Rapid screening of inorganic arsenic(iAs)in groundwater used for drinking by hundreds of millions of mostly rural residents worldwide is crucial for health protection.Most commercial field test kits are based on the G...Rapid screening of inorganic arsenic(iAs)in groundwater used for drinking by hundreds of millions of mostly rural residents worldwide is crucial for health protection.Most commercial field test kits are based on the Gutzeit reaction that uses mercury-based reagents for color development,an environmental concern that increasingly limits its utilization.This study further improves the Molybdenum Blue(MB)colorimetric method to allow for faster screening with more stable reagents.More importantly,a portable three-channel colorimeter is developed for screening iAs relative to the WHO drinking water guideline value(10μg/L).Adding the reducing reagents in sequence not only prolongs the storage time to>7 days,but also accelerates the color development time to 6 min in conjunction with lowering the H_(2)SO_(4) concentration in chromogenic reagents.The optimal pH ranges from 1.2 to 1.3 and is achieved by acidifying groundwater to 1%(V/V)HCl.With detection limits of 3.7μg/L for inorganic arsenate(iAs(V))and 3.8μg/L for inorganic arsenite(iAs(Ⅲ)),testing groundwater with-10μg/L of As has a precision<20%.The method works well for a range of phosphate concentrations of 48-950μg/L(0.5-10μmol/L).Concentrations of total_iAs(6-300μg/L),iAs(V)(6-230μg/L)and iAs(Ⅲ)(0-170μg/L)for 14 groundwater samples from Yinchuan Plain,Pearl River Delta,and Jianghan Plain,are in excellent agreements(linear regression slope:0.969-1.029)with the benchmark methods.The improved chemistry here lays the foundation for the MB colorimetric method to become a commercially viable screening tool,with further engineering and design improvement of the colorimeter.展开更多
The Stirling engine,as a closed-cycle power machine,exhibits excellent emission characteristics and broad energy adaptability.Second-order analysis methods are extensively used during the foundational design and therm...The Stirling engine,as a closed-cycle power machine,exhibits excellent emission characteristics and broad energy adaptability.Second-order analysis methods are extensively used during the foundational design and thermodynamic examination of Stirling engines,owing to their commendable model precision and remarkable efficiency.To scrutinize the effect of Stirling engine design parameters on the cyclical work output and efficiency,this study formulates a series of differential equations for the Stirling cycle by employing second-order analysis methods,subsequently augmenting the predictive accuracy by integrating considerations of loss mechanisms.In addition,an iterative method for the convergence of the average pressure was introduced.The predictive capability of the established model was validated using GPU-3 and RE-1000 experimental data.According to the model,parameters such as the operational fluid,porosity of the regenerator,and diameter of the wire mesh and their influence on the resulting work output and cyclic efficiency of the Stirling engine were analyzed,thereby facilitating a broader understanding of the engine's functional characteristics.These findings suggest that hydrogen,owing to its lower dynamic viscosity coefficient,can provide superior output power.The loss due to flow resistance tends to increase with the rotational speed.Additionally,under conditions of elevated rotational speed,the loss from flow resistance declines in cases of increased porosity,and the enhancement of the porosity to diminish flow resistance losses can boost both the output work and the cyclic efficiency of the engine.As the porosity increased further,the hydraulic diameter and dead volume in the regenerator continued to expand,causing the pressure drop within the engine to become the dominant factor in the gradual reduction of output power.Furthermore,extending the length of the regenerator results in a decrease in the output work,although the thermal cycle efficiency initially increases before eventually decreasing.Based on these insights,this study pursues the optimal designs for Stirling engines.展开更多
In order to accurately forecast the main engine fuel consumption and reduce the Energy Efficiency Operational Indicator(EEOI)of merchant ships in polar ice areas,the energy transfer relationship between ship-machine-p...In order to accurately forecast the main engine fuel consumption and reduce the Energy Efficiency Operational Indicator(EEOI)of merchant ships in polar ice areas,the energy transfer relationship between ship-machine-propeller is studied by analyzing the complex force situation during ship navigation and building a MATLAB/Simulink simulation platform based on multi-environmental resistance,propeller efficiency,main engine power,fuel consumption,fuel consumption rate and EEOI calculation module.Considering the environmental factors of wind,wave and ice,the route is divided into sections,the calculation of main engine power,main engine fuel consumption and EEOI for each section is completed,and the speed design is optimized based on the simulation model for each section.Under the requirements of the voyage plan,the optimization results show that the energy efficiency operation index of the whole route is reduced by 3.114%and the fuel consumption is reduced by 9.17 t.展开更多
Acrylamide(AA)is a neurotoxin and carcinogen that formed during the thermal food processing.Conventional quantification techniques are difficult to realize on-site detection of AA.Herein,a flower-like bimetallic FeCu ...Acrylamide(AA)is a neurotoxin and carcinogen that formed during the thermal food processing.Conventional quantification techniques are difficult to realize on-site detection of AA.Herein,a flower-like bimetallic FeCu nanozyme(FeCuzyme)sensor and portable platform were developed for naked-eye and on-site detection of AA.The FeCuzyme was successfully prepared and exhibited flower-like structure with 3D catalytic centers.Fe/Cu atoms were considered as active center and ligand frameworks were used as cofactor,resulting in collaborative substrate-binding features and remarkably peroxidase-like activity.During the catalytic process,the 3,3′,5,5′-tetrame-thylbenzidine(TMB)oxidation can be quenched by glutathione(GSH),and then restored after thiolene Michael addition reaction between GSH and AA.Given the“on–off–on”effect for TMB oxidation and high PODlike activity,FeCuzyme sensor exhibited a wide linear relationship from 0.50 to 18.00μM(R^(2)=0.9987)and high sensitivity(LOD=0.2360μM)with high stability.The practical application of FeCuzyme sensor was successfully validated by HPLC method.Furthermore,a FeCuzyme portable platform was designed with smartphone/laptop,and which can be used for naked-eye and on-site quantitative determination of AA in real food samples.This research provides a way for rational design of a novel nanozyme-based sensing platform for AA detection.展开更多
One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are ...One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are important parameters for measuring ground motion intensity and assessing earthquake damage.Due to the limited available information in EEW,CAV,I_(A),and SI cannot be accurately predicted using traditional EEW methods.In this paper,we propose an end-to-end deep learning-based Ground motion Intensity prediction Network(ENGINet)for on-site EEW.The aim of the ENGINet is to predict CAV,I_(A),and SI rapidly and reliably.ENGINet is based on a convolutional neural network and recurrent neural network.The inputs of the network are three-component acceleration records,three-component velocity records,and three-component displacement records obtained by a single station.The results from the test dataset show that at 3 s after the P-wave arrival,compared with the baseline models and other traditional methods,ENGINet has better performance in predicting CAV,I_(A),and SI.Our results indicate that ENGINet can quickly and accurately predict CAV,I_(A),and SI to some extent and has good potential in EEW efforts.展开更多
