Search Results (5,380)

Under varying demand, pump states, load allocation, speed settings, and supply pressure are strongly coupled in parallel pumping systems. This study develops a steady-state energy-efficiency optimization framework for homogeneous and heterogeneous three-branch systems by integrating continuous pump-performance modeling, hard hydraulic-feasibility handling, mixed-variable optimization, and demand-dependent pressure regulation. An improved snake optimizer (ISO) is constructed through targeted strategies for population initialization, global exploration, and local exploitation. Flow–head and flow–power models established from LVR5-5 and CDL3-50 experimental data achieved a total-power MAPE of 2.36% and R² = 0.9972 over 40 implemented steady-state schemes. Deterministic constrained solutions for all effective pump-state combinations were used as references for the pumping-system optimization. Under the same budget of 21,000 function evaluations, ISO, SO, PSO, DE, and GA completed 1500 independent runs; ISO achieved the best overall search performance, with all 300 runs reaching the 0.1% neighborhood of the reference solution and the lowest mean NAUC and final gaps. Using ISO for both pressure-control modes, variable-pressure operation reduced mean power consumption by 10.92% and 7.51% for the homogeneous and heterogeneous systems, respectively, relative to constant-pressure operation under the same minimum service-pressure requirement. The results demonstrate that combining high-quality mixed-variable optimization with demand-dependent pressure regulation can effectively improve the steady-state energy efficiency of parallel pumping systems. Full article

Distributed generation (DG) is reshaping distribution networks through bidirectional power flows, operational variability, and dependence on coordinated regulation, pricing, and control. This paper examines how regulatory architecture, grid-code requirements, tariff design, and Distributed Energy Resource Management Systems (DERMS) influence DG integration, emphasizing Honduras. A structured mixed-source review is applied, combining Scopus-based bibliometric analysis of 2438 records (2000–2026) with targeted synthesis of technical, regulatory, tariff-related, and institutional sources. The bibliometric results show sustained growth and a thematic shift from conventional voltage-control studies toward active distribution networks, DER coordination, storage, demand response, tariff reform, and digital energy management. The analytical synthesis shows that effective DG integration requires more than interconnection compliance: it depends on grid-support functions, cost-reflective and equitable tariffs, and operational tools capable of managing voltage deviations, reverse power flow, congestion, protection coordination, and limited visibility. DERMS is an enabling layer for voltage control, active and reactive power management, congestion mitigation, adaptive protection, and predictive operation. For Honduras, current regulatory progress should be complemented by phased modernization focused on observability, smart metering, data infrastructure, local flexibility, and progressive DERMS deployment. The study provides an integrated framework for aligning regulatory, economic, and operational dimensions of DG integration in emerging distribution systems. Full article

Background/Objectives: Adeno-associated virus (AAV) capsids undergo pH-dependent conformational gating at the 5-fold symmetry pore, but how these structural dynamics shape serotype-specific behavior and affinity-ligand recognition remains unclear, particularly for the clinically important serotypes AAV8 and AAV9. This study aimed to establish a pH-resolved structural framework linking 5-fold pore dynamics to peptide-ligand recognition and to translate this framework into sequence-based design principles for affinity capture of gene therapy vectors. Methods: AAV8 and AAV9 5-fold capsid assemblies were subjected to 500 ns molecular dynamics simulations under acidic (pH 5), neutral (pH 7), and basic (pH 9) conditions, with analysis of pore volume, inter-residue contact networks, electrostatic potential, and solvent-accessible surface area. In parallel, affinity chromatography using three mixed-mode peptide ligands (RVVAVYRI, TTFRAHHI, and TYHHHHII) was performed on clarified HEK293 lysates containing AAV8 or AAV9, with capsid yield, host-cell-protein clearance, and transduction activity assessed by ELISA, SEC-HPLC, and flow-cytometry-based transduction assays. Results: AAV8 displayed a heterogeneous, bimodal pore conformational landscape at pH 7, whereas AAV9 exhibited a discrete gate-like transition with maximal pore constriction at physiological pH; both serotypes showed pore-proximal contact remodeling with distinct network topologies. Experimentally, TYHHHHII achieved the highest selectivity for genome-containing capsids at pH 7, with transduction activity enrichment factors of 2.82 (AAV8) and 5.61 (AAV9), while TTFRAHHI provided the broadest operational pH range for bulk capsid recovery. Conclusions: These findings establish a structural framework linking pH-dependent pore dynamics to affinity ligand recognition and suggest practical sequence-design rules for ligand engineering: clustered histidines for neutral-pH selectivity, Arg-containing motifs for broad-pH robustness, and aromatic or hydrophobic residues for reinforcement of capsid binding. Full article

