Adapter Based on Pre-Trained Language Models for Classification of Medical Text

We present an approach to classify medical text at a sentence level automatically.Given the inherent complexity of medical text classification,we employ adapters based on pre-trained language models to extract information from medical text,facilitating more accurate classification while minimizing the number of trainable parameters.Extensive experiments conducted on various datasets demonstrate the effectiveness of our approach.

Neurogenesis dynamics in the olfactory bulb:deciphering circuitry organization, function, and adaptive plasticity

Adult neurogenesis persists after birth in the subventricular zone, with new neurons migrating to the granule cell layer and glomerular layers of the olfactory bulb, where they integrate into existing circuitry as inhibitory interneurons. The generation of these new neurons in the olfactory bulb supports both structural and functional plasticity, aiding in circuit remodeling triggered by memory and learning processes. However, the presence of these neurons, coupled with the cellular diversity within the olfactory bulb, presents an ongoing challenge in understanding its network organization and function. Moreover,the continuous integration of new neurons in the olfactory bulb plays a pivotal role in regulating olfactory information processing. This adaptive process responds to changes in epithelial composition and contributes to the formation of olfactory memories by modulating cellular connectivity within the olfactory bulb and interacting intricately with higher-order brain regions. The role of adult neurogenesis in olfactory bulb functions remains a topic of debate. Nevertheless, the functionality of the olfactory bulb is intricately linked to the organization of granule cells around mitral and tufted cells. This organizational pattern significantly impacts output, network behavior, and synaptic plasticity, which are crucial for olfactory perception and memory. Additionally, this organization is further shaped by axon terminals originating from cortical and subcortical regions. Despite the crucial role of olfactory bulb in brain functions and behaviors related to olfaction, these complex and highly interconnected processes have not been comprehensively studied as a whole. Therefore, this manuscript aims to discuss our current understanding and explore how neural plasticity and olfactory neurogenesis contribute to enhancing the adaptability of the olfactory system. These mechanisms are thought to support olfactory learning and memory, potentially through increased complexity and restructuring of neural network structures, as well as the addition of new granule granule cells that aid in olfactory adaptation. Additionally, the manuscript underscores the importance of employing precise methodologies to elucidate the specific roles of adult neurogenesis amidst conflicting data and varying experimental paradigms. Understanding these processes is essential for gaining insights into the complexities of olfactory function and behavior.

基于Adapter的软件总线体系结构

提出基于适配器Adapter的软件总线体系结构,引进适配器作为可复用构件和软件总线的中介,负责管理和存储与系统相关的构件的组装信息,在消息交换和数据共享中负责消息派送和数据格式转换的工作.适配器还参与可复用构件的组合,扩充和屏蔽可复用构件的现有功能.

基于Adapter模式的远程教育资源整合

首先分析各高校远程教育资源信息多平台问题,然后研究了现有系统整合的重要技术难点,在保证整体功能和原有框架的基础上,基于Adapter模式进行了资源系统整合的构建和实现,从而减少多系统带来的共享、安全等问题,是各种资源有效整合共享的探索和尝试。

使用Adapter模式在组态软件中实现串口通讯协议复用

本文使用Adapter模式对组态软件中串口通讯协议部分实现复用.应用该方法可以大大减少使用组态软件与第三方设备进行串口通讯的工作量。

基于TTCN-3的移动IPv6协议一致性测试中适配器Adapter的设计与实现

文章介绍了移动IPv6协议的TTCN-3测试系统适配器Adapter的设计与实现;首先根据TTCN-3 Adapter的功能划分,提出了移动IPv6协议一致性测试下Adapter三大模块(即测试系统适配器SA、平台适配器PA和编解码器CD)的测试要求;其次以Tau(测试工具)中已提供的Adapter接口函数为基础,设计并实现了针对移动IPv6协议一致性的某些函数的扩展功能;指出了这些函数中的难点所在。

