We demonstrate coherent optical frequency dissemination over a distance of 972 km by cascading two spans where the phase noise is passively compensated for.Instead of employing a phase discriminator and a phase lockin...We demonstrate coherent optical frequency dissemination over a distance of 972 km by cascading two spans where the phase noise is passively compensated for.Instead of employing a phase discriminator and a phase locking loop in the conventional active phase control scheme,the passive phase noise cancellation is realized by feeding double-trip beat-note frequency to the driver of the acoustic optical modulator at the local site.This passive scheme exhibits fine robustness and reliability,making it suitable for long-distance and noisy fiber links.An optical regeneration station is used in the link for signal amplification and cascaded transmission.The phase noise cancellation and transfer instability of the 972-km link is investigated,and transfer instability of 1.1×10^(-19)at 10^(4)s is achieved.This work provides a promising method for realizing optical frequency distribution over thousands of kilometers by using fiber links.展开更多
Bushfires are devastating to forest managers,owners,residents,and the natural environment.Recent tech-nological advances indicate a potential for faster response times in terms of detecting and suppressing fires.Howev...Bushfires are devastating to forest managers,owners,residents,and the natural environment.Recent tech-nological advances indicate a potential for faster response times in terms of detecting and suppressing fires.However,to date,all these technologies have been applied in isola-tion.This paper introduces the latest fire detection and sup-pression technologies from ground to space.An operations research method was used to assemble these technologies into a theoretical framework for fire detection and suppres-sion.The framework harnesses the advantages of satellite-based,drone,sensor,and human reporting technologies as well as image processing and artificial intelligence machine learning.The study concludes that,if a system is designed to maximise the use of available technologies and carefully adopts them through complementary arrangements,a fire detection and resource suppression system can achieve the ultimate aim:to reduce the risk of fire hazards and the dam-age they may cause.展开更多
Leveraging big data analytics and advanced algorithms to accelerate and optimize the process of molecular and materials design, synthesis, and application has revolutionized the field of molecular and materials scienc...Leveraging big data analytics and advanced algorithms to accelerate and optimize the process of molecular and materials design, synthesis, and application has revolutionized the field of molecular and materials science, allowing researchers to gain a deeper understanding of material properties and behaviors,leading to the development of new materials that are more efficient and reliable. However, the difficulty in constructing large-scale datasets of new molecules/materials due to the high cost of data acquisition and annotation limits the development of conventional machine learning(ML) approaches. Knowledgereused transfer learning(TL) methods are expected to break this dilemma. The application of TL lowers the data requirements for model training, which makes TL stand out in researches addressing data quality issues. In this review, we summarize recent progress in TL related to molecular and materials. We focus on the application of TL methods for the discovery of advanced molecules/materials, particularly, the construction of TL frameworks for different systems, and how TL can enhance the performance of models. In addition, the challenges of TL are also discussed.展开更多
Deep learning has emerged in many practical applications,such as image classification,fault diagnosis,and object detection.More recently,convolutional neural networks(CNNs),representative models of deep learning,have ...Deep learning has emerged in many practical applications,such as image classification,fault diagnosis,and object detection.More recently,convolutional neural networks(CNNs),representative models of deep learning,have been used to solve fault detection.However,the current design of CNNs for fault detection of wind turbine blades is highly dependent on domain knowledge and requires a large amount of trial and error.For this reason,an evolutionary YOLOv8 network has been developed to automatically find the network architecture for wind turbine blade-based fault detection.YOLOv8 is a CNN-backed object detection model.Specifically,to reduce the parameter count,we first design an improved FasterNet module based on the Partial Convolution(PConv)operator.Then,to enhance convergence performance,we improve the loss function based on the efficient complete intersection over the union.Based on this,a flexible variable-length encoding is proposed,and the corresponding reproduction operators are designed.Related experimental results confirmthat the proposed approach can achieve better fault detection results and improve by 2.6%in mean precision at 50(mAP50)compared to the existing methods.Additionally,compared to training with the YOLOv8n model,the YOLOBFE model reduces the training parameters by 933,937 and decreases the GFLOPS(Giga Floating Point Operations Per Second)by 1.1.展开更多
