bluuebunny/crossref_metadata_2025 huggingface dataset:
General Approach for Forest Woody Debris Detection in Multi-Platform LiDAR Data
Authors: dos Santos Renato César , Shin Sang-Yeop , Manish Raja , Zhou Tian , Fei Songlin , Habib Ayman
Published: February 2025

Woody debris (WD) is an important element in forest ecosystems. It provides critical habitats for plants, animals, and insects. It is also a source of fuel contributing to fire propagation and sometimes leads to catastrophic wildfires. WD inventory is usually conducted through field surveys using transects and sample plots. Light Detection and Ranging (LiDAR) point clouds are emerging as a valuable source for the development of comprehensive WD detection strategies. Results from previous LiDAR-based WD detection approaches are promising. However, there is no general strategy for handling point clouds acquired by different platforms with varying characteristics such as the pulse repetition rate and sensor-to-object distance in natural forests. This research proposes a general and adaptive morphological WD detection strategy that requires only a few intuitive thresholds, making it suitable for multi-platform LiDAR datasets in both plantation and natural forests. The conceptual basis of the strategy is that WD LiDAR points exhibit non-planar characteristics and a distinct intensity and comprise clusters that exceed a minimum size. The developed strategy was tested using leaf-off point clouds acquired by Geiger-mode airborne, uncrewed aerial vehicle (UAV), and backpack LiDAR systems. The results show that using the intensity data did not provide a noticeable improvement in the WD detection results. Quantitatively, the approach achieved an average recall of 0.83, indicating a low rate of omission errors. Datasets with a higher point density (i.e., from UAV and backpack LiDAR) showed better performance. As for the precision evaluation metric, it ranged from 0.40 to 0.85. The precision depends on commission errors introduced by bushes and undergrowth.
Development of a Multi-Channel Ultra-Wideband Electromagnetic Transient Measurement System
Authors: He Shaoyin , Chen Xiangyu , Zhang Bohao , Song Liang
Published: February 2025

In complex electromagnetic environments, such as substations, converter stations in power systems, and the compartments of aircraft, trains, and automobiles, electromagnetic immunity testing is crucial. It requires that the electric field sensor has features such as a large dynamic measurement range (amplitude from hundreds of V/m to tens of kV/m), a fast response speed (response time in the order of nanoseconds or sub-nanoseconds), a wide test bandwidth (DC to 1 GHz even above), miniaturization, and robustness to strong electromagnetic interference. This paper introduces a multi-channel, ultra-wideband transient electric field measurement system. The system’s analog bandwidth covers the spectrum from DC and a power frequency of 50 Hz to partial discharge signals, from DC to 1.65 GHz, with a storage depth of 2 GB (expandable). It overcomes issues related to the instability, insufficient bandwidth, and lack of accuracy of optical fibers in analog signal transmission by using front-end digital sampling based on field-programmable gate array (FPGA) technology and transmitting digital signals via optical fibers. This approach is effectively applicable to measurements in strong electromagnetic environments. Additionally, the system can simultaneously access four channels of signals, with synchronization timing reaching 300 picoseconds, can be connected to voltage and current sensors simultaneously, and the front-end sensor can be flexibly replaced. The performance of the system is verified by means of a disconnect switch operation and steady state test in an HVDC converter station. It is effectively applicable in scenarios such as the online monitoring of transient electromagnetic environments in high-voltage power equipment, fault diagnosis, and the precise localization of radiation sources such as partial discharge or intentional electromagnetic interference (IEMI).
Experimental Investigation on Passive Survivability of Lithium-Ion Batteries Under Extremely Low Temperatures
Authors: Soleimani Borujerdi Ali , Zhu Jinying , Zhang Bo , Guo Yinsheng
Published: February 2025

This paper presents an experimental study using an ultrasonic technique to investigate the impact of extremely low temperatures on the performance of lithium-ion batteries. Lithium-ion polymer batteries were aged in three low-temperature conditions: in a temperature chamber (−34 °C), in a dry ice bath (−78 °C), and in a liquid nitrogen bath (−196 °C). The battery aged in liquid nitrogen was damaged. The batteries aged in the chamber and dry ice bath were then subjected to charge and discharge cycles and simultaneously monitored using the ultrasonic technique. Three key ultrasonic parameters were measured, signal amplitude, time of flight (TOF), and TOF shift, using 5 MHz commercial ultrasonic transducers. These measurements were conducted alongside electrical measurements (voltage and current) to monitor the batteries throughout the testing cycles. The results showed that the aged batteries exhibited significantly lower ultrasonic amplitude compared to the control batteries. Additionally, as the cycle number increased, the TOF increased and the discharge capacity decreased. The TOF shift increased linearly with the discharge capacity. However, no clear correlation was observed between the slope of this linear relationship and the low-temperature aging history of the batteries. Overall, the ultrasonic amplitude proved to be a reliable parameter for differentiating the control and low-temperature aged batteries.
Optimized Machine Learning for the Early Detection of Polycystic Ovary Syndrome in Women
Authors: Panjwani Bharti , Yadav Jyoti , Mohan Vijay , Agarwal Neha , Agarwal Saurabh
Published: February 2025

