The use of pulse oximetry in evaluation of pulp vitality in immature permanent teeth

Background and aim: The current methods of pulp vitality assessment, either electric or thermal, are of limited use in children. Recently, traumatized and immature teeth may not respond to such methods and because such methods require subjective responses, it may not provide accurate results particularly in children. Pulse oximetry, an atraumatic approach, is used to measure oxygen saturation in vascular system. The aim of this study was to investigate the use of pulse oximetry to evaluate pulp vitality status in immature permanent teeth. Methods and materials: The study was conducted on 329 maxillary central and lateral incisors in children. The negative control group consisted of 10 root filled teeth. Systemic oxygen saturation was first measured on the thumb of the individual using a custom-made sensor. Oxygen saturation values of the teeth were then evaluated. The correlation between oxygen saturation measurement obtained from finger and tooth, and the correlation between oxygen saturation values and stage of root development were analyzed. A further comparison was made between the teeth with open and closed apex. Results: Mean oxygen values recorded in the patient's finger were 97.17, and mean oxygen values in the maxillary central and lateral incisors were 86.77 and 83/92, respectively. There was no significant correlation between blood oxygen levels in the finger and in the teeth. (P > 0.05) There was a significant negative correlation between the stage of root development and the blood oxygen levels in the patients' teeth. (P < 0.05) Mean oxygen values in the teeth with open apex were significantly higher than the teeth with closed apex. (P < 0.001). Conclusion: Vital teeth provided consistent oxygen saturation readings, and non-vital teeth recorded no oxygen saturation values. During tooth development, the oxygen saturation values decreased. These findings confirm that the pulse oximetry is capable of detecting the pulpal blood flow and oxygen saturation. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd

Bypassing the bandwidth theorem with PT symmetry

The beat time {\tau}_{fpt} associated with the energy transfer between two coupled oscillators is dictated by the bandwidth theorem which sets a lower bound {\tau}_{fpt}\sim 1/{\delta}{\omega}. We show, both experimentally and theoretically, that two coupled active LRC electrical oscillators with parity-time (PT) symmetry, bypass the lower bound imposed by the bandwidth theorem, reducing the beat time to zero while retaining a real valued spectrum and fixed eigenfrequency difference {\delta}{\omega}. Our results foster new design strategies which lead to (stable) pseudo-unitary wave evolution, and may allow for ultrafast computation, telecommunication, and signal processing.Comment: 5 pages, 3 figure

An intelligent group decision-support system and its application for project performance evaluation

Purpose: In any organization there are main goals, with lots of projects designed to achieve these goals. It is important for any organization to determine how much these projects affect the achievement of these goals. The purpose of this paper is to develop a fuzzy multiple attribute-based group decision-support system (FMAGDSS) to evaluate projects' performance in promoting the organization's goals utilizing simple additive weighting (SAW) algorithm and technique for order of preference by similarity to ideal solution (TOPSIS) algorithm. The proposed FMAGDSS deals with choosing the most appropriate fuzzy ranking algorithm for solving a given fuzzy multi attribute decision making (FMADM) problem with both qualitative and quantitative criteria (attributes), and uncertain judgments of decision makers. Design/methodology/approach: In this paper, a FMAGDSS model is designed to determine scores and ranks of every project in promoting the organization's goals. In the first step of FMAGDSS model, all projects are assessed by experts based on evaluation criteria and the organization's goals. The proposed FMAGDSS model will then choose the most appropriate fuzzy ranking method to solve the given FMADM problem. Finally, a sensitivity analysis system is developed to assess the reliability of the decision-making process and provide an opportunity to analyze the impacts of "criteria weights" and "projects" performance' on evaluating projects in achieving the organizations' goals, and to assess the reliability of the decision-making process. In addition, a software prototype has been developed on the basis of FMAGDSS model that can be applied to solve every FMADM problem that needs to rank alternatives according to certain attributes. Findings: The result of this study simplifies and accelerates the evaluation process. The proposed system not only helps organizations to choose the most efficient projects for sustainable development, but also helps them to assess the reliability of the decision-making process, and decrease the uncertainty in final decision caused by uncertain judgment of decision makers. Research limitations/implications: Future studies are suggested to expand this system to evaluate and rank the project proposals. To achieve this goal, the efficiency of the projects in line with organization's goals, should be predicted.Originality/value: This study contributes to the relevant literature by proposing a FMAGDSS model to evaluate projects in promoting organization's goals. The proposed FMAGDSS has ability to choose the most appropriate fuzzy ranking algorithm to solve a given FMADM problem based on the type and the number of attributes and alternatives, considering the least computation and time consumption for ranking alternatives. © Emerald Group Publishing Limited

