Flexible poly(styrene-ethylene-butadiene-styrene) hybrid nanofibers for bioengineering and water filtration applications

Among the thermoplastic elastomers that play important roles in the polymer industry due to their superior properties, styrene-based species and polyurethane block copolymers are of great interest. Poly(styrene-ethylene-butadiene-styrene) (SEBS) as a triblock copolymer seems to have the potential to meet many demands in different applications due to various industrial requirements where durability, biocompatibility, breaking elongation, and interfacial adhesion are important. In this study, the SEBS triblock copolymer was functionalized with natural (Satureja hortensis, SH) and synthetic (nanopowder, TiO₂) agents to obtain composite nanofibers by electrospinning and electrospraying methods for use in biomedical and water filtration applications. The results were compared with thermoplastic polyurethane (TPU) composite nanofibers, which are commonly used in these fields. Here, functionalized SEBS nanofibers exhibited antibacterial effect while at the same time improving cell viability. In addition, because of successful water filtration by using the SEBS composite nanofibers, the material may have a good potential to be used comparably to TPU for the application.     

Routing of a hazmat truck in the presence of weather systems

This paper focuses on the effects of weather systems on hazmat routing. We start by analyzing the effects of a weather system on a vehicle traversing a single link. This helps characterize the time-dependent attributes of a link due to movement of the weather systems. This analysis is used as a building block for the problem of finding a least risk path for hazmat transportation on a network exposed to such weather systems. Several methods are offered to solve the underlying problem, and computational results are reported. We draw two conclusions from this paper. First, it is possible to determine the time-dependent attributes for links on a network provided that some assumptions on the nature of the weather system are made. Second, heuristics can provide effective solutions for practical size problems while allowing for parking the vehicle to avoid weather system effects.     

Self-aligning planarization and passivation for integration applications in III-V semiconductor devices

This work reports an easy planarization and passivation approach for the integration of III-V semiconductor devices. Vertically etched III-V semiconductor devices typically require sidewall passivation to suppress leakage currents and planarization of the passivation material for metal interconnection and device integration. It is, however, challenging to planarize all devices at once. This technique offers wafer-scale passivation and planarization that is automatically leveled to the device top in the 1-3-/spl mu/m vicinity surrounding each device. In this method, a dielectric hard mask is used to define the device area. An undercut structure is intentionally created below the hard mask, which is retained during the subsequent polymer spinning and anisotropic polymer etch back. The spin-on polymer that fills in the undercut seals the sidewalls for all the devices across the wafer. After the polymer etch back, the dielectric mask is removed leaving the polymer surrounding each device level with its device top to atomic scale flatness. This integration method is robust and is insensitive to spin-on polymer thickness, polymer etch nonuniformity, and device height difference. It prevents the polymer under the hard mask from etch-induced damage and creates a polymer-free device surface for metallization upon removal of the dielectric mask. We applied this integration technique in fabricating an InP-based photonic switch that consists of a mesa photodiode and a quantum-well waveguide modulator using benzocyclobutene (BCB) polymer. We demonstrated functional integrated photonic switches with high process yield of >90%, high breakdown voltage of >25 V, and low ohmic contact resistance of /spl sim/10 /spl Omega/. To the best of our knowledge, such an integration of a surface-normal photodiode and a lumped electroabsorption modulator with the use of BCB is the first to be implemented on a single substrate.     

MMSE decision-feedback equalizers and coding. I. Equalizationresults

The minimum mean-squared-error decision-feedback equalizer (MMSE-DFE) has properties that suggest that it is a canonical equalization structure for systems that combine equalization with coded modulation. The structure and performance of the MMSE-DFE are succinctly derived using linear-estimation-theoretic principles in this first part of this two-part paper. The front-end of the MMSE-DFE, called the “mean-square whitened matched filter” (MS-WMF), is preferable in some ways to a matched filter or a whitened matched filter as a canonical receiver front end. In a coded system, the feedback filter of the MMSE-DFE may be implemented in the transmitter using precoding. The MMSE-DFE can perform significantly better than a zero-forcing decision-feedback equalizer, particularly at moderate-to-low SNR's and on severe-ISI channels. The MMSE-DFE is biased. The optimum unbiased MMSE-DFE is the MMSE-DFE with the bias removed. Removing bias improves error probability, but reduces the SNR to SNR_MMSE-DFE,U=SNR_MMSE-DFE-1. It is shown that this SNR relationship is a particular case of a very general result and that SNR_MMSE-DFE,U gives a more realistic estimate of SNR. The results are extended to partial response equalization and to equalization with correlated inputs in an appendix     

Finite element analysis of combined forming processes by means of rate dependent ductile damage modelling

Sheet metal forming is an inherent part of todays production industry. A major goal is to increase the forming limits of classical deep-drawing processes. One possibility to achieve that is to combine the conventional quasi-static (QS) forming process with electromagnetic high-speed (HS) post-forming. This work focuses on the finite element analysis of such combined forming processes to demonstrate the improvement which can be achieved. For this purpose, a cooperation of different institutions representing different work fields has been established. The material characterization is based on flow curves and forming limit curves for low and high strain rates obtained by novel testing devices. Further experimental investigations have been performed on the process chain of a cross shaped cup, referring to both purely quasi-static and quasi-static combined with electromagnetic forming. While efficient mathematical optimization algorithms support the new viscoplastic ductile damage modelling to find the optimum parameters based on the results of experimental material characterization, the full process chain is studied by means of an electro-magneto-mechanical finite element analysis. The constitutive equations of the material model are integrated in an explicit manner and implemented as a user material subroutine into the commercial finite element package LS-DYNA.     

