Application of the improved dung beetle optimizer,muti-head attention and hybrid deep learning algorithms to groundwater depth prediction in the Ningxia area,China

Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.

How Polymers Behave as Viscosity Index Improvers in Lubricating Oils

One of the requirements of engine lubricating oil is that it must have a low enough viscosity at low temperatures to assist in cold starting and a high enough viscosity at high temperatures to maintain its load-bearing characteristics. Viscosity Index (VI) is one approach used widely in the lubricating field to assess the variation of viscosity with temperature. The VI of both mineral and synthetic base oils can be improved by the addition of polymeric viscosity modifiers (VMs). VI improvement by VMs is widely attributed to the polymer coil size expanding with increasing temperature. However, there is very little physical data supporting this generally accepted mechanism. To address this issue, intrinsic viscosity measurements and Small-Angle Neutron Scattering (SANS) have been used to study the variation of polymer coil size with changing temperature and concentration in a selection of solvents. The results will show that coil size expansion with temperature is not necessary to achieve significant elevation of viscosity index.

Co-adsorption behaviors of asphaltenes and different flow improvers and their impacts on the interfacial viscoelasticity

Commonly used flow improvers in oilfields,such as ethylene–vinyl acetate copolymer(EVA),poly(octadecyl acrylate)(POA),and polymethylsilsesquioxane(PMSQ)are proven to be effective to enhance the flowability of crude oil.However,the addition of these flow improvers may change the stability of the emulsion and make the crude oil treatment process challenging.In this research,the impacts of different flow improvers on the interfacial properties of the emulsions containing asphaltenes are systematically investigated.The co-adsorption behaviors of the flow improvers and asphaltenes are analyzed through dynamic interfacial tension(DIFT).The rheological properties of the interfacial layer after the adsorption are explored via dilational viscoelasticity.Significant difference is observed in the structural properties of the interface adsorbed by different flow improvers,which is attributed to different interactions between the flow improvers and asphaltenes.To investigate these interactions,conductivity,asphaltenes precipitation,dynamic light scattering(DLS),and contact angle experiments are conducted systematically.Results show that EVA and POA can alter the interfacial properties by changing the asphaltene dispersion state.The interaction between EVA and asphaltenes is stronger than that between POA and asphaltenes due to the difference in molecular structures.Unlike EVA and POA,the change of interfacial property with the addition of PMSQ is attributed to the partial adsorption of asphaltenes on PMSQ.

Aminated Copolymers as Flow Improvers for Super-viscous Crude Oils

The new flow improvers for super-viscous crude oils were developed via esterification of polybasic high carbon alcohol with methacrylate and copolymerizafion of monomers followed by amination of copolymers. The structure of the synthesized polymer flow improver additive was confirmed by IR spectroscopy and the crystal structure of the flow improver additives were determined by X-ray diffrac- tion analysis. The structure of wax crystals was also studied at the same time. The results showed that the wax crystal structure was closely related with the crystal structure of the flow improver, which could change the pour point depression and viscosity reduction behavior of the crude oil. When the wax crystal structure matched well with that of the additive, the wax crystals were dispersed satisfactorily, resulting in favorable effects in terms of pour point depression and viscosity reduction. The new synthe- sized aminated polymer flow improver additive was most efficient for treating super-viscous crude oils. The super-viscous crude oil had a high content of resins and asphaltenes, which might aggregate onto the surface of wax crystals to form blocks to limit the crude oil fluidity. However, amination of copolymers having similar structure with the resins and asphaltenes contained in crude oil could dissolve the huge polar groups to make the deposit formation difficult.

An Underwater Target Detection Algorithm Based on Attention Mechanism and Improved YOLOv7

For underwater robots in the process of performing target detection tasks,the color distortion and the uneven quality of underwater images lead to great difficulties in the feature extraction process of the model,which is prone to issues like error detection,omission detection,and poor accuracy.Therefore,this paper proposed the CER-YOLOv7(CBAM-EIOU-RepVGG-YOLOv7)underwater target detection algorithm.To improve the algorithm’s capability to retain valid features from both spatial and channel perspectives during the feature extraction phase,we have added a Convolutional Block Attention Module(CBAM)to the backbone network.The Reparameterization Visual Geometry Group(RepVGG)module is inserted into the backbone to improve the training and inference capabilities.The Efficient Intersection over Union(EIoU)loss is also used as the localization loss function,which reduces the error detection rate and missed detection rate of the algorithm.The experimental results of the CER-YOLOv7 algorithm on the UPRC(Underwater Robot Prototype Competition)dataset show that the mAP(mean Average Precision)score of the algorithm is 86.1%,which is a 2.2%improvement compared to the YOLOv7.The feasibility and validity of the CER-YOLOv7 are proved through ablation and comparison experiments,and it is more suitable for underwater target detection.

