Evaluation Indicators Research Articles

Feature‑oriented energy consumption allowance approach of machining systems for energy‑efficient manufacturing

ABSTRACT The main problems in the manufacturing industry are high energy consumption and low energy efficiency. The application of manufacturing energy consumption allowance plays a crucial role in the energy saving of the machining systems. This paper presents a novel method for developing standard energy consumption allowance (ECA) for workpieces based on the inherent specific energy of machining system. First, the inherent specific energy of the machining system when machining a particular type of feature is determined. The standard energy consumption of the workpiece is then determined based on the specific energy of the machined workpiece feature. This paper respectively presents the specific mathematical model and the test acquisition method of the evaluation indicators. The approach to setting ECA proposed in this paper is more representative and general, taking into account the changing processes in the future. Moreover, this novel method of setting energy consumption allowance will help companies to more scientifically identify machining systems that are more suitable for machining certain types of workpieces.

The application of grey statistical method and analytic hierarchy process in the evaluation of community park rehabilitation landscapes

The rehabilitation landscape of community parks plays a significant role in the physical and mental health of urban residents, social interaction, improvement of the ecological environment, and the sustainable development of cities. This research applies the Grey Statistical Technique (GST) combined with the Analytic Hierarchy Process (AHP) model to establish an evaluation system for landscape assessment. The system is constructed based on three dimensions: physical rehabilitation, psychological rehabilitation, and spiritual rehabilitation. The GST method is utilized to screen and select evaluation indicators, while the AHP method is employed to construct the landscape evaluation system and calculate the weights of each indicator. The results are as follows: (1) Out of the 30 indicator factors, 13 were not selected through the GST method. (2) The weights of the criteria layer, from highest to lowest, are as follows: physical rehabilitation (D1) with a weight of 0.6370, psychological rehabilitation (D2) with a weight of 0.2583, and spiritual rehabilitation (D3) with a weight of 0.1047. (3) The highest and lowest values in the indicator layer are as follows: D1 (P14: illumination duration 0.2359, P17: hydrological conditions 0.0197); D2 (P21: sense of security 0.1433, P23: human-environment interaction 0.0162); D3 (P34: sense of pleasure 0.0400, P36: aesthetic value 0.0045). This research reduces the subjectivity in the evaluation indicators and provides valuable guidance for the design of rehabilitation landscapes in community parks.

Active frequency support capability evaluation of photovoltaic stations based on bi-level evaluation method

With the increasing penetration of photovoltaic (PV) in power grid, to cope with the deteriorating frequency security of the system, PV stations are required to participate in frequency regulation by grid codes. Knowing the active frequency support capability (AFSC) of PV stations is essential for strategy design of frequency response. Therefore, a comprehensive indicator system and an integrated evaluation method are proposed to evaluate the AFSC of PV stations. By considering several national standards, a comprehensive evaluation indicator system of AFSC for PV stations is established from three aspects: frequency stability, power support, and power regulation. In order to avoid the impact of subjective factors, this paper proposes a bi-level evaluation model combining decision-making trial and evaluation laboratory (DEMATEL), technique for order preference by similarity to ideal solution (TOPSIS), and antagonistic interpretive structural modeling (AISM) for weighting the indicators. Finally, case study was performed based on IEEE 39-bus test system integrated with PV station. The results show that the proposed indicator system and evaluation method can reflect the AFSC of PV stations effectively. The evaluation indicator system for the AFSC of PV stations is also developed into software to promote its application and implementation.