Revealing determinants of two‐phase dynamics of P53 network under gamma irradiation based on a reduced 2D relaxation oscillator model

This study proposes a two‐dimensional (2D) oscillator model of p53 network, which is derived via reducing the multidimensional two‐phase dynamics model into a model of ataxia telangiectasia mutated (ATM) and Wip1 variables, and studies the impact of p53‐regulators on cell fate decision. First, the authors identify a 6D core oscillator module, then reduce this module into a 2D oscillator model while preserving the qualitative behaviours. The introduced 2D model is shown to be an excitable relaxation oscillator. This oscillator provides a mechanism that leads diverse modes underpinning cell fate, each corresponding to a cell state. To investigate the effects of p53 inhibitors and the intrinsic time delay of Wip1 on the characteristics of oscillations, they introduce also a delay differential equation version of the 2D oscillator. They observe that the suppression of p53 inhibitors decreases the amplitudes of p53 oscillation, though the suppression increases the sustained level of p53. They identify Wip1 and P53DINP1 as possible targets for cancer therapies considering their impact on the oscillator, supported by biological findings. They model some mutations as critical changes of the phase space characteristics. Possible cancer therapeutic strategies are then proposed for preventing these mutations’ effects using the phase space approach.Inspec keywords: physiological models, cellular biophysics, cancer, difference equations, delays, enzymes, biochemistry, molecular biophysics, gamma‐rays, radiation therapyOther keywords: two‐phase dynamics model, P53 network, gamma irradiation, 2D relaxation oscillator model, ATM model, Wip1 variables, p53‐regulators, cell fate decision, excitable relaxation oscillator, Wip1 time delay, state‐dependent delay differential equation, cell cycle arrest, cell apoptosis, cancer therapies, Wip1 overexpression, Wip1 downregulation, ATM deficiency, Mdm2 overexpression, Mdm2 downregulation, mutation effects, phase space approach     

Multiobjective evolutionary clustering of Web user sessions: a case study in Web page recommendation

In this study, we experiment with several multiobjective evolutionary algorithms to determine a suitable approach for clustering Web user sessions, which consist of sequences of Web pages visited by the users. Our experimental results show that the multiobjective evolutionary algorithm-based approaches are successful for sequence clustering. We look at a commonly used cluster validity index to verify our findings. The results for this index indicate that the clustering solutions are of high quality. As a case study, the obtained clusters are then used in a Web recommender system for representing usage patterns. As a result of the experiments, we see that these approaches can successfully be applied for generating clustering solutions that lead to a high recommendation accuracy in the recommender model we used in this paper.     

An adaptive signal compression system with pre-specified reconstruction quality and compression rate

Two essential properties of a signal compression method are the compression rate and the distance between the original signal and the reconstruction from the compressed signal. These two properties are used to assess the performance and quality of the method. In a recent work [B. Tümer, B. Demir?z, Lecture Notes in Computer Science-Computer and Information Sciences, volume 2869, chapter Signal Compression Using Growing Cell Structures: A Transformational Approach, Springer Verlag, 2003, pp. 952-959], an adaptive signal compression system (ACS) is presented which defines the performance of the system as a function of the system complexity, system sensitivity and data size. For a compression method, it is desirable to formulate the performance of the system as a function of the system complexity and sensitivity to optimize the performance of the system. It would be further desirable to express the reconstruction quality in terms of the same system parameters so as to know up front what compression rate to end up with for a specific reconstruction quality. In this work, we modify ACS such that the modified ACS (MACS) estimates the reconstruction quality for a given system complexity and sensitivity. Once this relation is identified it is possible to optimize either compression rate or reconstruction quality with respect to system sensitivity and system complexity while limiting the other one.     

Profiling hospitals based on emergency readmission: a multilevel transition modelling approach

Emergency readmission is seen as an important part of the United Kingdom government policy to improve the quality of care that patients receive. In this context, patients and the public have the right to know how well different health organizations are performing. Most methods for profiling estimate the expected numbers of adverse outcomes (e.g. readmission, mortality) for each organization. A number of statistical concerns have been raised, such as the differences in hospital sizes and the unavailability of relevant data for risk adjustment. Having recognized these statistical concerns, a new framework known as the multilevel transition model is developed. Hospital specific propensities of the first, second and further readmissions are considered to be measures of performance, where these measures are used to define a new performance index. During the period 1997 and 2004, the national (English) hospital episodes statistics dataset comprise more than 5 million patient readmissions. Implementing a multilevel model using the complete population dataset could possibly take weeks to estimate the parameters. To resolve the problem, we extract 1000 random samples from the original data, where each random sample is likely to lead to differing hospital performance measures. For computational efficiency a Grid implementation of the model is developed. Analysing the output from the full 1000 sample, we noticed that 4 out of the 5 worst performing hospitals treating cancer patients were in London. These hospitals are known to be the leading NHS Trusts in England, providing diverse range of services to complex patients, and therefore it is inevitable to expect higher numbers of emergency readmissions.