Fluorescence Spectroscopy of Lysozyme-Silver Nanoparticles Complex

Identifying the nature of protein-nanoparticle interactions and favored binding sites is an important issue in functional characterization of biomolecules and their physiological responses. Herein, interaction of silver nanoparticles with lysozyme as a model protein has been monitored via fluorescence spectroscopy. Formation of complex between the biomolecule and silver nanoparticles (AgNPs) induced a steady state reduction in the fluorescence intensity of protein at different concentrations of nanoparticles. Tryptophan fluorescence quenching spectra suggested that silver nanoparticles act as a foreign quencher, approaching the protein via this residue. Analysis of the Stern-Volmer plot showed quenching constant of 3.73 μM−1. Moreover, a single binding site in lysozyme is suggested to play role during interaction with AgNPs, having low affinity of binding compared to gold nanoparticles. Unfolding studies of lysozyme showed that complex of lysozyme- AgNPs has not undergone structural perturbations compared to the bare protein. Results of this effort will pave the way for utilization of sensitive spectroscopic techniques for rational design of nanobiomaterials in biomedical applications.

Closing the Achievement Gap Within Reading and Mathematics Classrooms by Fostering Hispanic Students- Educational Resilience

While many studies have conducted the achievement gap between groups of students in school districts, few studies have utilized resilience research to investigate achievement gaps within classrooms. This paper aims to summarize and discuss some recent studies Waxman, Padr├│n, and their colleagues conducted, in which they examined learning environment differences between resilient and nonresilient students in reading and mathematics classrooms. The classes consist of predominantly Hispanic elementary school students from low-income families. These studies all incorporated learning environment questionnaires and systematic observation methods. Significant differences were found between resilient and nonresilient students on their classroom learning environments and classroom behaviors. The observation results indicate that the amount and quality of teacher and student academic interaction are two of the most influential variables that promote student outcomes. This paper concludes by suggesting the following teacher practices to promote resiliency in schools: (a) using feedback from classroom observation and learning environment measures, (b) employing explicit teaching practices; and (c) understanding students on a social and personal level.

Light Confinement in Low Index Nanometer Areas

In this work we numerically examine structures which could confine light in nanometer areas. A system consisting of two silicon disks with in plane separation of a few tens of nanometers has been studied first. The normalized unitless effective mode volume, Veff, has been calculated for the two lowest whispering gallery mode resonances. The effective mode volume is reduced significantly as the gap between the disks decreases. In addition, the effect of the substrate is also studied. In that case, Veff of approximately the same value as the non-substrate case for a similar two disk system can be obtained by using disks almost twice as thick. We also numerically examine a structure consisting of a circular slot waveguide which is formed into a silicon disk resonator. We show that the proposed structure could have high Q resonances thus raising the belief that it is a very promising candidate for optical interconnects applications. The study includes several numerical calculations for all the geometric parameters of the structure. It also includes numerical simulations of the coupling between a waveguide and the proposed disk resonator leading to a very promising conclusion about its applicability.

A Framework of the Factors Affecting the Adoption of ICT for Physical Education

Physical education (PE) is still neglected in schools despite its academic, social, psychological, and health benefits. Based on the assumption that Information and Communication Technologies (ICTs) can contribute to the development of PE in schools, this study aims to design a model of the factors affecting the adoption of ICTs for PE in schools. The proposed model is based on a sound theoretical framework. It was designed following a literature review of technology adoption theories and of ICT adoption factors for physical education. The technology adoption model that fitted to the best all ICT adoption factors was then chosen as the basis for the proposed model. It was found that the Unified Theory of Acceptance and Use of Technology (UTAUT) is the most adequate theoretical framework for the modeling of ICT adoption factors for physical education.

Location Update Cost Analysis of Mobile IPv6 Protocols

Mobile IP has been developed to provide the continuous information network access to mobile users. In IP-based mobile networks, location management is an important component of mobility management. This management enables the system to track the location of mobile node between consecutive communications. It includes two important tasks- location update and call delivery. Location update is associated with signaling load. Frequent updates lead to degradation in the overall performance of the network and the underutilization of the resources. It is, therefore, required to devise the mechanism to minimize the update rate. Mobile IPv6 (MIPv6) and Hierarchical MIPv6 (HMIPv6) have been the potential candidates for deployments in mobile IP networks for mobility management. HMIPv6 through studies has been shown with better performance as compared to MIPv6. It reduces the signaling overhead traffic by making registration process local. In this paper, we present performance analysis of MIPv6 and HMIPv6 using an analytical model. Location update cost function is formulated based on fluid flow mobility model. The impact of cell residence time, cell residence probability and user-s mobility is investigated. Numerical results are obtained and presented in graphical form. It is shown that HMIPv6 outperforms MIPv6 for high mobility users only and for low mobility users; performance of both the schemes is almost equivalent to each other.

