Search Results (63,084)

We focus on optimizing oil displacement in brownfields using alkali polymers (AP) flooding. The goal is to enhance rock–fluid and fluid–fluid interactions to improve oil recovery. The evaluation includes detailed screening of AP mixtures to ensure cost-effectiveness and maximize chemical slug efficiency, using an AP pilot project in Austria as a case study. Key aspects of the study involve assessing fluid properties to select appropriate chemical concentrations. Important parameters include the stability of produced emulsions, interfacial tension (IFT) measurements, and rheological analyses. Rock–fluid interactions were examined through core flooding experiments on both low- and high-permeability core plugs to understand fluid dynamics in heterogeneous reservoirs. A novel part of the research involved simulating the in situ aging of the AP slug, which increases its anionicity over time. Two-phase core flooding with aged chemicals provided insights into the evolution of chemical effectiveness and interactions. We found that an alkali concentration of 7500 ppm was optimal for the AP slug, particularly in its interaction with dead oil with a high total acid number (TAN), leading to emulsions with microscopic instability. Single-phase core flooding showed that the AP slug from Vendor B outperformed that from Vendor A despite mechanical stability issues. However, the additional recovery factor (RF) for polymer A-based slugs was higher in both high- and low-permeability core plugs. The findings suggest that in situ aging of the AP slug could reduce costs and enhance injection performance. Full article

The increasing use of unmanned aerial vehicles (UAVs) in the commercial and recreational sectors has led to a heightened demand for effective recovery solutions after a crash, particularly for lightweight drones. This paper presents the development of a long-range and low-cost emergency radio beacon designed specifically for small UAVs. Unlike traditional emergency locator transmitters (ELTs), our proposed beacon addresses the unique needs of UAVs by reducing size, weight, and cost, while maximizing range and power efficiency. The device utilizes a global system for mobile (GSM)-based communication module to transmit location data via short message service (SMS), eliminating the need for specialized receivers and expanding the operational range even in obstacle-rich environments. Additionally, a built-in global navigation satellite system (GNSS) receiver provides precise coordinates, activated only upon impact detection through an accelerometer, thereby saving power during normal operations. Experimental tests confirm the extended range, high precision, and compatibility of the prototype with common mobile networks. Cost-effective and easy to use, this beacon improves UAV recovery efforts by providing reliable localization data to users in real time, thus safeguarding the UAV investment. Full article

The fusion of multi-polarized petrographic images of rock thin sections involves the fusion of feature information from microscopic images of rock thin sections illuminated under both plane-polarized and orthogonal-polarized light. During the fusion process of rock thin section images, the inherent high resolution and abundant feature information of the images pose substantial challenges in terms of computational complexity when dealing with massive datasets. In engineering applications, to ensure the quality of image fusion while meeting the practical requirements for high-speed processing, this paper proposes a novel fast fusion Transformer. The model leverages a soft matching algorithm based on intuitionistic fuzzy sets to merge redundant tokens, effectively mitigating the negative effects of asymmetric dependencies between tokens. The newly generated artificial tokens serve as brokers for the Query (Q), forming a novel lightweight fusion strategy. Both subjective visual observations and quantitative analyses demonstrate that the Transformer proposed in this paper is comparable to existing fusion methods in terms of performance while achieving a notable enhancement in its inference efficiency. This is made possible by the attention paradigm, which is equivalent to a generalized form of linear attention, and the newly designed loss function. The model has been experimented on with multiple datasets of different rock types and has exhibited robust generalization capabilities. It provides potential for future research in diverse geological conditions and broader application scenarios. Full article