With the continuous advancement of China’s“peak carbon dioxide emissions and Carbon Neutrality”process,the proportion of wind power is increasing.In the current research,aiming at the problem that the forecasting m...With the continuous advancement of China’s“peak carbon dioxide emissions and Carbon Neutrality”process,the proportion of wind power is increasing.In the current research,aiming at the problem that the forecasting model is outdated due to the continuous updating of wind power data,a short-term wind power forecasting algorithm based on Incremental Learning-Bagging Deep Hybrid Kernel Extreme Learning Machine(IL-Bagging-DHKELM)error affinity propagation cluster analysis is proposed.The algorithm effectively combines deep hybrid kernel extreme learning machine(DHKELM)with incremental learning(IL).Firstly,an initial wind power prediction model is trained using the Bagging-DHKELM model.Secondly,Euclidean morphological distance affinity propagation AP clustering algorithm is used to cluster and analyze the prediction error of wind power obtained from the initial training model.Finally,the correlation between wind power prediction errors and Numerical Weather Prediction(NWP)data is introduced as incremental updates to the initial wind power prediction model.During the incremental learning process,multiple error performance indicators are used to measure the overall model performance,thereby enabling incremental updates of wind power models.Practical examples show the method proposed in this article reduces the root mean square error of the initial model by 1.9 percentage points,indicating that this method can be better adapted to the current scenario of the continuous increase in wind power penetration rate.The accuracy and precision of wind power generation prediction are effectively improved through the method.展开更多
High-order quantum coherence reveals the statistical correlation of quantum particles. Manipulation of quantum coherence of light in the temporal domain enables the production of the single-photon source, which has be...High-order quantum coherence reveals the statistical correlation of quantum particles. Manipulation of quantum coherence of light in the temporal domain enables the production of the single-photon source, which has become one of the most important quantum resources. High-order quantum coherence in the spatial domain plays a crucial role in a variety of applications, such as quantum imaging, holography, and microscopy. However, the active control of second-order spatial quantum coherence remains a challenging task. Here we predict theoretically and demonstrate experimentally the first active manipulation of second-order spatial quantum coherence,which exhibits the capability of switching between bunching and anti-bunching, by mapping the entanglement of spatially structured photons. We also show that signal processing based on quantum coherence exhibits robust resistance to intensity disturbance. Our findings not only enhance existing applications but also pave the way for broader utilization of higher-order spatial quantum coherence.展开更多
BACKGROUND Myocardial fibrosis,a condition linked to several cardiovascular diseases,is associated with a poor prognosis.Stem cell therapy has emerged as a potential treatment option and the application of stem cell t...BACKGROUND Myocardial fibrosis,a condition linked to several cardiovascular diseases,is associated with a poor prognosis.Stem cell therapy has emerged as a potential treatment option and the application of stem cell therapy has been studied extensively.However,a comprehensive bibliometric analysis of these studies has yet to be conducted.AIM To map thematic trends,analyze research hotspots,and project future directions of stem cell-based myocardial fibrosis therapy.METHODS We conducted a bibliometric and visual analysis of studies in the Web of Science Core Collection using VOSviewer and Microsoft Excel.The dataset included 1510 articles published between 2001 and 2024.Countries,organizations,authors,references,keywords,and co-citation networks were examined to identify evolving research trends.RESULTS Our findings revealed a steady increase in the number of publications,with a projected increase to over 200 publications annually by 2030.Initial research focused on stem cell-based therapy,particularly for myocardial infarction and heart failure.More recently,there has been a shift toward cell-free therapy,involving extracellular vesicles,exosomes,and microRNAs.Key research topics include angiogenesis,inflammation,apoptosis,autophagy,and oxidative stress.CONCLUSION This analysis highlights the evolution of stem cell therapies for myocardial fibrosis,with emerging interest in cellfree approaches.These results are expected to guide future scientific exploration and decision-making.展开更多
