Application of the dry‐spinning method to produce poly(ε‐caprolactone) fibers containing bovine serum albumin laden gelatin nanoparticles

We designed and manufactured a polymeric system with combined hydrophilic–hydrophobic properties by loading gelatin nanoparticles (GNPs) containing bovine serum albumin (BSA) into poly(ε‐caprolactone) (PCL) fibers. Our ultimate goal was to create a device capable of carrying and releasing protein drugs. Such a system could find several biomedical applications, such as those in controlled release systems, surgical sutures, and bioactive scaffolds for tissue engineering. A two‐step desolvation method was used to produce GNPs, whereas PCL fibers were produced by a dry‐spinning method. The morphological, mechanical, and thermal properties of the produced system were investigated, and the distribution of nanoparticles both inside and on the surface of the fibers was examined. The effect of the particles on the biodegradability of the fibers was also evaluated. In vitro preliminary tests were performed to study the release of BSA from nanoparticle‐laden fibers and to compare this with its release from free nanoparticles. Our results indicate that the distribution of particles inside the fibers was quite homogeneous and only a few of them were present on the surface. The presence of the particles in the fibers did not affect the thermal properties of the PCL polymer matrix, although it created voids that affected the degradation characteristics so the PCL fibers favored faster erosion compared to the plain fibers. Preliminary results indicate that the release from GNP‐laden fibers occurred much more slowly compared to that in the free GNPs. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 44233.     

局部时差约束邻域保持嵌入算法在故障检测中的应用

传统的邻域保持嵌入(neighborhood preserving embedding,NPE)算法通过k近邻(k-nearest neighbors,k-NN)方法选择邻域进行重构来实现降维。但在实际工业过程中采集的样本具有时序相关性,仅仅通过欧氏距离选择近邻样本不能充分反映数据中包含的信息,从而影响检测效果。因此,提出一种局部时差约束邻域保持嵌入(local time difference constrained neighborhood preserving embedding,LTDCNPE)算法,充分考虑样本间的时间和空间关系,从而建立准确的故障检测模型。首先,该算法在固定尺度的时间窗内,根据样本的时序关系和空间特征挑选出邻域。其次,利用样本间的时间差异为邻域样本进行加权,使数据特征保留了高维空间的局部结构。然后,对降维后得到的主元空间和残差空间构建T^{\mathrm{2}}和SPE统计量并确定控制限。最后,通过数值例子和Tennessee-Eastman(TE)过程仿真验证LTDCNPE算法的有效性。     

A nested online scheduling and nonlinear model predictive control framework for multi-product continuous systems

In the pursuit of integrated scheduling and control frameworks for chemical processes, it is important to develop accurate integrated models and computational strategies such that optimal decisions can be made in a dynamic environment. In this study, a recently developed switched system formulation that integrates scheduling and control decisions is extended to closed-loop operation embedded with nonlinear model predictive control (NMPC). The resulting framework is a nested online scheduling and control loop that allows to obtain fast and accurate solutions as no model reduction is needed and no integer variables are involved in the formulations. In the outer loop, the integrated model is solved to calculate an optimal product switching sequence such that the process economics is optimized, whereas in the inner loop, an NMPC implements the scheduling decisions. The proposed scheme was tested on two multi-product continuous systems. Unexpected large disturbances and rush orders were handled effectively.     

Discrete-time contraction constrained nonlinear model predictive control using graph-based geodesic computation

Modern chemical processes need to operate around time-varying operating conditions to optimize plant economy, in response to dynamic supply chains (e.g., time-varying specifications of product and energy costs). As such, the process control system needs to handle a wide range of operating conditions whilst optimizing system performance and ensuring stability during transitions. This article presents a reference-flexible nonlinear model predictive control approach using contraction based constraints. Firstly, a contraction condition that ensures convergence to any feasible state trajectories or setpoints is constructed. This condition is then imposed as a constraint on the optimization problem for model predictive control with a general (typically economic) cost function, utilizing Riemannian weighted graphs and shortest path techniques. The result is a reference flexible and fast optimal controller that can trade-off between the rate of target trajectory convergence and economic benefit (away from the desired process objective). The proposed approach is illustrated by a simulation study on a CSTR control problem.     

Multidrug Idebenone/Naproxen Co-loaded Aspasomes for Significant in vivo Anti-inflammatory Activity

The use of proper nanocarriers for dermal and transdermal delivery of anti-inflammatory drugs recently gained several attentions in the scientific community because they pass intact and accumulate payloads in the deepest layers of skin tissue. Ascorbyl palmitate-based vesicles (aspasomes) can be considered a promising nanocarrier for dermal and transdermal delivery due to their skin whitening properties and suitable delivery of payloads through the skin. The aim of this study was the synthesis of multidrug Idebenone/naproxen co-loaded aspasomes for the development of an effective anti-inflammatory nanomedicine. Aspasomes had suitable physicochemical properties and were safe in vivo if topically applied on human healthy volunteers. Idebenone/naproxen co-loaded aspasomes demonstrated an increased therapeutic efficacy of payloads compared to the commercially available Naprosyn® gel, with a rapid decrease of chemical-induced erythema on human volunteers. These promising results strongly suggested a potential application of Idebenone/naproxen multidrug aspasomes for the development of an effective skin anti-inflammatory therapy.     

Liquid-liquid extraction of protease from cold-adapted yeast Rhodotorula mucilaginosa L7 using biocompatible and biodegradable aqueous two-phase systems

This work aimed to optimize the extraction of an extracellular protease produced by the cold-adapted yeast Rhodotorula mucilaginosa L7 using aqueous two-phase systems (ATPS) comprising polyethylene glycol (PEG) and sodium citrate or sodium tartrate. First, the biocompatibility of the phase forming agents was assessed. The results obtained with PEG-2000, PEG-4000, and PEG-6000 demonstrated that even at large PEG concentrations (32 wt%) the protease maintains its activity after 3 h of reaction, whereas an increase in salt concentration provokes a gradual decrease in protease stability. Subsequently, the partitioning of the protease in both types of ATPS was assessed, evaluating the effect of temperature, molecular weight, and concentration of PEG on protease purification, using two 2³-full factorial designs. The best partitioning conditions were obtained in PEG-6000/sodium tartrate-based ATPS, at 30ºC (with a yield of 81.09 ± 0.66% and a purification factor of 2.51 ± 0.03). Thus, considering the biodegradable characteristics of the system, the PEG/sodium tartrate ATPS is a viable and economic low-resolution step in protease purification, with a strong potential for future industrial application.     

Solvothermal synthesis of zirconia nanomaterials: Latest developments and future

Due to excellent mechanical properties, thermal stability and catalytic characteristics, zirconia is considered as the most important ceramic materials. Different crystal forms make zirconia play a huge role in solid electrolyte fuel cells, catalysts, thermal barrier coatings, denture materials, mobile phone backplanes, etc. The purpose of this paper is to provide a comprehensive review about solvothermal synthesis of nano-zirconia. Firstly, the reactors and systems of solvothermal synthesis in recent years are introduced. Especially, the advancement of continuously flowing microreactors and field-coupled systems are analyzed. Secondly, influencing factors of zirconia solvothermal synthesis are discussed. In addition, solvent effects on the synthesis of nano-zirconia products are clarified, and suggestions for solvent selection are given. Furthermore, the design and mechanism of solvothermal synthesis of zero-, one-, two-and three-dimensional zirconia nanostructures are revealed. Simultaneously, experimental methods and kinetic studies are summarized. Finally, potential applications and challenges are presented for future research directions.