BEACON SYNCHRONIZATION TECHNOLOGY FOR “BEIDOU” TERRESTRIAL IMPROVEMENT SYSTEM

Synchronization is an essential technology in the radio navigation system. The technique for improving the “Beidou” positioning ability is presented through constituting the terrestrial improvement system, and the beacon synchronization of the improvement system with the “Beidou” one-way time transfer model is realized.The direct digital synthesis (DDS) is adopted to generate the pseudo-random code clock having high precision and stability. Meanwhile, the CPLD device is used to design the synchronization pulse picking-up module, the spread spectrum PN code generator and the spread spectrum modulator. Measurement results indicate that the beacon synchronization has the high precision and the stability.

Artificial-intelligent-powered safety and efficiency improvement for controlling and scheduling in integrated railway systems

The multi-mode integrated railway system,anchored by the high-speed railway,caters to the diverse travel requirements both within and between cities,offering safe,comfortable,punctual,and eco-friendly transportation services.With the expansion of the railway networks,enhancing the efficiency and safety of the comprehensive system has become a crucial issue in the advanced development of railway transportation.In light of the prevailing application of artificial intelligence technologies within railway systems,this study leverages large model technology characterized by robust learning capabilities,efficient associative abilities,and linkage analysis to propose an Artificial-intelligent(AI)-powered railway control and dispatching system.This system is elaborately designed with four core functions,including global optimum unattended dispatching,synergetic transportation in multiple modes,high-speed automatic control,and precise maintenance decision and execution.The deployment pathway and essential tasks of the system are further delineated,alongside the challenges and obstacles encountered.The AI-powered system promises a significant enhancement in the operational efficiency and safety of the composite railway system,ensuring a more effective alignment between transportation services and passenger demands.

Identifying a competency improvement strategy for infection prevention and control professionals:A rapid systematic review and cluster analysis

Remarkable progress has been made in infection prevention and control(IPC)in many countries,but some gaps emerged in the context of the coronavirus disease 2019(COVID-19)pandemic.Core capabilities such as standard clinical precautions and tracing the source of infection were the focus of IPC in medical institutions during the pandemic.Therefore,the core competences of IPC professionals during the pandemic,and how these contributed to successful prevention and control of the epidemic,should be studied.To investigate,using a systematic review and cluster analysis,fundamental improvements in the competences of infection control and prevention professionals that may be emphasized in light of the COVID-19 pandemic.We searched the PubMed,Embase,Cochrane Library,Web of Science,CNKI,WanFang Data,and CBM databases for original articles exploring core competencies of IPC professionals during the COVID-19 pandemic(from January 1,2020 to February 7,2023).Weiciyun software was used for data extraction and the Donohue formula was followed to distinguish high-frequency technical terms.Cluster analysis was performed using the within-group linkage method and squared Euclidean distance as the metric to determine the priority competencies for development.We identified 46 studies with 29 high-frequency technical terms.The most common term was“infection prevention and control training”(184 times,17.3%),followed by“hand hygiene”(172 times,16.2%).“Infection prevention and control in clinical practice”was the most-reported core competency(367 times,34.5%),followed by“microbiology and surveillance”(292 times,27.5%).Cluster analysis showed two key areas of competence:Category 1(program management and leadership,patient safety and occupational health,education and microbiology and surveillance)and Category 2(IPC in clinical practice).During the COVID-19 pandemic,IPC program management and leadership,microbiology and surveillance,education,patient safety,and occupational health were the most important focus of development and should be given due consideration by IPC professionals.

