This paper is the second part of the new evaluation of atomic masses, AME2012. From the results of a leastsquares calculation, described in Part I, for all accepted experimental data, we derive here tables and graphs ...This paper is the second part of the new evaluation of atomic masses, AME2012. From the results of a leastsquares calculation, described in Part I, for all accepted experimental data, we derive here tables and graphs to replace those of AME2003. The first table lists atomic masses. It is followed by a table of the influences of data on primary nuclides, a table of separation energies and reaction energies, and finally, a series of graphs of separation and decay energies. The last section in this paper lists all references to the input data used in Part I of this AME2012 and also to the data included in the NUBASE2012 evaluation （first paper in this issue）.展开更多
A genetic algorithm to solve the set covering problem proposed in the literature had some improvements which gave better solutions, i.e., better chromosomes in the first starting population, taking full account of do...A genetic algorithm to solve the set covering problem proposed in the literature had some improvements which gave better solutions, i.e., better chromosomes in the first starting population, taking full account of domain specific knowledge with sound programming skill. We have further investigated the input data dependency of their genetic algorithm, i.e., the dependency on costs and density. We have found that for input problem data sets with densities greater than or equal to 3%, our genetic algorithm is still practical both in computing time and approximation ratio.展开更多
Gridded model assessments require at least one climatic and one soil database for carrying out the simulations.There are several parallel soil and climate database development projects that provide sufficient,albeit c...Gridded model assessments require at least one climatic and one soil database for carrying out the simulations.There are several parallel soil and climate database development projects that provide sufficient,albeit considerably different,observation based input data for crop model based impact studies.The input database related uncertainty of the Biome-BGCMuSo agro-environmental model outputs was investigated using three and four different gridded climatic and soil databases,respectively covering an area of nearly 100.000 km2 with 1104 grid cells.Spatial,temporal,climate and soil database selection related variances were calculated and compared for four model outputs obtained from 30-year-long simulations.The choice of the input database introduced model output variability that was comparable to the variability the year-to-year change of the weather or the spatial heterogeneity of the soil causes.Input database selection could be a decisive factor in carbon sequestration related studies as the soil carbon stock change estimates may either suggest that the simulated ecosystem is a carbon sink or to the contrary a carbon source on the long run.Careful evaluation of the input database quality seems to be an inevitable and highly relevant step towards more realistic plant production and carbon balance simulations.展开更多
Discrete event simulation(DES)is a well-established decision support tool in modeling work flows in manufacturing industry.But,there are an amount of practical and financial obstacles that deter the employment of this...Discrete event simulation(DES)is a well-established decision support tool in modeling work flows in manufacturing industry.But,there are an amount of practical and financial obstacles that deter the employment of this technology in industry.One of the main weaknesses of operating DES is the costs spent on collecting and mapping input data from different enterprise data resources into a DES model.Another issue is the cost of integrating simulation applications with other manufacturing applications.These barriers hinder the automated input of data into DES models and as a result deter use of real-time DES in manufacturing.This review presents the existing research studies in the literature that address the above issues,demonstrating in parallel the already implemented concepts.The scope of this review is to provide an overview of the input data phase,focusing on its automation and motivating researchers to re-examine this phase by highlighting future research directions.展开更多
This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a...This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a novel dynamic linearization data model for the partially constrained combined spacecraft with external disturbances is established. The generalized disturbances composed of external disturbances and dynamic linearization errors are then reconstructed by a Discrete Extended State Observer(DESO). With the dynamic linearization data model and reconstructed information, a DESO-MFAC strategy for the combined spacecraft is proposed based only on input and output data. Next, the input saturation is overcome by introducing an antiwindup compensator. Finally, numerical simulations are carried out to demonstrate the effectiveness and feasibility of the proposed controller when the dynamic properties of the partially constrained combined spacecraft are completely unknown.展开更多
The study focuses on estimating the input power of a power plant from available data, using the theoretical inverter efficiency as the key parameter. The paper addresses the problem of missing data in power generation...The study focuses on estimating the input power of a power plant from available data, using the theoretical inverter efficiency as the key parameter. The paper addresses the problem of missing data in power generation systems and proposes an approach based on the efficiency formula widely documented in the literature. In the absence of input data, this method makes it possible to estimate the plant’s input power using data extracted from the site, in particular that provided by the Ministry of the Environment. The importance of this study lies in the need to accurately determine the input power in order to assess the overall performance of the energy system.展开更多
Antibodies currently comprise the predominant treatment modality for a variety of diseases;therefore,optimizing their properties rapidly and efficiently is an indispensable step in antibody-based drug development.Insp...Antibodies currently comprise the predominant treatment modality for a variety of diseases;therefore,optimizing their properties rapidly and efficiently is an indispensable step in antibody-based drug development.Inspired by the great success of artificial intelligence-based algorithms,especially deep learning-based methods in the field of biology,various computational methods have been introduced into antibody optimization to reduce costs and increase the success rate of lead candidate generation and optimization.Herein,we briefly review recent progress in deep learning-based antibody optimization,focusing on the available datasets and algorithm input data types that are crucial for constructing appropriate deep learning models.Furthermore,we discuss the current challenges and potential solutions for the future development of general-purpose deep learning algorithms in antibody optimization.展开更多
文摘This paper is the second part of the new evaluation of atomic masses, AME2012. From the results of a leastsquares calculation, described in Part I, for all accepted experimental data, we derive here tables and graphs to replace those of AME2003. The first table lists atomic masses. It is followed by a table of the influences of data on primary nuclides, a table of separation energies and reaction energies, and finally, a series of graphs of separation and decay energies. The last section in this paper lists all references to the input data used in Part I of this AME2012 and also to the data included in the NUBASE2012 evaluation （first paper in this issue）.
