018, the leaf area index (LAI) and evapotranspiration (ET) rate both increased significantly, with growth rates of 0.06 m2m−2/decade and 13.99 mm/decade, respectively. At the same time, the average PRR in Xinjiang was 13.92% and experienced significant growth at a rate of 1.28%/decade. The climate-driven and vegetation-induced PRR variations were quantified, which contributed 79.12% and 20.88%, respectively. In addition, the positive effects of both of these on PRR variations through ET did not increase with the increase in ET, but rather decreased sharply and then stabilized. This study can provide favorable theoretical support for mitigating the contradiction in water use and balancing economic development and ecological security by quantifying the regulation of precipitation by vegetation.
CFRNet: Cross-Attention-Based Fusion and Refinement Network for Enhanced RGB-T Salient Object Detection
Authors: Deng Biao , Liu Di , Cao Yang , Liu Hong , Yan Zhiguo , Chen Hu
Published: November 2024

Existing deep learning-based RGB-T salient object detection methods often struggle with effectively fusing RGB and thermal features. Therefore, obtaining high-quality features and fully integrating these two modalities are central research focuses. We developed an illumination prior-based coefficient predictor (MICP) to determine optimal interaction weights. We then designed a saliency-guided encoder (SG Encoder) to extract multi-scale thermal features incorporating saliency information. The SG Encoder guides the extraction of thermal features by leveraging their correlation with RGB features, particularly those with strong semantic relationships to salient object detection tasks. Finally, we employed a Cross-attention-based Fusion and Refinement Module (CrossFRM) to refine the fused features. The robust thermal features help refine the spatial focus of the fused features, aligning them more closely with salient objects. Experimental results demonstrate that our proposed approach can more accurately locate salient objects, significantly improving performance compared to 11 state-of-the-art methods.
DRBD-YOLOv8: A Lightweight and Efficient Anti-UAV Detection Model
Authors: Jiang Panpan , Yang Xiaohua , Wan Yaping , Zeng Tiejun , Nie Mingxing , Liu Zhenghai
Published: November 2024

Interest in anti-UAV detection systems has increased due to growing concerns about the security and privacy issues associated with unmanned aerial vehicles (UAVs). Achieving real-time detection with high accuracy, while accommodating the limited resources of edge-computing devices poses a significant challenge for anti-UAV detection. Existing deep learning-based models for anti-UAV detection often cannot balance accuracy, processing speed, model size, and computational efficiency. To address these limitations, a lightweight and efficient anti-UAV detection model, DRBD-YOLOv8, is proposed in this paper. The model integrates several innovations, including the application of a Re-parameterization Cross-Stage Efficient Layered Attention Network (RCELAN) and a Bidirectional Feature Pyramid Network (BiFPN), to enhance feature processing capabilities while maintaining a lightweight design. Furthermore, DN-ShapeIoU, a novel loss function, has been established to enhance detection accuracy, and depthwise separable convolutions have been included to decrease computational complexity. The experimental results showed that the proposed model outperformed YOLOV8n in terms of mAP50, mAP95, precision, and FPS while reducing GFLOPs and parameter count. The DRBD-YOLOv8 model is almost half the size of the YOLOv8n model, measuring 3.25 M. Its small size, fast speed, and high accuracy combine to provide a lightweight, accurate device that is excellent for real-time anti-UAV detection on edge-computing devices.
Application of Bivariate Reproducing Kernel-Based Best Interpolation Method in Electrical Tomography
Authors: Tan Yongguang , Wang Jingqi , Yu Junqi , Wu Boqi , Shen Jinchao , Guo Xiangchen
Published: November 2024

Electrical Tomography (ET) technology is widely used in multiphase flow detection due to its advantages of low cost, visualization, fast response, non-radiation, and non-invasiveness. However, ill-posed solutions lead to low image reconstruction resolution, which limits its practical engineering applications. Although existing interpolation approximation algorithms can alleviate the effects of the ill-posed solutions to some extent, the imaging results remain suboptimal due to the limited approximation capability of these methods. This paper proposes a Bivariate Reproducing Kernel-Based Best Interpolation (BRKBI) method, which offers smaller approximation errors and clearer image reconstruction quality compared to existing methods. The effectiveness of the BRKBI method is validated through theoretical analysis and experimental comparisons.
ICT Innovation to Promote Sustainable Development Goals: Implementation of Smart Water Pipeline Monitoring System Based on Narrowband Internet of Things
Authors: Cheng Yuh-Ming , Horng Mong-Fong , Chung Chih-Chao
Published: November 2024

