Theory of isomeric excitation of 229Th via electronic processes

A unified theoretical framework is presented for the isomeric excitation of the 229Th nucleus via electronic processes. These processes include nuclear excitation by electron transition (NEET), nuclear excitation by electron capture (NEEC), and nuclear excitation by inelastic electron scattering (NEIES). Detailed calculation results on the excitation rate and the excitation cross section are presented

Three-dimensional resolution-enhancement divided aperture correlation-differential confocal microscopy with nanometer axial focusing capability

Divided aperture confocal microscopy (DACM) provides an improved imaging depth, imaging contrast, and working distance at the expense of spatial resolution. Here, we present a new method-divided aperture correlation-differential confocal microscopy (DACDCM) to improve the DACM resolution and the focusing capability, without changing the DACM configuration. DACDCM divides the DACM image spot into two round regions symmetrical about the optical axis. Then the light intensity signals received simultaneously from two round regions by a charge-coupled device (CCD) are processed by correlation manipulation and differential subtraction to improve the DACM spatial resolution and axial focusing capability, respectively. Theoretical analysis and preliminary experiments indicate that, for the excitation wavelength of λ = 632.8 nm, numerical aperture NA = 0.8, and normalized offset vM = 3.2 of the two regions, the DACDCM resolution is improved by 32.5% and 43.1% in the x and z directions, simultaneously, compared with that of the DACM. The axial focusing resolution used for the sample surface profile imaging was also significantly improved to 2 nm

Hierarchical Task Planning for Multiarm Robot with Multiconstraint

Multiarm systems become the trends of space robots, for the on-orbit servicing missions are becoming more complex and various. A hierarchical task planning method with multiconstraint for multiarm space robot is presented in this paper. The process of task planning is separated into two hierarchies: mission profile analysis and task node planning. In mission profile analysis, several kinds of primitive tasks and operators are defined. Then, a complex task can be decomposed into a sequence of primitive tasks by using hierarchical task network (HTN) with those primitive tasks and operators. In task node planning, A⁎ algorithm is improved to adapt the continuous motion of manipulator. Then, some of the primitive tasks which cannot be executed directly because of constraints are further decomposed into several task nodes by using improved A⁎ algorithm. Finally, manipulators execute the task by moving from one node to another with a simple path plan algorithm. The feasibility and effectiveness of the proposed task planning method are verified by simulation

CLEAN-EVAL: Clean Evaluation on Contaminated Large Language Models

We are currently in an era of fierce competition among various large language models (LLMs) continuously pushing the boundaries of benchmark performance. However, genuinely assessing the capabilities of these LLMs has become a challenging and critical issue due to potential data contamination, and it wastes dozens of time and effort for researchers and engineers to download and try those contaminated models. To save our precious time, we propose a novel and useful method, Clean-Eval, which mitigates the issue of data contamination and evaluates the LLMs in a cleaner manner. Clean-Eval employs an LLM to paraphrase and back-translate the contaminated data into a candidate set, generating expressions with the same meaning but in different surface forms. A semantic detector is then used to filter the generated low-quality samples to narrow down this candidate set. The best candidate is finally selected from this set based on the BLEURT score. According to human assessment, this best candidate is semantically similar to the original contamination data but expressed differently. All candidates can form a new benchmark to evaluate the model. Our experiments illustrate that Clean-Eval substantially restores the actual evaluation results on contaminated LLMs under both few-shot learning and fine-tuning scenarios

Research on Construction Method of Operational Reliability Control Model for Space Manipulator Based on Particle Filter

The operational reliability of the space manipulator is closely related to the control method. However the existing control methods seldom consider the operational reliability from the system level. A method to construct the operational reliability system control model based on particle filter for the space manipulator is presented in this paper. Firstly, the definition of operational reliability and the degree of operational reliability are given and the state space equations of the control system are established as well. Secondly, based on the particle filter algorithm, a method to estimate the distribution of the end position error and calculate the degree of operational reliability with any form of noise distribution in real time is established. Furthermore, a performance model based on quality loss theory is built and a performance function is obtained to evaluate the quality of the control process. The adjustment value of the end position of the space manipulator can be calculated by using the performance function. Finally, a large number of simulation results show that the control method proposed in this paper can improve the task success rate effectively compared to the simulation results using traditional control methods and control methods based on Bayesian estimation

