蔡氏扶正消癥汤对胃癌细胞增殖的抑制作用研究

目的:观察蔡氏扶正消癥汤对胃癌细胞增殖的影响.方法:(1)采用倒置显微镜观察蔡氏扶正消癥汤对胃癌细胞形态的影响;(2)采用四甲基偶氮唑蓝(MTT)还原法检测蔡氏扶正消癥汤对胃癌细胞生长的影响.结果:蔡氏扶正消癥汤生药能抑制胃癌细胞的增殖.在实验浓度范围内,随着剂量的增加,抑制作用更加明显;同一剂量下,72h内药物作用时间越长,抑制作用越明显.结论:蔡氏扶正消癥汤能够抑制胃癌细胞的增殖.     

一种基于高斯混合模型与Markov建模的灰度图像分割方法

当灰度图像中存在区域间灰度变化不明显或者含有噪声时,图像分割效果会受到比较严重的影响,本文针对此类问题,基于高斯混合模型,提出了一种改进的灰度图像分割算法。首先,基于马尔可夫随机场建模,将梯度因素引入邻域约束,推导图像的能量函数。然后,采用改进的期望最大（EM）算法对能量函数进行求解,E步通过图割法求解各像素点的分类,M步通过改进的期望最大（EM）算法求解高斯混合模型中的各参数。实验结果表明,本文的方法相对于直接用图割法能够求得更低的能量值,获得较好的分割结果。     

混料均匀设计法在灯盏花素骨架片处方配比中的应用研究

目的:采用有约束混料均匀设计方法优化灯盏花素骨架缓释片中填充剂乳糖及阻滞剂HPMCSH4000与Carbopol 71 G的处方配比。方法:分别以单一因变量与综合因变量为指标,对不同处方进行评价,建立回归方程,求出综合最优解,从而筛选出最优处方。结果:两种方法筛选出的最佳配比较一致,所制得的片剂具有理想释药性能。结论:混料均匀设计较传统的均匀设计方法具有简单、直观、分布更为均匀的特点,适用于辅料用量固定的处方配比优化。     

正交试验法优选胃痛宁合剂水提工艺

目的：优选胃痛宁合剂的水提取工艺。方法：以芍药苷含量为指标,采用HPLC测定其含量,以加水倍数、煎煮时间、煎煮次数为考察因素,应用正交试验L9（3^4）筛选胃痛宁合剂的最佳提取工艺条件。结果：胃痛宁合剂的最佳水提工艺为6倍量水煎煮3次,每次1.5 h。结论：优选的水提取工艺稳定、合理,可为胃痛宁合剂的生产提供实验依据。     

基于肠肾轴理论谈通腑泄浊法治疗慢性肾脏病

肠-肾轴学说认为肠道菌群的紊乱能够引起肠道屏障功能受损及全身微炎症反应,进而加重慢性肾脏病进程,这一理论的提出为慢性肾脏病的治疗提供了新的方向。通腑泄浊法是通过加强肠腑传化功能,使蓄积于肠道的湿浊毒邪从大便排出,进而调节脏腑气机,祛邪以扶正,与肠肾轴理论不谋而合。本文基于肠-肾轴理论,讨论通腑泄浊法治疗慢性肾脏病的应用,为慢性肾脏病的治疗提供新的思路和方法。     

益气通腑汤治疗女性直肠前突随机平行对照研究

[目的]观察益气通腑汤治疗女性直肠前突疗效。[方法]使用随机平行对照方法,将123例随机分为两组,对照组60例麻仁丸口服,治疗组60例益气通腑汤化裁。3个月为1疗程,治疗1疗程(90d)判定疗效。[结果]治疗组临床治愈6例,有效40例,无效14例,总有效率76.67%。对照组临床治愈1例,有效21例,无效38例,总有效率36.67%。治疗组疗效优于对照组(P<0.01)。[结论]中医药以整体观念为原则,以调理脏腑机能为根本,弥补了西医治疗的不足,值得临床推广。     

Study on Low-Temperature Index and Improvement Measures of Emulsified Asphalt Cold Recycled Mixture

With the promotion of cold recycled mixture (CRM) in cold areas and the improvement of its application layer, the enhancement of the low-temperature performance of mixtures is particularly important. The applicability of the current low-temperature bending test method to CRM is controversial. Firstly, the low-temperature crack resistance of CRM with different gradations and emulsified asphalt contents was studied by the indirect tensile (IDT) test and the semi-circular bending (SCB) test. Thereafter, the low-temperature performance evaluation index suitable for CRM was put forward. Then, the low-temperature performance of CRM with different gradations, fiber types, and contents was evaluated by using the above low-temperature evaluation index. The results show that the low-temperature performance of CRM with different gradations and emulsified asphalt contents can be distinguished by fracture work (W) and fracture energy (G_f). Not only do the test results have little variability (about 12% and 15%, respectively), but also the correlation coefficient with the new asphalt film thickness is the highest (0.8595 and 0.8939, respectively). Compared with coarse gradation (AC-25) and fine gradation (AC-13), medium-gradation (AC-20) CRM has higher low-temperature performance, and polyester fiber can significantly improve the low-temperature performance of CRM. Compared with non-fiber, the W and G_f of CRM of polyester fiber (0.3% content) can be increased by at least 42% and 30%, respectively.     

