Research on the Internal Talent Training Path and Performance Evaluation Mechanism of New R&D Institutions in Zhejiang Province

New research and development(R&D)institutions are an important part of the national innovation system,playing an important role in promoting the transformation of scientific and technological achievements.In recent years,new R&D institutions have gradually become the driving force of innovation-driven development in China.Taking new R&D institutions in Zhejiang Province as the research object,this paper studies the internal talent training path and performance evaluation mechanism of new R&D institutions in Zhejiang Province by using the literature research method,comparison method,case verification method,and other methods.The investigation results show that there are problems such as lack of material and spiritual support and neglect of the absorption of local talents in the internal talent training,and there are problems such as unclear standards,insufficient data,and opaque processes in the performance evaluation mechanism,which greatly affect the establishment and improvement of the performance evaluation mechanism.Given the above problems,this paper puts forward a forward-looking,oriented,flexible,and compatible talent training path and performance evaluation mechanism,hoping to optimize the effective internal talent training path of new R&D institutions,improve the evaluation performance,and promote healthy development of new R&D institutions in Zhejiang Province.

Evaluation and prediction of earth pressure balance shield performance in complex rock strata:A case study in Dalian,China

This research explores the potential for the evaluation and prediction of earth pressure balance shield performance based on a gray system model.The research focuses on a shield tunnel excavated for Metro Line 2 in Dalian,China.Due to the large error between the initial geological exploration data and real strata,the project construction is extremely difficult.In view of the current situation regarding the project,a quantitative method for evaluating the tunneling efficiency was proposed using cutterhead rotation(R),advance speed(S),total thrust(F)and torque(T).A total of 80 datasets with three input parameters and one output variable(F or T)were collected from this project,and a prediction framework based gray system model was established.Based on the prediction model,five prediction schemes were set up.Through error analysis,the optimal prediction scheme was obtained from the five schemes.The parametric investigation performed indicates that the relationships between F and the three input variables in the gray system model harmonize with the theoretical explanation.The case shows that the shield tunneling performance and efficiency are improved by the tunneling parameter prediction model based on the gray system model.

A robust method for performance evaluation of the vapor cell for magnetometry

A robust performance evaluation method for vapor cells used in magnetometers is proposed in this work.The performance of the vapor cell determines the sensitivity of the magnetic measurement,which is the core parameter of a magnetometer.After establishing the relationship between intrinsic sensitivity and the total relaxation rate,the total relaxation rate of the vapor cell can be obtained to represent the intrinsic sensitivity of the magnetometer by fitting the parameters of the magnetic resonance experiments.The method for measurement of the total relaxation rate based on the magnetic resonance experiment proposed in this work is robust and insensitive to ambient noise.Experiments show that,compared with conventional sensitivity measurement,the total relaxation rate affected by magnetic noise below 0.9 n T,pump light frequency noise below 1.5 GHz,pump light power noise below 9%,probe light power noise below 3%and temperature fluctuation of 150±3℃deviates by less than 2%from the noise-free situation.This robust performance evaluation method for vapor cells is conducive to the construction of a multi-channel high-spatial-resolution cardio-encephalography system.

Recent Advances in the Rapid Detection and Performance Evaluation Methods of Detergent Additives for Gasoline

Although detergent additives for gasoline have been widely commercialized,their formulas are often kept confidential and there is still no standardized method for quickly detecting the main active ingredients and evaluating their effectiveness,which makes their regulation difficult.An overview of the current state of the development and application of detergent additives for gasoline in China and other regions,as well as a review of the rapid detection and performance evaluation methods available for analyzing detergent additives are given herein.The review focuses on the convenience,cost,efficiency,and feasibility of on-site detection and the evaluation of various methods,and also looks into future research directions,such as detecting and evaluating detergent additives in ethanol gasoline and with advanced engine technologies.

