Response of dispersed droplets to shock waves in supersonic mixing layers

The response of dispersed droplets to oblique shock waves in the supersonic mixing layer was investigated using the large eddy simulation coupled with the particle Lagrangian tracking model. The generated disturbances based on the most-unstable wave model were imposed to excite the development of supersonic shear layer. The oblique shock wave was numerically introduced in the flow field. Small- and medium-sized droplets remained their preferential distribution in the vortices after crossing the shock wave, while large-sized droplet became more dispersed. The influence of shock waves on the momentum and heat transfers from surrounding gas to droplets was analyzed by tracking droplets’ motion paths. Small-sized droplets responded easily to the shock wave. Compared with the aerodynamic response, the thermal response of droplets was slower, especially under the impaction of the shock wave. The present research conclusions are conductive to analyze the mixing of air and fuel droplets and of important academic value for further understanding the two-phase dynamics in combustors of scramjet

A detailed analysis of online pharmacy characteristics to inform safe usage by patients

Background: Evidence suggests that consumers potentially put themselves at risk when purchasing medicines on-line. Whilst logos provided by regulators may provide some level of reassurance there may be other indicators which could be used by consumers to identify those websites which may be safely used. Objectives: Identify characteristics of on-line pharmacies which are related to whether websites are regulated or non-regulated and those characteristics which could be used by patients to increase the likelihood of accessing regulated sites. Setting: Online pharmacies which supply diazepam, fluoxetine and simvastatin. Methods: Using piloted search terms via Google and Yahoo search engines, identified websites were screened for regulatory status, adherence to regulatory standards, administrative requirements, clinical assessment requirements and additional details deemed to be of relevance to a user. Characteristics of regulated and non-regulated (defined as those with an absence of a correctly linked regulatory logo) websites were compared to identify differences which could be used to improve patient safety. Main outcome measure: Regulatory status, adherence to regulatory standards, quality of information provision, barriers to medicines access. Results: 113 websites sold diazepam, fluoxetine and simvastatin; were identified within the first 100 results. Less than quarter were found to be regulated online pharmacies. 80 websites were willing to sell the medication without a prescription. The unregulated internet pharmacy websites (defined as those with an absence of a correctly linked regulatory logo) were found to adhere more closely to the clinical criteria, were less significantly likely to disclose a contact name and address, telephone number of the pharmacy or demand a prescription prior to sale (P\0.05, Fisher’s Exact). Conclusions: The three prescription-only medicines which are liable to abuse, have potentially serious interactions and require counselling to ensure patient safety are readily available via the internet. When purchasing medicines via this route UK consumers should be made aware of the importance of regulatory logos and additionally should ensure that the seller can be meaningfully contacted by the contact details provided. The provision of clinical information should not be used alone as an indication of the seller’s provenance

Chaotic motions in the real fuzzy electronic circuits

Fuzzy electronic circuit (FEC) is firstly introduced, which is implementing Takagi-Sugeno (T-S) fuzzy chaotic systems on electronic circuit. In the research field of secure communications, the original source should be blended with other complex signals. Chaotic signals are one of the good sources to be applied to encrypt high confidential signals, because of its high complexity, sensitiveness of initial conditions, and unpredictability. Consequently, generating chaotic signals on electronic circuit to produce real electrical signals applied to secure communications is an exceedingly important issue. However, nonlinear systems are always composed of many complex equations and are hard to realize on electronic circuits. Takagi-Sugeno (T-S) fuzzy model is a powerful tool, which is described by fuzzy IF-THEN rules to express the local dynamics of each fuzzy rule by a linear system model. Accordingly, in this paper, we produce the chaotic signals via electronic circuits through T-S fuzzy model and the numerical simulation results provided by MATLAB are also proposed for comparison. T-S fuzzy chaotic Lorenz and Chen-Lee systems are used for examples and are given to demonstrate the effectiveness of the proposed electronic circuit. © 2013 Shih-Yu Li et al

Knowledge-based identification of sleep stages based on two forehead electroencephalogram channels

© 2014 Huang, Lin, Ko, Liu, Su and Lin. Sleep quality is important, especially given the considerable number of sleep-related pathologies. The distribution of sleep stages is a highly effective and objective way of quantifying sleep quality. As a standard multi-channel recording used in the study of sleep, polysomnography (PSG) is a widely used diagnostic scheme in sleep medicine. However, the standard process of sleep clinical test, including PSG recording and manual scoring, is complex, uncomfortable, and time-consuming. This process is difficult to implement when taking the whole PSG measurements at home for general healthcare purposes. This work presents a novel sleep stage classification system, based on features from the two forehead EEG channels FP1 and FP2. By recording EEG from forehead, where there is no hair, the proposed system can monitor physiological changes during sleep in a more practical way than previous systems. Through a headband or self-adhesive technology, the necessary sensors can be applied easily by users at home. Analysis results demonstrate that classification performance of the proposed system overcomes the individual differences between different participants in terms of automatically classifying sleep stages. Additionally, the proposed sleep stage classification system can identify kernel sleep features extracted from forehead EEG, which are closely related with sleep clinician's expert knowledge. Moreover, forehead EEG features are classified into five sleep stages by using the relevance vector machine. In a leave-one-subject-out cross validation analysis, we found our system to correctly classify five sleep stages at an average accuracy of 76.7 ± 4.0 (SD) % [average kappa 0.68 ± 0.06 (SD)]. Importantly, the proposed sleep stage classification system using forehead EEG features is a viable alternative for measuring EEG signals at home easily and conveniently to evaluate sleep quality reliably, ultimately improving public healthcare

