bluuebunny/crossref_metadata_2025 huggingface dataset:
Observations of Saharan Dust Intrusions over Potenza, Southern Italy, During 13 Years of Lidar Measurements: Seasonal Variability of Optical Properties and Radiative Impact
Authors: De Rosa Benedetto , Mytilinaios Michail , Amodeo Aldo , Colangelo Canio , D’Amico Giuseppe , Dema Claudio , Gandolfi Ilaria , Giunta Aldo , Gumà-Claramunt Pilar , Laurita Teresa , Lolli Simone , Papagiannopoulos Nikolaos , Papanikolaou Christina-Anna , Rosoldi Marco , Summa Donato , Mona Lucia
Published: January 2025

We present a multi-year study of Saharan dust intrusions on a mountainous site located in the central Mediterranean Basin regarding their aerosol optical and geometrical properties. The observations were carried out at the Consiglio Nazionale delle Ricerche-Istituto di Metodologie per l’Analisi Ambientale (CNR-IMAA) located in Potenza (40,360N, 15,440E), Italy, from March 2010 to October 2022, using ACTRIS (Aerosol Clouds and Trace Gases Research InfraStructure). A total of 101 night-time lidar measurements of dust intrusions were identified. The following properties were calculated for the periods December, January, February (DJF), March, April, May (MAM), June, July, August (JJA) and September, October, November (SON): aerosol layer center of mass altitude, particle lidar ratio at 355 and 532 nm, particle depolarization ratio at 532 nm and backscattering Ångström exponent at 532–1064 nm. Both geometrical and optical aerosol properties vary considerably with the seasons. During SON and DJF, air masses transporting dust travel at lower altitudes, and become contaminated with local continental particles. In MAM and JJA, dust is also likely to travel at higher altitudes and rarely mix with other aerosol types. As a result, aerosols are larger in size and irregular in shape during the warm months. The ratio of the lidar ratios at 355 and 532 nm is 1.11 ± 0.15 in DJF, 1.12 ± 0.07 in SON, 0.94 ± 0.12 in MAM, and 0.92 ± 0.08 in JJA. The seasonal radiative effect estimated using the Fu–Liou–Gu (FLG) radiative transfer model indicates the most significant impact during the JJA period. A negative dust radiative effect is observed both at the surface (SRF) and at the top of the atmosphere (TOA) in all the seasons, and this could be related to a minimal contribution from black carbon. Specifically, the SRF radiative effect estimation is −14.48 ± 1.32 W/m2 in DJF, −18.00 ± 0.89 W/m2 in MAM, −22.08 ± 1.36 W/m2 in JJA, and −13.47 ± 1.12 W/m2 in SON. Instead, radiative effect estimation at the TOA is −22.23 ± 2.06 W/m2 in DJF, −38.23 ± 2.16 W/m2 in MAM, −51.36 ± 3.53 W/m2 in JJA, and −22.57 ± 2.11 W/m2 in SON. The results highlight how the radiative effects of the particles depend on the complex relationship between the dust load, their altitude in the troposphere, and their optical properties. Accordingly, the knowledge of aerosols optical property profiles is of primary importance to understand the radiative impact of dust.
Comparison of Three Temperature and Emissivity Separation Algorithms for Graybodies with Low Spectral Contrast: A Case Study on Water Bodies
Authors: Xiao Min , Zhou Shugui , Cheng Jie
Published: January 2025

The temperature and emissivity separation (TES) algorithm is currently adopted to retrieve the land surface temperature (LST) and emissivity (LSE) from Moderate Resolution Imaging Spectroradiometer (MODIS) images (i.e., the MOD/MYD21 product). Unfortunately, the TES algorithm often yields anomalous LSE spectra for graybodies with low spectral contrast. The MODIS TES algorithm does not effectively address this issue. To overcome this limitation, refined TES algorithms, including the optimized smoothing for temperature emissivity separation (OSTES) and the temperature and emissivity separation with nonlinear constraint (TESNC), have been proposed. Although these algorithms offer theoretical improvements, their performance has not been systematically validated using real MODIS data. This study evaluates the performance of three TES algorithms (MODIS TES, OSTES, and TESNC) in retrieving LST&E from MODIS data over six lakes on the Qinghai–Tibet Plateau, which serve as representative examples of low-spectral-contrast surfaces. Three years (2018–2020) of MODIS data from six lakes on the Qinghai–Tibet Plateau were collected to retrieve LST&E using three TES algorithms. Using the quality-controlled MODIS LST product (MOD11) as a benchmark, the TESNC algorithm achieved the highest accuracy, with bias and RMSE values of 0.18 K and 0.22 K, respectively, compared with the bias and RMSE values of 0.51 K and 0.53 K for the MODIS TES algorithm and 0.58 K and 0.60 K for the OSTES algorithm, respectively. In terms of LSE, the TESNC algorithm achieved an RMSE within 0.005 for all bands, demonstrating superior accuracy over the other algorithms. Overall, the TESNC algorithm significantly improved the accuracy of LST&E retrieval from MODIS for graybodies with low spectral contrast. This study is the first to systematically evaluate refined TES algorithms using real MODIS data over graybodies. The findings provide valuable insights for improving the MODIS LST&E product and advancing the retrieval of LST&E for low-spectral-contrast surfaces.
A Pixel-Based Machine Learning Atmospheric Correction for PeruSAT-1 Imagery
Authors: Saldarriaga Luis , Tan Yumin , Sabater Neus , Delegido Jesus
Published: January 2025

