为了优化煤直接液化工艺条件和提高油收率,本研究利用30 m L高压管式反应釜研究了煤直接液化重质产物前沥青烯加氢液化行为,考察了Fe S+S催化剂下反应温度(380、400、420和440℃)、液化时间(0、5、10、20、30和60 min)、5.0 MPa氢初压...为了优化煤直接液化工艺条件和提高油收率,本研究利用30 m L高压管式反应釜研究了煤直接液化重质产物前沥青烯加氢液化行为,考察了Fe S+S催化剂下反应温度(380、400、420和440℃)、液化时间(0、5、10、20、30和60 min)、5.0 MPa氢初压和四氢萘溶剂条件下前沥青烯液化转化行为,同时考察了前沥青烯的催化加氢液化反应动力学。利用集总动力学法建立了FeS+S催化前沥青烯加氢的动力学模型。研究表明,前沥青烯加氢直接生成沥青烯和焦渣,而沥青烯进一步加氢裂解生成油和气,高温下发生明显的逆向缩合反应,即前沥青烯生成焦渣和沥青烯生成前沥青烯。温度和反应时间的增加有利于提高前沥青烯的转化率和油气收率,440°C下反应60 min时,前沥青烯的转化率为79.45%,油气收率为34.7%。380-440℃温度下,动力学模型能够较好地描述小龙潭液化产物前沥青烯的加氢转化行为,各步转化均符合Arrhenius表观活化能公式,并且活化能变化为50-245 k J/mol。展开更多
BACKGROUND Spinal osteoporosis is a prevalent health condition characterized by the thinning of bone tissues in the spine,increasing the risk of fractures.Given its high incidence,especially among older populations,it...BACKGROUND Spinal osteoporosis is a prevalent health condition characterized by the thinning of bone tissues in the spine,increasing the risk of fractures.Given its high incidence,especially among older populations,it is critical to have accurate and effective predictive models for fracture risk.Traditionally,clinicians have relied on a combination of factors such as demographics,clinical attributes,and radiological characteristics to predict fracture risk in these patients.However,these models often lack precision and fail to include all potential risk factors.There is a need for a more comprehensive,statistically robust prediction model that can better identify high-risk individuals for early intervention.AIM To construct and validate a model for forecasting fracture risk in patients with spinal osteoporosis.METHODS The medical records of 80 patients with spinal osteoporosis who were diagnosed and treated between 2019 and 2022 were retrospectively examined.The patients were selected according to strict criteria and categorized into two groups:Those with fractures(n=40)and those without fractures(n=40).Demographics,clinical attributes,biochemical indicators,bone mineral density(BMD),and radiological characteristics were collected and compared.A logistic regression analysis was employed to create an osteoporotic fracture risk-prediction model.The area under the receiver operating characteristic curve(AUROC)was used to evaluate the model’s performance.RESULTS Factors significantly associated with fracture risk included age,sex,body mass index(BMI),smoking history,BMD,vertebral trabecular alterations,and prior vertebral fractures.The final risk-prediction model was developed using the formula:(logit[P]=-3.75+0.04×age-1.15×sex+0.02×BMI+0.83×smoking history+2.25×BMD-1.12×vertebral trabecular alterations+1.83×previous vertebral fractures).The AUROC of the model was 0.93(95%CI:0.88-0.96,P<0.001),indicating strong discriminatory capabilities.CONCLUSION The fracture risk-prediction model,utilizing accessible cli展开更多
Two key intermediates of cembranolides- (2E,6E,10E)-3,7,11,15-tetramethyl-9-phenylsulfonyl-2,6,10,14-tetraen-1-hexadecanol (1) and (2E,6E,10E,14E)-2,6,10,14-tetramethyl-8-phenylsulfonyl-2,6,10,14-tetraen-1,16-hexadec... Two key intermediates of cembranolides- (2E,6E,10E)-3,7,11,15-tetramethyl-9-phenylsulfonyl-2,6,10,14-tetraen-1-hexadecanol (1) and (2E,6E,10E,14E)-2,6,10,14-tetramethyl-8-phenylsulfonyl-2,6,10,14-tetraen-1,16-hexadecanediol (2) were synthesized starting from geraniol and linalool and some improved synthetic methods were used.展开更多
基金supported by the Natural Scientific Foundation of China(21476004,21476003,21476002,51174254)Natural Science Foundation of Anhui Provincial Education Department(KJ2016A808)the Provincial Innovative Group for Processing & Clean Utilization of Coal Resource and the Innovative Group of Anhui University of Technology
基金supported by the National Key Research and Development Program of China(2018YFB0604600)the Natural Scientific Foundation of China(21476003,21776001,21476002,21476004,20108002)+1 种基金the Anhui Natural Science Foundation(1608085M B40)the financial support from the Provincial Innovative Group for Processing&Clean Utilization of Coal Resource
文摘以锐钛矿TiO_2为载体,考察了CeO_2改性对Ag-CeO_2-V_2O_5/TiO_2催化3-甲基吡啶氧化脱甲基性能的影响,并优化了催化剂组成与制备条件.结果表明:Ce掺杂改性不仅能够与V物种作用形成Ce VO_4,而且促进V_2O_5分散,改善活性组分的氧化还原性能,从而提高3-甲基吡啶脱甲基转化率与选择性,改善Ag-V_2O_5/TiO_2催化性能.适宜的催化剂组成为V_2O_5负载量15%,Ce/V的摩尔比0.33,Ag质量分数1.0%.过高的焙烧温度将导致TiO_2载体向金红石型转变,Ag-CeO_2-V_2O_5/TiO_2适宜制备条件为450℃焙烧4 h.
