Taxonomy plays an important role in understanding the origin, evolution, and ecological functionality of biodiversity. There are large number of unknown species yet to be described by taxonomists, which together with ...Taxonomy plays an important role in understanding the origin, evolution, and ecological functionality of biodiversity. There are large number of unknown species yet to be described by taxonomists, which together with their ecosystem services cannot be effectively protected prior to description. Despite this, taxonomy has been increasingly underrated insufficient funds and permanent positions to retain young talents. Further, the impact factordriven evaluation systems in China exacerbate this downward trend, so alternative evaluation metrics are urgently necessary. When the current generation of outstanding taxonomists retires,there will be too few remaining taxonomists left to train the next generation. In light of these challenges, all co-authors worked together on this paper to analyze the current situation of taxonomy and put out a joint call for immediate actions to advance taxonomy in China.展开更多
This paper presents a simple proof for the stability of circular perfectly matched layer(PML)methods for solving acoustic scattering problems in two and three dimensions.The medium function of PML allows arbitrary-ord...This paper presents a simple proof for the stability of circular perfectly matched layer(PML)methods for solving acoustic scattering problems in two and three dimensions.The medium function of PML allows arbitrary-order polynomials,and can be extended to general nondecreasing functions with a slight modification of the proof.In the regime of high wavenumbers,the inf-sup constant for the PML truncated problem is shown to be O(k^(-1)).Moreover,the PML solution converges to the exact solution exponentially,with a wavenumber-explicit rate,as either the thickness or medium property of PML increases.Numerical experiments are presented to verify the theories and performances of PML for variant polynomial degrees.展开更多
The forecasting of time-series data plays an important role in various domains. It is of significance in theory and application to improve prediction accuracy of the time-series data. With the progress in the study of...The forecasting of time-series data plays an important role in various domains. It is of significance in theory and application to improve prediction accuracy of the time-series data. With the progress in the study of time-series, time-series forecasting model becomes more complicated, and consequently great concern has been drawn to the techniques in designing the forecasting model. A modeling method which is easy to use by engineers and may generate good results is in urgent need. In this paper, a gradient-boost AR ensemble learning algorithm (AREL) is put forward. The effectiveness of AREL is assessed by theoretical analyses, and it is demonstrated that this method can build a strong predictive model by assembling a set of AR models. In order to avoid fitting exactly any single training example, an insensitive loss function is introduced in the AREL algorithm, and accordingly the influence of random noise is reduced. To further enhance the capability of AREL algorithm for non-stationary time-series, improve the robustness of algorithm, discourage overfitting, and reduce sensitivity of algorithm to parameter settings, a weighted kNN prediction method based on AREL algorithm is presented. The results of numerical testing on real data demonstrate that the proposed modeling method and prediction method are effective.展开更多
Operation scheduling for a class of production systems with"instantly consumed"products is very important.It is challenging to satisfy the real time system demand and to consider the realizability of the pro...Operation scheduling for a class of production systems with"instantly consumed"products is very important.It is challenging to satisfy the real time system demand and to consider the realizability of the production schedules.This paper formulates a new model for optimization based production scheduling problems with integral constraints.Based on the detailed analysis of the production rate constraints,it is proved that this type of optimization problems is equivalent to a smooth nonlinear programming problem.The reachable upper and lower bounds of the production amount in every period can be expressed as functions of two variables,i.e.,the production rate at the start and end of that period.It is also proved that the gradients of these functions are monotonic,and their convexity or concavity is guaranteed.When the production cost function is convex,this type of optimization problems is equivalent to a convex programming problem.With the above analysis,a two-stage solution method is developed to solve the production scheduling problems with integral constraints,and in many applications the global optimal solution can be obtained efficiently.With the new model and solution method,the difficulties caused by the constraints on production rate can be overcome and the optimal schedule can be obtained with the real time system demand satisfied.Numerical testing for scheduling of electric power production systems is performed and the testing results are discussed.It is demonstrated that the new model and solution method are effective.展开更多