Odor emission has become a major issue in waste transfer stations. Hydrogen sulfide, methyl mercaptan (MM), and dimethyl disulfide (DMDS) are the main odorous gases. They have a low odor threshold and are difficult to remove. In this study, pine bark biochar was produced and modified with metal ions, including Ni²⁺, Ti²⁺, Mn²⁺, Zn²⁺, Mg²⁺, and Cu²⁺. It was then used for the removal of hydrogen sulfide, methyl mercaptan, and dimethyl disulfide. Among all modifications, the Cu²⁺ modified biochar showed the best sorption capacity, and the maximum sorption amounts were 20.50 mg/g for H₂S, 36.50 mg/g for MM, and 57.98 mg/g for DMDS. To understand the adsorption, BET, SEM, and XPS of the original and modified biochar were performed. This illustrated that modification with Cu²⁺ increased the surface area and porosity, thus enhancing the adsorption capacity. In the alkaline absorption study, it was found that the removal of the three odor gases increased with the pH increase. Based on the results, a combined process called absorption–adsorption was established to treat the odor gas generated in a local waste transfer station. Thirty-one gas components were detected in the odor gas of the waste transfer station. The process proceeded for 30 days, and these gas components were not found in the effluent during treatment. Regarding H₂S, MM, and DMDS, they were not detected even after 90 days. This indicates the high adsorption capacity of the modified biochar toward the three odor gases. In addition, the process is simple and easy to operate. This suggests that it is suitable for treating odor in places where there is no technician, and the odor needs efficient treatment. The study provides a feasible alternative for domestic waste transfer stations to control the odor problem. Full article

Marine microalgae are a rich source of natural products, and their amino acid-based antimicrobial agents are usually obtained by enzymatic hydrolysis, which is inefficient and limits the research on antimicrobial peptides (AMPs) from microalgae. In this study, Aureococcus anophagefferens is used as a model to predict antimicrobial peptides through high-throughput methods, and 471 putative peptides are identified based on the de novo transcriptome technique. Among them, three short peptides, P1, P6, and P7 were found to have antimicrobial activity against Escherichia coli, Staphylococcus aureus, Micro1coccus luteus, and yeast Pichia pastoris, and they showed no hemolytic activity even at higher concentrations up to 10 mg/mL. Especially P6, a 12-amino acid peptide with three positive charges, which exhibited the most significant microbicidal effect with the lowest MIC of 31.25 μg/mL against E. coli, and electron microscope observations showed the surface of P6 treated E. coli with granular protrusions and ruptures, suggesting that it likely caused cell death by directly destroying the bacterial cell membrane. This study may enrich the database of microalgal AMPs and demonstrate an efficient process for searching and validating microalgal source AMPs by combining computer analysis with bioactivity experiments. Full article

The integration of intermittent renewable energy sources into the energy supply has driven the need for large-scale energy storage technologies. Vanadium redox flow batteries (VRFBs) are considered promising due to their long lifespan, high safety, and flexible design. However, the graphite felt (GF) electrode, a critical component of VRFBs, faces challenges due to the scarcity of active sites, leading to low electrochemical activity. Herein, we developed a bismuth nanoparticle uniformly modified graphite felt (Bi-GF) electrode using a bismuth oxide-mediated hydrothermal pyrolysis method. The Bi-GF electrode demonstrated significantly improved electrochemical performance, with higher peak current densities and lower charge transfer resistance than those of the pristine GF. VRFBs utilizing Bi-GF electrodes achieved a charge-discharge capacity exceeding 700 mAh at 200 mA/cm², with a voltage efficiency above 84%, an energy efficiency of 83.05%, and an electrolyte utilization rate exceeding 70%. This work provides new insights into the design and development of efficient electrodes, which is of great significance for improving the efficiency and reducing the cost of VRFBs. Full article

This survey explores the evolution of test scenario generation for autonomous vehicles (AVs), distinguishing between non-adaptive and adaptive scenario approaches. Non-adaptive scenarios, where dynamic objects follow predetermined scripts, provide repeatable and reliable tests but fail to capture the complexity and unpredictability of real-world traffic interactions. In contrast, adaptive scenarios, which adapt in real time to environmental changes, offer a more realistic simulation of traffic conditions, enabling the assessment of an AV system’s adaptability, safety, and robustness. The shift from non-adaptive to adaptive scenarios is increasingly emphasized in AV research, to better evaluate system performance in complex environments. However, generating adaptive scenario is more complex and faces challenges. These include the limited diversity in behaviors, low model interpretability, and high resource requirements. Future research should focus on enhancing the efficiency of adaptive scenario generation and developing comprehensive evaluation metrics to improve the realism and effectiveness of AV testing. Full article

