The dewatering of fine, flotation cleaned coals from Huaibei and Xuzhou (bituminous) and Yongcheng (anthracite) were studied. The supernatant and filter cake were examined to determine the rate and extent of flocculat...The dewatering of fine, flotation cleaned coals from Huaibei and Xuzhou (bituminous) and Yongcheng (anthracite) were studied. The supernatant and filter cake were examined to determine the rate and extent of flocculation and dewatering. A starch-based filter aid was used to increase flocculation and dewatering rates. The filtration constant, K, and compression index, s, of the Yongcheng slurry were measured under various conditions. A designed experiment was performed to determine optimum conditions for dewatering. The results showed that the filter aid enhanced flocculation and coagulation of the fine cleaned coal slurry, enhanced the structure of the filter cake and promoted dewatering of the cake. Moisture content in the cake was reduced to 17% after vacuum filtration.展开更多
In order to improve the dewatering rate and the effect of fine clean coal(FCC), the advanced method offine coal( 0.5 mm) dewatering and the correlated basic theory were investigated in this study. It was found that th...In order to improve the dewatering rate and the effect of fine clean coal(FCC), the advanced method offine coal( 0.5 mm) dewatering and the correlated basic theory were investigated in this study. It was found that the dewatering by sleeve type press filter was an efficient way of FCC dewatering. On the other hand, the results also proved that particle size distribution, volatile matter, ash content, pore size distribution and specific surface area of coal particles of FCC samples, as well as viscosity and density of FCC slurry, were important parameters in determining the process of efficient dewatering. Especially, wet mass to dry mass, specific resistance of average mass, compressibility factor and microstructure of filter cake explained the reasons and mechanisms of fine clean coal efficient dewatering.展开更多
In this paper,the manufacturing of high-efficiency air filter paper is reported.The air filter paper was produced using ultra-fine fibers and wateroat fibers mercerized by alkali,using an electrospinning apparatus wit...In this paper,the manufacturing of high-efficiency air filter paper is reported.The air filter paper was produced using ultra-fine fibers and wateroat fibers mercerized by alkali,using an electrospinning apparatus with multiple rings.The high efficiency air filter paper has an antibacterial effect after adding a chitosan-copper complex which is harmless to humans.As a result of the measurement,the filtering efficiency of the air filter paper is approximately 99.998%and its antibacterial efficiency is approximately 99.5%.展开更多
【目的】研究外加电场和细颗粒物粒径对固定床颗粒层除尘器(granular bed filter,GBF)过滤性能的影响。【方法】建立GBF的三维过滤模型和电场力模型并验证其准确性;研究有、无外加电场及不同电场强度情况下GBF对粒径为1~21μm的细颗粒...【目的】研究外加电场和细颗粒物粒径对固定床颗粒层除尘器(granular bed filter,GBF)过滤性能的影响。【方法】建立GBF的三维过滤模型和电场力模型并验证其准确性;研究有、无外加电场及不同电场强度情况下GBF对粒径为1~21μm的细颗粒物的过滤情况,并分析不同粒径的细颗粒物在GBF内部的分布规律。【结果】外加电场的存在能显著提高GBF对粒径为3~21μm的细颗粒物的过滤效率,且外加电场强度越大,细颗粒物粒径越大,GBF过滤效率提升越明显;随着粒径的增大,细颗粒物在堆积颗粒层内部的分布更加集中在高气流速度区域,且更容易通过堆积颗粒层与GBF壁面之间形成的通道;外加电场的存在使得堆积颗粒层内部的细颗粒物数量减少,分布散乱,且大粒径细颗粒物在GBF壁面附近区域发生较大规模聚集。【结论】外加电场和细颗粒物粒径的增大与GBF内部细颗粒物的分布规律密切联系,且对GBF过滤性能的提升发挥积极作用。展开更多
Diagnosis and treatment of breast cancer have been improved during the last decade; however, breast cancer is still a leading cause of death among women in the whole world. Early detection and accurate diagnosis of th...Diagnosis and treatment of breast cancer have been improved during the last decade; however, breast cancer is still a leading cause of death among women in the whole world. Early detection and accurate diagnosis of this disease has been demonstrated an approach to long survival of the patients. As an attempt to develop a reliable diagnosing method for breast cancer, we integrated support vector machine (SVM), k-nearest neighbor and probabilistic neural network into a complex machine learning approach to detect malignant breast tumour through a set of indicators consisting of age and ten cellular features of fine-needle aspiration of breast which were ranked according to signal-to-noise ratio to identify determinants distinguishing benign breast tumours from malignant ones. The method turned out to significantly improve the diagnosis, with a sensitivity of 94.04%, a specificity of 97.37%, and an overall accuracy up to 96.24% when SVM was adopted with the sigmoid kernel function under 5-fold cross validation. The results suggest that SVM is a promising methodology to be further developed into a practical adjunct implement to help discerning benign and malignant breast tumours and thus reduce the incidence of misdiagnosis.展开更多
基金the financial support for this work provided by the Doctoral Fund of Ministry of Education of China (No.200802900503) the Science and Technology Foundation of China University of Mining & Technology (No.2008A027)
文摘The dewatering of fine, flotation cleaned coals from Huaibei and Xuzhou (bituminous) and Yongcheng (anthracite) were studied. The supernatant and filter cake were examined to determine the rate and extent of flocculation and dewatering. A starch-based filter aid was used to increase flocculation and dewatering rates. The filtration constant, K, and compression index, s, of the Yongcheng slurry were measured under various conditions. A designed experiment was performed to determine optimum conditions for dewatering. The results showed that the filter aid enhanced flocculation and coagulation of the fine cleaned coal slurry, enhanced the structure of the filter cake and promoted dewatering of the cake. Moisture content in the cake was reduced to 17% after vacuum filtration.