Polycystic ovary syndrome (PCOS) is a medical condition that impacts millions of women worldwide; however, due to a lack of public awareness, as well as the expensive testing involved in the identification of PCOS, 70% of cases go undiagnosed. Therefore, the primary objective of this study is to design an expert machine learning (ML) model for the early diagnosis of PCOS based on initial symptoms and health indicators; two datasets were amalgamated and preprocessed to accomplish this goal, resulting in a new symptomatic dataset with 12 attributes. An ensemble learning (EL) model, with seven base classifiers, and a deep learning (DL) model, as the meta-level classifier, are proposed. The hyperparameters of the EL model were optimized through the nature-inspired walrus optimization (WaO), cuckoo search optimization (CSO), and random search optimization (RSO) algorithms, leading to the WaOEL, CSOEL, and RSOEL models, respectively. The results obtained prove the supremacy of the designed WaOEL model over the other models, with a PCOS prediction accuracy of 92.8% and an area under the receiver operating characteristic curve (AUC) of 0.93; moreover, feature importance analysis, presented with random forest (RF) and Shapley additive values (SHAP) for positive PCOS predictions, highlights crucial clinical insights and the need for early intervention. Our findings suggest that patients with features related to obesity and high cholesterol are more likely to be diagnosed as PCOS positive. Most importantly, it is inferred from this study that early PCOS identification without expensive tests is possible with the proposed WaOEL, which helps clinicians and patients make better informed decisions, identify comorbidities, and reduce the harmful long-term effects of PCOS.
Beamforming for the Cooperative Non-Orthogonal Multiple Access Transmission with Full-Duplex Relaying with Application to Security Attack
Authors: Hwang Duckdong , Nam Sung Sik , Yang Janghoon , Song Hyoung-Kyu
Published: February 2025

We investigate the cooperative non-orthogonal multiple access (CNOMA) transmission through a full-duplex (FD) decode-and-forward (DaF) mode relay and propose two sub-optimal beamforming schemes for this CNOMA FD relay channel. For the optimization metric, we use the end-to-end information rate based on the mutual information from information theory. In addition to the pure CNOMA relay channel, the proposed beamforming schemes are applied to the security attack case as well, where an unauthorized eavesdropper tries to overhear the CNOMA transmission. The FD operation incurs the self-interference (SI) at the relay and the DaF mode along with CNOMA transmission forces the weakest link among the links toward three involved nodes to determine the end-to-end throughput. These facts lay the foundation for the designing and optimization of the beamforming vectors at the access point (AP) and at the relay. The first proposed sub-optimal optimization algorithm for the beamformer relies on the quadratically constrained quadratic problem (QCQP) in its central part, and this OCQP is iteratively applied with different interference level values at the near CNOMA user as the constraint term until some conditions for the design objectives are met. In addition to the first algorithm, a zero-forcing-based beamforming algorithm is proposed for a reference scheme. The proposed two algorithms are slightly modified to address the security-attacked CNOMA FD relay channel when a illegal user overhears the legitimate transmission. Simulation results are presented to advocate for the efficiency of the proposed algorithms for the CNOMA channel both with and without a security attack from an eavesdropper.
NELD-EC: Neighborhood-Effective-Line-Density-Based Euclidean Clustering for Point Cloud Segmentation
Authors: Su Zhigang , Du Shixing , Hao Jingtang , Han Bing , Ge Peng , Wang Yue
Published: February 2025

For the problem that it is difficult to effectively cluster lidar point clouds with irregular shapes and uneven densities, a Neighborhood Effective Line Density (NELD)-based Euclidean Clustering (NELD-EC) algorithm is proposed in this paper. The NELD-EC algorithm first eliminates the interfering points within the neighborhood of the data point by utilizing the distance relationship and calculates the NELD of the data point using the effective neighborhood set without interfering points of the data point. The NELD of a data point is taken as the local density of that data point. Then, the NELD-EC algorithm conducts clustering processing using the NELD of all data points and uses the reciprocal of the harmonic average of the local densities of all data points within each cluster after clustering as the distance threshold for the data points within the cluster. Finally, the NELD-EC algorithm completes the clustering of the point cloud based on the adjusted adaptive distance threshold. The clustering experimental results on simulated point clouds, fixed point clouds, and sequential point clouds indicate that, compared with several other typical Euclidean clustering algorithms, the NELD-EC algorithm requires simpler parameters to be set, is less sensitive to the initial distance threshold, can effectively reduce the occurrence probabilities of over-segmentation and under-segmentation, and has strong stability in clustering performance. The NELD-EC algorithm is more suitable for processing sequential point clouds in actual dynamic and complex scenarios.
Vision-Based Localization in Urban Areas for Mobile Robots
Authors: Alimovski Erdal , Erdemir Gokhan , Kuzucuoglu Ahmet Emin
Published: February 2025