基于Adapter模式的协同办公系统应用整合方案

企业应用集成是目前企业信息化建设的核心问题,企业业务整合和系统集成时数据共享是企业应用集成需要解决的最重要的问题之一。根据Adapter模式技术的特点,分析了协同办公环境下基于消息传输组件的特点,从数据集成的角度,提出了在该环境下实现信息资源共享的ABI模式的体系框架,并对集成方案的模型、消息传输组件及框架进行了详细论述。

3D heterogeneous integration of wideband RF chips using silicon-based adapter board technology

An ultra-wideband mixing component cascaded by a mixing multi-function chip and a frequency multiplier multi-function chip was demonstrated and implemented using 3D heterogeneous integration based on the silicon adapter board technology.Four layers of high-resistance silicon substrate stack packaging are implemented based on the wafer-level gold-gold bonding process.Each layer adopts though silicon via(TSV)technology to realize signal interconnection.A core monolithic integrated microwave chip(MMIC)is embedded in the silicon cavity,and the silicon-based filter is integrated with the high-resistance silicon substrate.The interconnect line,cavity and filter of the silicon-based adapter board are designed with AutoCAD,and HFSS is adopted for 3D electromagnetic field simulation.According to the measured results,the radio frequency(RF)of the mixing multi-function chip is 40-44 GHz and its intermediate frequency(IF)can cover the Ku band with a chip size of 10 mm×11 mm×1 mm.The multiplier multi-function chip operates at 16-20 GHz.The fundamental suppression is greater than 50 dB and the second harmonic suppression is better than 40 dB with a chip size of 8 mm×8 mm×1 mm.The cascaded fully assembled mixing component achieves a spur of better than-50 dBc and a gain of better than 15 dB.

Study on influencing factors of adapters separating with the underwater missile

To analyze main factors affecting the separation reliability between a missile and adapters for the launching process, a six DOF underwater dynamic model for the missile and adapters is utilized to simulate the separation process, considering elastic forces of separating springs, hydrodynamic forces, gravity and buoyancy. Moreover, a criterion based on the maximum separating distance is put forward to determine whether adapters separate with the missile reliably. The results show that the magnitude and position of elastic force, the wedge angle and mass of the adapter significantly affect the separating process. The local sensitivity analysis for the reference status of design parameters demonstrates that the wedge angle of adapters has the maximum influence about 70. 4% on the separating distance.

基于Android平台的通用Adapter适配器的设计与实现

Android开发中,ListView列表是使用率最高的UI组件,传统开发模式中,ListView的代码编写比较繁琐,项目中充斥着大量的Adapter适配器,该文在分析ListView开发原理的基础上,设计并实现一个可以通用于各种ListView场景开发的Adapter适配器,使得无论多少ListView,只需一个Adapter适配器,从而解决项目开发中代码高冗余、高复杂、管理麻烦等实际问题。

Structural Finite Element Software Coupling Using Adapter Elements

This paper describes a versatile and computationally efficient method for coupling several finite element analysis(FEA)programs together so that the unique modeling and analysis capabilities of each code can be utilized simultaneously to simulate the static or dynamic response of a complete numerical system.An arbitrary number of finite element analysis software packages can be coupled by adding two special types of elements,namely generic and adapter elements,to each of the finite element applications using their programming interface.These elements are inserted at the interfaces between the different sub-domains of the complete system modeled by each finite element analysis software package.Exchange of data between the coupled FEA codes is accomplished in a modular and synchronized manner using OpenFresco(Opensource Framework for Experimental Setup and Control).OpenFresco is an objectoriented,environment independent software framework initially developed for hybrid simulation in which certain aspects of a complete structure are simulated numerically and other aspects are simultaneously tested physically.An important practical advantage of this coupled analysis approach is that all of the connected FEA codes run concurrently and continuously,decreasing analysis time consumption by an order of magnitude or more compared to more traditional approaches that shut down and restart the coupled analysis codes at each integration time step.The implementation and accuracy of this approach to FE software coupling are demonstrated using dynamic analyses of three simple structural models from the field of earthquake engineering.