Targeted mutagenesis of amino acid transporter genes for rice quality improvement using the CRISPR/Cas9 system

High grain protein content(GPC) reduces rice eating and cooking quality(ECQ). We generated OsAAP6 and OsAAP10 knockout mutants in three high-yielding japonica varieties and one japonica line using the CRISPR/Cas9 system. Mutation efficiency varied with genetic background in the T_0 generation, and GPC in the T_1 generation decreased significantly,owing mainly to a reduction in glutelin content. Amylose content was down-regulated significantly in some Osaap6 and all Osaap10 mutants. The increased taste value of these mutants was supported by Rapid Visco Analysis(RVA) profiles, which showed higher peak viscosity and breakdown viscosity and lower setback viscosity than the wild type. There were no significant deficiencies in agronomic traits of the mutants. Targeted mutagenesis of OsAAP6 and OsAAP10, especially OsAAP10, using the CRISPR/Cas9 system can rapidly reduce GPC and improve ECQ of rice, providing a new strategy for the breeding cultivars with desired ECQ.

Biological improvement of saline alkali soil reference system:A review

This work presents a reference system overview to improve the efficiency of biological improvement of saline-alkali soil developed during the last thirty years, ranging from connotation, general methods and species, soil desalination, soil structure, soil organic content, microbial flora, enzyme activity, yield and economic benefits. The reference system presented is divided into three main groups: suitable varieties, suitable cultivation measures, and a comprehensive evaluation system.There has been a lot of research on biological improvement of saline alkali soil, but these studies are very fragmented and lack a comprehensive standard system. Also, there is a lack of practical significance, particularly with regard to optimal species, densities and times of sowing for particular regions. On the other hand, the corresponding cultivation measure is very important. Therefore, a reference system plays an important role to the effect of biological improvement of saline alkali soil.

Integrating artificial intelligence and high-throughput phenotyping for crop improvement

Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.

Reliability Improvement of Large Multi-state Series-parallel Systems

In the paper, excess methods for improving the reliability of multi-state series-parallel systems are presented： for the hot reserve of single components, the cold reserve of single components, and the mixed （hot and cold） reserve of single components. A process is also introduced to improve the reliability of these methods by replacing their components with more reliable ones. New theorems for multi-state limit reliability functions in homogeneous and non-homogeneous series-parallel large systems composed of components with improved reliability are presented, and applied to compare the effects of these systems in different reliability improving methods.

Phenotypic Characterization and Strategies for Genetic Improvement of WAD Goats under Backyard Systems

West African Dwarf (WAD) goats represent one of the predominant small ruminant breeds raised by resource-limited households in southern Nigeria as well as in the humid west and central Africa. This breed of goats is renowned for its adaptation to hot and humid environments, high fertility and prolificacy under backyard systems where they are raised almost with zero investment. On account of its contributions to household income and food security in southern Nigeria, there is the need for a detailed phenotypic and genetic characterization as well as the design of breeding strategies for its conservation through sustainable utilization. A critical challenge, however, is that there are no national breeding policies in most of the countries where WAD goats are raised. The objectives of this paper are: to review literature reports on trait-level information and estimates of genetic parameters for some economic characters of WAD goats;and to discuss a communal breeding scheme for its conservation through sustainable utilization. The presentation shows that WAD goats represent a highly diverse population, with particular reference to qualitative and performance-related traits, reflecting the role of traditional institutions in the maintenance of animal diversity in local populations. A genetic improvement programme involving dispersed open nucleus breeding scheme was discussed. The scheme involves backyard WAD goat units in villages as base population and dispersed communally managed schemes that maintain a population of bucks only, as nucleus units. Critical issues such as the definition of breeding goals by farmers, as well as communal project ownership, are emphasized. The ultimate goal of the breeding programme is to create opportunities for community-based management of WAD goat genetic resources for the benefit of backyard goat farmers in the region.

Holonic Management Tree Technique for Performance Improvement Over Self-Similar System Structures

This paper presents the detailed definition of technique for the automation of the management of complex business systems, whether they are constituted of services and productions. The technique has been referred here for the first time as Holonic Management Tree (HMT) and has been consistently contextualized into undergoing research on technological frameworks for the management cybernetics, in which the concept of viable system represents a fundamental stance. HMT is based on the use of recursive formulas over self-similar holonic structures for the attainment of continuous performance improvement in a complex and continuously evolving process. The problem is associated to a recursive tree of self-similar structures of which in this paper we discuss the interpretation with respect to knowledge modeling domain. The basic expressions for the computation of the 2nd degree trees are provided and explained in detail by means of an example in lean management context. Moreover, this work presents and discusses the expressions that handle the implementation of the n-th degree case as a recurrent abstraction of the basic and simple 2nd degree computation.

