A Novel Regulation Technique and Its Application to Design of Embedded SC DC-DC Converters

An optimized design of the monolithic switched capacitor DC-DC converter is presented.The general topologic circuit and its basic operating principles are discussed theoretically.Circuit equivalent resistance regulation method is proposed as a feasible method to design the on-chip converters.N-channel MOSFETs,instead of Schottky diodes,are used as the diodes in the converters because of their processing compatibility in monolithic fabrication.One more manufacture step,however,is expected to adjust the threshold voltage of the MOSFETs for improving output characteristics of the converters.As an example,a step-up switched-capacitor converter is fabricated in a 2μm p-well double-poly single-metal CMOS technology with breakdown voltage of 15V.Test results indicate that a single sampling cell with 0.4mm 2 of die size can deliver energy up to 0.63mW at 5V output under the condition of 3V input.Efficiency of the tested sample is 68% at 9.8MHz switching frequency...

Masquelet technique using an allogeneic cortical bone graft for a large bone defect:A case report

BACKGROUND The induced-membrane technique was initially described by Masquelet as an effective treatment for large bone defects,especially those caused by infection.Here,we report a case of chronic osteomyelitis of the radius associated with a 9 cm bone defect,which was filled with a large allogeneic cortical bone graft from a bone bank.Complete bony union was achieved after 14 months of follow-up.Previous studies have used autogenous bone as the primary bone source for the Masquelet technique;in our case,the exclusive use of allografts is as successful as the use of autologous bone grafts.With the advent of bone banks,it is possible to obtain an unlimited amount of allograft,and the Masquelet technique may be further improved based on this new way of bone grafting.CASE SUMMARY In this study,we reported a case of repair of a long bone defect in a 40-year-old male patient,which was characterized by the utilization of allograft cortical bone combined with the Masquelet technique for the treatment of the patient's long bone defect in the forearm.The patient's results of functional recovery of the forearm were surprising,which further deepens the scope of application of Masquelet technique and helps to strengthen the efficacy of Masquelet technique in the treatment of long bones indeed.CONCLUSION Allograft cortical bone combined with the Masquelet technique provides a new method of treatment to large bone defect.

An Enhanced Lung Cancer Detection Approach Using Dual-Model Deep Learning Technique

Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.

Advancements and challenges in neuroimaging for the diagnosis of intracranial aneurysms:Addressing false positive diagnoses and emerging techniques

Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We discuss how conditions like arterial occlusion with vascular stump formation and infundibular widening can mimic aneurysms,particularly in the anterior circulation.The article compares various imaging modalities,including computer tomography angiogram,magnetic resonance imaging/angiography,and digital subtraction angiogram,highlighting their strengths and limitations.We emphasize the im-portance of accurate differentiation to avoid unnecessary surgical interventions.The potential of emerging technologies,such as high-resolution vessel wall ima-ging and deep neural networks for automated detection,is explored as promising avenues for improving diagnostic accuracy.This manuscript underscores the need for continued research and clinical vigilance in the diagnosis of intracranial aneurysms.

Mismatch Calibration Techniques in Successive Approximation Analog-to-Digital Converters

Comparator offset cancellation and capacitor self-calibration techniques used in a successive approximation analog-to-digital converter （SA-ADC） are described. The calibration circuit works in parallel with the SAADC by adding additional calibration clock cycles to pursue high accuracy and low power consumption, and the calibrated resolution can be up to 14bit. This circuit is used in a 10bit 3Msps successive approximation ADC. This chip is realized with an SMIC 0. 18μm 1.8V process and occupies 0.25mm^2 . It consumes 3. 1mW when operating at 1.8MHz. The measured SINAD is 55. 9068dB, SFDR is 64. 5767dB, and THD is - 74. 8889dB when sampling a 320kHz sine wave.

Modeling, Steady-State Analysis of a SEPIC dc-dc Converter Based on Switching Function and Harmonic Balance Technique

The paper presents modeling approach of a Single Ended Primary Inductance Converter (SEPIC) system. The complete model derivation of the SEPIC converter system has been presented in different modes of operation. Steady state and small signal analysis was carried out on the converter dynamic equations using the method of Harmonic balance Technique. The steady state variables and their respective ripple quantities obtained were plotted against duty ratio D. The results obtained for a supply input voltage of 60 volts to the converter at a duty ratio of D = 0.8 , compares well with simulation results.

NEW PERTURBATION TECHNIQUE FOR TRANSIENT ANALYSIS AND ITS APPLICATIONS IN DC-DC PWM SWITCHING POWER CONVERTERS

An improved perturbation technique proposed in a recent paper (Int. J. Electronics, vol. 63, pp.403-414) has been successfully applied to steady-state analysis of PWM switching converters. This paper extends the algorithm to transient analysis of a broader class of non-linear systems. As an example, the transient response of a Boost PWM switching converter is analyzed to demonstrate its simplicity and accuracy.

