Search Results (138)

Accurate reservoir inflow forecasting is vital for effective water resource management. Reliable forecasts enable operators to optimize storage and release strategies to meet competing sectoral demands—such as water supply, irrigation, and hydropower scheduling—while also mitigating flood and drought risks. To address this need, in this study, we propose a novel time-variant encoder–decoder (ED) model designed specifically to improve multi-step reservoir inflow forecasting, enabling accurate predictions of reservoir inflows up to seven days ahead. Unlike conventional ED-LSTM and recursive ED-LSTM models, which use fixed encoder parameters or recursively propagate predictions, our model incorporates an adaptive encoder structure that dynamically adjusts to evolving conditions at each forecast horizon. Additionally, we introduce the Expected Baseline Integrated Gradients (EB-IGs) method for variable importance analysis, enhancing interpretability of inflow by incorporating multiple baselines to capture a broader range of hydrometeorological conditions. The proposed methods are demonstrated at several diverse reservoirs across the United States. Our results show that they outperform traditional methods, particularly at longer lead times, while also offering insights into the key drivers of inflow forecasting. These advancements contribute to enhanced reservoir management through improved forecasting accuracy and practical decision-making insights under complex hydroclimatic conditions. Full article

Water within coal reservoirs exerts dual effects on methane adsorption–desorption by competing for adsorption sites and reducing permeability. The bound water effect, caused by coal wettability, significantly constrains coalbed methane (CBM) production, rendering investigations into coal wettability crucial for efficient CBM development. Compared with other geological formations, coals are characterized by a highly developed microporous structure, making the CO₂ sequestration mechanism in coal seams closely linked to the microscale interactions among gas, water, and coal matrixes. However, the intrinsic mechanisms remain poorly understood. In this study, molecular dynamics simulations are employed to investigate the wettability behaviors of CO₂, CH₄, and water on different coal matrix surfaces under varying temperature and pressure conditions, for coal macromolecules representative of four coal ranks. The study reveals the evolution of water wettability in response to CO₂ and CH₄ injection, identifies wettability differences among coal ranks, and analyzes the microscopic mechanisms governing wettability. The results show the following: (1) The contact angle increases with gas pressure, and the variation in wettability is more pronounced in CO₂ environments than in CH₄. As pressure increases, the number of hydrogen bonds decreases, while the peak gas density of CH₄ and CO₂ increases, leading to larger contact angles. (2) Simulations under different temperatures for the four coal ranks indicate that temperature has minimal influence on low-rank Hegu coal, whereas for higher-rank coals, gas adsorption on the coal surface increases, resulting in reduced wettability. Interfacial tension analysis further suggests that higher temperatures reduce water surface tension, cause dispersion of water molecules, and consequently improve wettability. Understanding the wettability variations among different coal ranks under variable pressure–temperature conditions provides a fundamental model and theoretical basis for investigating deep coal seam gas–water interactions and CO₂ geological sequestration mechanisms. These findings have significant implications for the advancement of CO₂-ECBM technology. Full article

Autochthonous Chagas disease remains a health risk for humans in Latin American countries but is rarely found among residents of the United States (US), despite the presence of competent insect vectors and small mammal reservoirs of Trypanosoma cruzi in the lower two-thirds of the US. This report discusses the differences in the rates of autochthonous Chagas disease in Latin America and the US. The key to the differences may lie in the mode (or means) of transmission of parasites to humans. In both Latin America and the US, the so-called vectorial transmission of Chagas disease to humans is the mode of acquisition accepted by most authorities. This mode involves the improbable combination of an infected kissing bug defecating near the mouth or eyes or the site of the bite, followed by the bite victim rubbing infected feces into the wound site or mucous membranes. Outbreaks of Chagas disease due to fecal–oral contamination, known as oral Chagas, have been recorded in Latin America for decades, and at present, oral Chagas is the predominant mode of infection recognized in Brazil. It is perhaps time to consider fecal–oral transmission in its many manifestations as a risk factor for Chagas disease in the US rather than reflexively invoking vectorial transmission. Fecal–oral transmission includes contamination of food and drink by triatomine feces and infection via contaminated fomites and surfaces at home and at worksites, as well as transmission from infected small mammals and other routes discussed in this report. Full article

