Food antigens suppress small intestinal tumorigenesis.

Food components suppressing small intestinal tumorigenesis are not well-defined partly because of the rarity of this tumor type compared to colorectal tumors. Using Apcmin/+ mice, a mouse model for intestinal tumorigenesis, and antigen-free diet, we report here that food antigens serve this function in the small intestine. By depleting Peyer's patches (PPs), immune inductive sites in the small intestine, we found that PPs have a role in the suppression of small intestinal tumors and are important for the induction of small intestinal T cells by food antigens. On the follicle-associated epithelium (FAE) of PPs, microfold (M) cells pass food antigens from lumen to the dendritic cells to induce T cells. Single-cell RNA-seq (scRNA-seq) analysis of immune cells in PPs revealed a significant impact of food antigens on the induction of the PP T cells and the antigen presentation capacity of dendritic cells. These data demonstrate the role of food antigens in the suppression of small intestinal tumorigenesis by PP-mediated immune cell induction.

Multi-Phase Rotating Disk Triboelectric Nanogenerator with DC Output for Speed Monitoring.

Triboelectric nanogenerators (TENGs) are highly efficient devices for harvesting mechanical energy. Nevertheless, conventional TENGs often produce AC output, which, coupled with their high crest factor and pulsed output characteristics, poses limitations on their widespread adoption in real scenarios. In this paper, a multi-phase rotating disk triboelectric nanogenerator (MPRD-TENG) characterized by a low crest factor and DC output is prepared through the method of phase superposition. The findings reveal that by enhancing these parameters, namely, increasing the number of rotating disk TENGs, augmenting the number of grids, and elevating the rotational speed, the crest factor of the MPRD-TENG can be effectively reduced. Furthermore, this innovative MPRD-TENG demonstrates its versatility by successfully powering a fire alarm system, thereby offering a promising solution for early warning and monitoring of offshore oil exploration fires. Ultimately, the implementation of machine learning algorithms to train the DC output data collected by the MPRD-TENG significantly enhances the capability to predict and classify signals corresponding to varying speeds with greater precision. Consequently, the integration of machine learning methods not only facilitates a more effective warning system but also bolsters monitoring capabilities for unforeseen situations encountered in real-world engineering projects.

Optimal control strategies for high-efficiency non-isolated DC-DC buck converters in IoT applications: A comparative study.

A DC-DC buck converter (DDBC) plays a crucial role in facilitating the rapid evolution of Internet of Things (IoT) applications across a broad spectrum of load requirements. Achieving high efficiency under diverse load conditions necessitates a meticulous exploration of modulation and control methods. This paper aims to explore literature concerning modulation and control techniques employed in buck converters for IoT applications, with the goal of achieving optimal efficiency. The most often used control methods in the DDBC for power conversion efficiently are adaptive controlled pulse skip modulation (APSM), pulse frequency modulation (PFM), digital pulse width modulation (DPWM), and adaptive on time control (AOT). Based on the major drawbacks of high quiescent current, large ripple, and low efficiency, the control methods used in IoT applications to achieve high efficiency are discussed. The structure of DDBC with the unique controlling method and their capability of suppressing the output ripple voltage and minimizing quiescent current are briefly addressed. Comparison among the methods exhibits how control methods can achieve high efficiency. This paper outlines the major challenges in power converter control for future research and development.

High-temperature transport properties of a two-dimensional weakly doped parabolic semiconductor.

A version of the Mexican-hat Hamiltonian is used to study high-temperature transport properties of a two-dimensional weakly doped semiconductor with electron-hole symmetric bands. For a finite doping level and a temperature-dependent band gap, we find a closed analytical form of the temperature-dependent chemical potential. The effective concentrations of charge carriers participating in transport coefficients are analyzed in the space spanned by the total electron concentration and temperature. It is shown that these concentrations are the sum of a residual contribution and two thermally activated contributions, with a complicated dependence on temperature. The analytical expression for the Hall coefficient RHis also found. It is argued that it is a non-monotonic function of the doping level with the maximum at the doping nmax that is a linear function of temperature at high enough temperatures. The analysis of the real part of the interband conductivity shows that it is inversely proportional to incoming photon energy at low temperatures and that it is nearly constant over a wide energy range at high temperatures. This results are expected to be of significant importance in understanding transport and optical properties of weakly doped two-dimensional semiconductors with nearly symmetric parabolic bands. .