GENERALIZED TRANSFER FUNCTION OF CONTROL SYSTEM AND AN IMPROVEMENT ON THE DECISION METHOD OF MOVEMENT STABILITY

In this paper the definitions of generalized transfer functios of control system and itscontinuity are presented.Using generalized transfer function as a tool,a set of theorems fordeciding movement stability have been constructed.Thus basing understanding of thecharacteristics of a control dynamics system on its measured procedure will simplify thedecision method of movement stability problems.

A Preliminary Study on the Problems and Improvement of the Latest Land Use Classification System in China

The establishment of a unified land use classification system is the basis for realizing the unified management of land and sea,urban and rural areas,and aboveground and underground space.In November 2020,the Ministry of Natural Resources of the People's Republic of China issued the Classification Guide for Land and Space Survey,Planning and Use Control of Land and Sea(for Trial Implementation),which aims to establish a national unified land and sea use classification system,lay an important foundation for scientific planning and unified management of natural resources,rational use and protection of natural resources,and speed up the construction of a new pattern of land and space development and protection.However,there are still some obvious shortcomings in the Classification Guide.This paper analyzes some problems existing in this classification standard from three aspects of logicality,rigorousness and comprehensiveness,and puts forward some suggestions for further improvement.This has important practical significance to better guiding the practice of land use and land resources management,and then to achieving the goal of unified management of natural resources.

Study on the Applicable Principle and System Improvement of Contract Law to Liquidated Damages

Based on the applicable principle of liquidated damages in ＂contract law＂, based on the improvement of the system, the article first analyzes the status quo of the development of the default system and secondly puts forward some suggestions for improvement. The final purpose is to perfect the liquidated damages system with the Contract Law, in a bid to enhance the fairness of liquidated damages.

Stroke nurse-led intravenous thrombolytic therapy strategy for ischemic stroke based on timeline process:A quality improvement program from China

Objective:Early thrombolytic therapy for ischemic stroke within the therapeutic window is associated with improved clinical outcomes.This study investigated whether optimizing intravenous thrombolytic(IVT)therapy strategies for stroke could reduce treatment delays.Methods:To reduce delays in IVT therapy for ischemic stroke,a series of quality improvement measures were implemented at a tertiary hospital in Hangzhou,Zhejiang Province,from June 2021 to August 2023,which included developing a timeline process management system,forming a nurse-led stroke process management team,providing homogeneous training,standardizing the IVT therapy process for ischemic stroke,and introducing an incentive policy.During the pre-(from June 2021 to February 2022,group A)and post-(from March to November 2022,group B1;from December 2022 to August 2023,group B2[implementation of an additional incentive policy])of the implementation the strategy,the door-tocomputed tomographic angiography(CTA)time(DCT),CTA time,neurology consultation to consent for IVT,CTA-to-needle time(CNT),and door-to-needle time(DNT),the percentage of people who underwent CTA within 20 min,15 min,and 10 min and DNT within 60 min,45 min,and 30 min were collected and compared.Results:Following the implementation of the standardized IVT process management strategy for stroke,the DNT for group B1 and group B2 were 30(24,44)min and 31(24,41)min,respectively,both significantly lower than the 46(38,58)min in group A(P<0.001);the median DCT were both 13 min in group B1 and B2 lower than 17min in group A(P<0.001);the median CTA were 12 min in Group B1 and 9 min in Group B2 lower than 14 min in group A(P<0.001);similar results were observed during the neurology consultation to obtain consent for IVT and CNT.Compared with group A,the proportion of DCT20 min,15 min,and 10 min was higher in groups B1 and B2(P<0.05),and the same result was observed at DNT60 min,45 min,and 30 min(P<0.05).However,the additional incentive policy did not significantly differ between Group B2 and Group B1.Conclusions:Optimizing IVT therapy for ischemic stroke is a feasible approach to limit the DNT to 30 min in ischemic stroke,significantly reducing delays within the therapeutic window and increasing the number of patients meeting target time segments.Additionally,generating a timeline for the IVT therapy process by scanning positioning quick response codes was a significant breakthrough in achieving the informatization of IVT quality management for stroke.