Rapid Data Acquisition System for Complex Algorithm Testing in Plastic Molding Industry

Injection molding is a very complicated process to monitor and control. With its high complexity and many process parameters, the optimization of these systems is a very challenging problem. To meet the requirements and costs demanded by the market, there has been an intense development and research with the aim to maintain the process under control. This paper outlines the latest advances in necessary algorithms for plastic injection process and monitoring, and also a flexible data acquisition system that allows rapid implementation of complex algorithms to assess their correct performance and can be integrated in the quality control process. This is the main topic of this paper. Finally, to demonstrate the performance achieved by this combination, a real case of use is presented.

Cross-Industry Innovations – Systematic Identification and Adaption

Due to today-s fierce competition, companies have to be proactive creators of the future by effectively developing innovations. Especially radical innovations allow high profit margins – but they also entail high risks. One possibility to realize radical innovations and reduce the risk of failure is cross-industry innovation (CII). CII brings together problems and solution ideas from different industries. However, there is a lack of systematic ways towards CII. Bridging this gap, the present paper provides a systematic approach towards planned CII. Starting with the analysis of potentials, the definition of promising search strategies is crucial. Subsequently, identified solution ideas need to be assessed. For the most promising ones, the adaption process has to be systematically planned – regarding the risk affinity of a company. The introduced method is explained on a project from the furniture industry.

Design of a Tube Vent to Enhance the Role of Roof Solar Collector

The objective of this paper was to designing a ventilation system to enhance the performance of roof solar collector (RSC) for reducing heat accumulation inside the house. The RSC has 1.8 m2 surface area made of CPAC monier roof tiles on the upper part and gypsum board on the lower part. The space between CPAC monier and gypsum board was fixed at 14 cm. Ventilation system of modified roof solar collector (modified RSC) consists of 9 tubes of 0.15m diameter and installed in the lower part of RSC. Experimental result showed that the temperature of the room, and attic temperature. The average temperature reduction of room of house used modified RSC is about 2oC. and the percentage of room temperature reduction varied between 0 to 10%. Therefore, modified RSC is an interesting option in the sense that it promotes solar energy and conserve energy.

Near-Field Robust Adaptive Beamforming Based on Worst-Case Performance Optimization

The performance of adaptive beamforming degrades substantially in the presence of steering vector mismatches. This degradation is especially severe in the near-field, for the 3-dimensional source location is more difficult to estimate than the 2-dimensional direction of arrival in far-field cases. As a solution, a novel approach of near-field robust adaptive beamforming (RABF) is proposed in this paper. It is a natural extension of the traditional far-field RABF and belongs to the class of diagonal loading approaches, with the loading level determined based on worst-case performance optimization. However, different from the methods solving the optimal loading by iteration, it suggests here a simple closed-form solution after some approximations, and consequently, the optimal weight vector can be expressed in a closed form. Besides simplicity and low computational cost, the proposed approach reveals how different factors affect the optimal loading as well as the weight vector. Its excellent performance in the near-field is confirmed via a number of numerical examples.

Neural Network Control of a Biped Robot Model with Composite Adaptation Low

this paper presents a novel neural network controller with composite adaptation low to improve the trajectory tracking problems of biped robots comparing with classical controller. The biped model has 5_link and 6 degrees of freedom and actuated by Plated Pneumatic Artificial Muscle, which have a very high power to weight ratio and it has large stoke compared to similar actuators. The proposed controller employ a stable neural network in to approximate unknown nonlinear functions in the robot dynamics, thereby overcoming some limitation of conventional controllers such as PD or adaptive controllers and guarantee good performance. This NN controller significantly improve the accuracy requirements by retraining the basic PD/PID loop, but adding an inner adaptive loop that allows the controller to learn unknown parameters such as friction coefficient, therefore improving tracking accuracy. Simulation results plus graphical simulation in virtual reality show that NN controller tracking performance is considerably better than PD controller tracking performance.

