This study employed a simulation approach to model oxygen delivery in spontaneously breathing patients with chronic obstructive pulmonary disease (COPD). The Morozoff Model, originally designed for mechanically ventilated patients with a fixed fraction of inspired oxygen (FIO2), was adapted to incorporate the relationship between oxygen flow delivered through nasal cannula and FIO2, along with COPD-specific pathophysiological parameters. The effectiveness of constant and variable oxygen flow delivery was evaluated using a closed-loop control system with a Proportional-Integral-Derivative (PID) controller. The adapted Morozoff Model successfully replicated SpO2 variations observed in COPD patients, capturing desaturation patterns during rapid eye movement sleep and daily activities. Simulations showed that continuous oxygen flow was inadequate for maintaining SpO2 within the target range. Evaluating the closed-loop control system, a proportional (P) controller was found to be sufficient, with integral (I) and derivative (D) terms having negligible impact on performance for a baseline case. The proportional controller improved SpO2 regulation, increasing time within the target range (88%-92%) to 80%, compared to a maximum of 55% achieved with a constant oxygen flow system. However, as airway resistance increased compared to the baseline case, the controller's performance declined, highlighting the need for re-tuning P and potentially incorporating I and D terms to improve adaptability under varying pathophysiological parameters. In addition, more advanced control strategies, such as model-based controllers, may enhance adaptability to dynamic patient conditions. These findings support the development of adaptive oxygen delivery strategies for spontaneously breathing COPD patients.
- Publication type
- Journal Article MeSH
Early prediction of disability progression in multiple sclerosis (MS) remains challenging despite its critical importance for therapeutic decision-making. We present the first systematic evaluation of personalized federated learning (PFL) for 2-year MS disability progression prediction, leveraging multi-center real-world data from over 26,000 patients. While conventional federated learning (FL) enables privacy-aware collaborative modeling, it remains vulnerable to institutional data heterogeneity. PFL overcomes this challenge by adapting shared models to local data distributions without compromising privacy. We evaluated two personalization strategies: a novel AdaptiveDualBranchNet architecture with selective parameter sharing, and personalized fine-tuning of global models, benchmarked against centralized and client-specific approaches. Baseline FL underperformed relative to personalized methods, whereas personalization significantly improved performance, with personalized FedProx and FedAVG achieving ROC-AUC scores of 0.8398 ± 0.0019 and 0.8384 ± 0.0014, respectively. These findings establish personalization as critical for scalable, privacy-aware clinical prediction models and highlight its potential to inform earlier intervention strategies in MS and beyond.
- Publication type
- Journal Article MeSH
This paper presents two discrete circuit solutions for realizing passive, electronically adjustable constant-phase elements, specifically half-order capacitors with a -45° phase shift. Fractional-order capacitors with electronically adjustable pseudocapacitance are especially useful for designing tunable filters and oscillators. The ability to adjust pseudocapacitance electronically and continuously is a major improvement over traditional passive solutions. Their pseudocapacitance can be controlled by a DC voltage, allowing key parameters like the cut-off or oscillation frequency to be tuned. Two presented design approaches differ in accuracy, tuning range, and signal-handling capability. Both solutions maintain a constant phase over one frequency decade, with a phase ripple within ± 2°. The tuning range spans from hundreds of Hz to several MHz. Presented solutions allow pseudocapacitance tuning in range of hundreds of nano F/sec0.5 (with varicaps) and tens of micro F/sec0.5 (with MOSFETs). The MOS-based circuit offers a tuning ratio of 7 but shows a 19% deviation between simulation and measurement. It also suffers from notable nonlinearity, with undistorted operation limited to signal levels up to 20 mV peak-to-peak. The varicap-based solution achieves a tuning ratio of 5, with high accuracy (up to 6% error), and handles input signals in the hundreds of mV with acceptable distortion. PSpice simulations and laboratory measurements confirm the performance of both designs.