BACKGROUND The cognitive impairment in type 2 diabetes mellitus(T2DM)is a multifaceted and advancing state that requires further exploration to fully comprehend.Neu-roinflammation is considered to be one of the main m...BACKGROUND The cognitive impairment in type 2 diabetes mellitus(T2DM)is a multifaceted and advancing state that requires further exploration to fully comprehend.Neu-roinflammation is considered to be one of the main mechanisms and the immune system has played a vital role in the progression of the disease.AIM To identify and validate the immune-related genes in the hippocampus associated with T2DM-related cognitive impairment.METHODS To identify differentially expressed genes(DEGs)between T2DM and controls,we used data from the Gene Expression Omnibus database GSE125387.To identify T2DM module genes,we used Weighted Gene Co-Expression Network Analysis.All the genes were subject to Gene Set Enrichment Analysis.Protein-protein interaction network construction and machine learning were utilized to identify three hub genes.Immune cell infiltration analysis was performed.The three hub genes were validated in GSE152539 via receiver operating characteristic curve analysis.Validation experiments including reverse transcription quantitative real-time PCR,Western blotting and immunohistochemistry were conducted both in vivo and in vitro.To identify potential drugs associated with hub genes,we used the Comparative Toxicogenomics Database(CTD).RESULTS A total of 576 DEGs were identified using GSE125387.By taking the intersection of DEGs,T2DM module genes,and immune-related genes,a total of 59 genes associated with the immune system were identified.Afterward,machine learning was utilized to identify three hub genes(H2-T24,Rac3,and Tfrc).The hub genes were associated with a variety of immune cells.The three hub genes were validated in GSE152539.Validation experiments were conducted at the mRNA and protein levels both in vivo and in vitro,consistent with the bioinformatics analysis.Additionally,11 potential drugs associated with RAC3 and TFRC were identified based on the CTD.CONCLUSION Immune-related genes that differ in expression in the hippocampus are closely linked to microglia.We validated the expression of three hub genes both in vivo and in vitro,consistent with our bioinformatics results.We discovered 11 compounds associated with RAC3 and TFRC.These findings suggest that they are co-regulatory molecules of immunometabolism in diabetic cognitive impairment.展开更多
The couple between the power network and the transportation network(TN)is deepening gradually with the increasing penetration rate of electric vehicles(EV),which also poses a great challenge to the traditional voltage...The couple between the power network and the transportation network(TN)is deepening gradually with the increasing penetration rate of electric vehicles(EV),which also poses a great challenge to the traditional voltage control scheme.In this paper,we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV.In the first stage,the action of on-load tap changer and capacitor banks,etc.,are determined by optimal power flow calculation,and the node electricity price is also determined based on dynamic time-of-use tariff mechanism.In the second stage,multiple operating scenarios of multiple types of EVs such as cabs,private cars and buses are considered,and the scheduling results of each EV are solved by building an optimization model based on constraints such as queuing theory,Floyd-Warshall algorithm and traffic flow information.In the third stage,the output power of photovoltaic and energy storage systems is fine-tuned in the normal control mode.The charging power of EVs is also regulated in the emergency control mode to reduce the voltage deviation,and the amount of regulation is calculated based on the fair voltage control mode of EVs.Finally,we test the modified IEEE 33-bus distribution system coupled with the 24-bus Beijing TN.The simulation results show that the proposed scheme can mitigate voltage violations well.展开更多
