Gas explosion is a process involving complex hydrodynamics and chemical reactions.In order to investigate the interaction between the flame behavior and the dynamic overpressure resulting from the explosion of a premi...Gas explosion is a process involving complex hydrodynamics and chemical reactions.In order to investigate the interaction between the flame behavior and the dynamic overpressure resulting from the explosion of a premixed gasoline-air mixture in a confined space,a large eddy simulation(LES)strategy coupled with sub-grid combustion model has been implemented.The considered confined space consists of a long duct and four branches symmetrically distributed on both sides of the long duct.Comparisons between the simulated and experimental results have been considered with regard to the flame structure,flame speed and overpressure characteristics.It is shown that the explosion process can qualitatively be reproduced by the numerical simulation.Due to the branch structure,vortices are generated near the joint of the branch and long duct.Vortices rotate in opposite directions in the different branches.When the flame propagates into the branch,the flame front is influenced by the flow field structure and becomes more and more distorted.The overpressure displays a similar behavior in the two branches which have a different distance from the ignition point.It is finally shown that the overpressure change law can directly be put in relation with the shape of flame front.展开更多
BACKGROUND Robotic pancreaticoduodenectomy(RPD)can achieve similar surgical results to open and PD;however,RPD has a long learning curve and operation time(OT).To address this issue,we have summarized a surgical path ...BACKGROUND Robotic pancreaticoduodenectomy(RPD)can achieve similar surgical results to open and PD;however,RPD has a long learning curve and operation time(OT).To address this issue,we have summarized a surgical path to shorten the surgical learning curve and OT.AIM To investigate the effective learning curve of a“G”-shaped surgical approach in RPD for patients.METHODS A total of 60 patients,who received“G”-shaped RPD(GRPD)by a single surgeon in the First Hospital of Shanxi Medical University from May 2017 to April 2020,were included in this study.The OT,demographic data,intraoperative blood loss,complications,hospitalization time,and pathological results were recorded,and the cumulative sum(CUSUM)analysis was performed to evaluate the learning curve for GRPD.RESULTS According to the CUSUM analysis,the learning curve for GRPD was grouped into two phases:The early and late phases.The OT was 480±81.65 min vs 331±76.54 min,hospitalization time was 22±4.53 d vs 17±6.08 d,and blood loss was 308±54.78 mL vs 169.2±35.33 mL in the respective groups.Complications,including pancreatic fistula,bile leakage,reoperation rate,postoperative death,and delayed gastric emptying,were significantly decreased after this surgical technique.CONCLUSION GRPD can improve the learning curve and operative time,providing a new method for shortening the RPD learning curve.展开更多
Our previous study found that feeding with Lactobacillus plantarum Ep-M17 could effectively affect the growth performance,immune response,and gut microbiota of Penaeus vannamei.However,high temperature and pressure du...Our previous study found that feeding with Lactobacillus plantarum Ep-M17 could effectively affect the growth performance,immune response,and gut microbiota of Penaeus vannamei.However,high temperature and pressure during feed pelletizing is the main problem that can lead to a decrease in the activity of probiotics or cause their inactivation.Further investigation needs to investigate whether inactivated Ep-M17 can exert similar effects as live Ep-M17.Therefore,we evaluated the effects of inactivated L.plantarum Ep-M17 on growth performance,immune response,disease resistance,and gut microbiota in P.vannamei.Results show that adding inactivated Ep-M17 to the feed also promoted body weight gain and increased relative immune protection in shrimp.Also,histological examination revealed that the administration of inactivated Ep-M17 led to improvements in the density and distribution of microvilli in the intestines and enhancements in the abundance of B and R cells in the hepatopancreas.Additionally,the inactivated Ep-M17 supplementation resulted in increased activity levels of nutrient immune-related enzymes in both the shrimp hepatopancreas and intestines.Moreover,it stimulated the expression of Lvlec,PEN-3a,Crustin,LGBP,Lysozyme,and proPo genes in both the hepatopancreas and intestines.Furthermore,the inactivated Ep-M17 also increased bacterial diversity in the gut of shrimp and promoted the abundance of specific flora,facilitating the host organism’s metabolism and immunity to improve the disease resistance of shrimp.Therefore,supplementation of inactivated L.plantarum Ep-M17 in shrimp diets can exert similar effects as live L.plantarum Ep-M17 effectively improving growth performance,gut microbiota,immune response,and disease resistance in P.vannamei.展开更多
