Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (124,302)

Search Parameters:
Keywords = global

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
21 pages, 1147 KiB  
Review
Recent Advances in Developing Cell-Free Protein Synthesis Biosensors for Medical Diagnostics and Environmental Monitoring
by Tyler P. Green, Joseph P. Talley and Bradley C. Bundy
Biosensors 2025, 15(8), 499; https://doi.org/10.3390/bios15080499 (registering DOI) - 3 Aug 2025
Abstract
Cell-free biosensors harness the selectivity of cellular machinery without living cells’ constraints, offering advantages in environmental monitoring, medical diagnostics, and biotechnological applications. This review examines recent advances in cell-free biosensor development, highlighting their ability to detect diverse analytes including heavy metals, organic pollutants, [...] Read more.
Cell-free biosensors harness the selectivity of cellular machinery without living cells’ constraints, offering advantages in environmental monitoring, medical diagnostics, and biotechnological applications. This review examines recent advances in cell-free biosensor development, highlighting their ability to detect diverse analytes including heavy metals, organic pollutants, pathogens, and clinical biomarkers with high sensitivity and specificity. We analyze technological innovations in cell-free protein synthesis optimization, preservation strategies, and field deployment methods that have enhanced sensitivity, and practical applicability. The integration of synthetic biology approaches has enabled complex signal processing, multiplexed detection, and novel sensor designs including riboswitches, split reporter systems, and metabolic sensing modules. Emerging materials such as supported lipid bilayers, hydrogels, and artificial cells are expanding biosensor capabilities through microcompartmentalization and electronic integration. Despite significant progress, challenges remain in standardization, sample interference mitigation, and cost reduction. Future opportunities include smartphone integration, enhanced preservation methods, and hybrid sensing platforms. Cell-free biosensors hold particular promise for point-of-care diagnostics in resource-limited settings, environmental monitoring applications, and food safety testing, representing essential tools for addressing global challenges in healthcare, environmental protection, and biosecurity. Full article
Show Figures

Figure 1

22 pages, 5283 KiB  
Article
Transcriptome Analysis Reveals Candidate Pathways and Genes Involved in Wheat (Triticum aestivum L.) Response to Zinc Deficiency
by Shoujing Zhu, Shiqi Zhang, Wen Wang, Nengbing Hu and Wenjuan Shi
Biology 2025, 14(8), 985; https://doi.org/10.3390/biology14080985 (registering DOI) - 2 Aug 2025
Abstract
Zinc (Zn) deficiency poses a major global health challenge, and wheat grains generally contain low Zn concentrations. In this study, the wheat cultivar ‘Zhongmai 175’ was identified as zinc-efficient. Hydroponic experiments demonstrated that Zn deficiency induced the secretion of oxalic acid and malic [...] Read more.
Zinc (Zn) deficiency poses a major global health challenge, and wheat grains generally contain low Zn concentrations. In this study, the wheat cultivar ‘Zhongmai 175’ was identified as zinc-efficient. Hydroponic experiments demonstrated that Zn deficiency induced the secretion of oxalic acid and malic acid in root exudates and significantly increased total root length in ‘Zhongmai 175’. To elucidate the underlying regulatory mechanisms, transcriptome profiling via RNA sequencing was conducted under Zn-deficient conditions. A total of 2287 and 1935 differentially expressed genes (DEGs) were identified in roots and shoots, respectively. Gene Ontology enrichment analysis revealed that these DEGs were primarily associated with Zn ion transport, homeostasis, transmembrane transport, and hormone signaling. Key DEGs belonged to gene families including VIT, NAS, DMAS, ZIP, tDT, HMA, and NAAT. KEGG pathway analysis indicated that phenylpropanoid biosynthesis, particularly lignin synthesis genes, was significantly downregulated in Zn-deficient roots. In shoots, cysteine and methionine metabolism, along with plant hormone signal transduction, were the most enriched pathways. Notably, most DEGs in shoots were associated with the biosynthesis of phytosiderophores (MAs, NA) and ethylene. Overall, genes involved in Zn ion transport, phytosiderophore biosynthesis, dicarboxylate transport, and ethylene biosynthesis appear to play central roles in wheat’s adaptive response to Zn deficiency. These findings provide a valuable foundation for understanding the molecular basis of Zn efficiency in wheat and for breeding Zn-enriched varieties. Full article
Show Figures