Robust autonomous navigation systems rely on mapping, locomotion, path planning, and localization factors. Localization, one of the most essential factors of navigation, is a crucial requirement for a mobile robot because it needs the capability to localize itself in the environment. Global Positioning Systems (GPSs) are commonly used for outdoor mobile robot localization tasks. However, various environmental circumstances, such as high-rise buildings and trees, affect GPS signal quality, which leads to reduced precision or complete signal blockage. This study proposes a visual-based localization system for outdoor mobile robots in crowded urban environments. The proposed system comprises three steps. The first step is to detect the text in urban areas using the “Efficient and Accurate Scene Text Detector (EAST)” algorithm. Then, EasyOCR was applied to the detected text for the recognition phase to extract text from images that were obtained from EAST. The results from text detection and recognition algorithms were enhanced by applying post-processing and word similarity algorithms. In the second step, once the text detection and recognition process is completed, the recognized word (label/tag) is sent to the Places API in order to return the recognized word’s coordinates that are passed within the specified radius. Parallely, points of interest (POI) data are collected for a defined area by a certain radius while the robot has an accurate internet connection. The proposed system was tested in three distinct urban areas by creating five scenarios under different lighting conditions, such as morning and evening, using the outdoor delivery robot utilized in this study. In the case studies, it has been shown that the proposed system provides a low error of around 4 m for localization tasks. Compared to existing works, the proposed system consistently outperforms all other approaches using just one sensor. The results indicate the efficacy of the proposed system for localization tasks in environments where GPS signals are limited or completely blocked.
Improving Fall Classification Accuracy of Multi-Input Models Using Three-Axis Accelerometer and Heart Rate Variability Data
Authors: Kim Seunghui , Ko Jae Eun , Baek Seungbin , Kim Daechang , Kim Sungmin
Published: February 2025

Reduced body movement and weakened musculoskeletal function as a result of aging increase the risk of falls and serious physical injuries requiring medical attention. To solve this problem, a fall prevention algorithm using an acceleration sensor has been developed, and research is being conducted to enable continuous monitoring using a Holter electrocardiograph. In this study, we implemented a multi-input model that can detect and classify movements, including falls, utilizing the baroreflex characteristics of the heart’s potential energy changes due to movement, measured with an electrocardiogram with a three-axis acceleration sensor and a Holter electrocardiograph. Patterns were identified from the various movement characteristics of acceleration sensor data using a deep learning model consisting of CNN-LSTM, and heart rate variability (HRV) data were analyzed using a wide learning model to provide additional weight values for fall classification. Finally, a multi-input model using wide and deep learning was proposed to enhance the accuracy of fall classification. The results show that the HRV increased in fall case except in two motion types, while it decreased when standing up from a chair, indicating the application of the baroreflex characteristics reflecting the heart’s potential energy. Compared to the classification model using conventional HRV and ACC, a higher accuracy was achieved in the multi-input model using ACC-HRV data, and a precision, recall, and F1 score of 0.91 was measured, indicating improved performance. This is expected to have a positive impact on fall prevention by improving the accuracy of fall classification in the elderly for 15 different movements.
Spatial Distribution Characteristics, Source Tracing with Cadmium Isotopes, and a Risk Assessment of Heavy Metals in Soils in the Metal Mining Area of the Qinling Mountains, Central China
Authors: Feng Juan , Ai Hao , Li Hua , Lu Runfeng , Cheng Xing , Chen Qingmin
Published: February 2025

The Qinling Mountains in central China are rich in polymetallic mineralizations (e.g., Pb-Zn-Au deposits), and historic mining has resulted in large amounts of heavy metals being released into the environment. Thus, it is important to evaluate the ecological risk triggered by historic mining at this location. In this work, a gold mine was investigated as a case study to better understand the health risks present in the Qinling Mountains. To address this issue, a total of 84 soil samples and 23 surface water samples were collected from the gold mining district. Major and trace elements in soils, coupled with the pH and SO4−2 contents in water samples, were analyzed. The multivariate statistical analysis shows that human activities were found to have a significant impact on the levels of heavy metals (e.g., As, Hg, and Cd), pH, and SO4−2 in the soil within the study area, and the coefficient of variation for all indicators falls within a medium to high range (0.20–2.73). The maximum concentration of Cd can reach as high as 3005 mg·kg−1. The spatial distribution of Cd and its isotope signatures indicate that sedimentation ponds and slag piles are the primary sources of high pollution within the study area, with heavy metal concentrations decreasing gradually as they disperse into the surrounding cultivated areas. The present study confirms that Cd and its isotopes can be directly used to track heavy metal sources over a large area (0.8 km2), and the conclusions drawn could be valuable for future restoration and management efforts. Simultaneously, this approach could offer a novel framework for the management of heavy metal contamination in soils at other metal mining sites.
Impact of Urban Densification on Outdoor Microclimate and Design of Sustainable Public Open Space in Residential Neighborhoods: A Study of Niš, Serbia
Authors: Dinić Branković Milena , Igić Milica , Đekić Jelena , Ljubenović Milica
Published: February 2025