Channel prediction is critical to address the channel aging issue in mobile scenarios.Existing channel prediction techniques are mainly designed for discrete channel prediction,which can only predict the future channe...Channel prediction is critical to address the channel aging issue in mobile scenarios.Existing channel prediction techniques are mainly designed for discrete channel prediction,which can only predict the future channel in a fixed time slot per frame,while the other intra-frame channels are usually recovered by interpolation.However,these approaches suffer from a serious interpolation loss,especially for mobile millimeter-wave communications.To solve this challenging problem,we propose a tensor neural ordinary differential equation(TN-ODE)based continuous-time channel prediction scheme to realize the direct prediction of intra-frame channels.Specifically,inspired by the recently developed continuous mapping model named neural ODE in the field of machine learning,we first utilize the neural ODE model to predict future continuous-time channels.To improve the channel prediction accuracy and reduce computational complexity,we then propose the TN-ODE scheme to learn the structural characteristics of the high-dimensional channel by low-dimensional learnable transform.Simulation results show that the proposed scheme is able to achieve higher intra-frame channel prediction accuracy than existing schemes.展开更多
Coal seam gas content is frequently measured in quantity during underground coal mining operation and coalbed methane(CBM)exploration as a significant basic parameter.Due to the calculation error of lost gas and resid...Coal seam gas content is frequently measured in quantity during underground coal mining operation and coalbed methane(CBM)exploration as a significant basic parameter.Due to the calculation error of lost gas and residual gas in the direct method,the efficiency and accuracy of the current methods are not inadequate to the large area multi-point measurement of coal seam gas content.This paper firstly deduces a simplified theoretical dynamic model for calculating lost gas based on gas dynamic diffusion theory.Secondly,the effects of various factors on gas dynamic diffusion from coal particle are experimentally studied.And sampling procedure of representative coal particle is improved.Thirdly,a new estimation method of residual gas content based on excess adsorption and competitive adsorption theory is proposed.The results showed that the maximum error of calculating the losing gas content by using the new simplified model is only 4%.Considering the influence of particle size on gas diffusion law,the particle size of the collected coal sample is below 0.25 mm,which improves the measurement speed and reflects the safety representativeness of the sample.The determination time of gas content reduced from 36 to 3 h/piece.Moreover,the absolute error is 0.15–0.50 m^3/t,and the relative error is within 5%.A new engineering method for determining the coal seam gas content is developed according to the above research.展开更多
基金supported by the National Outstanding Youth Science Fund Project of National Natural Science Foundation of China[grant numbers 51704301]Foundation Strengthening Project of China[grant numbers 2019-JCJQ-JJ-024].
文摘Gas explosion is a process involving complex hydrodynamics and chemical reactions.In order to investigate the interaction between the flame behavior and the dynamic overpressure resulting from the explosion of a premixed gasoline-air mixture in a confined space,a large eddy simulation(LES)strategy coupled with sub-grid combustion model has been implemented.The considered confined space consists of a long duct and four branches symmetrically distributed on both sides of the long duct.Comparisons between the simulated and experimental results have been considered with regard to the flame structure,flame speed and overpressure characteristics.It is shown that the explosion process can qualitatively be reproduced by the numerical simulation.Due to the branch structure,vortices are generated near the joint of the branch and long duct.Vortices rotate in opposite directions in the different branches.When the flame propagates into the branch,the flame front is influenced by the flow field structure and becomes more and more distorted.The overpressure displays a similar behavior in the two branches which have a different distance from the ignition point.It is finally shown that the overpressure change law can directly be put in relation with the shape of flame front.
基金Supported by Shanxi Provincial Science and Technology Department Social Development Fund,No.201903D321144.
文摘BACKGROUND Robotic pancreaticoduodenectomy(RPD)can achieve similar surgical results to open and PD;however,RPD has a long learning curve and operation time(OT).To address this issue,we have summarized a surgical path to shorten the surgical learning curve and OT.AIM To investigate the effective learning curve of a“G”-shaped surgical approach in RPD for patients.METHODS A total of 60 patients,who received“G”-shaped RPD(GRPD)by a single surgeon in the First Hospital of Shanxi Medical University from May 2017 to April 2020,were included in this study.The OT,demographic data,intraoperative blood loss,complications,hospitalization time,and pathological results were recorded,and the cumulative sum(CUSUM)analysis was performed to evaluate the learning curve for GRPD.RESULTS According to the CUSUM analysis,the learning curve for GRPD was grouped into two phases:The early and late phases.The OT was 480±81.65 min vs 331±76.54 min,hospitalization time was 22±4.53 d vs 17±6.08 d,and blood loss was 308±54.78 mL vs 169.2±35.33 mL in the respective groups.Complications,including pancreatic fistula,bile leakage,reoperation rate,postoperative death,and delayed gastric emptying,were significantly decreased after this surgical technique.CONCLUSION GRPD can improve the learning curve and operative time,providing a new method for shortening the RPD learning curve.