Background:Recently,microbotulinum,a new technique that involves injecting botulinum toxin type A(BoNTA)microdroplets into superficial cutaneous tissue,has gained popularity.The precise distribution of BoNTA in the ta...Background:Recently,microbotulinum,a new technique that involves injecting botulinum toxin type A(BoNTA)microdroplets into superficial cutaneous tissue,has gained popularity.The precise distribution of BoNTA in the targeted area profoundly affects outcomes.Many factors may influence the effective area of BoNTA in the dermis.This study aimed to determine the dermal distribution properties of BoNTA to guide microbotulinum injection.Methods:Ten healthy males aged 18–65 years without BoNTA treatment in the previous year were recruited to receive intradermal injections in the chest and back.Ultrasound was used to ensure the intradermal delivery of injections and measure the dermal thickness.The minor iodine starch test was performed at baseline and 3 days,7 days,21 days,1 month,and 2 months after treatment.Results:All participants received intradermal injections.The dermis was thinner on the chest(thickness,0.20±0.03 cm)than on the back(thickness,0.39±0.07 cm)(P<0.05).An injection in the thicker dermis had a significantly smaller effective area at every follow-up visit.The drug concentration did not affect the effective area except at 3 days after treatment.Injection speed did not influence the effective area at any follow-up visits.Conclusion:An injection in a thicker dermis leads to a smaller effective area for intradermal injections.When the BoNTA dose is the same,the drug concentration and injection speed do not matter.展开更多
[Objectives]To establish a new management model for rational use of perioperative antibacterial drugs in surgical departments.[Methods]Based on evidence-based medicine,the department s drug pathway was formulated,and ...[Objectives]To establish a new management model for rational use of perioperative antibacterial drugs in surgical departments.[Methods]Based on evidence-based medicine,the department s drug pathway was formulated,and the new mode of rational drug use control was established by using fine pharmaceutical technology intervention,and the intervention effect was evaluated by the intensity of antibacterial drug use,per capita drug costs and the proportion of drugs.[Results]After adopting drug pathway in departments,the intensity of antibacterial drug use,per capita drug costs and the proportion of drugs decreased significantly,and the effect of rational drug use control was remarkable.[Conclusions]The drug pathway provides a new management and control mode for the rational use of perioperative antibacterial drugs in surgical departments of hospitals.Thus,it is worthy of popularization and application.展开更多
In this paper,the anti-tumor effects of Aconiti Radix were reviewed and summarized,and the clinical feasibility of Aconiti Radix as a potential anti-tumor drug was analyzed,in order to provide a useful reference for t...In this paper,the anti-tumor effects of Aconiti Radix were reviewed and summarized,and the clinical feasibility of Aconiti Radix as a potential anti-tumor drug was analyzed,in order to provide a useful reference for the future research and development of new anti-cancer drugs of Aconiti Radix.展开更多
Recycled large aggregate self-compacting concrete (RLA-SCC) within multiple weak areas. These weak areas have poor resistance to chloride ion erosion, which affects the service life of RLA-SCC in the marine environmen...Recycled large aggregate self-compacting concrete (RLA-SCC) within multiple weak areas. These weak areas have poor resistance to chloride ion erosion, which affects the service life of RLA-SCC in the marine environment. A three-dimensional multi-phase mesoscopic numerical model of RLA-SCC was established to simulate the chloride ions transportation in concrete. Experiments of RLA-SCC immersing in chloride solution were carried out to verify the simulation results. The effects of recycled large aggregate (RLA) content and RLA particle size on the service life of concrete were explored. The results indicate that the mesoscopic numerical simulation results are in good agreement with the experimental results. At the same depth, the closer to the surface of the RLA, the greater the chloride ion concentration. The service life of RLA-SCC in marine environment decreases with the increase of RLA content. Compared with the service life of 20% content, the service life of 25% and 30% content decreased by 20% and 42% respectively. Increasing the particle size of RLA can effectively improve the service life of RLA-SCC in chloride environment. Compared with the service life of 50 mm particle size, the service life of 70 mm and 90 mm increased by 61% and 163%, respectively. .展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12103059,12033007,12303077,and 12303076)the Fund from the Xi’an Science and Technology Bureau,China(Grant No.E019XK1S04)the Fund from the Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant No.1188000XGJ).