Difference between sentinel and non-sentinel lymph nodes in the distribution of dendritic cells and macrophages: An immunohistochemical and morphometric study using gastric regional nodes obtained in sentinel node navigation surgery for early gastric cancer.

The sentinel lymph node (SN) concept has a significant impact on cancer surgery. We aimed to examine which morphology of dendritic cells (DCs) and macrophages corresponds to "preconditioning" of the SN against cancer. Although macrophages are generally able to tolerate cancer metastasis, the CD169-positive subtype is believed to be a limited exception. Immunohistochemical and morphometric analyses were performed to examine DC-SIGN-, CD68-, and CD169-positive cells in SNs and non-SNs of 23 patients with gastric cancer with or without nodal metastasis. All patients survived for >5 years without recurrence. DCs were present in the subcapsular, paracortical, and medullary sinuses, the endothelia of which expressed DC-SIGN and smooth muscle actin (SMA). In the non-SNs of patients without metastasis, subcapsular DCs occupied a larger area than SNs, and this difference was statistically significant. Conversely, subcapsular DCs were likely to have migrated to the paracortical area of the SNs. DC clusters often overlapped with macrophage clusters; however, histiocytosis-like clusters of CD169-negative macrophages showed a smaller overlap. We found a significantly larger overlap between DC-SIGN and CD169-positive clusters in SNs than in non-SNs; the larger overlap seemed to correspond to a higher cross-presentation of cancer antigens between these cell populations. DC-SIGN-CD169-double positive cells might exist within this overlap. SNs in gastric cancers are usually preconditioned as a frontier of cancer immunity, but they may sometimes be suppressed earlier than non-SNs. DC-SIGN- and CD169-positive cells appeared to decrease owing to a long lag time from the primary lesion occurrence and a short distance from the metastasis.

The combination of apatinib and antigen-specific DC-induced T cells exert antitumor effects by potently improving the immune microenvironment of osteosarcoma.

Objective: Osteosarcoma (OS) is the most common primary bone sarcoma with a high propensity for local invasion and metastasis. Although the antitumor effect of apatinib has been well confirmed in advanced OS, the synergistic effect of apatinib and immunotherapies has not yet been elucidated. Methods: In this study, we established tumour-bearing mice and observed tumour size with low and high doses of apatinib treatments. The expression of 17 cytokines, including vascular endothelial growth factor (VEGF), was detected by protein microarray analysis. Moreover, we designed apatinib and antigen-specific dendritic cell (DC)-T combination treatment for tumour-bearing mice. Tumour growth was detected by statistical analysis of tumour size and microvessel density (MVD) counting, the protein expression of VEGF by western blotting, the cytokines interleukin 6 (IL-6), IL-17 and interferon-gamma (IFN-γ) by enzyme-linked immunosorbent assay (ELISA), and the numbers of myeloid-derived suppressor cells (MDSCs) and tumour-infiltration macrophages (TAMs) by flow cytometry. Results: The results showed that apatinib efficiently suppressed tumour growth, and high-dose apatinib achieved a stronger effect. The same was true for DC-T immunotherapy. However, their combination treatment revealed a better oncolytic effect. Meanwhile, apatinib or DC-T treatment inhibited the expression of VEGF and the proangiogenic mediators IL-6 and IL-17 but increased IFN-γ production. Combination therapy further reduced/increased these effects. In addition, the combination treatment reduced MDSC but enhanced TAM-M1 ratios in the OS microenvironment. These findings indicated that apatinib and antigen-specific DC-T combination therapy was more efficient in oncolysis by regulating pro-/anti-angiogenic inducers and improving the immune state in the OS microenvironment. Conclusion: This study proved that it was feasible to employ immunotherapy with therapeutic agents in OS treatment, which may provide a new approach in addition to the combination of surgery with chemotherapy in tumour treatment.