Scattering of Dirac electrons by circular mass barriers: valley filter and resonant scattering

The scattering of two-dimensional (2D) massless Dirac electrons is investigated in the presence of a random array of circular mass barriers. The inverse momentum relaxation time and the Hall factor are calculated and used to obtain parallel and perpendicular resistivity components within linear transport theory. We found a non zero perpendicular resistivity component which has opposite sign for electrons in the different K and K' valleys. This property can be used for valley filter purposes. The total cross-section for scattering on penetrable barriers exhibit resonances due to the presence of quasi-bound states in the barriers that show up as sharp gaps in the cross-section while for Schr\"{o}dinger electrons they appear as peaks.Comment: 10 pages, 11 figure

Tailor-made directional emission in nanoimprinted plasmonic-based light-emitting devices

We demonstrate an enhanced and tailor-made directional emission of light-emitting devices using nanoimprinted hexagonal arrays of aluminum nanoparticles. Fourier microscopy reveals that the luminescence of the device is not only determined by the material properties of the organic dye molecules but is also strongly influenced by the coherent scattering resulting from periodically arranged metal nanoparticles. Emitters can couple to lattice-induced hybrid plasmonic–photonic modes sustained by plasmonic arrays. Such modes enhance the spatial coherence of an emitting layer, allowing the efficient beaming of the emission along narrow angular and spectral ranges. We show that tailoring the separation of the nanoparticles in the array yields an accurate angular distribution of the emission. This combination of large-area metal nanostructures fabricated by nanoimprint lithography and light-emitting devices is beneficial for the design and optimization of solid-state lighting systems

Handling uncertainty in cloud resource management using fuzzy Bayesian networks

© 2015 IEEE. The success of cloud services depends critically on the effective management of virtualized resources. This paper aims to design and implement a decision support method to handle uncertainties in resource management from the cloud provider perspective that enables underlying complexity, automates resource provisioning and controls client-perceived quality of service. The paper includes a probabilistic decision making module that relies upon a fuzzy Bayesian network to determine the current situation status of a cloud infrastructure, including physical and virtual machines, and predicts the near future state, that will help the hypervisor to migrate or expand the VMs to reduce execution time and meet quality of service requirements. First, the framework of resource management is presented. Second, the decision making module is developed. Lastly, a series of experiments to investigate the performance of the proposed module is implemented. Experiments reveal the efficiency of the module prototype

A Multi-objective Optimization Model for Virtual Machine Mapping in Cloud Data Centres

© 2016 IEEE. Modern cloud computing environments exploit virtualization for efficient resource management to reduce computational cost and energy budget. Virtual machine (VM) migration is a technique that enables flexible resource allocation and increases the computation power and communication capability within cloud data centers. VM migration helps cloud providers to successfully achieve various resource management objectives such as load balancing, power management, fault tolerance, and system maintenance. However, the VM migration process can affect the performance of applications unless it is supported by smart optimization methods. This paper presents a multi-objective optimization model to address this issue. The objectives are to minimize power consumption, maximize resource utilization (or minimize idle resources), and minimize VM transfer time. Fuzzy particle swarm optimization (PSO), which improves the efficiency of conventional PSO by using fuzzy logic systems, is relied upon to solve the optimization problem. The model is implemented in a cloud simulator to investigate its performance, and the results verify the performance improvement of the proposed model

A Fuzzy Predictable Load Balancing Approach in Cloud Computing

Cloud computing is a new paradigm for hosting and delivering services on demand over the internet where users access services. It is an example of an ultimately virtualized system, and a natural evolution for data centers that employ automated systems management, workload balancing, and virtualization technologies. Live virtual machine (VM) migration is a technique to achieve load balancing in cloud environment by transferring an active overload VM from one physical host to another one without disrupting the VM. In this study, to eliminate whole VM migration in load balancing process, we propose a Fuzzy Predictable Load Balancing (FPLB) approach which confronts with the problem of overload VM, by assigning the extra tasks from overloaded VM to another similar VM instead of whole VM migration. In addition, we propose a Fuzzy Prediction Method (FPM) to predict VMs migration time. This approach also contains a multi-objective optimization model to migrate these tasks to a new VM host. In proposed FPLB approach there is no need to pause VM during migration time. Furthermore, considering this fact that VM live migration contrast to tasks migration takes longer to complete and needs more idle capacity in host physical machine (PM), the proposed approach will significantly reduce time, idle memory and cost consumption