Figure 1

18 pages, 4468 KiB  
Article
Proteomic and Functional Analysis Reveals Temperature-Driven Immune Evasion Strategies of Streptococcus iniae in Yellowfin Seabream (Acanthopagrus latus)
by Yanjian Yang, Guanrong Zhang, Ruilong Xu, Yiyang Deng, Zequan Mo, Yanwei Li and Xueming Dan
Biology 2025, 14(8), 986; https://doi.org/10.3390/biology14080986 (registering DOI) - 2 Aug 2025
Abstract
Streptococcus iniae (S. iniae) is a globally significant aquatic pathogen responsible for severe economic losses in aquaculture. While the S. iniae infection often exhibits distinct seasonal patterns strongly correlated with water temperature, there is limited knowledge regarding the temperature-dependent immune evasion [...] Read more.
Streptococcus iniae (S. iniae) is a globally significant aquatic pathogen responsible for severe economic losses in aquaculture. While the S. iniae infection often exhibits distinct seasonal patterns strongly correlated with water temperature, there is limited knowledge regarding the temperature-dependent immune evasion strategies of S. iniae. Our results demonstrated a striking temperature-dependent virulence phenotype, with significantly higher A. latus mortality rates observed at high temperature (HT, 33 °C) compared to low temperature (LT, 23 °C). Proteomic analysis revealed temperature-dependent upregulation of key virulence factors, including streptolysin S-related proteins (SagG, SagH), antioxidant-related proteins (SodA), and multiple capsular polysaccharide (cps) synthesis proteins (cpsD, cpsH, cpsL, cpsY). Flow cytometry analysis showed that HT infection significantly reduced the percentage of lymphocyte and myeloid cell populations in the head kidney leukocytes of A. latus, which was associated with elevated caspase-3/7 expression and increased apoptosis. In addition, HT infection significantly inhibited the release of reactive oxygen species (ROS) but not nitric oxide (NO) production. Using S. iniae cps-deficient mutant, Δcps, we demonstrated that the cps is essential for temperature-dependent phagocytosis resistance in S. iniae, as phagocytic activity against Δcps remained unchanged across temperatures, while NS-1 showed significantly reduced uptake at HT. These findings provide new insights into the immune evasion of S. iniae under thermal regulation, deepening our understanding of the thermal adaptation of aquatic bacterial pathogens. Full article
(This article belongs to the Special Issue Aquatic Economic Animal Breeding and Healthy Farming)
Show Figures

Figure 1

42 pages, 5770 KiB  
Review
Echoes from Below: A Systematic Review of Cement Bond Log Innovations Through Global Patent Analysis
by Lim Shing Wang, Muhammad Haarith Firdaous and Pg Emeroylariffion Abas
Inventions 2025, 10(4), 67; https://doi.org/10.3390/inventions10040067 (registering DOI) - 2 Aug 2025
Abstract
Maintaining well integrity is essential in the oil and gas industry to prevent environmental hazards, operational risks, and economic losses. Cement bond log (CBL) tools are essential in evaluating cement bonding and ensuring wellbore stability. This study presents a patent landscape review of [...] Read more.
Maintaining well integrity is essential in the oil and gas industry to prevent environmental hazards, operational risks, and economic losses. Cement bond log (CBL) tools are essential in evaluating cement bonding and ensuring wellbore stability. This study presents a patent landscape review of CBL technologies, based on 3473 patent documents from the Lens.org database. After eliminating duplicates and irrelevant entries, 167 granted patents were selected for in-depth analysis. These were categorized by technology type (wave, electrical, radiation, neutron, and other tools) and by material focus (formation, casing, cement, and borehole fluid). The findings reveal a dominant focus on formation evaluation (59.9%) and a growing reliance on wave-based (22.2%) and other advanced tools (25.1%), indicating a shift toward high-precision diagnostics. Geographically, 75% of granted patents were filed through the U.S. Patent and Trademark Office, and 97.6% were held by companies, underscoring the dominance of corporate innovation and the minimal presence of academia and individuals. The review also identifies notable patents that reflect significant technical innovations and discusses their role in advancing diagnostic capabilities. These insights emphasize the need for broader collaboration and targeted research to advance well integrity technologies in line with industry goals for operational performance and safety. Full article
Show Figures

