Conceptual design of a 714-MHz RFQ for compact proton injectors and development of a new tuning algorithm on its aluminium prototype

Radio frequency quadrupoles(RFQs),which are crucial components of proton injectors,significantly affect the performance of proton accelerator facilities.An RFQ with a high frequency of 714 MHz dedicated to compact proton injectors for medi-cal applications is designed in this study.The RFQ is designed to accelerate proton beams from 50 keV to 4 MeV within a short length of 2 m and can be matched closely with the downstream drift tube linac to capture more particles through a preliminary optimization.To develop an advanced RFQ,challenging techniques,including fabrication and tuning method,must be evaluated and verified using a prototype.An aluminium prototype is derived from the conceptual design of the RFQ and then redesigned to confirm the radio frequency performance,fabrication procedure,and feasibility of the tuning algorithm.Eventually,a new tuning algorithm based on the response matrix and least-squares method is developed,which yields favorable results based on the prototype,i.e.,the errors of the dipole and quadrupole components reduced to a low level after several tuning iterations.Benefiting from the conceptual design and techniques obtained from the prototype,the formal mechanical design of the 2-m RFQ is ready for the next manufacturing step.

Morphological disruption and visual tuning alterations in the primary visual cortex in glaucoma(DBA/2J)mice

Glaucoma is a leading cause of irreve rsible blindness wo rldwide,and previous studies have shown that,in addition to affecting the eyes,it also causes abnormalities in the brain.However,it is not yet clear how the primary visual cortex(V1)is altered in glaucoma.This study used DBA/2J mice as a model for spontaneous secondary glaucoma.The aim of the study was to compare the electrophysiological and histomorphological chara cteristics of neurons in the V1between 9-month-old DBA/2J mice and age-matched C57BL/6J mice.We conducted single-unit recordings in the V1 of light-anesthetized mice to measure the visually induced responses,including single-unit spiking and gamma band oscillations.The morphology of layerⅡ/Ⅲneurons was determined by neuronal nuclear antigen staining and Nissl staining of brain tissue sections.Eighty-seven neurons from eight DBA/2J mice and eighty-one neurons from eight C57BL/6J mice were examined.Compared with the C57BL/6J group,V1 neurons in the DBA/2J group exhibited weaker visual tuning and impaired spatial summation.Moreove r,fewer neuro ns were observed in the V1 of DBA/2J mice compared with C57BL/6J mice.These findings suggest that DBA/2J mice have fewer neurons in the VI compared with C57BL/6J mice,and that these neurons have impaired visual tuning.Our findings provide a better understanding of the pathological changes that occur in V1 neuron function and morphology in the DBA/2J mouse model.This study might offer some innovative perspectives regarding the treatment of glaucoma.

A highly sensitive LITES sensor based on a multi-pass cell with dense spot pattern and a novel quartz tuning fork with low frequency

A highly sensitive light-induced thermoelectric spectroscopy(LITES)sensor based on a multi-pass cell(MPC)with dense spot pattern and a novel quartz tuning fork(QTF)with low resonance frequency is reported in this manuscript.An erbi-um-doped fiber amplifier(EDFA)was employed to amplify the output optical power so that the signal level was further enhanced.The optical path length(OPL)and the ratio of optical path length to volume(RLV)of the MPC is 37.7 m and 13.8 cm^(-2),respectively.A commercial QTF and a self-designed trapezoidal-tip QTF with low frequency of 9461.83 Hz were used as the detectors of the sensor,respectively.The target gas selected to test the performance of the system was acetylene(C2H2).When the optical power was constant at 1000 mW,the minimum detection limit(MDL)of the C2H2-LITES sensor can be achieved 48.3 ppb when using the commercial QTF and 24.6 ppb when using the trapezoid-al-tip QTF.An improvement of the detection performance by a factor of 1.96 was achieved after replacing the commer-cial QTF with the trapezoidal-tip QTF.

Research on MBSE Application for Radio Navigation System

The rapid development of concepts and technologies for civil aircraft navigation systems has put forward higher requirements for agile iteration and integrated design verification in the research and development(R&D)process.Traditional document based system engineering(DBSE)methods have gradually become inadequate.Model based system engineering(MBSE)is fully based on user′s needs and is carried out from top to bottom,in line with the concept of forward design.It is gradually being applied in the development of civil aircraft systems.This article focuses on the civil aircraft radio navigation system and proposes a complete system engineering solution based on models,from system design and development to validation.Guided by the Arcadia methodology,with Capella modeling tool,Simulink simulation tool,and system validation tool,the complete R&D process from design and development to testing and validation was achieved through model construction,code generation,and testing validation.A radio navigation station selection optimization method based on machine learning was proposed,and results had good signal quality and persistence.The verification result of Beijing⁃Shanghai flight route shows MBSE method practiced in this article can ensure the feasibility of the entire process of radio navigation system development,as well as the rationality of tuning and positioning result.By automatically generating code to form a universal functional module,an optimization method that integrates different radio navigation station selection strategies is achieved,providing new ideas for the development and design of radio navigation systems.