This study proposes a low-cost, automatic, wide-area real-time water pipeline monitoring model based on Narrowband Internet of Things (NB-IoT) technology, aiming to solve the challenges faced in the context of global water pipeline management. This model focuses on real-time monitoring of pipeline operations to reduce water waste and improve management efficiency, directly contributing to the achievement of the sustainable development goals (SDGs). Water resource management faces several significant global challenges, including water scarcity, inefficient resource utilization, and infrastructure degradation. Traditional water pipeline monitoring systems are often manual, time-consuming, and unable to detect leaks or failures in real time, leading to significant water loss and financial costs. In response to these issues, NB-IoT technology offers a promising solution with its advantages of low power consumption, long-range communication, and cost-effectiveness. The development of an NB-IoT-based smart water pipeline monitoring system is therefore essential for enhancing the efficiency and sustainability of water resource management. Through enabling real-time monitoring and data collection, this system can address critical issues in global water management, reducing waste and supporting the sustainable development goals (SDGs). This model utilizes Low-Power Wide-Area Network (LPWAN) technology, combined with an LTE mobile network and ARM Cortex-M4 microcontroller, to achieve long-distance multi-sensor data collection and monitoring. The research results show that NB-IoT technology can effectively improve water resource management efficiency, reduce water waste, and is of great significance for the digital transformation of infrastructure and the development of smart cities. This technical solution not only supports “Goal 6: Clean Drinking Water and Sanitation” in the United Nations’ sustainable development goals (SDGs) but also promotes the realization of low-cost teaching aids related to engineering education-related information and communication technologies (ICTs). This study demonstrates the key role of ICTs in promoting sustainable development and provides a concrete practical example for smart water resource management.
External Transport Costs and Implications for Sustainable Transport Policy
Authors: Koba Rafał , Lipka Patryk , Kalinowski Marcin , Czaplewski Krzysztof , Witkowska Joanna , Weintrit Adam
Published: November 2024

This study investigated the external costs of different transport modes and their implications for sustainable transport policy. Utilising the INCONE60 Cargo Flow Model, we quantified and compared road and maritime transport’s environmental and health impacts within European logistics networks. Our findings revealed that road transport incurred external costs up to four times higher than sea transport due to greater emissions and health-related impacts. By implementing strategic modal shifts and optimising routes, we demonstrated the potential to reduce external costs by up to 80%. These results underscore the importance of integrating external costs into decision-making processes, aligning with global sustainability goals, and providing actionable insights for policymakers to promote sustainable practices in global trade.
Cognitive Recognition of Space and Social Connections of Traditional Villages in Shanxi Province: A Case Study of Ding, Shijiagou, and Yanjing Villages
Authors: Sun Cong , Lee Inhee
Published: November 2024

The traditional clan-based structure of village society is gradually disintegrating due to rural population outflow and excessive tourism development. The construction of a diversified development model oriented toward the needs of local villagers is key to sustainable development and the preservation of cultural heritage. In this study, a case analysis of the Ding, Shijiagou, and Yanjing Villages in Shanxi Province was conducted. The research approach of “cognitive recognition–spatial structure–social connections” was used to integrate cognitive maps and space syntax with social network analysis to quantitatively analyze the cognitive elements in these villages, with the establishment of a collective cognitive map, global integration value maps, and villagers’ intention element cognitive networks based on functional types. The spatial cognition patterns and social network structures of these villages were explored and analyzed in relation to the complex interactions between villages from the perspectives of spatial cognitive preference, spatial accessibility, and social interaction to compensate for the limitations of using a single analytical approach. Differences in village cognition patterns were found—the efficient use of different types of space is influenced by spatial cognitive preferences; the degree of spatial integration affects the distribution of functional spaces, with high-integration areas tending to overlap with high-cognition spaces and featuring strong accessibility and connectivity; the density and stability of social networks significantly influence spatial cognition and the interaction patterns in villages; high-density networks enhance the frequency of interactions between villagers and the effectiveness of space utilization; and differentiation in spatial cognition among different groups may reduce village space integration, thereby influencing the overall social functions and cultural heritage of the village. Therefore, it is crucial to enhance the connectivity and influence of key nodes, optimize spatial layouts and social network structures, and introduce modern elements while preserving traditional culture, an approach that can promote social interaction and spatial vitality in the villages. This study provides a scientific basis and serves as a reference for the construction of sustainable development models for villages.
Dynamic Control Method for CAV-Shared Lanes at Intersections in Mixed Traffic Flow
Authors: Hu Xiyuan , Li Mengying , Jiang Xiancai
Published: November 2024