文摘We demonstrate coherent optical frequency dissemination over a distance of 972 km by cascading two spans where the phase noise is passively compensated for.Instead of employing a phase discriminator and a phase locking loop in the conventional active phase control scheme,the passive phase noise cancellation is realized by feeding double-trip beat-note frequency to the driver of the acoustic optical modulator at the local site.This passive scheme exhibits fine robustness and reliability,making it suitable for long-distance and noisy fiber links.An optical regeneration station is used in the link for signal amplification and cascaded transmission.The phase noise cancellation and transfer instability of the 972-km link is investigated,and transfer instability of 1.1×10^(-19)at 10^(4)s is achieved.This work provides a promising method for realizing optical frequency distribution over thousands of kilometers by using fiber links.
基金supported by the National Institute for Forest Products Innovation (NIFPI) Australia (Project No. NS034),titled Scoping an Automated Forest Fire Detection and Suppression Framework for the Green Triangle.
文摘Bushfires are devastating to forest managers,owners,residents,and the natural environment.Recent tech-nological advances indicate a potential for faster response times in terms of detecting and suppressing fires.However,to date,all these technologies have been applied in isola-tion.This paper introduces the latest fire detection and sup-pression technologies from ground to space.An operations research method was used to assemble these technologies into a theoretical framework for fire detection and suppres-sion.The framework harnesses the advantages of satellite-based,drone,sensor,and human reporting technologies as well as image processing and artificial intelligence machine learning.The study concludes that,if a system is designed to maximise the use of available technologies and carefully adopts them through complementary arrangements,a fire detection and resource suppression system can achieve the ultimate aim:to reduce the risk of fire hazards and the dam-age they may cause.
基金National Key R&D Program of China (No. 2021YFC2100100)Shanghai Science and Technology Project (No. 21JC1403400, 23JC1402300)。
文摘Leveraging big data analytics and advanced algorithms to accelerate and optimize the process of molecular and materials design, synthesis, and application has revolutionized the field of molecular and materials science, allowing researchers to gain a deeper understanding of material properties and behaviors,leading to the development of new materials that are more efficient and reliable. However, the difficulty in constructing large-scale datasets of new molecules/materials due to the high cost of data acquisition and annotation limits the development of conventional machine learning(ML) approaches. Knowledgereused transfer learning(TL) methods are expected to break this dilemma. The application of TL lowers the data requirements for model training, which makes TL stand out in researches addressing data quality issues. In this review, we summarize recent progress in TL related to molecular and materials. We focus on the application of TL methods for the discovery of advanced molecules/materials, particularly, the construction of TL frameworks for different systems, and how TL can enhance the performance of models. In addition, the challenges of TL are also discussed.
基金supported by the Liaoning Province Applied Basic Research Program Project of China(Grant:2023JH2/101300065)the Liaoning Province Science and Technology Plan Joint Fund(2023-MSLH-221).
文摘Deep learning has emerged in many practical applications,such as image classification,fault diagnosis,and object detection.More recently,convolutional neural networks(CNNs),representative models of deep learning,have been used to solve fault detection.However,the current design of CNNs for fault detection of wind turbine blades is highly dependent on domain knowledge and requires a large amount of trial and error.For this reason,an evolutionary YOLOv8 network has been developed to automatically find the network architecture for wind turbine blade-based fault detection.YOLOv8 is a CNN-backed object detection model.Specifically,to reduce the parameter count,we first design an improved FasterNet module based on the Partial Convolution(PConv)operator.Then,to enhance convergence performance,we improve the loss function based on the efficient complete intersection over the union.Based on this,a flexible variable-length encoding is proposed,and the corresponding reproduction operators are designed.Related experimental results confirmthat the proposed approach can achieve better fault detection results and improve by 2.6%in mean precision at 50(mAP50)compared to the existing methods.Additionally,compared to training with the YOLOv8n model,the YOLOBFE model reduces the training parameters by 933,937 and decreases the GFLOPS(Giga Floating Point Operations Per Second)by 1.1.