Global precipitation products (GPPs) are vital in weather forecasting, efficient water management, and monitoring floods and droughts. However, the precision of these datasets varies considerably across different climatic regions and topographic conditions. Therefore, the accuracy assessment of the precipitation dataset is crucial at the local scale before its application. The current study initially compared the performance of recently modified and upgraded precipitation datasets, including Climate Research Unit Time-Series (CRU TS v4.08), fifth-generation ERA5-Land (ERA-5), Integrated Multi-satellite Retrievals for GPM (IMERG) final run (IMERG v07B), and Multi-Source Weighted-Ensemble Precipitation (MSWEP v2.8), against ground observations on the provincial basis across Pakistan from 2003 to 2020. Later, the study area was categorized into four regions based on the elevation to observe the impact of elevation gradients on GPPs’ skills. The monthly and seasonal precipitation estimations of each product were validated against in situ observations using statistical matrices, including the correlation coefficient (CC), root mean square error (RMSE), percent of bias (PBias), and Kling–Gupta efficiency (KGE). The results reveal that IMERG7 consistently outperformed across all the provinces, with the highest CC and lowest RMSE values. Meanwhile, the KGE (0.69) and PBias (−0.65%) elucidated, comparatively, the best performance of MSWEP2.8 in Sindh province. Additionally, all the datasets demonstrated their best agreement with the reference data toward the southern part (0–500 m elevation) of Pakistan, while their performance notably declined in the northern high-elevation glaciated mountain regions (above 3000 m elevation), with considerable overestimations. The superior performance of IMERG7 in all the elevation-based regions was also revealed in the current study. According to the monthly and seasonal scale evaluation, all the precipitation products except ERA-5 showed good precipitation estimation ability on a monthly scale, followed by the winter season, pre-monsoon season, and monsoon season, while during the post-monsoon season, all the datasets showed weak agreement with the observed data. Overall, IMERG7 exhibited comparatively superior performance, followed by MSWEP2.8 at a monthly scale, winter season, and pre-monsoon season, while MSWEP2.8 outperformed during the monsoon season. CRU TS showed a moderate association with the ground observations, whereas ERA-5 performed poorly across all the time scales. In the current scenario, this study recommends IMERG7 and MSWEP2.8 for hydrological and climate studies in this region. Additionally, this study emphasizes the need for further research and experiments to minimize bias in high-elevation regions at different time scales to make GPPs more reliable for future studies. Full article

Carbonyl sulfide (COS), an organosulfur compound commonly present in industrial gases, poses significant challenges for environmental protection and industrial processes due to its toxicity. This paper reviews recent advancements in the development of catalysts for COS hydrolysis, emphasizing the effects of various supports and active components on catalyst performance, as well as the mechanisms underlying the hydrolysis reaction. Traditional supports like γ-Al₂O₃ demonstrate high activity for COS hydrolysis but are susceptible to deactivation. In contrast, novel supports such as activated carbon, TiO₂, and ZrO₂ have garnered attention for their unique structures and properties. The incorporation of active components, including alkali metals, alkaline earth metals, transition metals, and rare earth metals, significantly enhances the hydrolysis efficiency and resistance to deactivation of the catalysts. Additionally, this paper outlines three primary mechanisms for COS hydrolysis: the alkali-catalyzed mechanism, the Langmuir–Hinshelwood model, and the Eley–Rideal model mechanism, as well as the thiocarbonate intermediate mechanism, which collectively elucidate the conversion of COS into the H₂S and CO₂ catalyzed by these systems. Future research efforts will concentrate on developing high-activity, high-stability, and cost-effective COS hydrolysis catalysts, along with a more in-depth exploration of the reaction mechanisms to facilitate the efficient removal of COS from industrial emissions. Full article

