Surrey Research Insight

    Active flow control on a square-back road vehicle

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    An experimental investigation focused on the manipulation of the wake generated by a square back car model is presented. Four continuously-blowing rectangular slot jets were mounted on the rear face of a 1:10 commercial van model. Load cell measurements evidence drag reduction for different forcing configurations, reaching a maximum of 12% for lateral and bottom jets blowing. The spectral analysis of the pressure fluctuations evidence, for all forced cases, an energy attenuation with respect to the natural case, especially close to the shedding frequency. An energy budget highlighted the most efficient forcing configurations accounting for both the drag reduction and the power required to feed the blowing system. Two main configurations are considered: the maximum drag reduction and the best compromise, yielding 5% drag reduction and a convenient energy balance. Particle Image Velocimetry (pPIV) and stereoscopic PIV (sPIV) experiments were performed allowing the three-dimensional reconstruction of the wake in the three considered configurations. Consistently with static and fluctuating pressure measurements, sPIV results reveal a dramatic change in the wake structure when the jets blow in the maximum drag reduction configuration. Conversely, the best compromise configuration reveals a wake structure similar to the natural one

    Evolutionary Multiobjective Optimization Driven by Generative Adversarial Networks (GANs)

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    Recently, increasing works have been proposed to drive evolutionary algorithms using machine-learning models. Usually, the performance of such model-based evolutionary algorithms is highly dependent on the training qualities of the adopted models. Since it usually requires a certain amount of data (i.e., the candidate solutions generated by the algorithms) for model training, the performance deteriorates rapidly with the increase of the problem scales due to the curse of dimensionality. To address this issue, we propose a multiobjective evolutionary algorithm driven by the generative adversarial networks (GANs). At each generation of the proposed algorithm, the parent solutions are first classified into real and fake samples to train the GANs; then the offspring solutions are sampled by the trained GANs. Thanks to the powerful generative ability of the GANs, our proposed algorithm is capable of generating promising offspring solutions in high-dimensional decision space with limited training data. The proposed algorithm is tested on ten benchmark problems with up to 200 decision variables. The experimental results on these test problems demonstrate the effectiveness of the proposed algorithm

    To Learn or Not to Learn: Deep Learning Assisted Wireless Modem Design

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    Deep learning is driving a radical paradigm shift in wireless communications, all the way from the application layer down to the physical layer. Despite this, there is an ongoing debate as to what additional values artificial intelligence (or machine learning) could bring to us, particularly on the physical layer design; and what penalties there may have? These questions motivate a fundamental rethinking of the wireless modem design in the artificial intelligence era. Through several physical-layer case studies, we argue for a significant role that machine learning could play, for instance in parallel error-control coding and decoding, channel equalization, interference cancellation, as well as multiuser and multiantenna detection. In addition, we will also discuss the fundamental bottlenecks of machine learning as well as their potential solutions in this paper

    An instrument to identify computerised primary care research networks, genetic and disease registries prepared to conduct linked research: TRANSFoRm International Research Readiness (TIRRE) survey

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    Purpose The Translational Research and Patients safety in Europe (TRANSFoRm) project aims to integrate primary care with clinical research whilst improving patient safety. The TRANSFoRm International Research Readiness survey (TIRRE) aims to demonstrate data use through two linked data studies and by identifying clinical data repositories and genetic databases or disease registries prepared to participate in linked research. Method The TIRRE survey collects data at micro-, meso- and macro-levels of granularity; to fulfil data, study specific, business, geographical and readiness requirements of potential data providers for the TRANSFoRm demonstration studies. We used descriptive statistics to differentiate between demonstration-study compliant and non-compliant repositories. We only included surveys with >70% of questions answered in our final analysis, reporting the odds ratio (OR) of positive responses associated with a demonstration-study compliant data provider. Results We contacted 531 organisations within the Eurpean Union (EU). Two declined to supply information; 56 made a valid response and a further 26 made a partial response. Of the 56 valid responses, 29 were databases of primary care data, 12 were genetic databases and 15 were cancer registries. The demonstration compliant primary care sites made 2098 positive responses compared with 268 in non-use-case compliant data sources [OR: 4.59, 95% confidence interval (CI): 3.93–5.35, p < 0.008]; for genetic databases: 380:44 (OR: 6.13, 95% CI: 4.25–8.85, p < 0.008) and cancer registries: 553:44 (OR: 5.87, 95% CI: 4.13–8.34, p < 0.008).Conclusions TIRRE comprehensively assesses the preparedness of data repositories to participate in specific research projects. Multiple contacts about hypothetical participation in research identified few potential sites