Design of rapid tuning system for a ferrite-loaded cavity

Introduction A high power,broadband and rapid frequency sweeping RF system was developed to satisfy the demand of China Spallation Neutron Source(CSNS)/Rapid Cycling Synchrotron(RCS).Material and methods The cavity tuning is the key issue which has a great impact on the performance of the whole RF system.To satisfy the requirements of cavity dynamic tuning caused by the nonlinear characteristics of ferrite,some new technologies were developed and applied.Conclusion In this paper,the overall design of the tuning system is introduced.The ensuing discussion focuses on the com-parison between different types of bias supplies,the control algorithm of low-level RF(LLRF)system.The commissioning results with beam power of 100 kW are also shown and discussed.

A tuning system for BEPC II

The tuning system plays a very important role when a superconducting cavity is in operation. It cooperates with other control loops to adjust the cavity frequency with high precision, reduce the reflection power, guarantee the stability of beam, and ensure the safety of the superconducting cavity. This paper focuses mainly on the tuning system working principle, the working state and problems that Beijing Electron Positron Collider （BEPC ｜I ） has encountered during operation.

Effect of Length Scale Tuning of Background Error in WRF-3DVAR System on Assimilation of High-Resolution Surface Data for Heavy Rainfall Simulation

We investigated the impact of tuning the length scale of the background error covariance in the Weather Research and Forecasting （WRF） three-dimensional variational assimilation （3DVAR） system. In particular, we studied the effect of this parameter on the assimilation of high-resolution surface data for heavy rainfall forecasts associated with mesoscale convective systems over the Korean Peninsula. In the assimilation of high-resolution surface data, the National Meteorological Center method tended to exaggerate the length scale that determined the shape and extent to which observed information spreads out. In this study, we used the difference between observation and background data to tune the length scale in the assimilation of high-resolution surface data. The resulting assimilation clearly showed that the analysis with the tuned length scale was able to reproduce the small-scale features of the ideal field effectively. We also investigated the effect of a double-iteration method with two different length scales, representing large and small-length scales in the WRF-3DVAR. This method reflected the large and small-scale features of observed information in the model fields. The quantitative accuracy of the precipitation forecast using this double iteration with two different length scales for heavy rainfall was high; results were in good agreement with observations in terms of the maximum rainfall amount and equitable threat scores. The improved forecast in the experiment resulted from the development of well-identified mesoscale convective systems by intensified low-level winds and their consequent convergence near the rainfall area.

A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method.In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.

Tuning PID Parameters Based on a Combination of the Expert System and the Improved Genetic Algorithms

a new strategy combining an expert system and improved genetic algorithms is presented for tuning proportional-integral-derivative （PID） parameters for petrochemical processes. This retains the advantages of genetic algorithms, namely rapid convergence and attainment of the global optimum. Utilization of an orthogonal experiment method solves the determination of the genetic factors. Combination with an expert system can make best use of the actual experience of the plant operators. Simulation results of typical process systems examples show a good control performance and robustness.

Development of seam tracking system with ultrasonic sensor using self-tuning fuzzy control

One kind of the SAW seam tracking system with contactless ultrasonic sensor is presented in this paper. The new contactless ultrasonic sensor for seam tracking and the working principle of the seam tracking with the sensor are introduced. Based on the experiments, the optimal values of the fuzzy control parameters α and k 3 are defined by means of the off line adjusting method. Because the self tuning fuzzy control is adopted in the seam tracking system, the overshoot of the system is restrained, the steady state error is reduced, and the system's response speed is improved effectively. The results of the SAW seam tracking experiments show that this system's tracking accuracy is up to ±0.5 mm and the system can satisfy the requirements of the engineering application.

