Full-domain collaborative deployment method of multiple interference sources and evaluation of its deployment effect

This paper realizes the full-domain collaborative deployment of multiple interference sources of the global satellite navigation system(GNSS)and evaluates the deployment effect to enhance the ability to disturb the attacker and the capability to defend the GNSS during navigation countermeasures.Key evaluation indicators for the jamming effect of GNSS suppressive and deceptive jamming sources are first created,their evaluation models are built,and their detection procedures are sorted out,as the basis for determining the deployment principles.The principles for collaboratively deploying multi-jamming sources are developed to obtain the deployment structures(including the required number,structures in demand,and corresponding positions)of three single interference sources required by collaboratively deploying.Accordingly,simulation and hardware-in-loop testing results are presented to determine a rational configuration of the collaborative deployment of multi-jamming sources in the set situation and further realize the full-domain deployment of an interference network from ground,air to space.Varied evaluation indices for the deployment effect are finally developed to evaluate the deployment effect of the proposed configuration and further verify its reliability and rationality.

Assessing target optical camouflage effects using brain functional networks:A feasibility study

Brain functional networks model the brain's ability to exchange information across different regions,aiding in the understanding of the cognitive process of human visual attention during target searching,thereby contributing to the advancement of camouflage evaluation.In this study,images with various camouflage effects were presented to observers to generate electroencephalography(EEG)signals,which were then used to construct a brain functional network.The topological parameters of the network were subsequently extracted and input into a machine learning model for training.The results indicate that most of the classifiers achieved accuracy rates exceeding 70%.Specifically,the Logistic algorithm achieved an accuracy of 81.67%.Therefore,it is possible to predict target camouflage effectiveness with high accuracy without the need to calculate discovery probability.The proposed method fully considers the aspects of human visual and cognitive processes,overcomes the subjectivity of human interpretation,and achieves stable and reliable accuracy.

Evaluation and Application of Flowback Effect in Deep Shale Gas Wells

The pivotal areas for the extensive and effective exploitation of shale gas in the Southern Sichuan Basin have recently transitioned from mid-deep layers to deep layers.Given challenges such as intricate data analysis,absence of effective assessment methodologies,real-time control strategies,and scarce knowledge of the factors influencing deep gas wells in the so-called flowback stage,a comprehensive study was undertaken on over 160 deep gas wells in Luzhou block utilizing linear flow models and advanced big data analytics techniques.The research results show that:(1)The flowback stage of a deep gas well presents the characteristics of late gas channeling,high flowback rate after gas channeling,low 30-day flowback rate,and high flowback rate corresponding to peak production;(2)The comprehensive parameter AcmKm1/2 in the flowback stage exhibits a strong correlation with the Estimated Ultimate Recovery(EUR),allowing for the establishment of a standardized chart to evaluate EUR classification in typical shale gas wells during this stage.This enables quantitative assessment of gas well EUR,providing valuable insights into production potential and performance;(3)The spacing range and the initial productivity of gas wells have a significant impact on the overall effectiveness of gas wells.Therefore,it is crucial to further explore rational well patterns and spacing,as well as optimize initial drainage and production technical strategies in order to improve their performance.

Evaluation of the effectiveness of preventive nursing measures for pressure injuries in patients in the neurology intensive care unit

BACKGROUND Patients in neurology intensive care units(ICU)are prone to pressure injuries(PU)due to factors such as severe illness,long-term bed rest,and physiological dysfunction.PU not only causes pain and complications to patients,but also increases medical burden,prolongs hospitalization time,and affects the recovery process.AIM To evaluate and optimize the effectiveness of pressure injury prevention nursing measures in neurology ICU patients.METHODS A retrospective study was conducted,and 60 patients who were admitted to the ICU of the Department of Neurology were selected and divided into an observation group and a control group according to the order of admission,with 30 people in each group.The observation group implemented pressure injury prevention and nursing measures,while the control group adopted routine care.RESULTS Comparison between observation and control groups following pressure injury prevention nursing intervention revealed significantly lower incidence rates in the observation group compared to the control group at 48 h(8.3%vs 26.7%),7 d(16.7%vs 43.3%),and 14 d(20.0%vs 50.0%).This suggests a substantial reduction in pressure injury incidence in the observation group,with the gap widening over time.Additionally,patients in the observation group exhibited quicker recovery,with a shorter average time to get out of bed(48 h vs 72 h)and a shorter average length of stay(12 d vs 15 d)compared to the control group.Furthermore,post-intervention,patients in the observation group reported significantly improved quality of life scores,including higher scores in body satisfaction,feeling and function,and comfort(both psychological and physiological),indicating enhanced overall well-being and comfort following the implementation of pressure injury prevention nursing measures.CONCLUSION Implementing pressure injury preventive care measures for neurology ICU patients will have better results.

