A novel diblock copolymer of (monomethoxy poly [ethylene glycol]-oleate) with a small hydrophobic fraction to make stable micelles/polymersomes for curcumin delivery to cancer cells

Curcumin is a potent natural anticancer agent, but its effectiveness is limited by properties such as very low solubility, high rate of degradation, and low rate of absorption of its hydrophobic molecules in vivo. To date, various nanocarriers have been used to improve the bioavailability of this hydrophobic biomaterial. This study investigates the encapsulation of curcumin in a novel nanostructure of monomethoxy poly(ethylene glycol)-oleate (mPEG-OA) and its anticancer effect. Tests were done to determine the critical micelle concentration (CMC), encapsulation efficiency, drug-loading efficiency, and cytotoxicity (against U87MG brain carcinoma cells and HFSF-PI3 cells as normal human fibroblasts) of some nanodevice preparations. The results of fluorescence microscopy and cell-cycle analyses indicated that the in vitro bioavailability of the encapsulated curcumin was significantly greater than that of free curcumin. Cytotoxicity evaluations showed that half maximal inhibitory concentrations of free curcumin and curcumin-loaded mPEG-OA for the U87MG cancer cell line were 48 μM and 24 μM, respectively. The Annexin-V-FLUOS assay was used to quantify the apoptotic effect of the prepared nanostructures. Apoptosis induction was observed in a dose-dependent manner after curcumin-loaded mPEG-OA treatments. Two common self-assembling structures, micelles and polymersomes, were observed by atomic force microscopy and dynamic light scat­tering, and the abundance of each structure was dependent on the concentration of the diblock copolymer. The mPEG-OA micelles had a very low CMC (13.24 μM or 0.03 g/L). Moreover, atomic force microscopy and dynamic light scattering showed that the curcumin-loaded mPEG-OA polymersomes had very stable structures, and at concentrations 1,000 times less than the CMC, at which the micelles disappear, polymersomes were the dominant structures in the dispersion with a reduced size distribution below 150 nm. Overall, the results from these tests revealed that this nanocarrier can be considered as an appropriate drug delivery system for delivering curcumin to cancer cells. © 2014 Erfani-Moghadam et al

Identifying Retweetable Tweets with a Personalized Global Classifier

In this paper we present a method to identify tweets that a user may find interesting enough to retweet. The method is based on a global, but personalized classifier, which is trained on data from several users, represented in terms of user-specific features. Thus, the method is trained on a sufficient volume of data, while also being able to make personalized decisions, i.e., the same post received by two different users may lead to different classification decisions. Experimenting with a collection of approx.\ 130K tweets received by 122 journalists, we train a logistic regression classifier, using a wide variety of features: the content of each tweet, its novelty, its text similarity to tweets previously posted or retweeted by the recipient or sender of the tweet, the network influence of the author and sender, and their past interactions. Our system obtains F1 approx. 0.9 using only 10 features and 5K training instances.Comment: This is a long paper version of the extended abstract titled "A Personalized Global Filter To Predict Retweets", of the same authors, which was published in the 25th ACM UMAP conference in Bratislava, Slovakia, in July 201

Artificial Intelligence (AI) and User Experience (UX) design: A systematic literature review and future research agenda

PurposeThe aim of this article is to map the use of AI in the user experience (UX) design process. Disrupting the UX process by introducing novel digital tools such as Artificial Intelligence (AI) has the potential to improve efficiency and accuracy, while creating more innovative and creative solutions. Thus, understanding how AI can be leveraged for UX has important research and practical implications.Design/Methodology/ApproachThis article builds on a systematic literature review approach and aims to understand how AI is used in UX design today, as well as uncover some prominent themes for future research. Through a process of selection and filtering, 46 research articles are analysed, with findings synthesized based on a user-centred design and development process.FindingsOur analysis shows how AI is leveraged in the UX design process at different key areas. Namely, these include understanding the context of use, uncovering user requirements, aiding solution design, and evaluating design, and for assisting development of solutions. We also highlight the ways in which AI is changing the UX design process through illustrative examples.Originality/valueWhile there is increased interest in the use of AI in organizations, there is still limited work on how AI can be introduced into processes that depend heavily on human creativity and input. Thus, we show the ways in which AI can enhance such activities and assume tasks that have been typically performed by humans