To accomplish on-site separation, preconcentration and cold storage of highly volatile organic compounds(VOCs) from water samples as well as their rapid transportation to laboratory, a high-throughput miniaturized pur...To accomplish on-site separation, preconcentration and cold storage of highly volatile organic compounds(VOCs) from water samples as well as their rapid transportation to laboratory, a high-throughput miniaturized purge-and-trap(μP&T) device integrating semiconductor refrigeration storage was developed in this work. Water samples were poured into the purge vessels and purged with purified air generated by an air pump. The VOCs in water samples were then separated and preconcentrated with sorbent tubes. After their complete separation and preconcentration, the tubes were subsequently preserved in the semiconductor refrigeration unit of the μP&T device. Notably, the high integration, small size, light weight, and low power consumption of the device makes it easy to be hand-carried to the field and transport by drone from remote locations, significantly enhancing the flexibility of field sampling. The performances of the device were evaluated by comparing analytical figures of merit for the detection of four cyclic volatile methylsiloxanes(cVMSs) in water. Compared to conventional collection and preservation methods, our proposed device preserved the VOCs more consistently in the sorbent tubes, with less than 5% loss of all analytes, and maintained stability for at least 20 days at 4℃. As a proof-of-concept,10 municipal wastewater samples were pretreated using this device with recoveries ranging from 82.5% to 99.9% for the target VOCs.展开更多
The integration of Global Navigation Satellite System(GNSS)technology into railway train control systems is a crucial step toward achieving the vision of a digital railway.Traditional train control systems undergo ext...The integration of Global Navigation Satellite System(GNSS)technology into railway train control systems is a crucial step toward achieving the vision of a digital railway.Traditional train control systems undergo extensive in-house tests and prolonged field tests for certification and approval before operational deployment,leading to high costs,delays,and operational disruptions.This paper introduces a GNSS-based train control localization framework which eliminates the need for on-site testing by leveraging train movement dynamics and 3D environment modeling to create a zero on-site testing platform.The proposed framework simulates train movement and the surrounding 3D environment using collected railway line location data and environmental attributes to generate realistic multipath signals and obscuration effects.This approach enables comprehensive laboratory-based case studies for train localization,reducing the huge amount test of needed for physical field trials.The framework is established in house,using the data collected at the Test Base of China Academy of Railway Sciences(Circular Railway).Results from the open area and cutting environment tests demonstrate high localization accuracy repeatability within the simulated environment,validating the feasibility and effectiveness of zero on-site testing for GNSS-based train control systems.This research highlights the potential of GNSS simulation platforms in enhancing cost efficiency,operational safety,and accuracy for future digital railways.展开更多
From the perspective of facilitating the design of fluidized hydrogen reduction reactors for iron ore powder and maintaining stable operation,the operational conditions and bubble behavior in stable state fluidization...From the perspective of facilitating the design of fluidized hydrogen reduction reactors for iron ore powder and maintaining stable operation,the operational conditions and bubble behavior in stable state fluidization of multi-particle size systems were investigated through cold-state experiments.To facilitate the identification of bubble behavior,a two-dimensional bubbling bed cold-state experiment was carried out using iron ore powder with a narrow particle size distribution and glass beads.Initially,the multi-stage fluidization characteristics of iron ore powder were examined.Then,using Geldart B-type glass beads to simulate a multi-particle size composition system,the particle size range and superficial gas velocity range for stable operation of the multi-particle composition system were explored.When the mass percentage of 150-μm glass beads was 15%,the stable fluidization operational gas velocity range was found to be(1.05-1.21)umf,where umf is the minimum fluidization velocity;when the content was 20%,the stable fluidized superficial gas velocity range was(1.09-1.26)umf.Under stable fluidization operating conditions,the dynamic behavior of bubbles(average equivalent diameter,rising velocity,and lateral migration velocity)was studied,and the quantitative relationship between the average equivalent diameter of bubbles and bed height in multi-particle size systems under stable fluidization conditions was also corrected.Additionally,the correlation between bubble rising velocity and bubble average equivalent diameter was established.展开更多
Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational s...Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational scenarios,considering the large amount of historical operational snapshot data.Specifically,DTSAs analyse the intrinsic mechanisms of different scheduling operational scenario switching to mathematically represent typical operational scenarios.A Gramian angular summation field-based operational scenario image encoder was designed to convert operational scenario sequences into highdimensional spaces.This enables DTSAs to fully capture the spatiotemporal characteristics of new power systems using deep feature iterative aggregation models.The encoder also facilitates the generation of typical operational scenarios that conform to historical data distributions while ensuring the integrity of grid operational snapshots.Case studies demonstrate that the proposed method extracted new fine-grained power system dispatch schemes and outperformed the latest high-dimensional feature-screening methods.In addition,experiments with different new energy access ratios were conducted to verify the robustness of the proposed method.DTSAs enable dispatchers to master the operation experience of the power system in advance,and actively respond to the dynamic changes of the operation scenarios under the high access rate of new energy.展开更多
Objective:To explore the application effect of the path for improving humanistic literacy of operating room nursing students based on the ORTCC model,in order to make up for the deficiency of systematic humanistic edu...Objective:To explore the application effect of the path for improving humanistic literacy of operating room nursing students based on the ORTCC model,in order to make up for the deficiency of systematic humanistic education in the traditional teaching model.Methods:120 nursing students who practiced in the operating room from June 2023 to June 2024 were randomly divided into the experimental group and the control group,with 60 students in each group.The control group received routine teaching,while the experimental group applied the ORTCC model on the basis of routine and intervened through setting humanistic literacy goals,formulating behavioral norms,conducting diversified training,implementing two-way assessment,and creating departmental culture.The effect of the intervention was evaluated using the Nurse Humanistic Quality Scale,the Clinical Communication Ability Assessment Scale for Operating Room Nursing Students,and a self-made nursing satisfaction questionnaire.Results:After the intervention,the total score of humanistic literacy in the experimental group(4 weeks of intervention:161.43±10.06 points,12 weeks of intervention:165.71±9.45 points)was significantly higher than that in the control group(139.38±10.95 points,143.31±10.52 points)(all p<0.001);The total score of clinical communication ability in the experimental group(109.69±8.05 points for 4 weeks of intervention,116.90±7.21 points for 12 weeks of intervention)was also significantly better than that in the control group(99.14±9.23 points,103.03±8.78 points)(all p<0.001);The total score of patient care satisfaction in the experimental group(94.2±4.3)was significantly higher than that in the control group(82.6±5.7)(p<0.001).Conclusion:The ORTCC model can systematically enhance the humanistic literacy,clinical communication skills and patient satisfaction of operating room nursing students,providing an effective approach for optimizing clinical teaching in the operating room.展开更多
