Fabrication of chitosan/polyvinyl alcohol/amine modified carbon nanotube composite films for rapid chromate removal

Composite adsorbent films with amine and hydroxyl functionalities were synthesized from chitosan (CS), polyvinyl alcohol (PVA), and amine-modified carbon nanotubes (a-MWCNT) by solvent casting method. Weight proportions of CS to PVA and weight percent of a-MWCNT were optimized to achieve highest chromate removal capacity. Structural characteristics of the composites were investigated using scanning electron microscopy, Fourier transform infrared spectroscopy, Raman spectroscopy, and thermal gravimetric analysis. Accordingly, incorporation of a-MWCNT to CS/PVA structure resulted in the generation of nanochannels, which enhanced adsorption capacity. Moreover, the composite comprising 0.4% wt. a-MWCNT provided over 99% of Cr (VI) removal from 50 mg L⁻¹ Cr (VI) solution within five minutes of contact time. Redlich–Peterson and Radke–Prausnitz isotherm models provided the highest conformity to adsorption data. Maximum chromate sorption capacity of CS/PVA/a-MWCNT composite film was determined as 134.2 mg g⁻¹ being 172% higher than that of CS/PVA. Regeneration was best achieved in 1.0 M NaOH and the composite was shown to retain at least 70% of its original capacity after five consecutive adsorption–desorption cycles.     

Modeling discrete event scalable network systems

Scalability in simulation tools is one of the most important traits to measure performance of software. The reason is that today’s Internet is the main instance of a large-scale and highly complex system. Simulation of Internet-scale network systems has to be supported by any simulation tool. Despite this fact, many network simulators lacks support for building large models. In this work, in order to propose a new approach for scalability issue in network simulation tools, a network simulator is developed based on behavior of honeybees and high performance DEVS, modular and hierarchical system theoretic approach. A biologically-inspired discrete event modeling approach is described for studying networks’ scalability and performance traits. Since natural systems can offer important concepts for modeling network systems, key adaptive and emergent attributes of honeybees and their societal properties are incorporated into a set of simulation models that are developed using the discrete event system specification approach. Large-scale network models are simulated and evaluated to show the benefits of nature-inspired network models.     

Surface modification of polysulfone based hemodialysis membranes with layer by layer self assembly of polyethyleneimine/alginate-heparin: a simple polyelectrolyte blend approach for heparin immobilization

This study intends to improve blood compatibility of polysulfone (PSF) membranes by generating a nonthrombogenic surface through heparin immobilization. To achieve this task, the support membrane prepared from a blend of PSF and sulfonated polysulfone (SPSF) was modified with layer by layer (LBL) deposition of polyethyleneimine (PEI) and alginate (ALG) and heparin blended with ALG was immobilized only on the outermost surface of the LBL assembly. The results have shown that the adsorption of human plasma proteins and platelet activation on the LBL modified membranes decreased significantly compared with the unmodified PSF and PSF-SPSF blend membranes. Furthermore, blending ALG with a small amount of heparin remarkably prolonged the APTT values of heparin free PEI/ALG coated membranes. It is envisaged that the use of a blend of HEP and ALG only in the terminating layer of the LBL assembly can be an economical and alternative modification technique to create nonthrombogenic surfaces.     

Review and comparative evaluation of symbolic dynamic filtering for detection of anomaly patterns

Symbolic dynamic filtering (SDF) has been recently reported in literature as a pattern recognition tool for early detection of anomalies (i.e., deviations from the nominal behavior) in complex dynamical systems. This paper presents a review of SDF and its performance evaluation relative to other classes of pattern recognition tools, such as Bayesian Filters and Artificial Neural Networks, from the perspectives of: (i) anomaly detection capability, (ii) decision making for failure mitigation and (iii) computational efficiency. The evaluation is based on analysis of time series data generated from a nonlinear active electronic system. This work has been supported in part by the U.S. Army Research Laboratory and the U.S. Army Research Office under Grant No. W911NF-07-1-0376, by the U.S. Office of Naval Research under Grant No. N00014-08-1-380, and by NASA under Cooperative Agreement No. NNX07AK49A.     

Magnetically controlled shape-memory effects of hybrid nanocomposites from oligo(ω-pentadecalactone) and covalently integrated magnetite nanoparticles

The covalent integration of inorganic nanoparticles in polymer matrices has gained significance for improving the structural properties of polymer-based materials. Here we report on the performance of poly(ω-pentadecalactone) networks with magnetite nanoparticles as netpoints in their magnetically-controlled shape-memory capability. Hybrid nanocomposites with magnetite nanoparticle content ranging from 5 to 11 wt% were prepared by reacting two types of oligo(ω-pentadecalactone) (OPDL) based precursors with terminal hydroxy groups, a three arm OPDL (³AOPDL, M_n = 6000 g mol⁻¹) and an OPDL (M_n = 3300 g mol⁻¹) coated magnetite nanoparticle (∅ = 10 nm), with a diisocyanate. Homogenous hybrid nanocomposites were obtained independent from the weight content of the OPDL decorated nanoparticles in the samples. At 100 °C (T > T_m-OPDL) the covalent integration of the nanoparticles increased the mechanical strength with increasing weight content whereby the elasticity remained almost constant. In magnetically-controlled one-way dual-shape experiments the shape fixity decreased from 95% to 90% but the shape recovery increased slightly from 95% to 97% when the nanoparticle content was increased. In magnetically-controlled reversible dual-shape experiments the nanoparticles had a restraining effect and the maximum shape-change of 65% for hybrid nanocomposites with 5 wt% magnetite nanoparticles was reduced to 36% when the particle content was increased to 11 wt%. These results show that the performance of hybrid nanocomposites can be tailored by nanoparticle content, however in terms of their applicability either mechanical strength or actuation capability should be focussed in the material selection.     

