In this research study, the effect of different electron transport layers (ETLs) and hole transport layers (HTLs) on the performance of aluminum quinolate (Alq₃)-based organic light-emitting diodes (OLEDs) was investigated. The research focused on material selection, interface optimization, and the tuning of parameters to enhance device performance. Oghmanano software was employed to analyze various electrical characteristics, including current-voltage (I-V), current density-voltage (J-V), photon flux-voltage (Φ-V), charge density-voltage (Qt-V), recombination rate-voltage (K-V), and photon flux-current (Φ-I) relationships for the initial modeled structure with the layer configuration indium tin oxide (ITO)/poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT: PSS)/Alq₃/C₆₀/lithium fluoride (LiF)/aluminum (Al). The initial simulated structure exhibited performance parameters of turn-on voltage (Vk) = 2.5V, current density (J) = 1.85 × 103 A cm- 2, photon flux (Φ) = 3.57 × 10- 7 W m- 2, charge density (Qt) = 1.65 × 1023 m- 3, and recombination rate (K) = 8.13 × 10- 16 m3 s- 1. Furthermore, the effects of varying the thicknesses of the emissive and charge conduction layers were studied to determine the optimal parameters for maximum performance. Among the examined materials, PEDOT: PSS as the HTL and bathophenanthroline (BPhen) as the ETL exhibited superior charge conduction and band alignment with Alq₃. The optimized simulated structure demonstrated improved parameters: Vk = 2.8V, J = 2.63 × 103 A m- 2, Φ = 7.35 × 10-4 Wm- 2, Qt = 1.89 × 1023 m- 3, and K = 2.79 × 10- 16m3 s- 1. These results suggest that the optimized OLED structure can serve as an effective alternative to conventional configurations for advanced optoelectronic applications in the visible spectrum. Moreover, the enhanced fluorescence efficiency and tunable visible emission of the optimized OLED structure highlight its potential for fluorescence-based biomedical applications such as bioimaging, biosensing, and photodynamic therapy.

Optimized 'Full Right' Instrument Configuration in Robotic Rectal Surgery With the Da Vinci Xi System: A Prospective Single-Center Experience.

Voltage instability and power quality degradation represent critical barriers to the reliable operation of modern wind farm-based microgrids. As the share of distributed wind generation continues to grow, fluctuating wind speeds and variable reactive power demands increasingly challenge grid stability. This study proposes an adaptive decentralized framework integrating a Dynamic Distribution Static Compensator (DSTATCOM) with an Artificial Neuro-Fuzzy Inference System (ANFIS)-based control strategy to enhance dynamic voltage and frequency stability in wind farm microgrids. Unlike conventional centralized STATCOM configurations, the proposed system employs parallel wind turbine modules that can be selectively switched based on voltage feedback to maintain optimal grid conditions. Each turbine is connected to a capacitive circuit for real-time voltage monitoring, while the ANFIS controller adaptively adjusts compensation signals to ensure minimal voltage deviation and reduced harmonic distortion. The framework was modeled and validated in the MATLAB/Simulink R2023a environment using the Simscape Power Systems toolbox. Simulation results demonstrated superior transient response, voltage recovery, and power factor correction compared with traditional PI and fuzzy-based controllers, achieving a total harmonic distortion below 2.5% and settling times under 0.5 s. The findings confirm that the proposed decentralized DSTATCOM–ANFIS approach provides an effective, scalable, and cost-efficient solution for maintaining dynamic stability and high power quality in wind farm based microgrids.