Copper and lead contamination in loess areas poses a potential threat to soil environmental quality and sustainable land use, while the low permeability, high clay content, and strong buffering capacity of loess often limit the efficiency of conventional electrokinetic (EK) remediation. In this study, a modified activated carbon–carbon fiber (MAC–CF) composite reactive barrier was introduced into an EK remediation system to enhance the soil-phase depletion of Cu and Pb from contaminated loess. The effects of ordinary activated carbon (AC), MAC, CF, and different MAC–CF mixing ratios on current, cumulative electroosmotic flow (EOF), soil pH, electrical conductivity (EC), and potentially toxic metal (PTM) removal were systematically investigated. The conventional AC barrier increased system resistance and inhibited current transmission and EOF. The MAC barrier exhibited enhanced OH⁻ adsorption and buffering capacity, decreasing the cathode-adjacent pH from approximately 9.8 to 8.8. CF incorporation improved barrier conductivity, increasing the peak current from 1.6 A for MAC (100%) to 4.0 A for MAC (25%) + CF (75%), while cumulative EOF increased from approximately 380 to 950 mL. The MAC (25%) + CF(75%) barrier provided the best balance between conductivity enhancement and cathodic alkalization regulation. Sectional Cu removal reached approximately 90% near the anode, whereas Pb removal ranged from approximately 18% to 29%, with a section-weighted mean of about 24.8%. The corresponding residual Pb concentrations (approximately 355–410 mg kg⁻¹) indicate that the system is more effective for Cu and would require additional treatment to meet a conservative agricultural-soil target for Pb. The results support complementary functions of CF in maintaining conductive pathways and MAC in regulating cathodic alkalization. Because Cu and Pb in the spent barrier and electrolyte chambers were not quantified, the proposed precipitation-suppression and migration mechanisms are interpreted from the combined electrochemical, pH, EC, adsorption, and soil-residual evidence rather than from a complete metal mass balance. Full article

Background: Cystic fibrosis (CF) is an inherited multisystemic disease. Despite advances in treatment, many patients still experience progressive lung dysfunction. Dental follicle-derived mesenchymal stem cells (DF-MSCs) possess significant immunomodulatory potential in inflammatory airway diseases. We evaluated the effects of DF-MSCs on lymphocyte proliferation, CD4⁺CD25⁺FoxP3⁺ regulatory T cell (Treg) frequency, and cytokine responses in peripheral blood mononuclear cells (PBMCs) from CF patients. Methods: PBMCs from 20 CF patients and 20 matched healthy controls were isolated by density gradient centrifugation, stimulated with a CD3/CD28 T-cell-activating antibody cocktail (CD-mix), and co-cultured ex vivo with cryopreserved DF-MSCs. Lymphocyte proliferation was assessed by carboxyfluorescein succinimidyl ester (CFSE)-based flow cytometry, and Tregs were analyzed by flow cytometry. Cytokine levels in culture supernatants were quantified using a multiplex immunoassay. Results: DF-MSC co-culture significantly suppressed lymphocyte proliferation in CF PBMCs. Treg frequency significantly increased in the stimulated CF samples following MSC co-culture. Following co-culture, levels of tumor necrosis factor-alpha (TNF-α), interleukin-8 (IL-8), and IL-23 decreased. In CF samples, levels of interferon-alpha 2 (IFN-α2), monocyte chemotactic protein-1 (MCP-1), interleukin-12 (IL-12), interleukin-18 (IL-18), and interleukin-33 (IL-33) were elevated. Conclusions: DF-MSCs reduced lymphocyte proliferation, increased Treg frequency, and regulated cytokine levels in CF, supporting their potential to restore immune balance. Full article

