Search Results (549)

Filtrate from dewatering anaerobically digested biosolids is a side-stream of wastewater treatment that contains high concentrations of nitrogen and phosphorus compounds that can serve as nutrients for cultivating microalgae biomass as biofilms for bioproduct production at Water Resource Recovery Facilities (WRRFs). One system used to cultivate attached microalgae biofilms is the rotating algal biofilm reactor (RABR). A pilot RABR with 72 m² growth surface area, 11.5 m² footprint area, and a liquid volume of 11,500 L was operated in an outdoor environment at the largest WRRF in Utah, U.S.A, the Central Valley Water Reclamation Facility (CVWRF). The configuration of the RABR was altered from the previous configuration with regard to temperature and duty cycle with the goal to maximize biomass productivity. Results included an increase in dry biomass productivity on a footprint basis from 8.8 g/m²/day to 26.8 g/m²/day (205%) while power requirements changed from 28.3 W to 91 W. The increase in biomass productivity has direct benefits for bioproducts including bioplastic, biofertilizer, and the extraction of lipids for conversion to biofuels. Full article

As the demand for high-quality video streaming applications continues to rise, multi-access edge computing (MEC)-assisted streaming schemes have emerged as a viable solution within the context of HTTP adaptive streaming (HAS). These schemes aim to enhance both quality of experience (QoE) and utilization of network resources. HAS faces a significant challenge when applied to mobile cellular networks. Designing a HAS scheme that fairly allocates bitrates to users ensures a high QoE and optimizes bandwidth utilization remains a challenge. To this end, we designed an MEC- and client-assisted adaptation framework for HAS, facilitating collaboration between the edge and client to enhance users’ quality of experience. The proposed framework employs fuzzy logic at the user end to determine the upper limit for the video streaming rate. On the MEC side, we developed an integer nonlinear programming (INLP) optimization model that collectively enhances the QoE of video clients by considering the upper limit set by the client. Due to the NP-hardness of the problem, we utilized a greedy algorithm to efficiently solve the quality adaptation optimization problem. The results demonstrate that the proposed framework, on average, (i) improves users’ QoE by 30%, (ii) achieves a fair allocation of bitrates by 22.6%, and (iii) enhances network utilization by 4.2% compared to state-of-the-art approaches. In addition, the proposed approach prevents playback interruptions regardless of the client’s buffer size and video segment duration. Full article

Recommender systems are essential tools in the digital age, helping users discover products, content, and services across platforms like streaming services, online stores, and social networks. Traditionally, these systems have relied on methods such as collaborative filtering, content-based, and knowledge-based approaches, using data like user–item interactions and demographic details. With the rise of big data, an increasing amount of “side information”, like contextual data, social behavior, and metadata, has become available, enabling more personalized and effective recommendations. This work provides a comparative analysis of traditional recommender systems and newer models incorporating side information, particularly visual features, to determine whether integrating such data improves recommendation quality. By evaluating the benefits and limitations of using complex formats like visual content, this work aims to contribute to the development of more robust and adaptive recommender systems, offering insights for future research in the field. Full article

Today’s linear nutrient flows are rooted in a long history of agronomic and wastewater engineering strategies that have created cascading environmental, social, and economic side effects, signaling the need for more holistic and circular approaches. Our examination of the regulatory pathways that enable and constrain urine recycling—an underutilized approach to repurposing human waste as fertilizer—addresses a persistent research gap related to the mainstreaming of transformative technologies. Framed around policy process theories—Street Level Bureaucracy and Multiple Streams Theory—our methods include a review and mapping of 54 regulatory documents; action research where we reflect on our own efforts to expand urine recycling; and interviews with 16 practitioners and regulators in four states which, to our knowledge, are the only places in the US with efforts to scale up urine recycling in community settings. Given its circular nature, a key challenge we find is a lack of clarity around which sectors, or what scales of government, “own” the decision to allow the collection and use of urine as a fertilizer. Working around these challenges, we show how practitioners use many practical strategies to simplify the approval process and reduce the risk aversion regulators face when confronted with ambiguous rulemaking. Full article