Figure 1

14 pages, 9090 KiB  
Article
Effects of Climate Change on the Global Distribution of Trachypteris picta (Coleoptera: Buprestidae)
by Huafeng Liu, Shuangyi Wang, Yunchun Li, Shuangmei Ding, Aimin Shi, Ding Yang and Zhonghua Wei
Insects 2025, 16(8), 802; https://doi.org/10.3390/insects16080802 (registering DOI) - 2 Aug 2025
Abstract
Trachypteris picta (Pallas, 1773) is a significant pest that can cause serious damage to poplars and willows. To assess the impact of climate change on the suitable habitats of T. picta, this study conducted a comparative analysis of its global suitable habitats [...] Read more.
Trachypteris picta (Pallas, 1773) is a significant pest that can cause serious damage to poplars and willows. To assess the impact of climate change on the suitable habitats of T. picta, this study conducted a comparative analysis of its global suitable habitats using climatic factors, global land use type, and global vegetation from different periods, in combination with the maximum entropy (MaxEnt) model. The results indicate that the annual mean temperature (Bio01), mean temperature of the coldest quarter (Bio11), precipitation of the coldest quarter (Bio19), and isothermality (Bio03) are the four most important climate variables determining the distribution of T. picta. Under the current climate conditions, the highly suitable areas are primarily located in southern Europe, covering an area of 2.22 × 106 km2. Under future climate scenarios, the suitable habitat for T. picta is expected to expand and shift towards higher latitudes. In the 2050s, the SSP5-8.5 scenario has the largest suitable area compared to other scenarios, while the SSP2-4.5 scenario has the largest suitable area in the 2090s. In addition, the centroids of the total suitable areas are expected to shift toward higher latitudes under future climate conditions. The results of this study provide valuable data for the monitoring, control, and management of this pest. Full article
(This article belongs to the Section Insect Pest and Vector Management)
Show Figures

