Waterpipe tobacco smoking legislation and policy enactment: a global analysis

Objective (1) To review how current global tobacco control policies address regulation of waterpipe tobacco smoking (WTS). (2) To identify features associated with enactment and enforcement of WTS legislation. Data Sources (1) Legislations compiled by Tobacco Control Laws (www.tobaccocontrollaws.org). (2) Weekly news articles by ‘Google Alerts’ (www.google.com/alerts) from July 2013 to August 2014. Study Selection (1) Countries containing legislative reviews, written by legal experts, were included. Countries prohibiting tobacco sales were excluded. (2) News articles discussing aspects of the WHO FCTC were included. News articles related to electronic-waterpipe, crime, smuggling, opinion pieces or brief mentions of WTS were excluded. Data Abstraction (1) Two reviewers independently abstracted the definition of “tobacco product” and/or “smoking”. Four tobacco control domains (smokefree law, misleading descriptors, health warning labels and advertising/promotion/sponsorship) were assigned one of four categories based on the degree to which WTS had specific legislation. (2) Two investigators independently assigned at least one theme and associated subtheme to each news article. Data Synthesis (1) Reviewed legislations of 62 countries showed that most do not address WTS regulation but instead rely on generic tobacco/smoking definitions to cover all tobacco products. Where WTS was specifically addressed, no additional legislative guidance accounted for the unique way it is smoked, except for in one country specifying health warnings on waterpipe apparatuses (2) News articles mainly reported on noncompliance with public smoking bans, especially in India, Pakistan and the UK. Conclusions A regulatory framework evaluated for effectiveness and tailored for the specificities of WTS needs to be developed

Aspirin Prophylaxis for the Prevention of Thrombosis: Expectations and Limitations

Platelets play a very important role in the pathogenesis of acute vascular events leading to thrombosis of the coronary and cerebral arteries. Blockage of these arteries leading to regional ischemia of heart and brain tissues precipitate heart attacks and stroke. Acetyl salicylic acid (Aspirin) has been the drug of choice for over half a century for the primary and secondary prophylaxis of thrombotic events. In spite of its extensive use as an antiplatelet drug for the prevention of vascular thrombosis, there is considerable concern about the degree of protection it offers, to patients under aspirin therapy. In this paper, we explain the phenomenon of aspirin resistance, discuss the limitations of aspirin therapy, and suggest methods to monitor “at-risk” individuals. Ability to monitor and determine at risk patients will provide opportunities for the clinicians to customize antiplatelet therapies

Parametric BIM-based Design Review

This research addressed the need for a new design review technology and method to express the tangible and intangible qualities of architectural experience of parametric BIM-based design projects. The research produced an innovative presentation tool by which parametric design is presented systematically. Focus groups provided assessments of the tool to reveal the usefulness of a parametric BIM-based design review method. The way in which we visualize architecture affects the way we design and perceive architectural form and performance. Contemporary architectural forms and systems are very complex, yet most architects who use Building Information Modeling (BIM) and generative design methods still embrace the two-dimensional 15th-century Albertian representational methods to express and review design projects. However, architecture cannot be fully perceived through a set of drawings that mediate our perception and evaluation of the built environment. The systematic and conventional approach of traditional architectural representation, in paper-based and slide-based design reviews, is not able to visualize phenomenal experience nor the inherent variation and versioning of parametric models. Pre-recorded walk-throughs with high quality rendering and imaging have been in use for decades, but high verisimilitude interactive walk-throughs are not commonly used in architectural presentations. The new generations of parametric and BIM systems allow for the quick production of variations in design by varying design parameters and their relationships. However, there is a lack of tools capable of conducting design reviews that engage the advantages of parametric and BIM design projects. Given the multitude of possibilities of in-game interface design, game-engines provide an opportunity for the creation of an interactive, parametric, and performance-oriented experience of architectural projects with multi-design options. This research has produced a concept for a dynamic presentation and review tool and method intended to meet the needs of parametric design, performance-based evaluation, and optimization of multi-objective design options. The concept is illustrated and tested using a prototype (Parametric Design Review, or PDR) based upon an interactive gaming environment equipped with a novel user interface that simultaneously engages the parametric framework, object parameters, multi-objective optimized design options and their performances with diagrammatic, perspectival, and orthographic representations. The prototype was presented to representative users in multiple focus group sessions. Focus group discussion data reveal that the proposed PDR interface was perceived to be useful if used for design reviews in both academic and professional practice settings