基金Supported by the Zhejiang Provincial Natural Science Foundation of China(No.LY23D060002)the Key Scientific and Technological Grant of Zhejiang for Breeding New Agricultural Varieties(No.2021C02069-5)+1 种基金the Pingyang County Science and Technology Strengthening Agriculture Industry Upgrading Project(No.2023PY003)the National Natural Science Foundation of China(No.41906107)。
文摘Our previous study found that feeding with Lactobacillus plantarum Ep-M17 could effectively affect the growth performance,immune response,and gut microbiota of Penaeus vannamei.However,high temperature and pressure during feed pelletizing is the main problem that can lead to a decrease in the activity of probiotics or cause their inactivation.Further investigation needs to investigate whether inactivated Ep-M17 can exert similar effects as live Ep-M17.Therefore,we evaluated the effects of inactivated L.plantarum Ep-M17 on growth performance,immune response,disease resistance,and gut microbiota in P.vannamei.Results show that adding inactivated Ep-M17 to the feed also promoted body weight gain and increased relative immune protection in shrimp.Also,histological examination revealed that the administration of inactivated Ep-M17 led to improvements in the density and distribution of microvilli in the intestines and enhancements in the abundance of B and R cells in the hepatopancreas.Additionally,the inactivated Ep-M17 supplementation resulted in increased activity levels of nutrient immune-related enzymes in both the shrimp hepatopancreas and intestines.Moreover,it stimulated the expression of Lvlec,PEN-3a,Crustin,LGBP,Lysozyme,and proPo genes in both the hepatopancreas and intestines.Furthermore,the inactivated Ep-M17 also increased bacterial diversity in the gut of shrimp and promoted the abundance of specific flora,facilitating the host organism’s metabolism and immunity to improve the disease resistance of shrimp.Therefore,supplementation of inactivated L.plantarum Ep-M17 in shrimp diets can exert similar effects as live L.plantarum Ep-M17 effectively improving growth performance,gut microbiota,immune response,and disease resistance in P.vannamei.
基金supported in part by the National Key Research and Development Program of China(Grant No.2020YFB1805005)in part by the National Natural Science Foundation of China(Grant No.62031019)in part by the European Commission through the H2020-MSCA-ITN META WIRELESS Research Project under Grant 956256。
文摘Channel prediction is critical to address the channel aging issue in mobile scenarios.Existing channel prediction techniques are mainly designed for discrete channel prediction,which can only predict the future channel in a fixed time slot per frame,while the other intra-frame channels are usually recovered by interpolation.However,these approaches suffer from a serious interpolation loss,especially for mobile millimeter-wave communications.To solve this challenging problem,we propose a tensor neural ordinary differential equation(TN-ODE)based continuous-time channel prediction scheme to realize the direct prediction of intra-frame channels.Specifically,inspired by the recently developed continuous mapping model named neural ODE in the field of machine learning,we first utilize the neural ODE model to predict future continuous-time channels.To improve the channel prediction accuracy and reduce computational complexity,we then propose the TN-ODE scheme to learn the structural characteristics of the high-dimensional channel by low-dimensional learnable transform.Simulation results show that the proposed scheme is able to achieve higher intra-frame channel prediction accuracy than existing schemes.
基金the National Natural Science Foundation of China(51774119,51374095,and 51604092)the primary research projects of critical scientific research in Henan Colleges and Universities(19zx003)+1 种基金Program for Innovative Research Team in University of Ministry of Education of China(IRT_16R22)State Key Laboratory Cultivation Base for Gas Geology and Gas Control(Henan Polytechnic University)(WS2018A02)。
文摘Coal seam gas content is frequently measured in quantity during underground coal mining operation and coalbed methane(CBM)exploration as a significant basic parameter.Due to the calculation error of lost gas and residual gas in the direct method,the efficiency and accuracy of the current methods are not inadequate to the large area multi-point measurement of coal seam gas content.This paper firstly deduces a simplified theoretical dynamic model for calculating lost gas based on gas dynamic diffusion theory.Secondly,the effects of various factors on gas dynamic diffusion from coal particle are experimentally studied.And sampling procedure of representative coal particle is improved.Thirdly,a new estimation method of residual gas content based on excess adsorption and competitive adsorption theory is proposed.The results showed that the maximum error of calculating the losing gas content by using the new simplified model is only 4%.Considering the influence of particle size on gas diffusion law,the particle size of the collected coal sample is below 0.25 mm,which improves the measurement speed and reflects the safety representativeness of the sample.The determination time of gas content reduced from 36 to 3 h/piece.Moreover,the absolute error is 0.15–0.50 m^3/t,and the relative error is within 5%.A new engineering method for determining the coal seam gas content is developed according to the above research.
