Effect of stents coated with a combination of sirolimus and alpha-lipoic acid in a porcine coronary restenosis model

The aim of this study was to evaluate antiproliferative sirolimus- and antioxidative alpha-lipoic acid (ALA)-eluting stents using biodegradable polymer [poly-l-lactic acid (PLA)] in a porcine coronary overstretch restenosis model. Forty coronary arteries of 20 pigs were randomized into four groups in which the coronary arteries had a bare metal stent (BMS, n = 10), ALA-eluting stent with PLA (AES, n = 10), sirolimus-eluting stent with PLA (SES, n = 10), or sirolimus- and ALA-eluting stent with PLA (SAS, n = 10). A histopathological analysis was performed 28 days after the stenting. The ALA and sirolimus released slowly over 30 days. There were no significant differences between groups in the injury or inflammation score; however, there were significant differences in the percent area of stenosis (56.2 ± 11.78 % in BMS vs. 51.5 ± 12.20 % in AES vs. 34.7 ± 7.23 % in SES vs. 28.7 ± 7.30 % in SAS, P < 0.0001) and fibrin score [1.0 (range 1.0–1.0) in BMS vs. 1.0 (range 1.0–1.0) in AES vs. 2.0 (range 2.0–2.0) in SES vs. 2.0 (range 2.0–2.0) in SAS, P < 0.0001] between the four groups. The percent area of stenosis based on micro-computed tomography corresponded with the restenosis rates based on histopathological stenosis in different proportions in the four groups (54.8 ± 7.88 % in BMS vs. 50.4 ± 14.87 % in AES vs. 34.5 ± 7.22 % in SES vs. 28.9 ± 7.22 % in SAS, P < 0.05). SAS showed a better neointimal inhibitory effect than BMS, AES, and SES at 1 month after stenting in a porcine coronary restenosis model. Therefore, SAS with PLA can be a useful drug combination for coronary stent coating to suppress neointimal hyperplasia.     

Highly Exposed ?NH2 Edge on Fragmented g-C3N4 Framework with Integrated Molybdenum Atoms for Catalytic CO2 Cycloaddition: DFT and Techno-Economic Assessment

This study focuses on the applicability of single-atom Mo-doped graphitic carbon nitride (GCN) nanosheets which are specifically engineered with high surface area (exfoliated GCN),  NH₂ rich edges, and maximum utilization of isolated atomic Mo for propylene carbonate (PC) production through CO₂ cycloaddition of propylene oxide (PO). Various operational parameters are optimized, for example, temperature (130 °C), pressure (20 bar), catalyst (Mo₂GCN), and catalyst mass (0.1 g). Under optimal conditions, 2% Mo-doped GCN (Mo₂GCN) has the highest catalytic performance, especially the turnover frequency (TOF) obtained, 36.4 h⁻¹ is higher than most reported studies. DFT simulations prove the catalytic performance of Mo₂GCN significantly decreases the activation energy barrier for PO ring-opening from 50–60 to 4.903 kcal mol⁻¹. Coexistence of Lewis acid/base group improves the CO₂ cycloaddition performance by the formation of coordination bond between electron-deficient Mo atom with O atom of PO, while  NH₂ surface group disrupts the stability of CO₂ bond by donating electrons into its low-level empty orbital. Steady-state process simulation of the industrial-scale consumes 4.4 ton h⁻¹ of CO₂ with PC production of 10.2 ton h⁻¹. Techno-economic assessment profit from Mo₂GCN is estimated to be 60.39 million USD year⁻¹ at a catalyst loss rate of 0.01 wt% h⁻¹.     

Periodic orbits: a new language for neuronal dynamics

A new nonlinear dynamical analysis is applied to complex behavior from neuronal systems. The conceptual foundation of this analysis is the abstraction of observed neuronal activities into a dynamical landscape characterized by a hierarchy of "unstable periodic orbits" (UPOs). UPOs are rigorously identified in data sets representative of three different levels of organization in mammalian brain. An analysis based on UPOs affords a novel alternative method of decoding, predicting, and controlling these neuronal systems.     

Hybrid phenol biosensor based on modified phenoloxidase electrode

Electrolytic deposition has been widely used to immobilize biomacromolecules, and it is always the most important factor to preserve or even increase an activity of the immobilized protein. We report here simple and rather universal method for the highly efficient immobilization of laccase for amperometric biosensing. Laccase from Cerrena unicolor has been successfully immobilized (electrolytic deposition) on the surface of thin, ordered polythiophene films (3-methylthiophene/3-thiopheneacetic acid/N-heptyl-3,6-bis(2-thiophene)carbazole). Two different compounds capable of mediating laccase-catalyzed reactions have been tested by cyclic voltammetry. They exhibited quasi-reversible electrodic behaviour with formal redox potentials ranging from 68 and 918 mV (E⁰vs. SCE). The immersion of the laccase-coated electrode in solution with substrate generated large catalytic currents easily recorded by cyclic voltammetry at low potential scan rates. Considering the fact, that immobilization strategy showed high efficiency, obtained results suggest that method for phenoloxidase immobilization has a great potential of enabling high throughput fabrication of bioelectronics’ devices.     

