Characterization of the Absorption of Theophylline From Immediate- and Controlled-Release Dosage Forms With a Numerical Approach Using the In Vitro Dissolution-Permeation Process Using Caco-2 Cells

After oral administration, drug absorption rate is recognized to be dependent on two major factors: dissolution and intestinal cells permeability. Caco-2 monolayer cells have been largely used as a permeation study model. In this study, a numerical approach funded on an exponential first-order time relationship was tested to compare immediate- and controlled-release tablets of theophylline using a dissolution-permeation system. The dissolution performance using USP II paddle apparatus was coupled to the permeability studies investigated in Caco-2 cell monolayers. The dissolved samples were taken at different times; their pH and osmolarity were adjusted to render them suitable to Caco-2 permeability studies (osmolarity = 300 mosm, pH = 7.4). The experimental data show that the dissolution fits the exponential first-order relationship rate. The permeability values were in a range of 4.45 10^- 6-5.28 10^- 6 cm/s, and percentages of absorbed drug dose were dependent on the fraction initially present in the donor compartment, indicating that absorption of theophylline was dissolution rate limited. Plotting experimental absorbed fractions (F_a) against experimental dissolved fractions (F_d) show that permeation is the rate-limiting step in drug absorption process in the extended release form of theophylline. Our results demonstrate a general agreement between observed F_a/F_d relationships and theoretical F_a/F_d relationships obtained with our approach funded on dissolution and permeation behavior. We concluded that the couple dissolution-caco-2 system could be a useful tool to characterize intestinal permeation for a new formulation of a drug compared with the conventional one.     

Fuzzy identification in fuzzy databases: The nuanced relational division

In the present article we review the main research works in fuzzy databases; propose an extension of relation division operator to fuzzy databases; provide a model for fuzzy information and resolve the identification problem in fuzzy databases. For this, three notions are relevant: (a) the concept of nuanced information for representing fuzzy values and the associated nuance, (b) the nuanced division operator, (c) the possibility of weighting attributes in order to express data and query pertinence and trust. We then show how to resolve the problem of fuzzy identification with the nuanced division operator. © 1994 John Wiley & Sons, Inc.     

只用一根线驱动LCD的微控制器

HD44780LCD是嵌入系统中最常见的字母显示器。它唯一的缺点是在4bit模式下要使用6个I/O脚．而在8bit模式下要用多达11个I／O脚。以前的设计实例中曾描述过很多节省或扩展I／O脚的方法（参考文献1、参考文献2、参考文献3）。在驱动一个HD44780兼容LCD时．最好使用基线微控制器,而不是逻辑芯片,因为微控制器成本较低．占用电路板空间较小,并且有编程特性。Microchip推出了最小的PIC10F系列微控制器．都采用6脚SOT-23封装。     

Polystyrene latex particles bearing primary amine groups via soap‐free emulsion polymerization

Polystyrene latexes were prepared in the presence of an amino‐containing functional comonomer, N‐(3‐aminopropyl)methacrylamide hydrochloride (APMH), via soap‐free batch emulsion polymerization initiated by the cationic initiator 2,2′‐azobis(2‐amidinopropane) dihydrochloride. These latexes were characterized by studying the influence of the ionic comonomers on the polymerization kinetics, particle size, surface charge density and colloidal properties. The synthesized latexes were monodisperse with a final size between 100 and 600 nm depending on the APMH concentration. The initial polymerization rate and the particle number increased in accordance with the Smith–Ewart theory for soap‐free styrene emulsion polymerization with a hydrophilic functional comonomer. The final functionalization rate of the particles has been particularly studied with the intention of fitting the prepared latexes to be used in the immobilization of biological molecules for biological sample preparation and diagnostic applications. © 2020 Society of Chemical Industry     

Potato Glycoalkaloids: occurrence,biological activities and extraction for biovalorisation – a review

Potato tuber (Solanum tuberosum L.) is the fourth most important agricultural product after wheat, rice and maize. With a total production of 388 million in 2017, c.a. 70% of this total production is processed in developed countries, producing a large amount of potato peel waste (PPW) as by-product. Although PPW is considered as a zero-value by-product by the feed industry because it is too fibrous, for other recycling industries it is an inexpensive by-product due to its significant contents of some interesting nutrients particularly polyphenols and glycoalkaloids. In potato, and Solanum species in general, many glycoalkaloids, predominantly α-chaconine and α-solanine, have been chemically and structurally identified. However, further research is needed to expand the knowledge of the biological values of potato glycoalkaloids in order to develop a recycling process to extract these technologically and nutritionally interesting bioactive ingredients for different sectors, in particular, the agricultural, food and pharmaceutical ones, which are demanding natural, safe and eco-friendly ingredients.     

