Search Results (1,521)

Buildings with electrified heat pump systems, onsite photovoltaic (PV) generation, and energy storage offer strong potential for demand flexibility. This study compares two storage configurations, thermal energy storage (TES) and battery energy storage (BESS), to evaluate their impact on cooling performance and cost savings. A Model Predictive Control (MPC) framework was developed to optimize system operations, aiming to minimize costs while maintaining occupant comfort. Results show that both configurations achieve substantial savings relative to a baseline. The TES system reduces daily operating costs by about 50%, while the BESS nearly eliminates them (over 90% reduction) and cuts grid electricity use by more than 65%. The BESS achieves superior performance because it can serve both the controllable heating, ventilation, and air conditioning (HVAC) system and the home’s broader electrical loads, thereby maximizing PV self-consumption. In contrast, the TES primarily influences the thermal load. These findings highlight that the choice between thermal and electrical storage greatly affects system outcomes. While the BESS provides a more comprehensive solution for whole-home energy management by addressing all electrical demands, further techno-economic evaluation is needed to assess the long-term feasibility and trade-offs of each configuration. Full article

Recent theoretical studies have shown that gapped Dirac materials (such as gapped monolayer graphene) optically pumped with circularly polarized light can host edge-localized plasmon modes with nonreciprocal dispersions driven by valley population imbalance. Here, we extend this framework to Bernal-stacked bilayer graphene. Using the Wiener–Hopf method, we compute the exact edge plasmon dispersion, confinement length, and electric potential. Our results show that bilayer graphene exhibits stronger nonreciprocity in edge plasmons, requiring approximately one order of magnitude lower pump amplitude to achieve splitting compared with monolayer Dirac systems. Furthermore, the gate-tunable energy gap of bilayer graphene provides an additional degree of control, positioning optically pumped bilayer graphene as a versatile platform for magnet-free nonreciprocal plasmonics. Full article

High-renewables grids are planned in min but judged in milliseconds; credible studies must therefore resolve both horizons within a single model. Current adequacy tools bypass fast frequency dynamics, while detailed simulators lack multi-hour optimization, leaving investors without a unified basis for sizing storage, shifting demand, or upgrading transfers. We present a two-layer Hierarchical Model Predictive Control framework that links 15-min scheduling with 1-s corrective action and apply it to Germany’s four TSO zones under a stringent zero-exchange stress test derived from the NEP 2045 baseline. Batteries, vehicle-to-grid, pumped hydro and power-to-gas technologies are captured through aggregators; a decentralized optimizer pre-positions them, while a fast layer refines setpoints as forecasts drift; all are subject to inter-zonal transfer limits. Year-long simulations hold frequency within ±2 mHz for 99.9% of hours and below ±10 mHz during the worst multi-day renewable lull. Batteries absorb sub-second transients, electrolyzers smooth surpluses, and hydrogen turbines bridge week-long deficits—none of which violate transfer constraints. Because the algebraic core is modular, analysts can insert new asset classes or policy rules with minimal code change, enabling policy-relevant scenario studies from storage mandates to capacity-upgrade plans. The work elevates predictive control from plant-scale demonstrations to system-level planning practice. It unifies adequacy sizing and dynamic-performance evaluation in a single optimization loop, delivering an open, scalable blueprint for high-renewables assessments. The framework is readily portable to other interconnected grids, supporting analyses of storage obligations, hydrogen roll-outs and islanding strategies. Full article

This research analyzes the energy balance of the purification water pumping system at the La Presa drinking water purification plant (DWPP) in Manises (Valencia) and evaluates alternatives to improve its energy efficiency. These alternatives include the construction of a storage tank at an elevation of 75 m between La Presa Plant and Valencia city, allowing the lower area of the city to be supplied independently from the upper zone. This configuration will adapt to the pressure levels of the whole city and control the residence time in the tanks, thereby improving both energy and quality parameters in the whole network. Hydraulic simulations were conducted in EPANET using models representing the system from the La Presa gallery to the delivery points under various demand scenarios and operational criteria. Three alternatives for feeding the new tank are studied: using additional pumps; using turbines; and a combination of both. From the data obtained in the simulations (flows and heads), the net energy consumed was calculated, and the average water residence time in the tanks was simulated as an indicator of water quality, using certain theoretical criteria. The results indicate that all alternatives represent a significant energy saving and maintain water quality at any moment. The best solution is proposed, which involves combining pumps and turbines and minimizing residence time in the tanks. In this case, a saving of 42.26% of energy is achieved when compared with the actual situation, with an average residence time in the tanks of less than 50 h. The combination of both restrictions of quality and energy savings represents a novelty in the management of future decisions for purification plants supplying real networks. Full article