The rapid expansion of renewable energy systems, particularly solar microgrids, has transformed electricity access in tropical developing regions. However, the sustainability of these systems is critically constrained by the short lifespan and reduced efficiency of battery energy storage systems (BESS) operating under high-temperature conditions. Conventional battery management systems (BMS) are often designed for temperate climates and do not dynamically respond to the extreme temperature fluctuations typical of tropical zones. This study develops an adaptive battery management system (ABMS) that utilizes real-time thermal monitoring, intelligent control algorithms, and adaptive charging regulation to enhance battery health and system longevity in solar microgrids. The proposed system employs temperature sensors, data-driven algorithms, and fuzzy logic control to maintain optimal charging profiles, reduce degradation rates, and prevent thermal runaway. Simulations using MATLAB/Simulink and prototype implementation demonstrate improved efficiency, enhanced safety, and up to 35% increase in estimated battery lifespan compared to conventional BMS configurations. The adaptive model provides a sustainable pathway for improving energy reliability and reducing maintenance costs in renewable microgrid systems deployed in tropical environments.

Achieving high metal loadings in metal-organic frameworks (MOFs)-based single-atom catalysts (SACs) remains a major challenge due to the degradation of anchoring sites during high-temperature synthesis. Here, a low-temperature photochemical reduction strategy that preserves the structural integrity of MOF and maximizes the density of unsaturated pyridinic nitrogen sites for efficient metal atom anchoring is reported. This pyrolysis-free approach enables the synthesis of SACs with record-high metal loadings, up to 20.5 wt.% for Pt, 16.9 wt.% for Ru, 15.4 wt.% for Os, 12.9 wt.% for Fe, and 9.6 wt.% for Cu, surpassing previous MOF-derived SACs by one order of magnitude. Density functional theory (DFT) calculations reveal that the unique Pt-N2Cl2 coordination significantly enhances oxidase-like activity compared to conventional Pt-N3 configurations. Furthermore, the high metal loading increases the density of catalytically active sites, thereby improving overall catalytic efficiency. As a proof of concept, a Pt-SACs@MOF-based immunosensor achieves ultrasensitive detection of α-fetoprotein (AFP) with a detection limit as low as 3 fg mL-1. This work offers a general and scalable strategy for synthesizing high-density SACs, addressing the long-standing trade-off between metal loading and structural stability in MOF-based catalysts.

A bstract The expanding application of classical thermodynamic methods to black hole physics has yielded significant advances in characterizing phase transition behavior. Among these approaches, thermodynamic analysis — particularly kinetic formulations like the Kramers escape rate — provides a robust framework for probing black hole phase transitions with minimal relativistic constraints. This study investigates the kinetics and dynamic evolution of first-order phase transitions in black holes exhibiting multiple critical points, employing a particle-based escape rate model. The distinct free energy landscapes inherent to multi-critical systems, which can simultaneously support multiple local minima under specific thermodynamic conditions (temperature and pressure) within a given reference frame, raise fundamental questions regarding transition pathways. We rigorously assess whether the Kramers escape rate retains its predictive validity in these complex multi-minima systems, as established for conventional single-minimum configurations. Furthermore, we examine whether transitions proceed via a sequential, stepwise mechanism between adjacent minima, or if pathways exist that bypass intermediate states through direct descent to the global minimum. Our analysis of black holes undergoing multiphase transitions reveals both parallels and significant deviations from single-transition models. Crucially, we demonstrate that the Kramers escape rate remains a quantitatively reliable indicator of first-order phase transitions in black holes, even within multi-critical frameworks. This approach offers deeper insights into the governing energetic landscapes and kinetic processes underlying these phenomena.