Autonomous Underwater Vehicles (AUVs) equipped with vision systems face unique challenges in real-time environmental perception due to harsh underwater conditions and computational constraints. This paper presents a novel cloud–edge framework for real-time vision–language analysis in underwater drones using the Qwen2.5-VL model. Our system employs a uniform frame sampling mechanism that balances temporal resolution with processing capabilities, achieving near real-time analysis at 1 fps from 23 fps input streams. We construct a comprehensive data flow model encompassing image enhancement, communication latency, cloud-side inference, and semantic result return, which is supported by a theoretical latency framework and sustainable processing rate analysis. Simulation-based experimental results across three challenging underwater scenarios—pipeline inspection, coral reef monitoring, and wreck investigation—demonstrate consistent scene comprehension with end-to-end latencies near 1 s. The Qwen2.5-VL model successfully generates natural language summaries capturing spatial structure, biological content, and habitat conditions, even under turbidity and occlusion. Our results show that vision–language models (VLMs) can provide rich semantic understanding of underwater scenes despite challenging conditions, enabling AUVs to perform complex monitoring tasks with natural language scene descriptions. This work contributes to advancing AI-powered perception systems for the growing autonomous underwater drone market, supporting applications in environmental monitoring, offshore infrastructure inspection, and marine ecosystem assessment. Full article

The production of microbial lipids through single-cell oil (SCO) technologies has gained increasing attention as a sustainable alternative source of lipids for industrial applications. This development is driven by the limitations of plant-based oils, particularly their competition with food production and demand for arable land. Cutaneotrichosporon oleaginosus has been recognized as one of the most promising oleaginous microorganisms for efficient SCO production. To improve sustainability and economic viability, it is vital to understand the underlying metabolic mechanism of SCO production as well as needs and limitations in bioprocess engineering for the efficient utilization of carbon sources derived from diverse agricultural and industrial side streams. This review focuses on recent studies exploring the potential of SCO production through C. oleaginosus in a bioprocess context through the application of low-cost agro-industrial by-products as alternative carbon sources aiming to supply lipid raw materials for various industrial applications. C. oleaginosus can grow on different agro-industrial waste-derived substrates, including lignocellulosic biomass hydrolysates, biodiesel production process side streams, chitin-based by-products, cheese whey permeates, fungal biomass hydrolysates and algal biomass hydrolysates. These substrates contain various carbon sources, such as glucose, galactose, mannose, xylose, lactose, N-acetyl-glucosamine and glycerol, facilitating efficient SCO production. Additionally, the specific composition of SCO sourced from C. oleaginosus, including the presence of functional compounds like squalene and prevalent long-chain unsaturated fatty acids in its fatty acid profile, make it an ideal option to be used as a raw material in cosmetics, biofuel and food products. This comprehensive overview aims to shed light on the potential of C. oleaginosus in leveraging carbon source alternatives for sustainable SCO production for multifaceted, industrial applications of SCO. Full article

In this study, high-yield biopolymer/ceramic hollow fibers were fabricated via a facile, modified polyol process in a spinneret setup, enabling the controlled adsorption of Cu²⁺ ions. Post sintering transformed these into catalytic copper-decorated carbon/ceramic (alumina) composite hollow fibers, with alginate serving as both a metal ion binder and a copper nanoparticle stabilizer. The resulting hollow fibers featured porous walls with a high surface area and were densely decorated with copper nanoparticles. Their structural and morphological characteristics were analyzed, and their NO reduction performance was assessed in a continuous flow configuration, where the gas stream passed through both the shell and lumen sides of a fiber bundle in a tangential flow mode. This study also examined the stability, longevity and regeneration potential of the catalytic fibers, including the mechanisms of deactivation and reactivation. Carbon content was found to be decisive for catalytic performance. High-carbon fibers exhibited a light-off temperature of 250 °C, maintained about 90% N₂ selectivity and sustained a consistently high NO reduction efficiency for over 300 h, even without reducing gases like CO. In contrast, low-carbon fibers displayed a higher light-off temperature of 350 °C and a reduced catalytic efficiency. The results indicate that carbon enhances both activity and selectivity, counterbalancing deactivation effects. Owing to their scalability, durability and effectiveness, these catalytic fibers and their corresponding bundle-type reactor configuration represent a promising technology for advanced NO abatement. Full article

Nowadays, guided acoustic waves (GAW) are used for many sensor and actuator applications. The use of numerical methods can facilitate the development and optimization process enormously. In this work, a universally applicable finite element method (FEM)-based model is introduced to determine the dispersion relations of guided acoustic waves. A 2-dimensional unit cell model with Floquet periodicity is used to calculate the corresponding band structure diagrams. Starting from a free plate the model is expanded to encompass single-sided fluid loading. Followed by a straightforward algorithm for post-processing, the data is presented. Additionally, a parametric optimizer is used to adapt the simulations to experimental data measured by a laser Doppler vibrometer on an aluminum plate. Finally, the accuracy of the FEM model is compared to two reference models, achieving good consistency. In the case of the fluid-loaded model, the behavior of critical interactions between the dispersion curves and model-based artifacts is discussed. This approach can be used to model 2D structures like phononic crystals, which cannot be simulated by common GAW models. Moreover, this method can be used as input for advanced multiphysics simulations, including acoustic streaming applications. Full article