Research on improving urban park green space landscape quality based on public psychological perception: a comprehensive AHP-TOPSIS-POE evaluation of typical parks in Jinan City

During rapid urbanization, environmental issues significantly affect urban residents health. Urban parks and green spaces play a crucial role in urban planning and layout, significantly impacting residents quality of life and livability. This study constructs a comprehensive landscape evaluation model, “AHP-TOPSIS-POE” from the perspective of behavioral psychological perception. It uses four urban parks in Jinan City (Qianfoshan Park, Baotu Spring Park, Daming Lake Park, and Quancheng Park) as case study samples. This method validates its feasibility by converting subjective perceptions into objective data. The research findings are as follows: (1) Urban park green space landscapes are significantly correlated with public psychological recovery; (2) The weight ranking of the criteria layer is as follows: Landscape Perception (B4) 0.5135 > Social Interaction (B3) 0.3015 > Spatial Form (B2) 0.1244 > Visual Quality (B1) 0.0606; (3) The relative closeness ranking of the four typical urban parks in Jinan City is as follows: Qianfoshan Park > Quancheng Park > Daming Lake Park > Baotu Spring Park. This study aims to reduce the subjectivity of evaluation indicators, raise public awareness of high-quality cognition and emotional experiences, and provide a scientific basis for the development of scientifically reasonable urban park green landscapes.

The coordinated development and evolutionary characteristics of “Port-Industry-City” System in Fangchenggang City of Western China

This study develops an integrated research framework that combines a Comprehensive Evaluation Indicator System, Coupling Coordination Degree Model, Composite System Evolution Model, and Obstacle Degree Model to analyze the dynamics of the 'Port-Industry-City' system. Using Fangchenggang, a keyt port in western China, as a case study, the paper contributes to the understanding of how port, industry, and city systems interact and evolve over time. The research findings indicate that: (1) At the system level, the coordination and interaction degree consistently improve, although the coupling and coordination exhibit fluctuating trends. The system progresses through various lag types, from port and city lag to industrial lag. (2) At the subsystem level, while the 'Industry-City' system remains stable, the 'Port-City' and 'Port-Industry' systems show fluctuating upward evolution, with U-shaped and W-shaped dynamic patterns. (3) At both the first- and second-level index factors, the primary lagging factors include industrial structure, city scale, and urban economy. Among the secondary indicators, the most significant lagging factors are total highway mileage and resident population. (4) The study highlights that the 'big port, small city' paradigm imposes significant constraints on the integrated development of Fangchenggang, with industrial development being the most critical challenge for future growth. This research provides new insights into the 'Port-Industry-City' literature by developing a multi-dimensional framework to assess the synergistic development of port cities and their industries.

A systematic review of the efficacy of repetitive transcranial magnetic stimulation in treating dysarthria in patients with Parkinson's disease

ObjectiveTo analyze the literature on the efficacy of repetitive transcranial magnetic stimulation (rTMS) in treating dysarthria in patients with Parkinson's disease (PD) and provide a reference for targeted clinical treatment of dysarthria in PD patients.MethodsA systematic search was conducted in English and Chinese databases, including Embase, Cochrane, Medline, PubMed, CNKI, Wanfang, Chinese Biomedical Literature Database, and VIP Database, for relevant literature on rTMS treatment for dysarthria in PD patients. The search timeframe was from the inception of each database to October 2023. Literature was screened according to inclusion and exclusion criteria. Two researchers extracted information on study subjects, age, intervention methods, intervention duration, intervention frequency, evaluation indicators, and intervention results from the included literature. The modified Jadad scale was used to evaluate the quality of the literature.ResultsA total of seven studies were included, mainly focusing on the frequency, duration, and stimulation site of rTMS for dysarthria in PD patients. Six studies indicated that rTMS treatment improved dysarthria in PD patients.ConclusionRepetitive transcranial magnetic stimulation has a positive effect on improving dysarthria in PD patients, but further research is needed to determine its efficacy.

A Multi-Objective Nutcracker Optimization Algorithm Based on Cubic Chaotic Map for Numerical Association Rule Mining

Traditional numerical association rule mining optimization algorithms have limitations in handling discrete attributes, and they are susceptible to becoming trapped in local optima, uneven population distribution, and poor convergence. To address these challenges, we propose a multi-objective nutcracker optimization algorithm based on a cubic chaotic map (C-MONOA), specifically designed for mining association rules from mixed data (continuous and discrete). Unlike existing models, C-MONOA leverages a chaotic map for population initialization, alongside Michigan rule encoding, to dynamically optimize feature intervals during the optimization process. This algorithm integrates continuous and discrete data more effectively and efficiently. This article uses support, confidence, Kulc metric, and comprehensibility as evaluation indicators for multi-objective optimization. The experimental results show that C-MONOA performs well in rule scoring and can generate frequent, simple, and accurate rule sets. This study extends the association rule mining method for mixed data, demonstrating high performance and robustness and providing new technical tools for application fields such as market analysis and disease prediction.

