Search Results (87)

This study investigates the structure of a metal hydride (MH) cartridge as a hydrogen storage tank for small-scale fuel cells (FCs). This cartridge is designed to be stacked and used in layers, allowing flexible capacity adjustment according to demand. MH enables compact and safe hydrogen storage for small-scale fuel cell (FC) applications due to its high energy density and low-pressure operation. However, because hydrogen desorption from MH is an endothermic reaction, an external heat supply is required for stable performance. To enhance both the heat transfer efficiency and cartridge usability, we propose a heat supply method that utilizes waste heat from an air-cooled proton-exchange membrane fuel cell (PEMFC). The proposed cartridge incorporates four cylindrical MH tanks that require uniform heat transfer. Therefore, we proposed the tank arrangements within the cartridge to minimize the non-uniformity of heat transfer distribution on the surface. The flow of exhaust air from the PEMFC into the cartridge was analyzed using computational fluid dynamics (CFD) simulations. In addition, an empirical correlation for the Nusselt number was developed to estimate the heat transfer coefficient. As a result, it was concluded that the heat utilization rate of the exhaust heat flowing into the cartridge was 13.2%. Full article

Background: Overactive bladder (OAB) has been linked to abnormal cerebral blood flow (CBF) and functional connectivity (FC). However, findings related to CBF and FC changes in OAB remain inconsistent across the literature. Methods: This feasibility study employed arterial spin labeling (ASL) to investigate abnormal CBF and posterior cingulate cortex (PCC) FC in individuals with OAB, both at rest and during bladder filling. ASL images were collected from twenty-two female participants (twelve with OAB and ten healthy controls) at bladder filling volumes of 0, 50, 100, 200, 350, and 500 mL. For OAB participants, scans were obtained both at baseline and following a single-session treatment. ASL images were categorized into low-urge and high-urge conditions based on participants’ subjective urge rating during bladder filling. A flexible factorial design was implemented with three factors: subject, group (control, OAB at baseline, and OAB posttreatment), and urge state (low vs. high). Results: Compared to controls, OAB participants exhibited significant decreases in ΔCBF (high urge minus low urge) in the medial prefrontal cortex and increases in ΔCBF in the supramarginal region. Additionally, ΔPCC FC with the insula was reduced in OAB participants. Posttreatment, OAB participants showed increased ΔPCC FC with the postcentral and parietal (PocP), regions associated with the sensorimotor network. Notably, changes in ΔPCC-PocP FC were associated with improvements in OAB symptoms. Conclusions: These findings support the feasibility of using ASL to probe dysfunctional brain–bladder control mechanisms and treatment-related changes in OAB participants, highlighting the involvement of sensory processing and attention regulation in this condition. Full article

The ongoing demand for reliable, cost-effective, and scalable diagnostic solutions during the COVID-19 pandemic emphasized the need for innovative production platforms. In this study, we present a plant-based molecular farming (PMF) strategy for the production of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein fused with an Fc region (RBDw-Fc). The RBDw-Fc antigen was transiently expressed in the Nicotiana benthamiana plant, achieving high yields and purity. Its functionality was assessed through antigen–antibody binding assays. The purified antigen was subsequently employed in the development of a rapid diagnostic blot assay capable of screening plasma EDTA samples from pre- and post-vaccinated as well as pre- and post-infected individuals, demonstrating high sensitivity and specificity. Our results show that the RBDw-Fc-based assay is effective for SARS-CoV-2 detection and offers considerable advantages in terms of production speed, scalability, and cost efficiency compared to traditional systems, such as cell-culture-based production. The assay delivers accurate results in just a few minutes, making it particularly suitable for clinical and resource-limited settings. This study highlights the versatility of PMF as a platform for producing high-quality reagents, with promising applications beyond SARS-CoV-2 diagnostics. The RBDw-Fc antigen-based method provides a model for the rapid, economical, and flexible development of screening tools for emerging infectious diseases and future pandemics. Full article