Figure 1

10 pages, 237 KiB  
Article
Current Status of Mental Health in Mexico City
by Erika Sanchez, Humberto Nicolini, Jorge Villatoro, Marycarmen Bustos, María Elena Medina-Mora, Paola Mejía-Ortiz, Beatriz Robles, Diego Mondragón, Gema Ibarra, Daniela Meza and Alma Delia Genis-Mendoza
Int. J. Environ. Res. Public Health 2025, 22(8), 1217; https://doi.org/10.3390/ijerph22081217 (registering DOI) - 2 Aug 2025
Abstract
There is limited information on the prevalence of mental health symptoms among the population of Mexico City. To provide an update and determine the prevalence of symptoms associated with various disorders in the city, a modified version of the “Screener Questionnaire” was used, [...] Read more.
There is limited information on the prevalence of mental health symptoms among the population of Mexico City. To provide an update and determine the prevalence of symptoms associated with various disorders in the city, a modified version of the “Screener Questionnaire” was used, the same instrument employed in the National Survey on Drug, Alcohol, and Tobacco Use (ENCODAT) 2016–2017. Data were collected at PILARES centers in different boroughs of Mexico City. A total of 868 questionnaires on symptoms of psychiatric disorders and the use of drugs, alcohol, and tobacco were completed. The most frequently reported symptoms were anxiety (52.67%), depression (39.34%), and post-traumatic stress disorder (44.57%). Additionally, results showed alcohol use at 15.1%, followed by tobacco (13.6%) and illicit drug use (6.8%). The prevalence of these symptoms was also compared with data from ENCODAT 2016–2017 to observe changes over the years. Full article
29 pages, 30467 KiB  
Article
Clay-Hosted Lithium Exploration in the Wenshan Region of Southeastern Yunnan Province, China, Using Multi-Source Remote Sensing and Structural Interpretation
by Lunxin Feng, Zhifang Zhao, Haiying Yang, Qi Chen, Changbi Yang, Xiao Zhao, Geng Zhang, Xinle Zhang and Xin Dong
Minerals 2025, 15(8), 826; https://doi.org/10.3390/min15080826 (registering DOI) - 2 Aug 2025
Abstract
With the rapid increase in global lithium demand, the exploration of newly discovered lithium in the bauxite of the Wenshan area in southeastern Yunnan has become increasingly important. However, the current research on clay-type lithium in the Wenshan area has primarily focused on [...] Read more.
With the rapid increase in global lithium demand, the exploration of newly discovered lithium in the bauxite of the Wenshan area in southeastern Yunnan has become increasingly important. However, the current research on clay-type lithium in the Wenshan area has primarily focused on local exploration, and large-scale predictive metallogenic studies remain limited. To address this, this study utilized multi-source remote sensing data from ZY1-02D and ASTER, combined with ALOS 12.5 m DEM and Sentinel-2 imagery, to carry out remote sensing mineral identification, structural interpretation, and prospectivity mapping for clay-type lithium in the Wenshan area. This study indicates that clay-type lithium in the Wenshan area is controlled by NW, EW, and NE linear structures and are mainly distributed in the region from north of the Wenshan–Malipo fault to south of the Guangnan–Funing fault. High-value areas of iron-rich silicates and iron–magnesium minerals revealed by ASTER data indicate lithium enrichment, while montmorillonite and cookeite identification by ZY1-02D have strong indicative significance for lithium. Field verification samples show the highest Li2O content reaching 11,150 μg/g, with six samples meeting the comprehensive utilization criteria for lithium in bauxite (Li2O ≥ 500 μg/g) and also showing an enrichment of rare earth elements (REEs) and gallium (Ga). By integrating stratigraphic, structural, mineral identification, geochemical characteristics, and field verification data, ten mineral exploration target areas were delineated. This study validates the effectiveness of remote sensing technology in the exploration of clay-type lithium and provides an applicable workflow for similar environments worldwide. Full article
Show Figures

Figure 1

27 pages, 7899 KiB  
Article
Digital Enablers of Sustainability: Insights from Sustainable Development Goals (SDGs) Research Mapping
by Jeongmi Ga, Jaewoo Bong, Myeongjun Yu and Minjung Kwak
Sustainability 2025, 17(15), 7031; https://doi.org/10.3390/su17157031 (registering DOI) - 2 Aug 2025
Abstract
As the global emphasis on sustainable development intensifies, the integration of digital technologies (DTs) into efforts to address the Sustainable Development Goals (SDGs) has gained increasing attention. However, existing research on the link between the SDGs and DTs remains fragmented and lacks a [...] Read more.
As the global emphasis on sustainable development intensifies, the integration of digital technologies (DTs) into efforts to address the Sustainable Development Goals (SDGs) has gained increasing attention. However, existing research on the link between the SDGs and DTs remains fragmented and lacks a comprehensive perspective on their interconnections. We aimed to address this gap by conducting a large-scale bibliometric analysis based on Elsevier’s SDG research mapping technique. Drawing on approximately 1.17 million publications related to both the 17 SDGs and 11 representative DTs, we explored research trends in the SDG–DT association, identified DTs that are most frequently tied to specific SDGs, and uncovered emerging areas of research within this interdisciplinary domain. Our results highlight the rapid expansion in the volume and variety of SDG–DT studies. Our findings shed light on the widespread relevance of artificial intelligence and robotics, the goal-specific applications of technologies such as 3D printing, cloud computing, drones, and extended reality, as well as the growing visibility of emerging technologies such as digital twins and blockchain. These findings offer valuable insights for researchers, policymakers, and industry leaders aiming to strategically harness DTs to support sustainable development and accelerate progress toward achieving the SDGs. Full article
Show Figures

