This paper focuses on the procurement of construction projects in universities,conducting research on the influencing factors of procurement risks in such projects.By combining questionnaire surveys with expert interv...This paper focuses on the procurement of construction projects in universities,conducting research on the influencing factors of procurement risks in such projects.By combining questionnaire surveys with expert interviews,numerous factors affecting procurement are analyzed.Subsequently,these factors are refined and summarized to construct a procurement risk evaluation index system for construction projects,which includes three first-level indicators,such as process management risk and ethical/legal risk,and is further subdivided into 13 second-level indicators.展开更多
The centralized procurement of drugs in the medical system is a key link,which not only affects the economic effect of institutions,but also relates to the medical quality and patient safety.In the current era,central...The centralized procurement of drugs in the medical system is a key link,which not only affects the economic effect of institutions,but also relates to the medical quality and patient safety.In the current era,centralized drug procurement in hospitals can meet the needs of most patients;however,the specific steps of the work still need to be optimized.Starting from the level of hospital drug centralized procurement work,this paper discusses the policy background,analyzes the practice of drug centralized procurement in tertiary hospitals,and provides specific work management suggestions,aiming to improve work efficiency and serve as a reference for optimizing subsequent hospital drug centralized procurement work.展开更多
Objective To quantitatively analyze the policy of centralized drug procurement centralized drug procurement in order to provide reference for the subsequent policy formulation and improvement.Methods Text mining metho...Objective To quantitatively analyze the policy of centralized drug procurement centralized drug procurement in order to provide reference for the subsequent policy formulation and improvement.Methods Text mining method was used to process 15 centralized drugs procurement policies issued at the national level during 2015-2022,and a PMC index evaluation model of centralized drug procurement policies was established.Then,15 centralized drug procurement policies were quantitatively analyzed from the overall and comparative perspective through an evaluation model.Results and Conclusion The average PMC index of 15 centralized drug procurement policies was 6.95,which was acceptable on the whole.Among them,eight were excellent and seven were acceptable.As to the first-order variables,the centralized drugs procurement policy still lacks incentives and constraints.The comparative results show that there are differences in the content and structure of policies,but they are strongly related to each other.Chinese centralized drug procurement policy has been basically formed,which is closely related to medical insurance and medical policies.However,it is still necessary to pay attention to the structure of the policy to ensure the elaboration of the policy content.展开更多
In the project procurement management process of telecommunication enterprises,due to the complexity of technology,the professional procurement project manager is responsible for the whole process of professional proc...In the project procurement management process of telecommunication enterprises,due to the complexity of technology,the professional procurement project manager is responsible for the whole process of professional procurement in a one-stop way.The integration of this management process superficially improves labor productivity,but in essence lacks effective checks and balances and supervision.In order to supervise the project procurement management process and ensure the legal compliance of procurement management,this paper studies the project procurement management process of telecommunication enterprises,proposes the optimization process of project procurement management in the segmentation of purchasing manager-business manager,and constructs a matrix project procurement management model,which will contribute to the overall improvement of the telecommunication enterprises’procurement performance.展开更多
With the acceleration of the global digital wave,enterprise procurement management is facing multiple challenges such as cost pressure,supply chain collaboration demand,and insufficient information ability.Based on dy...With the acceleration of the global digital wave,enterprise procurement management is facing multiple challenges such as cost pressure,supply chain collaboration demand,and insufficient information ability.Based on dynamic capability theory,resource-based view,and value chain theory,this paper constructs a four-level research framework of“driving factors-transformation paths-strategic actions-performance evaluation”.Firstly,through literature analysis and case review,it summarizes the internal and external driving factors such as external market competition pressure,supply chain coordination demand,policy and regulatory environment,as well as enterprise information foundation,organizational culture,and talent reserve,and analyzes their mechanism of action on procurement digital transformation.Secondly,the procurement digital transformation path is divided into two types:gradual upgrading and leap-forward reconstruction,and the strategic and tactical level strategies,such as top-level design,data governance,process remodeling,supplier collaboration platform construction,and intelligent decision support,are proposed.Thirdly,the implementation guarantee mechanism was designed from the four aspects of organization management,technology platform,talent culture,and risk control.Finally,the performance evaluation index system covering cost,cycle,quality,risk,and digital maturity was constructed,and the evaluation method and continuous improvement mechanism based on balanced scorecard and ROI/TCO analysis were proposed.The results show that the systematic strategy design and multi-dimensional guarantee can effectively improve the procurement efficiency of enterprises,reduce operating costs,enhance supply chain resilience,and provide theoretical and practical guidance for enterprises to achieve sustainable competitive advantage.展开更多
