Experimental and Numerical Benchmarking of an Improved Impeller Meanline Modelling Method for Automotive Turbocharger Centrifugal Compressors

After the development of a new single-zone meanline modelling technique, benchmarking of the technique and the modelling methods used during its development are presented. The new meanline model had been developed using the results of three automotive turbocharger centrifugal compressors, and single passage CFD models based on their geometry.

The target of the current study was to test the new meanline modelling method on two new centrifugal compressor stages, again from the automotive turbocharger variety. Furthermore the single passage CFD modelling method used in the previous study would be again employed here and also benchmarked.

The benchmarking was twofold; firstly test the overall performance prediction accuracy of the single-zone meanline model. Secondly, test the detailed performance estimation of the CFD model using detailed interstage static pressure tappings.

The final component of this study exposed the weaknesses in the current modelling methods used (explicitly during this study). The non-axisymmetric flow field at the leading and trailing edges for the two compressors was measured and is presented here for the complete compressor map, highlighting the distortion relative to the tongue.

UK publicly funded Clinical Trials Units supported a controlled access approach to share individual participant data but highlighted concerns

OBJECTIVES: Evaluate current data sharing activities of UK publicly funded Clinical Trial Units (CTUs) and identify good practices and barriers.

STUDY DESIGN AND SETTING: Web-based survey of Directors of 45 UK Clinical Research Collaboration (UKCRC)-registered CTUs.

RESULTS: Twenty-three (51%) CTUs responded: Five (22%) of these had an established data sharing policy and eight (35%) specifically requested consent to use patient data beyond the scope of the original trial. Fifteen (65%) CTUs had received requests for data, and seven (30%) had made external requests for data in the previous 12 months. CTUs supported the need for increased data sharing activities although concerns were raised about patient identification, misuse of data, and financial burden. Custodianship of clinical trial data and requirements for a CTU to align its policy to their parent institutes were also raised. No CTUs supported the use of an open access model for data sharing.

CONCLUSION: There is support within the publicly funded UKCRC-registered CTUs for data sharing, but many perceived barriers remain. CTUs are currently using a variety of approaches and procedures for sharing data. This survey has informed further work, including development of guidance for publicly funded CTUs, to promote good practice and facilitate data sharing.

Partial Palmprint Matching Using Invariant Local Minutiae Descriptors

In forensic investigations, it is common for forensic investigators to obtain a photograph of evidence left at the scene of crimes to aid them catch the culprit(s). Although, fingerprints are the most popular evidence that can be used, scene of crime officers claim that more than 30% of the evidence recovered from crime scenes originate from palms. Usually, palmprints evidence left at crime scenes are partial since very rarely full palmprints are obtained. In particular, partial palmprints do not exhibit a structured shape and often do not contain a reference point that can be used for their alignment to achieve efficient matching. This makes conventional matching methods based on alignment and minutiae pairing, as used in fingerprint recognition, to fail in partial palmprint recognition problems. In this paper a new partial-to-full palmprint recognition based on invariant minutiae descriptors is proposed where the partial palmprint’s minutiae are extracted and considered as the distinctive and discriminating features for each palmprint image. This is achieved by assigning to each minutiae a feature descriptor formed using the values of all the orientation histograms of the minutiae at hand. This allows for the descriptors to be rotation invariant and as such do not require any image alignment at the matching stage. The results obtained show that the proposed technique yields a recognition rate of 99.2%. The solution does give a high confidence to the judicial jury in their deliberations and decision.

Cloud benchmarking for performance

How can applications be deployed on the cloud to achieve maximum performance? This question has become significant and challenging with the availability of a wide variety of Virtual Machines (VMs) with different performance capabilities in the cloud. The above question is addressed by proposing a six step benchmarking methodology in which a user provides a set of four weights that indicate how important each of the following groups: memory, processor, computation and storage are to the application that needs to be executed on the cloud. The weights along with cloud benchmarking data are used to generate a ranking of VMs that can maximise performance of the application. The rankings are validated through an empirical analysis using two case study applications, the first is a financial risk application and the second is a molecular dynamics simulation, which are both representative of workloads that can benefit from execution on the cloud. Both case studies validate the feasibility of the methodology and highlight that maximum performance can be achieved on the cloud by selecting the top ranked VMs produced by the methodology.

Container-based Cloud Virtual Machine Benchmarking

With the availability of a wide range of cloud Virtual Machines (VMs) it is difficult to determine which VMs can maximise the performance of an application. Benchmarking is commonly used to this end for capturing the performance of VMs. Most cloud benchmarking techniques are typically heavyweight - time consuming processes which have to benchmark the entire VM in order to obtain accurate benchmark data. Such benchmarks cannot be used in real-time on the cloud and incur extra costs even before an application is deployed.