Deterioration Reason and Improvement Measure of the Retarding Effect of Protein Retarder on Phosphorus Building Gypsum

The retarding effect of protein retarder on phosphorus building gypsum(PBG)and desulfurization building gypsum(DBG)was investigated,and the results show that protein retarder for DBG can effectively prolong the setting time and displays a better retarding effect,but for PBG shows a poor retarding effect.Furthermore,the deterioration reason of the retarding effect of protein retarder on PBG was investigated by measuring the pH value and the retarder concentration of the liquid phase from vacuum filtration of PBG slurry at different hydration time,and the measure to improve the retarding effect of protein retarding on PBG was suggested.The pH value of PBG slurry(<5.0)is lower than that of DBG slurry(7.8-8.5).After hydration for 5 min,the concentration of retarder in liquid phase of DBG slurry gradually decreases,but in liquid phase of PBG slurry continually increases,which results in the worse retarding effect of protein retarder on PBG.The liquid phase pH value of PBG slurry can be adjusted higher by sodium silicate,which is beneficial to improvement in the retarding effect of the retarder.By adding 1.0%of sodium silicate,the initial setting time of PBG was efficiently prolonged from 17 to 210 min,but little effect on the absolute dry flexural strength was observed.

Anti-aging performance improvement and enhanced combustion efficiency of boron via the coating of PDA

Boron is an ambitious fuel in energetic materials since its high heat release values,but its application is prohibited by low combustion efficiency and oxidization during storage.The polydopamine(PDA)was introduced into boron particles,investigating the impact of PDA content on the energetic behavior of boron.The results indicated that the PDA coating formed a fishing net structure on the surface of boron particles.The heat release results showed that the combustion calorific value of B@PDA was higher than that of the raw boron.Specifically,the actual combustion heat of boron powder in B@10%PDA increased by 38.08%.Meanwhile,the DSC peak temperature decreased by 100.65℃under similar oxidation rate compared to raw boron.Simultaneously,the B@PDA@AP and B@AP composites were prepared,and their combustion properties were evaluated.It was demonstrated that B@10%PDA@AP exhibited superior performance in terms of peak pressure and burning time,respectively.The peak pressure is 12.43 kPa more than B@AP and burning time is 2.22 times higher than B@AP.Therefore,the coating of PDA effectively inhibits the oxidization of boron during storage and enhances the energetic behavior of boron and corresponding composites.

In situ digital testing method for quality assessment of soft soil improvement with polyurethane

This study purposes an in situ testing method on quality assessment of soil improvement.Factual drilling data includes the spatial distribution and in situ strength of untreated and treated soil along three different drillholes measured by on-site drilling monitoring method.These factual drilling data can characterize the degree of soil improvement by penetration injection with permeable polyurethane.Result from on-site drilling monitoring shows that the linear zones represent constant drilling speeds shown in the plot of drill bit advancement vs.net drilling time,which indicates the spatial distributions of soil profile.The soil profile at the study site is composed of four layers,which includes fill,untreated silty clay,treated silty clay,and mucky soil.The results of soil profile are verified by the parallel site loggings.The constant drilling speeds profile the coring-resistant strength of drilled soils.By comparing with the untreated silty clay,the constant drilling speeds of the treated silty clay have been decreased by 13.0-62.8%.Two drilling-speed-based indices of 61.2%and 65.6%are proposed to assess the decreased average drilling speed and the increased in situ strength of treated silty clay.Laboratory tests,i.e.uniaxial compressive strength(UCS)test,have been performed with core sample to investigate and characterize in situ strength by comparing that with drilling speeds.Results show that the average predicted strengths of treated silty clay are 2.4-6.9 times higher than the average measured strength of untreated silty clay.The UCS-based indices of 374.5%and 344.2%verified the quality assessment(QA)results by this new in situ method.This method provides a cost-effective tool for quality assessment of soil improvement by utilizing the digital drilling data.

