Photovoltaic (PV) technologies have attracted great interest due to their capability of generating electricity directly from sunlight. Machine learning(ML) is a technique for computer to learn how to perform a specifi...Photovoltaic (PV) technologies have attracted great interest due to their capability of generating electricity directly from sunlight. Machine learning(ML) is a technique for computer to learn how to perform a specific task using known data. It can be used in many areas and has become a hot research topic recently due to the rapid accumulation of data and advancement of computer hardware. The application of ML techniques in the design and fabrication of solar cells started slowly but has recently gained tremendous momentum. An exhaustive compilation of the literatures indicates that all the major aspects in the research and development of solar cells can be effectively assisted by ML techniques. If combined with other tools and fed with additional theoretical and experimental data, more accurate and robust results can be achieved from ML techniques. The aspects can be grouped into four categories:prediction of material properties,optimization of device structures, optimization of fabrication processes, and reconstruction of measurement data. A statistical analysis of the literatures shows that artificial neural network (ANN) and genetic algorithm (GA) are the two most applied ML techniques and the topics in the optimization of device structures and optimization of fabrication processes are more popular.This article can be used as a reference by all PV researchers who are interested in ML techniques.展开更多
The present trial was performed to reveal the regulatory effects of L-theanine on the levels of lipopolysaccharide(LPS)endotoxin within different biofluids,as well as relevant inflammatory responses of dairy cattle un...The present trial was performed to reveal the regulatory effects of L-theanine on the levels of lipopolysaccharide(LPS)endotoxin within different biofluids,as well as relevant inflammatory responses of dairy cattle under heat stress conditions.Thirty lactating Chinese Holstein dairy cattle(189±47 d in milk,and 2±1 parities)were allocated in a completely randomized design to each of 3 dietary treatments:the control(CON,0 g/d per cow L-theanine),the low L-theanine dosage treatment(LL,16 g/d per cow L-theanine),and the high L-theanine dosage treatment(HL,32 g/d per cow L-theanine).This trial consisted of 38 d(7 d for adaption and 31 d for data and sample collection),and sample collection for rumen liquid,blood plasma or serum,and milk were conducted on the d 27 and 38,respectively.Dairy cattle were constantly exposed to environmental heat stress during this experiment according to the recorded temperature-humidity index(THI).In the LL treatment,LPS concentration in rumen liquid was higher(P<0.05),whilst LPS densities in plasma and milk were lower(P<0.05)than those of the CON.Supplementing L-theanine at 2 dosages both significantly lowered(P<0.05)the level of interleukin(IL)-1βin the serum.Results of the present study suggested that L-theanine could be a promising additive in reducing the detrimental effects of heat stress on dairy cows,and L-theanine supplementation at 16 g/d per cow is preferred because it reduced the LPS translocation into the peripheral blood and LPS accumulation in the milk,as well as mitigated LPS-induced inflammatory reactions in dairy cows during heat stress.Further studies are necessitated to investigate the underlying mechanisms of L-theanine in LPS alteration and inflammation alleviation.展开更多
基金partialy supported by Nanchang University, under Research Grant 9166-2701010119
文摘Photovoltaic (PV) technologies have attracted great interest due to their capability of generating electricity directly from sunlight. Machine learning(ML) is a technique for computer to learn how to perform a specific task using known data. It can be used in many areas and has become a hot research topic recently due to the rapid accumulation of data and advancement of computer hardware. The application of ML techniques in the design and fabrication of solar cells started slowly but has recently gained tremendous momentum. An exhaustive compilation of the literatures indicates that all the major aspects in the research and development of solar cells can be effectively assisted by ML techniques. If combined with other tools and fed with additional theoretical and experimental data, more accurate and robust results can be achieved from ML techniques. The aspects can be grouped into four categories:prediction of material properties,optimization of device structures, optimization of fabrication processes, and reconstruction of measurement data. A statistical analysis of the literatures shows that artificial neural network (ANN) and genetic algorithm (GA) are the two most applied ML techniques and the topics in the optimization of device structures and optimization of fabrication processes are more popular.This article can be used as a reference by all PV researchers who are interested in ML techniques.
基金the funding through the Hunan Provincial Natural Science Foundation(Grant No.2019JJ50279,2019RS3021)Hunan Provincial Education Department(Grant No.19B257)+2 种基金Hunan Provincial Science and Technology Department(Grant No.2017NK1020)Ministry of Science and Technology of China(Grant No.2018YFD0501604)National Natural Science Foundation of China(Grant No.31772633)。
文摘The present trial was performed to reveal the regulatory effects of L-theanine on the levels of lipopolysaccharide(LPS)endotoxin within different biofluids,as well as relevant inflammatory responses of dairy cattle under heat stress conditions.Thirty lactating Chinese Holstein dairy cattle(189±47 d in milk,and 2±1 parities)were allocated in a completely randomized design to each of 3 dietary treatments:the control(CON,0 g/d per cow L-theanine),the low L-theanine dosage treatment(LL,16 g/d per cow L-theanine),and the high L-theanine dosage treatment(HL,32 g/d per cow L-theanine).This trial consisted of 38 d(7 d for adaption and 31 d for data and sample collection),and sample collection for rumen liquid,blood plasma or serum,and milk were conducted on the d 27 and 38,respectively.Dairy cattle were constantly exposed to environmental heat stress during this experiment according to the recorded temperature-humidity index(THI).In the LL treatment,LPS concentration in rumen liquid was higher(P<0.05),whilst LPS densities in plasma and milk were lower(P<0.05)than those of the CON.Supplementing L-theanine at 2 dosages both significantly lowered(P<0.05)the level of interleukin(IL)-1βin the serum.Results of the present study suggested that L-theanine could be a promising additive in reducing the detrimental effects of heat stress on dairy cows,and L-theanine supplementation at 16 g/d per cow is preferred because it reduced the LPS translocation into the peripheral blood and LPS accumulation in the milk,as well as mitigated LPS-induced inflammatory reactions in dairy cows during heat stress.Further studies are necessitated to investigate the underlying mechanisms of L-theanine in LPS alteration and inflammation alleviation.