Physiologically based pharmacokinetic (PBPK) modelling for biologics, such as monoclonal antibodies and therapeutic proteins, involves capturing complex processes, including target-mediated drug disposition (TMDD), FcRn-mediated recycling, and tissue-specific distribution. The Simcyp Designer Biologics PBPK Platform Model offers an intuitive and efficient platform for constructing mechanistic PBPK models with pre-defined templates and automated model assembly, reducing manual input and improving reproducibility. This tutorial provides a step-by-step guide to using the platform, highlighting features such as cross-species scaling, population variability simulations, and flexibility for model customization. Practical case studies demonstrate the platform’s capability to streamline workflows, enabling rapid, mechanistic model development to address key questions in biologics drug development. By automating critical processes, this tool enhances decision-making in translational research, optimizing the modelling and simulation of large molecules across discovery and clinical stages. Full article

Time-resolved fluorescence techniques, such as fluorescence lifetime imaging microscopy (FLIM), fluorescence correlation spectroscopy (FCS), and time-resolved fluorescence spectroscopy, are ideally suited for investigating molecular dynamics and interactions in biological and chemical systems. However, the analysis and interpretation of these datasets require advanced computational tools capable of handling diverse models and datasets. This paper presents a comprehensive software solution designed for model generation and analysis of time-resolved fluorescence data with a strong focus on fluorescence for quantitative structural analysis and biophysics. The software supports the integration of multiple fluorescence techniques and provides users with robust tools for performing complex model analysis across diverse experimental data. By enabling global analysis, model generation, data visualization, and sampling over model parameters, the software enhances the interpretability of intricate fluorescence phenomena. By providing flexible modeling capabilities, this solution offers a versatile platform for researchers to extract meaningful insights from time-resolved fluorescence data, aiding in the understanding of dynamic biomolecular processes. Full article

Type 1 protein phosphatases (PP1s) are crucial in various plant cellular processes. Their function is controlled by regulators known as PP1-interacting proteins (PIPs), often intrinsically disordered, such as Inhibitor 2 (I2), conserved across kingdoms. The durum wheat TdRL1 acts as a positive regulator of plant stress tolerance, presumably by inhibiting PP1 activity. In this work, co-immunoprecipitation and bimolecular fluorescence complementation (BiFC) assays demonstrate that the durum wheat TdPP1 interacts with both TdRL1 and At-I2 in vivo. YFP fluorescence restored after TdRL1-TdPP1 interaction decorated specifically the microtubular network of the tobacco co-infiltrated cells. In vitro phosphatase assays revealed that TdRL1 inhibited the activity of wild-type TdPP1 and two mutant forms (T243M and H135A) in a concentration-dependent manner, showing a novel and potent inhibition mechanism. Structural modeling of the TdPP1-inhibitor complexes suggested that both At-I2 and TdRL1 bind to TdPP1 by wrapping their flexible C-terminal tails around it, blocking access to the active site. Remarkably, the model showed that TdRL1 differs from At-I2 in its interaction with TdPP1 by trapping the phosphatase with its N-terminal tail. These findings provide important insights into the regulatory mechanisms governing the activity of PP1s in plants and highlight the potential for targeted inhibition to modulate plant stress responses. Full article

Glycosaminoglycans (GAGs) are key ligands for proteins involved in physiological and pathological processes. Specific GAG-binding patterns are rarely identified, with the heparin pentasaccharide as an Antithrombin-III ligand being the best characterized. Generating glycan-specific antibodies is difficult due to their size, pattern dispersion, and flexibility. Single-domain variable new antigen receptors (VNAR nanobodies) from nurse sharks are highly soluble, stable, and versatile. Their unique properties suggest advantages over conventional antibodies, particularly for challenging biotherapeutic targets. Here we have used VNAR semi-synthetic phage libraries to select high-affinity fondaparinux-binding VNARs that did not show cross-reactivity with other GAG species. Competition ELISA and surface plasmon resonance identified a single fondaparinux-selective VNAR clone. This VNAR exhibited an extraordinarily stable protein fold: the beta-strands are stabilized by a robust hydrophobic network, as revealed by heteronuclear NMR. Docking fondaparinux to the VNAR structure revealed a large contact surface area between the CDR3 loop of the antibody and the glycan. Fusing the VNAR with a human Fc domain resulted in a stable product with a high affinity for fondaparinux (Kd = 9.3 × 10⁻⁸ M) that could efficiently discriminate between fondaparinux and other glycosaminoglycans. This novel glycan-targeting screening technology represents a promising therapeutic strategy for addressing GAG-related diseases. Full article