In this paper, we present lightweight cloud benchmarking techniques that execute quickly and can be used in near real-time on the cloud. The exploration of lightweight benchmarking techniques are facilitated by the development of DocLite - Docker Container-based Lightweight Benchmarking. DocLite is built on the Docker container technology which allows a user-defined portion (such as memory size and the number of CPU cores) of the VM to be benchmarked. DocLite operates in two modes, in the first mode, containers are used to benchmark a small portion of the VM to generate performance ranks. In the second mode, historic benchmark data is used along with the first mode as a hybrid to generate VM ranks. The generated ranks are evaluated against three scientific high-performance computing applications. The proposed techniques are up to 91 times faster than a heavyweight technique which benchmarks the entire VM. It is observed that the first mode can generate ranks with over 90% and 86% accuracy for sequential and parallel execution of an application. The hybrid mode improves the correlation slightly but the first mode is sufficient for benchmarking cloud VMs.

Epidemiology, Patterns of Care, and Mortality for Patients With Acute Respiratory Distress Syndrome in Intensive Care Units in 50 Countries

Importance Limited information exists about the epidemiology, recognition, management, and outcomes of patients with the acute respiratory distress syndrome (ARDS).

Objectives To evaluate intensive care unit (ICU) incidence and outcome of ARDS and to assess clinician recognition, ventilation management, and use of adjuncts—for example prone positioning—in routine clinical practice for patients fulfilling the ARDS Berlin Definition.

Design, Setting, and Participants The Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE) was an international, multicenter, prospective cohort study of patients undergoing invasive or noninvasive ventilation, conducted during 4 consecutive weeks in the winter of 2014 in a convenience sample of 459 ICUs from 50 countries across 5 continents.

Exposures Acute respiratory distress syndrome.

Main Outcomes and Measures The primary outcome was ICU incidence of ARDS. Secondary outcomes included assessment of clinician recognition of ARDS, the application of ventilatory management, the use of adjunctive interventions in routine clinical practice, and clinical outcomes from ARDS.

Results Of 29 144 patients admitted to participating ICUs, 3022 (10.4%) fulfilled ARDS criteria. Of these, 2377 patients developed ARDS in the first 48 hours and whose respiratory failure was managed with invasive mechanical ventilation. The period prevalence of mild ARDS was 30.0% (95% CI, 28.2%-31.9%); of moderate ARDS, 46.6% (95% CI, 44.5%-48.6%); and of severe ARDS, 23.4% (95% CI, 21.7%-25.2%). ARDS represented 0.42 cases per ICU bed over 4 weeks and represented 10.4% (95% CI, 10.0%-10.7%) of ICU admissions and 23.4% of patients requiring mechanical ventilation. Clinical recognition of ARDS ranged from 51.3% (95% CI, 47.5%-55.0%) in mild to 78.5% (95% CI, 74.8%-81.8%) in severe ARDS. Less than two-thirds of patients with ARDS received a tidal volume 8 of mL/kg or less of predicted body weight. Plateau pressure was measured in 40.1% (95% CI, 38.2-42.1), whereas 82.6% (95% CI, 81.0%-84.1%) received a positive end-expository pressure (PEEP) of less than 12 cm H2O. Prone positioning was used in 16.3% (95% CI, 13.7%-19.2%) of patients with severe ARDS. Clinician recognition of ARDS was associated with higher PEEP, greater use of neuromuscular blockade, and prone positioning. Hospital mortality was 34.9% (95% CI, 31.4%-38.5%) for those with mild, 40.3% (95% CI, 37.4%-43.3%) for those with moderate, and 46.1% (95% CI, 41.9%-50.4%) for those with severe ARDS.

Conclusions and Relevance Among ICUs in 50 countries, the period prevalence of ARDS was 10.4% of ICU admissions. This syndrome appeared to be underrecognized and undertreated and associated with a high mortality rate. These findings indicate the potential for improvement in the management of patients with ARDS.