With the improvement of electricity markets,the gradual aggravation of energy shortage and the environment pollution,it is urgent to formulate a new model to precisely satisfy the system demand for energy and reserve....With the improvement of electricity markets,the gradual aggravation of energy shortage and the environment pollution,it is urgent to formulate a new model to precisely satisfy the system demand for energy and reserve.Currently,power system opti-mization dispatching is always formulated as a discrete-time scheduling model.In this paper,we first demonstrate through an example that the upper and lower bounds of spinning reserve offered by a unit,given in the discrete-time model framework as constraints,is unreachable.This causes the problem that the reserve delivery obtained by the discrete-time scheduling model cannot be carried out precisely.From the detailed analysis of the ramp rate constraints,it is proved that the reachable upper and lower bounds of spinning reserve in every period can be expressed as functions of two variables,i.e.,generation level of unit at the start and end of this period.Thus,a new method is provided to calculate the upper and lower bounds of spinning reserve which are reachable in average.Furthermore,a new model based on this proposed method for joint scheduling of generation and reserve is presented,which considers the ability to realize the scheduled energy and reserve delivery.It converts the opti-mization based accurate scheduling for generation and reserve of power system from a continuous-time optimal control prob-lem to a nonlinear programming problem.Therefore,the proposed model can avoid the difficulties in solving a continu-ous-time optimal control problem.Based on the sequential quadratic programming method,numerical experiments for sched-uling electric power production systems are performed to evaluate the model and the results show that the new model is highly effective.展开更多
Wireless sensor networks have a wide range of applications. Sensing coverage and communication coverage are two fundamental quality of service. In this paper, we present our work on energy efficient sensing coverage a...Wireless sensor networks have a wide range of applications. Sensing coverage and communication coverage are two fundamental quality of service. In this paper, we present our work on energy efficient sensing coverage and communication. We design several schemes for sensing coverage subject to different requirements and constraints respectively. We also propose a broadcasting communication protocol with high energy efficiency and low latency for large scale sensor networks based on the Small World network theory. Simulation and experiment results show that our schemes and protocol have good performance.展开更多
Resource planning for a remanufacturing system is in general extremely difficult in terms of problem size,uncertainties,complicated constraints,etc.In this paper,we present a new method based on constrained ordinal op...Resource planning for a remanufacturing system is in general extremely difficult in terms of problem size,uncertainties,complicated constraints,etc.In this paper,we present a new method based on constrained ordinal optimization(COO)for remanufacturing planning.The key idea of our method is to estimate the feasibility of plans by machine learning and to select a subset with the estimated feasibility based on the procedure of horse racing with feasibility model(HRFM).Numerical testing shows that our method is efficient and effective for selecting good plans with high probability.It is thus a scalable optimization method for large scale remanufacturing planning problems with complicated stochastic constraints.展开更多
Phytopathogenic fungi have attracted great attention as a promising source for new drug discovery.In the progress of our ongoing study for bioactive natural products from an in-house phytopathogenic fungi library,a pa...Phytopathogenic fungi have attracted great attention as a promising source for new drug discovery.In the progress of our ongoing study for bioactive natural products from an in-house phytopathogenic fungi library,a pathogenic fungus,Fusarium proliferatum strain 13294(FP13294),was selected for chemical investigation.Two novel aliphatic unsaturated alcohols named fusariumnols A and B(1 and 2),together with one previously characterized sesquiterpenoid lignoren(3)were identified.Structures of 1-3 were assigned by mass spectrometry and NMR spectroscopy.Their bioactivities were assessed against Staphylococcus epidermidis,S.aureus,and Methicillin-resistant S.aureus(MRSA).Compounds 1 and 2 exhibited weak antibacterial activity against S.epidermidis(MIC=100μM).展开更多
基金mainly supported by National Science Fund for Distinguished Young Scholars (31625024)a grant (2008DP173354) from the Key Laboratory of the Zoological Systematics and Evolution of the Chinese Academy of Sciences。
文摘Taxonomy plays an important role in understanding the origin, evolution, and ecological functionality of biodiversity. There are large number of unknown species yet to be described by taxonomists, which together with their ecosystem services cannot be effectively protected prior to description. Despite this, taxonomy has been increasingly underrated insufficient funds and permanent positions to retain young talents. Further, the impact factordriven evaluation systems in China exacerbate this downward trend, so alternative evaluation metrics are urgently necessary. When the current generation of outstanding taxonomists retires,there will be too few remaining taxonomists left to train the next generation. In light of these challenges, all co-authors worked together on this paper to analyze the current situation of taxonomy and put out a joint call for immediate actions to advance taxonomy in China.
