The morphological characteristics and the cuttlebone formation of Sepia esculenta exposed to different water temperature fluctuations were investigated under laboratory conditions. Temperature fluctuation cycles （15 ...The morphological characteristics and the cuttlebone formation of Sepia esculenta exposed to different water temperature fluctuations were investigated under laboratory conditions. Temperature fluctuation cycles （15 cycles, 60 d in total） consisted of the following three regimes of 4 d duration： keeping water temperature in 26℃ for 3 d （Group A）, 2 d （Group B）, 0 d （Group C, control）; then keeping water temperature in 16℃ for the next 1, 2, 4 d. No significant difference in the survival rate was observed between the control and temperature fluctuation groups （P〉0.05）. Lamellar depositions in a temperature fluctuation cycle were 2.45±0.02 for Group A, 2.00±0.02 for Group B, and 1.78±0.02 for Group C （P〈0.05）. The relationship between age and number of lamellas in the cuttlebone of S. esculenta under each water temperature fluctuation could be described as the linear model and the number of lamellas in the cuttlebone did not correspond to actual age. Group A had the highest cuttlebone growth index （CGI）, the lowest locular index （LI）, and inter-streak distances comparing with those of control group. However, the number of lamellas and LI or CGI showed a quadratic relationship for each temperature fluctuation group. In addition, temperature fluctuations caused the breakage of cuttlebone dark rings, which was considered a thermal mark. The position of the breakage in the dark rings was random. This thermal mark can be used as supplementary information for marking and releasing techniques.展开更多
The neon flying squid, Ommastrephes bartramii, is a species of economically important cephalopod in the Northwest Pacific Ocean. Its short lifespan increases the susceptibility of the distribution and abundance to the...The neon flying squid, Ommastrephes bartramii, is a species of economically important cephalopod in the Northwest Pacific Ocean. Its short lifespan increases the susceptibility of the distribution and abundance to the direct impact of the environmental conditions. Based on the generalized linear model(GLM) and generalized additive model(GAM), the commercial fishery data from the Chinese squid-jigging fleets during 1995 to 2011 were used to examine the interannual and seasonal variability in the abundance of O. bartramii, and to evaluate the influences of variables on the abundance(catch per unit effort, CPUE). The results from GLM suggested that year, month, latitude, sea surface temperature(SST), mixed layer depth(MLD), and the interaction term(SST×MLD) were significant factors. The optimal model based on GAM included all the six significant variables and could explain 42.43% of the variance in nominal CPUE. The importance of the six variables was ranked by decreasing magnitude: year, month, latitude, SST, MLD and SST×MLD. The squid was mainly distributed in the waters between 40?N and 44?N in the Northwest Pacific Ocean. The optimal ranges of SST and MLD were from 14 to 20℃ and from 10 to 30 m, respectively. The squid abundance greatly fluctuated from 1995 to 2011. The CPUE was low during 1995–2002 and high during 2003–2008. Furthermore, the squid abundance was typically high in August. The interannual and seasonal variabilities in the squid abundance were associated with the variations of marine environmental conditions and the life history characteristics of squid.展开更多
The generalized linear model is an indispensable tool for analyzing non-Gaussian response data, with both canonical and non-canonical link functions comprehensively used. When missing values are present, many existing...The generalized linear model is an indispensable tool for analyzing non-Gaussian response data, with both canonical and non-canonical link functions comprehensively used. When missing values are present, many existing methods in the literature heavily depend on an unverifiable assumption of the missing data mechanism, and they fail when the assumption is violated. This paper proposes a missing data mechanism that is as generally applicable as possible, which includes both ignorable and nonignorable missing data cases, as well as both scenarios of missing values in response and covariate.Under this general missing data mechanism, the authors adopt an approximate conditional likelihood method to estimate unknown parameters. The authors rigorously establish the regularity conditions under which the unknown parameters are identifiable under the approximate conditional likelihood approach. For parameters that are identifiable, the authors prove the asymptotic normality of the estimators obtained by maximizing the approximate conditional likelihood. Some simulation studies are conducted to evaluate finite sample performance of the proposed estimators as well as estimators from some existing methods. Finally, the authors present a biomarker analysis in prostate cancer study to illustrate the proposed method.展开更多