Background: Type 1 diabetes mellitus (T1DM) is one of the most frequently occurring chronic metabolic conditions in the pediatric and adolescent population. That is why our aim in this study was to compare metabolic control, eating habits, activity, and mental health in patients using insulin pumps with predictive low glucose suspend (PLGS) and advanced hybrid closed loop (AHCL) systems. Methods: We selected 37 patients and collected clinical, continuous glucose monitoring (CGM), and question-naire data (food frequency questionnaire (FFQ-6), physical activity questionnaire for children (PAQ-C), pediatric quality of life inventory (PedsQL). Additionally, all pa-tients participated in culinary workshops, which included education on a low-glycemic-index diet. Results: We observed a significant difference between the PLGS and the AHCL groups for mean glucose, coefficient of variation, and Time in Range (≤54, 70–140, 70–180, ≥180, and ≥250 mg/dL). Patients with higher Time Below Range consumed juices or sugary drinks more frequently. All participants had incor-rect eating habits and engaged in irregular physical activity. Conclusions: We observed no significant differences in the diabetes-specific quality of life scores between the PLGS and AHCL groups. Full article

This study investigates premature fatigue failure in rocker arm gears of large-mining-height shearers operating at alternating ±45° working angles, where insufficient lubrication generates non-uniform thermal -stress fields. In this study, an integrated multiphysics framework combining transient thermal–fluid–structure coupling simulations with fatigue life prediction is proposed. Transient thermo-mechanical coupling analysis simulated dry friction conditions, capturing temperature and stress fields under varying speeds. Fluid–thermal–solid coupling analysis modeled wet lubrication scenarios, incorporating multiphase flow to track oil distribution, and calculated convective heat transfer coefficients at different immersion depths (25%, 50%, 75%). These coupled simulations provided the critical time-varying temperature and thermal stress distributions acting on the gears (Z6 and Z7). Subsequently, these simulated thermo-mechanical loads were directly imported into ANSYS 2024R1 nCode DesignLife to perform fatigue life prediction. Simulations demonstrate that dry friction induces extreme operating conditions, with Z6 gear temperatures reaching over 800 °C and thermal stresses peaking at 803.86 MPa under 900 rpm, both escalating linearly with rotational speed. Lubrication depth critically regulates heat dissipation, where 50% oil immersion optimizes convective heat transfer at 8880 W/m²·K for Z6 and 11,300 W/m²·K for Z7, while 25% immersion exacerbates thermal gradients. Fatigue life exhibits an inverse relationship with speed but improves significantly with cooling. Z6 sustains a lower lifespan, exemplified by 25+ days at 900 rpm without cooling versus 50+ days for Z7, attributable to higher stress concentrations. Based on the multiphysics analysis results, two physics-informed engineering optimizations are proposed to reduce thermal stress and extend gear fatigue life: a staged cooling system using spiral copper tubes and an intelligent lubrication strategy with gear-pump-driven dynamic oil supply and thermal feedback control. These strategies collectively enhance gear longevity, validated via multiphysics-driven topology optimization. Full article

Air source heat pumps (ASHPs) have become a promising alternative to conventional heating and cooling systems, making accurate performance prediction increasingly important. This study presents a comparative analysis of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) models for evaluating the ASHP performance under varying ambient conditions, examining the symmetry or asymmetry of prediction behavior across cold and hot regimes. Two experimental campaigns were carried out in a controlled climate room: the first primarily covering moderate to high temperatures ($-3 °\mathrm{C}$ to $36 °\mathrm{C}$), and the second mainly covering negative and low ambient temperatures ($-16 °\mathrm{C}$ to $18 °\mathrm{C}$). Performance data were collected to capture system behavior under diverse thermal conditions, making predictions more challenging. Both models were optimized, ANFIS through grid partitioning and ANN via architecture selection. Results demonstrate that ANN models achieved a superior overall accuracy, with mean absolute errors of 0.061 to 0.064 for cold and hot ambient conditions, respectively, showing a particularly strong performance under cold conditions. ANFIS demonstrated remarkable robustness in low-temperature predictions, maintaining less than 3% deviation across variations in water inlet temperature. Both approaches revealed temperature-dependent characteristics: cold-condition modeling required more complex architectures but yielded higher precision, whereas warm-condition modeling performed reliably with simpler configurations but showed slightly reduced accuracy. Full article