Electrochemical lithium extraction has been proven to be an effective method for Li+ recovery from brine due to its environmental friendliness and excellent selectivity. In a conventional configuration, LiMn2O4 (LMO), LiFePO4 (LFP) or LiNixCoyMn1-x-yO2 (NCM) will be paired with activated carbon (AC) and anion exchange membrane (AEM) as an extraction assembly. The cathode materials are responsible for lithium extraction and AEM is essential to avoid the adsorption of Li+ onto the AC anode during Cl-desorbing. Anode and cathode materials have both been optimized for enhanced electrochemical lithium extraction.Here, layered double oxide (LDO) was applied as an anode material with high Cl- selectivity, replacing the AEM/AC assembly. Li+ intercalation capacity of LMO || CoAl-LDO reached 1.35 mmol g-1 at 1.2V with a maximum rate of 0.57 mmol g-1 min-1 and capacity retention of 70.83% after 20 cycles, higher than that of LMO || AC/AEM (1.12mmol g-1, 0.37 mmol g-1 min-1, 35.48%). Furthermore, Li+ selectivity in a Li+/Mg2+ solution (1:5) was investigated, showing that β_(Li+/Mg2+)= 2.67 in LMO || CoAl-LDO was close to LMO || AC/AEM (2.98). In-situ Raman characterization showed that high Cl- selectivity and capacity were induced by anion intercalation mechanism of CoAl-LDO, proving that LDO can be a promising anode material for lithium extraction.Moreover, high valent Nb element was doped onto LMO (LMO-Nb) to effectively enhance the cyclic stability and Li+ selectivity. The increased lattice constant of LMO reduced Li+ diffusion resistance and enhanced Li+ intercalation capacity, 5.50 mmol g-1 in origin Qarhan brine and 3.71 mmol g-1 in old Qarhan brine, higher than that of pristine LMO (4.73 mmol g-1, 3.05 mmol g-1). Meanwhile, the cyclic stability of LMO-Nb (69.77% after 50 cycles), compared to 56.52% of LMO, can be attributed to the strong bonding energy of Nb-O. The selectivity of LMO-Nb in origin Qarhan brine (β_(Li+/Mg2+)= 4.55, β_(Li+/Na+)=2.42) surpassed that of LMO (β_(Li+/Mg2+)= 3.90, β_(Li+/Na+)=1.76).In addition, LiNi0.33Co0.33Mn0.33O2 (NCM) was doped with Ti element (NCM-Ti) for electrochemical lithium extraction. Ti doping increased the lattice constant, which would be beneficial to the diffusion of Li+ and cycle stability. The lithium extraction capacity in 10mmol/L LiCl solution reached 1.3mmol/g, and maintained 87% after 20 cycles. The extraction capacity in the brine of Qarhan Salt Lake exceeded 5 mmol/g and the selectivity of NCM-Ti (β_(Li+/Mg2+)= 2.47, β_(Li+/Na+)=4.49) was higher than NCM (β_(Li+/Mg2+)= 1.74, β_(Li+/Na+)=3.61).

3D printed gas diffusion layers (GDL) have been proposed [1] and implemented [2,3] as model systems for innovative water management strategies addressing two-phase transport challenges within the GDL of polymer electrolyte fuel cells (PEFC). Digital light processing (DLP) resin 3D-printers can be used to fabricate polymer structures with a deterministic cubic lattice design, which are subsequently carbonized in a pyrolysis process. The carbonized samples feature minimum solid dimensions of ~50 μm and pore sizes as small as ~100 μm. These lattice structures show promising PEFC performance as GDL replacements, particularly due to the high convective flow velocities and reduced diffusive transport distances [3].In this presentation we discuss how such lattice structures can be used as an alternative cell architecture in which the conventional channel-rib flow field is entirely replaced by the printed structure (see Figure 1 a-b), similar as with metal foam flow fields [4]. The new architecture shows comparable performance to a conventional channel-rib configuration with commercial GDL materials (SGL-35BC), even when no GDL but only an MPL is used as an intermediate layer to the CL (see Figure 1c). The fuel cell performance characterization is complemented by operando X-ray radiography and X-ray tomography experiments using a lab-CT to gain insights into the liquid water distribution within the 3D-printed GFLs.

Metallic materials typically experience significant strength degradation at elevated temperatures. Traditional strengthening methods, which rely on thermally stable particle dispersion, exhibit limited effectiveness owing to the challenges in suppressing thermally activated dislocation motion. This work introduces a strategy for achieving exceptional high-temperature strength through a thermally stable nanoscale eutectic cellular network (ECN) enabled by additive manufacturing. A near-eutectic AlLaScZr alloy is developed for laser powder bed fusion, incorporating an Al-La nanoscale ECN and dense intracellular nanoprecipitates. This alloy demonstrates excellent printability and remarkable high-temperature yield strength above 0.6Tm (~250 MPa at 300 °C), outperforming conventional aluminium alloys by 2-5 times with minimal degradation after prolonged annealing. Compared with the conventional configuration of particle dispersion, the nanoscale ECN architecture enhances load-bearing capacity and strengthens aluminium by caging dislocation motion within ultrafine cells (~200 nm), effectively mitigating intrinsic high-temperature softening.