The transportation sector is a significant contributor to global carbon emissions, thus necessitating a transition toward renewable energy sources (RESs) and electric vehicles (EVs). Among EV technologies, fuel-cell EVs (FCEVs) offer distinct advantages in terms of refueling time and operational efficiency, thus rendering them a promising solution for sustainable transportation. Nevertheless, the integration of FCEVs in rural areas poses challenges due to the limited availability of refueling infrastructure and constraints in energy access. In order to address these challenges, this study proposes a multi-objective energy management model for a hydrogen refueling station (HRS) integrated with RESs, a battery storage system, an electrolyzer (EL), a fuel cell (FC), and a hydrogen tank, serving diverse FCEVs in rural areas. The model, formulated using mixed-integer linear programming (MILP), optimizes station operations to maximize both cost and load factor performance. Additionally, bi-directional trading with the power grid and hydrogen network enhances energy flexibility and grid stability, enabling a more resilient and self-sufficient energy system. To the best of the authors’ knowledge, this study is the first in the literature to present a multi-objective optimal management approach for grid-interactive, renewable-supported HRSs serving hydrogen-powered vehicles in rural areas. The simulation results demonstrate that RES integration improves economic feasibility by reducing costs and increasing financial gains, while maximizing the load factor enhances efficiency, cost-driven strategies that may impact stability. The impact of the EL on cost is more significant, while RES capacity has a relatively smaller effect on cost. However, its influence on the load factor is substantial. The optimization of RES-supported hydrogen production has been demonstrated to reduce external dependency, thereby enabling surplus trading and increasing financial gains to the tune of USD 587.83. Furthermore, the system enhances sustainability by eliminating gasoline consumption and significantly reducing carbon emissions, thus supporting the transition to a cleaner and more efficient transportation ecosystem. Full article

The major challenges in designing a Hybrid Renewable Energy System (HRES) include selecting appropriate renewable energy sources and storage systems, accurately sizing each component, and defining suitable optimization criteria. This study addresses these challenges by employing Particle Swarm Optimization (PSO) within a multi-criteria optimization framework to design an HRES in Kern County, USA. The proposed system integrates wind turbines (WTS), photovoltaic (PV) panels, Biomass Gasifiers (BMGs), batteries, electrolyzers (ELs), and fuel cells (FCs), aiming to minimize Annual System Cost (ASC), minimize Loss of Power Supply Probability (LPSP), and maximize renewable energy fraction (REF). Results demonstrate that the PSO-optimized system achieves an ASC of USD6,336,303, an LPSP of 0.01%, and a REF of 90.01%, all of which are reached after 25 iterations. When compared to the Genetic Algorithm (GA) and hybrid GA-PSO, PSO improved cost-effectiveness by 3.4% over GA and reduced ASC by 1.09% compared to GAPSO. In terms of REF, PSO outperformed GA by 1.22% and GAPSO by 0.99%. The PSO-optimized configuration includes WT (4669 kW), solar PV (10,623 kW), BMG (2174 kW), battery (8000 kWh), FC (2305 kW), and EL (6806 kW). Sensitivity analysis highlights the flexibility of the optimization framework under varying weight distributions. These results highlight the dependability, cost-effectiveness, and sustainability for the proposed system, offering valuable insights for policymakers and practitioners transitioning to renewable energy systems. Full article