Integrating artificial intelligence and high-throughput phenotyping for crop improvement

Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.

Rheological Study of Polymers Used as Viscosity Index Improvers for Automotive Lubricant Oils

In this work, a rheological study of automotive lubricant oils, neutral light paraffinic (NLP) and neutral medium paraffinic (NMP), additivated with two commercial viscosity index improvers-VIIs, based on hydrogenated poly (isoprene-co-styrene), at different concentrations, was carried out. The study included the determination of the kinematic viscosity of the mixtures, the calculation of the viscosity indexes and their behavior when subjected to various rheometric experiments, including stress sweep, steady state flow, creep and recovery, and temperature ramp oscillatory tests. The obtained results showed the efficacy of the additives as viscosity index improvers, enabling a significant increase in the viscosity index of the pure oils at relatively low concentrations. The determination of the storage (G’) and of the loss (G”) moduli for the mixtures oil/VII additives showed a large predominance of the viscous effect over the elastic one. Except when under low shear stress, the mixtures showed a pseudoplastic behavior, with the flow curves being adjusted to fit the Ostwald-de-Waele model (Power Law), with negative flow behavior indexes.

Nitrogen, Phosphorus, and Potassium Interactive Effects for Improving Drought Resistance on Mung Bean Varieties

The planting areas of mung bean are mostly arid and semi-arid areas, and lack of irrigation conditions. Many studies have reported that fertilization can increase drought resistance. In our previous research, optimized nitrogen (N), phosphorus (P) and potassium (K) combined fertilization model was established in mung bean. In the present study, the optimal fertilization was conducted in pot trails, and mung bean varieties Bailv9 and Bailv11 were used as materials, while the four water regimes, and three fertilization ratios of F120 (optimal fertilization), F100 (conventional fertilization), F50 (half of conventional fertilization) treatments were set, to compare each fertilization ratio effects and non-fertilization condition under each water regimes respectively. Under different water conditions, the investigation of N, P, and K effects of optimal fertilization showed that the yield of Bailv9 was not sensitive to water stress and had strong drought resistance;their water sensitivity index and drought resistance coefficient were BaiLv9 as Di = 0.89 and DC = 0.79. The yield of Bailv11 was sensitive to water stress, and their drought resistance was weak;their water sensitivity index and drought resistance coefficient were BL11 Di = 1.76 DC = 0.59, and under different water treatment conditions, Bailv9 and Bailv11 all had the best yield and other related traits increase in the F120 fertilization mode compared with other fertilization and non-fertilization conditions, and the average yield increases were 31.56% and 28.08%, respectively. The pot trails conduct the drought stress treatments in mung bean varieties Bailv9, Bailv11, Bailv935 and Bailv985 to determine the function of NPK optimized fertilization for improving plants growth in drought stress condition. Compared with the mung bean varieties treated with F50, F100, and F120, the yield of Bailv9 increased by 56.20%, 81.27%, and 107.22%, respectively;compared with that of F0, the yield of Bailv11 increased by 10.18%, 19.42%, and 45.88%, respectively;Bailv935 increased by 26.52%, 61.90%, 74.16% respectively, and Bailv985 increased by 23.78%, 56.92%, 87.62% respectively. The significant performances of optimized fertilization were also verified in 20 mung bean varieties in our filed trails. The research establishes a theoretical basis for introducing the model into production practice in the next step.

Effect of Gum Arabic from Acacia senegal var. kerensis as an Improver on the Rheological Properties of Wheat Flour Dough

Dough improvers are substances with functional characteristics used in baking industry to enhance dough properties. Currently, the baking industry is faced with increasing demand for natural ingredients owing to increasing consumer awareness, thus contributing to the rising demand for natural hydrocolloids. Gum Arabic from Acacia senegal var. kerensis is a natural gum exhibiting excellent water binding and emulsification capacity. However, very little is reported on how it affects the rheological properties of wheat dough. The aim of this study was therefore, to determine the rheological properties of wheat dough with partial additions of gum Arabic as an improver. Six treatments were analyzed comprising of: flour-gum blends prepared by adding gum Arabic to wheat flour at different levels (1%, 2% and 3%), plain wheat flour (negative control), commercial bread flour and commercial chapati flour (positive controls). The rheological properties were determined using Brabender Farinograph, Brabender Extensograph and Brabender Viscograph. Results showed that addition of gum Arabic significantly (p chapati. These findings support the need to utilize gum Arabic from Acacia senegal var. kerensis as a dough improver.