This study investigates the dual-storage capability ofa redoxflow battery (RFB) system, enabling simultaneous storage of heat andelectricity within a single platform. Through electrochemical andthermal experiments, we evaluated how heat storage affects batteryperformance and vice versa using a counterflow heat exchanger integratedin a conventional RFB configuration. The results show that incorporatingheat storage had a minimal impact on the electrochemical chargingand discharging processes. Further, the heat discharge operated independentlyof electrochemical storage, confirming that both functions can coexistwithout interference. The combined system also enhanced overall energyconversion efficiency, demonstrating its potential as an efficientsolution for supplying both thermal and electrical energythetwo most widely used energy forms.

To further explore the potential of CO2 emission reduction and optimize the cost of microgrids, a two-stage robust optimization configuration method for multi-energy microgrids is proposed, considering uncertainty, tiered carbon trading, and demand response. The model incorporates power-to-gas (P2G) and carbon capture and storage (CCS) technologies to enhance renewable energy utilization and reduce carbon emissions. A tiered carbon trading mechanism is introduced to penalize high emissions, while incentive-based demand response is employed to adjust load profiles and improve economic performance. The optimization model is formulated as a two-stage robust problem: the outer stage minimizes annual investment and maintenance costs, while the inner stage identifies the worst-case scenario under uncertainties. The model is solved using the Column-and-Constraint Generation (C&CG) algorithm and implemented in MATLAB R2022b with the Gourbi solver. Simulation results demonstrate that the proposed approach reduces carbon emissions by up to 31.9% and total costs by 3.28% compared to conventional configurations, while increasing the penetration of renewable energy. This study provides practical reference for the low-carbon and economic planning of microgrids with P2G and CCS integration.