The Effect of High-speed Milling on Surface Roughness of Hardened Tool Steel

The objective of this research was to study factors, which were affected on surface roughness in high speed milling of hardened tool steel. Material used in the experiment was tool steel JIS SKD 61 that hardened on 60 ±2 HRC. Full factorial experimental design was conducted on 3 factors and 3 levels (3 3 designs) with 2 replications. Factors were consisted of cutting speed, feed rate, and depth of cut. The results showed that influenced factor affected to surface roughness was cutting speed, feed rate and depth of cut which showed statistical significant. Higher cutting speed would cause on better surface quality. On the other hand, higher feed rate would cause on poorer surface quality. Interaction of factor was found that cutting speed and depth of cut were significantly to surface quality. The interaction of high cutting speed associated with low depth of cut affected to better surface quality than low cutting speed and high depth of cut.

An Anomaly Detection Approach to Detect Unexpected Faults in Recordings from Test Drives

In the automotive industry test drives are being conducted during the development of new vehicle models or as a part of quality assurance of series-production vehicles. The communication on the in-vehicle network, data from external sensors, or internal data from the electronic control units is recorded by automotive data loggers during the test drives. The recordings are used for fault analysis. Since the resulting data volume is tremendous, manually analysing each recording in great detail is not feasible. This paper proposes to use machine learning to support domainexperts by preventing them from contemplating irrelevant data and rather pointing them to the relevant parts in the recordings. The underlying idea is to learn the normal behaviour from available recordings, i.e. a training set, and then to autonomously detect unexpected deviations and report them as anomalies. The one-class support vector machine “support vector data description” is utilised to calculate distances of feature vectors. SVDDSUBSEQ is proposed as a novel approach, allowing to classify subsequences in multivariate time series data. The approach allows to detect unexpected faults without modelling effort as is shown with experimental results on recordings from test drives.

The Design and Implementation of Classifying Bird Sounds

This Classifying Bird Sounds (chip notes) project-s purpose is to reduce the unwanted noise from recorded bird sound chip notes, design a scheme to detect differences and similarities between recorded chip notes, and classify bird sound chip notes. The technologies of determining the similarities of sound waves have been used in communication, sound engineering and wireless sound applications for many years. Our research is focused on the similarity of chip notes, which are the sounds from different birds. The program we use is generated by Microsoft Cµ.

The Implementation of Good Manufacturing Practice in Polycarbonate Film Industry

This study reports the implementation of Good Manufacturing Practice (GMP) in a polycarbonate film processing plant. The implementation of GMP took place with the creation of a multidisciplinary team. It was carried out in four steps: conduct gap assessment, create gap closure plan, close gaps, and follow up the GMP implementation. The basis for the gap assessment is the guideline for GMP for plastic materials and articles intended for Food Contact Material (FCM), which was edited by Plastic Europe. The effective results of the GMP implementation in this study showed 100% completion of gap assessment. The key success factors for implementing GMP in production process are the commitment, intention and support of top management.

Alcoholic Extract of Terminalia Arjuna Protects Rabbit Heart against Ischemic-Reperfusion Injury: Role of Antioxidant Enzymes and Heat Shock Protein

The present study was designed to investigate the cardio protective role of chronic oral administration of alcoholic extract of Terminalia arjuna in in-vivo ischemic reperfusion injury and the induction of HSP72. Rabbits, divided into three groups, and were administered with the alcoholic extract of the bark powder of Terminalia arjuna (TAAE) by oral gavage [6.75mg/kg: (T1) and 9.75mg/kg: (T2), 6 days /week for 12 weeks]. In open-chest Ketamine pentobarbitone anaesthetized rabbits, the left anterior descending coronary artery was occluded for 15 min of ischemia followed by 60 min of reperfusion. In the vehicle-treated group, ischemic-reperfusion injury (IRI) was evidenced by depression of global hemodynamic function (MAP, HR, LVEDP, peak LV (+) & (- ) (dP/dt) along with depletion of HEP compounds. Oxidative stress in IRI was evidenced by, raised levels of myocardial TBARS and depletion of endogenous myocardial antioxidants GSH, SOD and catalase. Western blot analysis showed a single band corresponding to 72 kDa in homogenates of hearts from rabbits treated with both the doses. In the alcoholic extract of the bark powder of Terminalia arjuna treatment groups, both the doses had better recovery of myocardial hemodynamic function, with significant reduction in TBARS, and rise in SOD, GSH, catalase were observed. The results of the present study suggest that the alcoholic extract of the bark powder of Terminalia arjuna in rabbit induces myocardial HSP 72 and augments myocardial endogenous antioxidants, without causing any cellular injury and offered better cardioprotection against oxidative stress associated with myocardial IR injury.