基金funded by Liaoning Provincial Department of Science and Technology(2023JH2/101600058)。
文摘With the continuous advancement of China’s“peak carbon dioxide emissions and Carbon Neutrality”process,the proportion of wind power is increasing.In the current research,aiming at the problem that the forecasting model is outdated due to the continuous updating of wind power data,a short-term wind power forecasting algorithm based on Incremental Learning-Bagging Deep Hybrid Kernel Extreme Learning Machine(IL-Bagging-DHKELM)error affinity propagation cluster analysis is proposed.The algorithm effectively combines deep hybrid kernel extreme learning machine(DHKELM)with incremental learning(IL).Firstly,an initial wind power prediction model is trained using the Bagging-DHKELM model.Secondly,Euclidean morphological distance affinity propagation AP clustering algorithm is used to cluster and analyze the prediction error of wind power obtained from the initial training model.Finally,the correlation between wind power prediction errors and Numerical Weather Prediction(NWP)data is introduced as incremental updates to the initial wind power prediction model.During the incremental learning process,multiple error performance indicators are used to measure the overall model performance,thereby enabling incremental updates of wind power models.Practical examples show the method proposed in this article reduces the root mean square error of the initial model by 1.9 percentage points,indicating that this method can be better adapted to the current scenario of the continuous increase in wind power penetration rate.The accuracy and precision of wind power generation prediction are effectively improved through the method.
基金supported by the National Natural Science Foundation of China (Grant Nos.12234009,12275048,12304359,and 12274215)the National Key R&D Program of China (Grant No.2020YFA0309500)+4 种基金the Innovation Program for Quantum Science and Technology (Grant No.2021ZD0301400)the Program for Innovative Talents and Entrepreneurs in Jiangsu,the Natural Science Foundation of Jiangsu Province (Grant No.BK20220759)the Key R&D Program of Guangdong Province,China (Grant No.2020B0303010001)the China Postdoctoral Science Foundation (Grant No.2023M731611)the Jiangsu Funding Program for Excellent Postdoctoral Talent (Grant No.2023ZB717)。
文摘High-order quantum coherence reveals the statistical correlation of quantum particles. Manipulation of quantum coherence of light in the temporal domain enables the production of the single-photon source, which has become one of the most important quantum resources. High-order quantum coherence in the spatial domain plays a crucial role in a variety of applications, such as quantum imaging, holography, and microscopy. However, the active control of second-order spatial quantum coherence remains a challenging task. Here we predict theoretically and demonstrate experimentally the first active manipulation of second-order spatial quantum coherence,which exhibits the capability of switching between bunching and anti-bunching, by mapping the entanglement of spatially structured photons. We also show that signal processing based on quantum coherence exhibits robust resistance to intensity disturbance. Our findings not only enhance existing applications but also pave the way for broader utilization of higher-order spatial quantum coherence.
基金Supported by National Ten Thousand Talent Program(Young Top-notch Talent),No.03060011Traditional Chinese Medicine Ancient Book Documents and Characteristic Technology Inheritance Project of the National Administration of Traditional Chinese Medicine,No.GZY-KJS-2020-079Research and Transformation Application of Clinical Characteristic Diagnosis and Treatment Techniques in the Capital,No.Z221100007422081.
文摘BACKGROUND Myocardial fibrosis,a condition linked to several cardiovascular diseases,is associated with a poor prognosis.Stem cell therapy has emerged as a potential treatment option and the application of stem cell therapy has been studied extensively.However,a comprehensive bibliometric analysis of these studies has yet to be conducted.AIM To map thematic trends,analyze research hotspots,and project future directions of stem cell-based myocardial fibrosis therapy.METHODS We conducted a bibliometric and visual analysis of studies in the Web of Science Core Collection using VOSviewer and Microsoft Excel.The dataset included 1510 articles published between 2001 and 2024.Countries,organizations,authors,references,keywords,and co-citation networks were examined to identify evolving research trends.RESULTS Our findings revealed a steady increase in the number of publications,with a projected increase to over 200 publications annually by 2030.Initial research focused on stem cell-based therapy,particularly for myocardial infarction and heart failure.More recently,there has been a shift toward cell-free therapy,involving extracellular vesicles,exosomes,and microRNAs.Key research topics include angiogenesis,inflammation,apoptosis,autophagy,and oxidative stress.CONCLUSION This analysis highlights the evolution of stem cell therapies for myocardial fibrosis,with emerging interest in cellfree approaches.These results are expected to guide future scientific exploration and decision-making.