Prevention and Control Strategies of Nosocomial Infection and Effectiveness Evaluation in a Tertiary Teaching Hospital during the Epidemic of COVID-19

Objective: To evaluate the role of prevention and control strategies for nosocomial infection in a tertiary teaching hospital during the sudden outbreak of Corona Virus Disease 2019 (COVID-19). Methods: The hospital initiated an emergency plan involving multi-departmental defense and control. It adopted a series of nosocomial infection prevention and control measures, including strengthening pre-examination and triage, optimizing the consultation process, improving the hospital’s architectural composition, implementing graded risk management, enhancing personal protection, and implementing staff training and supervision. Descriptive research was used to evaluate the short-term effects of these in-hospital prevention and control strategies. The analysis compared changes in related evaluation indicators between January 24, 2020 and February 12, 2020 (Chinese Lunar New Year’s Eve 2020 to lunar January 19) and the corresponding lunar period of the previous year. Results: Compared to the same period last year, the outpatient fever rate increased by 1.85-fold (P P Conclusion: The nosocomial infection prevention and control strategies implemented during this specific period improved the detection and control abilities for the COVID-19 source of infection and enhanced the compliance with measures. This likely contributed significantly to avoiding the occurrence of nosocomial infection.

The Application and Effect Evaluation of Corpus Linguistics in English Teaching

This paper explores the application and effect evaluation of corpus linguistics in English teaching.It first introduces the basic concepts and development history of corpus linguistics,then analyzes its connection with language teaching theories,discussing the advantages and challenges of using corpora in language teaching.Next,it delves into the methods and technologies for building and utilizing corpora,as well as their role in developing teaching resources.Lastly,within the framework and methods of teaching effect evaluation,specific application cases of corpus linguistics in teaching design are analyzed,and their effects are assessed.Recommendations for teaching improvement and future development directions are also proposed.

Analysis of The Effect of General Medicine-Based Education in Type 2 Diabetes Mellitus Patients in Neijiang City, China

Objective:To investigate and analyze the current situation of cognition,attitude,behavior,and influencing factors of Type 2 Diabetes Mellitus(T2DM)patients in Neijiang City,and to explore the effectiveness of the application of the education program based on the popularization of science in general medicine.Methods:Seventy cases of T2DM patients in Neijiang City were selected and randomly divided into 35 cases each in the observation group and the control group.The observation group received general medicine science education intervention and the control group received traditional health education.Indicators such as cognitive level,attitude,and behavioral change between the two groups were compared to assess the effect of general medical science education.Results:Before the intervention,there was no difference between the two groups in terms of knowledge,beliefs,and behaviors in general medicine,glycemic control,body mass index(BMI),and satisfaction with health education(P>0.05).After 3 months of the intervention,there was a highly significant difference in the aforementioned levels between the two groups(P<0.05).Conclusion:The approach of general medicine popularization had a significant effect on the treatment and management of T2DM patients in Neijiang City.It improved the patient’s cognitive level and self-management ability of the disease,increased their treatment adherence,and improved the therapeutic effect.

Contribution of the MERISE-Type Conceptual Data Model to the Construction of Monitoring and Evaluation Indicators of the Effectiveness of Training in Relation to the Needs of the Labor Market in the Republic of Congo

This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.

Evaluation and Effect of Agro-meteorological Disasters on Agricultural Production in Liaoning Province

Based on statistic data of agricultural production and meteorological disasters in Liaoning Province from 1971 to 2008,the effect weight,disaster rate and variance value of main agro-meteorological disasters including drought,flood,wind,hail and frozen injury were calculated,and the variation characteristic of time series of agro-meteorological disasters was further analyzed,while the grade division and comprehensive evaluation of agro-meteorological disasters were carried out in our paper.The results showed that there was a negative correlation between grain yield and the degree of agro-meteorological disasters,and agro-meteorological disasters were relatively serious in 1989,1997 and 2000,with the reduction of grain yield.Meanwhile,the occurrence frequency of light disasters was highest,accounting for 39% of total years,and the adverse effect of agro-meteorological disasters on agricultural production became more and more severe decade by decade;the effect weight of drought reached 63%,so drought was the main agro-meteorological disaster influencing agricultural production.