A general evaluation system for optimal selection performance of radar clutter model

The optimal selection of radar clutter model is the premise of target detection,tracking,recognition,and cognitive waveform design in clutter background.Clutter characterization models are usually derived by mathematical simplification or empirical data fitting.However,the lack of standard model labels is a challenge in the optimal selection process.To solve this problem,a general three-level evaluation system for the model selection performance is proposed,including model selection accuracy index based on simulation data,fit goodness indexs based on the optimally selected model,and evaluation index based on the supporting performance to its third-party.The three-level evaluation system can more comprehensively and accurately describe the selection performance of the radar clutter model in different ways,and can be popularized and applied to the evaluation of other similar characterization model selection.

Performance evaluation of CLM5.0 in simulating liquid soil water in high mountainous area,Northwest China

The model performance in simulating soil water content(SWC) is crucial for successfully modeling earth’s system,especially in high mountainous areas.In this study,the performance of Community Land Model 5.0(CLM5.0) in simulating liquid SWC was evaluated against observations from nine in-situ sites in the upper reach of the Heihe River Watershed(HRW),Northwest China.The CLM5.0 shows reliable performance in the study area with correlation coefficients(R) ranging between 0.79–0.93,root mean standard errors(RMSE)ranging between 0.044–0.097 m^(3)/m^(3),and the mean bias(BIAS) ranging between-0.084–0.061 m^(3)/m^(3).The slightly worse performance of CLM5.0 than CLM4.5 on alpine meadow and grassland is mainly caused by the revised canopy interception parameterization.The CLM5.0 overestimates interception and underestimates evapotranspiration(ET) on both alpine meadow and grassland during the growth period.The systematical overestimations at all the grassland sites indicate that the underestimation of ET is much larger than the overestimation of interception on grassland during growth period,while the errors of simulated interception and ET are partially canceled out on alpine meadow.Moreover,the underestimation of ET is more responsible for the overestimation of SWC than the overestimation of interception in the high mountainous area.It is necessary to estimate reasonable empirical parameter α(proportion of leaf water collection area) in interception parameterization scheme and further improve the dry surface layerbased soil evaporation resistance parameterization introduced in CLM5.0 in future researches.The performance of CLM5.0 is better under completely frozen stage than thawing stage and freezing stage,because of low variations of liquid SWC caused by extremely low hydraulic conductivity of soils.The underestimation of liquid SWC under frozen state is caused by underestimation of soil temperature,which leads to more ice mass and less liquid water in total water content.

A Performance Evaluation Platform for Mega Satellite Constellation Network

With the rapid development of satellite technology, mega satellite constellations have become a research hotspot. A large number of related techniques have been developed on orbit topology, network routing, energy balance and resource control. However, it is difficult to accurately compare the performance of similar studies due to differences in the means of validation. Especially for invulnerability studies in many military applications, a unified evaluation system is essential. This paper proposes a network evaluation system for mega satellite constellations. Evaluation parameters include orbit topology, communication network, energy balance and invulnerability. Different application algorithms and traffic models were used to validate the specific system. .

Carbon materials toward efficient potassium storage:Rational design,performance evaluation and potassium storage mechanism

Potassium-ion batteries(PIBs)are potential“Beyond Li-ion Batteries”candidates for their resource advantage and low standard electrode potential.To date,the research on PIBs is in its early stages,the most urgent task is to develop high-performance electrode materials and reveal their potassium storage mechanism.For PIBs anode materials,carbon with tunable microstructure,excellent electrochemical activity,nontoxicity and low price is considered as one of the most promising anode materials for commercialization.Although some breakthrough works have emerged,the overall electrochemical performance of the reported carbon anode is still far away from practical application.Herein,we carry out a comprehensive overview of PIBs carbon anode in terms of three aspects of rational design of structure,performance evaluation criteria and characterization of potassium storage mechanism.First,the regulation mechanism of key structural features of carbon anode on its potassium storage performance and the representative structural regulation strategies are introduced.Then,in view of the undefined performance evaluation criteria of PIBs carbon anode,a reference principle for evaluating the potassium storage performance of carbon anode is proposed.Finally,the advanced characterization techniques for the potassium storage mechanism of carbon anode are summarize.This review aims to provide guidance for the development of practical PIBs anode.

