Semiconductor photocatalysts are extensively applied in environmental treatment and energy conversion.However,one of their major disadvantages is their relatively low photocatalytic performance owing to the recombinat...Semiconductor photocatalysts are extensively applied in environmental treatment and energy conversion.However,one of their major disadvantages is their relatively low photocatalytic performance owing to the recombination of generated electron-hole pairs.The presence of the phase junction is an effective way to promote the photocatalytic activity by increasing the separation efficiency of the electron-hole pairs.Accordingly,extensive research has been conducted on the design of phase junctions of photocatalysts to improve their charge transfer properties and efficiencies.Therefore,for the design of an appropriate phase junction and the understanding of the mechanism of electron-hole separation,the development of the photocatalytic phase junction,including the preparation methods of the heterogeneous materials,is tremendously important and helpful.Herein,the commonly used,externally induced phase transformation fabrication techniques and the primary components of the semiconductors are reviewed.Future directions will still focus on the design and optimization of the phase junction of photocatalytic materials according to the phase transition with higher efficiencies for broadband responses and solar energy utilization.Additionally,the most popular phase transformation fabrication techniques of phase junctions are briefly reviewed from the application viewpoint.展开更多
The hippocampus is considerably important in terms of its phylogenetic origins and participates in an extensive array of cognitive tasks and behaviors[1].The hippocampus can be partitioned into subfields based on its ...The hippocampus is considerably important in terms of its phylogenetic origins and participates in an extensive array of cognitive tasks and behaviors[1].The hippocampus can be partitioned into subfields based on its cytoarchitectonic variation and circuits:the dentate gyrus(DG),cornu ammonis(CA1-CA4),and subiculum(Sub).展开更多
The intrinsic neural timescale(INT)provides temporal windows in brain activity that process information of different durations,crucial for the integration and segregation of external inputs and ultimately shaping cogn...The intrinsic neural timescale(INT)provides temporal windows in brain activity that process information of different durations,crucial for the integration and segregation of external inputs and ultimately shaping cognition and behavior.Recent research has uncovered a pronounced INT hierarchy along the adult hippocampus's longaxis.Yet,the development of INT organization within the hippocampus—particularly the pattern of its hierarchical structure and its impact on cognitive development—has not been thoroughly investigated in youth.Here,we discovered that the INT distribution in youth presents a distinct hierarchical structure along both posterioranterior and proximal-distal axes of the hippocampus.Strikingly,this hierarchical structure correlates signifi-cantly with the first principal gradient of the hippocampal-cortical functional connectome and the thickness of hippocampal grey matter.Furthermore,we observed notable changes in the hippocampal INT landscape during youth,characterized by a general narrowing of timescales,alongside dedifferentiation along the hippocampal organizational axes.These maturational changes significantly link to improvements in inhibitory control and working memory performance.Collectively,our findings reveal the developmental patterns of temporal integration and segregation hierarchies within hippocampus,and highlights the profound significance of INT as a neural underpinning that orchestrates cognitive growth.展开更多
Here,we report a novel visible-light-driven I^(-)doped Bi_(2)O_(2)CO_(3)nano-sheet photocatalyst synthesized via a facile ion exchange route at room temperature.This obtained Bi_(2)O_(2)CO_(3)nano-sheet with I^(-)dopi...Here,we report a novel visible-light-driven I^(-)doped Bi_(2)O_(2)CO_(3)nano-sheet photocatalyst synthesized via a facile ion exchange route at room temperature.This obtained Bi_(2)O_(2)CO_(3)nano-sheet with I^(-)doping shows several ad-vantages.The specific surface area of I_(0.875)-Bi_(2)O_(2)CO_(3)is 2.16 times higher than that of Bi_(2)O_(2)CO_(3),providing more catalytic sites for the degradation reactions.Moreover,a 3.2 times photocurrent enhancement is observed in I_(0.875)-Bi_(2)O_(2)CO_(3)compared with Bi_(2)O_(2)CO_(3),producing more photogenerated electron-hole pairs for degradation.The synergistic effect between texture property and photoelectric effect boosts the removal of organic pollutants.Under visible light illumination,I_(0.875)-Bi_(2)O_(2)CO_(3)displays superior photocatalytic performance for the degradation of methyl orange(MO)and phenol.Notably,a phenol degradation rate,88%,is achieved by I_(0.875)-Bi_(2)O_(2)CO_(3)with illuminating for 60 min,which is about 29 times higher than that of pristine Bi_(2)O_(2)CO_(3).This finding may provide an opportunity to develop a promising I^(-)doped catalyst for organic pollutants removal.展开更多