Technological Properties of Improved Pigeon Pea Varieties in Machakos County, Kenya

Pigeon peas, a type of pulse, have immense nutritional potential to improve health in arid and semi-arid regions. However, unlocking this potential relies heavily on understanding their technological properties, such as hydration rate, volumetric expansion, and cooking time. These properties directly influence processing, accessibility, and acceptability as a food source. However, there is limited information on technological properties of improved varieties. The study aimed to determine technological properties of improved pigeon pea varieties grown in Machakos County. Seven improved pigeon peas varieties namely: KARI Mbaazi 1, KARI Mbaazi 2, ICEAP 00850, KAT 60/8, Mituki, Egerton Mbaazi 1, Egerton Mbaazi 2 and ICEAP 00554 (control variety) were used in this study. These varieties were tested for water absorption capacity (WAC), volumetric expansion, density, cooking time (CT) and total soluble solids (TSS) in the broth. The experiment was arranged in a Completely Randomized Design (CRD) replicated three times. Data analysis was conducted using SAS software version 9.1.3 (SAS, 2006). Means separation was done using Tukey’s honestly significant difference (HSD) at 95% Confidence Level. There were significant differences in water absorption capacity (WAC), volumetric expansion, density, TSS, and CT among the improved varieties (p p < 0.05). KARI Mbaazi 2 exhibited the greatest volumetric expansion after cooking (VEAC) at 11%. Additionally, control variety recorded the highest water absorption capacity (125.48%), which was significantly greater compared to the improved pigeon pea varieties. Cooking time in minutes was shortest for Mituki (46.0) and KAT 60/8 (55.7) and longest for both KARI Mbaazi 1 and ICEAP00850 at 160 minutes. All the varieties showed high TSS ranging from 10.5 to 26.7% indicating the potential to select varieties with desired flavour profiles. Improved pigeon pea varieties (Mituki and KAT60/8) displayed desired technological properties alongside the control variety. These findings inform the specific culinary applications and nutritional needs which enhance utilisation of pigeon peas as food. Further research is needed to determine the impact of the technological properties on the digestibility and glycaemic index of pigeon peas.

IGED:Towards Intelligent DDoS Detection Model Using Improved Generalized Entropy and DNN

As the scale of the networks continually expands,the detection of distributed denial of service(DDoS)attacks has become increasingly vital.We propose an intelligent detection model named IGED by using improved generalized entropy and deep neural network(DNN).The initial detection is based on improved generalized entropy to filter out as much normal traffic as possible,thereby reducing data volume.Then the fine detection is based on DNN to perform precise DDoS detection on the filtered suspicious traffic,enhancing the neural network’s generalization capabilities.Experimental results show that the proposed method can efficiently distinguish normal traffic from DDoS traffic.Compared with the benchmark methods,our method reaches 99.9%on low-rate DDoS(LDDoS),flooded DDoS and CICDDoS2019 datasets in terms of both accuracy and efficiency in identifying attack flows while reducing the time by 17%,31%and 8%.

Value of improved nursing measures and enhanced nursing management to reduce the occurrence of adverse events in pediatric infusion