Atmospheric correction is essential in remote sensing, as it reduces the effects of light absorption and scattering by suspended particles and gases, enabling accurate surface reflectance computation from the observed Top-of-Atmosphere (TOA) reflectance. Each satellite sensor requires a customized atmospheric correction processor due to its unique system characteristics. Currently, PeruSAT-1, the first Peruvian remote sensing satellite, does not include this capability in its image processing pipeline, which poses challenges for its effectiveness in defense, security, and natural disaster management applications. This research investigated pixel-based machine learning methods for atmospheric correction of PeruSAT-1, using Sentinel-2 harmonized Bottom-of-Atmosphere (BOA) surface reflectance images as a benchmark, alongside additional atmospheric, terrain, and acquisition parameters. A robust dataset was developed to align data across temporal, spatial, geometric, and contextual conditions. Experimental results showed R2 values between 0.886 and 0.938, and RMSE values ranging from 0.009 to 0.025 compared to the benchmarks. Among the models tested, the Feedforward Neural Network (FFNN) using the Leaky ReLU activation function achieved the best overall performance. These findings confirm the robustness of this approach, offering a scalable methodology for satellites with similar characteristics and establishing a foundation for a customized atmospheric correction pipeline for PeruSAT-1. Future work will focus on diversifying the dataset across spectral and seasonal conditions and optimizing the modeling to address challenges in shorter wavelengths and high-reflectance surfaces.
Co-LLaVA: Efficient Remote Sensing Visual Question Answering via Model Collaboration
Authors: Liu Fan , Dai Wenwen , Zhang Chuanyi , Zhu Jiale , Yao Liang , Li Xin
Published: January 2025

Large vision language models (LVLMs) are built upon large language models (LLMs) and incorporate non-textual modalities; they can perform various multimodal tasks. Applying LVLMs in remote sensing (RS) visual question answering (VQA) tasks can take advantage of the powerful capabilities to promote the development of VQA in RS. However, due to the greater complexity of remote sensing images compared to natural images, general-domain LVLMs tend to perform poorly in RS scenarios and are prone to hallucination phenomena. Multi-agent debate for collaborative reasoning is commonly utilized to mitigate hallucination phenomena. Although this method is effective, it comes with a significant computational burden (e.g., high CPU/GPU demands and slow inference speed). To address these limitations, we propose Co-LLaVA, a model specifically designed for RS VQA tasks. Specifically, Co-LLaVA employs model collaboration between Large Language and Vision Assistant (LLaVA-v1.5) and Contrastive Captioners (CoCas). It combines LVLM with a lightweight generative model, reducing computational burden compared to multi-agent debate. Additionally, through high-dimensional multi-scale features and higher-resolution images, Co-LLaVA can enhance the perception of details in RS images. Experimental results demonstrate the significant performance improvements of our Co-LLaVA over existing LVLMs (e.g., Geochat, RSGPT) on multiple metrics of four RS VQA datasets (e.g., +3% over SkySenseGPT on “Rural/Urban” accuracy in the test set of RSVQA-LR dataset).
SDGSAT-1 Cloud Detection Algorithm Based on RDE-SegNeXt
Authors: Li Xueyan , Hu Changmiao
Published: January 2025

This paper proposes an efficient cloud detection algorithm for Sustainable Development Scientific Satellite (SDGSAT-1) data. The core work includes the following: (1) constructing a SDGSAT-1 cloud detection dataset containing five types of elements: clouds, cloud shadow, snow, water body, and land, with a total of 15,000 samples; (2) designing a multi-scale convolutional attention unit (RDE-MSCA) based on a gated linear unit (GLU), with parallel re-parameterized convolution (RepConv) and detail-enhanced convolution (DEConv). This design focuses on improving the feature representation and edge detail capture capabilities of targets such as clouds, cloud shadow, and snow. Specifically, the RepConv branch focuses on learning a new global representation, reconstructing the original multi-branch deep convolution into a single-branch structure that can efficiently fuse channel features, reducing computational and memory overhead. The DEConv branch, on the other hand, uses differential convolution to enhance the extraction of high-frequency information, and is equivalent to a normal convolution in the form of re-parameterization during the inference stage without additional overhead; GLU then realizes adaptive channel-level information regulation during the multi-branch fusion process, which further enhances the model’s discriminative power for easily confused objects. It is integrated into the SegNeXt architecture based on RDE-MSCA and proposed as RDE-SegNeXt. Experiments show that this model can achieve 71.85% mIoU on the SDGSAT-1 dataset with only about 1/12 the computational complexity of the Swin-L model (a 2.71% improvement over Swin-L and a 5.26% improvement over the benchmark SegNeXt-T). It also significantly improves the detection of clouds, cloud shadow, and snow. It achieved competitive results on both the 38-Cloud and LoveDA public datasets, verifying its effectiveness and versatility.
Creating Refined Datasets for Better Chaos Detection
Authors: Augustyn Dariusz R. , Harężlak Katarzyna , Szczęsna Agnieszka , Josiński Henryk , Kasprowski Paweł , Świtoński Adam
Published: January 2025