Background:Atherosclerotic cardiovascular disease remains the leading cause of death worldwide.This study aims to explore the impact of national volume-based procurement(NVBP)on Chinese patent medicines and provide ev...Background:Atherosclerotic cardiovascular disease remains the leading cause of death worldwide.This study aims to explore the impact of national volume-based procurement(NVBP)on Chinese patent medicines and provide evidence for improving policies and promoting rational drug use.Methods:The study was based on data from the China National Health Insurance Agency that spanned January 2019 to December 2020.Descriptive analysis was conducted using volume and expenditure as variables.Interrupted time series analysis was applied to further analyze Chinese patent medicines.Results:The unit prices of atorvastatin and rosuvastatin decreased by 25%-96%,whereas the prices of Zhibitai and Xuezhikang fluctuated slightly.The affordability is measured as the monthly expenditure on treatment divided by the daily wage.After policy implementation,the affordability of atorvastatin and rosuvastatin improved from 0.242 to 0.014 and from 0.247 to 0.019,respectively.The defined daily doses(DDDs)for atorvastatin and rosuvastatin also increased,whereas total expenditures decreased in hospitals of all levels.Both at the national level and at all levels of hospital,the policy had no significant impact on expenditures for Zhibitai and Xuezhikang and their defined daily doses.Conclusions:The NVBP saved costs in the short term by incorporating high-quality,widely used lipid-lowering drugs.Notably,the policy impacted lipid-lowering chemical drugs,whereas Chinese patent medicines remained largely unaffected.Doctors'use of Chinese patent medicines did not decline,highlighting the clinical specificity of these medicines.展开更多
To elucidate the fracturing mechanism of deep hard rock under complex disturbance environments,this study investigates the dynamic failure behavior of pre-damaged granite subjected to multi-source dynamic disturbances...To elucidate the fracturing mechanism of deep hard rock under complex disturbance environments,this study investigates the dynamic failure behavior of pre-damaged granite subjected to multi-source dynamic disturbances.Blasting vibration monitoring was conducted in a deep-buried drill-and-blast tunnel to characterize in-situ dynamic loading conditions.Subsequently,true triaxial compression tests incorporating multi-source disturbances were performed using a self-developed wide-low-frequency true triaxial system to simulate disturbance accumulation and damage evolution in granite.The results demonstrate that combined dynamic disturbances and unloading damage significantly accelerate strength degradation and trigger shear-slip failure along preferentially oriented blast-induced fractures,with strength reductions up to 16.7%.Layered failure was observed on the free surface of pre-damaged granite under biaxial loading,indicating a disturbance-induced fracture localization mechanism.Time-stress-fracture-energy coupling fields were constructed to reveal the spatiotemporal characteristics of fracture evolution.Critical precursor frequency bands(105-150,185-225,and 300-325 kHz)were identified,which serve as diagnostic signatures of impending failure.A dynamic instability mechanism driven by multi-source disturbance superposition and pre-damage evolution was established.Furthermore,a grouting-based wave-absorption control strategy was proposed to mitigate deep dynamic disasters by attenuating disturbance amplitude and reducing excitation frequency.展开更多
Background:Acquiring relevant information about procurement targets is fundamental to procuring medical devices.Although traditional Natural Language Processing(NLP)and Machine Learning(ML)methods have improved inform...Background:Acquiring relevant information about procurement targets is fundamental to procuring medical devices.Although traditional Natural Language Processing(NLP)and Machine Learning(ML)methods have improved information retrieval efficiency to a certain extent,they exhibit significant limitations in adaptability and accuracy when dealing with procurement documents characterized by diverse formats and a high degree of unstructured content.The emergence of Large Language Models(LLMs)offers new possibilities for efficient procurement information processing and extraction.Methods:This study collected procurement transaction documents from public procurement websites,and proposed a procurement Information Extraction(IE)method based on LLMs.Unlike traditional approaches,this study systematically explores the applicability of LLMs in both structured and unstructured entities in procurement documents,addressing the challenges posed by format variability and content complexity.Furthermore,an optimized prompt framework tailored for procurement document extraction tasks is developed to enhance the accuracy and robustness of IE.The aim is to process and extract key information from medical device procurement quickly and accurately,meeting stakeholders'demands for precision and timeliness in information retrieval.Results:Experimental results demonstrate that,compared to traditional methods,the proposed approach achieves an F1 Score of 0.9698,representing a 4.85%improvement over the best baseline model.Moreover,both recall and precision rates are close to 97%,significantly outperforming other models and exhibiting exceptional overall recognition capabilities.Notably,further analysis reveals that the proposed method consistently maintains high performance across both structured and unstructured entities in procurement documents while balancing recall and precision effectively,demonstrating its adaptability in handling varying document formats.The results of ablation experiments validate the effectiveness of the proposed prompting strategy.Conclusion:Additionally,this study explores the challenges and potential improvements of the proposed method in IE tasks and provides insights into its feasibility for real-world deployment and application directions,further clarifying its adaptability and value.This method not only exhibits significant advantages in medical device procurement but also holds promise for providing new approaches to information processing and decision support in various domains.展开更多
The SiO_(2) inverse opal photonic crystals(PC)with a three-dimensional macroporous structure were fabricated by the sacrificial template method,followed by infiltration of a pyrene derivative,1-(pyren-8-yl)but-3-en-1-...The SiO_(2) inverse opal photonic crystals(PC)with a three-dimensional macroporous structure were fabricated by the sacrificial template method,followed by infiltration of a pyrene derivative,1-(pyren-8-yl)but-3-en-1-amine(PEA),to achieve a formaldehyde(FA)-sensitive and fluorescence-enhanced sensing film.Utilizing the specific Aza-Cope rearrangement reaction of allylamine of PEA and FA to generate a strong fluorescent product emitted at approximately 480 nm,we chose a PC whose blue band edge of stopband overlapped with the fluorescence emission wavelength.In virtue of the fluorescence enhancement property derived from slow photon effect of PC,FA was detected highly selectively and sensitively.The limit of detection(LoD)was calculated to be 1.38 nmol/L.Furthermore,the fast detection of FA(within 1 min)is realized due to the interconnected three-dimensional macroporous structure of the inverse opal PC and its high specific surface area.The prepared sensing film can be used for the detection of FA in air,aquatic products and living cells.The very close FA content in indoor air to the result from FA detector,the recovery rate of 101.5%for detecting FA in aquatic products and fast fluorescence imaging in 2 min for living cells demonstrate the reliability and accuracy of our method in practical applications.展开更多
Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on co...Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.展开更多
Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.P...Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.展开更多
