An Investigation into the Inactivation Kinetics of Hydrogen Peroxide Vapor Against Clostridium difficile Endospores

C. difficile spores are resistant to routine cleaning agents and are able to survive on inanimate surfaces for long periods of time. There is increasing evidence of the importance of the clinical environment as a reservoir for pathogenic agents and as a potential source of healthcare-associated infections (HCAIs). In this context, to reduce the risk of cross-transmission, terminal disinfection of hospital wards and isolation rooms using hydrogen peroxide vapor (HPV) is attracting attention. Spores of C. difficile (ribotype 027) were exposed to constant concentrations of HPV ranging between 11 and 92 mg m^?3 (ppm) for a range of exposure times in a specially designed chamber. The inactivation data thus obtained was fitted using the modified Chick–Watson inactivation model to obtain decimal reduction values (D values). D values ranged from 23 to 1.3 min at HPV concentrations of 11 and 92 ppm, respectively. We present a simple mathematical model based on the inactivation kinetic data obtained here to estimate the efficacy of commercial HPV processes used in healthcare environmental decontamination. C. difficile spores showed linear inactivation kinetics at steady HPV concentrations ranging between 10 and 90 ppm. The data obtained here was used to provide estimates of the inactivation efficacy of commercial HPV process cycles, which employ unsteady HPV concentrations during the decontamination process.     

Development of Polyoxyethylene Zwitterionic Surfactants for High-Salinity High-Temperature Reservoirs

Substantial efforts are underway to improve the recovery factor from existing oil reserves to meet the ever-growing global oil demand. Surfactants are known to increase oil recovery through reducing interfacial tension (IFT) and/or altering the rock wettability. The selection of surfactants for high-salinity high-temperature oil fields is a challenging task owing to poor thermal stability, precipitation, and adsorption of surfactants on reservoir rocks. Sulfobetaine-based polyoxyethylene zwitterionic surfactants have shown excellent thermal and surface properties. However, their solubility in high-salinity brines becomes poor particularly with a long hydrophobic tail (>C17). Recently, we synthesized such types of surfactants by incorporating ethylene oxide (EO) units into the hydrophobic tail, which improved the solubility in formation water (213,734 ppm) and seawater (SW) (57,643 ppm). In this work, we investigated the IFT, thermal stability, rheological behavior, and foaming properties of two polyoxyethylene zwitterionic surfactants having different degrees of ethoxylation. Aging experiments exhibited excellent thermal stability and no change in the chemical structure was detected. The surfactant with lesser EO units (EASB-1a) showed a lower IFT compared to the surfactant with higher EO units (EASB-1b). Rheological studies revealed that the addition of both surfactants reduced the viscosity of the acrylamide copolymer. However, the effect of EASB-1a was more prominent compared to that of EASB-1b. The surfactant with a higher degree of ethoxylation showed lower adsorption compared to the surfactant with a lesser degree of ethoxylation. Both surfactants showed excellent foamability and foam stability compared to the commercial surfactants. Excellent thermal stability, water solubility under harsh reservoir conditions, foaming properties, and lower adsorption make them a suitable choice for high-temperature, high-salinity reservoirs.     

Thermal-stability of electric field-induced strain and energy storage density in Nb-doped BNKT-ST piezoceramics

In this work, the relationship between the structural mechanisms and macroscopic electrical properties of the Nb-modified 0.96(Bi_0.5Na_0.84K_0.16TiO₃)–0.04SrTiO₃ (BNKT–ST) system were elucidated by using temperature dependent and in situ synchrotron X-ray diffraction (XRD) techniques. For the composition x?=?0.0175, a large-signal piezoelectric coefficient (S_max/E_max?=?d₃₃*) of 735 pm?V^?1 at 6?kV mm^?1 was observed at room temperature. Interestingly, at a higher temperature of 110?°C, the sample still showed a large d₃₃* of 570 pm V^?1. Furthermore, the temperature-invariant electrostrictive coefficient for this sample was found to be 0.0285?m⁴?C^?2 over the temperature range of 25–170?°C. Moreover, the energy density for x?=?0.030 sample was ～1.0?J?cm^?3 with an energy storage efficiency of ?70% in the temperature range of 25–135?°C. These results suggest that the synthesized Nb-modified BNKT–ST system is promising for the design of ceramic actuators as well as capacitor applications.     