This research examined changes in the microclimatic parameters affecting thermal comfort in three residential settings with various urban forms in the city of Niš, Serbia, that underwent intense post-socialist urban densification. Outdoor microclimate was modeled for summertime conditions in two scenarios, before and after transformation, by using ENVI-met software. The obtained results offer quantitative data on microclimatic conditions in the chosen settings and comparisons between scenarios. Findings revealed significant variations in the transformed scenarios, with distinct patterns in specific open spaces: a single mid-rise development forming a square in a high-rise setting showed a wind speed decrease, a daytime mean radiant temperature increase despite lower temperature, and an increase in humidity; extensive low- and mid-rise development in a green high-rise setting generated the highest temperature increase at night, notably reduced daytime and slightly elevated the nighttime mean radiant temperatures, and presented inverted temperature and humidity patterns in urban canyons during the day and night; dispersed densification in low-rise setting manifested the highest wind speed increase, significantly increased the daytime temperature, and mostly raised the nighttime mean radiant temperature. Urban design strategies for sustainable public open space that enhance the resilience of densified areas include using shading from transformed western/southern-edge buildings, avoiding small partly-framed spaces and fragmented grassy surfaces, implementing urban gaps to support nighttime cooling, and framing public open space with trees.
Impact of COP26 and COP27 Events on Investor Attention and Investor Yield to Green Bonds
Authors: Hong Nhung Do , Nguyen Vu Pham , Hong Quy Le , Duc Minh Nguyen Nhu , Hien Hau Nguyen Phan , Yen Nhi Han , Mai Van Trinh
Published: February 2025

Green bonds are a relatively new financial product that offers investors a variety of alternatives. However, many individuals continue to be suspicious about its long-term returns and risks. To clarify this issue, this study employed two global environment events—COP26 and COP27—to influence investor attention and investor yield of green bonds and conventional bonds. The data are collected from 15,188 bonds, including 779 green bonds and 14,409 conventional bonds issued from 2021 to 2023 worldwide. The event study method has been conducted with pre- and post-event data to estimate the impact of green bond issuance before and after COP26 and COP27 on investor returns, as well as the impact of investor attention on investment returns. The research results show that investors should buy shares of companies that issue green bonds after major environmental events to benefit from the higher CAR of these companies. Investors can also use the S&P 1200 index as a measure to assess risk and abnormal returns when making short-term investments in shares of organizations that issue green bonds.
Life Cycle Assessment of a Composite Prototype Battery Enclosure for Electric Vehicles
Authors: De Sio Paolo , Gaito Marica , Esperto Vitantonio , Cozzolino Ersilia , Astarita Antonello , Tucci Fausto
Published: February 2025

The use of lightweight components in automobiles started a new chapter in the automotive sector due to the renewable energy and sustainability increasing the overall efficiency of vehicles. As vehicle weight is directly linked to energy consumption, reducing mass through advanced materials can significantly decrease energy usage and emissions over the vehicle’s lifetime. This present study aims to conduct a preliminary life cycle assessment (LCA) of a prototype battery pack manufactured using pultruded composite materials with a volume fraction of 50% glass fibers and a volume fraction of 50% nylon 6 (PA6) matrix by quantifying the CO2 emissions and cumulative energy demand (CED) associated with each stage of the battery pack’s life cycle, encompassing production, usage, and end-of-life recycling. The results of the EuCia Eco Impact Calculator and from the literature reveal that the raw materials extraction and use phases are the most energy-intensive and contribute mainly to the environmental footprint of the battery pack. For a single battery pack for EV, the CED is 13,629.9 MJ, and the CO2 eq emissions during production are 1323.9 kg. These results highlight the need for innovations in material sourcing and design strategies to mitigate these impacts. Moreover, the variations in recycling methods were assessed using a sensitivity analysis to understand how they affect the overall environmental impact of the system. Specifically, shifting from mechanical recycling to pyrolysis results in an increase of 4% to 19% of the total CO2 emissions (kg CO2). Future goals include building a laboratory-scale model based on the prototype described in this paper to compare the environmental impacts considering equal mechanical properties with alternatives currently used in the automotive industry, such as aluminum and steel alloys.
Sustainable Social Innovation as a Solution for Systemic Change and Resilience
Authors: Jareh Alotaibi
Published: February 2025

This study focuses on the importance of social innovation in addressing socioeconomic and environmental challenges, as it fosters systemic change and resilience. This study places social innovations in the context of Sustainable Development Goals (SDGs) and focuses on their potential to create inclusive and sustainable solutions. Using mixed research methods, 400 highly cited articles published between 2014 and 2024 were analyzed. With respect to the results, a thematic analysis identified key mechanisms such as participative governance, stakeholder engagement, and the inclusion of digital technologies as critical success factors. An impact analysis highlighted the important social, environmental, and economic benefits of green innovation and blockchain initiatives. In contrast, a trend analysis revealed the growing alignment between theoretical advances and practical implementations. This analysis also highlighted the importance of adaptability to local contexts, including marginalized groups, and using interdisciplinary approaches.
Bioclimatic Design Guidelines for Design Decision Support to Enhance Residential Building Thermal Performance in Tropical Regions
Authors: Taing Kimnenh , Reiter Sigrid , Han Virak , Leclercq Pierre
Published: February 2025