In the heterogeneous power internet of things(IoT)environment,data signals are acquired to support different business systems to realize advanced intelligent applications,with massive,multi-source,heterogeneous and ot...In the heterogeneous power internet of things(IoT)environment,data signals are acquired to support different business systems to realize advanced intelligent applications,with massive,multi-source,heterogeneous and other characteristics.Reliable perception of information and efficient transmission of energy in multi-source heterogeneous environments are crucial issues.Compressive sensing(CS),as an effective method of signal compression and transmission,can accurately recover the original signal only by very few sampling.In this paper,we study a new method of multi-source heterogeneous data signal reconstruction of power IoT based on compressive sensing technology.Based on the traditional compressive sensing technology to directly recover multi-source heterogeneous signals,we fully use the interference subspace information to design the measurement matrix,which directly and effectively eliminates the interference while making the measurement.The measure matrix is optimized by minimizing the average cross-coherence of the matrix,and the reconstruction performance of the new method is further improved.Finally,the effectiveness of the new method with different parameter settings under different multi-source heterogeneous data signal cases is verified by using orthogonal matching pursuit(OMP)and sparsity adaptive matching pursuit(SAMP)for considering the actual environment with prior information utilization of signal sparsity and no prior information utilization of signal sparsity.展开更多
This paper deeply discusses the causes of gear howling noise,the identification and analysis of multi-source excitation,the transmission path of dynamic noise,simulation and experimental research,case analysis,optimiz...This paper deeply discusses the causes of gear howling noise,the identification and analysis of multi-source excitation,the transmission path of dynamic noise,simulation and experimental research,case analysis,optimization effect,etc.,aiming to better provide a certain guideline and reference for relevant researchers.展开更多
Objective To establish a scientific,reliable,objective,and effective clinical comprehensive evaluation system for drugs centralized bidding procurement by government,and to conduct reliability and validity test and em...Objective To establish a scientific,reliable,objective,and effective clinical comprehensive evaluation system for drugs centralized bidding procurement by government,and to conduct reliability and validity test and empirical analysis of the evaluation index system through simulated measurement.Methods Literature research method was used to select comprehensive evaluation indicators for drugs centralized bidding procurement.Then,Dephi method was applied to screen the final evaluation indicators,and the weight of the indicators was determined using analytic hierarchy process.Results and Conclusion The final clinical efficacy evaluation index system for drugs centralized bidding procurement includes 5 primary indicators and 13 secondary indicators.The experts authority coefficient in this study is high,and their opinions relatively coincide.Through the empirical research,the reliability and structural validity of the indicator system is good.This indicator system enriches methods and tools for scientifically evaluating the clinical efficacy of drugs centralized bidding procurement.展开更多
With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heter...With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heterogeneous data integration.In view of the heterogeneous characteristics of physical sensor data,including temperature,vibration and pressure that generated by boilers,steam turbines and other key equipment and real-time working condition data of SCADA system,this paper proposes a multi-source heterogeneous data fusion and analysis platform for thermal power plants based on edge computing and deep learning.By constructing a multi-level fusion architecture,the platform adopts dynamic weight allocation strategy and 5D digital twin model to realize the collaborative analysis of physical sensor data,simulation calculation results and expert knowledge.The data fusion module combines Kalman filter,wavelet transform and Bayesian estimation method to solve the problem of data time series alignment and dimension difference.Simulation results show that the data fusion accuracy can be improved to more than 98%,and the calculation delay can be controlled within 500 ms.The data analysis module integrates Dymola simulation model and AERMOD pollutant diffusion model,supports the cascade analysis of boiler combustion efficiency prediction and flue gas emission monitoring,system response time is less than 2 seconds,and data consistency verification accuracy reaches 99.5%.展开更多
Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electron...Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electronic reviews and consumer data sourced from third-party restaurant platforms collected in 2021.By performing weighted processing on two-dimensional point-of-interest(POI)data,clustering hotspots of high-dimensional restaurant data were identified.A hierarchical network of restaurant hotspots was constructed following the Central Place Theory(CPT)framework,while the Geo-Informatic Tupu method was employed to resolve the challenges posed by network deformation in multi-scale processes.These findings suggest the necessity of enhancing the spatial balance of Shanghai’s urban centers by moderately increasing the number and service capacity of suburban centers at the urban periphery.Such measures would contribute to a more optimized urban structure and facilitate the outward dispersion of comfort-oriented facilities such as the restaurant industry.At a finer spatial scale,the distribution of restaurant hotspots demonstrates a polycentric and symmetric spatial pattern,with a developmental trend radiating outward along the city’s ring roads.This trend can be attributed to the efforts of restaurants to establish connections with other urban functional spaces,leading to the reconfiguration of urban spaces,expansion of restaurant-dedicated land use,and the reorganization of associated commercial activities.The results validate the existence of a polycentric urban structure in Shanghai but also highlight the instability of the restaurant hotspot network during cross-scale transitions.展开更多