DEVELOPMENT OF A MICROFLUIDIC GAS GENERATOR FROM AN EFFICIENT FILM-BASED MICROFABRICATION METHOD

Recently, tape&film based microfabrication method has been studied for rapid prototyping of microfluidic devices due to its low cost and ease of fabrication [1]. But most of the reported film-based microfluidic devices are simple single-layer patterned 2D designs, whose potential applications are limited. In this paper, we present the design, fabrication and testing results of a 3D structured microfluidic gas generator prototype. This gas generator is used as an example to introduce our new approach of film-based fabrication method towards lab-use microfluidic research, which usually requires constant change of design and prefers low fabrication cost and short fabrication period. The prototype is a film-based comprehensive microfluidic gas generator which integrates self-circulation, self-regulation, catalytic reaction and gas/liquid separation. Time and economy efficiency are the biggest merit of this method. The only required facility during the whole process is a digital craft-cutter. The working principle of the device is illustrated in Fig.1

Bounded Verification with On-the-Fly Discrepancy Computation

Simulation-based verification algorithms can provide formal safety guarantees for nonlinear and hybrid systems. The previous algorithms rely on user provided model annotations called discrepancy function, which are crucial for computing reachtubes from simulations. In this paper, we eliminate this requirement by presenting an algorithm for computing piece-wise exponential discrepancy functions. The algorithm relies on computing local convergence or divergence rates of trajectories along a simulation using a coarse over-approximation of the reach set and bounding the maximal eigenvalue of the Jacobian over this over-approximation. The resulting discrepancy function preserves the soundness and the relative completeness of the verification algorithm. We also provide a coordinate transformation method to improve the local estimates for the convergence or divergence rates in practical examples. We extend the method to get the input-to-state discrepancy of nonlinear dynamical systems which can be used for compositional analysis. Our experiments show that the approach is effective in terms of running time for several benchmark problems, scales reasonably to larger dimensional systems, and compares favorably with respect to available tools for nonlinear models.Comment: 24 page

Nanocasting Synthesis of Ultrafine WO3 Nanoparticles for Gas Sensing Applications

Ultrafine WO3 nanoparticles were synthesized by nanocasting route, using mesoporous SiO2 as a template. BET measurements showed a specific surface area of 700 m 2/gr for synthesized SiO2, while after impregnation and template removal, this area was reduced to 43 m 2/gr for WO3 nanoparticles. HRTEM results showed single crystalline nanoparticles with average particle size of about 5 nm possessing a monoclinic structure, which is the favorite crystal structure for gas sensing applications. Gas sensor was fabricated by deposition of WO3 nanoparticles between electrodes via low frequency AC electrophoretic deposition. Gas sensing measurements showed that this material has a high sensitivity to very low concentrations of NO2 at 250°C and 300°C

Product assurance technology for procuring reliable, radiation-hard, custom LSI/VLSI electronics

Advanced measurement methods using microelectronic test chips are described. These chips are intended to be used in acquiring the data needed to qualify Application Specific Integrated Circuits (ASIC's) for space use. Efforts were focused on developing the technology for obtaining custom IC's from CMOS/bulk silicon foundries. A series of test chips were developed: a parametric test strip, a fault chip, a set of reliability chips, and the CRRES (Combined Release and Radiation Effects Satellite) chip, a test circuit for monitoring space radiation effects. The technical accomplishments of the effort include: (1) development of a fault chip that contains a set of test structures used to evaluate the density of various process-induced defects; (2) development of new test structures and testing techniques for measuring gate-oxide capacitance, gate-overlap capacitance, and propagation delay; (3) development of a set of reliability chips that are used to evaluate failure mechanisms in CMOS/bulk: interconnect and contact electromigration and time-dependent dielectric breakdown; (4) development of MOSFET parameter extraction procedures for evaluating subthreshold characteristics; (5) evaluation of test chips and test strips on the second CRRES wafer run; (6) two dedicated fabrication runs for the CRRES chip flight parts; and (7) publication of two papers: one on the split-cross bridge resistor and another on asymmetrical SRAM (static random access memory) cells for single-event upset analysis

Experimental Biological Protocols with Formal Semantics

Both experimental and computational biology is becoming increasingly automated. Laboratory experiments are now performed automatically on high-throughput machinery, while computational models are synthesized or inferred automatically from data. However, integration between automated tasks in the process of biological discovery is still lacking, largely due to incompatible or missing formal representations. While theories are expressed formally as computational models, existing languages for encoding and automating experimental protocols often lack formal semantics. This makes it challenging to extract novel understanding by identifying when theory and experimental evidence disagree due to errors in the models or the protocols used to validate them. To address this, we formalize the syntax of a core protocol language, which provides a unified description for the models of biochemical systems being experimented on, together with the discrete events representing the liquid-handling steps of biological protocols. We present both a deterministic and a stochastic semantics to this language, both defined in terms of hybrid processes. In particular, the stochastic semantics captures uncertainties in equipment tolerances, making it a suitable tool for both experimental and computational biologists. We illustrate how the proposed protocol language can be used for automated verification and synthesis of laboratory experiments on case studies from the fields of chemistry and molecular programming