In recent years, the analysis of signal properties (especially biomedical signals) has become an important research direction. One interesting feature of signals is their potential to be chaotic. This article concerns the issues of classification of real signals or synthetic ones in the context of detecting chaotic properties. In previous works, datasets of synthetic signals were created based on well-known chaotic and non-chaotic dynamical systems. They were published and used to train classifiers. This paper extends the previous studies and proposes a method for obtaining/extracting signals to force classifiers to learn to detect chaos. The proposed method allows the generation of groups of signals with similar initial conditions. The property of chaotic dynamical systems was used here, which consists of the strong dependence of the signal courses on a small change in the initial conditions. This method is based on reconstructing multidimensional phase space and data clustering. An additional goal of the work is to create referential datasets with so-called refined signals using the described method and to make them publicly available. The usefulness of the new datasets was confirmed during a simple experiment with the usage of the LSTM neural network.
Mitigating Voltage Violations in Smart City Microgrids Under Coordinated False Data Injection Cyberattacks: Simulation and Experimental Insights
Authors: Naderi Ehsan , Asrari Arash
Published: January 2025

This article investigates the impacts of coordinated false data injection attacks (FDIAs) on voltage profiles in smart microgrids integrated with renewable-based distributed energy resources (DERs), a critical component of urban energy infrastructure in smart cities. By leveraging simulation and experimental methods, a coordinated framework is developed for understanding and mitigating these threats, ensuring the stability of renewable-based DERs integral to modern urban systems. In the examined framework, a team of attackers independently identify the optimal times of two different cyberattacks leading to undervoltage and overvoltage in a smart microgrid. The objective function of each model is to increase the voltage violation in the form of either overvoltage or undervoltage caused by the corresponding FDIA. In such a framework, the attackers design a multi-objective optimization problem (MOOP) simultaneously resulting in voltage violations in the most vulnerable regions of the targeted microgrid. Considering the conflict between objective functions in the developed MOOP, a Pareto-based solution methodology is utilized to obtain a set of optimal solutions, called non-dominated solutions, as well as the best compromise solution (BCS). The effectiveness of the unified FDIA is verified based on simulation and experimental validations. In this regard, the IEEE 13-node test feeder has been modified as a microgrid for the simulation analysis, whereas the experimental validation has been performed on a lab-scale hybrid PV/wind microgrid containing renewable energy resources.
Psychosocial Differences Between Female and Male Students in Learning Patterns and Mental Health-Related Indicators in STEM vs. Non-STEM Fields
Authors: Elvira-Zorzo María Natividad , Gandarillas Miguel Ángel , Martí-González Mariacarla
Published: January 2025

This study explores psychosocial differences in mental health indicators and learning patterns between male and female students to promote inclusion and equality in university classrooms, focusing on STEM and non-STEM fields. Using a holistic approach, five learning dimensions comprising a diversity-in-learning (DinL) construct were analyzed: Coping with Difficulties, Effort, Autonomy, Understanding/Career Interest, and Social Context. Psychosocial predictors, including paternal and maternal parenting patterns, were also examined. Data were collected through a questionnaire completed by 2443 students from 83 undergraduate and postgraduate programs. Results indicated that male students reported higher levels of autonomy, while female students reported experiencing more mental health difficulties related to learning. Gender differences in learning dimensions were more pronounced in non-STEM fields. Parental influences also differed, with fathers and mothers shaping male and female students’ learning patterns in ways that reflect traditional gender roles. The findings highlight the lasting effects of gender roles on learning habits and psychological challenges in higher education. The study underscores the importance of addressing gender patterns in parenting and education to support more women in pursuing STEM fields, ultimately fostering greater equality and inclusion in academia.
Exploring the Dimensions of Academic Human Capital: Insights into Enhancing Higher Education Environments in Egypt
Authors: Pereira Manuel Sousa , Cardoso António , El Sherbiny Nourhan M. , da Silva Amândio F. C. , Figueiredo Jorge , Oliveira Isabel
Published: January 2025

The performance of higher education institutions is significantly influenced by their academic human capital (AHC), which encompasses research competencies, dynamic capacity, working capacity, critical thinking, social capital, and external relations. This study aims to investigate the interrelationships among these dimensions and their collective impact on institutional performance. Utilizing a comprehensive literature review and empirical analysis, we identify key factors that enhance AHC and propose strategies for optimizing these dimensions to foster innovation, adaptability, and organizational effectiveness. The quantitative study with a descriptive design uses a questionnaire, collecting 302 responses from university professors and researchers in Egypt. The findings highlight the pivotal role of research competencies and dynamic capacity in driving academic excellence and institutional resilience. Additionally, the study underscores the importance of external relations and social capital in enriching academic environments and facilitating knowledge transfer. By providing a nuanced understanding of AHC, this research offers actionable insights for policymakers and educational leaders aiming to bolster the performance and sustainability of higher education institutions.
Are Wolves the Real Problem? Challenges Faced by Livestock Farmers Living Alongside Wolves in Northwestern Greece
Authors: Petridou Maria , Kati Vassiliki
Published: January 2025