In recent years,research on nursing interruptions has been conducted at various levels in emergency departments,intensive care units,hemodialysis centers,operating rooms,and sterilization and supply centers.Nursing in...In recent years,research on nursing interruptions has been conducted at various levels in emergency departments,intensive care units,hemodialysis centers,operating rooms,and sterilization and supply centers.Nursing interruptions are closely related to adverse nursing events,and interruptions in operating room nursing can significantly impact the success of a patient’s surgery.However,there is a lack of in-depth theoretical research on safety risk assessment and response decision-making by operating room nurses when faced with nursing interruptions.This article reviews the concept,current status,and impact of nursing interruptions in the operating room,analyzes the cognitive level,coping strategies,and negative emotions of operating room nurses,and elaborates on management strategies to provide references for research and management of nursing interruptions in the operating room.展开更多
Safe and just operating spaces(SJOS)are influenced by complex cross-scale interactions and cascading effects spanning global,regional,and local landscape scales.However,existing SJOS research has often focused on sing...Safe and just operating spaces(SJOS)are influenced by complex cross-scale interactions and cascading effects spanning global,regional,and local landscape scales.However,existing SJOS research has often focused on single-scale assessments,overlooking the impacts of multiscale interactions and within-region heterogeneity on urban SJOS.To address this gap,we developed a cross-scale framework for assessing urban SJOS,explicitly incorporating top-down influences from upper-level constraints and bottom-up effects from lower-level heterogeneity.This approach was applied to China's five major metropolises to examine the states and cross-scale dynamics influencing urban SJOS between 1990 and 2020.Our findings reveal that the SJOS of China's metropolises were primarily influenced by factors at national and local landscape scales,with weaker influences from the global and continental scales.A persistent trade-off between social justice and environmental safety was identified across spatiotemporal scales.For instance,Chongqing in southwestern China lagged behind the eastern four metropolises in social performance but exhibited stronger environmental safety due to its extensive natural landscapes,which mitigated the anthropogenic impacts of urban centers.Regional issues,such as the overshoot of PM_(2.5)and ecological footprints(EF),were primarily driven by the bottom-up accumulation of localized pressures,while the overshoot of CO_(2)was attributed to national policy constraints and the universal exceedance of safe thresholds across scales.Addressing urban sustainability requires avoiding adverse cascading effects from other levels by emphasizing landscape heterogeneity within metropolises and fostering coordinated collaboration across scales,particularly at the regional landscape and national levels.展开更多
Objective:To explore the application effectiveness of the“Six-Step”Scenario-Based Teaching Method in operating room nursing education.Methods:Seventy nursing students undergoing clinical training in the operating ro...Objective:To explore the application effectiveness of the“Six-Step”Scenario-Based Teaching Method in operating room nursing education.Methods:Seventy nursing students undergoing clinical training in the operating room of a certain hospital from January 2024 to June 2025 were selected.They were randomly divided into an observation group(n=35)and a control group(n=35)using a random number table.The control group received traditional“mentor-apprentice”on-the-job training,while the observation group underwent the“six-step”scenario-based teaching method.The two groups were compared on final assessment scores,comprehensive competency,surgical nursing emergency response ability,and teaching satisfaction indicators.Results:The observation group achieved significantly higher final assessment scores(85.54±5.05)than the control group(78.63±4.75);After instruction,the observation group scored significantly higher than the control group in:mastery of basic duties and procedures(4.22±0.30 vs.3.98±0.30),understanding of surgical nursing essentials(4.39±0.19 vs.3.98±0.30),proficiency in surgical assistance(4.11±0.33 vs.3.98±0.30),aseptic awareness(4.32±0.24 vs.3.98±0.30),risk awareness(4.22±0.17 vs.3.98±0.30),and occupational safety awareness(4.01±0.23 vs.3.98±0.30).(4.01±0.23),which were significantly higher than the control group’s scores(3.36±0.28),(3.14±0.27),(3.29±0.24),(3.53±0.36),(3.17±0.25),and(3.51±0.18),respectively.Students in the observation group scored significantly higher than the control group in emergency hands-on skills(24.53±1.85 points),surgical coordination skills(27.65±1.87 points),emergency coordination skills(25.34±1.83 points),and patient condition observation skills(24.34±1.79 points)were significantly higher than those of the control group(20.78±1.74 points,26.31±1.95 points,22.92±1.69 points,and 21.58±1.77 points,respectively).The satisfaction rate with operating room nursing education among students in the observation group(97.00%)was significantly higher than that in the control group(77.00%).All differences were statistically significant(p<0.05).Conclusion:The“Six-Step”Scenario-Based Teaching Method effectively enhances operating room students’mastery of theoretical knowledge,practical skills,and core comprehensive abilities,while significantly improving their teaching satisfaction.It warrants promotion and application in operating room nursing education.展开更多
Effective fault identification is crucial for bearings, which are critical components of mechanical systems and play a pivotal role in ensuring overall safety and operational efficiency. Bearings operate under variabl...Effective fault identification is crucial for bearings, which are critical components of mechanical systems and play a pivotal role in ensuring overall safety and operational efficiency. Bearings operate under variable service conditions, and their diagnostic environments are complex and dynamic. In the process of bearing diagnosis, fault datasets are relatively scarce compared with datasets representing normal operating conditions. These challenges frequently cause the practicality of fault detection to decline, the extraction of fault features to be incomplete, and the diagnostic accuracy of many existing models to decrease. In this work, a transfer-learning framework, designated DSCNN-HA-TL, is introduced to address the enduring challenge of cross-condition diagnosis in rolling-bearing fault detection. The framework integrates a window global mixed attention mechanism with a deep separable convolutional network, thereby enabling adaptation to fault detection tasks under diverse operating conditions. First, a Convolutional Neural Network (CNN) is employed as the foundational architecture, where the original convolutional layers are enhanced through the incorporation of depthwise separable convolutions, resulting in a Depthwise Separable Convolutional Neural Network (DSCNN) architecture. Subsequently, the extraction of fault characteristics is further refined through a dual-branch network that integrates hybrid attention mechanisms, specifically windowed and global attention mechanisms. This approach enables the acquisition of multi-level feature fusion information, thereby enhancing the accuracy of fault classification. The integration of these features not only optimizes the characteristic extraction process but also yields improvements in accuracy, representational capacity, and robustness in fault feature recognition. In conclusion, the proposed method achieved average precisions of 99.93% and 99.55% in transfer learning tasks, as demonstrated by the experimental results obtained from the CWRU public dataset and the bearing fault detection platform dataset. The experimental findings further provided a detailed comparison between the diagnostic models before and after the enhancement, thereby substantiating the pronounced advantages of the DSCNN-HA-TL approach in accurately identifying faults in critical mechanical components under diverse operating conditions.展开更多