Evaluation of Pedestrian-Perceived Comfort on Urban Streets Using Multi-Source Data: A Case Study in Nanjing, China

Urban street comfort is a crucial measure of street environmental quality. However, traditional evaluations primarily focus on physical elements, often neglecting pedestrian perceptions. In this study, considering five core evaluation dimensions—safety, mobility, aesthetics, perceptibility, and convenience—an innovative quantitative evaluation model is proposed to assess pedestrian-perceived comfort on urban streets by integrating physical environmental factors and subjective experiences. This analysis comprises two steps: evaluation indicator extraction and weight application. Indicators are extracted from multi-source data (street-view images, real-time traffic data, points of interest, and pedestrian surveys) using a deep learning method. A comprehensive weighting method combining entropy weight and the analytic hierarchy process is used to determine the relative importance of each factor. This study focuses on Nanjing as a case study, and the results reveal significant variations across the five dimensions and their 11 secondary indicators. Street environment safety (0.143) is critical for street safety, while the degree of street traffic congestion (0.121) dominates street mobility. Street aesthetics is primarily influenced by building enclosure (0.105), and street convenience is strongly affected by the number of surrounding bus stops (0.260). Spatial analysis indicates higher comfort levels in urban centers due to well-developed infrastructure, whereas peripheral areas face challenges from inadequate facilities. Notably, areas around parks demonstrate elevated pedestrian-perceived comfort levels, highlighting the importance of green spaces. Overall, the proposed evaluation system provides new insights from the perspective of pedestrian experience and offers valuable guidance for urban planning and policy.

Analysis of Soil–Straw Movement Behavior in Saline–Alkali Soil Under Dual-Axis Rotary Tillage Based on EDEM

The layered soil crushing rotary tillage machine with L-shaped reclamation rotary blades and rotary-reclamation rotary blades combination was designed to deal with the problems of a low soil fragmentation rate, low straw mulching rate, and poor surface leveling after plowing in the traditional rotary tiller tillage mode in the coastal saline land of the Yellow River Delta. A dual active layered soil fragmentation tillage mode was proposed, and the key structural parameters, blade axis arrangement, and spatial layout of L-shaped reclamation rotary blades and rotary-reclamation rotary blades were determined based on the sliding cutting principle analysis. A discrete element model of soil straw tillage component aggregates suitable for coastal saline alkali land was constructed using EDEM, and the influence of L-shaped reclamation rotary blades and rotary-reclamation rotary blades on the soil tillage layer displacement performance and straw burial performance of saline alkali land was comprehensively analyzed from a microscopic perspective. Taking the rotation speed of the L-shaped reclamation rotary blades, the rotation speed of the rotary-reclamation rotary blades, and the forward speed as experimental factors, and using soil fragmentation rate and straw burial rate as evaluation indicators for experimental optimization analysis, the optimal parameters were obtained: the rotation speed of the L-shaped reclamation rotary blades was 295.04 r/min, the rotation speed of the rotary-reclamation rotary blades was 359.06 r/min, and the forward speed was 3.12 km/h. At this time, the theoretical soil fragmentation rate of saline alkali land was 94.67%, and the straw burial rate was 93.56%. Field experiments have shown that the average soil fragmentation rate of the L-shaped reclamation rotary blades and rotary-reclamation rotary blades combined layered soil crushing rotary tiller after cultivation is 94.37%, the straw burial rate is 95.68%, the surface flatness is 25.82 mm, and the stability of the tillage depth is 95.64%. The machine has shown increased performance in comparison to traditional single axis rotary tillers, meeting the needs of crop bed preparation in saline alkali land.