The existing signal control methods for mixed traffic related to connected automated vehicles (CAVs) and connected human-driven vehicles (CHVs) at intersections fail to tap the traffic potential of CAV-dedicated lanes. Accordingly, a dynamic allocation method of CAV-shared lanes is proposed, and the method of traffic flow scheduling and CAV trajectory optimization for multilane intersections with CAV-shared lanes is constructed to improve the traffic performance. The simulation results show that the optimization strategy proposed in this study can reduce the average delay at the intersection to varying degrees compared with the control strategy, using (a) the dynamic CAV-dedicated lane allocation method and (b) the shared-phase dedicated-lane method. Although the stops of CAVs will increase, the time utilization rate of most approach lanes is considerably improved, particularly CAV-shared lanes that can effectively improve the intersection performance. Further analysis shows that the number of CAV-shared lanes is closely dependent on the CAV penetration rate. The method proposed in this study is suitable for multilane intersections with a high CAV penetration rate.
Optimizing Multi-Channel Green Supply Chain Dynamics with Renewable Energy Integration and Emissions Reduction
Authors: Safaei Mehdi , Al Dawsari Saleh , Yahya Khalid
Published: November 2024

In response to the global imperative of mitigating greenhouse gas emissions (GHGs) and the shifting landscape of business models toward multi-channel structures, this study delves into the intricacies of a green supply chain. Operating through both online and traditional channels with uncertain demands, the producer’s distribution strategy prompts an exploration of supply chain dynamics. Utilizing an integer programming model, this study calculates optimal prices, optimizes total profit, and minimizes transportation costs to curtail carbon dioxide emissions, depending on the transportation mode. Additionally, this study incorporates renewable energy sources into the production and transportation processes to further minimize carbon dioxide emissions. The integration of renewable energy not only supports environmental goals, but also contributes to the overall profitability of the supply chain by reducing energy costs. Employing a theoretical technique for linearization, the model, resolved through the Jimenez and TH methods, demonstrates efficacy in reconciling economic and environmental goals. The Jimenez method enables the transformation of fuzzy parameters into deterministic equivalents, allowing for a more reliable optimization during uncertainty, while the TH method provides an interactive fuzzy multi-objective approach, aligning the model’s dual objectives for both economic and environmental goals. Notably, when transportation costs to both markets are equal, the model prioritizes devices with a lower environmental impact, showcasing adaptability. Furthermore, the proposed solution empowers decision makers to influence pricing and enhance the entire supply chain’s profitability. In conclusion, this research offers nuanced insights, strategically aligning economic viability with environmental sustainability in the discourse on green supply chains.
Exploring the Factors Influencing the Safety of Young Novice Drivers: A Qualitative Approach Based on Grounded Theory
Authors: Mohammadi Amin , Aghabayk Kayvan , Zabihzadeh Abbas
Published: November 2024

Risky driving behaviors of young novice drivers and related crashes pose not only a threat to road safety but also a significant challenge to sustainable development. The high rate of traffic crashes involving young drivers leads to substantial losses in human capital, productivity, and labor, which are irreparable and place a strain on societal resources. Addressing the safety issues of this vital group in society is crucial for promoting the long-term social and economic sustainability of communities. Despite this, studies have lacked a comprehensive explanation of the safety issues surrounding young novice drivers. Therefore, the aim of this study is to identify factors affecting the safety of young novice drivers in Iran, a developing country with a significant young population. The study uses a qualitative approach that is built on grounded theory to reveal the model. The statistical population of the study is specialists, experts, and researchers in the field of road safety who are spread across Iran. The data collection phase was realized through the conduction of semi-structured interviews with 36 of them, and the analysis process was continued until complete theoretical saturation was achieved. The research data were then analyzed using the coding method based on the systematic design of Strauss and Corbin’s grounded theory. Finally, the categories were organized into seventeen subcategories within the six dimensions of the paradigm model: main category (three subcategories), causal factors (three subcategories), contextual factors (three subcategories), strategies (two subcategories), environmental conditions (three subcategories), and consequences (three subcategories). These findings not only provide a deep understanding of the safety issues faced by young novice drivers but also offer strategies that can contribute to improving road safety, thereby fostering social sustainability. Enhancing driver safety is crucial for reducing the economic and social costs of road crashes, which aligns with the broader goals of sustainable development by preserving human capital and societal well-being.
Human-Centric Telework and Sustainable Well-Being: Evidence from Peru’s Public Sector
Authors: Ríos Villacorta Mauro Adriel , Ramos Farroñán Emma Verónica , Arbulú Ballesteros Marco Agustín , Otiniano León Mabel Ysabel , Bravo Jaico Jessie Leila , Suysuy Chambergo Ericka Julissa , Reyes-Pérez Moisés David , Ganoza-Ubillús Lucila María , Alarcón García Roger Ernesto
Published: November 2024

