In order to enhance grain sampling efficiency, in this work a truss type multi-rod grain sampling machine is designed and tested. The sampling machine primarily consists of truss support mechanism, main carriage mecha...In order to enhance grain sampling efficiency, in this work a truss type multi-rod grain sampling machine is designed and tested. The sampling machine primarily consists of truss support mechanism, main carriage mechanism, auxiliary carriage mechanism, sampling rods, and a PLC controller. The movement of the main carriage on the truss, the auxiliary carriage on the main carriage, and the vertical movement of the sampling rods on the auxiliary carriage are controlled through PLC programming. The sampling machine accurately controls the position of the sampling rods, enabling random sampling with six rods to ensure comprehensive and random sampling. Additionally, sampling experiments were conducted, and the results showed that the multi-rod grain sampling machine simultaneously samples with six rods, achieving a sampling frequency of 38 times per hour. The round trip time for the sampling rods is 33 seconds per cycle, and the sampling length direction reaches 18 m. This study provides valuable insights for the design of multi-rod grain sampling machines.展开更多
In order to improve the dust absorption performance of the reverse blowing pickup mouth, the gas-solid flow motion properties inside the reverse blowing pickup mouth were simulated by using computational fluid dynamic...In order to improve the dust absorption performance of the reverse blowing pickup mouth, the gas-solid flow motion properties inside the reverse blowing pickup mouth were simulated by using computational fluid dynamics( CFD) software,Fluent.The results show that both the front baffle inclination angle and the pressure drop across the pickup mouth have significant impacts on dust absorption performance. As the inclination angle is increased,there is an increase in the overall and grade removal efficiency. As the front baffle inclination angle or pressure drop is increased,there is an increase in the overall and grade removal efficiencies.However,pressure drop affects energy consumption. Front baffle inclination angle and pressure drop are optimized. Optimal inclination angle and pressure drop are 105° and 2 300 Pa respectively. Sample machine is made and measured,which further verifies the appropriateness of numerical simulation and practicability of optimum strategy.展开更多
Microplastics(MPs),pervasive environmental pollutants,have infiltrated human tissues,raising global health concerns.This study investigated the distribution and characteristics of MPs across seven major human organs(l...Microplastics(MPs),pervasive environmental pollutants,have infiltrated human tissues,raising global health concerns.This study investigated the distribution and characteristics of MPs across seven major human organs(lungs,heart,liver,spleen,brain,kidneys,and small intestine)using Raman imaging and machine learning.Tissue samples from eight donors were analyzed for MP presence and characteristics.A deep learningenhanced U-Net model segmented MPs in Raman images,while a random forest classifier was employed to identify organ-specific MP attribution using 120 imaging features.Animal models supported the systemic distribution of MPs.MPs were ubiquitous across all organs examined.The highest MP abundance was observed in the liver(65.28±23.94 particles/g),small intestine(61.06±25.25 particles/g),and kidneys(58.63±16.50 particles/g).Organ-specific variations in MP characteristics were identified:larger particles dominated the lungs(56.80±57.70μm),while smaller particles(<10μm)prevailed in the liver and spleen.Distinct polymer compositions and shape profiles were observed for each organ.The random forest classifier achieved 72.73%accuracy in organ-specific MP attribution.MP abundance was linked to organ vascularity.The findings highlight organ-specific risks of MPs and provide a framework for assessing health impacts,thus guiding targeted interventions to mitigate exposure.展开更多
文摘In order to enhance grain sampling efficiency, in this work a truss type multi-rod grain sampling machine is designed and tested. The sampling machine primarily consists of truss support mechanism, main carriage mechanism, auxiliary carriage mechanism, sampling rods, and a PLC controller. The movement of the main carriage on the truss, the auxiliary carriage on the main carriage, and the vertical movement of the sampling rods on the auxiliary carriage are controlled through PLC programming. The sampling machine accurately controls the position of the sampling rods, enabling random sampling with six rods to ensure comprehensive and random sampling. Additionally, sampling experiments were conducted, and the results showed that the multi-rod grain sampling machine simultaneously samples with six rods, achieving a sampling frequency of 38 times per hour. The round trip time for the sampling rods is 33 seconds per cycle, and the sampling length direction reaches 18 m. This study provides valuable insights for the design of multi-rod grain sampling machines.
基金National Natural Science Foundation of China(No.51375202)
文摘In order to improve the dust absorption performance of the reverse blowing pickup mouth, the gas-solid flow motion properties inside the reverse blowing pickup mouth were simulated by using computational fluid dynamics( CFD) software,Fluent.The results show that both the front baffle inclination angle and the pressure drop across the pickup mouth have significant impacts on dust absorption performance. As the inclination angle is increased,there is an increase in the overall and grade removal efficiency. As the front baffle inclination angle or pressure drop is increased,there is an increase in the overall and grade removal efficiencies.However,pressure drop affects energy consumption. Front baffle inclination angle and pressure drop are optimized. Optimal inclination angle and pressure drop are 105° and 2 300 Pa respectively. Sample machine is made and measured,which further verifies the appropriateness of numerical simulation and practicability of optimum strategy.
基金supported by the National Natural Science Foundation of China(82271913 and 42277207)the Shaanxi Province Key Industrial Innovation Chain under grant 2023-ZDLSF-12,the Shaanxi Provincial Natural Science Foundation General Project-General Program(2023-JC-YB-751)+1 种基金the FMMU special research project of crosscooperation(2024JC044)the Fundamental Research Funds for the Central Universities(GK202401003).
文摘Microplastics(MPs),pervasive environmental pollutants,have infiltrated human tissues,raising global health concerns.This study investigated the distribution and characteristics of MPs across seven major human organs(lungs,heart,liver,spleen,brain,kidneys,and small intestine)using Raman imaging and machine learning.Tissue samples from eight donors were analyzed for MP presence and characteristics.A deep learningenhanced U-Net model segmented MPs in Raman images,while a random forest classifier was employed to identify organ-specific MP attribution using 120 imaging features.Animal models supported the systemic distribution of MPs.MPs were ubiquitous across all organs examined.The highest MP abundance was observed in the liver(65.28±23.94 particles/g),small intestine(61.06±25.25 particles/g),and kidneys(58.63±16.50 particles/g).Organ-specific variations in MP characteristics were identified:larger particles dominated the lungs(56.80±57.70μm),while smaller particles(<10μm)prevailed in the liver and spleen.Distinct polymer compositions and shape profiles were observed for each organ.The random forest classifier achieved 72.73%accuracy in organ-specific MP attribution.MP abundance was linked to organ vascularity.The findings highlight organ-specific risks of MPs and provide a framework for assessing health impacts,thus guiding targeted interventions to mitigate exposure.