基金the National Natural Science Foundation of China (No. 21206190)the Science Fund Project of China University of Mining & Technology (No. 2008A027)the China Coal Industry Association 2012 Annual Scientific and Technological Guidance Project (Nos. MTKJ 2012-288 and MTKJ 2012-289) for their financial support
文摘In order to improve the dewatering rate and the effect of fine clean coal(FCC), the advanced method offine coal( 0.5 mm) dewatering and the correlated basic theory were investigated in this study. It was found that the dewatering by sleeve type press filter was an efficient way of FCC dewatering. On the other hand, the results also proved that particle size distribution, volatile matter, ash content, pore size distribution and specific surface area of coal particles of FCC samples, as well as viscosity and density of FCC slurry, were important parameters in determining the process of efficient dewatering. Especially, wet mass to dry mass, specific resistance of average mass, compressibility factor and microstructure of filter cake explained the reasons and mechanisms of fine clean coal efficient dewatering.
文摘In this paper,the manufacturing of high-efficiency air filter paper is reported.The air filter paper was produced using ultra-fine fibers and wateroat fibers mercerized by alkali,using an electrospinning apparatus with multiple rings.The high efficiency air filter paper has an antibacterial effect after adding a chitosan-copper complex which is harmless to humans.As a result of the measurement,the filtering efficiency of the air filter paper is approximately 99.998%and its antibacterial efficiency is approximately 99.5%.
文摘【目的】研究外加电场和细颗粒物粒径对固定床颗粒层除尘器(granular bed filter,GBF)过滤性能的影响。【方法】建立GBF的三维过滤模型和电场力模型并验证其准确性;研究有、无外加电场及不同电场强度情况下GBF对粒径为1~21μm的细颗粒物的过滤情况,并分析不同粒径的细颗粒物在GBF内部的分布规律。【结果】外加电场的存在能显著提高GBF对粒径为3~21μm的细颗粒物的过滤效率,且外加电场强度越大,细颗粒物粒径越大,GBF过滤效率提升越明显;随着粒径的增大,细颗粒物在堆积颗粒层内部的分布更加集中在高气流速度区域,且更容易通过堆积颗粒层与GBF壁面之间形成的通道;外加电场的存在使得堆积颗粒层内部的细颗粒物数量减少,分布散乱,且大粒径细颗粒物在GBF壁面附近区域发生较大规模聚集。【结论】外加电场和细颗粒物粒径的增大与GBF内部细颗粒物的分布规律密切联系,且对GBF过滤性能的提升发挥积极作用。
基金Joint Research Project Between Chongqing University and National University of Singapore (No. ARF-151-000-014-112)the Basic Research & Applied Basic Research Program of Chongqing University (No.71341103)Natural Science Foundation of Chongqing S & T Committee(No. CSTC,2006BB5240)
文摘Diagnosis and treatment of breast cancer have been improved during the last decade; however, breast cancer is still a leading cause of death among women in the whole world. Early detection and accurate diagnosis of this disease has been demonstrated an approach to long survival of the patients. As an attempt to develop a reliable diagnosing method for breast cancer, we integrated support vector machine (SVM), k-nearest neighbor and probabilistic neural network into a complex machine learning approach to detect malignant breast tumour through a set of indicators consisting of age and ten cellular features of fine-needle aspiration of breast which were ranked according to signal-to-noise ratio to identify determinants distinguishing benign breast tumours from malignant ones. The method turned out to significantly improve the diagnosis, with a sensitivity of 94.04%, a specificity of 97.37%, and an overall accuracy up to 96.24% when SVM was adopted with the sigmoid kernel function under 5-fold cross validation. The results suggest that SVM is a promising methodology to be further developed into a practical adjunct implement to help discerning benign and malignant breast tumours and thus reduce the incidence of misdiagnosis.