Figure 1

21 pages, 2077 KiB  
Article
Quantitative Risk Assessment of Liquefied Natural Gas Bunkering Hoses in Maritime Operations: A Case of Shenzhen Port
by Yimiao Gu, Yanmin Zeng and Hui Shan Loh
J. Mar. Sci. Eng. 2025, 13(8), 1494; https://doi.org/10.3390/jmse13081494 (registering DOI) - 2 Aug 2025
Abstract
The widespread adoption of liquefied natural gas (LNG) as a marine fuel has driven the development of LNG bunkering operations in global ports. Major international hubs, such as Shenzhen Port, have implemented ship-to-ship (STS) bunkering practices. However, this process entails unique safety risks, [...] Read more.
The widespread adoption of liquefied natural gas (LNG) as a marine fuel has driven the development of LNG bunkering operations in global ports. Major international hubs, such as Shenzhen Port, have implemented ship-to-ship (STS) bunkering practices. However, this process entails unique safety risks, particularly hazards associated with vapor cloud dispersion caused by bunkering hose releases. This study employs the Phast software developed by DNV to systematically simulate LNG release scenarios during STS operations, integrating real-world meteorological data and storage conditions. The dynamic effects of transfer flow rates, release heights, and release directions on vapor cloud dispersion are quantitatively analyzed under daytime and nighttime conditions. The results demonstrate that transfer flow rate significantly regulates dispersion range, with recommendations to limit the rate below 1500 m3/h and prioritize daytime operations to mitigate risks. Release heights exceeding 10 m significantly amplify dispersion effects, particularly at night (nighttime dispersion area at a height of 20 m is 3.5 times larger than during the daytime). Optimizing release direction effectively suppresses dispersion, with vertically downward releases exhibiting minimal impact. Horizontal releases require avoidance of downwind alignment, and daytime operations are prioritized to reduce lateral dispersion risks. Full article
(This article belongs to the Section Ocean Engineering)
Show Figures

