Dual-band electrochromic devices capable of the spectral-selective modulation of visible(VIS)light and near-infrared(NIR)can notably reduce the energy consumption of buildings and improve the occupants’visual and the...Dual-band electrochromic devices capable of the spectral-selective modulation of visible(VIS)light and near-infrared(NIR)can notably reduce the energy consumption of buildings and improve the occupants’visual and thermal comfort.However,the low optical modulation and poor durability of these devices severely limit its practical applications.Herein,we demonstrate an efficient and flexible bifunctional dual-band electrochromic device which not only shows excellent spectral-selective electrochromic performance with a high optical modulation and a long cycle life,but also displays a high capacitance and a high energy recycling efficiency of 51.4%,integrating energy-saving with energy-storage.The nanowires structure and abundant oxygen-vacancies of oxygen-deficient tungsten oxide nanowires endows it high flexibility and a high optical modulation of 73.1%and 85.3%at 633 and 1200 nm respectively.The prototype device assembled can modulate the VIS light and NIR independently and effectively through three distinct modes with a long cycle life(3.3%capacity loss after 10,000 cycles)and a high energy-saving performance(8.8℃lower than the common glass).Furthermore,simulations also demonstrate that our device outperforms the commercial low-emissivity glass in terms of energy-saving in most climatic zones around the world.Such windows represent an intriguing potential technology to improve the building energy efficiency.展开更多
Fast and accurate forecasting of schedulable capacity of electric vehicles(EVs)plays an important role in enabling the integration of EVs into future smart grids as distributed energy storage systems.Traditional metho...Fast and accurate forecasting of schedulable capacity of electric vehicles(EVs)plays an important role in enabling the integration of EVs into future smart grids as distributed energy storage systems.Traditional methods are insufficient to deal with large-scale actual schedulable capacity data.This paper proposes forecasting models for schedulable capacity of EVs through the parallel gradient boosting decision tree algorithm and big data analysis for multi-time scales.The time scale of these data analysis comprises the real time of one minute,ultra-short-term of one hour and one-day-ahead scale of 24 hours.The predicted results for different time scales can be used for various ancillary services.The proposed algorithm is validated using operation data of 521 EVs in the field.The results show that compared with other machine learning methods such as the parallel random forest algorithm and parallel k-nearest neighbor algorithm,the proposed algorithm requires less training time with better forecasting accuracy and analytical processing ability in big data environment.展开更多
Recent evidences show that nervous system acts as a crucial part of cancer microenvironment.Infiltration of nerve fibers into cancer microenvironment has an important active role in cancer progression.The stimulations...Recent evidences show that nervous system acts as a crucial part of cancer microenvironment.Infiltration of nerve fibers into cancer microenvironment has an important active role in cancer progression.The stimulations of both cancer growth and metastasis by members of nervous system such as neurons and glial cells have been demonstrated.However,how the nervous system is built in cancer is largely unknown.Here we show that a fraction of cancer stem cells(CSCs)derived from patients with gastric carcinoma and colorectal carcinoma are capable of producing neurons that are involved in tumor neurogenesis and tumor growth.Cancer stem cell monoclone derived from a single cancer stem cell was able to generate neurons including sympathetic and parasympathetic neurons to take part in the nervous system in cancer tissues.Knocking down the neural cell generating capability of the human CSCs inhibited the growth of xenograft tumors in mouse model.Our data demonstrate that human CSCs are able to produce one of most important components in the cancer microenvironment that are required for cancer development and progression.展开更多
基金support from the National Natural Science Foundation of China(Grant No.62105148)China Postdoctoral Science Foundation(2022TQ0148 and 2023M731651)Postgraduate Research&Practice Innovation Program of NUAA(xcxjh20230609).
文摘Dual-band electrochromic devices capable of the spectral-selective modulation of visible(VIS)light and near-infrared(NIR)can notably reduce the energy consumption of buildings and improve the occupants’visual and thermal comfort.However,the low optical modulation and poor durability of these devices severely limit its practical applications.Herein,we demonstrate an efficient and flexible bifunctional dual-band electrochromic device which not only shows excellent spectral-selective electrochromic performance with a high optical modulation and a long cycle life,but also displays a high capacitance and a high energy recycling efficiency of 51.4%,integrating energy-saving with energy-storage.The nanowires structure and abundant oxygen-vacancies of oxygen-deficient tungsten oxide nanowires endows it high flexibility and a high optical modulation of 73.1%and 85.3%at 633 and 1200 nm respectively.The prototype device assembled can modulate the VIS light and NIR independently and effectively through three distinct modes with a long cycle life(3.3%capacity loss after 10,000 cycles)and a high energy-saving performance(8.8℃lower than the common glass).Furthermore,simulations also demonstrate that our device outperforms the commercial low-emissivity glass in terms of energy-saving in most climatic zones around the world.Such windows represent an intriguing potential technology to improve the building energy efficiency.
基金supported by National Natural Science Foundation of China(No.51577047)International Collaboration Project supported by Bureau of Science and Technology,Anhui Province(No.1604b0602015).
文摘Fast and accurate forecasting of schedulable capacity of electric vehicles(EVs)plays an important role in enabling the integration of EVs into future smart grids as distributed energy storage systems.Traditional methods are insufficient to deal with large-scale actual schedulable capacity data.This paper proposes forecasting models for schedulable capacity of EVs through the parallel gradient boosting decision tree algorithm and big data analysis for multi-time scales.The time scale of these data analysis comprises the real time of one minute,ultra-short-term of one hour and one-day-ahead scale of 24 hours.The predicted results for different time scales can be used for various ancillary services.The proposed algorithm is validated using operation data of 521 EVs in the field.The results show that compared with other machine learning methods such as the parallel random forest algorithm and parallel k-nearest neighbor algorithm,the proposed algorithm requires less training time with better forecasting accuracy and analytical processing ability in big data environment.
基金This work was supported by the National Basic Research Program of China(to XM 2015CB942800)the Nature Science Foundation of China(to XM 81361120381to CF 81402446).
文摘Recent evidences show that nervous system acts as a crucial part of cancer microenvironment.Infiltration of nerve fibers into cancer microenvironment has an important active role in cancer progression.The stimulations of both cancer growth and metastasis by members of nervous system such as neurons and glial cells have been demonstrated.However,how the nervous system is built in cancer is largely unknown.Here we show that a fraction of cancer stem cells(CSCs)derived from patients with gastric carcinoma and colorectal carcinoma are capable of producing neurons that are involved in tumor neurogenesis and tumor growth.Cancer stem cell monoclone derived from a single cancer stem cell was able to generate neurons including sympathetic and parasympathetic neurons to take part in the nervous system in cancer tissues.Knocking down the neural cell generating capability of the human CSCs inhibited the growth of xenograft tumors in mouse model.Our data demonstrate that human CSCs are able to produce one of most important components in the cancer microenvironment that are required for cancer development and progression.