The blood–brain barrier (BBB) restricts the entry of therapeutic agents into the brain cardiovascular regulatory region, potentially contributing to drug-resistant hypertension. Objective: The objective of this study was to overcome this limitation by modifying PEGylated liposomes with transferrin (Tf) to facilitate Tf receptor binding at the BBB and penetratin (Pen), a cell-penetrating peptide, to enhance neuronal uptake. Methods: This study evaluated the efficacy of Tf-Pen-liposomes in delivering angiotensin-converting enzyme 2 (ACE2) or EGFP (control) genes across the BBB in rats. In addition, the therapeutic effect of intravenous administration of Tf-Pen-Lip carrying plasmid DNA encoding ACE2 (Tf-Pen-Lip-pACE2) was tested in a neurogenic hypertension model induced by intracerebroventricular (ICV) infusion of angiotensin II (Ang II) via osmotic pump implantation and brain cannulation. Results: Conjugation with Tf and Pen significantly enhanced liposome-mediated gene transfection in cultured cells and increased transport across an in vitro BBB model. In vivo, intravenous administration of Tf-Pen-Lip-pACE2 or Tf-Pen-Lip-pGFP successfully elevated ACE2 or EGFP expression, respectively, in the hypothalamic paraventricular nucleus (PVN). Chronic ICV infusion of Ang II produced a sustained increase in blood pressure and heart rate, accompanied by sympathetic overactivation and elevated arginine vasopressin (AVP) secretion, hallmarks of neurogenic hypertension. Notably, intravenous Tf-Pen-Lip-pACE2 treatment dramatically attenuated Ang II–induced neurogenic hypertension, whereas Tf-Pen-Lip-pGFP had no effect on pressor responses, sympathetic activity, or AVP secretion. Conclusions: This dual-functionalized liposomal delivery system effectively transported the ACE2 gene across the BBB into the brain, increased ACE2 expression, and markedly attenuated neurogenic hypertension following systemic administration. Full article

This study evaluated the performance of a hybrid heat pump system integrating photovoltaic–thermal (PVT) panels with a standing column well (SCW) geothermal system in a strawberry greenhouse. The PVT panels, installed over 10% of the area of a 175 m³ greenhouse, stored excess solar heat in an aquifer to offset the reduced efficiency of the geothermal source during extended operation. The results showed that the hybrid system can supply 11,253 kWh of heat energy during the winter, maintaining the night time indoor temperature at 10 °C even when outdoor conditions dropped to −10.5 °C. The PVT system captured 11,125 kWh of solar heat during heating the off season, increasing the heat supply up to 22,378 kWh annually. Additionally, the system generated 3839 kWh of electricity, which significantly offset the 36.72% of the annual pump system electricity requirements, enhancing the system coefficient of performance (COP) of 3.38. Strawberry production increased by 4% with 78% heating cost saving compared to a kerosene boiler system. The results show that the PVT system effectively supports the geothermal system, improving heating performance and demonstrating the feasibility of hybrid renewable energy in smart farms to enhance efficiency, reduce fossil fuel use, and advance carbon neutrality. Full article

The emergence of multidrug-resistant Pseudomonas aeruginosa strains is increasingly becoming a critical threat to global health. Among the resistance mechanisms, the MexAB–OprM efflux pump confers P. aeruginosa with an efficient method to export a broad spectrum of antibiotics. The antimicrobial peptide Esc (1-21)-1c was shown to downregulate this efflux system, though its mechanism of action has not been unveiled thus far. Here, we employed a combination of molecular modeling and experimental methods to investigate the precise peptide inhibitory mechanism. Functional proteomic experiments revealed the P. aeruginosa protein Q9I5H3, homologous to E. coli QseB, as a putative key target of Esc(1-21)-1c. Molecular docking predicted stable peptide–protein interactions, which were experimentally validated through fluorescence spectroscopy. Furthermore, electrophoretic mobility shift assays demonstrated that Q9I5H3 specifically binds the MexAB–OprM promoter and that Esc(1-21)-1c competitively inhibits this interaction in a dose-dependent manner. These findings reveal a previously uncharacterized regulatory pathway for efflux pump control and highlight Q9I5H3 as a promising therapeutic target against multidrug-resistant P. aeruginosa. Full article

