Modeling of quantitative relationships between physicochemical properties of active pharmaceutical ingredients and tensile strength of tablets using a boosted tree

Objectives: The aim of this study was to explore the potential of boosted tree (BT) to develop a correlation model between active pharmaceutical ingredient (API) characteristics and a tensile strength (TS) of tablets as critical quality attributes.

Methods: First, we evaluated 81 kinds of API characteristics, such as particle size distribution, bulk density, tapped density, Hausner ratio, moisture content, elastic recovery, molecular weight, and partition coefficient. Next, we prepared tablets containing 50% API, 49% microcrystalline cellulose, and 1% magnesium stearate using direct compression at 6, 8, and 10?kN, and measured TS. Then, we applied BT to our dataset to develop a correlation model. Finally, the constructed BT model was validated using k-fold cross-validation.

Results: Results showed that the BT model achieved high-performance statistics, whereas multiple regression analysis resulted in poor estimations. Sensitivity analysis of the BT model revealed that diameter of powder particles at the 10th percentile of the cumulative percentage size distribution was the most crucial factor for TS. In addition, the influences of moisture content, partition coefficients, and modal diameter were appreciably meaningful factors.

Conclusions: This study demonstrates that BT model could provide comprehensive understanding of the latent structure underlying APIs and TS of tablets.     

Human–machine shared control for lane departure assistance based on hybrid system theory

To improve the human–machine cooperation of lane departure assistance system (LDAS), a human–machine shared control strategy based on hybrid system theory was proposed. By considering vehicle’s discrete and continuous states and time-varying longitudinal speed, the hybrid system was formalized as hybrid automaton, and the shared control strategy was built to govern the human–machine interaction. Robust gain-scheduling energy-to-peak method was adopted to design the assistance system controller. The D-stability of the system was also studied and guaranteed by solving the linear matrix inequality (LMI). The proposed human–machine shared control method was evaluated via the co-simulation of CarSim/Simulink and the hardware-in-loop (HIL) experiment. The results showed that the proposed approach can effectively keep the vehicle in lane and a good human–machine coordination was demonstrated.     

Enhanced grouping league championship and optics inspired optimization algorithms for scheduling a batch processing machine with job conflicts and non-identical job sizes

This research aims to address scheduling of a single batch processing machine, where jobs are in different sizes and have a conflicting nature with each other, in the sense that two conflicting jobs cannot share the same batch and hence, cannot be processed simultaneously by the machine. The problem is referred to as SBMC. After formulating the problem, a strong lower bound procedure is developed by transforming a relaxed version of the scheduling problem to the multiple bottleneck transportation problem (MTP) with conflicts. An efficient Lagrangian relaxation procedure is proposed, which takes advantage of decomposable nature of the relaxed problem, to attain a lower bound for MTP which in essence is a lower bound for SBMC. To solve the problem, two metaheuristic algorithms, namely the League Championship Algorithm (LCA) and Optic Inspired Optimization (OIO), are adapted and fundamentally modified to match the problem unique structure (i.e., the grouping structure) and accordingly the grouping version of these algorithms is developed. The effectiveness of the lower bound procedure, as well as algorithms, are evaluated through extensive computational experiments. To show they perform efficiently in running times and effective in finding near-optimal bounds for most of the problem instances, we generate 20 different classes of problems according to variability in job sizes, number of jobs and density of incompatibility matrix. Then, we make comparison with two of extensively used algorithms from literature, SA and GA. Our proposed algorithms obtain solutions with objective values less than 6% gap from the lower bound and outperform SA and GA algorithms, especially for large instances. Moreover, values of the lower bound procedure lie within less than 4% of objective values provided by CPLEX.     

Modeling and surface texturing on surface roughness in machining LaPO4–Y2O3 composite

In this work, lanthanum phosphate with a 20% yttria (LaPO₄/Y₂O₃) composite prepared by an Aqueous Sol–Gel process is machined using an Abrasive Water Jet Machine (AWJM). The machinability of this composite is studied by varying the input parameters namely Jet Pressure (JP), Stand-Off Distance (SOD), and Traverse Speed (TS) on Surface finish. Garnet of 80 mesh size is used as an abrasive with a flow rate of 85?g/min. The microstructural characterization study reveals the presence of new element YPO₄. This element enhances the machinability and reduced porosity in the composite. Microscopy examinations on the machined surface reveals that partial overlapping at low JP, poor surface finish at high JP and SOD, forged deficiency at maximum SOD and TS. The minimum levels of all input parameters are influenced to obtain acceptable Ra. Atomic Force Microscopy (AFM) on the kerf surface shows micro wear track and peaks. The Multiple Regression Analysis (MRA) is developed for Ra to check the adequacy. From the Analysis of Variance (ANOVA), SOD has a significant effect on Ra with a contribution of 53%. The influence of JP and TS on Ra is found to be 31% and 15%, respectively.     