Taking the Ming Tombs Forest Farm in Beijing as the research object,this research applied multi-source data fusion and GIS heat-map overlay analysis techniques,systematically collected bird observation point data from...Taking the Ming Tombs Forest Farm in Beijing as the research object,this research applied multi-source data fusion and GIS heat-map overlay analysis techniques,systematically collected bird observation point data from the Global Biodiversity Information Facility(GBIF),population distribution data from the Oak Ridge National Laboratory(ORNL)in the United States,as well as information on the composition of tree species in suitable forest areas for birds and the forest geographical information of the Ming Tombs Forest Farm,which is based on literature research and field investigations.By using GIS technology,spatial processing was carried out on bird observation points and population distribution data to identify suitable bird-watching areas in different seasons.Then,according to the suitability value range,these areas were classified into different grades(from unsuitable to highly suitable).The research findings indicated that there was significant spatial heterogeneity in the bird-watching suitability of the Ming Tombs Forest Farm.The north side of the reservoir was generally a core area with high suitability in all seasons.The deep-aged broad-leaved mixed forests supported the overlapping co-existence of the ecological niches of various bird species,such as the Zosterops simplex and Urocissa erythrorhyncha.In contrast,the shallow forest-edge coniferous pure forests and mixed forests were more suitable for specialized species like Carduelis sinica.The southern urban area and the core area of the mausoleums had relatively low suitability due to ecological fragmentation or human interference.Based on these results,this paper proposed a three-level protection framework of“core area conservation—buffer zone management—isolation zone construction”and a spatio-temporal coordinated human-bird co-existence strategy.It was also suggested that the human-bird co-existence space could be optimized through measures such as constructing sound and light buffer interfaces,restoring ecological corridors,and integrating cultural heritage elements.This research provided an operational technical approach and decision-making support for the scientific planning of bird-watching sites and the coordination of ecological protection and tourism development.展开更多
As coal mining progresses to greater depths,controlling the stability of surrounding rock in deep roadways has become an increasingly complex challenge.Although four-dimensional(4D)support theoretically offers unique ...As coal mining progresses to greater depths,controlling the stability of surrounding rock in deep roadways has become an increasingly complex challenge.Although four-dimensional(4D)support theoretically offers unique advantages in maintaining the stability of rock mass,the disaster evolution processes and multi-source information response characteristics in deep roadways with 4D support remain unclear.Consequently,a large-scale physical model testing system and self-designed 4D support components were employed to conduct similarity model tests on the surrounding rock failure process under unsupported(U-1),traditional bolt-mesh-cable support(T-2),and 4D support(4D-R-3)conditions.Combined with multi-source monitoring techniques,including stress–strain,digital image correlation(DIC),acoustic emission(AE),microseismic(MS),parallel electric(PE),and electromagnetic radiation(EMR),the mechanical behavior and multi-source information responses were comprehensively analyzed.The results show that the peak stress and displacement of the models are positively correlated with the support strength.The multi-source information exhibits distinct response characteristics under different supports.The response frequency,energy,and fluctuationsof AE,MS,and EMR signals,along with the apparent resistivity(AR)high-resistivity zone,follow the trend U-1>T-2>4D-R-3.Furthermore,multi-source information exhibits significantdifferences in sensitivity across different phases.The AE,MS,and EMR signals exhibit active responses to rock mass activity at each phase.However,AR signals are only sensitive to the fracture propagation during the plastic yield and failure phases.In summary,the 4D support significantlyenhances the bearing capacity and plastic deformation of the models,while substantially reducing the frequency,energy,and fluctuationsof multi-source signals.展开更多
In order to make the supply chain select the best emergency procurement suppliers in case the procurement system encounters unexpected risks,six indices which can reflect the comprehensive abilities of alternative sup...In order to make the supply chain select the best emergency procurement suppliers in case the procurement system encounters unexpected risks,six indices which can reflect the comprehensive abilities of alternative suppliers are selected,i.e.,the product yield,the toll standard,the on-time-delivery rate,the rate of turnover industry experience and customer satisfaction.Then standardized processing of evaluation is performed.For quantitative indices,vector normalization is adopted to perform standardized processing,and qualitative fuzziness indices are quantified through assignment.Finally,each index can be transformed into a standardized mark which has dimensionless 1 and the same magnitude.And an expert method is used to determine the index weights and then the linear weighted sum method is used to calculate the alternative supplier's comprehensive ability score and by comparing these scores,the optimal emergency procurement supplier is selected.展开更多
Multi-source seismic technology is an efficient seismic acquisition method that requires a group of blended seismic data to be separated into single-source seismic data for subsequent processing. The separation of ble...Multi-source seismic technology is an efficient seismic acquisition method that requires a group of blended seismic data to be separated into single-source seismic data for subsequent processing. The separation of blended seismic data is a linear inverse problem. According to the relationship between the shooting number and the simultaneous source number of the acquisition system, this separation of blended seismic data is divided into an easily determined or overdetermined linear inverse problem and an underdetermined linear inverse problem that is difficult to solve. For the latter, this paper presents an optimization method that imposes the sparsity constraint on wavefields to construct the object function of inversion, and the problem is solved by using the iterative thresholding method. For the most extremely underdetermined separation problem with single-shooting and multiple sources, this paper presents a method of pseudo-deblending with random noise filtering. In this method, approximate common shot gathers are received through the pseudo-deblending process, and the random noises that appear when the approximate common shot gathers are sorted into common receiver gathers are eliminated through filtering methods. The separation methods proposed in this paper are applied to three types of numerical simulation data, including pure data without noise, data with random noise, and data with linear regular noise to obtain satisfactory results. The noise suppression effects of these methods are sufficient, particularly with single-shooting blended seismic data, which verifies the effectiveness of the proposed methods.展开更多
文摘This paper focuses on the procurement of construction projects in universities,conducting research on the influencing factors of procurement risks in such projects.By combining questionnaire surveys with expert interviews,numerous factors affecting procurement are analyzed.Subsequently,these factors are refined and summarized to construct a procurement risk evaluation index system for construction projects,which includes three first-level indicators,such as process management risk and ethical/legal risk,and is further subdivided into 13 second-level indicators.