DocLite: A Docker-Based Lightweight Cloud Benchmarking Tool

Existing benchmarking methods are time consuming processes as they typically benchmark the entire Virtual Machine (VM) in order to generate accurate performance data, making them less suitable for real-time analytics. The research in this paper is aimed to surmount the above challenge by presenting DocLite - Docker Container-based Lightweight benchmarking tool. DocLite explores lightweight cloud benchmarking methods for rapidly executing benchmarks in near real-time. DocLite is built on the Docker container technology, which allows a user-defined memory size and number of CPU cores of the VM to be benchmarked. The tool incorporates two benchmarking methods - the first referred to as the native method employs containers to benchmark a small portion of the VM and generate performance ranks, and the second uses historic benchmark data along with the native method as a hybrid to generate VM ranks. The proposed methods are evaluated on three use-cases and are observed to be up to 91 times faster than benchmarking the entire VM. In both methods, small containers provide the same quality of rankings as a large container. The native method generates ranks with over 90% and 86% accuracy for sequential and parallel execution of an application compared against benchmarking the whole VM. The hybrid method did not improve the quality of the rankings significantly.

Alpha-2 agonists for sedation of mechanically ventilated adults in intensive care units: a systematic review

BACKGROUND: Care of critically ill patients in intensive care units (ICUs) often requires potentially invasive or uncomfortable procedures, such as mechanical ventilation (MV). Sedation can alleviate pain and discomfort, provide protection from stressful or harmful events, prevent anxiety and promote sleep. Various sedative agents are available for use in ICUs. In the UK, the most commonly used sedatives are propofol (Diprivan(®), AstraZeneca), benzodiazepines [e.g. midazolam (Hypnovel(®), Roche) and lorazepam (Ativan(®), Pfizer)] and alpha-2 adrenergic receptor agonists [e.g. dexmedetomidine (Dexdor(®), Orion Corporation) and clonidine (Catapres(®), Boehringer Ingelheim)]. Sedative agents vary in onset/duration of effects and in their side effects. The pattern of sedation of alpha-2 agonists is quite different from that of other sedatives in that patients can be aroused readily and their cognitive performance on psychometric tests is usually preserved. Moreover, respiratory depression is less frequent after alpha-2 agonists than after other sedative agents.

OBJECTIVES: To conduct a systematic review to evaluate the comparative effects of alpha-2 agonists (dexmedetomidine and clonidine) and propofol or benzodiazepines (midazolam and lorazepam) in mechanically ventilated adults admitted to ICUs.

DATA SOURCES: We searched major electronic databases (e.g. MEDLINE without revisions, MEDLINE In-Process & Other Non-Indexed Citations, EMBASE and Cochrane Central Register of Controlled Trials) from 1999 to 2014.

METHODS: Evidence was considered from randomised controlled trials (RCTs) comparing dexmedetomidine with clonidine or dexmedetomidine or clonidine with propofol or benzodiazepines such as midazolam, lorazepam and diazepam (Diazemuls(®), Actavis UK Limited). Primary outcomes included mortality, duration of MV, length of ICU stay and adverse events. One reviewer extracted data and assessed the risk of bias of included trials. A second reviewer cross-checked all the data extracted. Random-effects meta-analyses were used for data synthesis.

RESULTS: Eighteen RCTs (2489 adult patients) were included. One trial at unclear risk of bias compared dexmedetomidine with clonidine and found that target sedation was achieved in a higher number of patients treated with dexmedetomidine with lesser need for additional sedation. The remaining 17 trials compared dexmedetomidine with propofol or benzodiazepines (midazolam or lorazepam). Trials varied considerably with regard to clinical population, type of comparators, dose of sedative agents, outcome measures and length of follow-up. Overall, risk of bias was generally high or unclear. In particular, few trials blinded outcome assessors. Compared with propofol or benzodiazepines (midazolam or lorazepam), dexmedetomidine had no significant effects on mortality [risk ratio (RR) 1.03, 95% confidence interval (CI) 0.85 to 1.24, I (2) = 0%; p = 0.78]. Length of ICU stay (mean difference -1.26 days, 95% CI -1.96 to -0.55 days, I (2) = 31%; p = 0.0004) and time to extubation (mean difference -1.85 days, 95% CI -2.61 to -1.09 days, I (2) = 0%; p < 0.00001) were significantly shorter among patients who received dexmedetomidine. No difference in time to target sedation range was observed between sedative interventions (I (2) = 0%; p = 0.14). Dexmedetomidine was associated with a higher risk of bradycardia (RR 1.88, 95% CI 1.28 to 2.77, I (2) = 46%; p = 0.001).

LIMITATIONS: Trials varied considerably with regard to participants, type of comparators, dose of sedative agents, outcome measures and length of follow-up. Overall, risk of bias was generally high or unclear. In particular, few trials blinded assessors.