Babesia odocoilei is an emerging zoonotic protozoan parasite primarily associated with cervids, with growing recognition among non-cervid hosts and in terms of potential public health implications. While this species has been documented in North America and parts of Europe, data on its presence in Romania remain scarce. This study aimed to investigate the presence of Babesia spp. in ticks collected from Romania, providing new information on the existing species and their distribution, as well as their potential epidemiologic significance. A total of 41 Ixodidae ticks were collected from 184 wild boars across six counties from Western and Central Romania. Ticks were identified using morphological assessments, and DNA was extracted from the samples using a standardized protocol. The presence of Babesia spp. was assessed using real-time PCR with primers and a Taq Man probe targeting 116 bp fragments of 18S rRNA genes. Molecular analysis was used to detect Babesia spp. DNA from a single tick sample (1/41, 2.43%), identified as Dermacentor marginatus, from Timiș County. The resulting amplicons were sequenced and compared with reference sequences in GenBank for species confirmation. This finding represents the first molecular identification of B. odocoilei in questing ticks from Romania. The expanding host range and geographic distribution of B. odocoilei raise concerns regarding its zoonotic potential. The presence of this pathogen in Dermacentor marginatus ticks suggests a broader vector competence than previously recognized, and future research should focus on host reservoirs, vector competence, and potential zoonotic transmission, with an emphasis on public health implications, including potential implications for veterinary diagnostics, vector control policies, and public health awareness regarding emerging tick-borne pathogens. Full article

Unconventional reservoirs are characterized by intricate fluid-phase behaviors, and physics-based shale oil well productivity prediction models often exhibit substantial deviations due to oversimplified theoretical frameworks and challenges in parameter acquisition. Under these circumstances, data-driven approaches leveraging actual production datasets have emerged as viable alternatives for productivity forecasting. Nevertheless, conventional data-driven architectures suffer from structural simplicity, limited capacity for processing low-dimensional feature spaces, and exclusive applicability to intra-sequence learning paradigms (e.g., production-to-production sequence mapping). This fundamentally conflicts with the underlying principles of mechanistic modeling, which emphasize pressure-to-production sequence transformations. To address these limitations, we propose a hybrid deep learning architecture integrating convolutional neural networks with bidirectional gated recurrent units (CNN-BiGRU). The model incorporates dedicated input pathways: fully connected layers for feature embedding and convolutional operations for high-dimensional feature extraction. By implementing a sequence-to-sequence (seq2seq) architecture with encoder–decoder mechanisms, our framework enables cross-domain sequence learning, effectively bridging pressure dynamics with production profiles. The CNN-BiGRU model was implemented on the TensorFlow framework, with rigorous validation of model robustness and systematic evaluation of feature importance. Hyperparameter optimization via grid searching yielded optimal configurations, while field applications demonstrated operational feasibility. Comparative analysis revealed a mean relative error (MRE) of 16.11% between predicted and observed production values, substantiating the model’s predictive competence. This methodology establishes a novel paradigm for machine learning-driven productivity prediction in unconventional reservoir engineering. Full article