基金supported by the National Key R&D Program of China(Grant Nos.2019YFA0709600,2019YFA0709602).
文摘This paper presents a simple proof for the stability of circular perfectly matched layer(PML)methods for solving acoustic scattering problems in two and three dimensions.The medium function of PML allows arbitrary-order polynomials,and can be extended to general nondecreasing functions with a slight modification of the proof.In the regime of high wavenumbers,the inf-sup constant for the PML truncated problem is shown to be O(k^(-1)).Moreover,the PML solution converges to the exact solution exponentially,with a wavenumber-explicit rate,as either the thickness or medium property of PML increases.Numerical experiments are presented to verify the theories and performances of PML for variant polynomial degrees.
基金supported by the National Natural Science Foundation of China (Grant No. 60974101)Program for New Century Talents of Education Ministry of China (Grant No. NCET-06-0828)
文摘The forecasting of time-series data plays an important role in various domains. It is of significance in theory and application to improve prediction accuracy of the time-series data. With the progress in the study of time-series, time-series forecasting model becomes more complicated, and consequently great concern has been drawn to the techniques in designing the forecasting model. A modeling method which is easy to use by engineers and may generate good results is in urgent need. In this paper, a gradient-boost AR ensemble learning algorithm (AREL) is put forward. The effectiveness of AREL is assessed by theoretical analyses, and it is demonstrated that this method can build a strong predictive model by assembling a set of AR models. In order to avoid fitting exactly any single training example, an insensitive loss function is introduced in the AREL algorithm, and accordingly the influence of random noise is reduced. To further enhance the capability of AREL algorithm for non-stationary time-series, improve the robustness of algorithm, discourage overfitting, and reduce sensitivity of algorithm to parameter settings, a weighted kNN prediction method based on AREL algorithm is presented. The results of numerical testing on real data demonstrate that the proposed modeling method and prediction method are effective.
基金Supported in part by the National Natural Science Foundation of China(Grant Nos.60736027,60704033)the National High Technology Research and Development Program of China(863 Program)(Grant No.2007AA04Z154)111 International Collaboration Program of China and Program for New Century Talents of Education Ministry of China(Grant No.NCET-08-0432)
文摘Operation scheduling for a class of production systems with"instantly consumed"products is very important.It is challenging to satisfy the real time system demand and to consider the realizability of the production schedules.This paper formulates a new model for optimization based production scheduling problems with integral constraints.Based on the detailed analysis of the production rate constraints,it is proved that this type of optimization problems is equivalent to a smooth nonlinear programming problem.The reachable upper and lower bounds of the production amount in every period can be expressed as functions of two variables,i.e.,the production rate at the start and end of that period.It is also proved that the gradients of these functions are monotonic,and their convexity or concavity is guaranteed.When the production cost function is convex,this type of optimization problems is equivalent to a convex programming problem.With the above analysis,a two-stage solution method is developed to solve the production scheduling problems with integral constraints,and in many applications the global optimal solution can be obtained efficiently.With the new model and solution method,the difficulties caused by the constraints on production rate can be overcome and the optimal schedule can be obtained with the real time system demand satisfied.Numerical testing for scheduling of electric power production systems is performed and the testing results are discussed.It is demonstrated that the new model and solution method are effective.