Modern web applications increasingly demand rendering techniques that optimize performance, responsiveness, and scalability. Progressive Server-Side Rendering (PSSR) bridges the gap between Server-Side Rendering and Client-Side Rendering by progressively streaming HTML content, improving perceived load times. Still, traditional HTML template engines often rely on blocking interfaces that hinder their use in asynchronous, non-blocking contexts required for PSSR. This paper analyzes how Java virtual threads, introduced in Java 21, enable non-blocking execution of blocking I/O operations, allowing the reuse of traditional template engines for PSSR without complex asynchronous programming models. We benchmark multiple engines across Spring WebFlux, Spring MVC, and Quarkus using reactive, suspendable, and virtual thread-based approaches. Results show that virtual threads allow blocking engines to scale comparably to those designed for non-blocking I/O, achieving high throughput and responsiveness under load. This demonstrates that virtual threads provide a compelling path to simplify the implementation of PSSR with familiar HTML templates, significantly lowering the barrier to entry while maintaining performance. Full article

Edge computing builds relevant services and applications on the edge server near the user side, which enables a faster service response. However, the lack of large-scale hardware resources leads to weak defense for edge devices. Therefore, proactive defense security mechanisms, such as Intrusion Detection Systems (IDSs), are widely deployed in edge computing. Unfortunately, most of those IDSs lack causal analysis capabilities and still suffer the threats from Advanced Persistent Threat (APT) attacks. To effectively detect APT attacks, we propose a heterogeneous graph neural networks threat detection model based on the provenance graph. Specifically, we leverage the powerful analysis and tracking capabilities of the provenance graph to model the long-term behavior of the adversary. Moreover, we leverage the predictive power of heterogeneous graph neural networks to embed the provenance graph by a node-level and semantic-level heterogeneous mutual attention mechanism. In addition, we also propose a provenance graph reduction algorithm based on the semantic similarity of graph substructures to improve the detection efficiency and accuracy of the model, which reduces and integrates redundant information by calculating the semantic similarity between substructures. The experimental results demonstrate that the prediction accuracy of our method reaches 99.8% on the StreamSpot dataset and achieves 98.13% accuracy on the NSL-KDD dataset. Full article

Global seafood production and consumption have increased in recent years, leading to a significant rise in side streams. Process waters are often disposed as wastewater, causing difficulties for industries in meeting the discharge standards. This is particularly relevant to the mussel processing industry, where one-third of the raw material ends up as high-organic content effluent. This study aims to optimize a nanofiltration–diafiltration (NF–DF) strategy to recover valuable savory compounds from mussel cooking water, to reduce the effluent organic pollution, and to evaluate its environmental sustainability using Life Cycle Assessment. Pilot trials lead to a configuration, combining a volumetric concentration factor of 10 in NF and 20 in DF, which achieved enhanced protein concentration (1.5-fold), amino acid concentration (5.2-fold), and COD removal (98.2%). The environmental assessment highlighted electricity consumption during NF and DF as the primary environmental hotspot, resulting in a carbon footprint of 0.12 kg CO₂ eq. kg⁻¹ of savory compounds and water use of 0.65 m³ deprived kg⁻¹. Prospective scenarios projected that ongoing energy system transitions could significantly reduce climate change and acidification impacts by over 75% by 2050. The proposed NF–DF strategy enhances resource efficiency and sustainability in seafood processing by recovering high-value compounds and facilitating water reuse. Full article

This study presents a comprehensive design, optimization, and intensification approach for enhancing the energy efficiency of electric grade isopropyl alcohol (IPA) production, a typical energy-intensive chemical process. The process entails preconcentration and dehydration steps, with the intensity of separation formulated from a multicomponent feed that consists of IPA and water, along with other impurities. Modeling and energy optimization were performed for a conventional distillation train as a base case by using the rigorous process simulator Aspen Plus V12.1. To improve energy efficiency, various options for intensifying distillation were examined. The side-stream preconcentration column was subsequently replaced by a dividing wall column (DWC) with two side streams, i.e., a Kaibel column, reducing the total energy consumption of corresponding distillation columns by 9.1% compared to the base case. Further strengthening was achieved by combining two columns in the preconcentration process into a single Kaibel column, resulting in a 22.8% reduction in reboiler duty compared to the base case. Optimization using the response surface methodology identified key operating parameters, such as side-draw positions and stage design, which significantly influence both energy efficiency and separation quality. The intensified Kaibel setup offers significant energy efficiencies and simplified column design, suggesting enormous potential for process intensification in energy-intensive distillation processes at the industrial level, including the IPA purification process. Full article