Spatial-temporal characteristics and influence factors of high-quality development of animal husbandry industry in China.

The animal husbandry industry stands as a pillar of the agricultural sector. According to the defining characteristics of high-quality development in animal husbandry, this paper establishes a comprehensive evaluative indicator system. This system evaluates the quality of development in the industry from 2010 to 2022, including five key dimensions: output efficiency, product safety, resource conservation, environmental friendliness, and the level of scientific and technological &management. Results indicate a positive overall trend in the high-quality development of China's animal industry throughout this period. Provinces exhibiting the highest average levels of development are, in descending order, Jiangsu, Shanghai, Anhui, Beijing, Fujian, Yunnan, Chongqing, Gansu, Guangdong, and Guangxi. Among these five dimensions, the level of environmental friendliness and the level of scientific and technological &management are better developed, while the level of resource conservation, the level of product safety, and the level of output efficiency are poorly developed. Regional differences have demonstrated a slight narrowing trend; however, the effect of intra-regional differences on the overall differences has remained relatively stable. In contrast, the effect of inter-regional differences on overall differences has gradually reduced, while the effect of hypervariable density has steadily increased, becoming the most significant factor. High-quality development in China's animal industry exhibits a strong path dependency, with advancements typically occurring incrementally between adjacent levels and an insignificant probability of leapfrogging. The level of high-quality development in a given region is significantly influenced by the development levels observed in neighbouring regions, illustrating a phenomenon akin to the adage that One who is near vermilion is stained red, one who is near ink is stained black. Factors such as urbanisation rates, levels of scientific and technological innovation, transport infrastructure, levels of agricultural financial development, and population density all contribute positively to the high-quality development of China's animal industry. At the same time, a larger share of animal husbandry in both the overall industrial sector and the agricultural industry further contributes to this high-quality development; whereas, GDP per capita and fiscal support for agriculture do not appear to have a significant effect.

Evaluating sowing uniformity in hybrid rice using image processing and the OEW-YOLOv8n network

Sowing uniformity is an important evaluation indicator of mechanical sowing quality. In order to achieve accurate evaluation of sowing uniformity in hybrid rice mechanical sowing, this study takes the seeds in a seedling tray of hybrid rice blanket-seedling nursing as the research object and proposes a method for evaluating sowing uniformity by combining image processing methods and the ODConv_C2f-ECA-WIoU-YOLOv8n (OEW-YOLOv8n) network. Firstly, image processing methods are used to segment seed image and obtain seed grids. Next, an improved model named OEW-YOLOv8n based on YOLOv8n is proposed to identify the number of seeds in a unit seed grid. The improved strategies include the following: (1) Replacing the Conv module in the Bottleneck of C2f modules with the Omni-Dimensional Dynamic Convolution (ODConv) module, where C2f modules are located at the connection between the Backbone and Neck. This improvement can enhance the feature extraction ability of the Backbone network, as the new modules can fully utilize the information of all dimensions of the convolutional kernel. (2) An Efficient Channel Attention (ECA) module is added to the Neck for improving the network’s capability to extract deep semantic feature information of the detection target. (3) In the Bbox module of the prediction head, the Complete Intersection over Union (CIoU) loss function is replaced by the Weighted Intersection over Union version 3 (WIoUv3) loss function to improve the convergence speed of the bounding box loss function and reduce the convergence value of the loss function. The results show that the mean average precision (mAP) of the OEW-YOLOv8n network reaches 98.6%. Compared to the original model, the mAP improved by 2.5%. Compared to the advanced object detection algorithms such as Faster-RCNN, SSD, YOLOv4, YOLOv5s YOLOv7-tiny, and YOLOv10s, the mAP of the new network increased by 5.2%, 7.8%, 4.9%, 2.8% 2.9%, and 3.3%, respectively. Finally, the actual evaluation experiment showed that the test error is from −2.43% to 2.92%, indicating that the improved network demonstrates excellent estimation accuracy. The research results can provide support for the mechanized sowing quality detection of hybrid rice and the intelligent research of rice seeder.