ROS2 Real-time Performance Optimization and Evaluation

Real-time interaction with uncertain and dynamic environments is essential for robotic systems to achieve functions such as visual perception,force interaction,spatial obstacle avoidance,and motion planning.To ensure the reliability and determinism of system execution,a flexible real-time control system architecture and interaction algorithm are required.The ROS framework was designed to improve the reusability of robotic software development by providing a distributed structure,hardware abstraction,message-passing mechanism,and application prototypes.Rich ecosystems for robotic development have been built around ROS1 and ROS2 architectures based on the Linux system.However,because of the fairness scheduling principle of the default Linux system design and the complexity of the kernel,the system does not have real-time computing.To achieve a balance between real-time and non-real-time computing,this paper uses the transmission mechanism of ROS2,combines it with the scheduling mechanism of the Linux operating system,and uses Preempt_RT to enhance the real-time computing of ROS1 and ROS2.The real-time performance evaluation of ROS1 and ROS2 is conducted from multiple perspectives,including throughput,transmission mode,QoS service quality,frequency,number of subscription nodes and EtherCAT master.This paper makes two significant contributions:firstly,it employs Preempt_RT to optimize the native ROS2 system,effectively enhancing the real-time performance of native ROS2 message transmission;secondly,it conducts a comprehensive evaluation of the real-time performance of both native and optimized ROS2 systems.This comparison elucidates the benefits of the optimized ROS2 architecture regarding real-time performance,with results vividly demonstrated through illustrative figures.

A Nationwide Evaluation of the State of Practice of Performance Measurements for Intelligent Transportation Systems

State departments of transportation’s (DOTs) decisions to invest resources to expand or implement intelligent transportation systems (ITS) programs or even retire existing infrastructure need to be based on performance evaluations. Nonetheless, an apparent gap exists between the need for ITS performance measurements and the actual implementation. The evidence available points to challenges in the ITS performance measurement processes. This paper evaluated the state of practice of performance measurement for ITS across the US and provided insights. A comprehensive literature review assessed the use of performance measures by DOTs for monitoring implemented ITS programs. Based on the gaps identified through the literature review, a nationwide qualitative survey was used to gather insights from key stakeholders on the subject matter and presented in this paper. From the data gathered, performance measurement of ITS is fairly integrated into ITS programs by DOTs, with most agencies considering the process beneficial. There, however, exist reasons that prevent agencies from measuring ITS performance to greater detail and quality. These include lack of data, fragmented or incomparable data formats, the complexity of the endeavor, lack of data scientists, and difficulty assigning responsibilities when inter-agency collaboration is required. Additionally, DOTs do not benchmark or compare their ITS performance with others for reasons that include lack of data, lack of guidance or best practices, and incomparable data formats. This paper is relevant as it provides insights expected to guide DOTs and other agencies in developing or reevaluating their ITS performance measurement processes.

Flow control performance evaluation of a tri-electrode sliding discharge plasma actuator

Tri-electrode sliding discharge(TED)plasma actuators are formed by adding a direct current(DC)exposed electrode to conventional dielectric barrier discharge(DBD)plasma actuators.There are three TED modes depending on the polarity and amplitude of the DC supply:DBD discharge,extended discharge and sliding discharge.This paper evaluates the electrical,aerodynamic and mechanical characteristics of a TED plasma actuator based on energy analysis,particle image velocimetry experiments and calculations using the Navier-Stokes equation.The flow control performances of different discharge modes are quantitatively analyzed based on characteristic parameters.The results show that flow control performance in both extended discharge and sliding discharge is more significant than that of DBD,mainly because of the significantly higher(up to 141%)body force of TED compared with DBD.However,conductivity loss is the primary power loss caused by the DC polarity for TED discharge.Therefore,power consumption can be reduced by optimizing the dielectric material and thickness,thus improving the flow control performance of plasma actuators.

