Purpose:Building on Leydesdorff,Bornmann,and Mingers(2019),we elaborate the differences between Tsinghua and Zhejiang University as an empirical example.We address the question of whether differences are statistically...Purpose:Building on Leydesdorff,Bornmann,and Mingers(2019),we elaborate the differences between Tsinghua and Zhejiang University as an empirical example.We address the question of whether differences are statistically significant in the rankings of Chinese universities.We propose methods for measuring statistical significance among different universities within or among countries.Design/methodology/approach:Based on z-testing and overlapping confidence intervals,and using data about 205 Chinese universities included in the Leiden Rankings 2020,we argue that three main groups of Chinese research universities can be distinguished(low,middle,and high).Findings:When the sample of 205 Chinese universities is merged with the 197 US universities included in Leiden Rankings 2020,the results similarly indicate three main groups:low,middle,and high.Using this data(Leiden Rankings and Web of Science),the z-scores of the Chinese universities are significantly below those of the US universities albeit with some overlap.Research limitations:We show empirically that differences in ranking may be due to changes in the data,the models,or the modeling effects on the data.The scientometric groupings are not always stable when we use different methods.Practical implications:Differences among universities can be tested for their statistical significance.The statistics relativize the values of decimals in the rankings.One can operate with a scheme of low/middle/high in policy debates and leave the more fine-grained rankings of individual universities to operational management and local settings.Originality/value:In the discussion about the rankings of universities,the question of whether differences are statistically significant,has,in our opinion,insufficiently been addressed in research evaluations.展开更多
Figs (Moracea: Ficus) and fig wasps (Hymenoptera: Chlocloids: Agaonideae) depend on each other to complete their reproduction. Monoecious fig species and their pollinating wasps are in conflict over the use of fig ov...Figs (Moracea: Ficus) and fig wasps (Hymenoptera: Chlocloids: Agaonideae) depend on each other to complete their reproduction. Monoecious fig species and their pollinating wasps are in conflict over the use of fig ovaries which can either produce one seed or one wasp. From observation on Ficus virens Ait., we showed that female flowers with outer layer of ovaries (near to the wall of syconium) had no significant difference from that with inner and interval layer of ovaries (near to the syconium cavity), in which most seeds and wasps were produced. This meant that fig tree provided the same potential resource for seed and wasps production. Observation indicated that there was usually only one foundress in syconium at female flower phase and no com- petition pollinators. Measurement of the style length of female flowers and the ovipositor of pollinators indicated that most ovaries could be reached by pollinator’s ovipositor. However, at the male flower phase, production of seeds was significantly more than that of wasps including non-pollinating wasps but there was no significant difference between seed and pollinating wasp production when without non-pollinating wasps produced. This result indicated that non-pollinating wasps competed ovaries not with seeds but with pollinating wasps for ovipositing. Bagged experiment showed that the sampling fig species was not self-sterile which was important for figs and wasps to survive bad season. Seed production in self-pollinated figs was not significantly different from total wasps in- cluding non-pollinating ones. This might be related with the weaker competition among wasps since bagged figs were not easy to reach by wasps from outside.展开更多
Objective： To discuss strategies and methods of normalization on how to deal with and analyze data for different chips with the combination of statistics, mathematics and bioinformatics in order to find significant d...Objective： To discuss strategies and methods of normalization on how to deal with and analyze data for different chips with the combination of statistics, mathematics and bioinformatics in order to find significant difference genes. Methods： With Excel and SPSS software, high or low density chips were analyzed through total intensity normalization （TIN） and locally weighted linear regression normalization （LWLRN）. Results： These methods effectively reduced systemic errors and made data more comparable and reliable. Conclusion： These methods can search the genes of significant difference, although normalization methods are being developed and need to be improved further. Great breakthrough will be obtained in microarray data normalization analysis and transformation with the development of non-linear technology, software and hardware of computer.展开更多
基金the National Natural Science Foundation of China(Grant No.71974150,71573085)。
文摘Purpose:Building on Leydesdorff,Bornmann,and Mingers(2019),we elaborate the differences between Tsinghua and Zhejiang University as an empirical example.We address the question of whether differences are statistically significant in the rankings of Chinese universities.We propose methods for measuring statistical significance among different universities within or among countries.Design/methodology/approach:Based on z-testing and overlapping confidence intervals,and using data about 205 Chinese universities included in the Leiden Rankings 2020,we argue that three main groups of Chinese research universities can be distinguished(low,middle,and high).Findings:When the sample of 205 Chinese universities is merged with the 197 US universities included in Leiden Rankings 2020,the results similarly indicate three main groups:low,middle,and high.Using this data(Leiden Rankings and Web of Science),the z-scores of the Chinese universities are significantly below those of the US universities albeit with some overlap.Research limitations:We show empirically that differences in ranking may be due to changes in the data,the models,or the modeling effects on the data.The scientometric groupings are not always stable when we use different methods.Practical implications:Differences among universities can be tested for their statistical significance.The statistics relativize the values of decimals in the rankings.One can operate with a scheme of low/middle/high in policy debates and leave the more fine-grained rankings of individual universities to operational management and local settings.Originality/value:In the discussion about the rankings of universities,the question of whether differences are statistically significant,has,in our opinion,insufficiently been addressed in research evaluations.
基金Supported by the Knowledge Innovation Research Program,Chinese Academy of Sciences (KSCX2-SW-105)
文摘Figs (Moracea: Ficus) and fig wasps (Hymenoptera: Chlocloids: Agaonideae) depend on each other to complete their reproduction. Monoecious fig species and their pollinating wasps are in conflict over the use of fig ovaries which can either produce one seed or one wasp. From observation on Ficus virens Ait., we showed that female flowers with outer layer of ovaries (near to the wall of syconium) had no significant difference from that with inner and interval layer of ovaries (near to the syconium cavity), in which most seeds and wasps were produced. This meant that fig tree provided the same potential resource for seed and wasps production. Observation indicated that there was usually only one foundress in syconium at female flower phase and no com- petition pollinators. Measurement of the style length of female flowers and the ovipositor of pollinators indicated that most ovaries could be reached by pollinator’s ovipositor. However, at the male flower phase, production of seeds was significantly more than that of wasps including non-pollinating wasps but there was no significant difference between seed and pollinating wasp production when without non-pollinating wasps produced. This result indicated that non-pollinating wasps competed ovaries not with seeds but with pollinating wasps for ovipositing. Bagged experiment showed that the sampling fig species was not self-sterile which was important for figs and wasps to survive bad season. Seed production in self-pollinated figs was not significantly different from total wasps in- cluding non-pollinating ones. This might be related with the weaker competition among wasps since bagged figs were not easy to reach by wasps from outside.
基金the National Natural Science Foundation of China(No. 60371034)the Scientific Research Foundation of Third Military Medical University(2007XG20)
文摘Objective： To discuss strategies and methods of normalization on how to deal with and analyze data for different chips with the combination of statistics, mathematics and bioinformatics in order to find significant difference genes. Methods： With Excel and SPSS software, high or low density chips were analyzed through total intensity normalization （TIN） and locally weighted linear regression normalization （LWLRN）. Results： These methods effectively reduced systemic errors and made data more comparable and reliable. Conclusion： These methods can search the genes of significant difference, although normalization methods are being developed and need to be improved further. Great breakthrough will be obtained in microarray data normalization analysis and transformation with the development of non-linear technology, software and hardware of computer.