    Energy-efficient QoE-driven Strategies forContext-aware RAT Selection

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    This paper formulates an optimization problem thatmaximizes an aggregate utility that captures the “in-context” suit-ability of available radio access technologies (RATs) to supportadaptive video streaming subject to a single-homing constraint.To efficiently solve the considered problem, a novel network-assisted quality-of-experience (QoE)-driven methodology is de-vised, and its impact on the end-user devices is evaluated.The proposed approach is evaluated and benchmarked againstits distributed and centralized counterparts from a cost-benefitperspective. The results reveal that the proposed strategy sig-nificantly outperforms its distributed counterpart, and performsdifferently with respect to its centralized counterpart dependingon the number of video clients. At low loads, it performs similarlywith much less control overhead. At high loads, the proposedstrategy scales up well, while the centralized approach getsoverwhelmed by an increasing uplink signaling. A practicalityanalysis of the proposed strategy for battery-powered devicesreveals that its gain in terms of uplink signaling outweighs its costin terms of processing load, which results in a drastic reduction ofthe consumed energy. Therefore, the proposed solution providesa win-win situation, where the video clients can sustain goodQoE levels at reduced energy consumption, while the networkcan accommodate more users with existing capacity

    The role of daylight for humans: Gaps in current knowledge

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    Daylight stems solely from direct, scattered and reflected sunlight, and undergoes dynamic changes in irradiance and spectral power composition due to latitude, time of day, time of year and the nature of the physical environment (reflections, buildings and vegetation). Humans and their ancestors evolved under these natural day/night cycles over millions of years. Electric light, a relatively recent invention, interacts and competes with the natural light–dark cycle to impact human biology. What are the consequences of living in industrialised urban areas with much less daylight and more use of electric light, throughout the day (and at night), on general health and quality of life? In this workshop report, we have classified key gaps of knowledge in daylight research into three main groups: (I) uncertainty as to daylight quantity and quality needed for “optimal” physiological and psychological functioning, (II) lack of consensus on practical measurement and assessment methods and tools for monitoring real (day) light exposure across multiple time scales, and (III) insufficient integration and exchange of daylight knowledge bases from different disciplines. Crucial short and long-term objectives to fill these gaps are proposed

    On the relevance of cocaine detection in a fingerprint

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    The finding that drugs and metabolites can be detected from fingerprints is of potential relevance to forensic science and as well as toxicology and clinical testing. However, discriminating between dermal contact and ingestion of drugs has never been verified experimentally. The inability to interpret the result of finding a drug or metabolite in a fingerprint has prevented widespread adoption of fingerprints in drug testing and limits the probative value of detecting drugs in fingermarks. A commonly held belief is that the detection of metabolites of drugs of abuse in fingerprints can be used to confirm a drug has been ingested. However, we show here that cocaine and its primary metabolite, benzoylecgonine, can be detected in fingerprints of non-drug users after contact with cocaine. Additionally, cocaine was found to persist above environmental levels for up to 48 hours after contact. Therefore the detection of cocaine and benzoylecgonine (BZE) in fingermarks can be forensically significant, but do not demonstrate that a person has ingested the substance. In contrast, the data here shows that a drug test from a fingerprint (where hands can be washed prior to donating a sample) CAN distinguish between contact and ingestion of cocaine. If hands were washed prior to giving a fingerprint, BZE was detected only after the administration of cocaine. Therefore BZE can be used to distinguish cocaine contact from cocaine ingestion, provided donors wash their hands prior to sampling. A test based on the detection of BZE in at least one of two donated fingerprint samples has accuracy 95%, sensitivity 90% and specificity of 100% (n = 86)