This work proposes an optimization method for gas storage operation parameters under multi-factor coupled constraints to improve the peak-shaving capacity of gas storage reservoirs while ensuring operational safety.Pr...This work proposes an optimization method for gas storage operation parameters under multi-factor coupled constraints to improve the peak-shaving capacity of gas storage reservoirs while ensuring operational safety.Previous research primarily focused on integrating reservoir,wellbore,and surface facility constraints,often resulting in broad constraint ranges and slow model convergence.To solve this problem,the present study introduces additional constraints on maximum withdrawal rates by combining binomial deliverability equations with material balance equations for closed gas reservoirs,while considering extreme peak-shaving demands.This approach effectively narrows the constraint range.Subsequently,a collaborative optimization model with maximum gas production as the objective function is established,and the model employs a joint solution strategy combining genetic algorithms and numerical simulation techniques.Finally,this methodology was applied to optimize operational parameters for Gas Storage T.The results demonstrate:(1)The convergence of the model was achieved after 6 iterations,which significantly improved the convergence speed of the model;(2)The maximum working gas volume reached 11.605×10^(8) m^(3),which increased by 13.78%compared with the traditional optimization method;(3)This method greatly improves the operation safety and the ultimate peak load balancing capability.The research provides important technical support for the intelligent decision of injection and production parameters of gas storage and improving peak load balancing ability.展开更多
The Healthcare Failure Mode and Effect Analysis(HFMEA)model,as a proactive risk assessment tool,systematically identifies potential infection risk points during surgical procedures and evaluates the failure modes and ...The Healthcare Failure Mode and Effect Analysis(HFMEA)model,as a proactive risk assessment tool,systematically identifies potential infection risk points during surgical procedures and evaluates the failure modes and their effects that may result from these risks.Evidence-based medicine,on the other hand,emphasizes making medical decisions based on the best available evidence.Combining these two approaches can provide more scientific and effective strategies for preventing infection in operating rooms.This paper delves into the application of the HFMEA model and evidence-based medicine in the field of infection prevention in operating rooms,aiming to offer new perspectives and methods for this critical aspect of healthcare.展开更多
Objective:To explore the application of moderate and hypothermia control in patients undergoing cerebral hemangioma surgery.By adjusting the precise body temperature of the patients and controlling the changes,the int...Objective:To explore the application of moderate and hypothermia control in patients undergoing cerebral hemangioma surgery.By adjusting the precise body temperature of the patients and controlling the changes,the intraoperative and postoperative risks can be reduced,thereby better promoting postoperative recovery.Methods:Thirty patients undergoing cerebral hemangioma surgery were randomly selected as the subjects.All the patients were inpatients in the neurology department between May 2023 and May 2024.The control group received traditional routine nursing management.For the patients in the experimental group,in addition to traditional nursing management,there was also moderate and hypothermia intervention.The body temperature was monitored at three points:the tympanic membrane,esophagus,and rectum.The body temperature was effectively monitored to make it fluctuate within a relatively ideal range.The postoperative recovery was paid attention to and monitored.Key monitoring will be conducted on the intraoperative body temperature changes,hemodynamic indicators of the patients,as well as the postoperative awakening time and neurological function recovery indicators of the patients.Results:Compared with the control group,the patients in the experimental group with moderate to low body temperature had relatively gentle body temperature curves and little fluctuation in body temperature.In terms of hemodynamics,patients in the experimental group were more stable than those in the control group.Meanwhile,they recovered faster after the operation,the time required for patients to regain consciousness was shortened,and the incidence of postoperative complications was lower,especially infection,cerebral edema,and electrolyte abnormalities were more prominent.The comfort level and satisfaction of patients were relatively higher compared with those in the control group.Therefore,it can play a very good promoting role for the patient in the postoperative recovery.Conclusion:The application of moderate and low body temperature in cerebral hemangioma surgery can better stabilize the patient’s condition,reduce the occurrence of complications,and is conducive to the recovery of the patient’s neurological function.This method has changed the deficiency of body temperature management in traditional nursing and created a more ideal surgical environment for patients.展开更多
This paper focuses on the key role and practical paths of operating room nurses in infection control,and studies the difficult problems in the prevention and control of surgical site infections.Analyze the infection r...This paper focuses on the key role and practical paths of operating room nurses in infection control,and studies the difficult problems in the prevention and control of surgical site infections.Analyze the infection risk links in the operating room and the core responsibilities of nurses,reveal the multiple role mechanisms of nurses in infection control,design practical strategies from dimensions such as process optimization,skill improvement,and monitoring feedback,and construct an infection control system involving all staff.Research shows that operating room nurses can effectively reduce the risk of infection,improve medical quality,provide core guarantees for patient safety,and promote the transformation of operating room infection control towards refined management through practical actions such as standardized operation execution,real-time risk monitoring,and team collaboration supervision.展开更多
In this paper,we present a necessary and sufficient condition for hyponormal block Toeplitz operators T on the vector-valued weighted Bergman space with symbolsΦ(z)=G^(*)(z)+F(z),where F(z)=∑^(N)_(i)=1 A_(i)z^(i)and...In this paper,we present a necessary and sufficient condition for hyponormal block Toeplitz operators T on the vector-valued weighted Bergman space with symbolsΦ(z)=G^(*)(z)+F(z),where F(z)=∑^(N)_(i)=1 A_(i)z^(i)and G(z)=∑^(N)_(i)=1 A_(−i)z^(i),A_(i)ae culants.展开更多
基金the National Key R&D Program of China(No.2021YFA0715900)the National Natural Science Foundation of China(No.41831279)+2 种基金the Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks(No.ZDSYS20220606100604008)the Guangdong Province Bureau of Education(No.2020KCXTD006)the Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control(No.2023B1212060002).