CONCLUSIONS: Evidence on the use of clonidine in ICUs is very limited. Dexmedetomidine may be effective in reducing ICU length of stay and time to extubation in critically ill ICU patients. Risk of bradycardia but not of overall mortality is higher among patients treated with dexmedetomidine. Well-designed RCTs are needed to assess the use of clonidine in ICUs and identify subgroups of patients that are more likely to benefit from the use of dexmedetomidine.

STUDY REGISTRATION: This study is registered as PROSPERO CRD42014014101.

FUNDING: The National Institute for Health Research Health Technology Assessment programme. The Health Services Research Unit is core funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates.

Spatial hearing and sound perception in musical composition

This thesis explores the possibilities of spatial hearing in relation to sound perception, and presents three acousmatic compositions based on a musical aesthetic that emphasizes this relation in musical discourse. The first important characteristic of these compositions is the exclusive use of sine waves and other time invariant sound signals. Even though these types of sound signals present no variations in time, it is possible to perceive pitch, loudness, and tone color variations as soon as they move in space due to acoustic processes involved in spatial hearing. To emphasize the perception of such variations, this thesis proposes to divide a tone in multiple sound units and spread them in space using several loudspeakers arranged around the listener. In addition to the perception of sound attribute variations, it is also possible to create rhythm and texture variations that depend on how sound units are arranged in space. This strategy permits to overcome the so called "sound surrogacy" implicit in acousmatic music, as it is possible to establish cause-effect relations between sound movement and the perception of sound attribute, rhythm, and texture variations. Another important consequence of using sound fragmentation together with sound spatialization is the possibility to produce diffuse sound fields independently from the levels of reverberation of the room, and to create sound spaces with a certain spatial depth without using any kind of artificial sound delay or reverberation.

Architecture for real-time coordination of multiple autonomous mobile units

Interest on using teams of mobile robots has been growing, due to their potential to cooperate for diverse purposes, such as rescue, de-mining, surveillance or even games such as robotic soccer. These applications require a real-time middleware and wireless communication protocol that can support an efficient and timely fusion of the perception data from different robots as well as the development of coordinated behaviours. Coordinating several autonomous robots towards achieving a common goal is currently a topic of high interest, which can be found in many application domains. Despite these different application domains, the technical problem of building an infrastructure to support the integration of the distributed perception and subsequent coordinated action is similar. This problem becomes tougher with stronger system dynamics, e.g., when the robots move faster or interact with fast objects, leading to tighter real-time constraints. This thesis work addressed computing architectures and wireless communication protocols to support efficient information sharing and coordination strategies taking into account the real-time nature of robot activities. The thesis makes two main claims. Firstly, we claim that despite the use of a wireless communication protocol that includes arbitration mechanisms, the self-organization of the team communications in a dynamic round that also accounts for variable team membership, effectively reduces collisions within the team, independently of its current composition, significantly improving the quality of the communications. We will validate this claim in terms of packet losses and communication latency. We show how such self-organization of the communications can be achieved in an efficient way with the Reconfigurable and Adaptive TDMA protocol. Secondly, we claim that the development of distributed perception, cooperation and coordinated action for teams of mobile robots can be simplified by using a shared memory middleware that replicates in each cooperating robot all necessary remote data, the Real-Time Database (RTDB) middleware. These remote data copies, which are updated in the background by the selforganizing communications protocol, are extended with age information automatically computed by the middleware and are locally accessible through fast primitives. We validate our claim showing a parsimonious use of the communication medium, improved timing information with respect to the shared data and the simplicity of use and effectiveness of the proposed middleware shown in several use cases, reinforced with a reasonable impact in the Middle Size League of RoboCup.

Heritability and The Units of Selection: A defense of Genic Selectionism

Tesina elaborada para obtener el MPhil en la Universidad de Cambridge, Inglaterra, 1987

Invariant multi-scale object categorisation and recognition

Object recognition requires that templates with canonical views are stored in memory. Such templates must somehow be normalised. In this paper we present a novel method for obtaining 2D translation, rotation and size invariance. Cortical simple, complex and end-stopped cells provide multi-scale maps of lines, edges and keypoints. These maps are combined such that objects are characterised. Dynamic routing in neighbouring neural layers allows feature maps of input objects and stored templates to converge. We illustrate the construction of group templates and the invariance method for object categorisation and recognition in the context of a cortical architecture, which can be applied in computer vision.

Neuro-genetic PID autotuning: time invariant case

The Proportional, Integral and Derivative (PID) controllers are widely used in induxtrial applications. Their popularity comes from their robust performance and also from their functional simplicity.