With the rise of building thermal comfort issues, the Bioclimatic Design Guideline for Cambodia (BDGC) has been developed to help architects make informed decisions during their design process to achieve maximum thermal comfort with minimum energy consumption. This paper aims to investigate the reliability of this guideline as decision support to enhance residential building thermal performance by using two research approaches: usability tests and calibrated thermal performance simulations based on real buildings monitoring and simulations using DesignBuilder. Five groups of architects and students in architectural engineering participated in the usability test to redesign two common typologies of single-family homes with weak thermal performance by using bioclimatic design guidelines, such as orientation, improved ventilation, shading, and green rood, to enhance their comfort level. The simulation shows that, by applying bioclimatic design strategies, the indoor temperature in the base case house can be lower from 2 to 4 °C. Various benefits are identified from the integration of the BDGC during the design process for improving residential building design. Moreover, the proposed methodology can be applied to develop and validate bioclimatic guidelines in other regions and various countries worldwide.
Towards Clean Energy Transition: An Exploratory Case Study from Rural Egypt
Authors: Abouaiana Ahmed , Battisti Alessandra
Published: February 2025

Rural areas are ideal for renewable energy facilities, supporting sustainable development and energy transition. Egypt aims to reduce greenhouse gas emissions in the electricity sector by 37% and energy consumption by 17% by 2030. Rural Egypt, hosting two-thirds of the population and building stock, consumes one-third of the total electricity. Thus, this paper provides an exploratory study to diagnose and benchmark the energy-use intensity of rural buildings and quantify the correlation between residential electricity consumption, built environment elements, and socio-economic factors, in addition to promoting techno-economic assessments of renewable energy from photovoltaic panels in rural Egypt, supporting national policies amid rapid rural development. The study utilized different analytical and field methods and statistical analyses. A typical agriculture-based rural village in the Delta region, northern Egypt, was selected; the built environment, building types, and socio-economic factors were examined. The results revealed a significant correlation between lifestyle, built-up area, household size, and floor numbers with residential buildings’ electricity consumption. The average annual electricity use intensity was benchmarked at 2.5–92.3 kWh/m2 for six non-residential building typologies and at 22 kWh/m2 and 6.67 kWh/dwelling for residential buildings. Under current regulations, rooftop solar panels can generate electricity significantly, but are not profitable. Eventually, insights for policymakers to inform energy transition policies and national initiatives for rural regeneration were provided. The research focused on a local context, but the methodology can be applied to rural settlements in similar contexts.
Resolving the Open Problem by Proving a Conjecture on the Inverse Mostar Index for c-Cyclic Graphs
Authors: Alex Liju , Das Kinkar Chandra
Published: February 2025

Inverse topological index problems involve determining whether a graph exists with a given integer as its topological index. One such index, the Mostar index, Mo(G), is defined as Mo(G)=∑uv∈E(G)|nu(e|G)−nv(e|G)|, where nu(e|G) and nv(e|G) represent the number of vertices closer to vertex u than v and closer to v than u, respectively, for an edge e=uv. The inverse Mostar index problem has gained significant attention recently. In their work, Alizadeh et al. [Solving the Mostar index inverse problem, J. Math. Chem. 62 (5) (2024) 1079–1093] proposed the following open problem: “Which nonnegative integers can be realized as Mostar indices of c-cyclic graphs, for a given positive integer c?”. Subsequently, one of the present authors [On the inverse Mostar index problem for molecular graphs, Trans. Comb. 14 (1) (2024) 65–77] conjectured that, except for finitely many positive integers, all other positive integers can be realized as the Mostar index of a c-cyclic graph, where c≥3. In this paper, we address the inverse Mostar index problem for c-cyclic graphs. Specifically, we construct infinitely many families of symmetric c-cyclic structures, thereby demonstrating a solution to the inverse Mostar index problem using an infinite family of such symmetric structures. By providing a comprehensive proof of the conjecture, we fully resolve this longstanding open problem.
Disentangling Multiannual Air Quality Profiles Aided by Self-Organizing Map and Positive Matrix Factorization
Authors: Fornasaro Stefano , Astel Aleksander , Barbieri Pierluigi , Licen Sabina
Published: February 2025

The evaluation of air pollution is a critical concern due to its potential severe impacts on human health. Currently, vast quantities of data are collected at high frequencies, and researchers must navigate multiannual, multisite datasets trying to identify possible pollutant sources while addressing the presence of noise and sparse missing data. To address this challenge, multivariate data analysis is widely used with an increasing interest in neural networks and deep learning networks along with well-established chemometrics methods and receptor models. Here, we report a combined approach involving the Self-Organizing Map (SOM) algorithm, Hierarchical Clustering Analysis (HCA), and Positive Matrix Factorization (PMF) to disentangle multiannual, multisite data in a single elaboration without previously separating the sites and years. The approach proved to be valid, allowing us to detect the site peculiarities in terms of pollutant sources, the variation in pollutant profiles during years and the outliers, affording a reliable interpretation.
Breaking Barriers: Candidalysin Disrupts Epithelial Integrity and Induces Inflammation in a Gut-on-Chip Model
Authors: Morelli Moran , Queiroz Karla
Published: February 2025