Developing a class of dual atom materials for multifunctional catalytic reactions

Dual atom catalysts, bridging single atom and metal/alloy nanoparticle catalysts, offer more opportunities to enhance the kinetics and multifunctional performance of oxygen reduction/evolution and hydrogen evolution reactions. However, the rational design of efficient multifunctional dual atom catalysts remains a blind area and is challenging. In this study, we achieved controllable regulation from Co nanoparticles to CoN4 single atoms to Co2N5 dual atoms using an atomization and sintering strategy via an N-stripping and thermal-migrating process. More importantly, this strategy could be extended to the fabrication of 22 distinct dual atom catalysts. In particular, the Co2N5 dual atom with tailored spin states could achieve ideally balanced adsorption/desorption of intermediates, thus realizing superior multifunctional activity. In addition, it endows Zn-air batteries with long-term stability for 800 h, allows water splitting to continuously operate for 1000 h, and can enable solar-powered water splitting systems with uninterrupted large-scale hydrogen production throughout day and night. This universal and scalable strategy provides opportunities for the controlled design of efficient multifunctional dual atom catalysts in energy conversion technologies

A Hierarchical Reliability Control Method for a Space Manipulator Based on the Strategy of Autonomous Decision-Making

In order to maintain and enhance the operational reliability of a robotic manipulator deployed in space, an operational reliability system control method is presented in this paper. First, a method to divide factors affecting the operational reliability is proposed, which divides the operational reliability factors into task-related factors and cost-related factors. Then the models describing the relationships between the two kinds of factors and control variables are established. Based on this, a multivariable and multiconstraint optimization model is constructed. Second, a hierarchical system control model which incorporates the operational reliability factors is constructed. The control process of the space manipulator is divided into three layers: task planning, path planning, and motion control. Operational reliability related performance parameters are measured and used as the system’s feedback. Taking the factors affecting the operational reliability into consideration, the system can autonomously decide which control layer of the system should be optimized and how to optimize it using a control level adjustment decision module. The operational reliability factors affect these three control levels in the form of control variable constraints. Simulation results demonstrate that the proposed method can achieve a greater probability of meeting the task accuracy requirements, while extending the expected lifetime of the space manipulator

Efficient three-dimensional high-resolution simulations of flow fields around cylinders

Few works use the fully three-dimensional computational fluid dynamic method to simulate the flow fields around the marine pipes with large aspect ratios due to the huge computation cost. In the present work, an operator-splitting method is used to efficiently solve the three-dimensional Reynolds Average Navier–Stokes governing equations of the fluid flow around pipes by separating the problem as a combination of a two-dimensional problem in the horizontal plane and an one-dimensional problem in the vertical direction. A second order total variation diminishing finite volume method is used to solve the model. The precision of the present model is validated by comparing the present numerical results of two typical three-dimensional cases with the available experimental and numerical results. The simulation results with a commercial software are also included in the comparison and the present model shows a higher performance in terms of computational time. Keywords: CFD, Cylinder, Cube, Operator-splitting, TVD, Three-dimensiona

A Novel Optimal Design of Measurement Configurations in Robot Calibration

Robot calibration highly depends on redundant measurement configurations to collect enough sample data for higher accuracy, but excessive measurements seem to be uneconomical and time-consuming. Thus lots of observability indexes to evaluate the goodness of the measurement configurations have been proposed. However, in some circumstances, it is of critical importance to obtain accurate kinematic parameters and estimate the end-effector pose precisely at the same time. Obviously one single observability index can hardly meet this need yet. Accordingly, after analyzing the essential constrains of robot calibration and the influence of measurement configurations on the observability indexes, an optimization model with two observability indexes to be taken into consideration is proposed in this paper, and then the existing DETMAX algorithm is modified to seek optimal design of measurement configurations, by adopting a set-constructing method and a set-shrinking method. Much better results have been obtained by simulation study, which implies that the proposed model and the modified DETMAX algorithm perform well in both kinematic parameter identification and pose estimation of the end-effector of the robot