Ontologies have been used for several years in life sciences to formally represent concepts and reason about knowledge bases in domains such as the semantic web, information retrieval and artificial intelligence. The ...Ontologies have been used for several years in life sciences to formally represent concepts and reason about knowledge bases in domains such as the semantic web, information retrieval and artificial intelligence. The exploration of these domains for the correspondence of semantic content requires calculation of the measure of semantic similarity between concepts. Semantic similarity is a measure on a set of documents, based on the similarity of their meanings, which refers to the similarity between two concepts belonging to one or more ontologies. The similarity between concepts is also a quantitative measure of information, calculated based on the properties of concepts and their relationships. This study proposes a method for finding similarity between concepts in two different ontologies based on feature, information content and structure. More specifically, this means proposing a hybrid method using two existing measures to find the similarity between two concepts from different ontologies based on information content and the set of common superconcepts, which represents the set of common parent concepts. We simulated our method on datasets. The results show that our measure provides similarity values that are better than those reported in the literature.展开更多
Converting customer needs into specific forms and providing consumers with services are crucial in product design.Currently,conversion is no longer difficult due to the development of modern technology,and various mea...Converting customer needs into specific forms and providing consumers with services are crucial in product design.Currently,conversion is no longer difficult due to the development of modern technology,and various measures can be applied for product realization,thus increasing the complexity of analysis and evaluation in the design process.The focus of the design process has thus shifted from problem solving to minimizing the total amount of information content.This paper presents a New Hybrid Axiomatic Design(AD)Methodology based on iteratively matching and merging design parameters that meet the independence axiom and attribute constraints by applying trimming technology,the ideal final results,and technology evolution theory.The proposed method minimizes the total amount of information content and improves the design quality.Finally,a case study of a rehabilitation robot design for hemiplegic patients is presented.The results indicate that the iterative matching and merging of related attributes can minimize the total amount of information content,reduce the cost,and improve design efficiency.Additionally,evolutionary technology prediction can ensure product novelty and improve market competitiveness.The methodology provides an excellent way to design a new(or improved)product.展开更多
The information gap in the M&A market hinders acquirers from effectively identifying high-quality targets. We examine whether VC/PEs convey information content in the M&A market and whether acquirers can use s...The information gap in the M&A market hinders acquirers from effectively identifying high-quality targets. We examine whether VC/PEs convey information content in the M&A market and whether acquirers can use such information to identify high-quality targets. We show that VC/PEs have significant information content and can signal high-quality target companies via ‘‘certification". When acquirers lack acquisition experience and targets are located in inferior information environments, VC/PE ‘‘certification" is more significant.The better reputation a VC/PE has, the more information it conveys. Syndicate VC/PEs convey stronger information than independent VC/PEs. We also find that acquirers do not pay higher premiums for high-quality targets. Overall, our results suggest that VC/PEs have value relevance in the M&A market,confirming their ‘‘certification" role. We present means for acquirers to select high-quality targets and investors to build efficient portfolios.展开更多
Machine learning(ML)-based prediction models for mapping hazard(e.g.,landslide and debris flow)susceptibility have been widely developed in recent research.However,in some specific areas,ML models have limited applica...Machine learning(ML)-based prediction models for mapping hazard(e.g.,landslide and debris flow)susceptibility have been widely developed in recent research.However,in some specific areas,ML models have limited application because of the uncertainties in identifying negative samples.The Parlung Tsangpo Basin exemplifies a region prone to recurrent glacial debris flows(GDFs)and is characterized by a prominent landform featuring deep gullies.Considering the limitations of the ML model,we developed and compared two combined statistical models(FA-WE and FA-IC)based on factor analysis(FA),weight of evidence(WE),and the information content(IC)method.The final GDF susceptibility maps were generated by selecting 8 most important static factors and considering the influence of precipitation.The results show that the FA-IC model has the best performance.The areas with a very high susceptibility to GDFs are primarily located in the narrow valley section upstream,on both sides of the valley in the middle and downstream of the Parlung Tsangpo River,and in the narrow valley section of each tributary.These areas encompass 86 gullies and are characterized as"narrow and steep".展开更多