Candida albicans is an opportunistic pathogenic yeast commonly found in the gastrointestinal tract of healthy humans. Under certain conditions, it can become invasive and cause life-threatening systemic infections. One mechanism used by C.albicans to breach the epithelial barrier is the secretion of candidalysin, a cytolytic peptide toxin. Candidalysin damages epithelial membranes and activates the innate immune response, making it key to C.albicans’ pathogenicity and a promising therapeutic target. Although candidalysin mediates C. albicans translocation through intestinal layers, its impact on epithelial responses is not fully understood. This study aims to characterize this response and develop scalable, quantitative methodologies to assess candidalysin’s toxicological effects using gut-on-chip models. We used the OrganoPlate® platform to expose Caco-2 tubules to candidalysin and evaluated their response with trans-epithelial electrical resistance (TEER), protein detection, and immunostaining. We then validated our findings in a proof-of-concept experiment using human intestinal organoid tubules. Candidalysin impaired barrier integrity, induced actin remodeling, and increased cell permeability. It also induced the release of LDH, cytokines, and the antimicrobial peptide LL37, suggesting cellular damage, inflammation, and antimicrobial activity. This study strengthens our understanding of candidalysin’s role in C. albicans pathogenesis and suggests new therapeutic strategies targeting this toxin. Moreover, patient-derived organoids show promise for capturing patient heterogeneity and developing personalized treatments.
Criteria for Establishing Priorities in Sidewalk Maintenance When Using Multi-Criteria Analysis in Order to Achieve Inclusive Mobility
Authors: Bashiri Samaneh , Raffini Luca , Cepolina Elvezia Maria
Published: February 2025

To create an inclusive city, it is essential to have accessible pedestrian infrastructure. The accessibility of pedestrian infrastructure is ensured through the proper maintenance of sidewalks. When resources are limited, it is necessary to prioritize sidewalks by identifying those in the most critical condition, and this is often achieved through multi-criteria analyses. This paper proposed an analysis of the criteria to be considered, which include not only pavement distresses but also the importance of the sidewalk in connecting various parts of the city and ensuring accessibility to significant places for all, including vulnerable users. Methodologies for evaluating a sidewalk in relation to these criteria were proposed and an application of these methods to a simple case study in Genoa was presented. In this context, the evaluation of the criteria weights was performed using subjective and objective methods. The weights calculated with the two methods generated the same priorities. All the experts interviewed agreed with the proposed set of criteria and two experts suggested considering a new criterion relating to the level of danger of the context in which a pavement is located.
Neuropathogenesis of Old World Alphaviruses: Considerations for the Development of Medical Countermeasures
Authors: Lantz Alyssa M. , Baxter Victoria K.
Published: February 2025

Chikungunya virus (CHIKV) and other alphaviruses that primarily induce arthritogenic disease in humans, known as “Old World” alphaviruses, present an emerging public health concern as geographic ranges of mosquito vectors expand due to climate change. While a vaccine against CHIKV has recently been approved by several countries in North America and Europe, access to effective preventative countermeasures against disease induced by Old World alphaviruses remains elusive for the most vulnerable populations. Furthermore, treatment options continue to be limited to supportive care. Atypical neurological disease manifestations caused by Old World alphaviruses, which make up as many as 25% of the cases in some CHIKV outbreaks, present special challenges when considering strategies for developing effective countermeasures. This review focuses on Old World alphaviruses, specifically CHIKV, Ross River virus, O’nyoug-nyoug virus, and Mayaro virus, concentrating on the atypical neurological disease manifestations they may cause. Our current understanding of Old World alphavirus neuropathogenesis, gained from human cases and preclinical animal models, is discussed, including viral and host factors’ roles in disease development. The current state of alphavirus preventatives and treatments, both virus-targeting and host-directed therapies, is then summarized and discussed in the context of addressing neurological disease induced by Old World alphaviruses.
The Effect of pH on Aniline Removal from Water Using Hydrophobic and Ion-Exchange Membranes
Authors: Filian Karla , Mendez-Ruiz Jonathan I. , Garces Daniel , Reveychuk Kateryna , Ma Lingshan , Melendez Jesus R. , Díaz-Mendoza Claudia , Cornelissen Emile , Valverde-Armas Priscila E. , Gutierrez Leo
Published: February 2025