Introduction: Obssesive compulsive disorder (OCD) is characterized by recurrent intrusive thoughts and repetitive behaviors performed to relieve distress related to obsessions. It is a prevalent psychiatric condition that affects 2-3% of the population and almost 30% of the patients can be refractory to first-line pharmacotherapy and psychotherapy. In these cases, neurosurgical procedures such as stereotactic lesioning and deep brain stimulation (DBS) are an option. Combining these treatments is relatively uncommon. The aim of this study is to report our experience with subthalamic nucleus (STN) stimulation in a patient that had previously undergone bilateral cingulotomy and relapsed. To our knowledge, this therapeutic approach has not been published in the literature before.Clinical description: 36 year-old male. OCD diagnosed more than twenty years ago with sexual and intra-psychic aggressive obsessions associated to compulsions dominated by mental rituals and repetitive hand movements. He required four hospital admissions, one of them after a major depressive episode with suicide attempt. Electro-convulsive therapy was carried out at that time. He received cognitive-behavioral therapy and complete pharmacological treatment. The patient had a severe OCD with 34 points in Yale-Brown Obsessive-Compulsive Scale (YBOCS). SPECT imaging showed bilateral prefrontal cortex hypoperfusion and right caudate nucleus hyperactivity. Ultimately, bilateral stereotactic cingulotomy was performed in 2011. The surgery resulted in dramatic improvement of his OCD and mood disorder. 1 year postoperatively YBOCS was reduced by 20 points (59% improvement) and depression remitted. However, 10 years later he showed progressive worsening of the OCD symptoms and mild depression. After several sessions of repetitive trans-cranial magnetic stimulation (rTMS) that had transient effect, the patient was still very disabled (YBOCS= 24). We proposed anteromedial subthalamic nucleus stimulation (amSTN DBS). He was implanted in December 2023 and the stimulator was turned on after one month with a conventional monopolar configuration at 130Hz and 60µs. Middle contacts were chosen according to the postoperative images and electrophysiological data. Interestingly, we found an unusual high power local field potential (LFP) in the theta band (7.81Hz) that was clearly reduced by increasing stimulation (Fig 1). During follow up we had to activate more dorsal contacts using a bipolar configuration due to a dysphoric-anxious reaction immediately elicited by ventral STN stimulation with amplitudes above 2.0mA. Micturition disturbances and subtle right upper limb dyskinesia were also observed. The former resolved with anticholinergic medication and the latter is not troublesome. The patient has now been followed for 20 months and reached YBOCS scores indicating mild OCD (12 points) with 50% improvement. There are no signs of depression. He is now able to work, live alone and take care of his daughter using low doses of medication.Discussion:Different targets, either for lesioning or DBS, have been proposed to treat refractory OCD. Most of them within the same neurobiological circuit involved in OCD pathogenesis. The ventral capsule (VC) and ventral striatum (VS- Nucleus accumbens) are frequently targeted regions. VC/VS DBS significantly decrease OCD symptoms with up to 46% improvement in YBOCS score. A randomized controlled trial of amSTN DBS demonstrated that active stimulation reduced YBOCS score by 11 points (40% improvement) compared to sham-stimulation and 75% of patients were responders. Metanalyses comparing both targets failed to show superiority of one over the other. However, amSTN but not VC/VS DBS significantly improved cognitive flexibility, whereas VC/VS DBS had a greater effect on mood. Capsulotomy and cingulotomy can effectively reduce OCD symptoms with similar results compared to DBS, although with higher incidence of adverse events, as these are irreversible and non-adjustable procedures. Our patient responses to cingulotomy and DBS were comparable to those in the literature and had a great impact in his quality of life. In this case, DBS acted as a rescue therapy after the disappearance of the cingulotomy effects and proved to be very helpful. Other cases of ventral capsule stimulation after capsulotomy have been reported with good resultsConclusions:Either ablative or DBS techniques are effective to alleviate symptoms of severe treatment-resistant OCD. Combining these therapies after one of them has failed may be a reasonable option in selected patients.

We report on a search for axion dark matter in the frequency range near 5.9GHz, conducted using the haloscope technique. The experiment employed an 8-cell microwave resonator designed to extend the accessible frequency range by a multifold factor relative to conventional single-cell configurations, while maintaining a large detection volume. To enhance sensitivity, a flux-driven Josephson parametric amplifier operating near the quantum noise limit was utilized, together with a sideband-summing method that coherently combines mirrored spectral components generated by the Josephson parametric amplifier. Data were acquired over the frequency range 5.83-5.94GHz. With no statistically significant excess observed, we exclude axion-photon couplings g_{aγγ} down to 1.2×10^{-14} GeV^{-1} at a 90%confidence level. The achieved sensitivity approaches the Kim-Shifman-Vainshtein-Zakharov benchmark prediction, setting the most stringent limits to date in this range.

Electron paramagnetic resonance (EPR) spectroscopy enables quantitative measurement of tissue oxygen levels. The conventional single-loop EPR resonator designs limit the oxygen measurements to superficial tissues within 1-3 cm depth and inadequately address clinical requirements for deep-tissue oxygen monitoring in anatomically complex regions and confined body cavities. The aim of this study was to develop a flexible RF coil-based sensor (OxyTrack) designed for real-time oxygen measurements in complex anatomical environments that are typically inaccessible to conventional rigid coil configurations. The RF coil configuration of the OxyTrack included a catheter-like, flexible design that incorporates the OxyChip (oxygen sensor) in the resonant loop. A modified coaxial cable arrangement with braided shielding was used for cavity measurements. The constructed coil/sensor was evaluated for power saturation thresholding, oxygen sensitivity (calibration), mechanical stability, and integrity of the coil under various stress conditions. Biological validation studies were performed to test dynamic oxygen variations in the gastrointestinal tract (GI) of murine subjects. The flexible OxyTrack exhibited an oxygen sensitivity of 14.8 mG/mmHg with a linear response across physiological ranges (0-160 mmHg), maintaining signal integrity under various mechanical stresses. In vivo validation experiments in mice GI tracts demonstrated statistically significant discrimination of rectal tissue oxygenation between normoxic (0.52 ± 0.04 mmHg) and hyperoxic conditions (6.43 ± 0.24 mmHg) with p < 0.001. Pre-clinical imaging compatibility established the absence of significant artifacts. This flexible RF coil sensor enables minimally invasive, real-time oxygen monitoring in complex anatomical locations, with implications for pre-clinical research and potential clinical translation in oxygen-related pathophysiology assessment.