The interaction between groundwater and surface water can be significant in lakes or irrigation channels, as well as in large dam reservoirs or along portions of them. To evaluate this interaction at a sampling location directly controlled by a large dam equipped with reversible pump-turbines, data from Rn-222 and physicochemical parameters at specific depths and times were obtained and studied using Principal Component Analysis and Hierarchical Clustering. Dimension 1 explains 45.3% of the total variability in the original data, which can be interpreted as the result of external factors related to seasonal variability (e.g., temperature, turbulent flow, and precipitation), while Dimension 2 explains up to 31.2% and can be interpreted as the variability related to groundwater inputs. Five hierarchical clusters based on these dimensions were considered and were related to the temporal variability observed in the water column throughout the year, as well as the depth relationships observed between successive surveys. A hypothesis-driven conceptual piston-like effect model is proposed for groundwater–surface water interactions, considering the identified relationships between variables, including higher Rn-222 concentrations in surface water after heavy rain. According to this simplified conceptual model, water infiltrates in a weathered granitic recharging area; during heavy rain, it is forced through the fracture systems of a lesser-weathered granite. Thus, an overall increase in pressure over the hydrological system forces the older radon-enriched water to discharge into the Mondego River. This work highlights the importance of exploratory techniques such as PCA and Hierarchical Clustering, in addition to underlying knowledge of the geological setting, for the proposal of simplified conceptual models that help in the management of important reservoirs. This work also demonstrates the utility of Rn-222 as a simple tracer of groundwater discharge into surface water. Full article

Fault slips induced by hydraulic fracturing are the primary mechanism of casing de-formation during deep shale gas development in Sichuan’s Luzhou Block, where de-formation rates reach 51% and severely compromise productivity. To address a critical gap in existing research on quantitative risk assessment systems, we developed a probabilistic model integrating pore pressure evolution dynamics with Monte Carlo simulations to quantify slip risks. The model incorporates key operational parameters (pumping pressure, rate, and duration) and geological factors (fault friction coefficient, strike/dip angles, and horizontal stress difference) validated through field data, showing >90% slip probability in 60% of deformed well intervals. The results demonstrate that prolonged high-intensity fracturing increases slip probability by 32% under 80–100 MPa pressure surges. Meanwhile, an increase in the friction coefficient from 0.40 to 0.80 reduces slip probability by 6.4% through elevated critical pore pressure. Fault geometry exhibits coupling effects: the risk of low-dip faults reaches its peak when strike parallels the maximum horizontal stress, whereas high-dip faults show a bimodal high-risk distribution at strike angles of 60–120°; here, the horizontal stress difference is directly proportional to the slip probability. We propose optimizing fracturing parameters, controlling operation duration, and avoiding high-risk fault geometries as mitigation strategies, providing a scientific foundation for enhancing the safety and efficiency of shale gas development. Full article

Probiotics like Lactobacillus sp. are extensively studied for their beneficial host interactions, including the gut–brain axis, anti-inflammatory effects, immune system interactions, restoration of gut dysbiosis, and anti-aging effects. In the current study, pearl millet was fermented with Lactobacillus plantarum strains DHCU 70 and MCC 5231, which enhanced the nutritional, bioactive, and functional properties of derived probiotic beverages. Compared to unfermented controls, fermented beverages exhibited increased protein content and vitamins B₁, B_2, and B₃, with decreased carbohydrate and dietary fiber levels. The probiotics have maintained viability exceeding 12 log CFU/mL and showed resistance to harsh gastrointestinal conditions. Fermentation increased total phenolic content from 13.38 ± 0.40 mg GAE/100 g to 42.10 ± 2.65 mg GAE/100 g (LPDB) and 47.76 ± 1.37 mg GAE/100 g (LPMB) and total flavonoid content from 13.01 ± 1.18 mg QE/100 g to 23.12 ± 2.73 mg QE/100 g and 24.21 ± 0.98 mg QE/100 g, respectively. Antioxidant assays showed DPPH radical scavenging improved by 37%, ferrous ion chelation rose from 71.69 ± 0.09 mg TE/100 g to 91.45 ± 0.006 mg TE/100 g, ABTS scavenging increased from 71.62 mg TE/100 g to 82.51 ± 0.04 mg TE/100 g (LPDB) and 89.74 ± 0.04 mg TE/100 g (LPMB) and superoxide radical inhibition rose from 51.40 ± 0.98% to 81.77 ± 0.03% (LPDB) and 79.92 ± 0.02% (LPMB). In the in vivo model, Caenorhabditis elegans, fermented beverage treatments significantly improved health-span parameters like head-swing frequency (13.51% increase), body bend frequency (8.41% increase), pharyngeal pumping (8.15% increase) with reduced lipofuscin accumulation and intracellular reactive oxygen species while median lifespan extended beyond 24 days versus 14–16 days in controls (p < 0.05). Gompertz mortality modeling revealed a significant decrease in the aging rate parameter, indicating systemic mitigation of stress-induced physiological decline. These combined nutritional, bioactive, and in vivo longevity results underscore the potential of L. plantarum-fermented pearl millet beverages as functional nutraceuticals that target oxidative stress and promote healthy aging. Full article