基金Supported by National Natural Science Foundation of China,No.82270845。
文摘BACKGROUND The cognitive impairment in type 2 diabetes mellitus(T2DM)is a multifaceted and advancing state that requires further exploration to fully comprehend.Neu-roinflammation is considered to be one of the main mechanisms and the immune system has played a vital role in the progression of the disease.AIM To identify and validate the immune-related genes in the hippocampus associated with T2DM-related cognitive impairment.METHODS To identify differentially expressed genes(DEGs)between T2DM and controls,we used data from the Gene Expression Omnibus database GSE125387.To identify T2DM module genes,we used Weighted Gene Co-Expression Network Analysis.All the genes were subject to Gene Set Enrichment Analysis.Protein-protein interaction network construction and machine learning were utilized to identify three hub genes.Immune cell infiltration analysis was performed.The three hub genes were validated in GSE152539 via receiver operating characteristic curve analysis.Validation experiments including reverse transcription quantitative real-time PCR,Western blotting and immunohistochemistry were conducted both in vivo and in vitro.To identify potential drugs associated with hub genes,we used the Comparative Toxicogenomics Database(CTD).RESULTS A total of 576 DEGs were identified using GSE125387.By taking the intersection of DEGs,T2DM module genes,and immune-related genes,a total of 59 genes associated with the immune system were identified.Afterward,machine learning was utilized to identify three hub genes(H2-T24,Rac3,and Tfrc).The hub genes were associated with a variety of immune cells.The three hub genes were validated in GSE152539.Validation experiments were conducted at the mRNA and protein levels both in vivo and in vitro,consistent with the bioinformatics analysis.Additionally,11 potential drugs associated with RAC3 and TFRC were identified based on the CTD.CONCLUSION Immune-related genes that differ in expression in the hippocampus are closely linked to microglia.We validated the expression of three hub genes both in vivo and in vitro,consistent with our bioinformatics results.We discovered 11 compounds associated with RAC3 and TFRC.These findings suggest that they are co-regulatory molecules of immunometabolism in diabetic cognitive impairment.
基金supported by the Science and Technology Project of North China Electric Power Research Institute,which is“Research on Key Technologies for Power Quality Evaluation and Improvement of New Distribution Network Based on Collaborative Interaction of Source-Network-Load-Storage”(KJZ2022016).
文摘The couple between the power network and the transportation network(TN)is deepening gradually with the increasing penetration rate of electric vehicles(EV),which also poses a great challenge to the traditional voltage control scheme.In this paper,we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV.In the first stage,the action of on-load tap changer and capacitor banks,etc.,are determined by optimal power flow calculation,and the node electricity price is also determined based on dynamic time-of-use tariff mechanism.In the second stage,multiple operating scenarios of multiple types of EVs such as cabs,private cars and buses are considered,and the scheduling results of each EV are solved by building an optimization model based on constraints such as queuing theory,Floyd-Warshall algorithm and traffic flow information.In the third stage,the output power of photovoltaic and energy storage systems is fine-tuned in the normal control mode.The charging power of EVs is also regulated in the emergency control mode to reduce the voltage deviation,and the amount of regulation is calculated based on the fair voltage control mode of EVs.Finally,we test the modified IEEE 33-bus distribution system coupled with the 24-bus Beijing TN.The simulation results show that the proposed scheme can mitigate voltage violations well.
基金supported by the National High Level Hospital Clinical Research Funding(grant nos.2022-PUMCH-B-041,2022-PUMCH-A-210,and 2022-PUMCH-C-025).