文摘Rapid screening of inorganic arsenic(iAs)in groundwater used for drinking by hundreds of millions of mostly rural residents worldwide is crucial for health protection.Most commercial field test kits are based on the Gutzeit reaction that uses mercury-based reagents for color development,an environmental concern that increasingly limits its utilization.This study further improves the Molybdenum Blue(MB)colorimetric method to allow for faster screening with more stable reagents.More importantly,a portable three-channel colorimeter is developed for screening iAs relative to the WHO drinking water guideline value(10μg/L).Adding the reducing reagents in sequence not only prolongs the storage time to>7 days,but also accelerates the color development time to 6 min in conjunction with lowering the H_(2)SO_(4) concentration in chromogenic reagents.The optimal pH ranges from 1.2 to 1.3 and is achieved by acidifying groundwater to 1%(V/V)HCl.With detection limits of 3.7μg/L for inorganic arsenate(iAs(V))and 3.8μg/L for inorganic arsenite(iAs(Ⅲ)),testing groundwater with-10μg/L of As has a precision<20%.The method works well for a range of phosphate concentrations of 48-950μg/L(0.5-10μmol/L).Concentrations of total_iAs(6-300μg/L),iAs(V)(6-230μg/L)and iAs(Ⅲ)(0-170μg/L)for 14 groundwater samples from Yinchuan Plain,Pearl River Delta,and Jianghan Plain,are in excellent agreements(linear regression slope:0.969-1.029)with the benchmark methods.The improved chemistry here lays the foundation for the MB colorimetric method to become a commercially viable screening tool,with further engineering and design improvement of the colorimeter.
基金supported by Sichuan Science and Technology Program(No.24NSFSC4579)National Natural Science Foundation of China(No.12305193)+2 种基金Sichuan Science and Technology Program(No.23NSFSC6149)National Natural Science Foundation of China(No.12305194)Technology on Reactor System Design Technology Laboratory Stable support Funding(No.2023_JCJQ_LB_003).
文摘The Stirling engine,as a closed-cycle power machine,exhibits excellent emission characteristics and broad energy adaptability.Second-order analysis methods are extensively used during the foundational design and thermodynamic examination of Stirling engines,owing to their commendable model precision and remarkable efficiency.To scrutinize the effect of Stirling engine design parameters on the cyclical work output and efficiency,this study formulates a series of differential equations for the Stirling cycle by employing second-order analysis methods,subsequently augmenting the predictive accuracy by integrating considerations of loss mechanisms.In addition,an iterative method for the convergence of the average pressure was introduced.The predictive capability of the established model was validated using GPU-3 and RE-1000 experimental data.According to the model,parameters such as the operational fluid,porosity of the regenerator,and diameter of the wire mesh and their influence on the resulting work output and cyclic efficiency of the Stirling engine were analyzed,thereby facilitating a broader understanding of the engine's functional characteristics.These findings suggest that hydrogen,owing to its lower dynamic viscosity coefficient,can provide superior output power.The loss due to flow resistance tends to increase with the rotational speed.Additionally,under conditions of elevated rotational speed,the loss from flow resistance declines in cases of increased porosity,and the enhancement of the porosity to diminish flow resistance losses can boost both the output work and the cyclic efficiency of the engine.As the porosity increased further,the hydraulic diameter and dead volume in the regenerator continued to expand,causing the pressure drop within the engine to become the dominant factor in the gradual reduction of output power.Furthermore,extending the length of the regenerator results in a decrease in the output work,although the thermal cycle efficiency initially increases before eventually decreasing.Based on these insights,this study pursues the optimal designs for Stirling engines.
文摘In order to accurately forecast the main engine fuel consumption and reduce the Energy Efficiency Operational Indicator(EEOI)of merchant ships in polar ice areas,the energy transfer relationship between ship-machine-propeller is studied by analyzing the complex force situation during ship navigation and building a MATLAB/Simulink simulation platform based on multi-environmental resistance,propeller efficiency,main engine power,fuel consumption,fuel consumption rate and EEOI calculation module.Considering the environmental factors of wind,wave and ice,the route is divided into sections,the calculation of main engine power,main engine fuel consumption and EEOI for each section is completed,and the speed design is optimized based on the simulation model for each section.Under the requirements of the voyage plan,the optimization results show that the energy efficiency operation index of the whole route is reduced by 3.114%and the fuel consumption is reduced by 9.17 t.
基金supported by the National Natural Science Foundation of China(32060577 and 32360619)Natural Science Foundation of Jiangxi Province(20224ACB203016 and 20212BAB203034)the Open Project of China Food Flavor and Nutrition Health Innovation Center(CFC2023B-013).
文摘Acrylamide(AA)is a neurotoxin and carcinogen that formed during the thermal food processing.Conventional quantification techniques are difficult to realize on-site detection of AA.Herein,a flower-like bimetallic FeCu nanozyme(FeCuzyme)sensor and portable platform were developed for naked-eye and on-site detection of AA.The FeCuzyme was successfully prepared and exhibited flower-like structure with 3D catalytic centers.Fe/Cu atoms were considered as active center and ligand frameworks were used as cofactor,resulting in collaborative substrate-binding features and remarkably peroxidase-like activity.During the catalytic process,the 3,3′,5,5′-tetrame-thylbenzidine(TMB)oxidation can be quenched by glutathione(GSH),and then restored after thiolene Michael addition reaction between GSH and AA.Given the“on–off–on”effect for TMB oxidation and high PODlike activity,FeCuzyme sensor exhibited a wide linear relationship from 0.50 to 18.00μM(R^(2)=0.9987)and high sensitivity(LOD=0.2360μM)with high stability.The practical application of FeCuzyme sensor was successfully validated by HPLC method.Furthermore,a FeCuzyme portable platform was designed with smartphone/laptop,and which can be used for naked-eye and on-site quantitative determination of AA in real food samples.This research provides a way for rational design of a novel nanozyme-based sensing platform for AA detection.