The Wufeng–Longmaxi formations in the Sichuan Basin have emerged as China’s principal shale gas exploration target, with drilling results confirming substantial resource potential. Although the Neijiang–Rongchang Block demonstrates promising production, significant performance variations among lithofacies and reservoir types highlight the need for enhanced understanding of reservoir evolution. This study integrates petrological analyses, SEM imaging, XRD characterization, seismic interpretation, and production data from multiple wells targeting the Wufeng–Long 1-1 Sub-member. Key insights reveal the following: (1) reservoir lithology consists predominantly of siliceous shale (68% occurrence), characterized by high quartz content (48% avg), low carbonates (<15%), and low clay (<30%); (2) organic-rich intervals contain Type I kerogen derived from planktonic algae, with thermal maturity indicating post-mature evolution; (3) premium reservoirs develop multi-scale pore networks combining organic-hosted pores, interparticle pores, and micro-fractures. Despite high brittle mineral content, mechanical competence decreases stratigraphically from the Wufeng Formation (78%) to Long 1-1⁷ (63%); (4) depositional redox conditions facilitated exceptional organic preservation. Core analyses reveal low porosity (5.5% avg) and ultra-low permeability (0.27 × 10⁻³ μm² avg), classifying reservoirs as multiple tight unconventional systems in the study area. The proposed lithofacies-controlled pore evolution model elucidates reservoir heterogeneity mechanisms, providing critical geological criteria for optimized shale gas development. Full article

Sustainable water management requires integrated approaches balancing competing demands and environmental sustainability. This study introduces the Sustainable Water Optimization Tool (SUWO), an open-source, Python-based simulation-optimization framework for basin-scale surface-water-resources management. SUWO employs the water–energy–food–ecosystem (WEF-E) nexus approach, utilizing a multi-objective genetic algorithm (MOGA) to generate Pareto-optimal solutions and facilitate a trade-off analysis among water uses through simulations of reservoir operations, hydro-energy production, irrigation, and flow regulation. SUWO integrates scenario analysis with multi-criteria decision making (MCDM), enabling the evaluation of various management, climate, and environmental scenarios. The framework was applied to the Sakarya River Basin (SRB) in Türkiye, a rapidly developing region pressured by water infrastructure development, hydroelectric power plants (HEPPs), and irrigation expansion. The SUWO-SRB model showed that while Non-dominated Sorting Genetic Algorithm II (NSGA-II) generally exhibited superior performance, NSGA-III presented a competitive alternative. The optimization results were analyzed across four management scenarios under varying hydrological conditions and environmental management classes (EMCs) for the near future. The model results highlight WEF-E nexus trade-offs. Maximizing energy production often impacts irrigation and the ecosystem, while prioritizing sustainable irrigation can reduce energy output. Dry conditions reduce hydropower and irrigation capacity, emphasizing water scarcity vulnerabilities. Ecological deviation negatively correlates with anthropogenic factors. Full article

Canine monocytic ehrlichiosis (CME) is a highly infectious disease with zoonotic potential. Ehrlichia canis, the causative agent, is primarily transmitted by Rhipicephalus sanguineus. Tick infestation and tick-borne diseases (TBDs) are serious human and veterinary health problems due to the lack of efficient control measures. This review aims to provide information about CME, detailing epidemiology, pathogenesis, clinical manifestations, and current strategies for diagnosis, treatment, and prevention. The review delves into the biology of R. sanguineus, exploring its lifecycle, habitat, and mechanisms of E. canis transmission. Ehrlichia canis infection follows a three-phase transition: acute, subclinical, and chronic, with distinct clinical signs, from mild to severe and even life-threatening in some cases, with the potential for asymptomatic long-term carriers acting as reservoirs. Pathogenesis involves complex interactions between the pathogen and host immune responses, influencing disease severity and progression. Additionally, the review highlights challenges in controlling CME due to the widespread distribution of R. sanguineus. Genetic diversity within R. sanguineus populations and their varying vector competence further complicate control efforts. The role of environmental changes in tick distribution aligns the control of CME within the One Health concept, integrating approaches to improve outcomes for humans, animals, and the environment. Preventive measures on tick control and potential vaccine development are also reviewed. Full article