文摘Background:Recently,microbotulinum,a new technique that involves injecting botulinum toxin type A(BoNTA)microdroplets into superficial cutaneous tissue,has gained popularity.The precise distribution of BoNTA in the targeted area profoundly affects outcomes.Many factors may influence the effective area of BoNTA in the dermis.This study aimed to determine the dermal distribution properties of BoNTA to guide microbotulinum injection.Methods:Ten healthy males aged 18–65 years without BoNTA treatment in the previous year were recruited to receive intradermal injections in the chest and back.Ultrasound was used to ensure the intradermal delivery of injections and measure the dermal thickness.The minor iodine starch test was performed at baseline and 3 days,7 days,21 days,1 month,and 2 months after treatment.Results:All participants received intradermal injections.The dermis was thinner on the chest(thickness,0.20±0.03 cm)than on the back(thickness,0.39±0.07 cm)(P<0.05).An injection in the thicker dermis had a significantly smaller effective area at every follow-up visit.The drug concentration did not affect the effective area except at 3 days after treatment.Injection speed did not influence the effective area at any follow-up visits.Conclusion:An injection in a thicker dermis leads to a smaller effective area for intradermal injections.When the BoNTA dose is the same,the drug concentration and injection speed do not matter.
基金Supported by Science and Technology Innovation Plan for Medical Workers in Shandong Province(SDYWZGKCJH2023095)Clinical Pharmacy Research Project of Shandong Provincial Medical Association(YXH2022ZX010)+1 种基金Traditional Chinese Medicine Science and Technology Development Project of Shandong Province(2019-0400&2021Q097)Traditional Chinese Medicine Research Program of Qingdao City(2020-zyy031)Medical Research Guidance Plan of Qingdao City(2020-WJZD087).
文摘[Objectives]To establish a new management model for rational use of perioperative antibacterial drugs in surgical departments.[Methods]Based on evidence-based medicine,the department s drug pathway was formulated,and the new mode of rational drug use control was established by using fine pharmaceutical technology intervention,and the intervention effect was evaluated by the intensity of antibacterial drug use,per capita drug costs and the proportion of drugs.[Results]After adopting drug pathway in departments,the intensity of antibacterial drug use,per capita drug costs and the proportion of drugs decreased significantly,and the effect of rational drug use control was remarkable.[Conclusions]The drug pathway provides a new management and control mode for the rational use of perioperative antibacterial drugs in surgical departments of hospitals.Thus,it is worthy of popularization and application.
基金Supported by Science and Technology Innovation Plan for Medical Workers in Shandong Province(SDYWZGKCJH2023095)Clinical Pharmacy Research Project of Shandong Provincial Medical Association(YXH2022ZX010)+1 种基金Traditional Chinese Medicine Science and Technology Development Project of Shandong Province(2019-0400&2021Q097)Traditional Chinese Medicine Research Program of Qingdao City(2020-zyy031)Medical Research Guidance Plan of Qingdao City(2020-WJZD087).
文摘In this paper,the anti-tumor effects of Aconiti Radix were reviewed and summarized,and the clinical feasibility of Aconiti Radix as a potential anti-tumor drug was analyzed,in order to provide a useful reference for the future research and development of new anti-cancer drugs of Aconiti Radix.
文摘Recycled large aggregate self-compacting concrete (RLA-SCC) within multiple weak areas. These weak areas have poor resistance to chloride ion erosion, which affects the service life of RLA-SCC in the marine environment. A three-dimensional multi-phase mesoscopic numerical model of RLA-SCC was established to simulate the chloride ions transportation in concrete. Experiments of RLA-SCC immersing in chloride solution were carried out to verify the simulation results. The effects of recycled large aggregate (RLA) content and RLA particle size on the service life of concrete were explored. The results indicate that the mesoscopic numerical simulation results are in good agreement with the experimental results. At the same depth, the closer to the surface of the RLA, the greater the chloride ion concentration. The service life of RLA-SCC in marine environment decreases with the increase of RLA content. Compared with the service life of 20% content, the service life of 25% and 30% content decreased by 20% and 42% respectively. Increasing the particle size of RLA can effectively improve the service life of RLA-SCC in chloride environment. Compared with the service life of 50 mm particle size, the service life of 70 mm and 90 mm increased by 61% and 163%, respectively. .