Data-driven diagnosis of high temperature PEM fuel cells based on the electrochemical impedance spectroscopy: Robustness improvement and evaluation

Utilizing machine learning techniques for data-driven diagnosis of high temperature PEM fuel cells is beneficial and meaningful to the system durability. Nevertheless, ensuring the robustness of diagnosis remains a critical and challenging task in real application. To enhance the robustness of diagnosis and achieve a more thorough evaluation of diagnostic performance, a robust diagnostic procedure based on electrochemical impedance spectroscopy (EIS) and a new method for evaluation of the diagnosis robustness was proposed and investigated in this work. To improve the diagnosis robustness: (1) the degradation mechanism of different faults in the high temperature PEM fuel cell was first analyzed via the distribution of relaxation time of EIS to determine the equivalent circuit model (ECM) with better interpretability, simplicity and accuracy;(2) the feature extraction was implemented on the identified parameters of the ECM and extra attention was paid to distinguishing between the long-term normal degradation and other faults;(3) a Siamese Network was adopted to get features with higher robustness in a new embedding. The diagnosis was conducted using 6 classic classification algorithms—support vector machine (SVM), K-nearest neighbor (KNN), logistic regression (LR), decision tree (DT), random forest (RF), and Naive Bayes employing a dataset comprising a total of 1935 collected EIS. To evaluate the robustness of trained models: (1) different levels of errors were added to the features for performance evaluation;(2) a robustness coefficient (Roubust_C) was defined for a quantified and explicit evaluation of the diagnosis robustness. The diagnostic models employing the proposed feature extraction method can not only achieve the higher performance of around 100% but also higher robustness for diagnosis models. Despite the initial performance being similar, the KNN demonstrated a superior robustness after feature selection and re-embedding by triplet-loss method, which suggests the necessity of robustness evaluation for the machine learning models and the effectiveness of the defined robustness coefficient. This work hopes to give new insights to the robust diagnosis of high temperature PEM fuel cells and more comprehensive performance evaluation of the data-driven method for diagnostic application.

Probabilistic Automata-Based Method for Enhancing Performance of Deep Reinforcement Learning Systems

Deep reinforcement learning(DRL) has demonstrated significant potential in industrial manufacturing domains such as workshop scheduling and energy system management.However, due to the model's inherent uncertainty, rigorous validation is requisite for its application in real-world tasks. Specific tests may reveal inadequacies in the performance of pre-trained DRL models, while the “black-box” nature of DRL poses a challenge for testing model behavior. We propose a novel performance improvement framework based on probabilistic automata,which aims to proactively identify and correct critical vulnerabilities of DRL systems, so that the performance of DRL models in real tasks can be improved with minimal model modifications.First, a probabilistic automaton is constructed from the historical trajectory of the DRL system by abstracting the state to generate probabilistic decision-making units(PDMUs), and a reverse breadth-first search(BFS) method is used to identify the key PDMU-action pairs that have the greatest impact on adverse outcomes. This process relies only on the state-action sequence and final result of each trajectory. Then, under the key PDMU, we search for the new action that has the greatest impact on favorable results. Finally, the key PDMU, undesirable action and new action are encapsulated as monitors to guide the DRL system to obtain more favorable results through real-time monitoring and correction mechanisms. Evaluations in two standard reinforcement learning environments and three actual job scheduling scenarios confirmed the effectiveness of the method, providing certain guarantees for the deployment of DRL models in real-world applications.

Reflections on Improvement of Utility Model System in China

Even since 1985 when the Patent Law was launched in China, the utility model patent has been playing a very important role. Over the two decades, the utility model system has played an active part in encouraging invention-creations, and promoting the progress and development of science and technology.