Mitigating human–wolf conflict is crucial, yet conventional approaches often overlook the broader socioeconomic challenges faced by farming communities. Wolves frequently become scapegoats for deeper rooted issues such as economic disadvantages, policy deficiencies, and rural depopulation. We conducted semi-structured interviews with 118 livestock farmers to examine (a) farmer profiles and wolf-related interactions, (b) professional challenges and proposed solutions, (c) reasons for perceiving wolves as a major problem, and (d) the impact of wolf presence on job dissatisfaction. Farmers reported low specialized education and job satisfaction, particularly regarding income. Many struggled to afford or find shepherds, especially sheep/goat farmers. Guardian dog poisoning incidents and dissatisfaction with the damage compensation system were prevalent. Key challenges included economic marginalization, wolf presence, climatic factors, inadequate grazing policies, infrastructure deficits, distrust in policy, rural depopulation, and a lack of services. Farmers who perceived wolves as a major problem implemented weaker preventive measures and moved herds seasonally over longer distances. Job dissatisfaction was linked to wolf presence, livestock type, and economic marginalization. Our findings emphasize that while wolves impact farmers, economic and policy-related factors play a greater role. Educational initiatives, supportive policies, effective depredation mitigation, and fair compensation systems are essential for sustainable livestock farming and coexistence with wolves. By tackling socioeconomic challenges, enhancing policies, and supporting farmers to adapt to evolving circumstances, the livestock farming sector can thrive while minimizing conflicts associated with wolves.
Train Planning for Through Operation Between Intercity and High-Speed Railways: Enhancing Sustainability Through Integrated Transport Solutions
Authors: Lin Li , Meng Xuelei , Song Kewei , Feng Liping , Han Zheng , Xia Ximan
Published: January 2025

In order to advocate for green and environmentally friendly travel modes, enhance the attractiveness of rail transit, and promote the sustainable development of rail transport, we focus on the transportation organization problem under limited-resource conditions. This paper studies the formulation of a train plan under the condition of through operation between intercity and high-speed railway, constructing a multi-objective nonlinear optimization model with train frequency, a stop plan, and turn-back station locations as decision variables. Given the high dimensionality of model variables and complex constraints, an improved multi-population genetic algorithm (IMGA) is designed. Through an actual case study of the through operation between the Chengdu–Mianyang–Leshan Intercity Railway and the Chengdu–Chongqing High-Speed Railway, a staged solution method is adopted for analysis. The results indicate that the through-operation mode can save operational costs for enterprises and travel costs for passengers, while also better adapting to changes in passenger flow. Additionally, the IMGA demonstrates better solution quality and higher efficiency compared to the classical genetic algorithm. The main contribution of this paper is to propose a novel approach to solve the train plan problem. It also contributes to creating a high-quality, high-efficiency, and high-comfort integrated transportation service network, promoting the sustainable development of rail transit.
Barabási–Albert-Based Network Growth Model to Sustainable Urban Planning
Authors: Abramov Aleksandr , Gorik Uliana , Velichko Andrei , Nelyub Vladimir , Samoshkin Aleksandr , Gantimurov Andrei , Borodulin Aleksei , Tynchenko Vadim S. , Malashin Ivan
Published: January 2025

Urban planning and development require methodologies to address the challenges of managing urban growth. This study uses Vladivostok as a case study to explore urban evolution and apply predictive models for socio-economic development. By analyzing the life cycle of the city and breaking down its growth processes into key components, specific patterns and strategies tailored to Vladivostok’s development are identified. The Barabási–Albert (BA) network growth model is used to study the temporal dynamics of the city’s urban network, enabling forecasts and optimization of its infrastructure, communication systems, and social environment. The approach shown in this study can be adapted to other cities, providing a framework for analyzing urban changes and supporting the development of strategies for sustainable growth and urban management.
A Proposal for the Improvement of Daylight Integration and Distribution in the Educational Interior Space Through a (Pro-Sun) Ceiling Design with Curved Surfaces
Authors: Fakıbaba Dedeoğlu Esin , Yalçın Meryem
Published: January 2025

The use of daylight as the primary lighting source in buildings is crucial for achieving energy savings. Significantly reducing the dependence on artificial lighting sources relies on more efficient utilization of available daylight and enhancement of its quantity and distribution within interior spaces. The appropriate use of daylight not only enhances energy efficiency in indoor spaces but also positively impacts users’ health and performance. A growing body of research has focused on methods for maximizing the use of daylight in interior environments. This study proposes a ceiling design aimed at utilizing daylight more efficiently in interior spaces. The quantity of daylight in an educational space was calculated using the VELUX Daylight Visualizer program by comparing the results of existing, diagonal, and curved ceiling designs. Light levels were measured before and after the addition of Pro-Sun to assess daylight integration and distribution in the studios’ interior spaces. The design studio was analyzed based on orientation (north-south), school semester, active hours, and ceiling type. As a result of the comparison of ceiling types, the Pro-Sun ceiling system with curved reflectors had the most daylight integration capacity and distribution in the deeper the studio’s interior space.
Mapping Gamification for Sustainable Urban Development: Generating New Insights for Tourism Education
Authors: Fraga Carla , Cardoso Lucília , de Stefano Ercília , Lima Santos Luís , Motta Natália
Published: January 2025