Study on effectiveness evaluation of weapon systems based on grey relational analysis and TOPSIS

To evaluate the effectiveness of weapon systems, the advantages and disadvantages of grey relational analysis and TOPSIS for multiattribute decision-making is pointed out, and an effectiveness evaluation model of weapon systems by combining grey relational analysis and TOPSIS is proposed. The model aggregates the grey relational grade and the distance to a new integrated closeness and reflects not only the trend but also the situation of the alternative. The example illuminates that the model is effective for the effectiveness evaluation of weapon systems.

A framework for equipment systems-of-systems effectiveness evaluation using parallel experiments approach

Equipment systems-of-systems （SOS） effectiveness evaluation can provide important reference for construction and optimization of the equipment SoS. After discussing the basic theory and methods of parallel experiments, we depict an SoS effectiveness analysis and evaluation method using parallel expe- riments theory in detail. A case study is carried out which takes the missile defense system as an example. An artificial system of the missile defense system is constructed with the multi-agent modeling method. Then, single factor, multiple factors and defense position deployment computational experiments are carried out and evaluated with the statistical analysis method. Experiment re- sults show that the altitude of the secondary interception missile is not the key factor which affects SoS effectiveness and putting the defense position ahead will increase defense effectiveness. The case study demonstrates the feasibility of the proposed method.

Evolutionary Pattern and Effect of Administrative Division Adjustment During Urbanization of China:Empirical Analysis on Multiple Scales

The adjustment of administrative divisions is one of the important factors guiding China's urbanization, which has profound economic and social effects for regional development. In this paper, we comprehensively describe the process of the adjustment of administrative divisions at provincial and municipal levels in China and summarize the effects on the basic structure and patterns of the spatial development. We quantitatively assess the effects on fields such as urbanization and social economy through the use of multidimensional scaling. The results show that: 1) Upgrading county to municipality(or city-governed district) is the main way of adjusting the administrative divisions. It is also an important factor in the spatial differentiation of interprovincial urbanization. China's population urbanization can be divided into four patterns including interprovincial migration, provincial migration, natural growth, and growth caused by the adjustment of administrative divisions, which is also the main reason for the increased Chinese urbanization rate at the provincial level. 2) Taking the city of Beijing as an example, we generalize five adjustment patterns made to administrative divisions: the set-up of sub-districts, the set-up of regional offices, the upgrading of townships to sub-districts, the upgrading of townships to towns, and the set-up of towns and the addition of new regional offices. We summarize the municipal urban spatial structure, including the sub-district office area in the central urban area, the regional office area in the new urban area, the mixed area of villages, towns, and sub-district offices in the suburb area, and the township area in the outer suburb area. 3) The adjustment of administrative divisions triggers a significant circulative accumulation effect, resulting in the spatial locking of population and industrial agglomeration. It affects the evolution of the urban spatial form and plays an important role in shaping the urban spatial structure to move to the characteristic of multicenter. In general, the adjustment of administrative divisions was an important factor affecting the inflated statistical level of urbanization and also an important driving force for the evolution of Chinese urban spatial organization structure.

Self-organizing fuzzy clustering neural network and application to electronic countermeasures effectiveness evaluation

A self-organizing fuzzy clustering neural network by combining the self-organizing Kohonen clustering network with the fuzzy theory is proposed. This network model is designed for the effectiveness evaluation of electronic countermeasures, which not only exerts the advantages of the fuzzy theory, but also has a good ability in machine learning and data analysis. The subjective value of sample versus class is computed by the fuzzy computing theory, and the classified results obtained by self-organizing learning of Kohonen neural network are represented on output layer. Meanwhile, the fuzzy competition learning algorithm keeps the similar information between samples and overcomes the disadvantages of neural network which has fewer samples. The simulation result indicates that the proposed algorithm is feasible and effective.

Is the crop insurance program effective in China? Evidence from farmers analysis in five provinces

This paper aims to evaluate the effectiveness of the Chinese crop insurance program in terms of farmers＇ utility and welfare. A simulation model based on the power utility function was first developed to evaluate the effectiveness of crop insurance. Then, the Monte Carlo approach was used to generate the datasets of area, price, yield, cost, and income based on the characteristics of representative farmers, which were clustered and calibrated using the farm-level data of 574 individual farmers from five Chinese provinces. Finally, the effectiveness of Chinese crop insurance was evaluated by comparing the certainty equivalence（CE） of farmers＇ utility/welfare under alternative crop insurance scenarios. Government subsidy is a necessary premise for implementing the crop insurance program. The government should subsidize more than 50% of the crop insurance premium to motivate more farmers to participate in the program. The findings also show that the current crop insurance program in China has increased the farmers＇ welfare but still need to be improved to achieve the Pareto improvement and to make full use of the financial fund of the government. This paper is believed to not only extend academic research but also has significant implications for policymakers, especially in the context of rapid development of Chinese crop insurance with much issues such as rate, subsidy and coverage level needed to be improved.