Prediction of the appearance of monkeys based on environmental conditions

Recently, agricultural damage caused by monkeys has become a critical problem in Japan. This paper proposes a system that predicts the dates and times at which monkeys approach farmland. In order to make predictions, monkeys were made to wear collars with transmitters, and the trend data of the monkeys' distances were collected by receivers in the system. Two years after this system was installed around a mountain, an average radio communication ability of 97.22% was obtained, and 25 million monkey signals were received. The time of appearance of the monkeys according to those signals as well as the environmental conditions were taken for estimation. Bayesian estimation and support vector machine (SVM) were adopted as linear and nonlinear methods, respectively. The use of Bayesian estimation resulted in little predictive effect. SVM, on the other hand, achieved 31% accuracy by combining two learning pattern methods, outperforming the Bayesian estimation and confirming the effectiveness of environmental conditions in a system of predicting the appearance of monkeys. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A call triage support system for emergency medical service using multiple random forests

This paper proposes a call triage system for emergency medical service with multiple random forests (RFs). A call triage is an operation to determine the level of first‐aid service quality required based on the severity and urgency of a victim. The aim is to achieve higher overall performance and clarify the method for deciding the determination thresholds while simultaneously achieving both fail‐safe determination and overall accuracy. To achieve the former aim, we apply the RF to determine the category. Furthermore, to achieve the latter aim, we propose a new algorithm for determining the severity using multiple RFs. The results of evaluation experiment show that the proposed algorithm can provide both accuracy and fail‐safe operation in the determination of severity.     

JSFR key technology evaluation on fuel handling system

A simplified fuel handling system design for the demonstration Japan sodium-cooled fast reactor (JSFR) has been proposed. Fast Reactor Cycle Technology Development project phase I results of key technology evaluations on a pantograph fuel handling machine (FHM), a fuel transfer pot with two core component positions, dry spent fuel cleaning and minor actinide-bearing fresh fuel shipping cask are summarized. A full-scale FHM mockup has been fabricated and tested in the air accumulating performance and seismic tolerance data. A mockup fuel transfer pot with fins and chromium carbide coating has been fabricated and tested with sodium accumulating heat transfer performance data. Several sodium cleaning tests using a dummy subassembly has been conducted accumulating cleaning performance data. For fresh fuel shipping cask, a design tool for evaluation of heat transfer capability has been developed and a helium gas cask shows cooling capability of minor actinide-bearing fresh fuel. Those experimental and analytical efforts have shown that key technologies to develop simplified fuel handling system are matured enough to proceed large-scale sodium experiments and conceptual design study for the demonstration JSFR.     

惰性气体氙β-γ符合测量系统进样装置的研制及应用

介绍了一套用于惰性气体氙β-γ符合系统的进样装置。该装置较好地解决了惰性气体氙β-γ符合系统在进样方面存在的问题,使系统具备了四种氙取样设备归档样品的测试能力,同时还可以进行归档瓶体积和压力的测量,扩展了系统的功能,使系统具备了独立完成氙归档样品现有分析项目的能力。利用该装置准确标定了系统中气相色谱的标准曲线,通过与Agilent6890气相色谱进行测量比对,二者在3%内符合,检验了所标定的标准曲线的准确性。     

三维增材鞋面印花机对位平台的冗余驱动控制策略

针对自动鞋面印花机在进行对版时定位精度低,影响鞋面印刷质量的问题,提出了基于冗余驱动的印花机对位平台。在原有的三轴并联机构对位平台的基础上通过增加1个Y轴,有效地提高了对位平台Y向的刚度和承载能力,从而提高了印花机对位平台的定位精度。由于冗余驱动机构运动过程中存在机构运动耦合,利用几何法进行解耦,提出了基于电子凸轮的控制策略。同时提出了对机构换向间隙补偿的控制策略,进一步提高对位平台的定位精度,保证了鞋面的印刷质量。经过实验验证,改进后的印花机对位平台Y向定位精度提高了85.7%,Z向旋转定位精度提高了72.9%,X向和Y向换向间隙分别提高了50% 和75%,Z向旋转换向间隙提高了42.86%。