The persistence of latent HIV-1 proviruses in CD4⁺ T cells is a major obstacle to curing HIV. The “shock and kill” strategy involves reversing latency with latency-reversing agents (LRAs) and selectively inducing cell death in infected cells. However, current LRAs have shown limited efficacy in eliminating the ex vivo HIV reservoir and thus failed in clinical study. In this study, we repurposed PZ703b, a pro-apoptotic protein degrader initially developed for anti-leukemia therapy, to target HIV eradication. PZ703b induced the degradation of Bcl-2 and Bcl-xL, activating the non-canonical NF-kB pathway and caspases cascade, resulting in latency reversal and the selective apoptosis of infected cells. The treatment of ex vivo CD4⁺ T cells from ART-suppressed HIV-1 patients led to approximately a 50% reduction in the replication-competent reservoir. While this result does not reach the threshold required for a complete cure, it demonstrates the potential of a dual degrader of Bcl-2/Bcl-xL in reversing HIV latency and inducing selective cell death. Our study provides a proof-of-concept for using dual degraders of Bcl-2/Bcl-xL as a novel category of LRAs in therapeutic strategies aimed at reducing HIV reservoirs. This approach may pave the way for the further exploration of targeted interventions to eliminate the HIV-inducible reservoir. Full article

Distributed Acoustic Sensing (DAS) has emerged as a groundbreaking technology in seismology, transforming fiber-optic cables into dense, cost-effective seismic monitoring arrays. DAS makes use of Rayleigh backscattering to detect and measure dynamic strain and vibrations over extended distances. It can operate using both pre-existing telecommunication networks and specially designed fibers. This review explores the principles of DAS, including Coherent Optical Time Domain Reflectometry (COTDR) and Phase-Sensitive OTDR (ϕ-OTDR), and discusses the role of optoelectronic interrogators in data acquisition. It examines recent advancements in fiber design, such as helically wound and engineered fibers, which improve DAS sensitivity, spatial resolution, and the signal-to-noise ratio (SNR). Additionally, innovations in deployment techniques include cemented borehole cables, flexible liners, and weighted surface coupling to further enhance mechanical coupling and data accuracy. This review also demonstrated the applications of DAS across earthquake detection, microseismic monitoring, reservoir characterization and monitoring, carbon storage sites, geothermal reservoirs, marine environments, and urban infrastructure surveillance. The study highlighted several challenges of DAS, including directional sensitivity limitations, vast data volumes, and calibration inconsistencies. It also addressed solutions to these problems, such as advances in signal processing, noise suppression techniques, and machine learning integration, which have improved real-time analysis and data interpretability, enabling DAS to compete with traditional seismic networks. Additionally, modeling approaches such as full waveform inversion and forward simulations provide valuable insights into subsurface dynamics and fracture monitoring. This review highlights DAS’s potential to revolutionize seismic monitoring through its scalability, cost-efficiency, and adaptability to diverse applications while identifying future research directions to address its limitations and expand its capabilities. Full article

This study evaluates the application of an expert opinion-based fuzzy method for reservoir operation in humid subtropical climate/hot-summer Mediterranean climatic classes (Cfa/Csa in the Köppen–Geiger climate classification system), which are characterized by humid subtropical to Mediterranean conditions with ample rainfall and seasonal water availability challenges. Effective reservoir management in these regions is critical for balancing water storage and downstream release and maintaining ecosystem health under variable hydrological conditions. The performance of the fuzzy method was compared to two meta-heuristic algorithms: gravitational search algorithm (GSA) and shuffled frog leaping algorithm (SFLA). System performance was assessed using key indices such as the reliability index as a measure of meeting water demands. The fuzzy method achieved the highest reliability index of 0.690, outperforming GSA (0.677) and SFLA (0.688), demonstrating its superior ability to ensure consistent water supply downstream. The fuzzy method, leveraging expert knowledge, not only enhanced downstream water supply reliability but also reduced computational time compared to the meta-heuristic approaches. The incorporation of expert opinions provides a practical, robust, and efficient framework for reservoir management in challenging climate conditions such as Cfa/Csa classes. Additionally, the fuzzy solution demonstrated superior adaptability to diverse hydrological conditions, balancing ecological and water supply needs effectively. These findings highlight the potential of using expert opinions to support sustainable reservoir operations by achieving optimal trade-offs between competing objectives and addressing challenges in water resource management under varying climatic conditions. Full article