The aviation industry plays a critical role in many aspects of modern life. It makes significant contributions while posing environmental and technical challenges that cannot be ignored. In particular, the increase in global carbon emissions and the need to reduce fossil fuel consumption make All Electric Aircraft (AEA) an increasingly significant alternative. AEA is an emerging concept in the aviation industry today, and advances in battery technologies and electric propulsion systems will accelerate its adoption. This study presents the conversion of the Tecnam P2008 JC to an All Electric Aircraft concept. A suitable battery and electric propulsion system were selected during the conversion process while maintaining the aircraft's structural architecture and operational limitations. A battery pack based on lithium-ion batteries was designed, and integration was completed by selecting the appropriate power electronics components. The electric aircraft's energy consumption and performance analyses on the specified flight route were carried out through simulations. In addition, energy costs and greenhouse gas emissions of electric and conventional configurations are compared. The study results provide an important perspective on the sustainable transformation of aviation by revealing the advantages of fully electric aircraft and the engineering challenges they may face.

Description of Case: A 58 year old man with non-ischemic cardiomyopathy (LVEF 21%) secondary to presumed (non-biopsy proven) cardiac sarcoidosis on prednisone and infliximab status post CRT-D placement, recurrent admissions for VT, and CKD presented to the emergency room with right upper quadrant pain. Chest x-ray revealed right lower lobe pneumonia and he was started on broad-spectrum antibiotics. He was admitted to the ICU and rapidly developed severe acute hypoxemic respiratory failure requiring intubation, maximum ventilator support, and neuromuscular paralysis. He concomitantly developed severe shock requiring high doses of three vasopressors. In this setting, he had hemodynamically unstable runs of monomorphic VT treated with IV amiodarone and lidocaine. He suffered a VT arrest (Image 1), with rates below his device detection zone, and was externally defibrillated. A Shock Team call was convened. He was cannulated on to veno-arterial-venous (V-AV) ECMO for refractory hypoxemia, VT and SCAI E cardiogenic shock. He underwent placement of an axillary Impella 5.5 for LV mechanical unloading. With time, his respiratory and circulatory status improved to the point of being able to liberate to V-V ECMO, which was subsequently decannulated, remaining on low-level Impella support throughout. His course was complicated by anuric renal failure requiring dialysis, mechanical device-related hemolysis, and a large, mobile right atrial thrombus. This clot appeared to be adherent to a PFO and was removed via AngioVac suction thrombectomy with live intra-cardiac echocardiographic guidance (Images 2, 3). Weaning of anti-arrhythmic drugs resulted in recurrence of VT. His back-up pacing rate was increased and he was deeply sedated, started on procainamide, and empirically treated for a sarcoidosis flare with pulse dose steroids, with residual breakthrough VT. Due to his ongoing infections, coagulopathy, multi-organ failure, and VT storm, he was deemed not a candidate for advanced therapies. He was transitioned to comfort-oriented care and passed away. Discussion: This case illustrates the utility of a less conventional ECMO configuration in patients with combined cardiopulmonary failure, while also highlighting the challenge of treating VT storm in a patient with inflammatory cardiomyopathy and septic shock. Finally, we demonstrate the role for suction thrombectomy in extracting large, mobile intra-cardiac thrombi to prevent embolic phenomena.