BACKGROUND Intravenous infusion is a common method of drug administration in clinical practice.Errors in any aspect of the infusion process,from the verification of medical orders,preparation of the drug solution,to infusion by nursing staff,may cause adverse infusion events.AIM To analyzed the value of improving nursing measures and enhancing nursing management to reduce the occurrence of adverse events in pediatric infusion.METHODS The clinical data of 130 children who received an infusion in the pediatric department of our hospital from May 2020 to May 2021 were analyzed and divided into two groups according to the differences in nursing measures and nursing management:65 patients in the control group received conventional nursing and nursing management interventions,while 65 patients in the observation group received improved nursing measure interventions and enhanced nursing management.The occurrence of adverse events,compliance of children,satisfaction of children’s families,and complaints regarding the transfusion treatment were recorded in both groups.RESULTS The incidence of fluid extravasation and infusion set dislodgement in the observation group were 3.08%and 1.54%,respectively,which were significantly lower than 12.31%and 13.85%in the control group(P<0.05),while repeated punctures and medication addition errors in the observation group were 3.08%and 0.00%,respectively,which were lower than 9.23%and 3.08%in the control group,but there was no significant difference(P>0.05).The compliance rate of children in the observation group was 98.46%(64/65),which was significantly higher than 87.69%(57/65)in the control group,and the satisfaction rate of children’s families was 96.92%(63/65),which was significantly higher than 86.15%(56/65)in the control group(P<0.05).The observation group did not receive any complaints from the child’s family,whereas the control group received four complaints,two of which were due to the crying of the child caused by repeated punctures,one due to the poor attitude of the nurse,and one due to medication addition errors,with a cumulative complaint rate of 6.15%.The cumulative complaint rate of the observation group was significantly lower than that of the control group(P<0.05).CONCLUSION Improving nursing measures and enhancing nursing management can reduce the incidence of fluid extravasation and infusion set dislodgement in pediatric patients,improve children’s compliance and satisfaction of their families,and reduce family complaints.

Approaches to Improving Selectivity During Photoelectrochemical Transformation of Small Molecules

Photoelectrochemical (PEC) small-molecule oxidation can selectively transform substrates into high-value-added fine chemicals and increase the rate of cathode hydrogen evolution. Nevertheless, achieving high-selectivity PEC oxidation of small molecules to produce specific products is a very challenging task. In general, selectivity can be improved by changing the surface catalyticsites of the photoanode and modulating the interfacial environments of the reactions. Herein, recent advances in approaches to improving selective PEC oxidation of small molecules are introduced. We first briefly discuss the basic concept and fundamentals of small-molecule PEC oxidation. The reported approaches to improving the performance of selective PEC oxidation of small molecules are highlighted from two aspects: (1) changing the surface properties of photoanodes by selecting suitable materials or modifying the photoanodes and (2) mediating the oxidation reactions using redox mediators. The PEC oxidation mechanism of these studies is emphasized. We also discuss the challenges in this research direction and offer a perspective on the further development of selective PEC-based small-molecule transformation.

Anti-aging performance improvement and enhanced combustion efficiency of boron via the coating of PDA

Boron is an ambitious fuel in energetic materials since its high heat release values,but its application is prohibited by low combustion efficiency and oxidization during storage.The polydopamine(PDA)was introduced into boron particles,investigating the impact of PDA content on the energetic behavior of boron.The results indicated that the PDA coating formed a fishing net structure on the surface of boron particles.The heat release results showed that the combustion calorific value of B@PDA was higher than that of the raw boron.Specifically,the actual combustion heat of boron powder in B@10%PDA increased by 38.08%.Meanwhile,the DSC peak temperature decreased by 100.65℃under similar oxidation rate compared to raw boron.Simultaneously,the B@PDA@AP and B@AP composites were prepared,and their combustion properties were evaluated.It was demonstrated that B@10%PDA@AP exhibited superior performance in terms of peak pressure and burning time,respectively.The peak pressure is 12.43 kPa more than B@AP and burning time is 2.22 times higher than B@AP.Therefore,the coating of PDA effectively inhibits the oxidization of boron during storage and enhances the energetic behavior of boron and corresponding composites.

Deterioration Reason and Improvement Measure of the Retarding Effect of Protein Retarder on Phosphorus Building Gypsum

The retarding effect of protein retarder on phosphorus building gypsum(PBG)and desulfurization building gypsum(DBG)was investigated,and the results show that protein retarder for DBG can effectively prolong the setting time and displays a better retarding effect,but for PBG shows a poor retarding effect.Furthermore,the deterioration reason of the retarding effect of protein retarder on PBG was investigated by measuring the pH value and the retarder concentration of the liquid phase from vacuum filtration of PBG slurry at different hydration time,and the measure to improve the retarding effect of protein retarding on PBG was suggested.The pH value of PBG slurry(<5.0)is lower than that of DBG slurry(7.8-8.5).After hydration for 5 min,the concentration of retarder in liquid phase of DBG slurry gradually decreases,but in liquid phase of PBG slurry continually increases,which results in the worse retarding effect of protein retarder on PBG.The liquid phase pH value of PBG slurry can be adjusted higher by sodium silicate,which is beneficial to improvement in the retarding effect of the retarder.By adding 1.0%of sodium silicate,the initial setting time of PBG was efficiently prolonged from 17 to 210 min,but little effect on the absolute dry flexural strength was observed.