Control parameter optimal tuning method based on annealing-genetic algorithm for complex electromechanical system

A new searching algorithm named the annealing-genetic algorithm(AGA) was proposed by skillfully merging GA with SAA. It draws on merits of both GA and SAA ,and offsets their shortcomings.The difference from GA is that AGA takes objective function as adaptability function directly,so it cuts down some unnecessary time expense because of float-point calculation of function conversion.The difference from SAA is that AGA need not execute a very long Markov chain iteration at each point of temperature, so it speeds up the convergence of solution and makes no assumption on the search space,so it is simple and easy to be implemented.It can be applied to a wide class of problems.The optimizing principle and the implementing steps of AGA were expounded. The example of the parameter optimization of a typical complex electromechanical system named temper mill shows that AGA is effective and superior to the conventional GA and SAA.The control system of temper mill optimized by AGA has the optimal performance in the adjustable ranges of its parameters.

Axonal tuning by GABA_(A) receptor unveils novel tricks from an old dog

In the last years,axonal conductance of action potential trains became a novel subject of study,changing the view of axons,from a static cable-like compartment to a more complex and dynamic system(Debanne et al.,2011).Axonal computation,indeed,is canonically constituted by the action of voltage-gated ion channels,such as the classic Na+and K+channels,but recent studies demonstrated that it can be modulated by the action of other ion channel pumps,and metabolic factors(Byczkowicz et al.,2019;Zang and Marder.

Lorentz detuning and tuning system study of 3+1/2cell DC-SC photo-injector for PKU-FEL

A 3＋1/2cell DC-SC photo-injector for PKU-FEL facility is under development, which is an upgrade design of the successful 1-4-1/2cell DC-SC photo-injector. The Lorentz detuning and tuning structure for the 3＋1/2cell superconducting cavity is presented in this paper. The Lorentz force detuning coefficient is 1.2 Hz/（MV/m）^2 with double stiffening rings for the half cell and single stiffening rings between the adjacent TESLA cells. With the special stiffening structure, the 3＋1/2cell whole cavity needs only one tuner. The influences of the tuning on frequency shift, field flatness and average gradient are discussed in this paper. The simulation results show that the stiffening rings＇ design is successful.

A Novel Tuning Method for Predictive Control of VAV Air Conditioning System Based on Machine Learning and Improved PSO

The variable air volume(VAV)air conditioning system is with strong coupling and large time delay,for which model predictive control(MPC)is normally used to pursue performance improvement.Aiming at the difficulty of the parameter selection of VAV MPC controller which is difficult to make the system have a desired response,a novel tuning method based on machine learning and improved particle swarm optimization(PSO)is proposed.In this method,the relationship between MPC controller parameters and time domain performance indices is established via machine learning.Then the PSO is used to optimize MPC controller parameters to get better performance in terms of time domain indices.In addition,the PSO algorithm is further modified under the principle of population attenuation and event triggering to tune parameters of MPC and reduce the computation time of tuning method.Finally,the effectiveness of the proposed method is validated via a hardware-in-the-loop VAV system.

Automated Performance Tuning of Data Management Systems with Materializations and Indices

Automated performance tuning of data management systems offer various benefits such as improved performance, declined administration costs, and reduced workloads to database administrators (DBAs). Currently, DBAs tune the performance of database systems with a little help from the database servers. In this paper, we propose a new technique for automated performance tuning of data management systems. Firstly, we show how to use the periods of low workload time for performance improvements in the periods of high workload time. We demonstrate that extensions of a database system with materialised views and indices when a workload is low may contribute to better performance for a successive period of high workload. The paper proposes several online algorithms for continuous processing of estimated database workloads and for the discovery of the best plan for materialised view and index database extensions and of elimination of the extensions that are no longer needed. We present the results of experiments that show how the proposed automated performance tuning technique improves the overall performance of a data management system.

Stark Tuning of Telecom Single-Photon Emitters Based on a Single Er^(3+)

The implementation of scalable quantum networks requires photons at the telecom band and long-lived spin coherence.The single Er^(3+) in solid-state hosts is an important candidate that fulfills these critical requirements simultaneously.However,to entangle distant Er^(3+) ions through photonic connections,the emission frequency of individual Er^(3+) in solid-state matrix must be the same,which is challenging because the emission frequency of Er^(3+) depends on its local environment.Herein,we propose and experimentally demonstrate the Stark tuning of the emission frequency of a single Er^(3+) in a Y_(2)SiO_(5) crystal by employing electrodes interfaced with a silicon photonic crystal cavity.We obtain a Stark shift of 182.9±0.8 MHz,which is approximately 27 times of the optical emission linewidth,demonstrating promising applications in tuning the emission frequency of independent Er^(3+) into the same spectral channels.Our results provide a useful solution for construction of scalable quantum networks based on single Er^(3+) and a universal tool for tuning emission of individual rare-earth ions.