Although scientific literature already shows the connections between gamification, tourism and sustainability, there is still a gap in research into how gamification can transform cities into more playful, sustainable and intelligent tourism destinations. Gamification in tourism promotes engagement, education and innovation, enriching experiences and driving the development of smart destinations. This study advances this debate by employing a mixed methodology, combining a systematic review (supported by Rayyan, an artificial intelligence) and content analysis (supported by Iramuteq, a textual software, version 0.7 Alpha 2). Additionally, we used Dreamscape by Voyant Tools online for a geographical analysis of the textual corpus formed by n = 61 abstracts. The intersection of main findings from the techniques applied provides eight new insights on urban tourism education through gamification, which are as follows: (1) exchange between the Global North and South; (2) local and global participation; (3) collaborations to achieve the 17 SDGs; (4) improve urban destination marketing by ethics principles; (5) deepening disruption technology and ethics studies; (6) the transformation of reality by sciences; (7) gamification on interdisciplinary perspectives; and (8) the role of gamification on the tourism and hospitality industry. The results suggest that gamification in tourism can offer a new ontological approach to addressing sustainable urban development, highlighting both theoretical and practical challenges. This research has both theoretical and practical implications, advancing the concept of ecogaming by integrating technology, entertainment and sustainability, and reinforces its potential to educate and engage in sustainable urban tourism practices.
Significance of Morphology in Characterizing Human Health Risk from di(2-ethylhexyl) Phthalate in Polyvinyl Chloride Microplastics in Groundwater
Authors: Song Ki-Han , Yoon Sang-Gyu , Lee Jin-Yong , An Jinsung
Published: January 2025

In this study, a human health risk assessment was performed on the ingestion route of groundwater containing polyvinyl chloride (PVC) microplastics (MPs), and the carcinogenic and non-carcinogenic risks of di(2-ethylhexyl) phthalate (DEHP), a representative additive, were determined. In particular, the impact of volume diversity according to the shape (morphology) of PVC MP (fragment, fiber, film) on the risk characterization was intensively explored. Firstly, a continuous particle size distribution following a power function was derived using the abundance ratio of PVC MPs by size in the investigated groundwater, and human health risk assessment for DEHP in the PVC MPs was performed through the volume distribution according to the shape of MPs. DEHP human health risk assessment showed an excess cancer risk (ECR) of below 10−6 for a 95% cumulative probability for all MP shapes, but the values varied depending on the shape. Sensitivity analysis showed that the parameter that most affected human health risk was MP volume, second to concentration, which is dependent on MP shape. Therefore, it is necessary to consider the variety of MP shapes during human health risk assessment, and it can be achieved through probabilistic risk assessment utilizing the probability distribution for size and shape of MPs.
Biting Hour and Host Seeking Behavior of Aedes Species in Urban Settings, Metema District, Northwest Ethiopia
Authors: Jemberie Wondmeneh , Dugassa Sisay , Animut Abebe
Published: January 2025

Background: Aedes species transmit arboviral diseases, such as dengue, chikungunya, yellow fever, and Zika. The diseases cause severe sickness, mortality, and economic losses. This study describes the biting hour and host-seeking behavior of Ae. aegypti and Ae. vittatus in three towns. Recently, chikungunya and dengue infections were reported in the study sites. Methods: Biting hour and host-seeking behaviors of Ae. aegypti and Ae. vittatus were studied from June to September 2023, in Genda-Wuha, Kokit, and Metema-Yohannes towns, Metema district, Northwest Ethiopia. CDC-LT traps were set running indoors and outdoors for 24 h closer to humans sleeping inside unimpregnated mosquito nets. At the same time, CDC-LT traps were set running overnight closer to domestic animals’ shelters located within a 50-m radius of the main residence. Mosquitoes trapped in CDC-LT were collected every hour. The study was conducted four times in each town during the wet season. A chi-square test was employed to examine biting hour and host-seeking behavior. Results: Aedes aegypti was observed to be highly exophilic and active during the daylight hours. Aedes aegypti exhibited a peak biting rate between 07:00 and 08:00 with the biting rate of 4.5/person/hour followed by from 17:00 pm to 18:00 pm with the biting rate of 3.75/person/hour. The hourly biting rate of Ae. aegypti differed significantly. Its peak indoor biting rate was from 19:00 to 20:00 with the rate of 2.00 bites/person/hour followed by from 08:00 to 09:00 with the rate of 1.50 bites/person/hour and the biting rates differed significantly across the hours (F = 240.046; p = 0.001). Aedes vittatus also exhibited a biting rate similar to that of Ae. aegypti. Both Ae. aegypti and Ae. vittatus were abundantly collected from nearby human sleeping arrangements than from the shelters of cattle, sheep, goats, and donkeys. The highest proportions of Ae. aegypti (91.21%) and Ae. vittatus (89.87%) were unfed. Conclusions: Aedes aegypti and Ae. vittatus exhibited peak biting rates during morning and early night hours that aligned with the active daily routine practices of the local community. This could potentially expose the inhabitants to viral diseases transmitted by Ae. aegypti and Ae. vittatus.
A Comprehensive Review of Riverbank Filtration Technology for Water Treatment
Authors: Gao Yuanchao , Tang Ye , Zhao Min , Zheng Xiangyong , Jin Huachang
Published: January 2025