The Eastern mosquitofish Gambusia holbrooki Girard, 1859, has been widely introduced into tropical and temperate countries as a biological agent to control mosquitos, which are associated with diseases such as malaria and yellow fever. However, the species exhibits invasive characteristics by competing with native species for food and habitat use. This study investigates the feeding ecology of G. holbrooki populations from three distinct freshwater environments (Lake Iris, Eğlenhoca Reservoir, and Parlak Reservoir) on the Karaburun Peninsula (North-Western Türkiye), a region outside its native range. The primary aim was to evaluate seasonal and spatial variations in the diet of the species. A total of 871 specimens were analysed: 247 from Iris Lake, 318 from Parlak Reservoir, and 306 from Eğlenhoca Reservoir. Low percentages of empty stomachs (≤20%) across all populations indicate high feeding intensity. The results reveal that G. holbrooki exhibits a generalist feeding strategy, consuming a wide range of food items such as insects, zooplankton, and plant material across all the investigated environments. The relative importance of food groups (determined by the Importance Index, MI%) varied seasonally but not spatially. In all three populations, the most important food source in the spring was dipterans, followed by plants in the summer and fall, and cladocerans in the winter. Plants accounted for the largest percentage of the diet in every population (MI% >65%). These findings suggest that G. holbrooki adapts its diet to seasonal food availability. Full article

This study investigates the efficacy of polyacrylamide-based polymers, specifically hydrolysed polyacrylamide (HPAM), in reducing solids production within carbonate reservoirs. Building on our earlier simulation approach, molecular simulations were conducted to examine how these polymers adsorb onto calcite, the main mineral found in carbonate formations. The adsorption process was affected by several factors, including polymer molecular weight, charge density, temperature, and salinity. Generally, increased molecular weight, charge density, and temperature resulted in higher adsorption rates. The effect of salinity was more nuanced, as salt-bridging and charge-screening effects created competing influences. The simulation outcomes correspond closely with experimental results, offering valuable insights for designing and optimizing polymer-based strategies aimed at controlling solids production in carbonate reservoirs. Full article

In crop fields, weeds are perfect hosts for plant pathogenic viruses. The effects of these viruses can range from latent infection to plant death, affecting crop quality and yield and leading to economic loss in the world. Virus infection threatens cereals used as food for most of the world’s population. Weeds growing in cereal fields can compete for essential supply and act as virus reservoirs, strengthening their deteriorating effect. In this review, we collected the current information on viruses presenting in the most important monocotyledonous weeds: Echinocloa crus-galli, Setaria viridis, Cynodon dactylon, Sorghum halepense and millet species growing as weeds. Identifying plant viruses in monocotyledonous weed hosts provides more information about viral infection flow and guides the development of management strategies for safeguarding our field crops. Full article

Background: Long-lived, re-activatable immunity to SARS-CoV-2 and its emerging variants will rely on T cells recognizing conserved regions of viral proteins across strains. Heterologous prime–boost regimens can elicit elevated levels of circulating CD8+ T cells that provide a reservoir of first responders upon viral infection. Although most vaccines are currently delivered intramuscularly (IM), the initial site of infection is the nasal cavity. Methods: Here, we tested the hypothesis that a heterologous prime and boost vaccine regimen delivered intranasally (IN) will generate improved immune responses locally at the site of virus infection compared to intramuscular vaccine/booster regimens. Results: In a transgenic human ACE2 murine model, both a Spike-expressing single-cycle adenovirus (SC-Ad) and an IFNß safety-enhanced replication-competent Vesicular Stomatitis Virus (VSV) platform generated anti-Spike antibody and T-cell responses that diminished with age. Although SC-Ad-Spike boosted a prime with VSV-Spike-mIFNß, SC-Ad-Spike alone induced maximal levels of IgG, IgA, and CD8+ T-cell responses. Conclusions: There were significant differences in T-cell responses in spleens compared to lungs, and the intranasal boost was significantly superior to the intramuscular boost in generating sentinel immune effectors at the site of the virus encounter in the lungs. These data show that serious consideration should be given to intranasal boosting with anti-SARS-CoV-2 vaccines. Full article