The primary goal in designing wind turbine blades is to maximize aerodynamic efficiency. One promising approach to achieve this is by modifying the blade geometry, with winglets to the tip. Winglets are intended to reduce the strength of the tip vortices, thereby reducing induced drag, increasing torque, and, ultimately, improving the power output of the wind turbines. In this study, computational fluid dynamics (CFD) simulations were utilized to assess the aerodynamic performance of wind turbine blades with and without winglets at various wind speeds (5, 7, 10, 13, 15, 20, and 25 m/s). The results indicate that winglets have a limited effect at low (5 and 7 m/s) and high (20 and 25 m/s) wind speeds due to fully attached and separated flows over the blade surface. However, within the 10–15 m/s range, winglets significantly enhance torque and power output. While this increased power generation is beneficial, it is essential to consider the potential impact of the associated increase in thrust force on turbine stability. Full article

Various ingredients are utilized to inhibit the growth of harmful bacteria associated with cavities, gum disease, and bad breath. However, the precise mechanisms by which these ingredients affect the oral microbiome have not been fully understood at the molecular level. To elucidate the molecular mechanisms, a high-throughput bacterial transcriptomics study was conducted, and the gene expression profiles of six common oral bacteria, including two Gram-positive bacteria (Actinomyces viscosus, Streptococcus mutans) and four Gram-negative bacteria (Porphyromonas gingivalis, Tannerella forsythia, Fusobacterium nucleatum, and Prevotella pallens), were analyzed. The bacteria were exposed to nine common ingredients in toothpaste and mouthwash at different concentrations (stannous fluoride, stannous chloride, arginine bicarbonate, cetylpyridinium chloride, sodium monofluorophosphate, sodium fluoride, potassium nitrate, zinc phosphate, and hydrogen peroxide). Across 78 ingredient–microorganism pairs with 360 treatment–control combinations, significant and reproducible ingredient-based transcriptional response profiles were observed, providing valuable insights into the effects of these ingredients on the oral microbiome at the molecular level. This research shows that oral care product ingredients applied at biologically relevant concentrations manifest differential effects on the transcriptomics of bacterial genes in a variety of oral periodontal pathogenic bacteria. Stannous fluoride, stannous chloride, and cetylpyridinium chloride showed the most robust efficacy in inhibiting the growth or gene expression of various bacteria and pathogenic pathways. Combining multiple ingredients targeting different mechanisms might be more efficient than single ingredients in complex oral microbiomes. Full article

Triply periodic minimal surfaces (TPMS) represent an innovative approach to the design of heat exchangers, enabling the optimisation of thermal and hydraulic performance. This study presents a comparative analysis of three geometric TPMS configurations: sheet gyroid, skeletal gyroid, and the newly proposed combined gyroid geometry. Using numerical analysis based on simulations of fluid flow and heat transfer, key parameters such as the heat transfer coefficient, Nusselt number, friction factor, Chilton–Colburn j-factor, and pressure drop were evaluated. The results demonstrated that the combined gyroid geometry achieves the highest heat transfer efficiency, exhibiting significant improvements in the Nusselt number and heat transfer coefficient across the entire flow range. Simultaneously, it maintains low pressure losses, making it well suited for applications demanding high thermal performance with minimal energy losses. This study highlights the potential of TPMS geometries for optimising heat exchanger design and opens new paths for their implementation in industrial systems. Full article