Online 3D path planning for Tri-copter drone using GWO-IBA algorithm

Robots at present are involved in many parts of life, especially mobile robots, which are two parts, ground robots and flying robots, and the best example of a flying robot is the drone. Path planning is a fundamental part of UAVs because the drone follows the path that leads it to goal with obstacle avoidance. Therefore, this paper proposes a hybrid algorithm (grey wolf optimization - intelligent bug algorithm GWO-IBA) to determine the best, shortest and without obstacles path. The hybrid algorithm was implemented and tested in the MATLAB program on the Tri-copter model, and it gave different paths in different environments. The paths obtained were characterized by being free of obstacles and the shortest paths available to reach the target

Three Dimensional Mapping of Texture in Dental Enamel

We have used synchrotron x-ray diffraction to study the crystal orientation in human dental enamel as a function of position within intact tooth sections. Keeping tooth sections intact has allowed us to construct 2D and 3D spatial distribution maps of the magnitude and orientation of texture in dental enamel. We have found that the enamel crystallites are most highly aligned at the expected occlusal points for a maxillary first premolar, and that the texture direction varies spatially in a three dimensional curling arrangement. Our results provide a model for texture in enamel which can aid researchers in developing dental composite materials for fillings and crowns with optimal characteristics for longevity, and will guide clinicians to the best method for drilling into enamel, in order to minimize weakening of remaining tooth structure, during dental restoration procedure

LearnSDN: optimizing routing over multimedia-based 5G-SDN using machine learning

With the advent of 5G networks and beyond, there is an increasing demand to leverage Machine Learning (ML) capabilities and develop new and innovative solutions that could achieve efficient use of network resources and improve users' Quality of Experience (QoE). One of the key enabling technologies for 5G networks is Software Defined Networking (SDN) as it enables fine-grained monitoring and control of the network. Given the variety of dynamic networking conditions within 5G-SDN environments and the diversity of routing algorithms, an intelligent control of these strategies should exist to maximize the Quality of Service (QoS) provisioning of multimedia traffic with more stringent requirements without penalizing the performance of the background traffic. This paper proposes LearnSDN, an innovative ML-based solution that enables QoS provisioning over multimedia-based 5G-SDN environments. LearnSDN uses ML to learn the most convenient routing algorithm to be employed on the background traffic based on the dynamic network conditions in order to cater for the QoS requirements of the multimedia traffic. The performance of the proposed LearnSDN solution is evaluated under a realistic emulation-based SDN environment. The results indicate that LearnSDN outperforms other state-of-the-art solutions in terms of QoS provisioning, PSNR and MOS

QoS-based routing over software defined networks

Quality of Service (QoS) relies on the shaping of preferential delivery services for applications in favour of ensuring sufficient bandwidth, controlling latency and reducing packet loss. QoS can be achieved by prioritizing important broadband data traffic over the less important one. Thus, depending on the users’ needs, video, voice or data traffic take different priority based on the prevalent importance within a particular context. This prioritization might require changes in the configuration of each network entity which can be difficult in traditional network architecture. To this extent, this paper investigates the use of a QoS-based routing scheme over a Software-Defined Network (SDN). A real SDN test-bed is constructed using Raspberry Pi computers as virtual SDN switches managed by a centralized controller. It is shown that a QoS-based routing approach over SDN generates enormous control possibilities and enables automation

Policy-based QoS management framework for software-defined networks

With the emerging trends of virtualization of cloud computing and big data applications, network management has become a challenging problem for optimizing the network state while satisfying the applications’ Quality of Service (QoS) requirements. This paper proposes a policy-based management framework over Software-Defined Networks (SDN) for QoS provisioning. The proposed approach monitors the QoS parameters of the active flows and dynamically enforces new decisions on the underlying SDN switches to adapt the network state to the current demanded high-level policies. Moreover, the proposed solution makes use of Neural Networks to identify the violating flows causing the network congestion. Upon detection of a policy violation two route management techniques are implemented, such as: rerouting and rate limiting. The proposed framework was implemented and evaluated within an experimental test bed setup. The results indicate that the proposed PBNM-based SDN framework enables QoS provisioning and outperforms the default SDN in terms of throughput, packet loss rate and latency

LearnQoS: a learning approach for optimizing QoS over multimedia-based SDNs

As video-based services become an integral part of the end-users’ lives, there is an imminent need for increase in the backhaul capacity and resource management efficiency to enable a highly enhanced multimedia experience to the endusers. The next-generation networking paradigm offers wide advantages over the traditional networks through simplifying the management layer, especially with the adoption of Software Defined Networks (SDN). However, enabling Quality of Service (QoS) provisioning still remains a challenge that needs to be optimized especially for multimedia-based applications. In this paper, we propose LearnQoS, an intelligent QoS management framework for multimedia-based SDNs. LearnQoS employs a policy-based network management (PBNM) to ensure the compliance of QoS requirements and optimizes the operation of PBNM through Reinforcement Learning (RL). The proposed LearnQoS framework is implemented and evaluated under an experimental setup environment and compared with the default SDN operation in terms of PSNR, MOS, throughput and packet loss