Genetic diversity of two chicken ecotypes from Ismailia-Egypt (ISM) and Taif-Saudi Arabia (TA) was evaluated using 39 microsatellites. DNA was extracted from blood of 25 chickens/ecotype. The number of alleles was 157...Genetic diversity of two chicken ecotypes from Ismailia-Egypt (ISM) and Taif-Saudi Arabia (TA) was evaluated using 39 microsatellites. DNA was extracted from blood of 25 chickens/ecotype. The number of alleles was 157 and 138, the number of alleles/locus averaged 4.2±2.2 and 3.6±1.6, and the highest number of private alleles was 9 and 5 for ISM and TA, respectively. Percentage of shared alleles between the two ecotypes was 45%. This panel of markers is reasonably informative as the mean polymorphic information content for ISM and TA was 0.47±0.21, and 0.41±0.2. Similar average of observed heterozygosity was attained for both ecotypes. Conversely, averages of expected heterozygosity differed between two ecotypes, 0.52±0.23 vs. 0.45±0.21 for ISM and TA. 8 and 12 loci have significantly deviated from HWE of ISM and TA. Estimate of genetic distance was 0.2 and F<sub>ST</sub> index was 0.29. Results showed only 6% of genetic diversity is shared between these two ecotypes.展开更多
Betula utilis D.Don.is an important species of alpine Himalaya and forms the major treeline component of western Himalaya.The different populations of B.utilis are declining and are under high risk.In the present stud...Betula utilis D.Don.is an important species of alpine Himalaya and forms the major treeline component of western Himalaya.The different populations of B.utilis are declining and are under high risk.In the present study,novel expressed sequence tag-simple sequence repeat(EST-SSR)primers were developed from expressed sequence tag(EST)data of different Betula species.Of the10,796 designed primers,the percentages of di-,tri-,tetra-,penta-,and hexa-repeats were 36%,35%,15%,5.5%and7.7%,respectively.For validation,50 primers were synthesized randomly and were characterized in 20 different B.utilis accessions from north-western Himalaya.Of these,45 primers amplified fragments in a range of 1-6.The 24 polymorphic primers produced 111 fragments in aggregate with 4.6 fragments on average.Polymorphism information content(PIC)ranged from 0.288 in marker BUMS-24 to 0.497 in BUMS-3 and BUMS-7,with an average of 0.447 among polymorphic markers.Dendrogram based on Jaccard’s similarity coefficient and UPGMA method showed that newly developed SSR markers distinguished twenty accessions of B.utilis into two groups.As no SSR markers were available in this species,the newly developed markers will foster molecular genetics research and conservation efforts for this species.展开更多
文摘Ontologies have been used for several years in life sciences to formally represent concepts and reason about knowledge bases in domains such as the semantic web, information retrieval and artificial intelligence. The exploration of these domains for the correspondence of semantic content requires calculation of the measure of semantic similarity between concepts. Semantic similarity is a measure on a set of documents, based on the similarity of their meanings, which refers to the similarity between two concepts belonging to one or more ontologies. The similarity between concepts is also a quantitative measure of information, calculated based on the properties of concepts and their relationships. This study proposes a method for finding similarity between concepts in two different ontologies based on feature, information content and structure. More specifically, this means proposing a hybrid method using two existing measures to find the similarity between two concepts from different ontologies based on information content and the set of common superconcepts, which represents the set of common parent concepts. We simulated our method on datasets. The results show that our measure provides similarity values that are better than those reported in the literature.
基金Supported by Research Startup Fund Project of Fujian University of Technology(Grant No.GY-Z20089)Science Foundation for Young Scholars of Fujian Province of China(Grant No.2018J05099)Education and Scientific Research Projects of Young Teachers in Fujian Province of China(Grant No.JAT160313).
文摘Converting customer needs into specific forms and providing consumers with services are crucial in product design.Currently,conversion is no longer difficult due to the development of modern technology,and various measures can be applied for product realization,thus increasing the complexity of analysis and evaluation in the design process.The focus of the design process has thus shifted from problem solving to minimizing the total amount of information content.This paper presents a New Hybrid Axiomatic Design(AD)Methodology based on iteratively matching and merging design parameters that meet the independence axiom and attribute constraints by applying trimming technology,the ideal final results,and technology evolution theory.The proposed method minimizes the total amount of information content and improves the design quality.Finally,a case study of a rehabilitation robot design for hemiplegic patients is presented.The results indicate that the iterative matching and merging of related attributes can minimize the total amount of information content,reduce the cost,and improve design efficiency.Additionally,evolutionary technology prediction can ensure product novelty and improve market competitiveness.The methodology provides an excellent way to design a new(or improved)product.
