Chemical species and organic aerosol(OA)sources of atmospheric non-refractory particulate matter(NR-PM)were compared between Beijing and Tianjin during warm seasons.Beijing exhibits superior PM2.5 control efficacy,...Chemical species and organic aerosol(OA)sources of atmospheric non-refractory particulate matter(NR-PM)were compared between Beijing and Tianjin during warm seasons.Beijing exhibits superior PM2.5 control efficacy,with consistently lower concentrations and better spatial uniformity than those in Tianjin.Tianjin shows higher concentrations of OA,nitrate,and ammonium.The secondary OA(SOA)composition differs significantly between the two cities.Tianjin suffers severer photochemical pollution with higher O3 and oxidant levels,revealing stronger atmospheric oxidation capacity.Beijing s dominant wind directions feature alternating northerly and southerly winds,while Tianjin is characterized by persistent easterly and southerly flows.This difference in wind patterns results in a 5-h disparity in the diurnal peak timing of NR-PM2.5 between the two cities.Additionally,compositional and meteorological differences lead to distinct pollution formation mechanisms.Tianjin shows pronounced nocturnal accumulation of primary emissions,while Beijing demonstrates more stable nighttime levels.Source analysis highlights Beijing's effective vehicle emission control despite its larger vehicle fleet.Tianjin's peak hourly increase rate of COA is 1.8 times Beijing's in spring but only 0.4 times in summer.Sharing control experience and co-developing a real-time,high-resolution“cooking-traffic”emission inventory will help both cities refine source-specific controls.Both cities face PM2.5-O3 co-pollution challenges,more severe in Tianjin,with secondary inorganic aerosols dominating during high pollution episodes.Furthermore,our results underscore the necessity for enhanced regional collaborative governance to combat secondary pollution.Pollutants transport to Tianjin are dominated by southerly and easterly transport,whereas Beijing is primarily influenced by southerly transport and nearby northwestern regions.展开更多
To address the difficulty in self-starting for vertical-axis water turbines with fixed pitch angles and to improve the efficiency of marine energy utilization,a hybrid power generation device was proposed that incorpo...To address the difficulty in self-starting for vertical-axis water turbines with fixed pitch angles and to improve the efficiency of marine energy utilization,a hybrid power generation device was proposed that incorporated a Savonius-type wind rotor to assist in starting the vertical-axis water turbine.Numerical simulations were conducted to investigate the dynamic output characteristics of this integrated device.Firstly,a three-dimensional two-phase flow numerical tank was constructed using Fluent software,and the mesh partitioning scheme was determined by comparing the values of the power output parameters of the device under different mesh densities,and at the same time,the validity of the numerical tank was confirmed.Secondly,the established numerical tank was used to simulate the variation law of torque,speed and power coefficient of power generation devices under different flow field conditions with different water wheel blade numbers,radius ratios and height ratios.The results show that the device performs better in terms of torque stability,speed characteristics,and energy utilization in the simulated working condition range when the water wheel blades are 3 to 4,the radius ratio is 0.25 to 0.375,and the height ratio is 1/6 to 1/3.The device is able to start quickly in the presence of wind,and the power coefficient reaches 0.3 to 0.4 or even exceeds 0.4,with good starting and power generation performance.The research results can provide a reference for the design and application of the device.展开更多
Background Yueju Pill,a classic traditional Chinese medicine,shows antidepressant effects rapidly.However,biomarkers that can predict its treatment outcomes in major depressive disorder(MDD)are still lacking.Multimoda...Background Yueju Pill,a classic traditional Chinese medicine,shows antidepressant effects rapidly.However,biomarkers that can predict its treatment outcomes in major depressive disorder(MDD)are still lacking.Multimodal magnetic resonance imaging(MRI)offers a promising avenue to identify such biomarkers.Aims This pilot study aimed to explore whether therapeutic responses to Yueju Pill could be predicted by MRI-derived brain networks and to identify drug-specific biomarkers in comparison to escitalopram,a mainstream antidepressant.Methods We collected multimodal MRI data and blood samples from 28 outpatients with MDD from the Fourth People's Hospital of Taizhou,who were randomly divided into two groups to receive either Yueju Pill(23 gime/day)or escitalopram(10 mg,two times a day)for 4 days.Morphological and functional brain networks were constructed and used to predict individual changes in symptoms quantified by the 24-item Hamilton Depression Scale(HAMD-24)scores and serum brain-derived neurotrophic factor(BDNF)levels.Results After the treatment,both groups exhibited significant reductions in the HAMD-24 scores,while only the Yueju Pill group showed significant increases in the BDNF levels.Gyrification Index-based morphological networks predicted change rates of the HAMD-24 scores in both groups,but sulcus depth-based and cortical thickness-based morphological networks predicted change rates of the HAMD-24 scores and BDNF levels,respectively,only in the Yueju Pill group.Subnetwork analyses revealed that the visual network independently predicted the changes in both the HAMD-24 scores(sulcus depth-based networks)and BDNF levels(cortical thickness-based networks)following Yueju Pill treatment.Conclusions Morphological but not functional brain networks can predict symptom improvement and BDNF changes of patients with MDD after Yueju Pill treatment.Sulcus depth-based and cortical thickness-based morphological brain networks,particularly their visual subnetworks,might serve as Yueju Pill-specific biomarkers for predicting the therapeutic responses.These findings have the potential to guide personalised therapy for patients with MDD early in the therapeutic process.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(No.2025JBMC046)the National Natural Science Foundation of China(No.42475114)the National Key Development Program(No.2023YFC3709500)。