Solar water splitting for hydrogen production using Zn electrodes: a green and sustainable approach.

The global transition towards clean and sustainable energy sources has led to an increasing interest in green hydrogen production. The present work focuses on the development and assessment of a solar-assisted green hydrogen production system. The basic objective of this work is to investigate the influence of solar radiation to drive the electrolysis process for green hydrogen production. The system design includes photovoltaic solar panel to capture solar radiation and convert it into electrical energy. This energy is further utilized to operate an electrolyzer with zinc electrodes that facilitates the water-splitting reaction resulting in the production of hydrogen gas. The solar panel outputs along with global radiation and other relevant climatic conditions are monitored. The hydrogen production is analyzed at three different voltages, i.e., 11 V, 12 V, and 13 V. After 60 min of operations, the maximum amount of hydrogen (2952 mL) is produced at 13 V. The fabricated electrolyzer has been found suitable and economically feasible.

Fuzzy inference system enabled neural network feedforward compensation for position leap control of DC servo motor.

To improve dynamic performance and steady-state accuracy of position leap control of the direct current (DC) servo motor, a fuzzy inference system (FIS) enabled artificial neural network (ANN) feedforward compensation control method is proposed in this study. In the method, a proportional-integral-derivative (PID) controller is used to generate the baseline control law. Then, an ANN identifier is constructed to online learn the reverse model of the DC servo motor system. Meanwhile, the learned parameters are passed in real-time to an ANN compensator to provide feedforward compensation control law accurately. Next, according to system tracking error and network modeling error, an FIS decider consisting of an FI basic module and an FI finetuning module is developed to adjust the compensation quantity and prevent uncertain disturbance from undertrained ANN adaptively. Finally, the feasibility and efficiency of the proposed method are verified by the tracking experiments of step and square signals on the DC servo motor testbed. Experimental results show that the proposed FIS-enabled ANN feedforward compensation control method achieves lower overshoot, faster adjustment, and higher precision than other comparative control methods.

Dual-Mode Embedded Impulse-Radio Ultra-Wideband Radar System for Biomedical Applications.

This paper presents a real-time and non-contact dual-mode embedded impulse-radio (IR) ultra-wideband (UWB) radar system designed for microwave imaging and vital sign applications. The system is fully customized and composed of three main components, an RF front-end transmission block, an analog signal processing (ASP) block, and a digital processing block, which are integrated in an embedded system. The ASP block enables dual-path receiving for image construction and vital sign detection, while the digital part deals with the inverse scattering and direct current (DC) offset issues. The self-calibration technique is also incorporated into the algorithm to adjust the DC level of each antenna for DC offset compensation. The experimental results demonstrate that the IR-UWB radar, based on the proposed algorithm, successfully detected the 2D image profile of the object as confirmed by numerical derivation. In addition, the radar can wirelessly monitor vital sign behavior such as respiration and heartbeat information.

Ultrasonic Obstacle Avoidance and Full-Speed-Range Hybrid Control for Intelligent Garages.

In the current study, which focuses on the operational safety problem in intelligent three-dimensional garages, an obstacle avoidance measurement and control scheme for the AGV parking robot is proposed. Under the premise of high-precision distance detection using Kalman filtering, a mathematical model of a brushless DC (BLDC) motor with full-speed range hybrid control is established. MATLAB/Simulink (R2022a) is used to build the control model, which has dual closed-loop vector-controlled motors in the low- to medium-speed range, with photoelectric encoders for speed feedback. The simulation results show that, at lower to medium speeds, the maximum overshoot of the output response curve is 1.5%, and the response time is 0.01 s. However, at higher speeds, there is significant jitter in the speed output waveform. Therefore, the speed feedback is switched to a sliding mode observer (SMO) instead of the original speed sensor at high speeds. Experiments show that, based on the SMO, the problem of speed waveform jitter at high motor speeds can be significantly improved, and the BLDC motor system has strong robustness. The above shows that the motor speed under the full-speed range hybrid control system can meet the AGV control and safety requirements.