基金Scientific Research Fund of Institute of Engineering Mechanics,China Earthquake Administration under Grant No.2024B08。
文摘One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are important parameters for measuring ground motion intensity and assessing earthquake damage.Due to the limited available information in EEW,CAV,I_(A),and SI cannot be accurately predicted using traditional EEW methods.In this paper,we propose an end-to-end deep learning-based Ground motion Intensity prediction Network(ENGINet)for on-site EEW.The aim of the ENGINet is to predict CAV,I_(A),and SI rapidly and reliably.ENGINet is based on a convolutional neural network and recurrent neural network.The inputs of the network are three-component acceleration records,three-component velocity records,and three-component displacement records obtained by a single station.The results from the test dataset show that at 3 s after the P-wave arrival,compared with the baseline models and other traditional methods,ENGINet has better performance in predicting CAV,I_(A),and SI.Our results indicate that ENGINet can quickly and accurately predict CAV,I_(A),and SI to some extent and has good potential in EEW efforts.
基金the National Natural Science Foundation of China (No. 22306146)the PhD Scientific Research Startup Foundation of Xihua University (No. RX2200002003) for their financial support。
文摘To accomplish on-site separation, preconcentration and cold storage of highly volatile organic compounds(VOCs) from water samples as well as their rapid transportation to laboratory, a high-throughput miniaturized purge-and-trap(μP&T) device integrating semiconductor refrigeration storage was developed in this work. Water samples were poured into the purge vessels and purged with purified air generated by an air pump. The VOCs in water samples were then separated and preconcentrated with sorbent tubes. After their complete separation and preconcentration, the tubes were subsequently preserved in the semiconductor refrigeration unit of the μP&T device. Notably, the high integration, small size, light weight, and low power consumption of the device makes it easy to be hand-carried to the field and transport by drone from remote locations, significantly enhancing the flexibility of field sampling. The performances of the device were evaluated by comparing analytical figures of merit for the detection of four cyclic volatile methylsiloxanes(cVMSs) in water. Compared to conventional collection and preservation methods, our proposed device preserved the VOCs more consistently in the sorbent tubes, with less than 5% loss of all analytes, and maintained stability for at least 20 days at 4℃. As a proof-of-concept,10 municipal wastewater samples were pretreated using this device with recoveries ranging from 82.5% to 99.9% for the target VOCs.
基金supported by the National Natural Science Foundation of China(62027809,U2268206,T2222015,U2468202).
文摘The integration of Global Navigation Satellite System(GNSS)technology into railway train control systems is a crucial step toward achieving the vision of a digital railway.Traditional train control systems undergo extensive in-house tests and prolonged field tests for certification and approval before operational deployment,leading to high costs,delays,and operational disruptions.This paper introduces a GNSS-based train control localization framework which eliminates the need for on-site testing by leveraging train movement dynamics and 3D environment modeling to create a zero on-site testing platform.The proposed framework simulates train movement and the surrounding 3D environment using collected railway line location data and environmental attributes to generate realistic multipath signals and obscuration effects.This approach enables comprehensive laboratory-based case studies for train localization,reducing the huge amount test of needed for physical field trials.The framework is established in house,using the data collected at the Test Base of China Academy of Railway Sciences(Circular Railway).Results from the open area and cutting environment tests demonstrate high localization accuracy repeatability within the simulated environment,validating the feasibility and effectiveness of zero on-site testing for GNSS-based train control systems.This research highlights the potential of GNSS simulation platforms in enhancing cost efficiency,operational safety,and accuracy for future digital railways.
基金supported by the China Baowu Low Carbon Metallurgy Innovation Foundation(No.202114)National Natural Science Foundation of China(No.51874056)Sichuan Science and Technology Program(2025ZNSFSC0378).
文摘From the perspective of facilitating the design of fluidized hydrogen reduction reactors for iron ore powder and maintaining stable operation,the operational conditions and bubble behavior in stable state fluidization of multi-particle size systems were investigated through cold-state experiments.To facilitate the identification of bubble behavior,a two-dimensional bubbling bed cold-state experiment was carried out using iron ore powder with a narrow particle size distribution and glass beads.Initially,the multi-stage fluidization characteristics of iron ore powder were examined.Then,using Geldart B-type glass beads to simulate a multi-particle size composition system,the particle size range and superficial gas velocity range for stable operation of the multi-particle composition system were explored.When the mass percentage of 150-μm glass beads was 15%,the stable fluidization operational gas velocity range was found to be(1.05-1.21)umf,where umf is the minimum fluidization velocity;when the content was 20%,the stable fluidized superficial gas velocity range was(1.09-1.26)umf.Under stable fluidization operating conditions,the dynamic behavior of bubbles(average equivalent diameter,rising velocity,and lateral migration velocity)was studied,and the quantitative relationship between the average equivalent diameter of bubbles and bed height in multi-particle size systems under stable fluidization conditions was also corrected.Additionally,the correlation between bubble rising velocity and bubble average equivalent diameter was established.
基金The Key R&D Project of Jilin Province,Grant/Award Number:20230201067GX。
文摘Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational scenarios,considering the large amount of historical operational snapshot data.Specifically,DTSAs analyse the intrinsic mechanisms of different scheduling operational scenario switching to mathematically represent typical operational scenarios.A Gramian angular summation field-based operational scenario image encoder was designed to convert operational scenario sequences into highdimensional spaces.This enables DTSAs to fully capture the spatiotemporal characteristics of new power systems using deep feature iterative aggregation models.The encoder also facilitates the generation of typical operational scenarios that conform to historical data distributions while ensuring the integrity of grid operational snapshots.Case studies demonstrate that the proposed method extracted new fine-grained power system dispatch schemes and outperformed the latest high-dimensional feature-screening methods.In addition,experiments with different new energy access ratios were conducted to verify the robustness of the proposed method.DTSAs enable dispatchers to master the operation experience of the power system in advance,and actively respond to the dynamic changes of the operation scenarios under the high access rate of new energy.