Proposed in this paper is a systematic methodology to identify cementitious paste mix design and printing parameters suitable for yielding dimensionally accurate 3D-printed specimens. Using a Box–Behnken surface response experimental design approach, the first work phase generated mathematical models to predict ink flow based on the paste water–binder ratio and dosage of superplasticising and viscosity-modifying admixtures. In the second work phase, favourable mixes were investigated further, again using a Box–Behnken surface response experimental design and corresponding mathematical models to predict printing accuracy in relation to printing parameters including ranges of print speed, extrusion multipliers and layer height. Confirmed by parallel preliminary print trials, favourable ink mix designs were efficiently identified for inks comprising either Portland cement only, or ternary blends of calcined clay, silica fume and Portland cement. For the Portland cement binder, the favourable mix design comprised a water–binder ratio of 0.26 and superplasticising and viscosity-modifying admixture dosages of 1.12% and 1.10% by mass of the binder respectively. Corresponding values for the calcined clay/silica fume/Portland cement binder ink were 0.27, 1.1% and 1.1% respectively. For both binder types, corresponding favourable values of the above listed print parameters were identified as 5 mm/s, 1.1% and 1.0 mm respectively. In the final work phase, the outputs from phases one and two were validated via print trials of hollow cube, beam, hexagonal and circular elements enabling measurements of the dimensional accuracy and buildability. With deviations in element height and width ranging from only ±0.3 to 2.6% from corresponding CAD designs, the appropriateness of the methodology was established. Full article

This study investigates the network-level traffic and safety effects of increasing Market Penetration Rate (MPR) of SAE Level 2 and Level 3 automated vehicles under take-over conditions. A calibrated microsimulation model of a real-world 50 km highway corridor in Greece (Nea Odos) was used to develop 18 scenarios combining two take-over contexts (Lane Closure and ODD Exit), two Time Budget (TB) configurations, and four MPR levels (25–100%), complemented by two baselines. Traffic performance was assessed through five network-level indicators (speed, delay, lane-changing frequency, travel time, and density). Safety was evaluated through 674 conflict events extracted via the Surrogate Safety Assessment Model (SSAM), using Time-to-Collision (TTC) as the primary indicator. MPR is the dominant feature of both dimensions. Increasing MPR produces a monotonic reduction in speed (−19.2% at 100% MPR), a sharp decline in lane-changing (−59.8%), and increases in density (+21.1%) and travel time (+22.4%), delay peaks non-monotonically at 50% MPR (+107.9%). Spearman correlations between MPR and the traffic indicators are very strong for speed, lane changes, travel time, and density, while delay time yields a weaker correlation reflecting its non-monotonic response. All operating points remain within free-flow conditions throughout the MPR range. The MPR effect on TTC is marginal (p = 0.065) but non-monotonic, with 75% MPR yielding significantly higher mean TTC than 50% and 100% MPR. Neither TB duration nor TOR context produces a statistically significant effect on traffic indicators or TTC distributions, with negligible effect sizes in both cases. Traffic costs of mixed-traffic automation appear at partial penetration, while network-level safety benefits remain limited and non-linear. Full article