Multivariate approach to assess the bioactive compounds of Atractylodes chinensis (DC.) Koidz in different harvest periods.

BACKGROUND: The Atractylodes chinensis (DC.) Koidz (A. chinensis) Chinese herb possesses numerous therapeutic properties and is extensively utilized in the pharmaceutical industry. Its quality is closely associated with the harvest periods. However, the optimal quality and harvest periods of A. chinensis remain elusive. METHODS: The bioactive compounds of perennial A. chinensis were detected by ultra-high-performance liquid chromatography coupled with quadrupole Orbitrap mass spectrometry (UHPLC-Q-Orbitrap/MS) metabolomics, and differentially abundant compounds were selected by multivariate statistical analysis. Then, variations in the content of differential compounds in samples harvested at different periods were analyzed, while correlation analysis was carried out on the differential compounds to determine the suitable harvest period for distinct components. RESULTS: A total of 61 bioactive compounds were detected in all samples, grouped into 9 known classes. The results revealed that the chemical compositions of A. chinensis at different harvest periods were significantly different. The volatile oil content in the four-year-old and five-year-old samples was relatively high, at 31.92 mg/g and 32.42 mg/g, respectively. There were also significant differences in the content of the six active ingredients, for example, the five-year-old sample had the highest content of atractylodin (4.38 mg/g). Indeed, the harvest period was correlated with the abundance of most bioactive compounds. Specifically, quinquennial samples were significantly negatively correlated with the abundance of organic acids and aliphatics while moderately positively correlated with the abundance of other classes of bioactive compounds. CONCLUSIONS: According to the results, the ideal harvest time for atractylenolide Ⅲ was 3 years. Regarding organic acids, the optimal harvest time was around 2-3 years. Taken together, these results offer valuable insights to producers for optimizing the harvest period for A. chinensis.

Antibacterial and Antioxidant Activities of Hydroalcoholic and Phenolic Extracts from Ternstroemia dentisepala and T. lineata Leaves.

Traditional Mexican medicine commonly uses infusions of Ternstroemia spp. to treat insomnia, injuries, and infections. The antibacterial activities of Ternstroemia dentisepala and Ternstroemia lineata were evaluated for the first time against a panel of Gram-positive and Gram-negative bacteria that have implications for human health, including Enterococcus faecalis, Streptococcus agalactiae, Streptococcus pyogenes, Salmonella typhi, Pseudomonas aeruginosa, and Vibrio parahaemolyticus. Furthermore, the scavenging potential of the hydroalcoholic (HAEs) and total phenolic extracts (TPEs) from the leaves of both plants by a 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) assay (ABTS•+) was determined. Also, the total phenolic contents of the HAEs using the Folin-Ciocalteu reagent were assayed. T. dentisepala HAE and TPE were active against all bacterial strains tested, with a minimum inhibitory concentration between 1.0 and 6.0 mg/mL, with the last one being the most active. However, the T. lineata extracts only demonstrated effectiveness against S. typhi and P. aeruginosa. The TPEs from T. dentisepala and T. lineata improved the activity by approximately 30% in all bacteria tested in comparison with the HAEs. The T. dentisepala HAE had a higher total phenolic content than the T. lineata extract, which was consistent with its ABTS•+-scavenging activity. The two HAEs had different chemical profiles, mostly because of the types and amounts of phenolic compounds they contained. These profiles were obtained using thin-layer chromatography (TLC), high-performance liquid chromatography (HPLC), and proton nuclear magnetic resonance (1H NMR) experiments.

Effectiveness analysis of deceleration capacity and traditional heart rate variability in diagnosing vasovagal syncope.