文摘The centralized procurement of drugs in the medical system is a key link,which not only affects the economic effect of institutions,but also relates to the medical quality and patient safety.In the current era,centralized drug procurement in hospitals can meet the needs of most patients;however,the specific steps of the work still need to be optimized.Starting from the level of hospital drug centralized procurement work,this paper discusses the policy background,analyzes the practice of drug centralized procurement in tertiary hospitals,and provides specific work management suggestions,aiming to improve work efficiency and serve as a reference for optimizing subsequent hospital drug centralized procurement work.
文摘Objective To quantitatively analyze the policy of centralized drug procurement centralized drug procurement in order to provide reference for the subsequent policy formulation and improvement.Methods Text mining method was used to process 15 centralized drugs procurement policies issued at the national level during 2015-2022,and a PMC index evaluation model of centralized drug procurement policies was established.Then,15 centralized drug procurement policies were quantitatively analyzed from the overall and comparative perspective through an evaluation model.Results and Conclusion The average PMC index of 15 centralized drug procurement policies was 6.95,which was acceptable on the whole.Among them,eight were excellent and seven were acceptable.As to the first-order variables,the centralized drugs procurement policy still lacks incentives and constraints.The comparative results show that there are differences in the content and structure of policies,but they are strongly related to each other.Chinese centralized drug procurement policy has been basically formed,which is closely related to medical insurance and medical policies.However,it is still necessary to pay attention to the structure of the policy to ensure the elaboration of the policy content.
文摘In the project procurement management process of telecommunication enterprises,due to the complexity of technology,the professional procurement project manager is responsible for the whole process of professional procurement in a one-stop way.The integration of this management process superficially improves labor productivity,but in essence lacks effective checks and balances and supervision.In order to supervise the project procurement management process and ensure the legal compliance of procurement management,this paper studies the project procurement management process of telecommunication enterprises,proposes the optimization process of project procurement management in the segmentation of purchasing manager-business manager,and constructs a matrix project procurement management model,which will contribute to the overall improvement of the telecommunication enterprises’procurement performance.
文摘With the acceleration of the global digital wave,enterprise procurement management is facing multiple challenges such as cost pressure,supply chain collaboration demand,and insufficient information ability.Based on dynamic capability theory,resource-based view,and value chain theory,this paper constructs a four-level research framework of“driving factors-transformation paths-strategic actions-performance evaluation”.Firstly,through literature analysis and case review,it summarizes the internal and external driving factors such as external market competition pressure,supply chain coordination demand,policy and regulatory environment,as well as enterprise information foundation,organizational culture,and talent reserve,and analyzes their mechanism of action on procurement digital transformation.Secondly,the procurement digital transformation path is divided into two types:gradual upgrading and leap-forward reconstruction,and the strategic and tactical level strategies,such as top-level design,data governance,process remodeling,supplier collaboration platform construction,and intelligent decision support,are proposed.Thirdly,the implementation guarantee mechanism was designed from the four aspects of organization management,technology platform,talent culture,and risk control.Finally,the performance evaluation index system covering cost,cycle,quality,risk,and digital maturity was constructed,and the evaluation method and continuous improvement mechanism based on balanced scorecard and ROI/TCO analysis were proposed.The results show that the systematic strategy design and multi-dimensional guarantee can effectively improve the procurement efficiency of enterprises,reduce operating costs,enhance supply chain resilience,and provide theoretical and practical guidance for enterprises to achieve sustainable competitive advantage.
基金funded by the Beijing Natural Science Foundation(grant number 9232010)Capital's Funds for Health Improvement and Research(grant number 2022-2-4079).
文摘Background:Atherosclerotic cardiovascular disease remains the leading cause of death worldwide.This study aims to explore the impact of national volume-based procurement(NVBP)on Chinese patent medicines and provide evidence for improving policies and promoting rational drug use.Methods:The study was based on data from the China National Health Insurance Agency that spanned January 2019 to December 2020.Descriptive analysis was conducted using volume and expenditure as variables.Interrupted time series analysis was applied to further analyze Chinese patent medicines.Results:The unit prices of atorvastatin and rosuvastatin decreased by 25%-96%,whereas the prices of Zhibitai and Xuezhikang fluctuated slightly.The affordability is measured as the monthly expenditure on treatment divided by the daily wage.After policy implementation,the affordability of atorvastatin and rosuvastatin improved from 0.242 to 0.014 and from 0.247 to 0.019,respectively.The defined daily doses(DDDs)for atorvastatin and rosuvastatin also increased,whereas total expenditures decreased in hospitals of all levels.Both at the national level and at all levels of hospital,the policy had no significant impact on expenditures for Zhibitai and Xuezhikang and their defined daily doses.Conclusions:The NVBP saved costs in the short term by incorporating high-quality,widely used lipid-lowering drugs.Notably,the policy impacted lipid-lowering chemical drugs,whereas Chinese patent medicines remained largely unaffected.Doctors'use of Chinese patent medicines did not decline,highlighting the clinical specificity of these medicines.