This study addresses a large-scale location–allocation problem in a three-echelon automotive supply chain comprising 382 suppliers, candidate distribution centers, and six assembly plants. The planning task is to redesign the inbound consolidation network while minimizing transportation and distribution center operating costs, enforcing a 480 km supplier-to-center service radius, and achieving at least 90% demand-weighted coverage. We formulate a mixed discrete-continuous model with supplier-to-center assignment, center location, throughput, and flow decisions. A feasibility-oriented hybrid algorithm uses a genetic algorithm as the main search engine, ant colony construction to seed solutions near the feasible region, adaptive mutation and simulated annealing to preserve exploration and refine elite solutions, and an online neural surrogate to avoid a subset of costly exact fitness evaluations. The design differs from a simple collection of metaheuristics: all components share one variable-length encoding, the same feasibility metrics, and periodic exact reevaluation of candidate solutions. Using the competition case data, the redesigned network reduces total cost by 27.0% relative to the six-center baseline, decreases the demand-weighted average supplier-to-center distance from 461.3 km to 53.0 km, lowers the maximum distance from 2807.22 km to 441.78 km, and raises coverage from 45.0% to 100%. Across ten independent runs, the hybrid method obtains a mean cost 10.3% below that of a standard genetic algorithm, with lower run-to-run dispersion. The results show that feasibility-aware initialization, adaptive search, and selective surrogate evaluation can support practical redesign of a strongly constrained, national-scale inbound logistics network. The directly attached reproducibility package provides the MATLAB implementation and the seven supplied input workbooks used by the reported model. The evidence is limited to one deterministic competition instance, a fixed cost schedule, and fixed-topology sensitivity calculations; generalization under demand uncertainty, facility disruption, and alternative road conditions remains to be tested. Full article

This paper investigates distributed optimization-assisted output consensus for nonlinear multi-agent systems with mutually incommensurate Caputo orders, unavailable velocity-like states, bounded disturbances, measurement noise, and actuator saturation. A mixed-power exact penalty flow generates practical optimal references from local costs and intermittent neighbor broadcasts. The penalty gain and a smoothing bias bound are determined from a public interval, topology information, and certified local gradient data without prior knowledge of the aggregate optimizer. An autonomous decaying threshold provides event-triggered communication, an initial condition-independent fixed-time practical certificate for the integer-order optimizer, and exclusion of finite-time event accumulation. The physical layer is analyzed with established Caputo quadratic inequalities and agentwise Mittag–Leffler comparison. Fractional reference and command filters, a composite observer, and two-gain anti-saturation compensation form the output feedback controller, while the physical result is formulated as a finite-horizon regional verification certificate. Numerical studies include same-model and communication budget comparisons, a recent method-inspired optimizer benchmark, certificate tightening, and robustness tests for initialization, the fractional order, measurement noise, and the integration step size. Full article

Heart failure (HF) is a systemic syndrome in which prognosis depends on cardiac dysfunction, congestion, cardiorenal and cardiohepatic interactions, inflammation, and metabolic dysregulation. The liver is exposed to elevated systemic venous pressure and reduced forward flow, and contributes to albumin and coagulation factor synthesis, bile acid metabolism, iron homeostasis, and the acute-phase response. Cardiohepatic injury involves hemodynamic stress, sinusoidal endothelial dysfunction, oxidative stress, inflammatory signaling, fibrogenesis, and altered metabolic regulation. Congestive hepatopathy is associated with right-sided HF, tricuspid regurgitation (TR), pulmonary hypertension, and elevated central venous pressure, whereas hypoxic hepatitis develops during low-output states, shock, or acute circulatory deterioration. These mechanisms may coexist, producing congestive/cholestatic, hypoperfusive/ischemic and mixed/systemic reserve profiles. Composite liver-related scores, including Model for End-Stage Liver Disease (MELD), MELD excluding International Normalized Ratio (MELD-XI), MELD with sodium (MELD-Na), MELD-Albumin and albumin–bilirubin (ALBI) score, may reflect congestion, hepatorenal dysfunction, nutritional status and reduced systemic reserve. This review summarizes hemodynamic and molecular mechanisms of cardiohepatic injury, liver-related biomarkers and composite scores, with emphases on advanced HF, left ventricular assist device (LVAD) therapy and heart transplantation. Liver-related abnormalities remain underrecognized in HF. Their serial interpretation may support risk stratification, but composite scores should complement rather than replace comprehensive clinical assessment. Full article