基金supported by the National Natural Science Foundation of China(Grant Nos.60921003,60736027,61174161,60974101)the Spe-cialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20090121110022)+3 种基金the Fundamental Research Funds for the Central Universities of Xiamen University(Grant Nos.2011121047,201112G018,CXB2011035)the Key Research Project of Fujian Province of China(Grant No.2009H0044)Xiamen University National 211 3rd Period Project of China)(Grant No.0630-E72000)the Natural Sci-ence Foundation of Fujian Province,China(Grant No.2011J05154)
文摘With the improvement of electricity markets,the gradual aggravation of energy shortage and the environment pollution,it is urgent to formulate a new model to precisely satisfy the system demand for energy and reserve.Currently,power system opti-mization dispatching is always formulated as a discrete-time scheduling model.In this paper,we first demonstrate through an example that the upper and lower bounds of spinning reserve offered by a unit,given in the discrete-time model framework as constraints,is unreachable.This causes the problem that the reserve delivery obtained by the discrete-time scheduling model cannot be carried out precisely.From the detailed analysis of the ramp rate constraints,it is proved that the reachable upper and lower bounds of spinning reserve in every period can be expressed as functions of two variables,i.e.,generation level of unit at the start and end of this period.Thus,a new method is provided to calculate the upper and lower bounds of spinning reserve which are reachable in average.Furthermore,a new model based on this proposed method for joint scheduling of generation and reserve is presented,which considers the ability to realize the scheduled energy and reserve delivery.It converts the opti-mization based accurate scheduling for generation and reserve of power system from a continuous-time optimal control prob-lem to a nonlinear programming problem.Therefore,the proposed model can avoid the difficulties in solving a continu-ous-time optimal control problem.Based on the sequential quadratic programming method,numerical experiments for sched-uling electric power production systems are performed to evaluate the model and the results show that the new model is highly effective.
基金The research is supported in part by National Natural Science Foundation （No. 60574087, 60574064） and the ＂111 International Collaboration Project＂ of China.
文摘Wireless sensor networks have a wide range of applications. Sensing coverage and communication coverage are two fundamental quality of service. In this paper, we present our work on energy efficient sensing coverage and communication. We design several schemes for sensing coverage subject to different requirements and constraints respectively. We also propose a broadcasting communication protocol with high energy efficiency and low latency for large scale sensor networks based on the Small World network theory. Simulation and experiment results show that our schemes and protocol have good performance.
基金The research presented in this paper was supported in part by the National Natural Science Foundation of China(Grant Nos.60274011,60574087,60704008,and 90924001)the National High Technology Research and Development Program of China(Grant No.2007AA04Z154)+2 种基金the Program for New Century Excellent Talents in University(NCET-04-0094)the Specialized Research Fund for the Doctoral Program of Higher Education(20070003110)the 111 International Collaboration Project(B06002).
文摘Resource planning for a remanufacturing system is in general extremely difficult in terms of problem size,uncertainties,complicated constraints,etc.In this paper,we present a new method based on constrained ordinal optimization(COO)for remanufacturing planning.The key idea of our method is to estimate the feasibility of plans by machine learning and to select a subset with the estimated feasibility based on the procedure of horse racing with feasibility model(HRFM).Numerical testing shows that our method is efficient and effective for selecting good plans with high probability.It is thus a scalable optimization method for large scale remanufacturing planning problems with complicated stochastic constraints.
基金This work was supported by the National Key Research and Development Program of China(2020YFA0907200,2019YFA0906200,and 2020YFA0907800)the National Natural Science Foundation of China(21877038,21907031,21977029,31720103901,and 81903529)+1 种基金Shanghai Rising-Star Program(20QA1402800)the Open Project Funding of the State Key Laboratory of Bioreactor Engineering,and the 111 Project(B18022).
文摘Phytopathogenic fungi have attracted great attention as a promising source for new drug discovery.In the progress of our ongoing study for bioactive natural products from an in-house phytopathogenic fungi library,a pathogenic fungus,Fusarium proliferatum strain 13294(FP13294),was selected for chemical investigation.Two novel aliphatic unsaturated alcohols named fusariumnols A and B(1 and 2),together with one previously characterized sesquiterpenoid lignoren(3)were identified.Structures of 1-3 were assigned by mass spectrometry and NMR spectroscopy.Their bioactivities were assessed against Staphylococcus epidermidis,S.aureus,and Methicillin-resistant S.aureus(MRSA).Compounds 1 and 2 exhibited weak antibacterial activity against S.epidermidis(MIC=100μM).