Riverbank filtration (RBF) technology has been applied and investigated worldwide for water supplies due to its sustainable water quantity guarantee and reliable quality improvement. In this work, the development history, application status, research progress, and technical overview of RBF are reviewed and summarized. RBF usually uses rivers, lakes, and groundwater as raw water, with a few cases using seawater. Nitrogen removal in RBF systems primarily occurs through key geochemical processes such as adsorption, denitrification, organic nitrogen mineralization, and dissimilatory nitrate reduction to ammonium (DNRA). For the attenuation of emerging contaminants in groundwater environments, key processes such as filtration, adsorption, and biotransformation play a crucial role, and microorganisms are essential. Based on a discussion of the advantages and disadvantages, we proposed the research prospects of RBF. To further enhance the water-supply safety and security with RBF, the mechanisms of surface water and groundwater interaction, pollutant removal, and blockage; the impact of capturing surface water on the stability of river ecosystems; and the coupling and synergistic effect of RBF with other water treatment technologies should be deeply investigated.
Best approximation of Hartley-Bessel multiplier operators on weighted Sobolev spaces
Authors: Chana Ahmed , Akhlidj Abdellatif
Published: January 2025

The main goal of this paper is to introduce the Hartley-Bessel \(L^2_\alpha\)-multiplier operators and to give for them some new results as Plancherel’s, Calderon’s reproducing formulas and Heisenberg’s, Donoho-Stark’s uncertainty principles. Next, using the theory of reproducing kernels we give best approximation and an integral representation of the extremal functions related to these operators on weighted Sobolev spaces.
Natural Language Processing Identifies Under-Documentation of Symptoms in Patients on Hemodialysis
Authors: Dai Yang , Wen Huei Hsun , Yang Joanna , Gupta Neepa , Rhee Connie , Horowitz Carol R. , Mohottige Dinushika , Nadkarni Girish N. , Coca Steven , Chan Lili
Published: January 2025

Background:

Patients on hemodialysis (HD) have a high burden of emotional and physical symptoms. These symptoms are often under-recognized. NLP can be used to identify patient symptoms from the EHR. However, whether symptom documentation matches patient reported burden is unclear.

Methods:

We conducted a prospective study of patients seen at an ambulatory nephrology practice from September 2020 to April 2021. We collected symptom surveys from patients, nurses, and physicians. We then developed a natural language processing (NLP) algorithm to identify symptoms from the patients’ electronic health records (EHR) and validated the performance of this algorithm using manual chart review and patient surveys as a reference standard. Using patient surveys as the reference standard, we compared symptom identification by 1) physicians, 2) nurses, 3) physicians or nurses, and 4) NLP.

Results:

We enrolled 97 patients into our study, 63% were female, 49% were Non-Hispanic Black, and 41% were Hispanic. The most common symptoms reported by patients were fatigue (61%), cramping (59%), dry skin (53%), muscle soreness (43%), and itching (41%). Physicians and nurses significantly under-recognized patients’ symptoms (sensitivity 0.51 (95% CI 0.40-0.61) and 0.63 (95% CI 0.52-0.72) respectively). Nurses were better at identifying symptoms when patients reported more severe symptoms. There was no difference in results by patients’ sex or ethnicity. NLP had a sensitivity of 0.92, specificity of 0.95, PPV of 0.75, and NPV of 0.99 with manual EHR review as the reference standard, and a sensitivity of 0.58 (95% CI 0.47-0.68), specificity of 0.73 (95% CI 0.48-0.89), PPV of 0.92 (95% CI 0.82-0.97), and NPV of 0.24 (95% CI 0.14-0.38) compared with patient surveys.

Conclusions:

While patients on HD report high prevalence of symptoms, symptoms are under-recognized and under-documented. NLP was accurate at identifying symptoms when they were documented. Larger studies in representative populations are needed to assess the generalizability of the results of the study.
New-onset Seizure Presenting as Status Epilepticus Secondary to Envenomation and Anaphylaxis: A Case Report
Authors: Almaraz Lira Josué Saul , Chávez Haro Alfredo Luis
Published: January 2025

Introduction.Venomous bites and stings from insects and arachnids can lead to severe neurological complications, including status epilepticus. While the mechanisms are not entirely understood, neurotoxic venom effects and immune responses are thought to play critical roles. Certain medications like non-steroidal anti-inflammatory drugs (NSAID), often prescribed for pain management in envenomation cases, may inadvertently exacerbate these effects. This report highlights a case involving a previously healthy patient who experienced status epilepticus and other severe complications following a venomous bite and subsequent NSAID administration. Case Presentation. A male patient without previous epileptic seizures, reported a bite on the right wrist, initially experiencing localized pain and swelling. Symptoms rapidly progressed over 24 hours, prompting the patient to seek emergency treatment. Ketorolac was administered for analgesia, but this led to severe respiratory distress, necessitating advanced airway management and intensive care unit admission. Persistent tonic-clonic seizures followed, unresponsive to initial sedation and anticonvulsant therapy, requiring additional agents, including dexamethasone and Alacramyn. Imaging revealed potential demyelinating lesions and elevated inflammatory markers indicated a systemic response to envenomation. Conclusions.This case highlights the complexity and risks associated with venomous bites, particularly when compounded by the use of medications such as NSAIDs. While the presented status epilepticus may be linked to envenomation and an adverse drug reaction, the speculative nature of this connection underscores the need for further investigation. The uncertainty regarding underlying mechanisms, whether direct neurotoxicity, enhanced immunological responses, drug interactions, or genetic predispositions, needs cautious clinical management. Early recognition and timely intervention are essential to mitigate potential sequelae and improve patient outcomes.
Work-integrated learning challenges of engineering diploma students at select South African universities of technology
Authors: Soobramoney Jayanathan , Govender Krishna
Published: January 2025