Soft set theory applied to p-ideals of BCI-algebras related to fuzzy points

The notions of $(\overline{\in}, \overline{\in} \vee \overline{\hbox{q}})The notions of ([`( ? )],[`( ? )] ú[`q])(\overline{\in}, \overline{\in} \vee \overline{\hbox{q}})-fuzzy p-ideals and fuzzy p-ideals with thresholds related to soft set theory are discussed. Relations between ([`( ? )],[`( ? )] ú[`q])(\overline{\in}, \overline{\in} \vee \overline{\hbox{q}})-fuzzy ideals and ([`( ? )],[`( ? )] ú[`q])(\overline{\in}, \overline{\in} \vee \overline{\hbox{q}})-fuzzy p-ideals are investigated. Characterizations of an ([`( ? )],[`( ? )] ú[`q])(\overline{\in}, \overline{\in} \vee \overline{\hbox{q}})-fuzzy p-ideal and a fuzzy p-ideal with thresholds are displayed. Implication-based fuzzy p-ideals are discussed.     

Robust portfolio optimization via solution to the Hamilton–Jacobi–Bellman equation

We consider a problem of dynamic stochastic portfolio optimization modelled by a fully non-linear Hamilton–Jacobi–Bellman (HJB) equation. Using the Riccati transformation, the HJB equation is transformed to a simpler quasi-linear partial differential equation. An auxiliary quadratic programming problem is obtained, which involves a vector of expected asset returns and a covariance matrix of the returns as input parameters. Since this problem can be sensitive to the input data, we modify the problem from fixed input parameters to worst-case optimization over convex or discrete uncertainty sets both for asset mean returns and their covariance matrix. Qualitative as well as quantitative properties of the value function are analysed along with providing illustrative numerical examples. We show application to robust portfolio optimization for the German DAX30 Index.     

A flexible encapsulated MEMS pressure sensor system for biomechanical applications

 The use of pressure sensors made of conductive polymers is common in biomechanical applications. Unfortunately, hysteresis, nonlinearity, non-repeatability and creep have a significant effect on the pressure readings when such conductive polymers are used. The objective of this paper is to explore the potential of a new flexible encapsulated micro electromechanical system (MEMS) pressure sensor system as an alternative for human interface pressure measurement. A prototype has been designed, fabricated, and characterized. Testing has shown that the proposed packaging approach shows very little degradation in the performance characteristics of the original MEMS pressure sensor. The much-needed characteristics of repeatability, linearity, low hysteresis, temperature independency are preserved. Thus the flexible encapsulated MEMS pressure sensor system is very promising and shows superiority over the commercially available conductive polymer film sensors for pressure measurement in biomechanical applications. Received: 1 December 1999/Accepted: 17 August 2000     

A low cost, non-individualized surround sound system based upon head related transfer functions: an ergonomics study and prototype development

This paper reports on the types and magnitudes of localization errors of simulated binaural direction cues generated using non-individualized, head-related transfer functions (HRTFs) with different levels of complexity. Four levels of complexity, as represented by the number of non-zero coefficients of the associated HRTF filters (128, 64, 32, 18 non-zero coefficients), were studied. Experiment 1 collected 1728 data runs that were exhaustive combinations of the four levels of complexity, nine simulated directions of sound (no direction (i.e., diotical-mono), 0 degrees , 45 degrees , 90 degrees , 135 degrees , 180 degrees , 225 degrees , 270 degrees , and 315 degrees azimuth angles at 0 degrees elevation), two repetitions, and 24 participants). Binaural cues generated from HRTFs of reduced complexity (from 128 to 18 non-zero coefficients) produced significantly higher localization errors for the directions of 45 degrees , 135 degrees , 225 degrees , and 315 degrees azimuth angles (p<0.01). From the directions of 0 degrees , 90 degrees , and 270 degrees azimuth angles, the cues produced by HRTFs with reduced complexity did not affect the localization error (p>0.2). Surprisingly, cues produced by HRTFs of 128 non-zero coefficients did not have the lowest number of errors. From 45 degrees , 135 degrees , 225 degrees , and 315 degrees , the lowest numbers of errors were obtained from cues produced by HRTFs of 64, 32, 32, and 64 non-zero coefficients, respectively. Based on these findings, a prototype virtual headphone-based surround-sound (VHSS) system was developed. A double-blind usability experiment with 32 participants indicated that the prototype VHSS system received significantly better surround-sound ratings than did a Dolby stereo system (p<0.02). This paper reports results from an original ergonomics study and the application of these results to the design of a consumer product.     

Computation of madalines' sensitivity to input and weight perturbations

The sensitivity of a neural network's output to its input and weight perturbations is an important measure for evaluating the network's performance. In this letter, we propose an approach to quantify the sensitivity of Madalines. The sensitivity is defined as the probability of output deviation due to input and weight perturbations with respect to overall input patterns. Based on the structural characteristics of Madalines, a bottom-up strategy is followed, along which the sensitivity of single neurons, that is, Adalines, is considered first and then the sensitivity of the entire Madaline network. By means of probability theory, an analytical formula is derived for the calculation of Adalines' sensitivity, and an algorithm is designed for the computation of Madalines' sensitivity. Computer simulations are run to verify the effectiveness of the formula and algorithm. The simulation results are in good agreement with the theoretical results.