Establishment and effectiveness evaluation of a scoring system for exertional heat stroke by retrospective analysis

Background: Heat stroke(HS) is a serious, life-threatening disease. However, there is no scoring system for HS so far. This research is to establish a scoring system that can quantitatively assess the severity of exertional heat stroke(EHS).Methods: Data were collected from a total of 170 exertional heat stroke(EHS) patients between 2005 and 2016 from 52 hospitals in China. Univariate statistical methods and comparison of the area under the receiver operating characteristic(ROC) curve(AUC) were used to screen exertional heat stroke score(EHSS) parameters, including but not limited body temperature(T), Glasgow Coma Scale(GCS) and others. By comparing the sizes of the AUCs of the APACHE II, SOFA and EHSS assessments, the effectiveness of EHSS in evaluating the prognosis of EHS patients was verified.Results: Through screening with a series of methods, as described above, the present study determined 12 parameters – body temperature(T), GCS, p H, lactate(Lac), platelet count(PLT), prothrombin time(PT), fibrinogen(Fib), troponin I(Tn I), aspartate aminotransferase(AST), total bilirubin(TBIL), creatinine(Cr) and acute gastrointestinal injury(AGI) classification – as EHSS parameters. It is a 0–47 point system designed to reflect increasing severity of heat stroke. Low(EHSS<20) and high scores(EHSS>35) showed 100% survival and 100% mortality, respectively. We found that AUCEHSS>AUCSOFA>AUCAPACHE II.Conclusions: A total of 12 parameters – T, GCS, p H, Lac, PLT, PT, Fib, Tn I, AST, TBIL, Cr and gastrointestinal AGI classification – are the EHSS parameters with the best effectiveness in evaluating the prognosis of EHS patients. As EHSS score increases, the mortality rate of EHS patients gradually increases.

Design and operation strategies of the system for destroying time-sensitive target based on system effectiveness

To improve the effect of destroying time-sensitive target （TST）, a method of operational effectiveness evaluation is presented and some influential factors are analyzed based on the combat flow of system for destroying TST. Considering the possible operation modes of the system, a waved operation mode and a continuous operation mode are put forward at first. At the same time, some relative formulas are modified. In examples, the influential factors and operation modes are analyzed based on the system effectiveness. From simulation results, some design and operation strategies of the system for destroying time sensitive targets are concluded, which benefit to the improvement of the system effectiveness.

Effectiveness of enhanced recovery after surgery in the perioperative management of patients with bone surgery in China

BACKGROUND Enhanced recovery after surgery(ERAS)was introduced in China in 2007.Over time,the scope of ERAS has expanded from abdominal surgery to orthopedics,urology and other fields.Continuous development and research has contributed to progress of ERAS in China.In 2019,to promote the application of ERAS in bone tumor surgery,we formed the“Consensus of Experts on Perioperative Management of Accelerated Rehabilitation in Major Surgery of Bone Tumors in China”.AIM To evaluate the effect of enhanced recovery after bone tumor surgery in perioperative management in China.METHODS One hundred and seven patients who underwent bone tumor surgery at the Second Affiliated Hospital of Xi’an Jiaotong University between May 2019 and April 2021 were randomized into a study group(53 cases)and a control group(54 cases).The study group adopted the ERAS protocol and the control group adopted conventional care.Main outcome measures included postoperative length of stay(LOS),postoperative complications,mortality,and 30-d readmission rates.Secondary outcomes included postoperative visual analog scale(VAS)score of pain,number of blood transfusions,drainage volume in 24 h after operation,patient satisfaction 30 d after discharge,VAS score at 30 d after discharge,and daily standing walking time.RESULTS There were no significant differences in the baseline data,clinical features and surgical site between the two groups.The LOS in the study group with the ERAS protocol was 7.72±3.34 d compared with 10.28±4.27 d in the control group who followed conventional care.The incidence of postoperative nausea and vomiting(PONV)in the study group was 19%and 37%in the control group.The VAS scores of pain on postoperative day 1(POD1)and POD3 in the study group were 4.79±2.34 and 2.79±1.53 compared with 5.28±3.27 and 3.98±2.27 in the control group.The drainage volume in 24 h after the operation was 124.36±23.43 mL in the study group and 167.43±30.87 mL in the control group.The number of blood transfusions in the study group was also lower.The patient satisfaction rate was higher in the study group than in the control group.CONCLUSION The ERAS protocol in the perioperative period of bone tumor surgery can decrease LOS,PONV,and postoperative pain,blood transfusion and 24-h drainage,improve patient satisfaction and accelerate recovery.