A skeleton extraction method for large-scale spatial interaction networks considering spatial distribution characteristics

Constructing spatial interaction (SI) networks from massive geographic flow data is an important method for understanding the correlation patterns and trends among regions. However, large-scale SI networks usually cause complex edge interleaving and a sharp increase in noise information. A network skeleton can represent the key structure of the corresponding complex network with generalized network data. However, the existing extraction methods only consider the topological information of networks and ignore spatial information, which may cause difficulty maintaining the spatial distribution characteristics and the exclusion of key spatial information. To address the issue, we have developed a skeleton extraction method for large-scale SI networks. First, the network nodes are divided into different clusters via adaptive spatial clustering. Second, an entropy weight method is used to define a comprehensive evaluation indicator of the network node importance, and the nodes in each cluster are sorted and selected according to the comprehensive evaluation indicator. Finally, the skeleton structure of the SI network is reconstructed according to the selected nodes and their adjacent edges. Compared with the existing methods for extracting network skeletons, the proposed method can maintain the spatial distribution characteristics of SI networks while preserving key topological features.

Development of E-Books Based on 4C Skills Through a Differentiation Approach to Science Learning

E-books are essential in developing 4C skills and differentiated learning because they offer accessibility and flexibility that support students' diverse learning styles. In addition, they allow customization of teaching materials according to students' needs, which increases motivation and learning independence. This research aims to develop an e-book based on 4C skills through a differentiated approach to valid, practical science learning. This study falls within the development research category that uses the ADDIE model. With an average validation score of 3.73, this e-book falls into the “very valid” category. In practical terms, this media is easy for teachers and students to use, fits the learning plan, and shows a learning implementation rate of 90%. Student responses were very good, with an average of 89.79% for four evaluation indicators, showing great benefits and a high level of satisfaction in the learning process. Overall, the e-book based on 4C developed through a differentiated approach to science learning can be categorized as valid and practical because it can increase student involvement in learning. In addition, interactive features in e-books support communication and collaboration between students, allowing them to share ideas and opinions. E-books also enable teachers to adapt material to individual needs so each student can learn at the pace and style they desire.

Current efforts in regional climate planning: A dataset from Italian NUTS2 regions.

This data article provides a comprehensive description of climate change mitigation and adaptation policies implemented by 21 Italian regions (NUTS2 level) as of January 2024. It was developed as part a wider research work published by the authors [2]. The dataset collects information on the efforts the regions are making to tackle the climate crisis. In particular, it contains a collection of regional climate plans (RCPs) and a catalogue of their contents analysed with regard to objectives, planned actions and monitoring and evaluation indicators. To complete the regional framework, the dataset also provides an overview of the socio-economic data for the Italian regions, derived from EUROSTAT (as of 2023), and the climate indicators from the Italian CIRO (Climate Indicators for Italian Regions) database, updated to 2021. Regional sustainable development strategies were also examined for consistency with climate planning and climate emergency declarations. Moreover, specific data are presented on the regions' participation in transnational networks and initiatives, as well as references on climate legislation currently in force (January 2024).

Modeling the spatiotemporal distribution, bioaccumulation, and ecological risk assessment of microplastics in aquatic ecosystems: A review.

Microplastic (MP) pollution poses a significant threat to aquatic ecosystems. Numerical modeling has emerged as an effective tool for predicting the distribution, accumulation, and risk assessment of MPs in aquatic ecosystems. However, published work has not systematically assessed the strengths and weaknesses of various modeling approaches. Therefore, we conducted a thorough review of the main modeling approaches for MPs over the past six years. We classified the approaches into three categories as: spatial and temporal distribution, bioaccumulation, and systematic ecological risk assessment. The review analyzed application scenarios, modeling methods, and the advantages and disadvantages of models. The results indicate that the accurate simulation of MPs spatial and temporal distribution requires reasonable parameterization and comprehensive transport considerations. Meanwhile, it is important to focus on coupling process models with other types of models. To enhance risk assessment models, expanding the relevant evaluation indicators is essential.