Previous studies have shown that amnestic mild cognitive impairment(aMCI)involves in the morphological abnormalities of multiple regions,including cortical thickness,sulcus depth,surface area,gray matter volume,jacobi...Previous studies have shown that amnestic mild cognitive impairment(aMCI)involves in the morphological abnormalities of multiple regions,including cortical thickness,sulcus depth,surface area,gray matter volume,jacobian metric and average curvature.All the measures have unique neuropathological and genetic meanings.However,most existing methods simply average or concatenate these measures when constructing the classifiers,which may include redundant information and ignore the relationships among them.In this study,we treat each measure as a task in our multitask learning framework.Considering the actual situation that we do not know the correlation between tasks in advance,we use a robust multitask feature learning(rMTFL)method to select a group of features among correlated measures and provide additional information by identifying outlier tasks at the same time.Then,we train several SVM classifiers and for each measure,we input the selected features into the corresponding SVM classifier.Finally,we use an ensemble classification strategy to combine the results of these classifiers based on the accuracy to make the final prediction.We use the leave-one-out cross-validation to evaluate our proposed method with 46 amnestic mild cognitive impairment(aMCI)and 52 normal controls(NC).The results show that rMTFL algorithm is superior to the group lasso method and average curvature is the outlier task based on multidimensional surface measures.展开更多
基金supported by the National Natural Science Foundation of China(21707055,21567008,21607064)Program of Qingjiang Excellent Young Talents,Jiangxi University of Science and Technology,Program of 5511 Talents in Scientific and Technological Innovation of Jiangxi Province(20165BCB18014)+3 种基金Academic and Technical Leaders of the Main Disciplines in Jiangxi Province(20172BCB22018)Jiangxi Province Natural Science Foundation(20161BAB203090,20181BAB213010,20181BAB203018)Young Science Foundation of Jiangxi Province Education Office(GJJ160671)Open Project Program of the State Key Laboratory of Photocatalysis on Energy and Environment(SKLPEE-KF201712)in Fuzhou University基金来源:国家自然科学基金(21707055,21567008,21607064)~~
文摘Semiconductor photocatalysts are extensively applied in environmental treatment and energy conversion.However,one of their major disadvantages is their relatively low photocatalytic performance owing to the recombination of generated electron-hole pairs.The presence of the phase junction is an effective way to promote the photocatalytic activity by increasing the separation efficiency of the electron-hole pairs.Accordingly,extensive research has been conducted on the design of phase junctions of photocatalysts to improve their charge transfer properties and efficiencies.Therefore,for the design of an appropriate phase junction and the understanding of the mechanism of electron-hole separation,the development of the photocatalytic phase junction,including the preparation methods of the heterogeneous materials,is tremendously important and helpful.Herein,the commonly used,externally induced phase transformation fabrication techniques and the primary components of the semiconductors are reviewed.Future directions will still focus on the design and optimization of the phase junction of photocatalytic materials according to the phase transition with higher efficiencies for broadband responses and solar energy utilization.Additionally,the most popular phase transformation fabrication techniques of phase junctions are briefly reviewed from the application viewpoint.
基金supported by the Scientific and Technological Innovation 2030-Major Projects(2021ZD0200500)the National Natural Science Foundation of China(32271146 and 82021004)the Startup Funds for Top-notch Talents at Beijing Normal University。
文摘The hippocampus is considerably important in terms of its phylogenetic origins and participates in an extensive array of cognitive tasks and behaviors[1].The hippocampus can be partitioned into subfields based on its cytoarchitectonic variation and circuits:the dentate gyrus(DG),cornu ammonis(CA1-CA4),and subiculum(Sub).