The presence of aniline, a toxic aromatic amine, has been recorded in different industrial wastewaters. This study aims to investigate the transport of charged and neutral aniline species in aqueous solutions through hydrophobic and ion-exchange membranes (IEMs). Hydrophobic polyoctylmethylsiloxane (POMS) and polydimethylsiloxane (PDMS) membranes and cationic (CEMs) and anionic (AEMs) exchange membranes were tested using diffusion cells and electrodialysis (ED). Diffusion experiments showed that neutral aniline removal reached 90% with POMS and 100% with PDMS due to the concentration gradient between feed (pH = 10) and receiving (pH = 3) solutions. For IEMs, neutral aniline exhibited a faster transport than charged species, with neutral-to-charged transport ratios of 6.6:1 for AEMs and 3.2:1 for CEMs, type I. During ED experiments, an external electric potential increased the charged aniline transport, achieving higher initial fluxes (124.7 mmol·m2·h−1 at pH 4) compared to neutral aniline (43.6 and 53.2 mmol·m2·h−1 for AEMs and CEMs, type I). ED also demonstrated that charged aniline can be removed up to 97% using IEMs. These findings demonstrate the effectiveness of hydrophobic and IEMs in removing aniline, providing insights into its transport mechanism, contributing to the optimization of membrane technologies in treating industrial wastewater effluents, and environmental sustainability.
Control Effect of a Novel Polyurethane (W-OH) on Colluvial Deposit Slope Erosion in the Benggang Area of Southern China
Authors: Zhang Zhenggang , Chen Yuyang , Zhu Zhehao , Meng Ying , Wu Wei , Zhou Yiyang , Zhang Yue , Lin Jinshi , Huang Yanhe , Jiang Fangshi
Published: February 2025

A novel polyurethane (W-OH), namely an eco-friendly hydrophilic polymer, has been widely applied in the field of soil erosion. However, recent research has not revealed the process and mechanisms through which W-OH application influences the soil detachment by concentrated overland flow (hereinafter referred to as soil detachment). In this study, the effects of the W-OH concentration on the physical and mechanical properties and the detachment capacity of colluvial deposit slope soil were investigated, and the impact of the relationship between the flow discharge and the W-OH concentration on the soil detachment capacity was examined under the experimental conditions. The results indicated that W-OH application significantly increased the large-particle content in the soil samples, enhanced the strength properties of the soil samples, reduced their separation capacity, and increased their stability. The structural equation modelling results revealed that W-OH application influences the soil detachment capacity primarily by affecting the shear strength, which exerts a significant negative effect on the detachment capacity (path coefficient = −0.57, p < 0.001). The soil detachment capacity prediction equation, which is based on the flow discharge and W-OH concentration, exhibited satisfactory accuracy (Nash–Sutcliffe efficiency (NSE) = 0.964) and can be used to predict the soil detachment capacity with high precision under similar experimental conditions. In addition, at a W-OH concentration above 1.53%, the impact on the soil detachment capacity is greater than that of the flow discharge. This study focused on investigating the process and mechanisms through which W-OH application reduces soil erosion on colluvial deposit slopes, thereby providing reference data for the management of Benggang erosion.
Analytical and Computational Methods for Optimizing Gabion-Pile Coastal Structures
Authors: Ferren Vinsensia , Magdalena Ikha , Saengsupavanich Cherdvong , Dhiya Muhammad Nabil Farras , Sanitwong-Na-Ayutthaya Sarinya , Chandrasekaran Srinivasan , Solekhudin Imam , Azis Mohammad Ivan , Widowati
Published: February 2025

Wooden or bamboo fences, commonly used for coastal protection, have limited effectiveness in reducing wave height due to their porous structure, which provides only moderate wave damping. To address this issue, our study proposes a modification that retains these fences while strategically incorporating submerged rocks, similar to gabions, to exploit friction and achieve significant wave height reduction. We employed a mathematical model based on modified Shallow Water Equations to investigate the wave attenuation. A key measure, the wave transmission coefficient (Kt), for quantifying wave height reduction was determined using both analytical and numerical methods. The numerical Kt obtained from simulations was 0.2831, whereas the analytically computed Kt value was 0.2622, which indicates a reduction of over 70% in the initial wave amplitude due to the combined effect of submerged rocks and wooden fences. These results, which align closely with experimental data, validate the credibility of our approach. A detailed sensitivity analysis illustrates the effectiveness of both wooden fences and submerged rocks in attenuating wave height, which depends on structure dimensions and friction coefficients. Optimization studies present various optimal structures, underscoring the critical role of the structure’s friction coefficient in minimizing the wave transmission coefficient, and recommend the use of rough materials for optimal wave height reduction. In summary, our paper offers a robust exploration of an innovative coastal protection strategy that integrates wooden fences and rocks. The validated model, supported by analytical, numerical, and experimental evidence, has the potential to provide practical insights for coastal engineers seeking efficient wave attenuation solutions.
A New Model for Quantifying the Impact of the Social Economy on the Sustainability of Water Resources
Authors: Georgescu Lucian Puiu , Ionescu Romeo-Victor , Antohi Valentin-Marian , Zlati Monica Laura , Iticescu Catalina
Published: February 2025