In this study we quantify and analyze different components of nocturnal losses from a heated greenhouse with the presence of vegetation for typical winter weather conditions in Marrakesh-Morocco,using a non linear mod...In this study we quantify and analyze different components of nocturnal losses from a heated greenhouse with the presence of vegetation for typical winter weather conditions in Marrakesh-Morocco,using a non linear model,based on the greenhouse heat and mass balance.It was found that 12% of the total input heat was dissipate as a sensible and latent leakage losses,66% was lost by convective exchange through air-inner cover.This gain of energy at the inner-cover is dissipated at the outer-cover by radiation(66%)and convection(34%).This results point toward some practical measures to reduce heat losses:increasing air tightness,using covering materials with low-emissivity in the long wave band or putting up an external thermal curtain should provide significant energy savings.展开更多
The optimally weighted least squares estimate and the linear minimum variance estimateare two of the most popular estimation methods for a linear model.In this paper,the authors makea comprehensive discussion about th...The optimally weighted least squares estimate and the linear minimum variance estimateare two of the most popular estimation methods for a linear model.In this paper,the authors makea comprehensive discussion about the relationship between the two estimates.Firstly,the authorsconsider the classical linear model in which the coefficient matrix of the linear model is deterministic,and the necessary and sufficient condition for equivalence of the two estimates is derived.Moreover,under certain conditions on variance matrix invertibility,the two estimates can be identical providedthat they use the same a priori information of the parameter being estimated.Secondly,the authorsconsider the linear model with random coefficient matrix which is called the extended linear model;under certain conditions on variance matrix invertibility,it is proved that the former outperforms thelatter when using the same a priori information of the parameter.展开更多
基金Supported by the National High Technology Research and Development Program of China (863 Program) (No. 2010AA10A404)the National Marine Public Welfare Research Project (No. 200805069)the NMOE Project (No. 1011010603)
文摘The morphological characteristics and the cuttlebone formation of Sepia esculenta exposed to different water temperature fluctuations were investigated under laboratory conditions. Temperature fluctuation cycles （15 cycles, 60 d in total） consisted of the following three regimes of 4 d duration： keeping water temperature in 26℃ for 3 d （Group A）, 2 d （Group B）, 0 d （Group C, control）; then keeping water temperature in 16℃ for the next 1, 2, 4 d. No significant difference in the survival rate was observed between the control and temperature fluctuation groups （P〉0.05）. Lamellar depositions in a temperature fluctuation cycle were 2.45±0.02 for Group A, 2.00±0.02 for Group B, and 1.78±0.02 for Group C （P〈0.05）. The relationship between age and number of lamellas in the cuttlebone of S. esculenta under each water temperature fluctuation could be described as the linear model and the number of lamellas in the cuttlebone did not correspond to actual age. Group A had the highest cuttlebone growth index （CGI）, the lowest locular index （LI）, and inter-streak distances comparing with those of control group. However, the number of lamellas and LI or CGI showed a quadratic relationship for each temperature fluctuation group. In addition, temperature fluctuations caused the breakage of cuttlebone dark rings, which was considered a thermal mark. The position of the breakage in the dark rings was random. This thermal mark can be used as supplementary information for marking and releasing techniques.