Underwater four-quadrant dual-beam circumferential scanning laser fuze using nonlinear adaptive backscatter filter based on pauseable SAF-LMS algorithm

The phenomenon of a target echo peak overlapping with the backscattered echo peak significantly undermines the detection range and precision of underwater laser fuzes.To overcome this issue,we propose a four-quadrant dual-beam circumferential scanning laser fuze to distinguish various interference signals and provide more real-time data for the backscatter filtering algorithm.This enhances the algorithm loading capability of the fuze.In order to address the problem of insufficient filtering capacity in existing linear backscatter filtering algorithms,we develop a nonlinear backscattering adaptive filter based on the spline adaptive filter least mean square(SAF-LMS)algorithm.We also designed an algorithm pause module to retain the original trend of the target echo peak,improving the time discrimination accuracy and anti-interference capability of the fuze.Finally,experiments are conducted with varying signal-to-noise ratios of the original underwater target echo signals.The experimental results show that the average signal-to-noise ratio before and after filtering can be improved by more than31 d B,with an increase of up to 76%in extreme detection distance.

The Design and Experiment Studies of Optical Adapter with Integrated Dust Protection and Shutter Design

High power lasers (> +21dBm) have gradually become the common solution for signal transmitting systems including regional cable television, Fiber To The Home (FTTH), and gigabit passive optical networks (G- PONs) due to their ability to generate signals that can be transmitted over long distances. However, if protective design is not implemented in the facility at the client side, users may be exposed to health hazards such as eye damage from these high-power lasers. High-power optical adapters with laser shutter use metal masks to prevent eye exposure to direct laser beams. They have progressively replaced conventional optical adapters and entered the market mainstream. Our study uses the Elastic-Plastic theory together with parametric design to investigate the effect of geometry on the initial spring-back angle of a laser shutter. Once the force stabilizes, the angles of the initial spring back are found to be the same as the simulated results for several attempts. In our study, it is observed that factors including the thickness of the metal masking plate, the initial design angle, the stiffness of the material and the boundary conditions have significant influence on the spring back angle. These can be used as references in design control.

An adaptive physics-informed deep learning method for pore pressure prediction using seismic data

Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum engineering.Recent deep learning technique has been receiving more interest due to the great potential to deal with pore pressure prediction.However,most of the traditional deep learning models are less efficient to address generalization problems.To fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic data.Specifically,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss function.Through machine training,the developed model can automatically select the optimal physical model to constrain the results for each pore pressure prediction.The CGP-NN model has the best generalization when the physicsrelated metricλ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few labels.To validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization ability.The adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.

Adaptive Robust Servo Control for Vertical Electric Stabilization System of Tank and Experimental Validation

A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.

Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach

The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

Automatic modulation recognition of radio fuzes using a DR2D-based adaptive denoising method and textural feature extraction

The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.

Standard for Universal Power Adapter for Mobile Terminals

This paper introduces the choices of the technology solutions pertinent to the industrial standard of Chinese communications industry, YD/T 1591 Technical Requirements and Test Method of Charger and lnterface for Mobile Telecommunication Terminal Equipment, as well as its development and revision process. It also elaborates the technology contents for Recommendation of Improving the Standard ITU-TL.1000.

Adaptive Optimal Discrete-Time Output-Feedback Using an Internal Model Principle and Adaptive Dynamic Programming

In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization problem. We then design an observer to reproduce the full state of the system by measuring the inputs and outputs. Moreover, this technique includes both a policy iteration algorithm and a value iteration algorithm to determine the optimal feedback gain without using a dynamic system model. It is important that with this concept one does not need to solve the regulator equation. Finally, this control method was tested on an inverter system of grid-connected LCLs to demonstrate that the proposed method provides the desired performance in terms of both tracking and disturbance rejection.