基金by the National Natural Science Foundation of China (Project Nos. 71702038 71572201+1 种基金 71672204)the Natural Science Foundation of Guangdong Province (Project No. 2015A030313074)
文摘The information gap in the M&A market hinders acquirers from effectively identifying high-quality targets. We examine whether VC/PEs convey information content in the M&A market and whether acquirers can use such information to identify high-quality targets. We show that VC/PEs have significant information content and can signal high-quality target companies via ‘‘certification". When acquirers lack acquisition experience and targets are located in inferior information environments, VC/PE ‘‘certification" is more significant.The better reputation a VC/PE has, the more information it conveys. Syndicate VC/PEs convey stronger information than independent VC/PEs. We also find that acquirers do not pay higher premiums for high-quality targets. Overall, our results suggest that VC/PEs have value relevance in the M&A market,confirming their ‘‘certification" role. We present means for acquirers to select high-quality targets and investors to build efficient portfolios.
基金funded by the National Natural Science Foundation of China(Grant Nos.42377170).
文摘Machine learning(ML)-based prediction models for mapping hazard(e.g.,landslide and debris flow)susceptibility have been widely developed in recent research.However,in some specific areas,ML models have limited application because of the uncertainties in identifying negative samples.The Parlung Tsangpo Basin exemplifies a region prone to recurrent glacial debris flows(GDFs)and is characterized by a prominent landform featuring deep gullies.Considering the limitations of the ML model,we developed and compared two combined statistical models(FA-WE and FA-IC)based on factor analysis(FA),weight of evidence(WE),and the information content(IC)method.The final GDF susceptibility maps were generated by selecting 8 most important static factors and considering the influence of precipitation.The results show that the FA-IC model has the best performance.The areas with a very high susceptibility to GDFs are primarily located in the narrow valley section upstream,on both sides of the valley in the middle and downstream of the Parlung Tsangpo River,and in the narrow valley section of each tributary.These areas encompass 86 gullies and are characterized as"narrow and steep".
文摘Genetic diversity of two chicken ecotypes from Ismailia-Egypt (ISM) and Taif-Saudi Arabia (TA) was evaluated using 39 microsatellites. DNA was extracted from blood of 25 chickens/ecotype. The number of alleles was 157 and 138, the number of alleles/locus averaged 4.2±2.2 and 3.6±1.6, and the highest number of private alleles was 9 and 5 for ISM and TA, respectively. Percentage of shared alleles between the two ecotypes was 45%. This panel of markers is reasonably informative as the mean polymorphic information content for ISM and TA was 0.47±0.21, and 0.41±0.2. Similar average of observed heterozygosity was attained for both ecotypes. Conversely, averages of expected heterozygosity differed between two ecotypes, 0.52±0.23 vs. 0.45±0.21 for ISM and TA. 8 and 12 loci have significantly deviated from HWE of ISM and TA. Estimate of genetic distance was 0.2 and F<sub>ST</sub> index was 0.29. Results showed only 6% of genetic diversity is shared between these two ecotypes.
基金This work was nancially supported by DBT-IPLS scheme[Reference No.BT/PR4548/INF/22/146/2012].
文摘Betula utilis D.Don.is an important species of alpine Himalaya and forms the major treeline component of western Himalaya.The different populations of B.utilis are declining and are under high risk.In the present study,novel expressed sequence tag-simple sequence repeat(EST-SSR)primers were developed from expressed sequence tag(EST)data of different Betula species.Of the10,796 designed primers,the percentages of di-,tri-,tetra-,penta-,and hexa-repeats were 36%,35%,15%,5.5%and7.7%,respectively.For validation,50 primers were synthesized randomly and were characterized in 20 different B.utilis accessions from north-western Himalaya.Of these,45 primers amplified fragments in a range of 1-6.The 24 polymorphic primers produced 111 fragments in aggregate with 4.6 fragments on average.Polymorphism information content(PIC)ranged from 0.288 in marker BUMS-24 to 0.497 in BUMS-3 and BUMS-7,with an average of 0.447 among polymorphic markers.Dendrogram based on Jaccard’s similarity coefficient and UPGMA method showed that newly developed SSR markers distinguished twenty accessions of B.utilis into two groups.As no SSR markers were available in this species,the newly developed markers will foster molecular genetics research and conservation efforts for this species.