This study examines the relationships among telework, job satisfaction, and quality of work life among employees in the Peruvian public sector, specifically at the National University Pedro Ruiz Gallo in Lambayeque. Using a quantitative approach with an explanatory scope and a nonexperimental cross-sectional design, data were collected from 194 employees through a structured questionnaire. Structural equation modeling (SEM) was employed to analyze the relationships between variables. The results reveal a positive impact of telework on both job satisfaction (β = 0.389, p < 0.001) and quality of work life (β = 0.323, p < 0.001). Job satisfaction was found to mediate the relationship between telework and quality of work life (β = 0.425, p < 0.001). Additionally, years of work experience negatively moderated the relationship between telework and job satisfaction (β = −0.114, p = 0.017), whereas gender had a positive moderating effect (β = 0.275, p = 0.016). These findings contribute to the understanding of telework dynamics in the public sector and offer valuable insights for tailoring telework policies to maximize employee well-being and organizational effectiveness.
Selecting a Time-Series Model to Predict Drinking Water Extraction in a Semi-Arid Region in Chihuahua, Mexico
Authors: Legarreta-González Martín Alfredo , Meza-Herrera César A. , Rodríguez-Martínez Rafael , Loya-González Darithsa , Chávez-Tiznado Carlos Servando , Contreras-Villarreal Viridiana , Véliz-Deras Francisco Gerardo
Published: November 2024

As the effects of global climate change intensify, it is increasingly important to implement more effective water management practices, particularly in arid and semi-arid regions such as Meoqui, Chihuahua, situated in the arid northern center of Mexico. The objective of this study was to identify the optimal time-series model for analyzing the pattern of water extraction volumes and predicting a one-year forecast. It was hypothesized that the volume of water extracted over time could be explained by a statistical time-series model, with the objective of predicting future trends. To achieve this objective, three time-series models were evaluated. To assess the pattern of groundwater extraction, three time-series models were employed: the seasonal autoregressive integrated moving average (SARIMA), Prophet, and Prophet with extreme gradient boosting (XGBoost). The mean extraction volume for the entire period was 50,935 ± 47,540 m3, with a total of 67,233,578 m3 extracted from all wells. The greatest volume of water extracted has historically been from urban wells, with an average extraction of 55,720 ± 48,865 m3 and a total of 63,520,284 m3. The mean extraction volume for raw water wells was determined to be 20,629 ± 19,767 m3, with a total extraction volume of 3,713,294 m3. The SARIMA(1,1,1)(1,0,0)12 model was identified as the optimal time-series model for general extraction, while a “white noise” model, an ARIMA(0,1,0) for raw water, and an SARIMA(2,1,1)(2,0,0)12 model were identified as optimal for urban wells. These findings serve to reinforce the efficacy of the SARIMA model in forecasting and provide a basis for water resource managers in the region to develop policies that promote sustainable water management.
Confidence Intervals for the Coefficient of Variation in Delta Inverse Gaussian Distributions
Authors: Khumpasee Wasurat , Niwitpong Sa-Aat , Niwitpong Suparat
Published: November 2024

The inverse Gaussian distribution is characterized by its asymmetry and right-skewed shape, indicating a longer tail on the right side. This distribution represents extreme values in one direction, such as waiting times, stochastic processes, and accident counts. Moreover, depending on if the accident counts data can occur or not and may have zero value, the Delta Inverse Gaussian (Delta-IG) distribution is more suitable. The confidence interval (CI) for the coefficient of variation (CV) of the Delta-IG distribution in accident counts is essential for risk assessment, resource allocation, and the creation of transportation safety policies. Our objective is to establish CIs of CV for the Delta-IG population using various methods. We considered seven CI construction methods, namely Generalized Confidence Interval (GCI), Adjusted Generalized Confidence Interval (AGCI), Parametric Bootstrap Percentile Confidence Interval (PBPCI), Fiducial Confidence Interval (FCI), Fiducial Highest Posterior Density Confidence Interval (F-HPDCI), Bayesian Credible Interval (BCI), and Bayesian Highest Posterior Density Credible Interval (B-HPDCI). We utilized Monte Carlo simulations to assess the proposed CI technique for average widths (AWs) and coverage probability (CP). Our findings revealed that F-HPDCI and AGCI exhibited the most effective coverage probability and average widths. We applied these methods to generate CIs of CV for accident counts in India.
A Numerical Analysis on Gradient Coils in Nuclear Magnetic Resonance for Imaging
Authors: Barbaraci Gabriele
Published: November 2024