Effect of bar shape on the pull-out capacity of fully-grouted rockbolts

This paper presents experimental results obtained from the direct pull-out test using different types of rockbolts having different shape of lugs. These are smooth surface bars, ribbed bars, single conical lugged bars, double conical lugged bars and triple conical lugged bars. It is found that the failure mechanism of the conical lugged rock bolt is different from that of conventional rockbolts, in which the adhesion or the shear strength at the bolt–grout interface provides the load bearing capacity. From the results of experimental study, the use of the conical lugged rock bolts is suggested, because it provides a greater anchorage strength due to wedging effect that is a combination of the shear and compressive strength of the grouting material.     

Peptide Human Neutrophil Elastase Inhibitors from Natural Sources: An Overview

Elastases are a broad group of enzymes involved in the lysis of elastin, the main component of elastic fibres. They are produced and released in the human body, mainly by neutrophils and the pancreas. The imbalance between elastase activity and its endogenous inhibitors can cause different illnesses due to their excessive activity. The main aim of this review is to provide an overview of the latest advancements on the identification, structures and mechanisms of action of peptide human neutrophil elastase inhibitors isolated from natural sources, such as plants, animals, fungi, bacteria and sponges. The discovery of new elastase inhibitors could have a great impact on the pharmaceutical development of novel drugs through the optimization of the natural lead compounds. Bacteria produce mainly cyclic peptides, while animals provide for long and linear amino acid sequences. Despite their diverse natural sources, these elastase inhibitors show remarkable IC₅₀ values in a range from nM to μM values, thus representing an interesting starting point for the further development of potent bioactive compounds on human elastase enzymes.     

Evaluation of heat transfer correlations for HCCI engine modeling

Combustion in HCCI engines is a controlled auto-ignition of well-mixed fuel, air and residual gas. The thermal conditions of the combustion chamber are governed by chemical kinetics strongly coupled with heat transfer from the hot gas to the walls. The heat losses have a critical effect on HCCI ignition timing and burning rate, so it is essential to understand heat transfer process in the combustion chamber in the modeling of HCCI engines. In the present paper, a comparative analysis is performed to investigate the performance of well-known heat transfer correlations in an HCCI engine. The results from the existing correlations are compared with the experimental results obtained in a single-cylinder engine. Significant differences are observed between the heat transfer results obtained by using Woschni, Assanis and Hohenberg correlations.     

Elliptical slot based polarization insensitive compact and flexible chipless RFID tag

A miniaturized, polarization insensitive, and fully passive chipless radio frequency identification tag is proposed in this research article. The realized tag is based on slotted elliptical structures in a nested loop fashion with identical lengths and widths of slot resonators. Alteration of data sequence is accomplished by addition and elimination of nested resonators in the geometric structure. The tag is capable to encode 10 bits of data and covers spectral range from 3.6 to 15.6 GHz. The formulated structure demonstrates polarization insensitive characteristic. The data encoding structure is analyzed and optimized for different substrates that are, Rogers RT/duroid/5880, Rogers RT/duroid/5870, and Taconic TLX‐0 over the miniaturized footprint of 22.8 × 16 mm². The presented tag is robust, novel, compact, and flexible exhibiting a stable response to impinging electromagnetic waves at various angles of incidence.     

Strategic effort allocation in online innovation tournaments

Online innovation tournaments, such as those hosted by crowdsourcing platforms (e.g., Kaggle), have been widely adopted by firms to evolve creative solutions to various problems. Solvers compete in these tournaments to earn rewards. In such competitive environments, it is imperative that solvers provide creative solutions with minimum effort. This article explores the factors that influence the solvers’ effort allocation decisions in a dynamic tournament setting. Specifically, comprehensive time variant data of teams that participated in crowdsourcing competitions on Kaggle were analyzed to gain insight into how solvers continually formulate strategies in light of performance feedback obtained through interim ranking. The results suggest that solvers strategically allocate their efforts throughout the contest to dynamically optimize their payoffs through balancing the probability of winning and the cost of expending effort. In particular, solvers tend to increase their efforts toward the end of tournaments or when they get closer to winning positions. Furthermore, our findings indicate that a last-minute surge in effort is more prevalent among high-skill solvers than in those with lower skill levels. In addition to providing insights that may help solvers develop strategies to improve their performance, the study has implications for the design of online crowdsourcing platforms, particularly in terms of incentivizing solvers to put forth their best effort.