Fuel cells (FCs) offer several operational advantages when integrated as a power source in electric vehicles (EVs). Since the voltage of these cells is typically low, usually less than 1 V, the power conversion system requires a DC–DC converter capable of providing a high voltage conversion ratio to match the input voltage of the motor propulsion system, which can exceed 400 V and reach up to 800 V. The modular DC–DC boost converter proposed in this paper is designed to achieve a high voltage step-up ratio for the input FC voltages through the use of isolated series-connecting boosting submodules connected. The power electronic topology employed in the submodules (SMs) is designed to provide a flexible output voltage while maintaining a continuous input current from the fuel cells with minimal current ripple to improve the FC’s performance. The proposed step-up modular converter provides several benefits including scalability, better controllability, and improved reliability, especially in the presence of partial faults. Computer simulations using MATLAB/SIMULINK^® software (R2024a) have been used to study the feasibility of the proposed converter when connected to a permanent magnet synchronous motor (PMSM). Also, experimental results using a 1 kW prototype composed of four SMs have been obtained to validate the performance of the proposed converter. Full article

The ridge–furrow plastic mulching technique has been widely applied due to its benefits of increasing temperature, conserving moisture, reducing evaporation, and boosting yields. Hydrus-2D is a computer model designed to simulate the two-dimensional movement of water in soil characterized by a low cost and high flexibility compared to field experiments. This study, based on field experiment data from Jianping County, Liaoning Province, China, during 2017–2018, developed Hydrus-2D models for two distinct field management practices: non-mulched flat cultivation (NM-FC) and mulched ridge tillage (M-RT). Furthermore, it simulated the dynamic changes in farmland water variations during the summer maize growth period (2021–2100) under climate change scenarios, specifically medium and high emission pathways (SSP2-4.5 and SSP5-8.5), based on the FGOALS-g3 model, which exhibits the highest similarity to the climate pattern of Jianping County in the Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models and the Shared Socioeconomic Pathways (SSPs). The results showed that in the future FGOALS-g3 model, net radiation exhibited a significant upward trend under the SSP2-4.5 scenario (Z = 2.38), while the average air temperature showed a highly significant increase under both SSP2-4.5 and SSP5-8.5 scenarios, with Z-values of 6.48 and 8.90, respectively. The Hydrus-2D model demonstrated high simulation accuracy in both NM-FC and M-RT treatments (R² ranging from 0.86 to 0.96, with RMSE not exceeding 0.011), accurately simulating the dynamic changes in soil water content (SWC) under future climate change. Compared to NM-FC, M-RT reduced evaporation, increased transpiration, and effectively decreased the leakage caused by increased future precipitation, resulting in a 0.04 and 0.01 cm³/cm³ increase in surface and deep soil SWC, respectively, during the summer maize growing season, significantly improving water use efficiency. Moreover, M-RT treatment reduced the impact coefficients of climate change on various water balance parameters, stabilizing changes in these parameters and SWC under future climate conditions. This study demonstrates the significant advantages of M-RT in coping with climate change, providing key scientific evidence for future agricultural water resource management. These findings offer valuable insights for policymakers and farmers, particularly in developing adaptive land management and irrigation strategies, helping to improve water use efficiency and promote sustainable agricultural practices. Full article

Dysfunction in the prefrontal cortex can lead to cognitive inflexibility due to multifactorial causes as included cardiometabolic disorders, stress, inadequate diets, as well as an imbalance of the gut–brain axis microbiota. However, these risk factors have not been evaluated jointly. The purpose of this study was to evaluate the effect of physical stress (MS: Male Stress and FS: Female Stress) and high-fat diet (MD: Male Diet and FD: Female Diet) supplementation on the gut microbiota and cognitive flexibility. Methods: The study was performed on 47 mice, 30 male (M) and 17 female (F) BALBc, exposed to chronic stress physical (S) and high-fat diet (D). Cognitive flexibility was evaluated using the Attentional Set-Shifting Test (ASST) and the gut microbiota composition in terms of relative abundance (%) and alpha–beta diversity. Results: Results showed that S and D reduced cognitive flexibility in male and female mice (p < 0.0001). Significant changes occurred in Alistipes spp. (MM vs. MS:MD; p < 0.0001), Barnesiella spp. (FC vs. FS; p = 0.0002; FC vs. FD, p = 0.0033); Dorea spp. (MC vs. MD, p = 0.0008; MM vs. MD, p < 0.0001) and Lactobacillus spp. (MC vs. MD and FM vs. FS, p < 0.0001; FM vs. MD, p = 0.0393) genera among groups. Predictive functional analysis (QIIME2 and PICRUSt2) showed a significant increase in the expression of histidine kinase, alanine dehydrogenase, glutamine synthase, glutamate synthase, arginine succinyl synthase, and tryptophan synthase genes (p < 0.05), the latter being a precursor of serotonin (5-HT). Conclusions: Chronic physical stress and a high-fat diet modify cognitive flexibility and the composition and predictive function of the gut microbiota. Full article