基金supported by the National Key R&D Program of China(No.2023YFB2603602)the National Natural Science Foundation of China(Nos.52222810 and 52178383).
文摘To elucidate the fracturing mechanism of deep hard rock under complex disturbance environments,this study investigates the dynamic failure behavior of pre-damaged granite subjected to multi-source dynamic disturbances.Blasting vibration monitoring was conducted in a deep-buried drill-and-blast tunnel to characterize in-situ dynamic loading conditions.Subsequently,true triaxial compression tests incorporating multi-source disturbances were performed using a self-developed wide-low-frequency true triaxial system to simulate disturbance accumulation and damage evolution in granite.The results demonstrate that combined dynamic disturbances and unloading damage significantly accelerate strength degradation and trigger shear-slip failure along preferentially oriented blast-induced fractures,with strength reductions up to 16.7%.Layered failure was observed on the free surface of pre-damaged granite under biaxial loading,indicating a disturbance-induced fracture localization mechanism.Time-stress-fracture-energy coupling fields were constructed to reveal the spatiotemporal characteristics of fracture evolution.Critical precursor frequency bands(105-150,185-225,and 300-325 kHz)were identified,which serve as diagnostic signatures of impending failure.A dynamic instability mechanism driven by multi-source disturbance superposition and pre-damage evolution was established.Furthermore,a grouting-based wave-absorption control strategy was proposed to mitigate deep dynamic disasters by attenuating disturbance amplitude and reducing excitation frequency.
文摘Background:Acquiring relevant information about procurement targets is fundamental to procuring medical devices.Although traditional Natural Language Processing(NLP)and Machine Learning(ML)methods have improved information retrieval efficiency to a certain extent,they exhibit significant limitations in adaptability and accuracy when dealing with procurement documents characterized by diverse formats and a high degree of unstructured content.The emergence of Large Language Models(LLMs)offers new possibilities for efficient procurement information processing and extraction.Methods:This study collected procurement transaction documents from public procurement websites,and proposed a procurement Information Extraction(IE)method based on LLMs.Unlike traditional approaches,this study systematically explores the applicability of LLMs in both structured and unstructured entities in procurement documents,addressing the challenges posed by format variability and content complexity.Furthermore,an optimized prompt framework tailored for procurement document extraction tasks is developed to enhance the accuracy and robustness of IE.The aim is to process and extract key information from medical device procurement quickly and accurately,meeting stakeholders'demands for precision and timeliness in information retrieval.Results:Experimental results demonstrate that,compared to traditional methods,the proposed approach achieves an F1 Score of 0.9698,representing a 4.85%improvement over the best baseline model.Moreover,both recall and precision rates are close to 97%,significantly outperforming other models and exhibiting exceptional overall recognition capabilities.Notably,further analysis reveals that the proposed method consistently maintains high performance across both structured and unstructured entities in procurement documents while balancing recall and precision effectively,demonstrating its adaptability in handling varying document formats.The results of ablation experiments validate the effectiveness of the proposed prompting strategy.Conclusion:Additionally,this study explores the challenges and potential improvements of the proposed method in IE tasks and provides insights into its feasibility for real-world deployment and application directions,further clarifying its adaptability and value.This method not only exhibits significant advantages in medical device procurement but also holds promise for providing new approaches to information processing and decision support in various domains.
基金supported by the National Natural Science Foundation of China(21663032 and 22061041)the Open Sharing Platform for Scientific and Technological Resources of Shaanxi Province(2021PT-004)the National Innovation and Entrepreneurship Training Program for College Students of China(S202110719044)。
文摘The SiO_(2) inverse opal photonic crystals(PC)with a three-dimensional macroporous structure were fabricated by the sacrificial template method,followed by infiltration of a pyrene derivative,1-(pyren-8-yl)but-3-en-1-amine(PEA),to achieve a formaldehyde(FA)-sensitive and fluorescence-enhanced sensing film.Utilizing the specific Aza-Cope rearrangement reaction of allylamine of PEA and FA to generate a strong fluorescent product emitted at approximately 480 nm,we chose a PC whose blue band edge of stopband overlapped with the fluorescence emission wavelength.In virtue of the fluorescence enhancement property derived from slow photon effect of PC,FA was detected highly selectively and sensitively.The limit of detection(LoD)was calculated to be 1.38 nmol/L.Furthermore,the fast detection of FA(within 1 min)is realized due to the interconnected three-dimensional macroporous structure of the inverse opal PC and its high specific surface area.The prepared sensing film can be used for the detection of FA in air,aquatic products and living cells.The very close FA content in indoor air to the result from FA detector,the recovery rate of 101.5%for detecting FA in aquatic products and fast fluorescence imaging in 2 min for living cells demonstrate the reliability and accuracy of our method in practical applications.
基金supported by the Sichuan Science and Technology Program(Nos.2024JDRC0100 and 2023YFQ0091)the National Natural Science Foundation of China(Nos.U21A20167 and 52475138)the Scientific Research Foundation of the State Key Laboratory of Rail Transit Vehicle System(No.2024RVL-T08).
文摘Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.