An Improved JSO and Its Application in Spreader Optimization of Large Span Corridor Bridge

In this paper,given the shortcomings of jellyfish search algorithmwith low search ability in the early stage and easy to fall into local optimal solution,this paper introduces adaptive weight function and elite strategy,improving the global search scope in the early stage and the ability to refine the local development in the later stage.In the numerical study,the benchmark problem of dimensional optimization with a 10-bar truss structure and simultaneous dimensional shape optimization with a 15-bar truss structure is adopted,and the corresponding penalty method is used for constraint treatment.The test results show that the improved jellyfish search algorithm can provide better truss sections as well as weights.Because when the steel main truss of the large-span covered bridge is lifted,the site is limited and the large lifting equipment cannot enter the site,and the original structure does not meet the problem of stress concentration and large deformation of the bolt group,so the spreader is used to lift,and the improved jellyfish search algorithm is introduced into the design optimization of the spreader.The results show that the improved jellyfish algorithm can efficiently and accurately find out the optimal shape and weight of the spreader,and throughMidas Civil simulation,the spreader used canmeet the requirements of weight and safety.

An improved typhoon monitoring model based on precipitable water vapor and pressure

The potential of monitoring the movement of typhoons using the precipitable water vapor(PWV) has been confirmed. However, monitoring the movement of typhoon is focused on PWV, making it difficult to describe the movement of a typhoon in detail minutely and resulting in insufficient accuracy. Hence,based on PWV and meteorological data, we propose an improved typhoon monitoring mode. First, the European Centre for Medium-Range Weather Forecasts Reanalysis 5-derived PWV(ERA5-PWV) and the Global Navigation Satellite System-derived PWV(GNSS-PWV) were compared with the reference radiosonde PWV(RS-PWV). Then, using the PWV and atmospheric parameters derived from ERA5, we discussed the anomalous variations of PWV, pressure(P), precipitation, and wind speed during different typhoons. Finally, we compiled a list of critical factors related to typhoon movement, PWV and P. We developed an improved multi-factor typhoon monitoring mode(IMTM) with different models(i.e.,IMTM-I and IMTM-II) in different cases with a higher density of GNSS observation or only Numerical Weather Prediction(NWP) data. The IMTM was evaluated through the reference movement speeds of HATO and Mangkhut from the China Meteorological Observatory Typhoon Network(CMOTN). The results show that the root mean square(RMS) of the IMTM-I is 1.26 km/h based on ERA5-P and ERA5-PWV,and the absolute bias values are mostly within 2 km/h. Compared with the models considering the single factor ERA5-P/ERA5-PWV, the RMS of the IMTM-I is improved by 26.3% and 38.5%, respectively. The IMTM-II model manifests a residual of only 0.35 km/h. Compared with the single-factor model based on GNSS-PWV/P, the residual of the IMTM-II model is reduced by 90.8% and 84.1%, respectively. These results propose that the typhoon movement monitoring approach combining PWV and P has evident advantages over the single-factor model and is expected to supplement traditional typhoon monitoring.

Enhancing Private Healthcare Effectiveness in Lagos State, Nigeria: An Overview of the Effect of Quality Improvement Initiatives and Implications for Sustainable Healthcare Delivery