A mathematical discussion is introduced to describe the gradient coils characterizing the NMRI system. A comparison between the physical laws characterizing the magnetic field of winding coils and a magnetohydrodynamic analysis is built up. The requirements for gradient coil performance are described and analyzed. Design methods are characterized by mathematical manipulation to reduce the nonlinearities that make the magnetic field not suitable for image extraction. A mathematical study has been shown to represent the Golay’s pairs as generators of linear magnetic fields. The entire study shows how the choice of the magnetic field pattern inside the NMRI can occur by choosing the proper geometrical parameters that are a function of the nonlinearities involved in the gradient coils design.
Characterization of a Diaporthe toxica Strain: Growth, Spore Formation, Phomopsin-A, and Alkaloids Production on Lupins
Authors: Buccioni Francesco , Rossi Chiara , Serio Annalisa , Fanti Federico , Paparella Antonello
Published: November 2024

The growing interest in vegetable proteins, namely those derived from lupins, has raised concerns over potential safety risks associated with these food products. Lupin serves as the main host for the mycotoxin-producing fungus called Diaporthe toxica. This species, which is associated with animal diseases, has been scarcely characterized. Recently, phomopsin-A (PHO-A), the main mycotoxin produced by D. toxica, was found to be harmful to humans. Therefore, this study aimed at characterizing D. toxica growth and spore formation both in vitro and on lupin samples. In addition, the production of PHO-A and alkaloids was investigated on lupin beans by using three different inoculation methods. Particularly, growth and spore production were evaluated on different media, while PHO-A and alkaloid production were determined by means of µSPE extraction followed by UHPLC-MS/MS and HPLC-MS/MS, respectively. The results have demonstrated differences in growth on different media, with potato and oat-flakes-based media being the best options. Conversely, D. toxica was not able to produce spores on agar media, but only on lupin beans. Moreover, a thorough analysis of PHO-A production revealed an increase over time, reaching values up to 1082.17 ppm after 21 days on artificially rehydrated samples. On the other side, the analysis of alkaloids revealed impressive results, as this species produced great quantities of the quinolizidine alkaloids (QA) that are normally present in lupin seeds such as lupanine, sparteine, multiflorine, and hydroxylupanine. On balance, considering these results, different metabolic pathways were demonstrated in D. toxica, which are not adequately described in the existing literature. These data are of paramount importance to deepen the knowledge about a fungal species that is important to ensure the safety of lupin and lupin-based products.
Emerging Insights into Memory Natural Killer Cells and Clinical Applications
Authors: Kokiçi Jonida , Preechanukul Anucha , Arellano-Ballestero Helena , Gorou Frances , Peppa Dimitra
Published: November 2024

Natural killer (NK) cells are innate lymphocytes that can rapidly mount a response to their targets by employing diverse mechanisms. Due to their functional attributes, NK cells have been implicated in anti-viral and anti-tumour immune responses. Although traditionally known to mount non-specific, rapid immune responses, in recent years, the notion of memory NK cells with adaptive features has gained more recognition. Memory NK cells emerge in response to different stimuli, such as viral antigens and specific cytokine combinations. They form distinct populations, accompanied by transcriptional, epigenetic and metabolic reprogramming, resulting in unique phenotypic and functional attributes. Several clinical trials are testing the efficacy of memory NK cells due to their enhanced functionality, bioenergetic profile and persistence in vivo. The therapeutic potential of NK cells is being harnessed in viral infections, with wider applications in the cancer field. In this review, we summarise the current state of research on the generation of memory NK cells, along with their clinical applications in viral infection and cancer.
Numerical Simulation and Validation of Constructed Wetlands for Effluent Treatment in Eastern China: An Evaluation of MIKE21 in Enhancing Water Purification Efficiency
Authors: Xiong Xing , Yang Shanrui , Zhang Junxiang , Chen Jiafan , Zhang Xinyu , Zhang Qinghai
Published: November 2024