Background: Vasovagal syncope (VVS) is a prevalent medical condition with a lack of efficient methods for its detection. Aim: This study aimed to explore an objective clinical indicator in diagnosing VVS. Methods: The retrospective analysis involved clinical data of 243 syncope patients from 1 June 2020 to 31 July 2023. Among them, 108 patients had a negative result in the tilt test (TTT), while the remaining 135 patients had a positive result in the TTT. Relevant statistical methods were utilized to examine the correlation between VVS and different indicators of heart rate variability. Results: After screening, 354 patients being considered for VVS were evaluated, resulting in a final sample size of 243. Sex, age, deceleration capacity (DC), and standard deviation of all normal-to-normal intervals (SDNNs) were the variables that showed statistical significance between the TTT(-) group and the TTT(+) group. Independent risk factors identified by multivariate logistic regression were DC [odds ratio (OR) 1.710, 95% confidence interval (CI) 1.388-2.106, P < 0.001] and SDNN (OR 1.033, 95% CI 1.018-1.049, P < 0.001). Comparing the groups, receiver operating characteristic analysis revealed a notable distinction in both DC and SDNN [the respective areas under the curve were 0.789 (95% CI 0.730-0.848) and 0.702 (95% CI 0.637-0.767); the cutoff values were 7.15 and 131.42; P < 0.001, respectively]. Conclusion: In summary, DC can function as an impartial and easily accessible clinical marker for differentiating VVS. A value exceeding 7.15 ms might suggest a higher likelihood of syncope.

STING-activating dendritic cell-targeted nanovaccines that evoke potent antigen cross-presentation for cancer immunotherapy.

Recently, nanovaccine-based immunotherapy has been robustly investigated due to its potential in governing the immune response and generating long-term protective immunity. However, the presentation of a tumor peptide-major histocompatibility complex to T lymphocytes is still a challenge that needs to be addressed for eliciting potent antitumor immunity. Type 1 conventional dendritic cell (cDC1) subset is of particular interest due to its pivotal contribution in the cross-presentation of exogenous antigens to CD8+ T cells. Here, the DC-derived nanovaccine (denoted as Si9GM) selectively targets cDC1s with marginal loss of premature antigen release for effective stimulator of interferon genes (STING)-mediated antigen cross-presentation. Bone marrow dendritic cell (BMDC)-derived membranes, conjugated to cDC1-specific antibody (αCLEC9A) and binding to tumor peptide (OVA257-264), are coated onto dendrimer-like polyethylenimine (PEI)-grafted silica nanoparticles. Distinct molecular weight-cargos (αCLEC9A-OVA257-264 conjugates and 2'3'-cGAMP STING agonists) are loaded in hierarchical center-radial pores that enables lysosome escape for potent antigen-cross presentation and activates interferon type I, respectively. Impressively, Si9GM vaccination leads to the upregulation of cytotoxic T cells, a reduction in tumor regulatory T cells (Tregs), M1/M2 macrophage polarization, and immune response that synergizes with αPD-1 immune checkpoint blockade. This nanovaccine fulfills a dual role for both direct T cell activation as an artificial antigen-presenting cell and DC subset maturation, indicating its utility in clinical therapy and precision medicine.

Design of a high voltage gain converter using coupled inductor with reduced voltage stress for photovoltaic energy based systems.

This paper presents the design and analysis of a high voltage gain converter utilizing a coupled inductor with reduced voltage stress, specifically for photovoltaic energy-based systems. The proposed converter employs a two-winding coupled inductor and voltage multiplier cells to achieve an increase in output voltage while mitigating voltage stress across semiconductor components. Additionally, the voltage multiplier cells function as voltage clamps for the power switch, further enhancing the converter's performance. The converter features a single switch design, which simplifies control, reduces cost, and improves reliability. Key advantages of the converter include a low component count, a common ground between input and output ports, and high efficiency. The converter's performance is thoroughly investigated through mode analysis and steady-state analysis. Comparative evaluations with similar converters are conducted to highlight the benefits and performance of the proposed design. To validate the theoretical analysis, a 125 W prototype with 26 V input and 200 V output voltages operating at a 50 kHz switching frequency is developed, and experimental results are presented, demonstrating the effectiveness and practicality of the proposed high voltage gain converter.