Unsteady Free Convection Flow Over a Three-Dimensional Stagnation Point With Internal Heat Generation or Absorption

This paper considers the effect of heat generation proportional l to (T - T∞ )p , where T is the local temperature and T∞ is the ambient temperature, in unsteady free convection flow near the stagnation point region of a three-dimensional body. The fluid is considered in an ambient fluid under the assumption of a step change in the surface temperature of the body. The non-linear coupled partial differential equations governing the free convection flow are solved numerically using an implicit finite-difference method for different values of the governing parameters entering these equations. The results for the flow and heat characteristics when p ≤ 2 show that the transition from the initial unsteady-state flow to the final steadystate flow takes place smoothly. The behavior of the flow is seen strongly depend on the exponent p.

A Local Statistics Based Region Growing Segmentation Method for Ultrasound Medical Images

This paper presents the region based segmentation method for ultrasound images using local statistics. In this segmentation approach the homogeneous regions depends on the image granularity features, where the interested structures with dimensions comparable to the speckle size are to be extracted. This method uses a look up table comprising of the local statistics of every pixel, which are consisting of the homogeneity and similarity bounds according to the kernel size. The shape and size of the growing regions depend on this look up table entries. The algorithms are implemented by using connected seeded region growing procedure where each pixel is taken as seed point. The region merging after the region growing also suppresses the high frequency artifacts. The updated merged regions produce the output in formed of segmented image. This algorithm produces the results that are less sensitive to the pixel location and it also allows a segmentation of the accurate homogeneous regions.

Burning Rate Response of Solid Fuels in Laminar Boundary Layer

Solid fuel transient burning behavior under oxidizer gas flow is numerically investigated. It is done using analysis of the regression rate responses to the imposed sudden and oscillatory variation at inflow properties. The conjugate problem is considered by simultaneous solution of flow and solid phase governing equations to compute the fuel regression rate. The advection upstream splitting method is used as flow computational scheme in finite volume method. The ignition phase is completely simulated to obtain the exact initial condition for response analysis. The results show that the transient burning effects which lead to the combustion instabilities and intermittent extinctions could be observed in solid fuels as the solid propellants.

A Training Model for Successful Implementation of Enterprise Resource Planning

It well recognized that one feature that makes a successful company is its ability to successfully align its business goals with its information communication technologies platform. Enterprise Resource Planning (ERP) systems contribute to achieve better performance by integrating various business functions and providing support for information flows. However, the technological systems complexity is known to prevent the business users to exploit in an efficient way the Enterprise Resource Planning Systems (ERP). This paper aims to investigate the role of training in improving the usage of ERP systems. To this end, we have designed an instrument survey to employees of a Norwegian multinational global provider of technology solutions. Based on the analysis of collected data, we have delineated a training model that could be high relevance for both researchers and practitioners as a step towards a better understanding of ERP system implementation.

Land Use around Metro Stations: A Case Study

Transport and land use are two systems that are mutually influenced. Their interaction is a complex process associated with continuous feedback. The paper examines the existing land use around an under construction metro station of the new metro network of Thessaloniki, Greece, through the use of field investigations, around the station-s predefined location. Moreover, except from the analytical land use recording, a sampling questionnaire survey is addressed to several selected enterprises of the study area. The survey aims to specify the characteristics of the enterprises, the trip patterns of their employees and clients, as well as the stated preferences towards the changes the new metro station is considered to bring to the area. The interpretation of the interrelationships among selected data from the questionnaire survey takes place using the method of Principal Components Analysis for Categorical Data. The followed methodology and the survey-s results contribute to the enrichment of the relevant bibliography concerning the way the creation of a new metro station can have an impact on the land use pattern of an area, by examining the situation before the operation of the station.