Suction boxes are used in the paper industry to simultaneously drain a pulp suspension and form a fibre mat (or filter cake). This research addresses the modelling of fibre deposition in the forming unit of an indus...Suction boxes are used in the paper industry to simultaneously drain a pulp suspension and form a fibre mat (or filter cake). This research addresses the modelling of fibre deposition in the forming unit of an industrial papermachine, assuming a filtration process, and that of the flowing suspension drained through the building fibre mat and the wire on a suction box. From experimental data of the cumulative drained V volume, per unit surface area, for two vacuum pressures △P and 6 dwell times t, an extension of the classical law (t/V) versus V is proposed, validated and applied. This relation enables determining the average specific filtration resistance of the fibre mat over the box and the mass of solids deposited before and over the suction box. The model obtained is as precise as 1% and can be used to limit and reduce the energy consumption of drainage vacuum assisted devices such as suction boxes in the forming unit of industrial papermachines.展开更多
In order to study the effect of different modification methods on polysilsesquioxane(POSS)modified cellulose,a molecular dynamics method was used to establish a pure cellulose model and a series of modified models mod...In order to study the effect of different modification methods on polysilsesquioxane(POSS)modified cellulose,a molecular dynamics method was used to establish a pure cellulose model and a series of modified models modified by polysilsesquioxane in different ways.And their thermodynamic properties were calculated.The results showed that the performance of cellulose models was better than that of unmodified model,and the modified effect was the best when two cellulose chains were grafted onto polysilsesquioxane by chemical bond(M2 model).Compared with pure cellulose model,the cohesive energy density and solubility parameters of M2 model are increased by 9%,and the values of tensile modulus,bulk modulus,shear modulus and Cauchy pressure increased by 38.6%,29.5%,41.1% and 29.5%,respectively.In addition,the free volume fraction and mean square displacement of each model were calculated and analyzed in this work.Compared with the pure cellulose model,the molecular chain entanglement of cellulose was increased due to the existence of the chemical bonds in the M2 model,which made the cellulose molecular chains occupy more free volume,so that the system had a smaller free volume fraction,inhibited the chain movement of cellulose chains,and thus improved the thermal stability of cellulose.展开更多
Although genome-wide association studies (GWAS) have successfully identified thousands of genomic loci associated with hun- dreds of complex traits in the past decade, the debate about such problems as missing herit...Although genome-wide association studies (GWAS) have successfully identified thousands of genomic loci associated with hun- dreds of complex traits in the past decade, the debate about such problems as missing heritabiUty and weak interpretability has been appealing for effective computational methods to facilitate the advanced analysis of the vast volume of existing and antici- pated genetic data. Towards this goal, gene-tevel integrative GWAS analysis with the assumption that genes associated with a phenotype tend to be enriched in biological gene sets or gene networks has recently attracted much attention, due to such advan- tages as straightforward interpretation, tess multiple testing burdens, and robustness across studies. However, existing methods in this category usually exploit non-tissue-specific gene networks and thus lack the ability to utilize informative tissue-specific characteristics. To overcome this limitation, we proposed a Bayesian approach called SIGNET (Simultaneously Inference of GeNEs and Tissues) to integrate GWAS data and multiple tissue-specific gene networks for the simultaneous inference of phenotype- associated genes and relevant tissues. Through extensive simulation studies, we showed the effectiveness of our method in find- ing both associated genes and relevant tissues for a phenotype. In applications to real GWAS data of 14 complex phenotypes, we demonstrated the power of our method in both deciphering genetic basis and discovering biological insights of a phenotype. With this understanding, we expect to see SIGNET as a valuable tool for integrative GWAS analysis, thereby boosting the preven- tion, diagnosis, and treatment of human inherited diseases and eventually facilitating precision medicine.展开更多
文摘Suction boxes are used in the paper industry to simultaneously drain a pulp suspension and form a fibre mat (or filter cake). This research addresses the modelling of fibre deposition in the forming unit of an industrial papermachine, assuming a filtration process, and that of the flowing suspension drained through the building fibre mat and the wire on a suction box. From experimental data of the cumulative drained V volume, per unit surface area, for two vacuum pressures △P and 6 dwell times t, an extension of the classical law (t/V) versus V is proposed, validated and applied. This relation enables determining the average specific filtration resistance of the fibre mat over the box and the mass of solids deposited before and over the suction box. The model obtained is as precise as 1% and can be used to limit and reduce the energy consumption of drainage vacuum assisted devices such as suction boxes in the forming unit of industrial papermachines.
基金supported by the the National Key Research and Development Program of China(No.2017YFB0902700 and No.2017YBF0902702)the National Natural Science Foundation of China(No.51977179)Fundamental Research Funds for the Central Universities(No.XDJK2020D018).
文摘In order to study the effect of different modification methods on polysilsesquioxane(POSS)modified cellulose,a molecular dynamics method was used to establish a pure cellulose model and a series of modified models modified by polysilsesquioxane in different ways.And their thermodynamic properties were calculated.The results showed that the performance of cellulose models was better than that of unmodified model,and the modified effect was the best when two cellulose chains were grafted onto polysilsesquioxane by chemical bond(M2 model).Compared with pure cellulose model,the cohesive energy density and solubility parameters of M2 model are increased by 9%,and the values of tensile modulus,bulk modulus,shear modulus and Cauchy pressure increased by 38.6%,29.5%,41.1% and 29.5%,respectively.In addition,the free volume fraction and mean square displacement of each model were calculated and analyzed in this work.Compared with the pure cellulose model,the molecular chain entanglement of cellulose was increased due to the existence of the chemical bonds in the M2 model,which made the cellulose molecular chains occupy more free volume,so that the system had a smaller free volume fraction,inhibited the chain movement of cellulose chains,and thus improved the thermal stability of cellulose.
文摘Although genome-wide association studies (GWAS) have successfully identified thousands of genomic loci associated with hun- dreds of complex traits in the past decade, the debate about such problems as missing heritabiUty and weak interpretability has been appealing for effective computational methods to facilitate the advanced analysis of the vast volume of existing and antici- pated genetic data. Towards this goal, gene-tevel integrative GWAS analysis with the assumption that genes associated with a phenotype tend to be enriched in biological gene sets or gene networks has recently attracted much attention, due to such advan- tages as straightforward interpretation, tess multiple testing burdens, and robustness across studies. However, existing methods in this category usually exploit non-tissue-specific gene networks and thus lack the ability to utilize informative tissue-specific characteristics. To overcome this limitation, we proposed a Bayesian approach called SIGNET (Simultaneously Inference of GeNEs and Tissues) to integrate GWAS data and multiple tissue-specific gene networks for the simultaneous inference of phenotype- associated genes and relevant tissues. Through extensive simulation studies, we showed the effectiveness of our method in find- ing both associated genes and relevant tissues for a phenotype. In applications to real GWAS data of 14 complex phenotypes, we demonstrated the power of our method in both deciphering genetic basis and discovering biological insights of a phenotype. With this understanding, we expect to see SIGNET as a valuable tool for integrative GWAS analysis, thereby boosting the preven- tion, diagnosis, and treatment of human inherited diseases and eventually facilitating precision medicine.