基金supported by Natural Science Foundation of China(Nos.62303126,62362008,author Z.Z,https://www.nsfc.gov.cn/,accessed on 20 December 2024)Major Scientific and Technological Special Project of Guizhou Province([2024]014)+2 种基金Guizhou Provincial Science and Technology Projects(No.ZK[2022]General149) ,author Z.Z,https://kjt.guizhou.gov.cn/,accessed on 20 December 2024)The Open Project of the Key Laboratory of Computing Power Network and Information Security,Ministry of Education under Grant 2023ZD037,author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024)Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(No.ICT2024B25),author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024).
文摘Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.
基金supported by National Natural Science Foundation of China(12174350)Science and Technology Project of State Grid Henan Electric Power Company(5217Q0240008).
文摘In the heterogeneous power internet of things(IoT)environment,data signals are acquired to support different business systems to realize advanced intelligent applications,with massive,multi-source,heterogeneous and other characteristics.Reliable perception of information and efficient transmission of energy in multi-source heterogeneous environments are crucial issues.Compressive sensing(CS),as an effective method of signal compression and transmission,can accurately recover the original signal only by very few sampling.In this paper,we study a new method of multi-source heterogeneous data signal reconstruction of power IoT based on compressive sensing technology.Based on the traditional compressive sensing technology to directly recover multi-source heterogeneous signals,we fully use the interference subspace information to design the measurement matrix,which directly and effectively eliminates the interference while making the measurement.The measure matrix is optimized by minimizing the average cross-coherence of the matrix,and the reconstruction performance of the new method is further improved.Finally,the effectiveness of the new method with different parameter settings under different multi-source heterogeneous data signal cases is verified by using orthogonal matching pursuit(OMP)and sparsity adaptive matching pursuit(SAMP)for considering the actual environment with prior information utilization of signal sparsity and no prior information utilization of signal sparsity.
文摘This paper deeply discusses the causes of gear howling noise,the identification and analysis of multi-source excitation,the transmission path of dynamic noise,simulation and experimental research,case analysis,optimization effect,etc.,aiming to better provide a certain guideline and reference for relevant researchers.
文摘Objective To establish a scientific,reliable,objective,and effective clinical comprehensive evaluation system for drugs centralized bidding procurement by government,and to conduct reliability and validity test and empirical analysis of the evaluation index system through simulated measurement.Methods Literature research method was used to select comprehensive evaluation indicators for drugs centralized bidding procurement.Then,Dephi method was applied to screen the final evaluation indicators,and the weight of the indicators was determined using analytic hierarchy process.Results and Conclusion The final clinical efficacy evaluation index system for drugs centralized bidding procurement includes 5 primary indicators and 13 secondary indicators.The experts authority coefficient in this study is high,and their opinions relatively coincide.Through the empirical research,the reliability and structural validity of the indicator system is good.This indicator system enriches methods and tools for scientifically evaluating the clinical efficacy of drugs centralized bidding procurement.
文摘With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heterogeneous data integration.In view of the heterogeneous characteristics of physical sensor data,including temperature,vibration and pressure that generated by boilers,steam turbines and other key equipment and real-time working condition data of SCADA system,this paper proposes a multi-source heterogeneous data fusion and analysis platform for thermal power plants based on edge computing and deep learning.By constructing a multi-level fusion architecture,the platform adopts dynamic weight allocation strategy and 5D digital twin model to realize the collaborative analysis of physical sensor data,simulation calculation results and expert knowledge.The data fusion module combines Kalman filter,wavelet transform and Bayesian estimation method to solve the problem of data time series alignment and dimension difference.Simulation results show that the data fusion accuracy can be improved to more than 98%,and the calculation delay can be controlled within 500 ms.The data analysis module integrates Dymola simulation model and AERMOD pollutant diffusion model,supports the cascade analysis of boiler combustion efficiency prediction and flue gas emission monitoring,system response time is less than 2 seconds,and data consistency verification accuracy reaches 99.5%.
基金Under the auspices of the Key Program of National Natural Science Foundation of China(No.42030409)。
文摘Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electronic reviews and consumer data sourced from third-party restaurant platforms collected in 2021.By performing weighted processing on two-dimensional point-of-interest(POI)data,clustering hotspots of high-dimensional restaurant data were identified.A hierarchical network of restaurant hotspots was constructed following the Central Place Theory(CPT)framework,while the Geo-Informatic Tupu method was employed to resolve the challenges posed by network deformation in multi-scale processes.These findings suggest the necessity of enhancing the spatial balance of Shanghai’s urban centers by moderately increasing the number and service capacity of suburban centers at the urban periphery.Such measures would contribute to a more optimized urban structure and facilitate the outward dispersion of comfort-oriented facilities such as the restaurant industry.At a finer spatial scale,the distribution of restaurant hotspots demonstrates a polycentric and symmetric spatial pattern,with a developmental trend radiating outward along the city’s ring roads.This trend can be attributed to the efforts of restaurants to establish connections with other urban functional spaces,leading to the reconfiguration of urban spaces,expansion of restaurant-dedicated land use,and the reorganization of associated commercial activities.The results validate the existence of a polycentric urban structure in Shanghai but also highlight the instability of the restaurant hotspot network during cross-scale transitions.
基金Sponsored by Beijing Youth Innovation Talent Support Program for Urban Greening and Landscaping——The 2024 Special Project for Promoting High-Quality Development of Beijing’s Landscaping through Scientific and Technological Innovation(KJCXQT202410).
