The Effect of Nitrided Layer on Antibacterial Properties for Biomedical Stainless Steel

AbstractPlasma nitriding of AISI type 303 austenitic stainless steel using microwave system at various input powers was conducted in present study. The nitrided layers were characterized via scanning electron microscopy, transmission electron microscopy and Vickers microhardness tester. The anti-bacterial property of this nitrided layer was also evaluated. The analytical results revealed the hardness of AISI type 303 stainless steel could be enhanced with nitriding process. The microstructure of the nitrided layer comprised of nitrogen-expanded γ phase. Bacterial test demonstrated the nitrided layer processed the excellent an ti-bacterial properties. The enhanced hardness and anti-bacterial properties make the nitrided AISI type 303 austenitic stainless steel the potential material in the biomedical applications

Differentially private multidimensional data publishing

© 2017, Springer-Verlag London Ltd., part of Springer Nature. Various organizations collect data about individuals for various reasons, such as service improvement. In order to mine the collected data for useful information, data publishing has become a common practice among those organizations and data analysts, research institutes, or simply the general public. The quality of published data significantly affects the accuracy of the data analysis and thus affects decision making at the corporate level. In this study, we explore the research area of privacy-preserving data publishing, i.e., publishing high-quality data without compromising the privacy of the individuals whose data are being published. Syntactic privacy models, such as k-anonymity, impose syntactic privacy requirements and make certain assumptions about an adversary’s background knowledge. To address this shortcoming, we adopt differential privacy, a rigorous privacy model that is independent of any adversary’s knowledge and insensitive to the underlying data. The published data should preserve individuals’ privacy, yet remain useful for analysis. To maintain data utility, we propose DiffMulti, a workload-aware and differentially private algorithm that employs multidimensional generalization. We devise an efficient implementation to the proposed algorithm and use a real-life data set for experimental analysis. We evaluate the performance of our method in terms of data utility, efficiency, and scalability. When compared to closely related existing methods, DiffMulti significantly improved data utility, in some cases, by orders of magnitude

Effects of carbohydrate, branched-chain amino acids, and arginine in recovery period on the subsequent performance in wrestlers

Many athletes need to participate in multiple events in a single day. The efficient post-exercise glycogen recovery may be critical for the performance in subsequent exercise. This study examined whether post-exercise carbohydrate supplementation could restore the performance in the subsequent simulated wrestling match. The effect of branched-chain amino acids and arginine on glucose disposal and performance was also investigated. Nine well-trained male wrestlers participated in 3 trials in a random order. Each trial contained 3 matches with a 1-hr rest between match 1 and 2, and a 2-hr rest between match 2 and 3. Each match contained 3 exercise periods interspersed with 1-min rests. The subjects alternated 10-s all-out sprints and 20-s rests in each exercise period. At the end of match 2, 3 different supplementations were consumed: 1.2 g/kg glucose (CHO trial), 1 g/kg glucose + 0.1 g/kg Arg + 0.1 g/kg BCAA (CHO+AA trial), or water (placebo trial). The peak and average power in the 3 matches was similar in the 3 trials. After the supplementation, CHO and CHO+AA trial showed significantly higher glucose and insulin, and lower glycerol and non-esterified fatty acid concentrations than the placebo trial. There was no significant difference in these biochemical parameters between the CHO and CHO+AA trials. Supplementation of carbohydrate with or without BCAA and arginine during the post-match period had no effect on the performance in the following simulated match in wrestlers. In addition, BCAA and arginine did not provide additional insulinemic effect

Uranium on uranium collisions at relativistic energies

Deformation and orientation effects on compression, elliptic flow and particle production in uranium on uranium collisions (UU) at relativistic energies are studied within the transport model ART. The density compression in tip-tip UU collisions is found to be about 30% higher and lasts approximately 50% longer than in body-body or spherical UU reactions. The body-body UU collisions have the unique feature that the nucleon elliptic flow is the highest in the most central collisions and remain a constant throughout the reaction. We point out that the tip-tip UU collisions are more probable to create the QGP at AGS and SPS energies while the body-body UU collisions are more useful for studying properties of the QGP at higher energies.Comment: 8 pages + 4 figure

A Hybrid Framework for Sentiment Analysis Using Genetic Algorithm Based Feature Reduction

© 2019 IEEE. Due to the rapid development of Internet technologies and social media, sentiment analysis has become an important opinion mining technique. Recent research work has described the effectiveness of different sentiment classification techniques ranging from simple rule-based and lexicon-based approaches to more complex machine learning algorithms. While lexicon-based approaches have suffered from the lack of dictionaries and labeled data, machine learning approaches have fallen short in terms of accuracy. This paper proposes an integrated framework which bridges the gap between lexicon-based and machine learning approaches to achieve better accuracy and scalability. To solve the scalability issue that arises as the feature-set grows, a novel genetic algorithm (GA)-based feature reduction technique is proposed. By using this hybrid approach, we are able to reduce the feature-set size by up to 42% without compromising the accuracy. The comparison of our feature reduction technique with more widely used principal component analysis (PCA) and latent semantic analysis (LSA) based feature reduction techniques have shown up to 15.4% increased accuracy over PCA and up to 40.2% increased accuracy over LSA. Furthermore, we also evaluate our sentiment analysis framework on other metrics including precision, recall, F-measure, and feature size. In order to demonstrate the efficacy of GA-based designs, we also propose a novel cross-disciplinary area of geopolitics as a case study application for our sentiment analysis framework. The experiment results have shown to accurately measure public sentiments and views regarding various topics such as terrorism, global conflicts, and social issues. We envisage the applicability of our proposed work in various areas including security and surveillance, law-and-order, and public administration