Adaptive image denoising using cuckoo algorithm

This paper presents a novel denoising approach based on smoothing linear and nonlinear filters combined with an optimization algorithm. The optimization algorithm used was cuckoo search algorithm and is employed to determine the optimal sequence of filters for each kind of noise. Noises that would be eliminated form images using the proposed approach including Gaussian, speckle, and salt and pepper noise. The denoising behaviour of nonlinear filters and wavelet shrinkage threshold methods have also been analysed and compared with the proposed approach. Results show the robustness of the proposed filter when compared with the state-of-the-art methods in terms of peak signal-to-noise ratio and image quality index. Furthermore, a comparative analysis is provided between the said optimization algorithm and the genetic algorithm.     

Comparison of EEG signal decomposition methods in classification of motor-imagery BCI

A brain–computer interface (BCI) provides a link between the human brain and a computer. The task of discriminating four classes (left and right hands and feet) of motor imagery movements of a simple limb-based BCI is still challenging because most imaginary movements in the motor cortex have close spatial representations. We aimed to classify binary limb movements, rather than the direction of movement within one limb. We also investigated joint time-frequency methods to improve classification accuracies. Neither of these, to our knowledge, has been investigated previously in BCI. We recorded EEG data from eleven participants, and demonstrated the classification of four classes of simple-limb motor imagery with an accuracy of 91.46% using intrinsic time-scale decomposition and 88.99% using empirical mode decomposition. In binary classifications, we achieved average accuracies of 89.90% when classifying imaginary movements of left hand versus right hand, 93.1% for left hand versus right foot, 94.00% for left hand versus left foot, 83.82% for left foot versus right foot, 97.62% for right hand versus left foot, and 95.11% for right hand versus right foot. The results show that the binary classification performance is slightly better than that of four-class classification. Our results also show that there is no significant difference in terms of spatial distribution between left and right foot motor imagery movements. There is also no difference in classification performances involving left or right foot movement. This work demonstrates that binary and four-class movements of the left and right feet and hands can be classified using recorded EEG signals of the motor cortex, and an intrinsic time-scale decomposition (ITD) feature extraction method can be used for real time brain computer interface.

     

Numerical investigation on 2D viscoelastic fluid due to exponentially stretching surface with magnetic effects: an application of non-Fourier flux theory

Two-dimensional flow of Casson fluid toward an exponentially stretched surface in view of Cattaneo–Christove flux theory is discoursed in current communication. Flow pattern within boundary layer under the effectiveness of magnetic field is also contemplated in the communication. Non-dimensionalized governing expressions are attained through transformation procedure. To anticipate the fascinating features of present work, solution of resulted nonlinear differential system is computed with the collaborated help of shooting scheme and Runge–Kutta method. The influence of involved variables on velocity and temperature fields is scrutinized. Contribution of thermal relaxation is explicitly pointed out. Evaluation of convective heat transfer and friction factor in the fluid flow is visualized through graphs and tables. Additionally, the assurance of present work is affirmed by developing comparison with previous findings in the literature which sets a trade mark for the implementation of numerical approach. It is inferred from the thorough examination of the analysis that present formulation reduces to classical Fourier’s problem by considering \(\varLambda = 0\). Furthermore, decreasing pattern in temperature distribution is depicted in the presence of Cattaneo–Christove flux law as compared to heat transfer due to the Fourier’s law.

     

Peer to peer trade in HTM5 meta model for agent oriented cloud robotic systems

Cloud computing is a methodology and not a technology. Adaptation of cloud computing services for robotic applications is relatively straightforward while adaptation of underlying ideas will require a new design attitude. Cloud computing is a cost-effective and dynamic business model. Currently cloud robotics is understood as a client server methodology which enables robots utilize resources and services placed at centralized servers. These cloud servers treat robots as any other client computer offering them platform, infrastructure, process or algorithm as a service. HTM5 is an OMG MDA based multi-view meta-model for agent oriented development of cloud robotic systems. HTM5 encourages design of peer-to-peer service ecosystems based on an open registry and matchmaking mechanism. In peer-to-peer cloud robotics, a robot can trade its hardware, software and functional resources as a service to other robots in the ecosystem. The peer-to-peer trade in such systems may be driven by contracts and relationships between its member agents. This article discusses trade-view model of HTM5 methodology and its use in developing a cloud robotic ecosystem that implements peer-to-peer, contract based economy. The article also presents a case study with experiments that implement distributed artificial intelligence and peer-to-peer service oriented trade on simulated and real robot colonies.