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.     

Isometric Texture Mapping for Free-form Surfaces

Texture mapping is a frequently exploited technique in computer graphics aimed at the emulation of high-resolution details in surfaces. In this paper we present a distance-ratios preservation method for bivariate raster texture mapping to free-form surfaces in an arbitrarily precise manner. The proposed method reduces the original general problem of computing the inverse of a three-dimensional parametric surface mapping into a problem of two-dimensional image warping. Several examples that demonstrate the proposed approach are also provided.     

Selective determination of urea using urease immobilized on ZnO nanowires

Well-aligned zinc oxide (ZnO) nanowire arrays were fabricated on gold-coated plastic substrates using a low-temperature aqueous chemical growth (ACG) method. The ZnO nanowire arrays with 50–130 nm diameters and ∼1 μm in lengths were used in an enzyme-based urea sensor through immobilization of the enzyme urease that was found to be sensitive to urea concentrations from 0.1 mM to 100 mM. Two linear sensitivity regions were observed when the electrochemical responses (EMF) of the sensors were plotted vs. the logarithmic concentration range of urea from 0.1 mM to 100 mM. The proposed sensor showed a sensitivity of 52.8 mV/decade for 0.1–40 mM urea and a fast response time less than 4 s was achieved with good selectivity, reproducibility and negligible response to common interferents such as ascorbic acid and uric acid, glucose, K⁺ and Na⁺ ions.     

Integrated Data Management for a Fleet of Search‐and‐rescue Robots

Search‐and‐rescue operations have recently been confronted with the introduction of robotic tools that assist the human search‐and‐rescue workers in their dangerous but life‐saving job of searching for human survivors after major catastrophes. However, the world of search and rescue is highly reliant on strict procedures for the transfer of messages, alarms, data, and command and control over the deployed assets. The introduction of robotic tools into this world causes an important structural change in this procedural toolchain. Moreover, the introduction of search‐and‐rescue robots acting as data gatherers could potentially lead to an information overload toward the human search‐and‐rescue workers, if the data acquired by these robotic tools are not managed in an intelligent way. With that in mind, we present in this paper an integrated data combination and data management architecture that is able to accommodate real‐time data gathered by a fleet of robotic vehicles on a crisis site, and we present and publish these data in a way that is easy to understand by end‐users. In the scope of this paper, a fleet of unmanned ground and aerial search‐and‐rescue vehicles is considered, developed within the scope of the European ICARUS project. As a first step toward the integrated data‐management methodology, the different robotic systems require an interoperable framework in order to pass data from one to another and toward the unified command and control station. As a second step, a data fusion methodology will be presented, combining the data acquired by the different heterogenic robotic systems. The computation needed for this process is done in a novel mobile data center and then (as a third step) published in a software as a service (SaaS) model. The SaaS model helps in providing access to robotic data over ubiquitous Ethernet connections. As a final step, we show how the presented data‐management architecture allows for reusing recorded exercises with real robots and rescue teams for training purposes and teaching search‐and‐rescue personnel how to handle the different robotic tools. The system was validated in two experiments. First, in the controlled environment of a military testing base, a fleet of unmanned ground and aerial vehicles was deployed in an earthquake‐response scenario. The data gathered by the different interoperable robotic systems were combined by a novel mobile data center and presented to the end‐user public. Second, an unmanned aerial system was deployed on an actual mission with an international relief team to help with the relief operations after major flooding in Bosnia in the spring of 2014. Due to the nature of the event (floods), no ground vehicles were deployed here, but all data acquired by the aerial system (mainly three‐dimensional maps) were stored in the ICARUS data center, where they were securely published for authorized personnel all over the world. This mission (which is, to our knowledge, the first recorded deployment of an unmanned aerial system by an official governmental international search‐and‐rescue team in another country) proved also the concept of the procedural integration of the ICARUS data management system into the existing procedural toolchain of the search and rescue workers, and this in an international context (deployment from Belgium to Bosnia). The feedback received from the search‐and‐rescue personnel on both validation exercises was highly positive, proving that the ICARUS data management system can efficiently increase the situational awareness of the search‐and‐rescue personnel.     

Wire antennas optimized using genetic algorithm

In this work, wire antennas are designed to jam GSM frequencies using genetic algorithms. These antennas are designed to block communication at 3-band GSM frequencies. They are planned to be mounted on a vehicle and therefore are modeled on a ground plane. Jammer antennas designed in this work are composed of wires, placed on two square dielectric frames, perpendicular to each other. Genetic optimization routines are developed on MATLAB environment for the designs carried out in this work. Electromagnetic simulation program called SuperNEC, which analyses antennas by the method of moments, is used to determine the antenna performances and is called by the developed GA routines. The purpose of the antenna optimization is to obtain low VSWR values and omni-directional radiation pattern near ground at θ = [70° 80° 90°] planes at all GSM frequencies, since the targets will be near ground for this application. Original and interesting antenna designs are obtained as the result of genetic optimization, and are presented in the paper.     