A new neuro-fuzzy controller based maximum power point tracking for a partially shaded grid-connected photovoltaic system.

Today, renewable energy systems like photovoltaic system are widely used in various applications. Among the different types of microgrids, hybrid microgrids are the most used type, therefore, inverters should be used to exchange power between DC and AC sides. According to the existing economic issues, extracting the maximum possible power from these systems are an important issue. This paper presents a new neuro-fuzzy controller for achieving maximum power point tracking (MPPT) in a grid-connected PV system under partially shaded conditions. This controller uses the Gravity Search Algorithm (GSA) to track the global maximum power point (GMPP) of the presented grid-connected PV system. The method controls the grid-connected inverter at the desired voltage to achieve maximum power after receiving its required specifications from the system. The Matlab/Simulink software is used to evaluate the performance of the proposed method. The results show that the proposed method can track the maximum power point under uniform and partial shading conditions with high speed and accuracy. Specifically, the proposed algorithm improves the tracking speed and increases the power output compared to traditional methods. The neuro-fuzzy controller's adaptive capabilities allow it to respond efficiently to dynamic changes in shading, ensuring stable and optimal power output. These advantages make the proposed method a significant improvement over existing MPPT techniques.

Temporomandibular Joint Discectomy in Patients With Disc Displacement: Assessment of Osteoarthritis at 10- and 30-Year Follow-Up.

BACKGROUND: Few ≥ 10-year follow-up studies of temporomandibular joint (TMJ) discectomy without replacement in patients with disc displacement (DD) analyse the relationship between the surgery and osteoarthritis (OA) exist. OBJECTIVES: To radiologically evaluate bony joint changes and OA development 10 and 30 years after TMJ discectomy as well as 30-year clinical outcome. METHODS: Twenty-two discectomy patients at the University of Oslo, Norway, with records confirming initial TMJ diagnosis and attendance of 10-year radiological follow-up were evaluated and eligible for 30-year follow-up. Primary variables: discectomy and CT-/CBCT-diagnosed OA at follow-ups. Secondary variables: perioperative TMJ diagnoses and remodelling at follow-up. Unoperated TMJs (Unop-TMJs) in unilaterally operated patients were controls. Statistical association and correlation analyses were performed for the 10-year follow-up (significance level p < 0.05). RESULTS: Twenty-two patients attended the 10-year follow-up (mean follow-up 11 years) with 27 operated TMJs (Op-TMJs) and 17 Unop-TMJs. OA perioperatively was associated with DD without reduction (p = 0.001) and additional disc abnormalities (p = 0.016). Although statistically non-significant, the number of TMJs with OA had increased at 10-year follow-up (p = 0.114, Op-TMJs: 14 to 20 joints; Unop-TMJs: 2 to 5 joints). Remodelling was correlated with discectomy (p = 0.003) and to OA (p = 0.006). Nine patients attended the 30-year follow-up (mean follow-up 32 years, 11 Op-TMJs). All TMJs with OA at 30-year follow-up had OA at 10-year follow-up. Mean maximal interincisal opening was 39 mm. No DC-TMD-diagnosed arthralgia was found. CONCLUSION: Osteoarthritis developed similarly between Op- and Unop-TMJs. Only remodelling, not OA, was correlated to the surgery. The clinical results were still favourable at final follow-up.

Performance comparison between PID and Fuzzy logic controllers for the hardware implementation of traditional high voltage DC-DC boost converter.