Mixture Optimization of Cementitious Materials Using Machine Learning and Metaheuristic Algorithms: State of the Art and Future Prospects

The hybrid optimization of modern cementitious materials requires concrete to meet many competing objectives (e.g., mechanical properties, cost, workability, environmental requirements, and durability). This paper reviews the current literature on optimizing mixing ratios using machine learning and metaheuristic optimization algorithms based on past studies on varying methods. In this review, we first discuss the conventional methods for mixing optimization of cementitious materials. Then, the problem expression of hybrid optimization is discussed, including decision variables, constraints, machine learning algorithms for modeling objectives, and metaheuristic optimization algorithms for searching the best mixture ratio. Finally, we explore the development prospects of this field, including, expanding the database by combining field data, considering more influencing variables, and considering more competitive targets in the production of functional cemented materials. In addition, to overcome the limitation of the swarm intelligence-based multi-objective optimization (MOO) algorithm in hybrid optimization, this paper proposes a new MOO algorithm based on individual intelligence (multi-objective beetle antenna search algorithm). The development of computationally efficient robust MOO models will continue to make progress in the field of hybrid optimization. This review is adapted for engineers and researchers who want to optimize the mixture proportions of cementitious materials using machine learning and metaheuristic algorithms.     

Mixture Design and Mechanical Properties of Recycled Mortar and Fully Recycled Aggregate Concrete Incorporated with Fly Ash

Recycled aggregate concrete (RAC) is a sort of green, low carbon, environmental protection building material, its application is of great significance to the low carbonization of the construction industry. The performance and strength of RAC are much lower than natural aggregate concrete (NAC), which are the key factors restricting its application. Class F fly ash is a cementitious material that is considered environmentally hazardous. In this paper, appropriate water-binder (w/b) ratios were found through a mortar expansion test at first. The compressive strength of recycled mortar incorporated with class F fly ash was further studied. On this basis, the mechanical properties of nine groups of fully recycled aggregate concrete (FRAC) with a w/b ratio of 0.3, 0.35, and 0.4, and fly ash replacement ratios of 0, 20%, and 40%, were studied. The influence of the w/b ratio and fly ash replacement ratio on mechanical properties was analyzed and compared with previous research results. In addition, the conversion formulas between the splitting tensile strength, flexural strength, and compressive strength of FRAC were fitted and established. The research results have a certain guiding significance for the mixture design of FRAC and further application of class F fly ash.     

Crushing Characteristics of Coarse Aggregates for Asphalt Mixtures under Simulated Laboratory Compaction Loads and Repeated Traffic Loads

The crushing characteristics of coarse aggregates for asphalt concrete were investigated under static and dynamic aggregate crushing value tests (ACVTs). The effect of various compaction loads was also examined by using a Marshall hammer, gyratory compactor and steel roller. Six types of coarse aggregates were tested, including basalt aggregate, steel slag, limestone aggregate, marble aggregate, recycled concrete aggregate and slightly weathered limestone aggregate. Test results indicate that static ACVT failed to reflect the crushing behavior of coarse aggregates under traditional traffic and compaction loads. The type of aggregate strongly influenced the crushing resistance, independent of type of load. The compaction loads simulated by using a Marshall hammer, gyratory compactor and steel roller resulted in a high aggregate breakage ratio and can distinguish the coarse aggregates with high crushing susceptibility. The crushing resistance was evaluated by using various crushing parameters and the corresponding critical value of these parameters was established. Gyratory compactor compaction resulted in more serious aggregate crushing when compared to Marshall hammer and steel roller compaction. Finite element modelling results on roller compaction and Marshall hammer compaction are in agreement with the aggregate crushing results. The aggregate crushing mechanism was found to be controlled by the fracture mode; the contribution of the attrition and abrasion modes was relatively small. When coarse aggregates with low crushing resistance are considered for the use for asphalt mixture, proper compaction is proved to be vital to prevent excessive aggregate breakage during mixture preparation and construction.