Figure 1

30 pages, 3080 KiB  
Article
Unsupervised Multimodal Community Detection Algorithm in Complex Network Based on Fractal Iteration
by Hui Deng, Yanchao Huang, Jian Wang, Yanmei Hu and Biao Cai
Fractal Fract. 2025, 9(8), 507; https://doi.org/10.3390/fractalfract9080507 (registering DOI) - 2 Aug 2025
Abstract
Community detection in complex networks plays a pivotal role in modern scientific research, including in social network analysis and protein structure analysis. Traditional community detection methods face challenges in integrating heterogeneous multi-source information, capturing global semantic relationships, and adapting to dynamic network evolution. [...] Read more.
Community detection in complex networks plays a pivotal role in modern scientific research, including in social network analysis and protein structure analysis. Traditional community detection methods face challenges in integrating heterogeneous multi-source information, capturing global semantic relationships, and adapting to dynamic network evolution. This paper proposes a novel unsupervised multimodal community detection algorithm (UMM) based on fractal iteration. The core idea is to design a dual-channel encoder that comprehensively considers node semantic features and network topological structures. Initially, node representation vectors are derived from structural information (using feature vectors when available, or singular value decomposition to obtain feature vectors for nodes without attributes). Subsequently, a parameter-free graph convolutional encoder (PFGC) is developed based on fractal iteration principles to extract high-order semantic representations from structural encodings without requiring any training process. Furthermore, a semantic–structural dual-channel encoder (DC-SSE) is designed, which integrates semantic encodings—reduced in dimensionality via UMAP—with structural features extracted by PFGC to obtain the final node embeddings. These embeddings are then clustered using the K-means algorithm to achieve community partitioning. Experimental results demonstrate that the UMM outperforms existing methods on multiple real-world network datasets. Full article
24 pages, 1593 KiB  
Article
Robust Adaptive Multiple Backtracking VBKF for In-Motion Alignment of Low-Cost SINS/GNSS
by Weiwei Lyu, Yingli Wang, Shuanggen Jin, Haocai Huang, Xiaojuan Tian and Jinling Wang
Remote Sens. 2025, 17(15), 2680; https://doi.org/10.3390/rs17152680 (registering DOI) - 2 Aug 2025
Abstract
The low-cost Strapdown Inertial Navigation System (SINS)/Global Navigation Satellite System (GNSS) is widely used in autonomous vehicles for positioning and navigation. Initial alignment is a critical stage for SINS operations, and the alignment time and accuracy directly affect the SINS navigation performance. To [...] Read more.
The low-cost Strapdown Inertial Navigation System (SINS)/Global Navigation Satellite System (GNSS) is widely used in autonomous vehicles for positioning and navigation. Initial alignment is a critical stage for SINS operations, and the alignment time and accuracy directly affect the SINS navigation performance. To address the issue that low-cost SINS/GNSS cannot effectively achieve rapid and high-accuracy alignment in complex environments that contain noise and external interference, an adaptive multiple backtracking robust alignment method is proposed. The sliding window that constructs observation and reference vectors is established, which effectively avoids the accumulation of sensor errors during the full integration process. A new observation vector based on the magnitude matching is then constructed to effectively reduce the effect of outliers on the alignment process. An adaptive multiple backtracking method is designed in which the window size can be dynamically adjusted based on the innovation gradient; thus, the alignment time can be significantly shortened. Furthermore, the modified variational Bayesian Kalman filter (VBKF) that accurately adjusts the measurement noise covariance matrix is proposed, and the Expectation–Maximization (EM) algorithm is employed to refine the prior parameter of the predicted error covariance matrix. Simulation and experimental results demonstrate that the proposed method significantly reduces alignment time and improves alignment accuracy. Taking heading error as the critical evaluation indicator, the proposed method achieves rapid alignment within 120 s and maintains a stable error below 1.2° after 80 s, yielding an improvement of over 63% compared to the backtracking-based Kalman filter (BKF) method and over 57% compared to the fuzzy adaptive KF (FAKF) method. Full article
(This article belongs to the Section Urban Remote Sensing)
14 pages, 265 KiB  
Article
Bovine Leptospirosis: Serology, Isolation, and Risk Factors in Dairy Farms of La Laguna, Mexico
by Alejandra María Pescador-Gutiérrez, Jesús Francisco Chávez-Sánchez, Lucio Galaviz-Silva, Juan José Zarate-Ramos, José Pablo Villarreal-Villarreal, Sergio Eduardo Bernal-García, Uziel Castillo-Velázquez, Rubén Cervantes-Vega and Ramiro Avalos-Ramirez
Life 2025, 15(8), 1224; https://doi.org/10.3390/life15081224 (registering DOI) - 2 Aug 2025
Abstract