Performance evaluation of high/ultra-high-degree global geopotential models over Vietnam using GNSS/leveling data

The availability of many high-degree Global Geopotential Models(GGMs), namely EGM2008, EIGEN-6C4,GECO, SGG-UGM-1, SGG-UGM-2, XGM2019e_2159, and GGMPlus, challenges users regarding which model is best for Vietnam. This study, therefore, evaluates their performance by comparing them with GNSS/leveling data over Vietnam. Results show that their absolute and relative performances are largely independent of topographic conditions and geographical location and can be ranked into three classes:(1)XGM2019e_2159 has the highest accuracy,(2) the models EIGEN-6C4, GECO, SGG-UGM-1, SGG-UGM-2, and GGMPlus, have a very similar level of medium accuracy, while(3) EGM2008 is found to be the least accurate. In an absolute sense, the differences between GNSS/leveling and EGM2008-based height anomalies have a standard deviation(STD) of 0.290 ± 0.010 m, whereas, for XGM2019e_2159, this is 0.156 ± 0.006 m.All other models have STDs of(0.18-0.19) ± 0.007 m. Regarding relative performance without fitting, all GGMs have comparable accuracies for baseline length of 5-20 km, while for baselines longer than 20 km,the STD of XGM2019e_2159 is 1.5 ppm-0.5 ppm(approximately 19%-40%) lower compared with EGM2008, and 0.5 ppm-0.25 ppm(approximately 7%-36%) lower compared with EIGEN6C4, GECO,SGG-UGM-1, SGG-UGM-2, and GGMPlus. In addition, the STDs decrease significantly from 20 to 12 ppm in the range of 5-10 km, slightly from 12 to 6 ppm for 10-35 km, very slightly from 6 to 2.5 ppm for35-200 km, and then remain almost unchanged for longer baselines. After fitting, the relative accuracies of all GGMs are at the same level with negligible STD/RMSE values. Furthermore, only EGM2008 experiences significant regional differences, while other GGMs show more homogeneous spatial variation of absolute accuracy over Vietnam. These findings can contribute to the development of local quasigeoid models in Vietnam and may be helpful with the improvement of GGMs in the future.

Performance evaluation of ecological compensation policy for cultivated land in China

The paper evaluates the changes in the ecological environment of cultivated land in the major crop-producing areas major crop-producing areas in the past 20 years by constructing an ecological pollution index;and quantitatively analyzes the effects of the existing policies and their main influencing factors by applying the PSM-DID method based on the frequency of policy enactment.The results are as follows:first,the existing ecological compensation policies for cultivated land are effective but not significant in improving the ecological environment in the major crop-producing areas.The economic development level and grain cultivation area of the major crop-producing areas are significantly and positively correlated with the improvement of the arable land ecological environment,while the level of agricultural infrastructure construction is significantly and negatively correlated with the improvement of the arable land ecological environment.Second,the reason for the ineffectiveness of the current arable ecological land compensation policy in protecting the arable land ecological environment in the main grain-producing regions is that the existing arable ecological land compensation policy in China has its own institutional defects and needs to be further improved.At the same time,the level of environmental pollution of cultivated land in the main grain-producing regions is positively correlated with the level of income from cultivated land and cultivated area.

Analysis of Highway Roadbed Performance Evaluation Technology

With the continuous development of China,the requirements for road construction are also increasing.Among them,strengthening the performance of roadbed test can effectively improve road construction.Besides,it is also crucial to perform suitable tests in a timely manner.Therefore,highway inspection technology should be improved for the continuous development of highway construction,which will be explained in this paper,in hopes of improving the construction of highway in China.

Assessing the Performance of CMIP6 Models in Simulating Droughts across Global Drylands

Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed.While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.