Constructed wetlands for effluent treatment (CW-ET) play a vital role in the degradation of pollutants, the purification of water, and the improvement of freshwater ecosystems. However, conventional designs often lack a methodical approach for quantifying the efficacy of these wetlands. In this context, numerical simulations aid in optimizing vegetation selection and placement in these systems, thereby enhancing their overall efficiency. In this study, the MIKE21 hydrodynamic (HD) module was coupled with the advection–dispersion (AD) module to simulate the Yingtai CW-ET in Hai’an. Accordingly, key parameters involved in effective water purification were calibrated and the system’s performance in treating effluent from wastewater treatment facilities was evaluated. The findings demonstrated significant removal efficiencies for chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and ammonia (NH3-N), with average rates of 51.14%, 43.14%, 63.82%, and 54.38%, respectively. In addition, the simulations exhibited high accuracy, with hydrodynamic predictions deviating by under 5% and water quality approximations by under 15%. The treated water quality met the requirements for Class IV surface water standards. Utilizing numerical simulations offers valuable insights for the design and performance evaluation of future constructed wetlands.
Evaluation of Three High-Resolution Satellite and Meteorological Reanalysis Precipitation Datasets over the Yellow River Basin in China
Authors: Xie Meixia , Di Zhenhua , Liu Jianguo , Zhang Wenjuan , Sun Huiying , Tian Xinling , Meng Hao , Wang Xurui
Published: November 2024

Recently, Integrated Multi-satellite Retrievals for the Global Precipitation Measurement (IMERG) mission and European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) precipitation datasets have been widely used in remote sensing and atmospheric studies, respectively, because of their high accuracy. A dataset of 268 site-gauge precipitation measurements over the Yellow River Basin in China was used in this study to comprehensively evaluate the performance of three high-resolution precipitation products, each with a spatial resolution of 0.1°, consisting of two satellite-derived datasets, IMERG and multisource weighted-ensemble precipitation (MSWEP), and one ERA5-derived dataset, ERA5-Land. The results revealed that the spatial distribution of IMERG annual precipitation closely resembled that of the observed rainfall and generally exhibited a downward trend from southeast to northwest. Among the three products, IMERG had the best performance at the annual scale, whereas ERA5-Land had the worst performance due to significant overestimation. Specifically, IMERG demonstrated the highest correlation coefficient (CC) above 0.8 and the lowest BIAS and root mean square error (RMSE), with values in most regions of 24.79 mm/a and less than 100 mm/a, respectively, whereas ERA5-Land presented the highest RMSE exceeding 500 mm/a, BIAS of 1265.7 mm/a, and the lowest CC below 0.2 in most regions. At the season scale, IMERG also exhibited the best performance across all four seasons, with a maximum of 17.99 mm/a in summer and a minimum of 0.55 mm/a in winter. Following IMERG, the MSWEP data closely aligned with the observations over the entire area in summer, southern China in spring and winter, and middle China in autumn. In addition, IMERG presented the highest Kling–Gupta efficiency coefficient (KGE) of 0.823 at the annual scale and the highest KGE (>0.77) across all four seasons among the three products compared with ERA5-Land and MSWEP, which had KEG values of −2.718 and −0.403, respectively. Notably, ERA5-Land exhibited a significant positive deviation from the observations at both the annual and seasonal scales, whereas the other products presented relatively smaller biases.
A Novel Modular Suspended Underwater Dredging Robot with a Suction and Jet-of-Pump Combination
Authors: Deng Xiangsheng , Luo Jianbin , Pan Cuilin
Published: November 2024

This article introduces a novel modular suspended underwater dredging robot used for the biochemical reaction tanks of underground water treatment plants. The presented underwater robot can be used to perform dredging operations without touching underwater bottom facilities. The approach achieved a suction and jet-of-pump combination. This requires the underwater robot system to maintain a stable operation attitude in turbulent water flow which is generated by the pump. The study involves the overall design of underwater robots coordinated with the dredging module and details the development of a ground control platform and underwater sensing sonar system. Depending on the location of the dredging, the robot has two operation modes: suspended mode and bottom sitting mode. The experimental results validate the feasibility and effectiveness of the underwater dredging robot. This research can achieve dredging in biochemical reaction tanks without interrupting operations and facilitates the development of intelligent operations in the water treatment industry.
Research on the Spatial Distribution Characteristics and Inhalation Health Risk Assessment of Bacterial Aerosols in Spraying Environments
Authors: Gao Qian , Dai Miao , Lei Guangyu , Hou Xiandong , Zhang Dawei , Du Weiwei
Published: November 2024