Anomalous behavior detection-based approach for authenticating smart home system users

International Journal of Information Security - This paper presents Duenna, an authentication framework for smart home systems (SHSs). When using controlling apps (e.g., a smartphone app), Duenna...     

ECRP: an energy-aware cluster-based routing protocol for wireless sensor networks

Energy conservation is the main issue in wireless sensor networks. Many existing clustering protocols have been proposed to balance the energy consumption and maximize the battery lifetime of sensor nodes. However, these protocols suffer from the excessive overhead due to repetitive clustering resulting in high-energy consumption. In this paper, we propose energy-aware cluster-based routing protocol (ECRP) in which not only the cluster head (CH) role rotates based on energy around all cluster members until the end of network functioning to avoid frequent re-clustering, but also it can adapt the network topology change. Further, ECRP introduces a multi-hop routing algorithm so that the energy consumption is minimized and balanced. As well, a fault-tolerant mechanism is proposed to cope up with the failure of CHs and relay nodes. We perform extensive simulations on the proposed protocol using different network scenarios. The simulation results demonstrate the superiority of ECRP compared with recent and relevant existing protocols in terms of main performance metrics.

     

Feature selection and fault‐severity classification–based machine health assessment methodology for point machine sliding‐chair degradation

In this paper, we propose an offline and online machine health assessment (MHA) methodology composed of feature extraction and selection, segmentation‐based fault severity evaluation, and classification steps. In the offline phase, the best representative feature of degradation is selected by a new filter‐based feature selection approach. The selected feature is further segmented by utilizing the bottom‐up time series segmentation to discriminate machine health states, ie, degradation levels. Then, the health state fault severity is extracted by a proposed segment evaluation approach based on within segment rate‐of‐change (RoC) and coefficient of variation (CV) statistics. To train supervised classifiers, a priori knowledge about the availability of the labeled data set is needed. To overcome this limitation, the health state fault‐severity information is used to label (eg, healthy, minor, medium, and severe) unlabeled raw condition monitoring (CM) data. In the online phase, the fault‐severity classification is carried out by kernel‐based support vector machine (SVM) classifier. Next to SVM, the k‐nearest neighbor (KNN) is also used in comparative analysis on the fault severity classification problem. Supervised classifiers are trained in the offline phase and tested in the online phase. Unlike to traditional supervised approaches, this proposed method does not require any a priori knowledge about the availability of the labeled data set. The proposed methodology is validated on infield point machine sliding‐chair degradation data to illustrate its effectiveness and applicability. The results show that the time series segmentation‐based failure severity detection and SVM‐based classification are promising.     

SupraCells: Living Mammalian Cells Protected within Functional Modular Nanoparticle‐Based Exoskeletons

Creating a synthetic exoskeleton from abiotic materials to protect delicate mammalian cells and impart them with new functionalities could revolutionize fields like cell‐based sensing and create diverse new cellular phenotypes. Herein, the concept of “SupraCells,” which are living mammalian cells encapsulated and protected within functional modular nanoparticle‐based exoskeletons, is introduced. Exoskeletons are generated within seconds through immediate interparticle and cell/particle complexation that abolishes the macropinocytotic and endocytotic nanoparticle internalization pathways that occur without complexation. SupraCell formation is shown to be generalizable to wide classes of nanoparticles and various types of cells. It induces a spore‐like state, wherein cells do not replicate or spread on surfaces but are endowed with extremophile properties, for example, resistance to osmotic stress, reactive oxygen species, pH, and UV exposure, along with abiotic properties like magnetism, conductivity, and multifluorescence. Upon decomplexation cells return to their normal replicative states. SupraCells represent a new class of living hybrid materials with a broad range of functionalities.