基金financially supported by the National HighTech R&D Program(863 Program)of China(2012AA 092303)the Project of Shanghai Science and Technology Innovation(12231203900)+3 种基金the Industrialization Program of National Development and Reform Commission(2159999)the National Key Technologies R&D Program of China(2013BAD13B00)the Shanghai Universities First-Class Disciplines Project(Fisheries A)the Funding Program for Outstanding Dissertations in Shanghai Ocean University
文摘The neon flying squid, Ommastrephes bartramii, is a species of economically important cephalopod in the Northwest Pacific Ocean. Its short lifespan increases the susceptibility of the distribution and abundance to the direct impact of the environmental conditions. Based on the generalized linear model(GLM) and generalized additive model(GAM), the commercial fishery data from the Chinese squid-jigging fleets during 1995 to 2011 were used to examine the interannual and seasonal variability in the abundance of O. bartramii, and to evaluate the influences of variables on the abundance(catch per unit effort, CPUE). The results from GLM suggested that year, month, latitude, sea surface temperature(SST), mixed layer depth(MLD), and the interaction term(SST×MLD) were significant factors. The optimal model based on GAM included all the six significant variables and could explain 42.43% of the variance in nominal CPUE. The importance of the six variables was ranked by decreasing magnitude: year, month, latitude, SST, MLD and SST×MLD. The squid was mainly distributed in the waters between 40?N and 44?N in the Northwest Pacific Ocean. The optimal ranges of SST and MLD were from 14 to 20℃ and from 10 to 30 m, respectively. The squid abundance greatly fluctuated from 1995 to 2011. The CPUE was low during 1995–2002 and high during 2003–2008. Furthermore, the squid abundance was typically high in August. The interannual and seasonal variabilities in the squid abundance were associated with the variations of marine environmental conditions and the life history characteristics of squid.
基金supported by the Chinese 111 Project B14019the US National Science Foundation under Grant Nos.DMS-1305474 and DMS-1612873the US National Institutes of Health Award UL1TR001412
文摘The generalized linear model is an indispensable tool for analyzing non-Gaussian response data, with both canonical and non-canonical link functions comprehensively used. When missing values are present, many existing methods in the literature heavily depend on an unverifiable assumption of the missing data mechanism, and they fail when the assumption is violated. This paper proposes a missing data mechanism that is as generally applicable as possible, which includes both ignorable and nonignorable missing data cases, as well as both scenarios of missing values in response and covariate.Under this general missing data mechanism, the authors adopt an approximate conditional likelihood method to estimate unknown parameters. The authors rigorously establish the regularity conditions under which the unknown parameters are identifiable under the approximate conditional likelihood approach. For parameters that are identifiable, the authors prove the asymptotic normality of the estimators obtained by maximizing the approximate conditional likelihood. Some simulation studies are conducted to evaluate finite sample performance of the proposed estimators as well as estimators from some existing methods. Finally, the authors present a biomarker analysis in prostate cancer study to illustrate the proposed method.
基金the financial support of the CNRST as part of Program URAC,Convention URAC28
文摘In this study we quantify and analyze different components of nocturnal losses from a heated greenhouse with the presence of vegetation for typical winter weather conditions in Marrakesh-Morocco,using a non linear model,based on the greenhouse heat and mass balance.It was found that 12% of the total input heat was dissipate as a sensible and latent leakage losses,66% was lost by convective exchange through air-inner cover.This gain of energy at the inner-cover is dissipated at the outer-cover by radiation(66%)and convection(34%).This results point toward some practical measures to reduce heat losses:increasing air tightness,using covering materials with low-emissivity in the long wave band or putting up an external thermal curtain should provide significant energy savings.
基金supported in part by the National Natural Science Foundation of China under Grant Nos 60232010, 60574032the Project 863 under Grant No. 2006AA12A104
文摘The optimally weighted least squares estimate and the linear minimum variance estimateare two of the most popular estimation methods for a linear model.In this paper,the authors makea comprehensive discussion about the relationship between the two estimates.Firstly,the authorsconsider the classical linear model in which the coefficient matrix of the linear model is deterministic,and the necessary and sufficient condition for equivalence of the two estimates is derived.Moreover,under certain conditions on variance matrix invertibility,the two estimates can be identical providedthat they use the same a priori information of the parameter being estimated.Secondly,the authorsconsider the linear model with random coefficient matrix which is called the extended linear model;under certain conditions on variance matrix invertibility,it is proved that the former outperforms thelatter when using the same a priori information of the parameter.