Development and performance characterization of a new standard mercury manometer

A new standard mercury manometer has been developed to calibrate low vacuum gauges in the range from atmospheric pressure to 1 mbar. It consists of a cistern that is a small stainless steel container used as mercury reservoir and also as the first Hg column connected to a long glass tube used as the second Hg column. Manometer scale covers the difference in Hg heights in two columns up to the length equivalent to 1000 mbars. This is a novel low cost manometer with simple design, compact fabrication, better accuracy, easy operation, low vibration, and thermal stability. In order to evaluate the performance of the equipment, its generated pressures are compared with those of secondary standard, i.e., calibrated capacitance diaphragm gauge, giving the average correction factor 0.998. Different uncertainties of the generated pressures are discussed in detail along with the evaluation of correction factors. The relative uncertainty in the higher pressure side is found to be in the range of 10(-4) which is within the limit (approximately 10(-4)).     

GENOTOXICITY IN CHIRONOMUS KIIENSIS (CHIRONOMIDAE: DIPTERA) AFTER EXPOSURE TO POLLUTED SEDIMENTS FROM RIVERS OF NORTH PENINSULAR MALAYSIA: IMPLICATION FOR ECOTOXICOLOGICAL MONITORING

Rapid industrialization and urbanization has led to increasing input of chemical contaminants into the aquatic environment of Malaysia. Despite the threat civilization poses to the biota, there are still very few relevant studies on ecotoxicological testing of river ecosystems. To overcome this knowledge gap, we examined lethal and genotoxic effects of sediments from different rivers of the northern Malaysia against Chironomus kiiensis, a group well represented in the aquatic fauna of this region. We exposed the larvae to sediments from Selama River (SR), Permatang Rawa River (PRR) and Kilang Ubi River (KUR) at various durations (0, 6, 12, 24 and 48 h). The larval mortality was monitored, whereas DNA damage in survivors' cells was determined using the comet assay. Pollution level indexed by the amounts of heavy metals and other organic contaminants in the sediment showed progressive increases from SR to PRR to KUR. Highly polluted sediments (PRR to KUR) were detrimental to C. kiiensis larvae, most of which did not survive following exposure for long periods. DNA analyses revealed greater damages in nuclei derived from larvae maintained on polluted sediments, in particular, those from KUR. The effects on the genomic material of C. kiiensis larvae occurred in a time‐dependent manner, with damage level increasing as exposure time progressed. Our results highlight the genotoxic properties of polluted sediments. More importantly, this study showed that C. kiiensis larvae could respond to different levels of pollution with respect to exposure time. It is concluded that C. kiiensis larvae is a potential candidate for river ecotoxicological monitoring. Copyright © 2012 John Wiley & Sons, Ltd.     

A new external sorting algorithm with no additional disk space

This paper is concerned with an external sorting algorithm with no additional disk space. The proposed algorithm is a hybrid one that uses Quicksort and special merging process in two distinct phases. The algorithm excels in sorting a huge file, which is many times larger than the available memory of the computer. This algorithm creates no extra backup file for manipulating huge records. For this, the algorithm saves huge disk space, which is needed to hold the large file. Also our algorithm switches to special merging process after the first phase that uses Quicksort. This reduces the time complexity and makes the algorithm faster.     

A non-contact method for part-based process performance monitoring in end milling operations

Surface response to excitation (SuRE) method was originally developed for structural health monitoring (SHM) applications. SuRE was used to evaluate the performance of completed milling operations. The method generates surface waves on the plate and studies the spectrum changes at selected points to detect defects and change of compressive forces. In this study, the length, depth, and width of a slot were changed step by step. The surface of the aluminum plate was excited in the 20–400 kHz range with a piezoelectric element. A laser scanning vibrometer was used to monitor the vibrations at the predetermined grid points after the dimensions of the slot were changed methodically. The frequency spectrums of measured vibrations were calculated by using the Fast Fourier Transformation (FFT). The sums of the squares of the differences (SSD) of the spectrums were calculated to evaluate the change of the spectrums. The SuRE method was able to determine if the dimensions were changed in each case at all the selected points. The scanning laser vibrometer is not feasible to be used at the shop floor. However, the study demonstrated that a piezoelectric element attached to any of the grid points would be able to evaluate the completed machining process.     

Hierarchical behavior categorization using correlation based adaptive resonance theory

This paper introduces a new model for robot behavior categorization. Correlation based adaptive resonance theory (CobART) networks are integrated hierarchically in order to develop an adequate categorization, and to elicit various behaviors performed by the robot. The proposed model is developed by adding a second layer CobART network which receives first layer CobART network categories as an input, and back-propagates the matching information to the first layer networks. The first layer CobART networks categorize self-behavior data of a robot or an object in the environment while the second layer CobART network categorizes the robot's behavior with respect to its effect on the object. Experiments show that the proposed model generates reasonable categorization of behaviors being tested. Moreover, it can learn different forms of the behaviors, and it can detect the relations between them. In essence, the model has an expandable architecture and it contains reusable parts. The first layer CobART networks can be integrated with other CobART networks for another categorization task. Hence, the model presents a way to reveal all behaviors performed by the robot at the same time.