The importance of sustainable use of water sources in the context of social economy development is a topic of interest in the context of current regional and global challenges. The main objective of this study is to analyze the disparity of correlations between sector-specific social economy indicators and their impact on water sources at the EU27 level. The methods used are meta-analysis, followed by the substantiation of working hypotheses based on this, as well as database design for modeling and the use of correlational and econometric statistical methods. The novelty of this approach is the definition and validation of a new model, on the basis of which we formulate viable public policy proposals to support the evolution of the green social economy. The present study is characterized by its complexity (a very large number of statistical variables analyzed) and dynamic approach. The main conclusion of our research is that even with sustained efforts on environmental protection, the European social economy’s fluctuating results tend to overshadow environmental objectives, even at the risk of exceeding budget allocations in the field.
Biosphere-centric Model of Cultural and Natural Heritage as a Tool for Sustainable Development of Countries and the Planet: from Traditions to Innovations of the Digital Age
Authors:   Section of Synthesis of Arts of the Creative Union of Artists of Russia, Laureate of the European Academy of Sciences Award, Garber N. M.
Published: February 2025

The UNESCO Convention Concerning the Protection of the World Cultural and Natural
Heritage of 1972, ratifi ed by the majority of countries of the Planet, is the fi rst global
document of humanity considering the noosphere of the cultural heritage of humanity as
a continuation of Earth's biosphere. I built the components of the Convention according to
Maslow's motivation levels and in accordance with the tasks of sustainable development of
the Planet, turning it into an instrument of cultural diplomacy that ensures cooperation of the
countries of the Planet in the productive development of the world ocean of cultures from
traditions to innovations of the noosphere of the XXI century. Under the Eurasian approach,
the article analyzes Spanish and Tibetan models of thinking when applied to the problem
of sustainable development of cultural brands of the countries of the digital age. Based on
the cultural parallel of “The Gypsies” by Pushkin and “Carmen” by Mérimée, an example of
a conscious rethinking of the methods of Eurasian cultural geopolitics as an instrument of
cooperation of cultures in the development of thinking for the sustainable development
of the Planet is created. The article is illustrated with the author's internationally exhibited
visual works created with the usage of artificial intelligence, demonstrating the innovative
creative potential of cultural diplomacy in the digital age.
New media as a subject of formation of youth value ideals
Authors:   Department of Journalism, Moscow University for the Humanities, Akimova Elena Mikhailovna , Ivanova Olga Petrovna ,   Department of Journalism, Moscow University for the Humanities
Published: February 2025

The authors explore the role of new media in the formation of value ideals of young people,
analyze the factors that make new media a key tool for infl uencing the consciousness
of the younger generation, and reveal the importance of social networks, blogs, and
platforms in promoting such values as family, work, patriotism, and education. The formation
of value ideals of the youth in modern Russia has acquired particular relevance,
which is due to a number of factors. The most important among them are the accelerating
profound changes in the socio-economic, socio-political, and socio-cultural spheres
of society, which are of a crisis nature and cover Russia and the entire world community.
Second (2nd) Trimester Kidney Function and Adverse Pregnancy Outcomes among Patients with Lupus
Authors: Lucas Anika M. , Miller Cameron , Eudy Amanda , Myers Rachel , Wyatt Christina M. , Wheeler Sarahn , Petri Michelle , Fischer-Betz Rebecca , Mokbel Abir , Nalli Cecilia , Andreoli Laura , Tincani Angela , Molad Yair , Balevic Stephen , Gladman Dafna D. , Urowitz Murray , Clowse Megan E.B.
Published: February 2025

Background:

Kidney function is not routinely assessed during pregnancy. Several studies have proposed antepartum kidney function, particularly 2nd trimester kidney function, as a potential predictor of adverse pregnancy outcomes. It has been previously established that patients with Systemic Lupus Erythematosus are at increased risk for adverse pregnancy outcomes. The association between 2nd trimester kidney function and adverse pregnancy outcomes has not been evaluated in diverse patient populations, particularly among patients with high obstetrical risk.

Methods:

In this observational study of pregnant patients with lupus in North America and Europe from 1995-2017, we used 2nd trimester creatinine and the estimated glomerular filtration rate (eGFR) to model the log odds of preeclampsia, preterm birth, low birthweight, fetal loss, and a composite of those outcomes. We incorporated these measures into a regression setting using fractional polynomials, and we further examined discrete formulations of eGFR.

Results:

Among 684 pregnancies in patients with lupus, the mean 2nd trimester creatinine was 0.63mg/dL ± SD 0.26 and the median value 0.60 (IQR 0.50-0.70). At least 1 in 3 patients in this combined cohort experienced an adverse outcome. Mixtures of U-shaped and linear relationships between continuous kidney function and the log odds of adverse pregnancy outcomes were observed. Stratifying the cohort by diagnosis of lupus nephritis (active or in remission) or without diagnosis of nephritis, we found differences in the relationship between kidney function and adverse outcomes.

Conclusions:

We observed high rates of adverse pregnancy outcomes in our diverse patient population comprised of pregnant patients with lupus with and without lupus nephritis. We identified complex relationships between 2nd trimester kidney function and adverse pregnancy outcomes that differed by the outcome and diagnosis of lupus nephritis.