Leptospirosis is a globally significant zoonosis affecting animal health, productivity, and the environment. While typically associated with tropical climates, its persistence in semi-arid regions such as La Laguna, Mexico—characterized by low humidity, high temperatures, and limited water sources—remains poorly understood. Although these adverse [...] Read more.
Leptospirosis is a globally significant zoonosis affecting animal health, productivity, and the environment. While typically associated with tropical climates, its persistence in semi-arid regions such as La Laguna, Mexico—characterized by low humidity, high temperatures, and limited water sources—remains poorly understood. Although these adverse environmental conditions theoretically limit the survival of Leptospira, high livestock density and synanthropic reservoirs (e.g., rodents) may compensate, facilitating transmission. In this cross-sectional study, blood sera from 445 dairy cows (28 herds: 12 intensive [MI], 16 semi-intensive [MSI] systems) were analyzed via microscopic agglutination testing (MAT) against 10 pathogenic serovars. Urine samples were cultured for active Leptospira detection. Risk factors were assessed through epidemiological surveys and multivariable analysis. This study revealed an overall apparent seroprevalence of 27.0% (95% CI: 22.8–31.1), with significantly higher rates in MSI (54.1%) versus MI (12.2%) herds (p < 0.001) and an estimated true seroprevalence of 56.3% (95% CI: 50.2–62.1) in MSI and 13.1% (95% CI: 8.5–18.7) in MI herds (p < 0.001). The Sejroe serogroup was isolated from urine in both systems, confirming active circulation. In MI herds, rodent presence (OR: 3.6; 95% CI: 1.6–7.9) was identified as a risk factor for Leptospira seropositivity, while first-trimester abortions (OR:10.1; 95% CI: 4.2–24.2) were significantly associated with infection. In MSI herds, risk factors associated with Leptospira seropositivity included co-occurrence with hens (OR: 2.8; 95% CI: 1.5–5.3) and natural breeding (OR: 2.0; 95% CI: 1.1–3.9), whereas mastitis/agalactiae (OR: 2.8; 95% CI: 1.5–5.2) represented a clinical outcome associated with seropositivity. Despite semi-arid conditions, Leptospira maintains transmission in La Laguna, particularly in semi-intensive systems. The coexistence of adapted (Sejroe) and incidental serogroups underscores the need for targeted interventions, such as rodent control in MI systems and poultry management in MSI systems, to mitigate both zoonotic and economic impacts. Full article
(This article belongs to the Section Animal Science)
38 pages, 6505 KiB  
Review
Trends in Oil Spill Modeling: A Review of the Literature
by Rodrigo N. Vasconcelos, André T. Cunha Lima, Carlos A. D. Lentini, José Garcia V. Miranda, Luís F. F. de Mendonça, Diego P. Costa, Soltan G. Duverger and Elaine C. B. Cambui
Water 2025, 17(15), 2300; https://doi.org/10.3390/w17152300 (registering DOI) - 2 Aug 2025
Abstract
Oil spill simulation models are essential for predicting the oil spill behavior and movement in marine environments. In this study, we comprehensively reviewed a large and diverse body of peer-reviewed literature obtained from Scopus and Web of Science. Our initial analysis phase focused [...] Read more.
Oil spill simulation models are essential for predicting the oil spill behavior and movement in marine environments. In this study, we comprehensively reviewed a large and diverse body of peer-reviewed literature obtained from Scopus and Web of Science. Our initial analysis phase focused on examining trends in scientific publications, utilizing the complete dataset derived after systematic screening and database integration. In the second phase, we applied elements of a systematic review to identify and evaluate the most influential contributions in the scientific field of oil spill simulations. Our analysis revealed a steady and accelerating growth of research activity over the past five decades, with a particularly notable expansion in the last two. The field has also experienced a marked increase in collaborative practices, including a rise in international co-authorship and multi-authored contributions, reflecting a more global and interdisciplinary research landscape. We cataloged the key modeling frameworks that have shaped the field from established systems such as OSCAR, OIL-MAP/SIMAP, and GNOME to emerging hybrid and Lagrangian approaches. Hydrodynamic models were consistently central, often integrated with biogeochemical, wave, atmospheric, and oil-spill-specific modules. Environmental variables such as wind, ocean currents, and temperature were frequently used to drive model behavior. Geographically, research has concentrated on ecologically and economically sensitive coastal and marine regions. We conclude that future progress will rely on the real-time integration of high-resolution environmental data streams, the development of machine-learning-based surrogate models to accelerate computations, and the incorporation of advanced biodegradation and weathering mechanisms supported by experimental data. These advancements are expected to enhance the accuracy, responsiveness, and operational value of oil spill modeling tools, supporting environmental monitoring and emergency response. Full article
(This article belongs to the Special Issue Advanced Remote Sensing for Coastal System Monitoring and Management)
Show Figures