Study on the Effect of Polishing Pad on Catalytic Composite Abrasive Clusters Friction Chemical Mechanical Polishing Single Crystal SiC Substrate

Aiming at the difficulties of low efficiency and high cost during the ultra-precision machining of monocrystalline silicon carbide (SiC) substrates, a new type of UV-cured polishing pad (UV-CPD) for friction chemical mechanical polishing (TCMP) of SiC is proposed. Four different types of modified resin blends were prepared, and four types of UV-CPD were produced by light curing technology. Hardness, elastic modulus, and coefficient of friction were used as evaluation indicators to compare the mechanical properties of UV-CPD with commercial polyurethane polishing pads (CPPD). TCMP experiments were conducted on SiC substrates using laboratory-made catalytic composite abrasive clusters to compare the processing effects of UV-CPD and CPPD-polished SiC substrates as far as material removal rate (MRR) and surface roughness. Scanning electron microscopy and white light interferometer were used to test and characterize the materials for wear mechanisms. Experimental results indicated that the MRR of 3#UV-CPD was the highest, with a 46.856% increase compared to CPPD, reaching 333.119 nm min−1. After 1#UV-CPD polishing, the surface roughness of SiC was the lowest, reduced by 15% compared to CPPD, at 50.599 nm. UV-CPD can realize ultra-precision machining of SiC. This study provides a reference for the selection of soft polishing pads and the realization of ultra-precision machining of SiC.

Table Tennis Elective Course Evaluation Indicators System and Standard Formulation

Table tennis has been incorporated into physical education courses in most colleges and universities in China; establishing evaluation standards in the reform of public physical education elective courses is an effective measure. Taking the establishment of evaluation standards for elective courses of table tennis as an example, the standards are as follows: (i) In the evaluation indicators system of table tennis elective course, the first level indicators include general physical fitness and table tennis skills. The second-level indicators include sit-ups for girls and push-ups for boys, and forehand and backhand serve, forehand stroke, and backhand stroke. (ii) Use the deviation method to develop five-level evaluation criteria to evaluate the eight third-level norms, namely, excellent, good, medium, lower, and poor. Establishing evaluation standards for table tennis elective courses significantly promotes students’ physical literacy by systematically enhancing their physical fitness, technical skills, and confidence in movement through a structured, multi-level assessment framework.

Monitoring and evaluation of ecological restoration in open-pit coal mine using remote sensing data based on a OM-RSEI model

ABSTRACT Open-pit coal mining poses a severe threat to regional ecological security. Rapid and accurate monitoring of ecological quality changes is crucial for regional ecological restoration. In this study, taking the Wujiata open-pit coal mine as an example, the Red-Edge Normalized Difference Vegetation Index (RENDVI), Salinity Index (SI-T), WETness index (WET), Normalized Differential Built Soil Index (NDBSI), Land Surface Temperature (LST), and Desertification Index (DI) were used to construct the Open-pit Mine Remote Sensing Ecological Index (OM-RSEI) through Principal Component Analysis (PCA). The ecological quality and restoration conditions of typical mining areas in arid and semi-arid regions were monitored and evaluated. The results shown that: (1) The contribution rates and eigenvalues of OM-RSEI were higher than those of conventional RSEI, OM-RSEI was more applicable in open-pit mining areas. (2) From 2018 to 2023, the OM-RSEI of the Wujiata open-pit coal mine showed a ‘V’ shaped fluctuation that was damaged and then gradually recovered. (3) The degraded area of Wujiata open-pit coal mine and its 5 km buffer zone accounted for 78.02%, and the improved area accounted for 19.16%. (4) The average Moran’s I index of OM-RSEI in the study area was 0.8189, and the high–high clustering corresponded to the ‘good’ and ‘excellent’ distributions, while the low–low clustering corresponded to the ‘poor’ and ‘less-poor’ distributions. The OM-RSEI provided a new indicator for monitoring and evaluation of ecological restoration in open-pit coal mines, which can provide theoretical support for ecological restoration in open-pit coal mining areas.