With buildings accounting for 40% of global energy consumption, heating, ventilation, and air conditioning (HVAC) systems represent the single largest opportunity for emissions reduction, consuming up to 60% of commercial building energy while maintaining occupant comfort. This critical balance between energy efficiency and human comfort has traditionally relied on rule-based and model predictive control strategies. Given the multi-objective nature and complexity of modern HVAC systems, these approaches fall short in satisfying both objectives. Recently, reinforcement learning (RL) has emerged as a method capable of learning optimal control policies directly from system interactions without requiring explicit models. However, standard RL approaches frequently violate comfort constraints during exploration, making them unsuitable for real-world deployment where occupant comfort cannot be compromised. This paper addresses two fundamental challenges in HVAC control: the difficulty of constrained optimization in RL and the challenge of defining appropriate comfort constraints across diverse conditions. We adopt a safe RL with a neural barrier certificate framework that (1) transforms the constrained HVAC problem into an unconstrained optimization and (2) constructs these certificates in a data-driven manner using neural networks, adapting to building-specific comfort patterns without manual threshold setting. This approach enables the agent to almost guarantee solutions that improve energy efficiency and ensure defined comfort limits. We validate our approach through seven experiments spanning residential and commercial buildings, from single-zone heat pump control to five-zone variable air volume (VAV) systems. Our safe RL framework achieves energy reduction compared to baseline operation while maintaining higher comfort compliance than unconstrained RL. The data-driven barrier construction discovers building-specific comfort patterns, enabling context-aware optimization impossible with fixed thresholds. While neural approximation prevents absolute safety guarantees, reducing catastrophic safety failures compared to unconstrained RL while maintaining adaptability positions this approach as a developmental bridge between RL theory and real-world building automation, though the considerable gap in both safety and energy performance relative to rule-based control indicates the method requires substantial improvement for practical deployment. Full article

Floating photovoltaic (FPV) systems are promising for coastal aquaculture where reliable electricity is essential for pumping, oxygenation, sensing, and control. A sustainable FPV–storage hybrid tailored to monsoon-prone sites is developed, with emphasis on energy efficiency and structural resilience. The prototype combines dual-axis solar tracking with a spray-cooling and cleaning subsystem and an active wind-protection strategy that automatically flattens the array when wind speed exceeds 8.0 m/s. Temperature, wind speed, and irradiance sensors are coordinated by an Arduino-based supervisor to optimize tracking, thermal management, and tilt control. A 10 W floating module and a fixed-tilt reference were fabricated and tested outdoors in Penghu, Taiwan. The FPV achieved a 25.17% energy gain on a sunny day and a 40.29% gain under overcast and windy conditions, while module temperature remained below 45 °C through on-demand spraying, reducing thermal losses. In addition, a hybrid energy storage system (HESS), integrating a 12 V/10 Ah lithium-ion battery and a 12 V/24 Ah lead-acid battery, was validated using a priority charging strategy. During testing, the lithium-ion unit was first charged to stabilize the control circuits, after which excess solar energy was redirected to the lead-acid battery for long-term storage. This hierarchical design ensured both immediate power stability and extended endurance under cloudy or low-irradiance conditions. The results demonstrate a practical, low-cost, and modular pathway to couple FPV with hybrid storage for coastal energy resilience, improving yield and maintaining safe operation during adverse weather, and enabling scalable deployment across cage-aquaculture facilities. Full article