Support vector regression-based operational effectiveness evaluation approach to reconnaissance satellite system

As one of the most important part of weapon system of systems(WSoS),quantitative evaluation of reconnaissance satellite system(RSS)is indispensable during its construction and application.Aiming at the problem of nonlinear effectiveness evaluation under small sample conditions,we propose an evaluation method based on support vector regression(SVR)to effectively address the defects of traditional methods.Considering the performance of SVR is influenced by the penalty factor,kernel type,and other parameters deeply,the improved grey wolf optimizer(IGWO)is employed for parameter optimization.In the proposed IGWO algorithm,the opposition-based learning strategy is adopted to increase the probability of avoiding the local optima,the mutation operator is used to escape from premature convergence and differential convergence factors are applied to increase the rate of convergence.Numerical experiments of 14 test functions validate the applicability of IGWO algorithm dealing with global optimization.The index system and evaluation method are constructed based on the characteristics of RSS.To validate the proposed IGWO-SVR evaluation method,eight benchmark data sets and combat simulation are employed to estimate the evaluation accuracy,convergence performance and computational complexity.According to the experimental results,the proposed method outperforms several prediction based evaluation methods,verifies the superiority and effectiveness in RSS operational effectiveness evaluation.

Remediation Effects of Soil Conditioners for CdPolluted Paddy Fields

A field experiment was conducted to evaluate the remediation effects of 14 soil conditioners for Cd-polluted paddy fields contrasted with conventional fertilization and liming.The results showed that soil conditioners had no significant impact on rice yields.Though the soil conditioners had stable effects on decreasing the Cd content in grains,the effects varied with the category of conditioners.In general,The Cd contents of early rice and late rice were reduced by 22.65%~44.24%and 15.20%~63.03%,respectively.Additionally,the stem and leaves showed the same decreasing tendency.Cluster analysis suggested that soil conditioners can be divided into three categories:the first category increases the soil pH to inhibit the Cd activity and cut down the Cd translocation from soil to stem and leaves,which is most efficient in the reduction of Cd content in rice grains;the other category relies on the antagonism or co-precipitation between Cd and certain elements to inhibit the translocation and redistribution of Cd from rice stems to grains,providing a common effect on Cd reduction;the last category can be seen as a combination of the former two categories from the perspective of its functional mechanism and it has a moderate effect on the reduction of Cd contents in rice grains.

Applying the AHP-FUZZY method to evaluate the measure effect of rubble roadbed engineering in permafrost regions of Qinghai-Tibet Plateau: a case study of Chaidaer-Muli Railway

This article attempts to investigate the measure effect of rubble roadbed engineering in permafrost regions of Qinghai-Tibet Plateau. As a case study, Chaidaer-Muli Railway is used to evaluate the measure effect of rubble roadbed engineering in permafrost regions. The AHP(Analytic Hierarchy Process) method is thus employed to establish the evaluation indicator system. The evaluation factor is selected by analyzing the mutual relation between the permafrost environment and roadbed engineering. Thus, a hierarchical structure model is established based on the selected evaluation indices. Each factor is weighted to determine the status in the evaluation system, and grading standards are built for providing a basis for the evaluation. Then, the fuzzy mathematical method is introduced to evaluate the measure effect of rubble roadbed engineering in permafrost regions along the Chadaer-Muli Railway. Results show that most of the permafrost roadbed is in a preferable condition(b) along the Chaidaer-Muli Railway due to rubble engineering measures. This proportion reaches to 86.1%. The proportion in good(a), general(c) and poor states(d) are 0.0%, 7.5% and 6.4%, respectively, in all the evaluation sections along the Chaidaer-Muli Railway. Ground-temperature monitoring results are generally consistent with AHP-FUZZY evaluation results. This means that the AHP-FUZZY method can be applied to evaluate the effect of rubble roadbed engineering measures in permafrost regions. The effect evaluation of engineering measures will provide timely and effective feedback information for further engineering design. The series of engineering measures will more effectively protect permafrost stability.