Semi-Automatic Modeling Technique of Torque Converter Flow Passage

The modeling technique of hydrodynamic torque converter flow passage was investigated. The semi-automatic modeling technique of torque converter flow passage was proposed. The flow passage model of each converter wheel is considered as a revolution entity sliced by two curved surfaces. In order to generate the revolution entity, a new approximation method, condition optimum arc approximation, was proposed. The method was used to approximate the meridional streamlines of the inner and outer wall. As a result, the three-dimensional revolution entity can be conveniently generated. In order to create slice surfaces, the central stream surface of flow passage was approximated with a quadric surface. The normal vector of the quadric surface and the thickness/thickness-function of bade were used to calculate the discrete point coordinates of blade surfaces. Via the rotation transformation to the coordinates, the discrete point coordinates of slice surfaces were obtained. A parameterized program code used for the hydrodynamic torque converter design and semi-automatic modeling was developed. Modeling errors were calculated and analyzed. The flow passage model was generated in several minutes with the help of the program code, Auto CAD and Solidworks software. Finally, the model was inputted into Gambit, and the pre-processing task used for the numerical simulation of torque converter flow field was successfully completed. The investigation results show that the semi-automatic modeling not only can ensure the accuracy of modeling, but also librates the research and design workers of torque converter from the time-consuming modeling work, which paves the way for the numerical simulation of the complex flow field of the hydrodynamic torque converter.

LIMITATION OF SOFT-SWITCHING TECHNIQUE IN AC/DC POWER CONVERTER'S EFFICIENCY IMPROVEMENT

Soft-switching techniques are attractive to unity-power-factor AC/DC converter in the view of the size reduction and EMI suppression. A soft-switched boost PFC converter has been studied based on its topology analysis, PSIM simulation and circuit experiment. A special limitation of soft-switching techniques has been found in their AC/DC applications.

Application research on ZVZCS full-bridge converter technique

Based on ZVZCS （zero voltage zero current switching） full bridge converter technique, a novel inverter welding power supply is designed, in which the secondary side of the transformer adopts passive clamping circuit to reduce voltage stress of rectifying components. This supply can realize power switches ZVS （zero voltage switching ） or ZCS （zero current switching） within a very wide range of load; Only through setting up blocking capacitor in the primary side of transformer, the power transformer＇s bias in the full-bridge converter is suppressed and the primary current can be reset easily. In addition, how to calculate the blocking capacitor and its influence to power supply performance are also subjects discussed in this paper.

A Novel Over-Current Protection Technique Applied to Peak-Current Type DC-DC Converter

The change of the over-current protection point of the power switches, caused by slope compensation, is analyzed in detail. It is discovered that the peak current protecting value increases as the duty cycle decreases. As a result, the safety operation of the switches is damaged greatly. A novel solution to improve over-current protection with constant peak current limitation is proposed by inducing synchronous slope compensation into the current limit function instead of the original constant voltage. The design principle and method of the protection circuit based on a UC3846 PWM controller for the interleaved dual-forward converter is presented. Experimental results are given to verify the analysis.

Buck converter stability techniques for secondary filters and adaptive voltage positioning

To reduce output voltage noise and improve dynamic response performance,this study designed a buck converter on the basis of secondary filters and adaptive voltage positioning(AVP).A hybrid control method was proposed for the compensation of the secondary filter.The introduction of a high-frequency feedback path,in addition to the traditional feedback path,effectively improved the influence of the secondary filter on the loop stability and direct current regulation performance.A small-signal model of the buck converter based on the proposed control method was derived,and the stability and selection of control parameters were analyzed.AVP is realized using an easy-to-implement and low-cost control method that was proposed to improve dynamic response performance by changing the low-frequency gain of the control loop and load regulation of the output voltage.The experimental results of the buck converter showed that the proposed method effectively reduced the output voltage noise by 50%and improved the dynamic response capability to meet the target requirements of mainstream electronic systems.

Inductor Losses Estimation in DC-DC Converters by Means of Averaging Technique

A suitable inductor modeling for power electronic DC-DC converters is presented in this paper. It is developed with the aim of improving inductor losses estimation achievable by averaged models, which inherently neglect inductor current ripple. In order to account for its contribution to the overall inductor losses, an appropriate parallel resistance is thus enclosed into the inductor model, whose value should be chosen in accordance with the DC-DC converter operating conditions. This allows the development of improved averaged models of DC-DC converters, especially in terms of power losses estimation. The effectiveness of the proposed modeling approach has been validated through a simulation study, which refers to the case of a boost DC-DC converter and is performed by means of a suitable circuit simulator designed for rapid modelling of switching power systems （SIMetrix/SIMPLIS）.

EMI Reduction in Low Input Ripple DC-DC Converter using Chaos PWM technique

This paper presents a chaotic PWM switching technique for a high boost DC-DC converter with a very low ripple at the input current.The use of a choatic PWM allows a reduction of Electromagnetic In(EMI)at the output of power converters by spreading the energy spectrum of the output voltage.In this paper a chaotic PWM,using the Chua oscillator,has been implemented in Matlab for the converter under study and a comparison with a traditional PWM control has been done.A detailed description of the generation of the chaotic carrier is presented and the effect on the output EMI mitigation has been shown.