文摘Objective:To explore the application effect of the path for improving humanistic literacy of operating room nursing students based on the ORTCC model,in order to make up for the deficiency of systematic humanistic education in the traditional teaching model.Methods:120 nursing students who practiced in the operating room from June 2023 to June 2024 were randomly divided into the experimental group and the control group,with 60 students in each group.The control group received routine teaching,while the experimental group applied the ORTCC model on the basis of routine and intervened through setting humanistic literacy goals,formulating behavioral norms,conducting diversified training,implementing two-way assessment,and creating departmental culture.The effect of the intervention was evaluated using the Nurse Humanistic Quality Scale,the Clinical Communication Ability Assessment Scale for Operating Room Nursing Students,and a self-made nursing satisfaction questionnaire.Results:After the intervention,the total score of humanistic literacy in the experimental group(4 weeks of intervention:161.43±10.06 points,12 weeks of intervention:165.71±9.45 points)was significantly higher than that in the control group(139.38±10.95 points,143.31±10.52 points)(all p<0.001);The total score of clinical communication ability in the experimental group(109.69±8.05 points for 4 weeks of intervention,116.90±7.21 points for 12 weeks of intervention)was also significantly better than that in the control group(99.14±9.23 points,103.03±8.78 points)(all p<0.001);The total score of patient care satisfaction in the experimental group(94.2±4.3)was significantly higher than that in the control group(82.6±5.7)(p<0.001).Conclusion:The ORTCC model can systematically enhance the humanistic literacy,clinical communication skills and patient satisfaction of operating room nursing students,providing an effective approach for optimizing clinical teaching in the operating room.
基金Analysis of Lung Compliance Measurement and its Guided Therapeutic Effects in Patients with ARDS Secondary to Severe Multiple Trauma(Project No.:XSD-2023-002)。
文摘In recent years,research on nursing interruptions has been conducted at various levels in emergency departments,intensive care units,hemodialysis centers,operating rooms,and sterilization and supply centers.Nursing interruptions are closely related to adverse nursing events,and interruptions in operating room nursing can significantly impact the success of a patient’s surgery.However,there is a lack of in-depth theoretical research on safety risk assessment and response decision-making by operating room nurses when faced with nursing interruptions.This article reviews the concept,current status,and impact of nursing interruptions in the operating room,analyzes the cognitive level,coping strategies,and negative emotions of operating room nurses,and elaborates on management strategies to provide references for research and management of nursing interruptions in the operating room.
基金supported by the National Natural Science Foundation of China(Grant No.42101296)the Natural Science Foundation of Chongqing(Grant No.CSTB2023NSCQ-MSX0041)Chongqing Municipal Training Program of Innovation and Entrepreneurship Project(Grants No.S202410635155 and X202410635116)。
文摘Safe and just operating spaces(SJOS)are influenced by complex cross-scale interactions and cascading effects spanning global,regional,and local landscape scales.However,existing SJOS research has often focused on single-scale assessments,overlooking the impacts of multiscale interactions and within-region heterogeneity on urban SJOS.To address this gap,we developed a cross-scale framework for assessing urban SJOS,explicitly incorporating top-down influences from upper-level constraints and bottom-up effects from lower-level heterogeneity.This approach was applied to China's five major metropolises to examine the states and cross-scale dynamics influencing urban SJOS between 1990 and 2020.Our findings reveal that the SJOS of China's metropolises were primarily influenced by factors at national and local landscape scales,with weaker influences from the global and continental scales.A persistent trade-off between social justice and environmental safety was identified across spatiotemporal scales.For instance,Chongqing in southwestern China lagged behind the eastern four metropolises in social performance but exhibited stronger environmental safety due to its extensive natural landscapes,which mitigated the anthropogenic impacts of urban centers.Regional issues,such as the overshoot of PM_(2.5)and ecological footprints(EF),were primarily driven by the bottom-up accumulation of localized pressures,while the overshoot of CO_(2)was attributed to national policy constraints and the universal exceedance of safe thresholds across scales.Addressing urban sustainability requires avoiding adverse cascading effects from other levels by emphasizing landscape heterogeneity within metropolises and fostering coordinated collaboration across scales,particularly at the regional landscape and national levels.
文摘Objective:To explore the application effectiveness of the“Six-Step”Scenario-Based Teaching Method in operating room nursing education.Methods:Seventy nursing students undergoing clinical training in the operating room of a certain hospital from January 2024 to June 2025 were selected.They were randomly divided into an observation group(n=35)and a control group(n=35)using a random number table.The control group received traditional“mentor-apprentice”on-the-job training,while the observation group underwent the“six-step”scenario-based teaching method.The two groups were compared on final assessment scores,comprehensive competency,surgical nursing emergency response ability,and teaching satisfaction indicators.Results:The observation group achieved significantly higher final assessment scores(85.54±5.05)than the control group(78.63±4.75);After instruction,the observation group scored significantly higher than the control group in:mastery of basic duties and procedures(4.22±0.30 vs.3.98±0.30),understanding of surgical nursing essentials(4.39±0.19 vs.3.98±0.30),proficiency in surgical assistance(4.11±0.33 vs.3.98±0.30),aseptic awareness(4.32±0.24 vs.3.98±0.30),risk awareness(4.22±0.17 vs.3.98±0.30),and occupational safety awareness(4.01±0.23 vs.3.98±0.30).(4.01±0.23),which were significantly higher than the control group’s scores(3.36±0.28),(3.14±0.27),(3.29±0.24),(3.53±0.36),(3.17±0.25),and(3.51±0.18),respectively.Students in the observation group scored significantly higher than the control group in emergency hands-on skills(24.53±1.85 points),surgical coordination skills(27.65±1.87 points),emergency coordination skills(25.34±1.83 points),and patient condition observation skills(24.34±1.79 points)were significantly higher than those of the control group(20.78±1.74 points,26.31±1.95 points,22.92±1.69 points,and 21.58±1.77 points,respectively).The satisfaction rate with operating room nursing education among students in the observation group(97.00%)was significantly higher than that in the control group(77.00%).All differences were statistically significant(p<0.05).Conclusion:The“Six-Step”Scenario-Based Teaching Method effectively enhances operating room students’mastery of theoretical knowledge,practical skills,and core comprehensive abilities,while significantly improving their teaching satisfaction.It warrants promotion and application in operating room nursing education.
基金supported by the National Natural Science Foundation of China(12272259)the Key Research and Development Fund of Universities in Hebei Province(2510800601A).