This research introduces a hardware implementation of DC-DC boost converter designed to elevate the DC voltage generated by renewable sources while effectively regulating it against line and load fluctuations for inverter application. The main objective is to boost the DC link voltage to the level of Vmax in the output AC voltage obtained from inverter circuits. This enables the inverters for transformer-less power conversion from DC to AC to reduce magnetic losses, size and weight of the inverter circuits used in the utility application. The proposed converter's topology and switching sequences play a crucial role in enhancing overall performance. Utilizing a Zero Current Switching (ZCS) technique, the converter efficiently recovers stored energy from the magnetics. The proposed converter attained the output voltage of 350 V at its current of 1A from the input voltage of 20 V at its current of 19 A. The ZCS technique and the topology of the converter enhances the efficiency to 92 %. The study employs traditional Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) controllers for effective voltage regulation, analysing time domain specifications. Additionally, a Fuzzy logic controller is introduced as an alternative to PID controllers to compare their performance metrics, evaluating the optimization of the converter's transient and steady-state behaviours. The proposed converter is designed, simulated and their performance metrics are analysed using MATLAB for both with and without controllers. The step-time characteristics of the proposed converter with load resistance of RL = 500 Ω and an input voltage of Vi = 20 V has been determined and analysed. The PID system attained a rise time of 88.781 ms, an overshoot value of 9.341 %, and a steady-state error of 0.00043. The fuzzy system achieved a low-rise time of 10.624 ms, a low overshoot of 0.55 %, and a steady-state error of 0.0584. The hardware prototype of the proposed converter is implemented with a FPGA based PID and Fuzzy logic controllers for providing better voltage regulation and to improve the performance metrics of the converter. The simulation and experimental findings are contrasted, examined, and confirmed to ensure improved consistency in performance measures.

Design and implementation of a universal converter for microgrid applications using approximate dynamic programming and artificial neural networks.

This paper introduces a novel design for a universal DC-DC and DC-AC converter tailored for DC/AC microgrid applications using Approximate Dynamic Programming and Artificial Neural Networks (ADP-ANN). The proposed converter is engineered to operate efficiently with both low-power battery and single-phase AC supply, utilizing identical side terminals and switches for both chopper and inverter configurations. This innovation reduces component redundancy and enhances operational versatility. The converter's design emphasizes minimal switch usage while ensuring efficient conversion to meet diverse load requirements from battery or AC sources. A conceptual example illustrates the design's principles, and comprehensive analyses compare the converter's performance across various operational modes. A test bench model, rated at 3000W, demonstrates the converter's efficacy in all five operational modes with AC/DC inputs. Experimental results confirm the system's robustness and adaptability, leveraging ADP-ANN for optimal performance. The paper concludes by outlining potential applications, including microgrids, electric vehicles, and renewable energy systems, highlighting the converter's key advantages such as reduced complexity, increased efficiency, and broad applicability.

Efficient DC motor speed control using a novel multi-stage FOPD(1 + PI) controller optimized by the Pelican optimization algorithm.

This paper introduces a novel multi-stage FOPD(1 + PI) controller for DC motor speed control, optimized using the Pelican Optimization Algorithm (POA). Traditional PID controllers often fall short in handling the complex dynamics of DC motors, leading to suboptimal performance. Our proposed controller integrates fractional-order proportional-derivative (FOPD) and proportional-integral (PI) control actions, optimized via POA to achieve superior control performance. The effectiveness of the proposed controller is validated through rigorous simulations and experimental evaluations. Comparative analysis is conducted against conventional PID and fractional-order PID (FOPID) controllers, fine-tuned using metaheuristic algorithms such as atom search optimization (ASO), stochastic fractal search (SFS), grey wolf optimization (GWO), and sine-cosine algorithm (SCA). Quantitative results demonstrate that the FOPD(1 + PI) controller optimized by POA significantly enhances the dynamic response and stability of the DC motor. Key performance metrics show a reduction in rise time by 28%, settling time by 35%, and overshoot by 22%, while the steady-state error is minimized to 0.3%. The comparative analysis highlights the superior performance, faster response time, high accuracy, and robustness of the proposed controller in various operating conditions, consistently outperforming the PID and FOPID controllers optimized by other metaheuristic algorithms. In conclusion, the POA-optimized multi-stage FOPD(1 + PI) controller presents a significant advancement in DC motor speed control, offering a robust and efficient solution with substantial improvements in performance metrics. This innovative approach has the potential to enhance the efficiency and reliability of DC motor applications in industrial and automotive sectors.