文摘A genetic algorithm to solve the set covering problem proposed in the literature had some improvements which gave better solutions, i.e., better chromosomes in the first starting population, taking full account of domain specific knowledge with sound programming skill. We have further investigated the input data dependency of their genetic algorithm, i.e., the dependency on costs and density. We have found that for input problem data sets with densities greater than or equal to 3%, our genetic algorithm is still practical both in computing time and approximation ratio.
基金supported by Széchenyi 2020 programme,the European Regional Development Fund‘Investing in your future’,the Hungarian Government:[grant number GINOP-2.3.2-15-2016-00028]Hungarian Scientific Research Fund:[grant number FK-128709,K-129118]+1 种基金Advanced research supporting the forestry and wood-processing sector's adaptation to global change and the 4thindustrial revolution[grant number CZ.02.1.01/0.0/0.0/16_019/0000803]financed by Operational Programme Research,Development and EducationJános Bolyai Research Scholarship of the Hungarian Academy of Sciences:[grant number BO/00088/18/4 and BO/00254/20/10].
文摘Gridded model assessments require at least one climatic and one soil database for carrying out the simulations.There are several parallel soil and climate database development projects that provide sufficient,albeit considerably different,observation based input data for crop model based impact studies.The input database related uncertainty of the Biome-BGCMuSo agro-environmental model outputs was investigated using three and four different gridded climatic and soil databases,respectively covering an area of nearly 100.000 km2 with 1104 grid cells.Spatial,temporal,climate and soil database selection related variances were calculated and compared for four model outputs obtained from 30-year-long simulations.The choice of the input database introduced model output variability that was comparable to the variability the year-to-year change of the weather or the spatial heterogeneity of the soil causes.Input database selection could be a decisive factor in carbon sequestration related studies as the soil carbon stock change estimates may either suggest that the simulated ecosystem is a carbon sink or to the contrary a carbon source on the long run.Careful evaluation of the input database quality seems to be an inevitable and highly relevant step towards more realistic plant production and carbon balance simulations.
基金This research is funded by the EU Seventh Framework Programme under grant agreement n° 314364.
文摘Discrete event simulation(DES)is a well-established decision support tool in modeling work flows in manufacturing industry.But,there are an amount of practical and financial obstacles that deter the employment of this technology in industry.One of the main weaknesses of operating DES is the costs spent on collecting and mapping input data from different enterprise data resources into a DES model.Another issue is the cost of integrating simulation applications with other manufacturing applications.These barriers hinder the automated input of data into DES models and as a result deter use of real-time DES in manufacturing.This review presents the existing research studies in the literature that address the above issues,demonstrating in parallel the already implemented concepts.The scope of this review is to provide an overview of the input data phase,focusing on its automation and motivating researchers to re-examine this phase by highlighting future research directions.
基金supported by National Natural Science Foundation of China(Nos.61603114,61673135)the Fundamental Research Funds for the Central Universities of China(No.HIT.NSRIF.201826)
文摘This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a novel dynamic linearization data model for the partially constrained combined spacecraft with external disturbances is established. The generalized disturbances composed of external disturbances and dynamic linearization errors are then reconstructed by a Discrete Extended State Observer(DESO). With the dynamic linearization data model and reconstructed information, a DESO-MFAC strategy for the combined spacecraft is proposed based only on input and output data. Next, the input saturation is overcome by introducing an antiwindup compensator. Finally, numerical simulations are carried out to demonstrate the effectiveness and feasibility of the proposed controller when the dynamic properties of the partially constrained combined spacecraft are completely unknown.
文摘The study focuses on estimating the input power of a power plant from available data, using the theoretical inverter efficiency as the key parameter. The paper addresses the problem of missing data in power generation systems and proposes an approach based on the efficiency formula widely documented in the literature. In the absence of input data, this method makes it possible to estimate the plant’s input power using data extracted from the site, in particular that provided by the Ministry of the Environment. The importance of this study lies in the need to accurately determine the input power in order to assess the overall performance of the energy system.
基金supported by the National Natural Science Foundation of China(No.12104396)the National Key R&D Program of China(Nos.2021YFF1200404 and 2021YFA1201200)+2 种基金the National Independent Innovation Demonstration Zone Shanghai Zhangjiang Major Projects(No.ZJZX2020014)the Starry Night Science Fund at Shanghai Institute for Advanced Study of Zhejiang University(No.SN-ZJU-SIAS-003)the Shanghai Artificial Intelligence Lab(No.P22KN00272),China.
文摘Antibodies currently comprise the predominant treatment modality for a variety of diseases;therefore,optimizing their properties rapidly and efficiently is an indispensable step in antibody-based drug development.Inspired by the great success of artificial intelligence-based algorithms,especially deep learning-based methods in the field of biology,various computational methods have been introduced into antibody optimization to reduce costs and increase the success rate of lead candidate generation and optimization.Herein,we briefly review recent progress in deep learning-based antibody optimization,focusing on the available datasets and algorithm input data types that are crucial for constructing appropriate deep learning models.Furthermore,we discuss the current challenges and potential solutions for the future development of general-purpose deep learning algorithms in antibody optimization.