- Keywords
- Adjustability, Constant phase element, Fractional-order, MOSFET, Pseudocapacitance, Tunability, Varicap,
- Publication type
- Journal Article MeSH
Ligand-stabilized metallic nanoclusters are emerging as promising agents for photodynamic therapy (PDT). This study explores how precisely tailored ligands can optimize the anti-cancer PDT efficiency of molybdenum-iodide nanoclusters. Utilizing click chemistry, we synthesized a series of triazolate-capped nanoclusters by reacting Na2[Mo6I8(N3)6] with dibenzo[a,e]cyclooctyne (DBCO) derivatives. Dynamic light scattering and luminescence measurements confirmed that the bulky DBCO moieties effectively stabilized the nanoclusters in aqueous media, while the appended side chains dictated their colloidal behavior and photosensitizing capabilities. In vitro experiments with HeLa cancer cells revealed that the side chain's nature critically influences cellular uptake and phototoxicity. Positively charged nanoclusters exhibited enhanced cell membrane interactions and potent phototoxic effects, whereas negatively charged counterparts displayed reduced internalization and diminished PDT efficacy. Notably, the nanoclusters maintained consistent phototoxicity even after prolonged exposure to aqueous media, demonstrating the robust stability conferred by the DBCO ligands. These results higlight the potential for fine-tuning molybdenum-iodide nanocluster properties to optimize PDT applications, achieving a delicate balance between water stability, cellular interaction, and phototoxicity, thereby isolating key parameters that govern PDT efficiency.
- MeSH
- Photochemotherapy * MeSH
- Photosensitizing Agents * pharmacology chemistry chemical synthesis MeSH
- HeLa Cells MeSH
- Iodides * chemistry pharmacology MeSH
- Humans MeSH
- Ligands MeSH
- Molecular Structure MeSH
- Molybdenum * chemistry pharmacology MeSH
- Antineoplastic Agents * pharmacology chemistry chemical synthesis MeSH
- Drug Screening Assays, Antitumor MeSH
- Particle Size MeSH
- Cell Survival drug effects MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Photosensitizing Agents * MeSH
- Iodides * MeSH
- Ligands MeSH
- Molybdenum * MeSH
- Antineoplastic Agents * MeSH
Model phosphonamidates derived from 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) with molecular flexibility tuned by amino acid substituents were prepared as pairs of diastereoisomers (DSIs) differing in configuration on phosphorus atom. X-ray diffraction (XRD) determined absolute configuration on phosphorus and revealed conformational flexibility of six-membered oxa-phospha-cycle. Quantum-chemical calculations combined with machine learning provided 2-4 representative conformers from each DSI present in solution. 31P chemical shift of RS DSIs was higher compared to the SS ones. Calculated 31P-1H as well as 31P-13C J-couplings followed Karplus dependence of J-coupling values on dihedral angles between interacting nuclei, showing reasonable match with the literature data. The effect of molecular flexibility quantified by parameter nConf20 on NMR parameters was significant, especially for residual dipolar couplings (RDCs), where Pearson correlation factor R decreased with increasing nConf20 parameter.
- Keywords
- 31P NMR spectroscopy, DOPO derivatives, Karplus-like dependence, conformational equilibria, stereochemical analysis,
- Publication type
- Journal Article MeSH
Temperature regulation in nonlinear and highly dynamic processes such as the continuous stirred-tank heater (CSTH) is a challenging task due to the inherent system nonlinearities and disturbances. This study proposes a novel metaheuristic-driven control strategy, combining the two degrees of freedom-PID acceleration (2DOF-PIDA) controller with the recently developed starfish optimization algorithm (SFOA) for temperature control of the CSTH process. The 2DOF-PIDA controller enhances system performance by decoupling setpoint tracking and disturbance rejection, while the SFOA ensures optimal tuning of controller parameters by leveraging its powerful exploration and exploitation capabilities. Simulation results validate the effectiveness of the proposed approach, demonstrating improved tracking accuracy, disturbance rejection, and robustness compared to conventional methods. The combination of 2DOF-PIDA and SFOA provides a flexible and efficient solution for controlling highly nonlinear systems, with significant implications for industrial temperature regulation applications.
Understanding how to tune the properties of electroactive materials is a key parameter for their applications in energy storage systems. This work presents a comprehensive study in tailoring polyaniline (PANI) suspensions by acid-assisted polymerization method and their subsequent deposition on boron-doped diamond (BDD) supports with low/high B concentrations. The porous or densely packed morphology of PANI is successfully controlled by varying the monomer-to-initiator ratio. The interaction between PANI and BDDs leads to the shift in oxidation and reduction potentials, and the high B doping resulted in the reduction of the oxidation potentials. Notably, the highest specific capacitance of 958 F g-1, which represents 90% of the theoretical capacitance, is recorded for the support with relatively low B content. Moreover, PANI obtained by slow kinetic has a stronger interaction with the B-doped diamond support, which is confirmed by electrochemical impedance spectroscopy. This study provides valuable insights for optimizing PANI suspension preparation methods and selecting appropriate boron doping concentrations in nanodiamond supports for composite electrodes in energy storage applications.