Robust Facial Alignment for Face Recognition

© 2017, Springer International Publishing AG. This paper proposes a robust real-time face recognition system that utilizes regression tree based method to locate the facial feature points. The proposed system finds the face region which is suitable to perform the recognition task by geometrically analyses of the facial expression of the target face image. In real-world facial recognition systems, the face is often cropped based on the face detection techniques. The misalignment is inevitably occurred due to facial pose, noise, occlusion, and so on. However misalignment affects the recognition rate due to sensitive nature of the face classifier. The performance of the proposed approach is evaluated with four benchmark databases. The experiment results show the robustness of the proposed approach with significant improvement in the facial recognition system on the various size and resolution of given face images

Multi-Photon Signals from Composite Models at LHC

We analyze the collider signals of composite scalars that emerge in certain little Higgs models and models of vectorlike confinement. Similar to the decay of the pion into photon pairs, these scalars mainly decay through anomaly-induced interactions into electroweak gauge bosons, leading to a distinct signal with three or more photons in the final state. We study the standard model backgrounds for these signals, and find that the LHC can discover these models over a large range of parameter space with 30 fb$^{-1}$ at 14 TeV. An early discovery at the current 7 TeV run is possible in some regions of parameter space. We also discuss possibilities to measure the spin of the particles in the $\gamma \gamma$ and $Z\gamma$ decay channels.Comment: 18 pages, LaTe

The Osteoporosis Society of Hong Kong (OSHK): 2013 OSHK Guideline for Clinical Management of Postmenopausal Osteoporosis in Hong Kong

published_or_final_versio

Colored Resonant Signals at the LHC: Largest Rate and Simplest Topology

We study the colored resonance production at the LHC in a most general approach. We classify the possible colored resonances based on group theory decomposition, and construct their effective interactions with light partons. The production cross section from annihilation of valence quarks or gluons may be on the order of 400 - 1000 pb at LHC energies for a mass of 1 TeV with nominal couplings, leading to the largest production rates for new physics at the TeV scale, and simplest event topology with dijet final states. We apply the new dijet data from the LHC experiments to put bounds on various possible colored resonant states. The current bounds range from 0.9 to 2.7 TeV. The formulation is readily applicable for future searches including other decay modes.Comment: 29 pages, 9 figures. References updated and additional K-factors include

A robust real-time facial alignment system with facial landmarks detection and rectification for multimedia applications

© 2020, Springer Science+Business Media, LLC, part of Springer Nature. Face detection often plays the first step in various visual applications. Large variants of facial deformations due to head movements and facial expression make it difficult to identify appropriate face region. In this paper, a robust real-time face alignment system, including facial landmarks detection and face rectification, is proposed. A facial landmarks detection model based on regression tree is utilized in the proposed system. In face rectification framework, 2-D geometrical analysis based on pitch, yaw and roll movements is designed to solve the misalignment problem in face detection. The experiments on the two datasets verify the performance significantly improved by the proposed method in the facial recognition task and outperform than those obtained by other alignment methods. Furthermore, the proposed method can achieve robust recognition results even if the amount of training images is not large

The landscape of potential health benefits of carotenoids as natural supportive therapeutics in protecting against Coronavirus infection

The Coronavirus Disease-2019 (COVID-19) pandemic urges researching possibilities for prevention and management of the effects of the virus. Carotenoids are natural phytochemicals of anti-oxidant, anti-inflammatory and immunomodulatory properties and may exert potential in aiding in combatting the pandemic. This review presents the direct and indirect evidence of the health benefits of carotenoids and derivatives based on in vitro and in vivo studies, human clinical trials and epidemiological studies and proposes possible mechanisms of action via which carotenoids may have the capacity to protect against COVID-19 effects. The current evidence provides a rationale for considering carotenoids as natural supportive nutrients via antioxidant activities, including scavenging lipid-soluble radicals, reducing hypoxia-associated superoxide by activating antioxidant enzymes, or suppressing enzymes that produce reactive oxygen species (ROS). Carotenoids may regulate COVID-19 induced over-production of pro-inflammatory cytokines, chemokines, pro-inflammatory enzymes and adhesion molecules by nuclear factor kappa B (NF-κB), renin-angiotensin-aldosterone system (RAS) and interleukins-6- Janus kinase-signal transducer and activator of transcription (IL-6-JAK/STAT) pathways and suppress the polarization of pro-inflammatory M1 macrophage. Moreover, carotenoids may modulate the peroxisome proliferator-activated receptors γ by acting as agonists to alleviate COVID-19 symptoms. They also may potentially block the cellular receptor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), human angiotensin-converting enzyme 2 (ACE2). These activities may reduce the severity of COVID-19 and flu-like diseases. Thus, carotenoid supplementation may aid in combatting the pandemic, as well as seasonal flu. However, further in vitro, in vivo and in particular long-term clinical trials in COVID-19 patients are needed to evaluate this hypothesis