基金The project was supported by the Project of Coal Joint Fund from Natural Science Foundation of China and Shenhua Group Corporation Limited(U1361125,U1261208),the Natural Scientific Foundation of China(21776001,21476002,21476003,21476004),the Key Science a
基金supported by the National Natural Science Foundation of China (Grants 21776001, U1710114, 21808002, 21878001, 21978002,21978003, 22008001, 22078002)。
文摘为了优化煤直接液化工艺条件和提高油收率,本研究利用30 m L高压管式反应釜研究了煤直接液化重质产物前沥青烯加氢液化行为,考察了Fe S+S催化剂下反应温度(380、400、420和440℃)、液化时间(0、5、10、20、30和60 min)、5.0 MPa氢初压和四氢萘溶剂条件下前沥青烯液化转化行为,同时考察了前沥青烯的催化加氢液化反应动力学。利用集总动力学法建立了FeS+S催化前沥青烯加氢的动力学模型。研究表明,前沥青烯加氢直接生成沥青烯和焦渣,而沥青烯进一步加氢裂解生成油和气,高温下发生明显的逆向缩合反应,即前沥青烯生成焦渣和沥青烯生成前沥青烯。温度和反应时间的增加有利于提高前沥青烯的转化率和油气收率,440°C下反应60 min时,前沥青烯的转化率为79.45%,油气收率为34.7%。380-440℃温度下,动力学模型能够较好地描述小龙潭液化产物前沥青烯的加氢转化行为,各步转化均符合Arrhenius表观活化能公式,并且活化能变化为50-245 k J/mol。
基金supported by the National Key Research and Development Program of China(2018YFB0604600)the Natural Science Foundation of China(21776001+5 种基金21878001U17101142187500121808002)Anhui Province Key Laboratory of Coal Clean Conversion and High Valued UtilizationAnhui University of Technology(CHV19-01)。
文摘BACKGROUND Spinal osteoporosis is a prevalent health condition characterized by the thinning of bone tissues in the spine,increasing the risk of fractures.Given its high incidence,especially among older populations,it is critical to have accurate and effective predictive models for fracture risk.Traditionally,clinicians have relied on a combination of factors such as demographics,clinical attributes,and radiological characteristics to predict fracture risk in these patients.However,these models often lack precision and fail to include all potential risk factors.There is a need for a more comprehensive,statistically robust prediction model that can better identify high-risk individuals for early intervention.AIM To construct and validate a model for forecasting fracture risk in patients with spinal osteoporosis.METHODS The medical records of 80 patients with spinal osteoporosis who were diagnosed and treated between 2019 and 2022 were retrospectively examined.The patients were selected according to strict criteria and categorized into two groups:Those with fractures(n=40)and those without fractures(n=40).Demographics,clinical attributes,biochemical indicators,bone mineral density(BMD),and radiological characteristics were collected and compared.A logistic regression analysis was employed to create an osteoporotic fracture risk-prediction model.The area under the receiver operating characteristic curve(AUROC)was used to evaluate the model’s performance.RESULTS Factors significantly associated with fracture risk included age,sex,body mass index(BMI),smoking history,BMD,vertebral trabecular alterations,and prior vertebral fractures.The final risk-prediction model was developed using the formula:(logit[P]=-3.75+0.04×age-1.15×sex+0.02×BMI+0.83×smoking history+2.25×BMD-1.12×vertebral trabecular alterations+1.83×previous vertebral fractures).The AUROC of the model was 0.93(95%CI:0.88-0.96,P<0.001),indicating strong discriminatory capabilities.CONCLUSION The fracture risk-prediction model,utilizing accessible cli
基金Project supported by the National Natural Science Foundation of China and the Natural Science Foundation of Zhongshan University.
文摘 Two key intermediates of cembranolides- (2E,6E,10E)-3,7,11,15-tetramethyl-9-phenylsulfonyl-2,6,10,14-tetraen-1-hexadecanol (1) and (2E,6E,10E,14E)-2,6,10,14-tetramethyl-8-phenylsulfonyl-2,6,10,14-tetraen-1,16-hexadecanediol (2) were synthesized starting from geraniol and linalool and some improved synthetic methods were used.
基金The project was supported by the Natural Scientific Foundation of China(21878001,22078002,21776001,21875001,21978002,21808002,22008001,and U1710114).