Developing a more efficient, cleaner, and energy-saving pretreatment process is the primary goal for lignocellulosic biofuels production. This study demonstrated the feasibility of circulating high-concentration acetone–butanol–ethanol (ABE) obtained via in situ product recovery (ISPR) as a pretreatment liquor. Taking ABE solvent separated from pervaporation (PV) and gas stripping (GS) as examples, results indicated that under dilute alkaline (1% NaOH) catalysis, the highly recalcitrant lignocellulosic matrices can be efficiently depolymerized, thereby improving fermentable sugars recovery in saccharification stage and ABE yield in subsequent fermentation stage. Results also revealed delignification of 91.5% (stream from PV) and 94.3% (stream from GS), with total monosaccharides recovery rates of 56.5% and 57.1%, respectively, can be realized when using corn stover as feedstock. Coupled with ABE fermentation, mass balance indicated a maximal 106.6 g of ABE (65.8 g butanol) can be produced from 1 kg of dry corn stover by circulating the GS condensate in pretreatment (the optimized pretreatment conditions were 1% w/v alkali and 160 °C for 1 h). Additionally, technical lignin with low molecular weight and narrow distribution was isolated, which enabled further side-stream valorisation. Therefore, integrating ISPR product circulation with lignocellulosic biobutanol shows strong potential for application under the concept of biorefinery. Full article

‘Mushy halibut syndrome’ (MHS) is associated with inferior fillet quality in Greenland halibut and is reported to occur in commercial catches across the North Atlantic. MHS constitutes a quality issue in fisheries and leads to economic losses and food wastage. Despite the known challenges associated with MHS, quantitative data on product properties are lacking, and yet they are crucial to assess actual losses and value-adding processing potential. As part of a larger effort to document and characterize MHS in Greenland halibut, we investigated how thaw drip loss (TDL), cooked drip loss (CDL), cooked yield, and tissue compressibility and elasticity differ between normal and ‘mushy’ halibut fillets. The fillets were sorted into three categories: normal, intermediate MHS, and severe MHS. The mean TDL and CDL increased more than three-fold in both MHS categories compared to normal fillets, while cooked yield decreased by approximately 20%. Fillets severely affected by MHS demonstrated high tissue compressibility (56%) and poor elasticity (46%), while the elasticity of the fillets belonging to the intermediate MHS category did not differ significantly from that of normal ones. These findings provide new insights into the product attributes of fillets affected by MHS, which are important for developing utilization and valorization strategies. Full article

Firstly, this paper reviews the fundamental theories of solid surface wettability and contact angle hysteresis. Subsequently, it further introduces four typical wettability-engineered surfaces with low hysteresis (superhydrophobic, superamphiphobic, super-slippery, and liquid-like smooth surfaces). Finally, it focuses on the latest research progress in the field of droplet manipulation on open planar surfaces with engineered wettability. To achieve droplet manipulation, the core driving forces primarily stem from natural forces guided by bioinspired gradient surfaces or the regulatory effects of external fields. In terms of bioinspired self-propelled droplet movement, this paper summarizes research inspired by natural organisms such as desert beetles, cacti, self-aligning floating seeds of emergent plants, or water-walking insects, which construct bioinspired special gradient surfaces to induce Laplace pressure differences or wettability gradients on both sides of droplets for droplet manipulation. Moreover, this paper further analyzes the mechanisms, advantages, and limitations of these self-propelled approaches, while summarizing the corresponding driving force sources and their theoretical formulas. For droplet manipulation under external fields, this paper elaborates on various external stimuli including electric fields, thermal fields, optical fields, acoustic fields, and magnetic fields. Among them, electric fields involve actuation mechanisms such as directly applied electrostatic forces and indirectly applied electrocapillary forces; thermal fields influence droplet motion through thermoresponsive wettability gradients and thermocapillary effects; optical fields cover multiple wavelengths including near-infrared, ultraviolet, and visible light; acoustic fields utilize horizontal and vertical acoustic radiation pressure or acoustic wave-induced acoustic streaming for droplet manipulation; the magnetic force acting on droplets may originate from their interior, surface, or external substrates. Based on these different transport principles, this paper comparatively analyzes the unique characteristics of droplet manipulation under the five external fields. Finally, this paper summarizes the current challenges and issues in the research of droplet manipulation on the open planar surfaces and provides an outlook on future development directions in this field. Full article