Electrode design for multimode suppression of aluminum nitride tuning fork resonators

This paper is focused on electrode design for piezoelectric tuning fork resonators.The relationship between the performance and electrode pattern of aluminum nitride piezoelectric tuning fork resonators vibrating in the in-plane flexural mode is investigated based on a set of resonators with different electrode lengths,widths,and ratios.Experimental and simulation results show that the electrode design impacts greatly the multimode effect induced from torsional modes but has little influence on other loss mechanisms.Optimizing the electrode design suppresses the torsional mode successfully,thereby increasing the ratio of impedance at parallel and series resonant frequencies(R_(p)/R_(s))by more than 80%and achieving a quality factor(Q)of 7753,an effective electromechanical coupling coefficient(kt_(eff)^(2))of 0.066%,and an impedance at series resonant frequency(R_(m))of 23.6 kΩ.The proposed approach shows great potential for high-performance piezoelectric resonators,which are likely to be fundamental building blocks for sensors with high sensitivity and low noise and power consumption.

An 80-GHz DCO utilizing improved SC ladder and promoted DCTL-based hybrid tuning banks

An 80-GHz DCO based on modified hybrid tuning banks is introduced in this paper.To achieve sub-MHz frequency res-olution with reduced circuit complexity,the improved circuit topology replaces the conventional circuit topology with two binary-weighted SC cells,enabling eight SC-cell-based improved SC ladders to achieve the same fine-tuning steps as twelve SC-cell-based conventional SC ladders.To achieve lower phase noise and smaller chip size,the promoted binary-weighted digi-tally controlled transmission lines(DCTLs)are used to implement the coarse and medium tuning banks of the DCO.Compared to the conventional thermometer-coded DCTLs,control bits of the proposed DCTLs are reduced from 30 to 8,and the total length is reduced by 34.3%(from 122.76 to 80.66μm).Fabricated in 40-nm CMOS,the DCO demonstrated in this work fea-tures a small fine-tuning step(483 kHz),a high oscillation frequency(79-85 GHz),and a smaller chip size(0.017 mm^(2)).Com-pared to previous work,the modified DCO exhibits an excellent figure of merit with an area(FoMA)of-198 dBc/Hz.

A spin-based magnetic scanning microscope for in-situ strain tuning of soft matter

We present a magnetic scanning microscope equipped with a nitrogen-vacancy(NV) center scanning probe that has the ability to mechanically tune the strain of soft matter in-situ. The construction of the microscope and a continuous straintuning sample holder are discussed. An optically detected magnetic resonance protocol utilized in the imaging is described.In order to show the reliability of this microscope, the strain conduction is estimated with finite element simulation, and xray diffraction is required for calibration when freestanding crystal films are under consideration. A magnetic imaging result is displayed to demonstrate the nano-scale imaging capability. The microscope presented in this work is helpful in studying strain-coupled magnetic physics such as magnetic phase transition under strain and strain-tuned cycloidal orientation tilting.

PSTCNN: Explainable COVID-19 diagnosis using PSO-guided self-tuning CNN

Since 2019,the coronavirus disease-19(COVID-19)has been spreading rapidly worldwide,posing an unignorable threat to the global economy and human health.It is a disease caused by severe acute respiratory syndrome coronavirus 2,a single-stranded RNA virus of the genus Betacoronavirus.This virus is highly infectious and relies on its angiotensin-converting enzyme 2-receptor to enter cells.With the increase in the number of confirmed COVID-19 diagnoses,the difficulty of diagnosis due to the lack of global healthcare resources becomes increasingly apparent.Deep learning-based computer-aided diagnosis models with high generalisability can effectively alleviate this pressure.Hyperparameter tuning is essential in training such models and significantly impacts their final performance and training speed.However,traditional hyperparameter tuning methods are usually time-consuming and unstable.To solve this issue,we introduce Particle Swarm Optimisation to build a PSO-guided Self-Tuning Convolution Neural Network(PSTCNN),allowing the model to tune hyperparameters automatically.Therefore,the proposed approach can reduce human involvement.Also,the optimisation algorithm can select the combination of hyperparameters in a targeted manner,thus stably achieving a solution closer to the global optimum.Experimentally,the PSTCNN can obtain quite excellent results,with a sensitivity of 93.65%±1.86%,a specificity of 94.32%±2.07%,a precision of 94.30%±2.04%,an accuracy of 93.99%±1.78%,an F1-score of 93.97%±1.78%,Matthews Correlation Coefficient of 87.99%±3.56%,and Fowlkes-Mallows Index of 93.97%±1.78%.Our experiments demonstrate that compared to traditional methods,hyperparameter tuning of the model using an optimisation algorithm is faster and more effective.