Purpose. The study aimed to identify the challenges experienced by select universities of technology, industry mentors, and engineering diploma students regarding the work-integrated learning (WIL) component of the study programme.
Methodology. A concurrent mixed-methods approach was used, which included a survey and focus group interviews. Both purposive and convenient sampling processes were used to select the sample. The survey sample comprised 25 university of technology employees, 28 industry mentors, and 165 learners. The focus group was comprised of six members selected based on their involvement and expertise with WIL issues, including a placement officer, a training manager, a WIL facilitator, senior technicians, and a corporate director.
Results. The most significant challenge was the long waiting period for learners to find suitable placements, which impacted their completion and graduation. Learners lacked the relevant computer literacy skills required by the industry, as well as communication skills. Learners also faced challenges working with industrial drawings and documentation, and could not manage projects in the workplace. The inability to work in teams, and having the correct attitude to work were also highlighted as challenges. The responsibilities outlined in the logbooks did not always correspond with those in the workplace either. The learners also complained about infrequent visits from university staff to monitor their performance in the workplace. It also became apparent that the academic institutions did not adequately prepare the learners for the world of work.
Conclusions. The study highlighted the many challenges encountered by the learners, the academic staff involved in WIL activities and the industry mentors, implying the need for a strategic overview, and overhaul of the relevant WIL programme, including policies and processes. Recommendations are made on how all the players could address the challenges.
Dictionnaire et atlas : propriétés lexicales et sémantiques des urbanonymes en français
Authors:   Beijing Language and Culture University, China, Samo Giuseppe , Ursini Francesco-Alessio ,   Central China Normal University, Wuhan, China
Published: January 2025

The aim of this article is to study the semantic-lexical relations that emerge between French urban place names (e.g., rue Calvin) via their generic terms (e.g., rue). To achieve this objective, the article proposes a classification of urban place names in the canton of Geneva (Switzerland) based on a two-stage model. The first stage involves a lexicographic analysis of geonyms extracted from a French language dictionary. The second stage involves analysing the geographical distribution of these generic terms. It is then proposed that the lexicographic analysis should identify the meanings of the generic terms, while the geolinguistic analysis should identify the referential relationships between the generic terms and the types of places they describe. Using this model, a taxonomy of generic terms in place names can be proposed, based on hyponymy relationships. This taxonomy reflects a conceptualisation of urban places through the prism of French language.
Categorizing personal names among Jews in the contemporary United States
Authors:   Hebrew Union College – Jewish Institute of Religion, Los Angeles, CA, USA, Benor Sarah Bunin , Chandler Alicia B. ,   Wayne State University, Detroit, Michigan, USA
Published: January 2025

This paper analyses the distribution of American Jews’ personal names based on a survey of 6,816 American Jews. The non-random sample yielded 2,868 discreet names. We developed ten naming categories: Hebrew Biblical Character, English Biblical Character, Ambiguous Biblical Character, Hebrew Post-Biblical, Yiddish Biblical Character, Yiddish, Hebrew Biblical Modern, Hebrew Modern, Ambiguously Jewish, and No Jewish Origin. Respondents were asked to rate the likelihood of Jewishness for 26 names, their name, their spouse’s name, and their children’s names. Based on this data, we developed two umbrella categories: Distinctively Jewish and Not Distinctively Jewish. Most names in our sample were Not Distinctively Jewish, such as No Jewish Origin and English Biblical names. The use of Distinctively Jewish names increased significantly beginning in 1970, and name category correlates with various religious and demographic dimensions. We discuss the findings in historical and sociological context, and we explain the implications for onomastic research.
Оценка наличия эндофитной микоризы у Krascheninnikovia ceratoides (L.) Gueldenst. в засушливых условиях
Authors: Крылов П.А. , Малов В.О. , Кузьмин П.А.
Published: January 2025

Для борьбы с опустыниванием и восстановлением деградированных территорий юга России используются ксерофитные растения, например, одним из самых распространенных является терескен серый (Krascheninnikovia ceratoides (L.) Gueldenst.). Устойчивость данного растения связана не только с его видовой спецификой, но и наличием эндофитной микоризы, в число которой входит арбускулярная эндомикориза (АМ). Формирование АМ у растений способствует повышению устойчивости к неблагоприятным факторам внешней среды, в частности, засухе. В связи с этим целью работы стало проведение поиска возможного наличия АМ в корневой системе K. ceratoides. Для достижения поставленной цели были использованы морфологические методы исследования, с помощью которых проводили оценку микоризации и образования АМ по методу Травло. В результате исследования были выявлены характерные элементы, присущие как эндофитной микоризе, так и представителям АМ у K. ceratoides. Интенсивность заселения корневой системы эндофитной микоризой составила 37 %. Количество выявленных элементов АМ было 18 %, а число в микоризованных фрагментов корня около 3 %. Полученные данные свидетельствуют о том, что скорее всего есть симбиотическая связь между эндофитными грибами, включая АМ и K. ceratoides, что может способствовать его устойчивости к неблагоприятным факторам внешней среды. Установленный факт может представлять интерес для дальнейших исследований, направленных на отбор групп эндофитных грибов, повышающих устойчивость растений к засухе.