The introduction of Connected and Autonomous Vehicles (CAVs) into the existing traffic system represents one of the greatest challenges of modern road traffic engineering. Beyond their role as active traffic participants, CAVs can also be regarded as mobile (floating) sensors, effectively turning the vehicle fleet itself into a distributed, city-wide and motorway-wide sensing infrastructure. The transition from fully human-driven vehicles to fully autonomous vehicles will take decades, giving rise to a prolonged mixed-traffic period in which vehicles with different levels of automation share the same road space. This paper analyses the parameters and measures used for evaluating the throughput, environmental impact, and safety of traffic networks at different CAV penetration rates. It further reviews studies that rely exclusively on data collected from CAVs acting as mobile sensors, examining data-aggregation and traffic-state-estimation methods used to reconstruct macroscopic traffic parameters such as flow, density, headway, and speed. Additionally, measures for evaluating specific use cases for CAVs including mobility-on-demand services and their cost comparison with human-driven taxi operations are also addressed. The energy and emissions implications of CAV deployment, including the added burden of sensing hardware and system-level rebound effects, are also examined. Based on the synthesis performed, a set of representative CAVs penetration rates is proposed as a standardised framework for future mixed-traffic flow evaluations. Full article

To address the core industrial bottlenecks of conventional batch tannic acid-based germanium precipitation processes—high reagent consumption, long reaction cycles of several hours, severe impurity co-precipitation as well as the common mismatch between single-channel microreactor throughput and industrial production demands. This work combines numerical simulation with experimental validation to investigate microscale two-phase flow regulation, high-throughput microreactor optimization, and tannic acid precipitation intensification. Two-dimensional two-phase flow models are established for straight and zigzag microchannels, with the level set method applied to track interfacial evolution. The regulatory effects of inlet velocity and channel geometry on flow patterns, droplet behavior and mixing performance are clarified. Zigzag channels induce chaotic convection via periodic corners, achieving an order-of-magnitude improvement in mixing efficiency at low Reynolds numbers (Re < 400), which lays a fundamental basis for reaction intensification. Taking zigzag channels as core units, a bidirectional symmetric superposition scale-up strategy is proposed to break the throughput limitation of single-channel systems, and a 3D-printed high-throughput microreactor integrating 78 parallel zigzag channels is designed. 3D simulations reveal a three-stage mixing mechanism and uniform flow distribution among parallel channels, with total throughput two orders of magnitude higher than a single channel. Single-channel experiments with industrial germanium-bearing raffinate yield 91.81% precipitation efficiency under optimal conditions, reducing the reaction residence time from hours in conventional batch processes to the second scale. Staged reagent addition and two-stage serial configuration further raise the efficiency to ~98%, realizing deep germanium recovery with significantly improved reagent utilization and reduced impurity co-precipitation. This process achieves efficient intensification of the chelation precipitation process while balancing throughput and mixing performance, providing a novel and technically feasible approach for efficient low-consumption germanium recovery, and offering solid technical support for the industrial application of microreactors in the hydrometallurgy field. Full article

The coordinated operation of interconnected multi-carrier energy hubs is a key enabler of cost-efficient and flexible energy management in modern smart cities. This paper develops a comprehensive optimization framework for the day-ahead scheduling of interconnected energy hubs in residential and commercial sectors. The problem is formulated as a mixed-integer linear programming (MILP) model that jointly manages electricity, natural gas, and thermal energy flows. To enhance operational flexibility, the proposed model incorporates demand response programs for both electrical and thermal loads, multiple energy storage technologies, and electric vehicles with vehicle-to-grid (V2G) capability. Six operating scenarios are defined to assess the impact of different resources and coordination levels, ranging from independent hub operation to fully integrated interconnected scheduling. Simulation results show that coordinated operation of the energy hubs, supported by flexible loads, storage systems, and electric vehicles, can significantly reduce total daily operating costs compared with conventional standalone configurations. The findings confirm that energy exchange among hubs, combined with demand-side flexibility and EV participation, improves both economic performance and system efficiency. The proposed framework offers a scalable scheduling approach for future integrated multi-energy systems. Full article