As a key water source for urban landscape entertainment and miscellaneous municipal uses, the reuse safety of reclaimed water has attracted much attention. Given the deficiencies in the current research on bacterial aerosol-related risks, this study conducted systematic research on the spatial distribution law of bacterial aerosols in spraying environments and the exposure characteristics of various populations through simulated spraying experiments and population surveys, and on this basis, quantitatively evaluated the inhalation risk of bacterial aerosols. Results indicated that the concentration of bacterial aerosols in the spatial position within the water source and their residence time at different positions were related to the bacterial concentration of the sprayed water source. Specifically, the concentration of bacterial aerosols and the atomization factor decreased with the increase in the horizontal distance from the nozzle, and reached a saturated state at the eighth minute after the nozzle started spraying. At a height of 1.5 m, and at distances of 1 m, 2 m, 3 m, and 4 m from the nozzle, the atomization coefficients (mL water/m3 air) were 30.25, 8.52, 0.81, and 1.33 × 10−3, respectively. However, the particle size distribution of bacterial aerosols in space was independent of the bacterial concentration in the water source. The peak particle size of bacterial aerosols was between 2.1 and 4.7 µm, and its concentration accounts for more than 50%. Based on the above results, the exposure characteristics of the instantaneous contact time of the crowd exposed to the spray water of park lawn irrigation and the spray water of sprinklers on roads were obtained through simulated shooting experiments. Results showed that under the same environment, when people were exposed to the spray of park lawn irrigation and the spray of sprinklers on roads, the health risk of a single inhalation was relatively high. The single health risk of the crowd manifested as follows: adult males > adult females > children; however, none of them exceed the acceptable risk level of 10−3. The research findings of this paper can provide a scientific basis for the safe reuse of reclaimed water
Assessment of Water Service Levels and User Satisfaction for Domestic Water Use in Emina-Boadi-Kumasi to Achieve the Sustainable Development of Urban Water Supply Systems in Ghana
Authors: Mantey Emmanuel Padmore , Kanwar Rameshwar S. , Appiah-Effah Eugene
Published: November 2024

Access to reliable water supply is critical for sustainable development and public health, yet many peri-urban and rural communities in the developing world face challenges such as poor maintenance, faulty infrastructure, and inadequate governance of water services, hindering the UN’s Sustainable Development Goals (SDG). In Emina-Boadi, a small town in Kumasi, Ghana, residents increasingly rely on boreholes due to substandard service from the Ghana Water Company Limited (GWCL). This shift highlights concerns about water reliability, quality, and affordability, impacting public health and hindering progress toward SDG 6. This case study assesses water service levels using key performance indicators (KPIs) such as quantity, quality, affordability, accessibility, and reliability, focusing on sources like boreholes, hand pumps, piped water, hand-dug wells, rainwater, and surface waters. The study aims to delineate the roles of different water providers, understand community dynamics, and evaluate contributions to rural development and SDG 6 through stakeholder interviews and questionnaires. By leveraging the WASHCost framework, which aims to improve planning methods and the provision of water and sanitation services by addressing the lack of cost information in rural and peri-urban areas, and the Joint Monitoring Programme (JMP) framework, which monitors progress toward global targets related to water, sanitation, and hygiene, the study categorizes indicators and draws connections among them. The findings reveal a significant preference for borehole services, with 87% usage and an 83% reliability rate compared to 13% for GWCL. Daily water consumption averages 60.75 L per person, with on-premises access improving water collection efficiency to 7 min. Dissatisfaction with GWCL services highlights the need for improved delivery aligned with community needs and SDG targets. Adopting sustainable management practices, enhancing infrastructure, and improving governance are crucial for ensuring safe and affordable water access for all residents of Emina-Boadi and similar communities.
Increased Nutrient Levels Induce Different Allocation Strategies Between Canopy-Forming and Rosette-Like Submerged Macrophytes
Authors: Zhi Yongwei , Wang Wei , Li Wei , Cao Yu , Xia Manli
Published: November 2024