基金Shuyu Li is supported by the National Natural Science Foundation of China(32271146)the Startup Funds for Top-notch Talents at Beijing Normal University。
文摘The intrinsic neural timescale(INT)provides temporal windows in brain activity that process information of different durations,crucial for the integration and segregation of external inputs and ultimately shaping cognition and behavior.Recent research has uncovered a pronounced INT hierarchy along the adult hippocampus's longaxis.Yet,the development of INT organization within the hippocampus—particularly the pattern of its hierarchical structure and its impact on cognitive development—has not been thoroughly investigated in youth.Here,we discovered that the INT distribution in youth presents a distinct hierarchical structure along both posterioranterior and proximal-distal axes of the hippocampus.Strikingly,this hierarchical structure correlates signifi-cantly with the first principal gradient of the hippocampal-cortical functional connectome and the thickness of hippocampal grey matter.Furthermore,we observed notable changes in the hippocampal INT landscape during youth,characterized by a general narrowing of timescales,alongside dedifferentiation along the hippocampal organizational axes.These maturational changes significantly link to improvements in inhibitory control and working memory performance.Collectively,our findings reveal the developmental patterns of temporal integration and segregation hierarchies within hippocampus,and highlights the profound significance of INT as a neural underpinning that orchestrates cognitive growth.
基金the National Natural Science Foundation of China(No.22272034)Environment and Energy Green Catalysis Innovation Team of Colleges and Universities of Guangdong Province(2022KCXTD019)+2 种基金Maoming City Science and Technology Project(2023SZX034)2024 Provincial Student Innovation Training Project(24B096)Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme(2019).
文摘Here,we report a novel visible-light-driven I^(-)doped Bi_(2)O_(2)CO_(3)nano-sheet photocatalyst synthesized via a facile ion exchange route at room temperature.This obtained Bi_(2)O_(2)CO_(3)nano-sheet with I^(-)doping shows several ad-vantages.The specific surface area of I_(0.875)-Bi_(2)O_(2)CO_(3)is 2.16 times higher than that of Bi_(2)O_(2)CO_(3),providing more catalytic sites for the degradation reactions.Moreover,a 3.2 times photocurrent enhancement is observed in I_(0.875)-Bi_(2)O_(2)CO_(3)compared with Bi_(2)O_(2)CO_(3),producing more photogenerated electron-hole pairs for degradation.The synergistic effect between texture property and photoelectric effect boosts the removal of organic pollutants.Under visible light illumination,I_(0.875)-Bi_(2)O_(2)CO_(3)displays superior photocatalytic performance for the degradation of methyl orange(MO)and phenol.Notably,a phenol degradation rate,88%,is achieved by I_(0.875)-Bi_(2)O_(2)CO_(3)with illuminating for 60 min,which is about 29 times higher than that of pristine Bi_(2)O_(2)CO_(3).This finding may provide an opportunity to develop a promising I^(-)doped catalyst for organic pollutants removal.
基金supported by the National Key Research and Development Program of China(2016YFC1306300)the National Natural Science Foundation of China(Grant No.61633018,81622025 and 81471731)Beijing Municipal Commission of Health and Family Planning(PXM2019_026283_000002)。
文摘Previous studies have shown that amnestic mild cognitive impairment(aMCI)involves in the morphological abnormalities of multiple regions,including cortical thickness,sulcus depth,surface area,gray matter volume,jacobian metric and average curvature.All the measures have unique neuropathological and genetic meanings.However,most existing methods simply average or concatenate these measures when constructing the classifiers,which may include redundant information and ignore the relationships among them.In this study,we treat each measure as a task in our multitask learning framework.Considering the actual situation that we do not know the correlation between tasks in advance,we use a robust multitask feature learning(rMTFL)method to select a group of features among correlated measures and provide additional information by identifying outlier tasks at the same time.Then,we train several SVM classifiers and for each measure,we input the selected features into the corresponding SVM classifier.Finally,we use an ensemble classification strategy to combine the results of these classifiers based on the accuracy to make the final prediction.We use the leave-one-out cross-validation to evaluate our proposed method with 46 amnestic mild cognitive impairment(aMCI)and 52 normal controls(NC).The results show that rMTFL algorithm is superior to the group lasso method and average curvature is the outlier task based on multidimensional surface measures.