Figure 1

41 pages, 7942 KiB  
Article
Ionospheric Statistical Study of the ULF Band Electric Field and Electron Density Variations Before Strong Earthquakes Based on CSES Data
by Lei Nie, Xuemin Zhang, Hong Liu and Shukai Wang
Remote Sens. 2025, 17(15), 2677; https://doi.org/10.3390/rs17152677 (registering DOI) - 2 Aug 2025
Abstract
Anomalous ionospheric disturbances have been observed as potential precursors to earthquakes. This study utilized data from the CSES satellite to investigate anomalies in the ULF band ionospheric electric field and electron density preceding earthquakes with magnitudes of Ms ≥ 6.0 in China and [...] Read more.
Anomalous ionospheric disturbances have been observed as potential precursors to earthquakes. This study utilized data from the CSES satellite to investigate anomalies in the ULF band ionospheric electric field and electron density preceding earthquakes with magnitudes of Ms ≥ 6.0 in China and neighboring regions from 2019 to 2021. Comparative analysis with a randomly generated earthquake catalog indicated that these anomalies were spatially concentrated over the epicenter and temporally clustered on specific dates prior to the events. To assess the global relevance of these findings, the analysis was extended to earthquakes with Ms ≥ 7.0 worldwide during the same period, revealing consistent spatiotemporal patterns of ionospheric anomalies in both regional and global datasets. Furthermore, by combining the two earthquake catalogs and classifying events into oceanic and continental categories, additional statistical analyses were conducted to identify distinct ionospheric disturbance patterns associated with these different tectonic environments. These results provide a solid foundation for future research aimed at identifying and extracting ionospheric anomalies as potential pre-earthquake indicators. Full article
Show Figures

Figure 1

23 pages, 2663 KiB  
Article
How Nanofluids May Enhance Energy Efficiency and Carbon Footprint in Buildings?
by Sylwia Wciślik
Sustainability 2025, 17(15), 7035; https://doi.org/10.3390/su17157035 (registering DOI) - 2 Aug 2025
Abstract
Nanofluids are an innovative working medium in solar hot water installations (DHWs), thanks to their increased thermal conductivity and heat transfer coefficient. The aim of this work was to assess the effect of Al2O3 nanofluids in a water–ethylene glycol base [...] Read more.
Nanofluids are an innovative working medium in solar hot water installations (DHWs), thanks to their increased thermal conductivity and heat transfer coefficient. The aim of this work was to assess the effect of Al2O3 nanofluids in a water–ethylene glycol base (40:60%) and with the addition of Tween 80 surfactant (0.2 wt%) on thermal efficiency (ε) and exergy (ηex) in a plate heat exchanger at DHW flows of 3 and 12 L/min. The numerical NTU–ε model was used with dynamic updating of thermophysical properties of nanofluids and the solution of the ODE system using the ode45 method, and the validation was carried out against the literature data. The results showed that the nanofluids achieved ε ≈ 0.85 (vs. ε ≈ 0.87 for the base fluid) and ηex ≈ 0.72 (vs. ηex ≈ 0.74), with higher entropy generation. The addition of Tween 80 reduced the viscosity by about 10–15%, resulting in a slight increase of Re and h-factor; however, the impact on ε and ηex was marginal. The environmental analysis with an annual demand of Q = 3000 kWh/year and an emission factor of 0.2 kg CO2/kWh showed that for ε < 0.87 the nanofluids increased the emissions by ≈16 kg CO2/year, while at ε ≈ 0.92, a reduction of ≈5% was possible. This paper highlights the need to optimize nanofluid viscosity and exchanger geometry to maximize energy and environmental benefits. Nowadays, due to the growing problems of global warming, the analysis of energy efficiency and carbon footprint related to the functioning of a building seems to be crucial. Full article
Show Figures

Figure 1

Back to TopTop