This paper presents an overview of the status and prospects of fuel cell electric vehicles (FC-EVs) for grid integration. In recent years, renewable energy has been explored on every front to extend the use of fossil fuels. Advanced technologies involving wind and solar energy, electric vehicles, and vehicle-to-everything (V2X) are becoming more popular for grid support. With recent developments in solid oxide fuel cell electric vehicles (SOFC-EVs), a more flexible fuel option than traditional proton-exchange membrane fuel cell electric vehicles (PEMFC-EVs), the potential for vehicle-to-grid (V2G)’s implementation is promising. Specifically, SOFC-EVs can utilize renewable biofuels or natural gas and, thus, they are not limited to pure hydrogen fuel only. This opens the opportunity for V2G’s implementation by using biofuels or readily piped natural gas at home or at charging stations. This review paper will discuss current V2G technologies and, importantly, compare battery electric vehicles (BEVs) to SOFC-EVs for V2G’s implementation and their impacts. Full article

Model Predictive Control (MPC) has emerged as a promising alternative for controlling power converters, offering benefits such as flexibility, simplicity, and rapid control response, particularly when short-horizon algorithms are employed. This paper introduces a system using a short-horizon Finite Control Set MPC (FCS-MPC) strategy to specifically address the challenge of non-minimum phase behavior in boost converters. The non-minimum phase issue, which complicates the control process by introducing an initial inverse response, is effectively mitigated by the proposed method. A Proportional–Integral (PI) controller is integrated to dynamically adjust the reference current based on the output voltage error, thereby enhancing overall system stability and performance. Unlike conventional PI-MPC methods, where the PI controller has an influence on the system dynamics, the PI controller in this approach is solely used for tuning the reference current needed for the FCS-MPC controller. The PI controller addresses small deviations in output voltage, primarily due to model prediction inaccuracies, ensuring steady-state accuracy, while the FCS-MPC handles fast dynamic responses to adapt the controller’s behavior based on load conditions. This dual control strategy effectively balances the need for precise voltage regulation and rapid adaptation to varying load conditions. The proposed method’s effectiveness is validated through a multi-stage simulation test, demonstrating significant improvements in response time and stability compared to traditional control methods. Hardware-in-the-loop testing further confirms the system’s robustness and potential for real-time applications in power electronics. Full article

This paper investigates the fixed-time tracking control problem for agile missiles with multiple heterogeneous actuators in the presence of saturation constraints and external disturbances. To reduce the turning radius and promote maneuvering envelope, a novel combination scheme for blended actuators is introduced in this paper, consisting of a flexible mechanism control system (FCS), reaction-jet control system (RCS), and aerodynamic control. Based on the proposed nonsingular terminal sliding mode surface, a fixed-time anti-saturation controller with an auxiliary system is presented first to ensure global fixed-time stability and to compensate for the adverse effects of input saturation. Subsequently, a fixed-time disturbance observer is constructed to estimate uncertainties and lumped disturbances, and to address the chattering problem. To assign the total virtual control command to different actuators, a control allocation based on dynamic programming considering actuator dynamics is established. Finally, detailed numerical simulations and comparisons are provided to verify the effectiveness and superiority of the proposed control scheme. Full article