Abstract In this paper, aimed at designing aft CG (center of gravity) limit for civil aircraft with conventional wing-mounted engine configuration in low-weight takeoff condition, a calculation method considering nose wheel ground maneuverability is proposed. Based on the mechanical model of aircraft during takeoff, a mechanical model is established by introducing rigid body assumption and neglecting the constraints of aerodynamic force and vertical acceleration, and the analytical relationship between the takeoff aft CG limit and the nose wheel vertical load, aircraft weight, engine thrust, and geometric parameters is derived. Combined with the example analysis of X1 aircraft, the deflection angle, acceleration, and moment of inertia under different weights are fitted by using the data of similar aircraft types, and then substituted into the theoretical model to calculate the aft CG limit, which is verified by comparing with the actual design value. The results show that the maximum deviation between the theoretical calculation value and the actual value is 0.66% MAC (error -1.6%) when the aircraft weight is 81, 800 kg, and the deviation is controlled within ± 0.4% MAC under other weights, which verifies the feasibility of the method. The study provides a theoretical basis for the quantitative analysis of nose wheel handling constraints in the design of aircraft CG envelope, and has engineering application value for the optimization of CG corner cut design under the low weight aft CG.

The Modular Multilevel Converter (MMC) has emerged as the preferred architecture for integrating renewable energy power plants into the grid via undersea HVDC cables and HVDC overhead lines. However, to mitigate the significant power pulsations introduced by the single-phase AC–DC conversion in its arms, the MMC necessitates the use of large DC-link capacitors. To address these limitations, the Alternate Arm Converter (AAC) topology integrates MMC arms with Director Switches (DS), thereby reducing the required number of sub-modules, potentially by half, when compared to conventional MMC configurations. Furthermore, the AAC provides inherent DC fault-blocking capability, which is a critical feature for future DC grid applications. Model Predictive Control (MPC) is widely employed due to its flexibility in incorporating multiple control objectives within a unified cost function. Nonetheless, the extensive number of possible switching states in AAC results in substantial computational complexity, posing challenges for real-time control implementation. To alleviate this computational burden, this work proposes the development of machine learning (ML)-based controllers for AAC, leveraging training data generated through model predictive control (MPC) operation. The system architecture utilizes a solar photovoltaic (PV) array as the DC energy source, interfaced with the AC grid via the proposed AACbased high-voltage direct current (HVDC) transmission link. In this study, an artificial neural network (ANN) is employed as the machine learning (ML) framework. The wellness of the proposed scheme is confirmed over a comprehensive simulation analysis that employs a detailed switching converter model.

A Novel Draping Technique for Temporomandibular Joint Arthroscopy: Enhancing Fluid Management and Ergonomics.

Abstract Optoelectronic synapses have attracted considerable attention for emulating biological visual perception by enabling the recognition of complex visual stimuli, including spatial patterns and multicolor information. Despite significant progress, the realization of multicolor classification with simple and scalable device architecture remains a fundamental challenge, requiring strategies that overcome the limitations of conventional device configurations. Here, a scalable van der Waals heterostructure device is presented that enables multicolor optoelectronic processing by vertically integrating solution‐processed molybdenum disulfide (MoS 2 ) as a light‐absorbing layer and single‐walled carbon nanotubes (SWCNTs) as a semiconducting channel. Unlike conventional complex architectures, such as serially connected synaptic devices and optical‐sensors, the approach employs an electronically disconnected but interactive MoS 2 layer to facilitate photon‐modulated carrier doping in the adjacent SWCNTs channel. This configuration enables bi‐directional photocurrent behavior under different wavelength illumination, essential for emulating the retina's chromatic adaptation while maintaining a structurally simple and scalable design. Leveraging this unique bi‐directional photoresponse, an optical neural network framework is integrated that independently processes distinct spectral information, enabling highly efficient multicolor pattern classification. This synergistic strategy is essential for realizing scalable optoelectronic synapses, as evidenced by a classification accuracy of 92.0%, offering a promising platform for next‐generation vision systems.