Pion dispersion relation at finite density and temperature

We study the behavior of the pion dispersion relation in a pion medium at finite density and temperature. We introduce a pion chemical potential to describe the finite pion number density and argue that such description is valid during the hadronic phase of a relativistic heavy-ion collision between chemical and thermal freeze-out. We make use of an effective Lagrangian that explicitly respects chiral symmetry through the enforcement of the chiral Ward identities. The pion dispersion relation is computed through the computation of the pion self-energy in a non-perturbative fashion by giving an approximate solution to the Schwinger-Dyson equation for this self-energy. The dispersion relation is described in terms of a density and temperature dependent mass and an index of refraction which is also temperature, density as well as momentum dependent. The index of refraction is larger than unity for all values of the momentum for finite $\mu$ and $T$. We conclude by exploring some of the possible consequences for the propagation of pions through the boundary between the medium and vacuum.Comment: 7 pages, 5 figures, 3 new references, published versio

A study of children facial recognition for privacy in smart TV

© Springer International Publishing AG 2017. Nowadays Smart TV is becoming very popular in many families. Smart TV provides computing and connectivity capabilities with access to online services, such as video on demand, online games, and even sports and healthcare activities. For example, Google Smart TV, which is based on Google Android, integrates into the users’ daily physical activities through its ability to extract and access context information dependent on the surrounding environment and to react accordingly via built-in camera and sensors. Without a viable privacy protection system in place, however, the expanding use of Smart TV can lead to privacy violations through tracking and user profiling by broadcasters and others. This becomes of particular concern when underage users such as children who may not fully understand the concept of privacy are involved in using the Smart TV services. In this study, we consider digital imaging and ways to identify and properly tag pictures of children in order to prevent unwanted disclosure of personal information. We have conducted a preliminary experiment on the effectiveness of facial recognition technology in Smart TV where experimental recognition of child face presence in feedback image streams is conducted through the Microsoft’s Face Application Programming Interface

The directed flow maximum near c_s=0

We investigate the excitation function of quark-gluon plasma formation and of directed in-plane flow of nucleons in the energy range of the BNL-AGS and for the E(Lab)=40AGeV Pb+Pb collisions performed recently at the CERN-SPS. We employ the three-fluid model with dynamical unification of kinetically equilibrated fluid elements. Within our model with first-order phase transition at high density, droplets of QGP coexisting with hadronic matter are produced already at BNL-AGS energies, E(Lab)=10AGeV. A substantial decrease of the isentropic velocity of sound, however, requires higher energies, E(Lab)=40AGeV. We show the effect on the flow of nucleons in the reaction plane. According to our model calculations, kinematic requirements and EoS effects work hand-in-hand at E(Lab)=40AGeV to allow the observation of the dropping velocity of sound via an increase of the directed flow around midrapidity as compared to top BNL-AGS energy.Comment: 10 pages, 4 figures; plot of p(e) at various specific entropies shows why mixed phase is not soft at AGS energ

Transverse flow and hadro-chemistry in Au+Au collisions at \sqrt{s_{NN}}=200 GeV

We present a hydrodynamic assessment of preliminary particle spectra observed in Au+Au collisions at \sqrt{s_{NN}}=200 GeV. The hadronic part of the underlying equation of state is based on explicit conservation of (measured) particle ratios throughout the resonance gas stage after chemical freezeout by employing chemical potentials for stable mesons, nucleons and anti-nucleons. We find that under these conditions the data (in particular the proton spectra) favor a low freeze-out temperature of around 100 MeV. Furthermore we show that through inclusion of a moderate pre-hydrodynamic transverse flow field the shape of the spectra improves with respect to the data. The effect of the initial transverse boost on elliptic flow and the freeze-out geometry of the system is also elucidated.Comment: as published: more data included in Fig. 1, discussions throughout the text improved, 6 pages, 4 figure

Thermal and Chemical Equilibration in Relativistic Heavy Ion Collisions

We investigate the thermalization and the chemical equilibration of a parton plasma created from Au+Au collision at LHC and RHIC energies starting from the early moment when the particle momentum distributions in the central region become for the first time isotropic due to longitudinal cooling. Using the relaxation time approximation for the collision terms in the Boltzmann equations for gluons and for quarks and the real collision terms constructed from the simplest QCD interactions, we show that the collision times have the right behaviour for equilibration. The magnitude of the quark (antiquark) collision time remains bigger than the gluon collision time throughout the lifetime of the plasma so that gluons are equilibrating faster than quarks both chemically and kinetically. That is we have a two-stage equilibration scenario as has been pointed out already by Shuryak sometimes ago. Full kinetic equilibration is however slow and chemical equilibration cannot be completed before the onset of the deconfinement phase transition assumed to be at $T_c=200$ MeV. By comparing the collision entropy density rates of the different processes, we show explicitly that inelastic processes, and \emph{not} elastic processes as is commonly assumed, are dominant in the equilibration of the plasma and that gluon branching leads the other processes in entropy generation. We also show that, within perturbative QCD, processes with higher power in \alpha_s need not be less important for the purpose of equilibration than those with lower power. The state of equilibration of the system has also a role to play. We compare our results with those of the parton cascade model.Comment: 17 pages, revtex+psfig style with 14 embedded postscript figures, to appear in Phys. Rev.