Extreme weather couples spatially correlated component damage with photovoltaic (PV) derating, changing electric-vehicle (EV) demand, repair delay, and time-varying network topology. This paper develops a coordinated restoration architecture for multi-area feeders containing PV, battery energy storage, and charging stations. Its weather-facing layer constructs joint outage-risk, renewable-error, charging-demand, and voltage-vulnerability descriptors. Those descriptors parameterize a two-stage mixed-integer second-order-cone program with a finite-support optimal-transport ambiguity set that remains well defined for discontinuous mixed-integer recourse. Regional actor–critic agents propose five-minute corrections around the hourly robust schedule; constrained projection, non-linear AC power-flow screening, emergency fallback, and margin-tightened re-optimization retain the authority to accept or reject each proposal. The evaluation uses public 33-node and 123-node feeders together with synthetic 240-node and 850-node stress networks. A pre-fit manifest allocates 240 records to training, 80 to validation, and 320 to final testing, while aggregate operational outcomes cover 50 random streams. Within this controlled benchmark, accepted schedules restore 93.6% of critical-load energy (SD 2.1 percentage points), serve 96.7% of total demand (SD 1.8 percentage points), retain 82–86% of EV service across hazard classes, and reduce the modeled 24 h objective by 25.8% relative to deterministic dispatch. The full pipeline records two to four candidate-stage voltage-limit events by hazard, and 4.9% of candidates undergo tightened re-optimization before accepted schedules reach zero reported AC voltage-limit violations. Between-method comparisons are descriptive and unpaired; the larger synthetic cases are structural stress tests rather than feeder-transfer tests. Full article

In recent years, hydrogen-fueled internal combustion engines offer significant potential for achieving high efficiency and near-zero carbon emissions. However, stable combustion remains challenging due to the limited time available for fuel–air mixing, particularly in direct-injection concepts. This study investigates the influence of injector orientation on in-cylinder charge preparation in a heavy-duty spark-ignition engine operating with a side-mounted hydrogen direct-injection strategy. Three-dimensional computational fluid dynamics (CFD) simulations are performed to evaluate the effects of injector blow-cap inclination and azimuthal alignment on hydrogen jet evolution, flow-field development, and mixture formation. Under high-pressure injection conditions, hydrogen enters the cylinder as a highly under-expanded jet with strong momentum, resulting in significant interaction with the in-cylinder flow field. The results show that injector inclination influences jet impingement behavior, wall-guided flow development, and subsequent vortex evolution, while injector rotation modifies the interaction between the jet trajectory and in-cylinder swirl motion, affecting aerodynamic shear and flow-field complexity. The resulting mixture formation is evaluated through local air–fuel ratio distribution together with flow-field analysis and streamline evolution, demonstrating strong sensitivity to injector orientation and its coupling with in-cylinder aerodynamic structures. Quantitatively, injector orientation produces significant changes in the local air–fuel ratio distribution, with up to 25% reduction in the standard deviation of local air–fuel ratio for inclination variations and up to 35% for azimuthal variations between the extreme configurations, indicating improved mixture uniformity. Configurations promoting earlier jet disruption and enhanced spatial dispersion achieve more homogeneous charge preparation, whereas stronger wall-guided jet attachment results in localized fuel-rich regions. The findings provide physical insight into the role of jet–wall interaction, aerodynamic shear, and vortex restructuring in governing hydrogen mixing processes. The simulation framework captures the relevant in-cylinder flow physics and provides trends consistent with available experimental observations in the literature, which report improved efficiency and reduced NOx emissions under enhanced mixture homogeneity conditions. Full article