P-1093. In Vitro Activity of Eravacycline against Carbapenem-Resistant Acinetobacter baumannii as Evaluated by Broth Microdilution, MIC Test Strip and Disc Diffusion

Abstract Background Eravacycline is a new type of fully synthetic fluorocycline antibiotic. The Chinese Committee on Antimicrobial Susceptibility Testing (ChinaCAST) published the clinical breakpoints of eravacycline, including MIC breakpoints and their inhibition zone diameter correlates. MIC test strip (MTS) is a gradient diffusion method that represents a simple alternative to the broth microdilution (BMD) method for performing antimicrobial susceptibility testing (AST). The aim of this study was to compare the susceptible rate of carbapenem-resistant Acinetobacter baumannii (CRAB) to eravacycline by three different testing methods. Methods 587 strains of CRAB were collected from the Huashan Hospital affiliated to Fudan University from 2019 to 2023. According to the antimicrobial susceptibility test recommended by the American Society for Clinical and Laboratory Standards 2023, the activity of eravacycline was determined. In this study, the BMD was used as the reference standard, and the clinical breakpoints standard published by ChinaCAST ( Acinetobacter baumannii susceptible MIC, ≤ 1 μg / mL or inhibition zone diameter , ≥ 15 mm ) was used to detect the susceptible rate of eravacycline to CRAB. Results The MIC50/90s were as follows: BMD, 0.5/1 mg/L; MTS, 0.38/0.75 mg/L. Based on the BMD method, the susceptible rate of CRAB to eravacycline was 98.13% (576/587) according to the ChinaCAST breakpoints, while 97.96% (575/587) was observed in MTS method. The results of DD method showed that the sensitivity rate was 97.61% (573/587). Compared with the results of BMD, the essential agreement (EA) rate of MTS was 94.55%. The categorical agreement (CA) rates of MTS and DD were 99.83% and 99.49%, respectively. The total major error (ME) rate and total very major error (VME) rate of MTS were 0.17% and 0%, respectively. The total ME rate and total VME rate of DD were 0.51% and 0%, respectively. Conclusion The susceptible rate of eravacycline to CRAB is high. CA, ME or VME all met the methodological evaluation indicators. The results of the sensitivity of CRAB to eravacycline determined by MTS and DD methods were similar, and the consistency with the BMD method was good. Both of them can be used as reliable AST methods for the determination of eravacycline antibacterial activity in clinical microbiology laboratories. Disclosures All Authors: No reported disclosures

Driver muscle fatigue analysis based on monorail crane operating environment biomechanical coupling model and surface electromyography signal

To quantitatively analyze and evaluate the driving fatigue of monorail crane drivers, this research established a biomechanical coupling model of the cab-driver operation environment within the Anybody. Muscle activation and muscle force were utilized as evaluation indicators to analyze the driving fatigue characteristics of monorail crane drivers. The research revealed that during the driving process, the biceps brachii displays the most pronounced variation for muscle activation and muscle force. In contrast, the trapezius and latissimus dorsi show less force and activation, with smoother curve changes. The extensor digitorum significantly exerts force during driving times of 1∼2, 12∼15.8, and 27∼30 s, with minimal activity otherwise. The rectus femoris, gastrocnemius, and soleus exhibit a cyclical pattern of increasing and then decreasing muscle force and activation. Peak durations for these muscles are 3∼21 and 27∼39 s, while the biceps femoris has the lowest muscle force and activation with minimal variation. A comprehensive analysis indicated that the overall fatigue of the lower limbs showed a continuous increase, with the fatigue being greater for lower limbs than upper limbs. Subsequently, surface electromyography experiment was conducted to validate the model by testing muscle electrical signal during maximum voluntary contraction (MVC). The results demonstrated that the relative error between the model and the experimental data was less than 15%, and the correlation coefficients were all greater than 0.966 ( p < 0.05), indicating a strong consistency between the model and the experimental data. Finally, EMG was employed to calculate and analyze the changes in muscle activity during the driving process. The findings from this research can serve as a theoretical foundation and provide data references for the optimization design of monorail crane.