Submerged macrophytes play an important role in maintaining the structure and function of shallow lakes. Under eutrophication, the community of submerged macrophytes shows a shift of growth forms from rosette-like to canopy-forming macrophytes and a further decline due to the increasing shading from epiphyton and phytoplankton. However, at the early phase of eutrophication, the population of submerged macrophytes may increase due to increased nutrient availability, and the responses of submerged macrophytes to eutrophication are expected to be growth-form dependent. To explore the direct effects of nutrient enrichment on the submerged macrophytes of both growth forms, we constructed a mesocosm study with rosette-like macrophytes (Vallisneria denseserrulata and V. spinulosa) and canopy-forming macrophytes (Potamogeton lucens and P. wrightii) under two nutrient levels but maintained low phytoplankton and epiphyton biomass. Nutrient enrichment had a positive effect on the plant size for both macrophyte growth forms under low algal shading. Based on the 21 plant traits determined, the same growth form responded similarly to the increase in nutrient availability with few exceptions. Interestingly, increased nutrient levels induced different allocation strategies between canopy-forming (especially for ‘magnopotamid’) and rosette-like submerged macrophytes. The increased nutrients promoted leaf growth in rosette-like macrophytes and ramet production in canopy-forming macrophytes. These results provide a case study on the direct effects of increased nutrient levels on submerged macrophytes during the early phase of eutrophication in shallow lakes.
Socioeconomic Implications of Upstream–Downstream Relationships and Watershed Communities: A New York City Watershed Case Study
Authors: Lamsal Anusha , Germain René H. , Bevilacqua Eddie
Published: November 2024

The historic New York City (NYC) Watershed Memorandum of Agreement signed in 1997, which established the Watershed Protection and Partnership Program (WPPP), aimed to safeguard water quality for downstream NYC communities and enhance community vitality within the upstream watershed. Up to now, the focus has been on maintaining water quality, with less attention on the socioeconomic and demographic well-being of the upstream communities. This study bridges this gap by examining the socioeconomic and demographic trends within the upstream watershed communities. We collected census data from the U.S. Census Bureau and American Community Survey (ACS) from 1990, 2000, 2010, and 2020. The data were collected primarily for the Catskill-Delaware Watershed region, as well as the five immediate watershed counties, New York State, the U.S., and two rural counties similar in population density to the Watershed to serve as comparison areas. This study analyzed demographic factors and economic, and community characteristics to identify trends and shifts over time. Our findings reveal the demographic shift towards an older retiree population, decreasing labor force, higher unemployment rates, higher disparities in income distribution, and longer commute times in the Watershed compared to our comparison areas. The Watershed also experiences higher home vacancies than the comparison areas, suggesting a shift towards seasonal or second-home use of properties. While this study offers insights into socioeconomic and demographic shifts in watershed communities, its reliance on census data may limit the precision in establishing causal links between watershed protection measures and these shifts. Incorporating qualitative analysis in future research will deepen our understanding of these relationships.
Pollution and Ecological Risk Assessment of Potentially Toxic Elements in Sediments Along the Fluvial-to-Marine Transition Zone of the Don River
Authors: Konstantinova Elizaveta , Minkina Tatiana , Nevidomskaya Dina , Bauer Tatiana , Zamulina Inna , Latsynnik Elizaveta , Dudnikova Tamara , Yadav Rajendra Kumar , Burachevskaya Marina , Mandzhieva Saglara
Published: November 2024

The quality of sediments in the mixing zone of river freshwater and marine saline water as an important geochemical barrier for potentially toxic elements (PTEs) remains poorly understood. This study aims to analyze the current pollution with PTEs and associated ecological risks in sediments of the Don River delta and the surrounding area of the Taganrog Bay of the Sea of Azov (Russia). The PTE content was determined in fifty-four collected samples using the WDXRF and assessed using geochemical and ecotoxicological indicators. The source of Cr, Mn, Ni and Pb is mainly river runoff, and Cu, Zn and Cd are from a variety of anthropogenic sources. As shown by the assessment of the geoaccumulation index (Igeo), single pollution index (PI) and contamination factor (CF), these elements are the priority pollutants. According to these estimates, high and very high contamination of sediments in the estuarine zone of the Don River with Cd and Pb was detected in 72–94% and 2–57% of samples, respectively. However, environmental risks are determined almost exclusively by the level of Cd. Total contamination as assessed by the Nemerow pollution index (NPI), modified degree of contamination (mCd) and metal pollution index (MPI) is of concern in 83–98% of the samples studied. The most heavily polluted sediments are in the vicinity of residential areas of the Taganrog Bay. Despite the lower average pollution levels of deltaic sediments, freshwater biota are exposed to higher potential toxic risks of adverse effects by PTE, particularly from Ni and Pb. Thus, the complex hydrological regime and uneven anthropogenic impact predetermine the geochemical state of the sediments of the estuarine zone of the Don River.