- Keywords
- acid‐assisted polymerization, boron‐doped diamond, cyclic voltammetry, electrochemical impedance spectroscopy, polyaniline, supercapacitor,
- Publication type
- Journal Article MeSH
Precise pressure control in shell-and-tube steam condensers is crucial for ensuring efficiency in thermal power plants. However, traditional controllers (PI, PD, PID) struggle with nonlinearities and external disturbances, while classical tuning methods (Ziegler-Nichols, and Cohen-Coon) fail to provide optimal parameter selection. These challenges lead to slow response, high overshoot, and poor steady-state performance. To address these limitations, this study proposes a cascaded PI-PDN control strategy optimized using the electric eel foraging optimizer (EEFO). EEFO, inspired by the prey-seeking behavior of electric eels, efficiently tunes controller parameters, ensuring improved stability and precision. A comparative analysis against recent metaheuristic algorithms (SMA, GEO, KMA, QIO) demonstrates superior performance of EEFO in regulating condenser pressure. Additionally, validation against documented studies (CSA-based FOPID, RIME-based FOPID, GWO-based PI, GA-based PI) highlights its advantages over existing methods. Simulation results confirm that EEFO reduces settling time by 22.7%, overshoot by 78.7%, steady-state error by three orders of magnitude, and ITAE by 81.2% compared to metaheuristic based methods. The EEFO-based controller achieves faster convergence, enhanced robustness to disturbances, and precise tracking, making it a highly effective solution for real-world applications. These findings contribute to optimization-based control strategies in thermal power plants and open pathways for further bio-inspired control innovations.
- Keywords
- Cascaded PI-PDN controller, Electric eel foraging optimizer, Metaheuristics, Nonlinear system, Pressure control, Steam condenser,
- Publication type
- Journal Article MeSH
In this study, we explored and described various parameters of microbially induced calcite precipitation (MICP) using the alkaliphilic bacterium Sporosarcina pasteurii DSM 33, which exhibits ureolytic activity, to stabilize and strengthen waste concrete fines (WCF). Bacterial cell concentration, single and repeated addition of bacterial suspension, and pH adjustment were tested in stage 1 of the experimental agenda in order to tune parameters for sample preparation in stage 2 focused on the effect of MICP treatment duration (14, 30, 60, and 90 days). Two types of WCF materials differing in their physicochemical properties were used for the stabilization. The results of the EDS and XRD analyses confirmed the presence of CaCO3 crystals, which increased by about 10-12% over time, affecting the porosity, compactness, and strength of the formed composites. The XRD results also indicated that the WCF properties significantly influence the formation of the type of CaCO3 crystals, supported also by microscopy observations. This study highlights the potential of MICP technology to make concrete recycling more sustainable, aligning with the concept of a circular economy; however, the interplay between the WCF materials of various properties and bacterial activity must be further scrutinized.
- Keywords
- Sporosarcina pasteurii, CaCO3 crystals, MICP, Ureolytic activity, Waste concrete fines,
- Publication type
- Journal Article MeSH
The rapid growth in power demand, integration of renewable energy sources (RES), and intermittent uncertainties have significantly challenged the stability and reliability of interconnected power systems. The integration of electric vehicles (EVs), with their bidirectional power flow, further exacerbates the frequency fluctuation in the power system. So, to mitigate the frequency & power deviations as well as to stabilize the power system integrated with distributed generators (DGs) and EVs, robust & intelligent control strategies are indispensable. This study dedicates a novel Fuzzy-Sliding Mode Controller (FSMC) utilized for load frequency control (LFC). First, the dynamic response has been evaluated by using a Sliding Mode Controller (SMC), showcasing its robustness against external disturbances and parameter uncertainties. Second, to enhance the performance, fuzzy logic is integrated with SMC, leveraging its adaptability to create the FSMC controller. This FSMC has achieved the superiority by handling non-linearities, communication delays and parameter variations in the system. A significant contribution like the design and tuning of the controllers using a Modified Gannet Optimization Algorithm (MGOA) has been established. The potential of MGOA over GOA has been corroborated by convergence speed and precision through benchmark functions. Furthermore, the paper extensively analyzes the impact of EV integration to the frequency and tie-line power dynamics under varying regulation capacities and uncertain operating conditions. Comparative studies demonstrate that the MGOA-tuned FSMC achieves faster settling times, reduced overshoot, and improved stability metrics compared to conventional and state-of-the-art methods. Finally, the MATLAB-based simulation results are validated through real-time implementation on the OPAL-RT 4510 platform, confirming the robustness and practicality of the proposed methodology in addressing modern power system challenges involving high renewable penetration and EV integration.