文摘Effective fault identification is crucial for bearings, which are critical components of mechanical systems and play a pivotal role in ensuring overall safety and operational efficiency. Bearings operate under variable service conditions, and their diagnostic environments are complex and dynamic. In the process of bearing diagnosis, fault datasets are relatively scarce compared with datasets representing normal operating conditions. These challenges frequently cause the practicality of fault detection to decline, the extraction of fault features to be incomplete, and the diagnostic accuracy of many existing models to decrease. In this work, a transfer-learning framework, designated DSCNN-HA-TL, is introduced to address the enduring challenge of cross-condition diagnosis in rolling-bearing fault detection. The framework integrates a window global mixed attention mechanism with a deep separable convolutional network, thereby enabling adaptation to fault detection tasks under diverse operating conditions. First, a Convolutional Neural Network (CNN) is employed as the foundational architecture, where the original convolutional layers are enhanced through the incorporation of depthwise separable convolutions, resulting in a Depthwise Separable Convolutional Neural Network (DSCNN) architecture. Subsequently, the extraction of fault characteristics is further refined through a dual-branch network that integrates hybrid attention mechanisms, specifically windowed and global attention mechanisms. This approach enables the acquisition of multi-level feature fusion information, thereby enhancing the accuracy of fault classification. The integration of these features not only optimizes the characteristic extraction process but also yields improvements in accuracy, representational capacity, and robustness in fault feature recognition. In conclusion, the proposed method achieved average precisions of 99.93% and 99.55% in transfer learning tasks, as demonstrated by the experimental results obtained from the CWRU public dataset and the bearing fault detection platform dataset. The experimental findings further provided a detailed comparison between the diagnostic models before and after the enhancement, thereby substantiating the pronounced advantages of the DSCNN-HA-TL approach in accurately identifying faults in critical mechanical components under diverse operating conditions.
基金supported by the Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN202401501,KJZD-M202401501).
文摘This work proposes an optimization method for gas storage operation parameters under multi-factor coupled constraints to improve the peak-shaving capacity of gas storage reservoirs while ensuring operational safety.Previous research primarily focused on integrating reservoir,wellbore,and surface facility constraints,often resulting in broad constraint ranges and slow model convergence.To solve this problem,the present study introduces additional constraints on maximum withdrawal rates by combining binomial deliverability equations with material balance equations for closed gas reservoirs,while considering extreme peak-shaving demands.This approach effectively narrows the constraint range.Subsequently,a collaborative optimization model with maximum gas production as the objective function is established,and the model employs a joint solution strategy combining genetic algorithms and numerical simulation techniques.Finally,this methodology was applied to optimize operational parameters for Gas Storage T.The results demonstrate:(1)The convergence of the model was achieved after 6 iterations,which significantly improved the convergence speed of the model;(2)The maximum working gas volume reached 11.605×10^(8) m^(3),which increased by 13.78%compared with the traditional optimization method;(3)This method greatly improves the operation safety and the ultimate peak load balancing capability.The research provides important technical support for the intelligent decision of injection and production parameters of gas storage and improving peak load balancing ability.
文摘The Healthcare Failure Mode and Effect Analysis(HFMEA)model,as a proactive risk assessment tool,systematically identifies potential infection risk points during surgical procedures and evaluates the failure modes and their effects that may result from these risks.Evidence-based medicine,on the other hand,emphasizes making medical decisions based on the best available evidence.Combining these two approaches can provide more scientific and effective strategies for preventing infection in operating rooms.This paper delves into the application of the HFMEA model and evidence-based medicine in the field of infection prevention in operating rooms,aiming to offer new perspectives and methods for this critical aspect of healthcare.
文摘Objective:To explore the application of moderate and hypothermia control in patients undergoing cerebral hemangioma surgery.By adjusting the precise body temperature of the patients and controlling the changes,the intraoperative and postoperative risks can be reduced,thereby better promoting postoperative recovery.Methods:Thirty patients undergoing cerebral hemangioma surgery were randomly selected as the subjects.All the patients were inpatients in the neurology department between May 2023 and May 2024.The control group received traditional routine nursing management.For the patients in the experimental group,in addition to traditional nursing management,there was also moderate and hypothermia intervention.The body temperature was monitored at three points:the tympanic membrane,esophagus,and rectum.The body temperature was effectively monitored to make it fluctuate within a relatively ideal range.The postoperative recovery was paid attention to and monitored.Key monitoring will be conducted on the intraoperative body temperature changes,hemodynamic indicators of the patients,as well as the postoperative awakening time and neurological function recovery indicators of the patients.Results:Compared with the control group,the patients in the experimental group with moderate to low body temperature had relatively gentle body temperature curves and little fluctuation in body temperature.In terms of hemodynamics,patients in the experimental group were more stable than those in the control group.Meanwhile,they recovered faster after the operation,the time required for patients to regain consciousness was shortened,and the incidence of postoperative complications was lower,especially infection,cerebral edema,and electrolyte abnormalities were more prominent.The comfort level and satisfaction of patients were relatively higher compared with those in the control group.Therefore,it can play a very good promoting role for the patient in the postoperative recovery.Conclusion:The application of moderate and low body temperature in cerebral hemangioma surgery can better stabilize the patient’s condition,reduce the occurrence of complications,and is conducive to the recovery of the patient’s neurological function.This method has changed the deficiency of body temperature management in traditional nursing and created a more ideal surgical environment for patients.
文摘This paper focuses on the key role and practical paths of operating room nurses in infection control,and studies the difficult problems in the prevention and control of surgical site infections.Analyze the infection risk links in the operating room and the core responsibilities of nurses,reveal the multiple role mechanisms of nurses in infection control,design practical strategies from dimensions such as process optimization,skill improvement,and monitoring feedback,and construct an infection control system involving all staff.Research shows that operating room nurses can effectively reduce the risk of infection,improve medical quality,provide core guarantees for patient safety,and promote the transformation of operating room infection control towards refined management through practical actions such as standardized operation execution,real-time risk monitoring,and team collaboration supervision.
文摘In this paper,we present a necessary and sufficient condition for hyponormal block Toeplitz operators T on the vector-valued weighted Bergman space with symbolsΦ(z)=G^(*)(z)+F(z),where F(z)=∑^(N)_(i)=1 A_(i)z^(i)and G(z)=∑^(N)_(i)=1 A_(−i)z^(i),A_(i)ae culants.