    Two-neutron knockout as a probe of the composition of states in 22Mg, 23Al, and 24Si

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    Simpson and Tostevin proposed that the width and shape of exclusive parallel momentum distributions of the

    Antlia 2’s Role in Driving the Ripples in the Outer Gas Disk of the Galaxy

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    We employ the earlier published proper motions of the newly discovered Antlia 2 dwarf galaxy derived from Gaia data to calculate its orbital distribution in the cosmologically recent past. Using these observationally motivated orbits, we calculate the effect of the Antlia 2 dwarf galaxy on the outer H I disk of the Milky Way, using both test particle and smoothed particle hydrodynamics simulations. We find that orbits with low pericenters, ∼10 kpc, produce disturbances that match the observed outer H I disk perturbations. We have independently recalculated the proper motion of the Antlia 2 dwarf from Gaia data and found a proper motion of (μ α cosδ, μ δ ) = (−0.068, 0.032) ± (0.023, −0.031) mas yr−1, which agrees with results from Torrealba et al. within the errors, but gives lower mean pericenters, e.g., ∼15 kpc for our fiducial model of the Milky Way. We also show that the Sagittarius dwarf galaxy interaction does not match the observed perturbations in the outer gas disk. Thus, Antlia 2 may be the driver of the observed large perturbations in the outer gas disk of the Galaxy. The current location of the Antlia 2 dwarf galaxy closely matches that predicted by an earlier dynamical analysis of the dwarf galaxy that drove ripples in the outer Galaxy, and, in particular, its orbit is nearly coplanar to the Galactic disk. If the Antlia 2 dwarf galaxy is responsible for the perturbations in the outer Galactic disk, it would have a specific range of proper motions that we predict here; this can be tested soon with Gaia DR-3 and Gaia DR-4 data

    Partial mitigation of oxidised phospholipid-mediated mitochondrial dysfunction in neuronal cells by oxocarotenoids

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    Mitochondria are important (patho)physiological sources of reactive oxygen species (ROS) that mediate mitochondrial dysfunction and phospholipid oxidation; an increase in mitochondrial content of oxidised phospholipid (OxPL) associates with cell death. Previously we showed that the circulating OxPL 1-palmitoyl-2-(5'-oxo-valeroyl)-sn-glycero-3-phosphocholine (POVPC) increases in patients with Alzheimer’s disease (AD), and associates with lower plasma antioxidant oxocarotenoids, zeaxanthin and lutein. Since oxocarotenoids are metabolised in mitochondria, we propose that during AD, lower concentrations of mitochondrial zeaxanthin and lutein may result in greater phospholipid oxidation and predispose to neurodegeneration. Here, we have investigated whether non-toxic POVPC concentrations impair mitochondrial metabolism in differentiated (d)SH-SY5Y neuronal cells and whether there is any protective role for oxocarotenoids against mitochondrial dysfunction. After 24 hours, glutathione (GSH) concentration was lower in neuronal cells exposed to POVPC (1-20μM) compared with vehicle control without loss of viability compared to control. However, mitochondrial ROS production (determined by MitoSOX oxidation) was increased by 50% only after 20μM POVPC. Following delivery of lutein (0.1-1μM) and zeaxanthin (0.5-5μM) over 24 hours in vitro, oxocarotenoid recovery from dSH-SY5Y cells was >50%. Co-incubation with oxocarotenoids prevented loss of GSH after 1μM but not 20μM POVPC, whereas the increase in ROS production induced by 20μM POVPC was prevented by lutein and zeaxanthin. Mitochondrial uncoupling increases and ATP production is inhibited by 20μM but not 1 μM POVPC; carotenoids protected against uncoupling although did not restore ATP production. In summary, 20μM POVPC induced loss of GSH and a mitochondrial bioenergetic deficit in neuronal cells that was not mitigated by oxocarotenoids
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