Background: Nigeria, a nation grappling with rapid population growth, economic intricacies, and complex healthcare challenges, particularly in Lagos State, the economic hub and most populous state, faces the challenge of ensuring quality healthcare access. The overview of the effect of quality improvement initiatives in this paper focuses on private healthcare providers in Lagos State, Nigeria. The study assesses the impact of donor-funded quality improvement projects on these private healthcare facilities. It explores the level of participation, perceived support, and tangible effects of the initiatives on healthcare delivery within private healthcare facilities. It also examines how these initiatives influence patient inflow and facility ratings, and bring about additional benefits and improvements, provides insights into the challenges faced by private healthcare providers in implementing quality improvement projects and elicits recommendations for improving the effectiveness of such initiatives. Methods: Qualitative research design was employed for in-depth exploration, utilizing semi-structured interviews. Private healthcare providers in Lagos involved in the SP4FP Quality Improvement Project were purposively sampled for diversity. Face-to-face interviews elicited insights into participation, perceived support, and project effects. Questions covered participation levels, support perception, changes observed, challenges faced, and recommendations. Thematic analysis identified recurring themes from interview transcripts. Adherence to ethical guidelines ensured participant confidentiality and informed consent. Results: Respondents affirmed active involvement in the SP4FP Quality Improvement Project, echoing literature emphasizing private-sector collaboration with the public sector. While acknowledging positive influences on facility ratings, respondents highlighted challenges within the broader Nigerian healthcare landscape affecting patient numbers. Respondents cited tangible improvements, particularly in staff management and patient care processes, validating the positive influence of quality improvement projects. Financial constraints emerged as a significant challenge, aligning with existing literature emphasizing the pragmatic difficulties faced by private healthcare providers. Conclusions: This study illuminates the complex landscape of private healthcare provision in Lagos State, emphasizing the positive impact of donor-funded quality improvement projects. The findings provide nuanced insights, guiding policymakers, healthcare managers, and practitioners toward collaborative, sustainable improvements. As Nigeria progresses, these lessons will be crucial in shaping healthcare policies prioritizing population well-being.

Stroke nurse-led intravenous thrombolytic therapy strategy for ischemic stroke based on timeline process:A quality improvement program from China

Objective:Early thrombolytic therapy for ischemic stroke within the therapeutic window is associated with improved clinical outcomes.This study investigated whether optimizing intravenous thrombolytic(IVT)therapy strategies for stroke could reduce treatment delays.Methods:To reduce delays in IVT therapy for ischemic stroke,a series of quality improvement measures were implemented at a tertiary hospital in Hangzhou,Zhejiang Province,from June 2021 to August 2023,which included developing a timeline process management system,forming a nurse-led stroke process management team,providing homogeneous training,standardizing the IVT therapy process for ischemic stroke,and introducing an incentive policy.During the pre-(from June 2021 to February 2022,group A)and post-(from March to November 2022,group B1;from December 2022 to August 2023,group B2[implementation of an additional incentive policy])of the implementation the strategy,the door-tocomputed tomographic angiography(CTA)time(DCT),CTA time,neurology consultation to consent for IVT,CTA-to-needle time(CNT),and door-to-needle time(DNT),the percentage of people who underwent CTA within 20 min,15 min,and 10 min and DNT within 60 min,45 min,and 30 min were collected and compared.Results:Following the implementation of the standardized IVT process management strategy for stroke,the DNT for group B1 and group B2 were 30(24,44)min and 31(24,41)min,respectively,both significantly lower than the 46(38,58)min in group A(P<0.001);the median DCT were both 13 min in group B1 and B2 lower than 17min in group A(P<0.001);the median CTA were 12 min in Group B1 and 9 min in Group B2 lower than 14 min in group A(P<0.001);similar results were observed during the neurology consultation to obtain consent for IVT and CNT.Compared with group A,the proportion of DCT20 min,15 min,and 10 min was higher in groups B1 and B2(P<0.05),and the same result was observed at DNT60 min,45 min,and 30 min(P<0.05).However,the additional incentive policy did not significantly differ between Group B2 and Group B1.Conclusions:Optimizing IVT therapy for ischemic stroke is a feasible approach to limit the DNT to 30 min in ischemic stroke,significantly reducing delays within the therapeutic window and increasing the number of patients meeting target time segments.Additionally,generating a timeline for the IVT therapy process by scanning positioning quick response codes was a significant breakthrough in achieving the informatization of IVT quality management for stroke.

Introduction of Western Medicines into China and Improvement on Decoctions during Modern China

During the late Qing dynasty(1840 A.D.-1912 A.D.),a large quantity of Western medicines entered China,which continuously impacted the traditional Chinese medicine(TCM)market and revealed the shortcomings of Chinese medicines.Some personages in the TCM community followed the trend of learning from the West,and attempted to reform TCM,with the improvement on decoction becoming an important aspect of this effort.Through debates and trials,the improvement on decoction underwent three stages of conceptual evolution:“taking Chinese medicines as the foundation and referring to the dosage forms of Western medicines”,“introducing Western techniques to serve the preparation of decoctions”and“integrating the theories of TCM and Western medicine to improve decoctions”.The study highlights the effective complementarity between modern TCM and Western medicine in the field of pharmacy,and provides valuable experience and support for the reevaluation of the value of TCM in contemporary society.