Xerophytic plants are used to combat desertification and restore degraded territories in Southern Russia, for example, one of the most common is Teresken gray (Krascheninnikovia ceratoides (L.) Gueldenst.). The stability of this plant is associated not only with its species specificity, but also with the presence of endophytic mycorrhiza, which includes arbuscular endomycorrhiza fungi (AMF). The formation of AMF in plants contributes to increased resistance to adverse environmental factors, in particular drought. In this regard, the aim of the work was to search for the possible presence of AMF in the root system of K. ceratoides. To achieve this goal, morphological research methods were used, with the help of which mycorrhization and AMF formation were evaluated using the Etching method. The research results revealed elements inherent in both endophytic mycorrhiza and representatives of AMF in K. ceratoides. The intensity of colonization of the root system by endophytic mycorrhiza was 37 %. The number of identified AMF elements was 18 %, and the number in mycorrhizal root fragments was about 3 %. The data obtained indicate that there is most likely a symbiotic relationship between endophytic fungi, including AMF and K. ceratoides, which may contribute to its resistance to adverse environmental factors. This fact may be of interest for further research aimed at selecting groups of endophytic fungi that increase plant resistance to drought.
Влияние весенних заморозков на репродуктивность видов рода Robinia L. в защитных лесонасаждениях Волгоградской области
Authors: Мельник К.А. , Передриенко А.И.
Published: January 2025

Родовой комплекс Robinia L., представляет большую ценность для агролесомелиорации и защитного лесоразведения в Волгоградской области. Объектами исследований являлись виды рода Robinia: R. neomexicana A. Gray. и R. pseudoacacia L., которые произрастают на территории питомника и дендросада в Волгоградской области (ФНЦ агроэкологии РАН и Нижневолжская станция по селекции древесных пород). Цель работы – провести оценку репродуктивной системы видов рода Robinia, а также толерантность к весенним заморозкам во время цветения на территории Волгоградской области. На основе проведенных исследований выявлено, что в процессе постепенной адаптации во время весенних заморозков в фазе «цветение» исследуемые деревья в возрасте до 30 лет значительно повысили толерантность к низким температурам. Изучаемые виды способны формировать устойчивые насаждения, являющиеся перспективными в засушливых условиях. Установлено, что за 2024 г. у R. neomexicana A. Gray. и R. pseudoacacia L. сроки цветения сместились на 12-15 суток от среднего значения. Отмечено вторичное цветение древесных интродуцентов в сухостепных условиях Волгоградской области, что связано со стресс-факторами и погодными условиями данного региона. На территории Нижневолжской станции селекции древесных пород у R. neomexicana балл зимостойкости выше (3,7), чем у R. pseudoacacia L (3,6), так как у данного вида цветение произошло позднее и плодов образовалось на деревьях больше (3,8).

The genus Robinia L. holds significant value for agroforestry and protective afforestation initiatives in the Volgograd region. The subjects of this study were R. neomexicana A. Gray and R. pseudoacacia L., growing in the nursery and dendrological garden of the Volgograd region (Federal Research Center for Agroecology of the Russian Academy of Sciences and the Nizhnevolzhskaya Tree Breeding Station). The aim of the study was to evaluate the reproductive systems of Robinia species and their tolerance to spring frosts during the flowering period in the Volgograd region. The research revealed that during the process of gradual adaptation to spring frosts in the flowering phase, the studied trees, aged up to 30 years, significantly increased their tolerance to low temperatures. The studied species demonstrated the ability to form resilient plantations, making them promising candidates for cultivation in arid regions. It was found that, in 2024, the flowering periods of R. neomexicana A. Gray and R. pseudoacacia L. shifted by 12–15 days from the average values. Secondary flowering of the introduced species was observed under dry-steppe conditions of the Volgograd region, which was attributed to stress factors and the region's climatic conditions. At the Nizhnevolzhskaya Tree Breeding Station, R. neomexicana demonstrated a higher winter hardiness score (3.7) compared to R. pseudoacacia L. (3.6), as its flowering occurred later, resulting in a greater fruit yield (3.8).
Validación por juicio de expertos de una rúbrica socioformativa que busca autoevaluar la práctica docente en el contexto del desarrollo social sostenible
Authors: Arredondo Cortés Sergio Alejandro
Published: January 2025

Los retos actuales relacionados a la sostenibilidad van en aumento, por ello el análisis de la propia práctica docente sigue siendo un área de oportunidad que nos permita reflexionar acerca de nuestras fortalezas y debilidades. Uno de los objetivos de este artículo fue diseñar una rúbrica socioformativa para autoevaluar la práctica docente para favorecer el desarrollo social sostenible, así como su validación. La rúbrica fue analizada por 3 expertos, para validar el contenido estuvo en manos de 15 jueces expertos, mediante un análisis cuantitativo por medio de la V de Aiken. Se aplicó la rúbrica a un grupo piloto de 15 maestros para analizar la confiabilidad del instrumento, este está compuesto por tres dimensiones y 11 preguntas. Los resultados obtenidos del análisis de los jueces con relación a la pertinencia y redacción (V de Aiken > 0.80). Lo que corresponde a los resultados del grupo piloto en alfa de Cronbach: 0.923. Para un análisis más profundo y preciso en su confiabilidad se recomienda aplicarlo a un grupo significativo.