摘要Chemical species and organic aerosol(OA)sources of atmospheric non-refractory particulate matter(NR-PM)were compared between Beijing and Tianjin during warm seasons.Beijing exhibits superior PM2.5 control efficacy,with consistently lower concentrations and better spatial uniformity than those in Tianjin.Tianjin shows higher concentrations of OA,nitrate,and ammonium.The secondary OA(SOA)composition differs significantly between the two cities.Tianjin suffers severer photochemical pollution with higher O3 and oxidant levels,revealing stronger atmospheric oxidation capacity.Beijing s dominant wind directions feature alternating northerly and southerly winds,while Tianjin is characterized by persistent easterly and southerly flows.This difference in wind patterns results in a 5-h disparity in the diurnal peak timing of NR-PM2.5 between the two cities.Additionally,compositional and meteorological differences lead to distinct pollution formation mechanisms.Tianjin shows pronounced nocturnal accumulation of primary emissions,while Beijing demonstrates more stable nighttime levels.Source analysis highlights Beijing's effective vehicle emission control despite its larger vehicle fleet.Tianjin's peak hourly increase rate of COA is 1.8 times Beijing's in spring but only 0.4 times in summer.Sharing control experience and co-developing a real-time,high-resolution“cooking-traffic”emission inventory will help both cities refine source-specific controls.Both cities face PM2.5-O3 co-pollution challenges,more severe in Tianjin,with secondary inorganic aerosols dominating during high pollution episodes.Furthermore,our results underscore the necessity for enhanced regional collaborative governance to combat secondary pollution.Pollutants transport to Tianjin are dominated by southerly and easterly transport,whereas Beijing is primarily influenced by southerly transport and nearby northwestern regions.
摘要To address the difficulty in self-starting for vertical-axis water turbines with fixed pitch angles and to improve the efficiency of marine energy utilization,a hybrid power generation device was proposed that incorporated a Savonius-type wind rotor to assist in starting the vertical-axis water turbine.Numerical simulations were conducted to investigate the dynamic output characteristics of this integrated device.Firstly,a three-dimensional two-phase flow numerical tank was constructed using Fluent software,and the mesh partitioning scheme was determined by comparing the values of the power output parameters of the device under different mesh densities,and at the same time,the validity of the numerical tank was confirmed.Secondly,the established numerical tank was used to simulate the variation law of torque,speed and power coefficient of power generation devices under different flow field conditions with different water wheel blade numbers,radius ratios and height ratios.The results show that the device performs better in terms of torque stability,speed characteristics,and energy utilization in the simulated working condition range when the water wheel blades are 3 to 4,the radius ratio is 0.25 to 0.375,and the height ratio is 1/6 to 1/3.The device is able to start quickly in the presence of wind,and the power coefficient reaches 0.3 to 0.4 or even exceeds 0.4,with good starting and power generation performance.The research results can provide a reference for the design and application of the device.
基金supported by the National Key Research and Development Program of China(No.2022YFE0201000)National Natural Science Foundation of China(Nos.82472092,82174002,81874374 and 81673625)+2 种基金a grant from the Research Center for Brain Cognition and Human Development,Guangdong,China(No.2024B0303390003)Key Realm R&D Program of Guangzhou(No.202206010109)Taizhou Science and Technology Support Program(Social Development)project(No.TS2016-12).
摘要Background Yueju Pill,a classic traditional Chinese medicine,shows antidepressant effects rapidly.However,biomarkers that can predict its treatment outcomes in major depressive disorder(MDD)are still lacking.Multimodal magnetic resonance imaging(MRI)offers a promising avenue to identify such biomarkers.Aims This pilot study aimed to explore whether therapeutic responses to Yueju Pill could be predicted by MRI-derived brain networks and to identify drug-specific biomarkers in comparison to escitalopram,a mainstream antidepressant.Methods We collected multimodal MRI data and blood samples from 28 outpatients with MDD from the Fourth People's Hospital of Taizhou,who were randomly divided into two groups to receive either Yueju Pill(23 gime/day)or escitalopram(10 mg,two times a day)for 4 days.Morphological and functional brain networks were constructed and used to predict individual changes in symptoms quantified by the 24-item Hamilton Depression Scale(HAMD-24)scores and serum brain-derived neurotrophic factor(BDNF)levels.Results After the treatment,both groups exhibited significant reductions in the HAMD-24 scores,while only the Yueju Pill group showed significant increases in the BDNF levels.Gyrification Index-based morphological networks predicted change rates of the HAMD-24 scores in both groups,but sulcus depth-based and cortical thickness-based morphological networks predicted change rates of the HAMD-24 scores and BDNF levels,respectively,only in the Yueju Pill group.Subnetwork analyses revealed that the visual network independently predicted the changes in both the HAMD-24 scores(sulcus depth-based networks)and BDNF levels(cortical thickness-based networks)following Yueju Pill treatment.Conclusions Morphological but not functional brain networks can predict symptom improvement and BDNF changes of patients with MDD after Yueju Pill treatment.Sulcus depth-based and cortical thickness-based morphological brain networks,particularly their visual subnetworks,might serve as Yueju Pill-specific biomarkers for predicting the therapeutic responses.These findings have the potential to guide personalised therapy for patients with MDD early in the therapeutic process.