文摘Taking the Ming Tombs Forest Farm in Beijing as the research object,this research applied multi-source data fusion and GIS heat-map overlay analysis techniques,systematically collected bird observation point data from the Global Biodiversity Information Facility(GBIF),population distribution data from the Oak Ridge National Laboratory(ORNL)in the United States,as well as information on the composition of tree species in suitable forest areas for birds and the forest geographical information of the Ming Tombs Forest Farm,which is based on literature research and field investigations.By using GIS technology,spatial processing was carried out on bird observation points and population distribution data to identify suitable bird-watching areas in different seasons.Then,according to the suitability value range,these areas were classified into different grades(from unsuitable to highly suitable).The research findings indicated that there was significant spatial heterogeneity in the bird-watching suitability of the Ming Tombs Forest Farm.The north side of the reservoir was generally a core area with high suitability in all seasons.The deep-aged broad-leaved mixed forests supported the overlapping co-existence of the ecological niches of various bird species,such as the Zosterops simplex and Urocissa erythrorhyncha.In contrast,the shallow forest-edge coniferous pure forests and mixed forests were more suitable for specialized species like Carduelis sinica.The southern urban area and the core area of the mausoleums had relatively low suitability due to ecological fragmentation or human interference.Based on these results,this paper proposed a three-level protection framework of“core area conservation—buffer zone management—isolation zone construction”and a spatio-temporal coordinated human-bird co-existence strategy.It was also suggested that the human-bird co-existence space could be optimized through measures such as constructing sound and light buffer interfaces,restoring ecological corridors,and integrating cultural heritage elements.This research provided an operational technical approach and decision-making support for the scientific planning of bird-watching sites and the coordination of ecological protection and tourism development.
基金supported by the National Natural Science Foundation of China(Grant Nos.U22A20598 and 52104107)the"Qinglan Project"of Jiangsu Colleges and Universities,Young Elite Scientists Sponsorship Program of Jiangsu Province(Grant No.TJ-2023-086).
文摘As coal mining progresses to greater depths,controlling the stability of surrounding rock in deep roadways has become an increasingly complex challenge.Although four-dimensional(4D)support theoretically offers unique advantages in maintaining the stability of rock mass,the disaster evolution processes and multi-source information response characteristics in deep roadways with 4D support remain unclear.Consequently,a large-scale physical model testing system and self-designed 4D support components were employed to conduct similarity model tests on the surrounding rock failure process under unsupported(U-1),traditional bolt-mesh-cable support(T-2),and 4D support(4D-R-3)conditions.Combined with multi-source monitoring techniques,including stress–strain,digital image correlation(DIC),acoustic emission(AE),microseismic(MS),parallel electric(PE),and electromagnetic radiation(EMR),the mechanical behavior and multi-source information responses were comprehensively analyzed.The results show that the peak stress and displacement of the models are positively correlated with the support strength.The multi-source information exhibits distinct response characteristics under different supports.The response frequency,energy,and fluctuationsof AE,MS,and EMR signals,along with the apparent resistivity(AR)high-resistivity zone,follow the trend U-1>T-2>4D-R-3.Furthermore,multi-source information exhibits significantdifferences in sensitivity across different phases.The AE,MS,and EMR signals exhibit active responses to rock mass activity at each phase.However,AR signals are only sensitive to the fracture propagation during the plastic yield and failure phases.In summary,the 4D support significantlyenhances the bearing capacity and plastic deformation of the models,while substantially reducing the frequency,energy,and fluctuationsof multi-source signals.
基金The National Key Technology R&D Program of China during the 11th Five-Year Plan Period(No.2006BAH02A06)
文摘In order to make the supply chain select the best emergency procurement suppliers in case the procurement system encounters unexpected risks,six indices which can reflect the comprehensive abilities of alternative suppliers are selected,i.e.,the product yield,the toll standard,the on-time-delivery rate,the rate of turnover industry experience and customer satisfaction.Then standardized processing of evaluation is performed.For quantitative indices,vector normalization is adopted to perform standardized processing,and qualitative fuzziness indices are quantified through assignment.Finally,each index can be transformed into a standardized mark which has dimensionless 1 and the same magnitude.And an expert method is used to determine the index weights and then the linear weighted sum method is used to calculate the alternative supplier's comprehensive ability score and by comparing these scores,the optimal emergency procurement supplier is selected.
文摘Multi-source seismic technology is an efficient seismic acquisition method that requires a group of blended seismic data to be separated into single-source seismic data for subsequent processing. The separation of blended seismic data is a linear inverse problem. According to the relationship between the shooting number and the simultaneous source number of the acquisition system, this separation of blended seismic data is divided into an easily determined or overdetermined linear inverse problem and an underdetermined linear inverse problem that is difficult to solve. For the latter, this paper presents an optimization method that imposes the sparsity constraint on wavefields to construct the object function of inversion, and the problem is solved by using the iterative thresholding method. For the most extremely underdetermined separation problem with single-shooting and multiple sources, this paper presents a method of pseudo-deblending with random noise filtering. In this method, approximate common shot gathers are received through the pseudo-deblending process, and the random noises that appear when the approximate common shot gathers are sorted into common receiver gathers are eliminated through filtering methods. The separation methods proposed in this paper are applied to three types of numerical simulation data, including pure data without noise, data with random noise, and data with linear regular noise to obtain satisfactory results. The noise suppression effects of these methods are sufficient, particularly with single-shooting blended seismic data, which verifies the effectiveness of the proposed methods.