Wearable communication technologies necessitate antenna designs that harmonize ergonomic compatibility, reliable performance, and minimal interaction with human tissues. However, high specific absorption rate (SAR) levels, limited radiation efficiency, and challenges in integration with flexible materials have significantly constrained widespread deployment. To address these limitations, this manuscript introduces a novel wearable cavity-backed substrate-integrated waveguide (SIW) antenna augmented with artificial magnetic conductor (AMC) structures. The proposed architecture is meticulously engineered using diverse textile substrates, including cotton, jeans, and jute, to synergistically integrate SIW and AMC technologies, mitigating body-induced performance degradation while ensuring safety and high radiation efficiency. The proposed design demonstrates significant performance enhancements, achieving SAR reductions to 0.672 W/kg on the spine and 0.341 W/kg on the forelimb for the cotton substrate. Furthermore, the AMC-backed implementation attains ultra-low reflection coefficients, as low as −26.56 dB, alongside a gain improvement of up to 1.37 dB, culminating in a total gain of 7.09 dBi. The impedance bandwidth exceeds the ISM band specifications, spanning 150 MHz (2.3–2.45 GHz). The design maintains remarkable resilience and operational stability under varying conditions, including dynamic bending and proximity to human body models. By substantially suppressing back radiation, enhancing directional gain, and preserving impedance matching, the AMC integration optimally adapts the antenna to body-centric communication scenarios. This study uniquely investigates the dielectric and mechanical properties of textile substrates within the AMC-SIW configuration, emphasizing their practicality for wearable applications. This research sets a precedent for wearable antenna innovation, achieving an unprecedented balance of flexibility, safety, and electromagnetic performance while establishing a foundation for next-generation wearable systems. Full article

This paper examines Connected Smart Green Buildings (CSGBs) in Burnaby, BC, Canada, with a focus on townhouses with one to four bedrooms. The proposed model integrates sustainable materials and smart components such as recycled insulation, Photovoltaic (PV) solar panels, smart meters, and high-efficiency systems. These elements improve energy efficiency and promote sustainability. Operating in island mode, CSGBs can function independently of the grid, providing resilience during power outages and reducing reliance on external energy sources. Real data on electricity, gas, and water consumption are used to optimize load management under isolated conditions. Electric Vehicles (EVs) are also considered in the system. They serve as energy storage devices and, through Vehicle-to-Grid (V2G) technology, can supply power when needed. A hybrid Machine Learning (ML) model combining Long Short-Term Memory (LSTM) and a Convolutional Neural Network (CNN) is proposed to improve the performance. The metrics considered include accuracy, efficiency, emissions, and cost. The performance was compared with several well-known models including Linear Regression (LR), CNN, LSTM, Random Forest (RF), Gradient Boosting (GB), and hybrid LSTM–CNN, and the results show that the proposed model provides the best results. For a four-bedroom Connected Smart Green Townhouse (CSGT), the Mean Absolute Percentage Error (MAPE) is 4.43%, the Root Mean Square Error (RMSE) is 3.49 kWh, the Mean Absolute Error (MAE) is 3.06 kWh, and $R^2$ is 0.81. These results indicate that the proposed model provides robust load optimization, particularly in island mode, and highlight the potential of CSGBs for sustainable urban living. Full article

In the face of increasingly complex application scenarios, there is an urgent need for (Radio Frequency Identification) RFID systems that are capable of accurately identifying microwave signals of different frequency bands. Based on the acumen detection characteristics of microwave signals by lithium niobate electro-optic modulators, applying large-bandwidth thin-film lithium niobate electro-optic modulation to RFID systems can achieve efficient operation across multiple frequency bands. This study discusses, in detail, the design, simulation, fabrication, and testing process of the electro-optic modulator to obtain a high-performance, large-bandwidth lithium niobate electro-optic modulator. By using multilayer lithography techniques to prepare thick traveling-wave electrodes, the problem of irregular cross-sections during the fabrication of thick electrodes has been successfully reduced, improving the stability and controllability of the device. Test results show that the insertion loss of the electro-optic modulator is about 6 dB, the extinction ratio is 36.5 dB, the optical waveguide mode field is 1 μm, the full-band characteristic impedance is 50 Ω, the test bandwidth is 50 GHz, and the half-wave voltage is 1.8 V. Compared with existing optimization schemes, this design not only achieves a large bandwidth and a small half-wave voltage, but also proposes a new fabrication process scheme, optimizing the process and resulting in samples with stable performance. Full article