Comparative evaluation of commercial Douchi by different molds:biogenic amines,non-volatile and volatile compounds

To provide new insights into the development and utilization of Douchi artificial starters,three common strains(Aspergillus oryzae,Mucor racemosus,and Rhizopus oligosporus)were used to study their influence on the fermentation of Douchi.The results showed that the biogenic amine contents of the three types of Douchi were all within the safe range and far lower than those of traditional fermented Douchi.Aspergillus-type Douchi produced more free amino acids than the other two types of Douchi,and its umami taste was more prominent in sensory evaluation(P<0.01),while Mucor-type and Rhizopus-type Douchi produced more esters and pyrazines,making the aroma,sauce,and Douchi flavor more abundant.According to the Pearson and PLS analyses results,sweetness was significantly negatively correlated with phenylalanine,cysteine,and acetic acid(P<0.05),bitterness was significantly negatively correlated with malic acid(P<0.05),the sour taste was significantly positively correlated with citric acid and most free amino acids(P<0.05),while astringency was significantly negatively correlated with glucose(P<0.001).Thirteen volatile compounds such as furfuryl alcohol,phenethyl alcohol,and benzaldehyde caused the flavor difference of three types of Douchi.This study provides theoretical basis for the selection of starting strains for commercial Douchi production.

Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.

Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat

In order to further improve the utility of unmanned aerial vehicle(UAV)remote-sensing for quickly and accurately monitoring the growth of winter wheat under film mulching, this study examined the treatments of ridge mulching,ridge–furrow full mulching, and flat cropping full mulching in winter wheat.Based on the fuzzy comprehensive evaluation (FCE) method, four agronomic parameters (leaf area index, above-ground biomass, plant height, and leaf chlorophyll content) were used to calculate the comprehensive growth evaluation index (CGEI) of the winter wheat, and 14 visible and near-infrared spectral indices were calculated using spectral purification technology to process the remote-sensing image data of winter wheat obtained by multispectral UAV.Four machine learning algorithms, partial least squares, support vector machines, random forests, and artificial neural network networks(ANN), were used to build the winter wheat growth monitoring model under film mulching, and accuracy evaluation and mapping of the spatial and temporal distribution of winter wheat growth status were carried out.The results showed that the CGEI of winter wheat under film mulching constructed using the FCE method could objectively and comprehensively evaluate the crop growth status.The accuracy of remote-sensing inversion of the CGEI based on the ANN model was higher than for the individual agronomic parameters, with a coefficient of determination of 0.75,a root mean square error of 8.40, and a mean absolute value error of 6.53.Spectral purification could eliminate the interference of background effects caused by mulching and soil, effectively improving the accuracy of the remotesensing inversion of winter wheat under film mulching, with the best inversion effect achieved on the ridge–furrow full mulching area after spectral purification.The results of this study provide a theoretical reference for the use of UAV remote-sensing to monitor the growth status of winter wheat with film mulching.

Research on a TOPSIS energy efficiency evaluation system for crude oil gathering and transportation systems based on a GA-BP neural network

As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.

PARE:Privacy-Preserving Data Reliability Evaluation for Spatial Crowdsourcing in Internet of Things

The proliferation of intelligent,connected Internet of Things(IoT)devices facilitates data collection.However,task workers may be reluctant to participate in data collection due to privacy concerns,and task requesters may be concerned about the validity of the collected data.Hence,it is vital to evaluate the quality of the data collected by the task workers while protecting privacy in spatial crowdsourcing(SC)data collection tasks with IoT.To this end,this paper proposes a privacy-preserving data reliability evaluation for SC in IoT,named PARE.First,we design a data uploading format using blockchain and Paillier homomorphic cryptosystem,providing unchangeable and traceable data while overcoming privacy concerns.Secondly,based on the uploaded data,we propose a method to determine the approximate correct value region without knowing the exact value.Finally,we offer a data filtering mechanism based on the Paillier cryptosystem using this value region.The evaluation and analysis results show that PARE outperforms the existing solution in terms of performance and privacy protection.