A Dual-Mode Step-up DC/DC Converter IC with Current-Limiting and EMI Reduction Techniques

This paper presents a novel dual-mode step-up （boost） DC/DC converter. Pulse-frequency modulation （PFM） is used to improve the efficiency at light load. This converter can operate between pulse-width modulation （PWM） and pulse-frequency modulation. The converter will operate in PFM mode at light load and in PWM mode at heavy load. The maximum conversion efficiency of this converter is 96%. The conversion efficiency is greatly improved when load current is below 100 mA. Additionally, a soft-start circuit and a variable-sawtooth frequency circuit are proposed in this paper. The former is used to avoid the large switching current at the start up of the converter and the latter is utilized to reduce the EMI of the converter.

The General Technique of Selected Harmonics Elimination for Multilevel Converters

Forhigh power applications,multilevel converters have many advantages in comparison with other circuit topologies with output transformers. Cascaded inverters are one type of multilevel converters,they are easy to implement,very suitable for modularized layout and packaging.Their manufacturing cost is low.A multilevel PWM technique,called as General Technique of Selected Harmonics Elimination (GTSHE) ,is proposed in the paper. A general harmonic elimination equation for N cells,M pulses per half cycle,nth harmonic is derived,and verified by simulation results.

Investigation of Current Control Techniques of AC-DC Interleaved Boost PFC Converter

This paper presents the comparison of various current control strategies employed for an interleaved power factor correction (PFC) boost converter for improving the power quality. The major control strategies discussed in this paper are: peak current control, average current control, hysteresis control, borderline current control and non-linear control. These strategies are implemented in MATLAB/SIMULINK and the performance of the proposed converter is compared under open loop and closed loop operation. From the results, the input current waveform was close to input voltage waveform implying improved power factor and reduced total harmonic distortion for nonlinear current control technique. Experimental results validate the proposed method.

Clinical diagnostic advances in intestinal anastomotic techniques:Hand suturing,stapling,and compression devices

The development of intestinal anastomosis techniques,including hand suturing,stapling,and compression anastomoses,has been a significant advancement in surgical practice.These methods aim to prevent leakage and minimize tissue fibrosis,which can lead to stricture formation.The healing process involves various phases:hemostasis and inflammation,proliferation,and remodeling.Mechanical staplers and sutures can cause inflammation and fibrosis due to the release of profibrotic chemokines.Compression anastomosis devices,including those made of nickel-titanium alloy,offer a minimally invasive option for various surgical challenges and have shown safety and efficacy.However,despite advancements,anastomotic techniques are evaluated based on leakage risk,with complications being a primary concern.Newer devices like Magnamosis use magnetic rings for compression anastomosis,demonstrating greater strength and patency compared to stapling.Magnetic technology is also being explored for other medical treatments.While there are promising results,particularly in animal models,the realworld application in humans is limited,and further research is needed to assess their safety and practicality.

Predictive modeling for postoperative delirium in elderly patients with abdominal malignancies using synthetic minority oversampling technique

BACKGROUND Postoperative delirium,particularly prevalent in elderly patients after abdominal cancer surgery,presents significant challenges in clinical management.AIM To develop a synthetic minority oversampling technique(SMOTE)-based model for predicting postoperative delirium in elderly abdominal cancer patients.METHODS In this retrospective cohort study,we analyzed data from 611 elderly patients who underwent abdominal malignant tumor surgery at our hospital between September 2020 and October 2022.The incidence of postoperative delirium was recorded for 7 d post-surgery.Patients were divided into delirium and non-delirium groups based on the occurrence of postoperative delirium or not.A multivariate logistic regression model was used to identify risk factors and develop a predictive model for postoperative delirium.The SMOTE technique was applied to enhance the model by oversampling the delirium cases.The model’s predictive accuracy was then validated.RESULTS In our study involving 611 elderly patients with abdominal malignant tumors,multivariate logistic regression analysis identified significant risk factors for postoperative delirium.These included the Charlson comorbidity index,American Society of Anesthesiologists classification,history of cerebrovascular disease,surgical duration,perioperative blood transfusion,and postoperative pain score.The incidence rate of postoperative delirium in our study was 22.91%.The original predictive model(P1)exhibited an area under the receiver operating characteristic curve of 0.862.In comparison,the SMOTE-based logistic early warning model(P2),which utilized the SMOTE oversampling algorithm,showed a slightly lower but comparable area under the curve of 0.856,suggesting no significant difference in performance between the two predictive approaches.CONCLUSION This study confirms that the SMOTE-enhanced predictive model for postoperative delirium in elderly abdominal tumor patients shows performance equivalent to that of traditional methods,effectively addressing data imbalance.