Machine learning prediction for classification of outcomes in local minimisation

NASA Astrophysics Data System (ADS)

Das, Ritankar; Wales, David J.

2017-01-01

Machine learning schemes are employed to predict which local minimum will result from local energy minimisation of random starting configurations for a triatomic cluster. The input data consists of structural information at one or more of the configurations in optimisation sequences that converge to one of four distinct local minima. The ability to make reliable predictions, in terms of the energy or other properties of interest, could save significant computational resources in sampling procedures that involve systematic geometry optimisation. Results are compared for two energy minimisation schemes, and for neural network and quadratic functions of the inputs.

Focal psychodynamic therapy, cognitive behaviour therapy, and optimised treatment as usual in outpatients with anorexia nervosa (ANTOP study): randomised controlled trial.

PubMed

Zipfel, Stephan; Wild, Beate; Groß, Gaby; Friederich, Hans-Christoph; Teufel, Martin; Schellberg, Dieter; Giel, Katrin E; de Zwaan, Martina; Dinkel, Andreas; Herpertz, Stephan; Burgmer, Markus; Löwe, Bernd; Tagay, Sefik; von Wietersheim, Jörn; Zeeck, Almut; Schade-Brittinger, Carmen; Schauenburg, Henning; Herzog, Wolfgang

2014-01-11

Psychotherapy is the treatment of choice for patients with anorexia nervosa, although evidence of efficacy is weak. The Anorexia Nervosa Treatment of OutPatients (ANTOP) study aimed to assess the efficacy and safety of two manual-based outpatient treatments for anorexia nervosa--focal psychodynamic therapy and enhanced cognitive behaviour therapy--versus optimised treatment as usual. The ANTOP study is a multicentre, randomised controlled efficacy trial in adults with anorexia nervosa. We recruited patients from ten university hospitals in Germany. Participants were randomly allocated to 10 months of treatment with either focal psychodynamic therapy, enhanced cognitive behaviour therapy, or optimised treatment as usual (including outpatient psychotherapy and structured care from a family doctor). The primary outcome was weight gain, measured as increased body-mass index (BMI) at the end of treatment. A key secondary outcome was rate of recovery (based on a combination of weight gain and eating disorder-specific psychopathology). Analysis was by intention to treat. This trial is registered at http://isrctn.org, number ISRCTN72809357. Of 727 adults screened for inclusion, 242 underwent randomisation: 80 to focal psychodynamic therapy, 80 to enhanced cognitive behaviour therapy, and 82 to optimised treatment as usual. At the end of treatment, 54 patients (22%) were lost to follow-up, and at 12-month follow-up a total of 73 (30%) had dropped out. At the end of treatment, BMI had increased in all study groups (focal psychodynamic therapy 0·73 kg/m(2), enhanced cognitive behaviour therapy 0·93 kg/m(2), optimised treatment as usual 0·69 kg/m(2)); no differences were noted between groups (mean difference between focal psychodynamic therapy and enhanced cognitive behaviour therapy -0·45, 95% CI -0·96 to 0·07; focal psychodynamic therapy vs optimised treatment as usual -0·14, -0·68 to 0·39; enhanced cognitive behaviour therapy vs optimised treatment as usual -0·30, -0·22 to 0·83). At 12-month follow-up, the mean gain in BMI had risen further (1·64 kg/m(2), 1·30 kg/m(2), and 1·22 kg/m(2), respectively), but no differences between groups were recorded (0·10, -0·56 to 0·76; 0·25, -0·45 to 0·95; 0·15, -0·54 to 0·83, respectively). No serious adverse events attributable to weight loss or trial participation were recorded. Optimised treatment as usual, combining psychotherapy and structured care from a family doctor, should be regarded as solid baseline treatment for adult outpatients with anorexia nervosa. Focal psychodynamic therapy proved advantageous in terms of recovery at 12-month follow-up, and enhanced cognitive behaviour therapy was more effective with respect to speed of weight gain and improvements in eating disorder psychopathology. Long-term outcome data will be helpful to further adapt and improve these novel manual-based treatment approaches. German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF), German Eating Disorders Diagnostic and Treatment Network (EDNET). Copyright © 2014 Elsevier Ltd. All rights reserved.

Feasibility and Clinical Utility of High-definition Transcranial Direct Current Stimulation in the Treatment of Persistent Hallucinations in Schizophrenia.

PubMed

Bose, A; Shivakumar, V; Chhabra, H; Parlikar, R; Sreeraj, V S; Dinakaran, D; Narayanaswamy, J C; Venkatasubramanian, G

2017-12-01

Persistent auditory verbal hallucination is a clinically significant problem in schizophrenia. Recent studies suggest a promising role for add-on transcranial direct current stimulation (tDCS) in treatment. An optimised version of tDCS, namely high-definition tDCS (HD-tDCS), uses smaller electrodes arranged in a 4x1 ring configuration and may offer more focal and predictable neuromodulation than conventional tDCS. This case report illustrates the feasibility and clinical utility of add-on HD-tDCS over the left temporoparietal junction in a 4x1 ring configuration to treat persistent auditory verbal hallucination in schizophrenia.

Nonlinear predictive control of a boiler-turbine unit: A state-space approach with successive on-line model linearisation and quadratic optimisation.

PubMed

Ławryńczuk, Maciej

2017-03-01

This paper details development of a Model Predictive Control (MPC) algorithm for a boiler-turbine unit, which is a nonlinear multiple-input multiple-output process. The control objective is to follow set-point changes imposed on two state (output) variables and to satisfy constraints imposed on three inputs and one output. In order to obtain a computationally efficient control scheme, the state-space model is successively linearised on-line for the current operating point and used for prediction. In consequence, the future control policy is easily calculated from a quadratic optimisation problem. For state estimation the extended Kalman filter is used. It is demonstrated that the MPC strategy based on constant linear models does not work satisfactorily for the boiler-turbine unit whereas the discussed algorithm with on-line successive model linearisation gives practically the same trajectories as the truly nonlinear MPC controller with nonlinear optimisation repeated at each sampling instant. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

GNAQPMS v1.1: accelerating the Global Nested Air Quality Prediction Modeling System (GNAQPMS) on Intel Xeon Phi processors

NASA Astrophysics Data System (ADS)

Wang, Hui; Chen, Huansheng; Wu, Qizhong; Lin, Junmin; Chen, Xueshun; Xie, Xinwei; Wang, Rongrong; Tang, Xiao; Wang, Zifa

2017-08-01

The Global Nested Air Quality Prediction Modeling System (GNAQPMS) is the global version of the Nested Air Quality Prediction Modeling System (NAQPMS), which is a multi-scale chemical transport model used for air quality forecast and atmospheric environmental research. In this study, we present the porting and optimisation of GNAQPMS on a second-generation Intel Xeon Phi processor, codenamed Knights Landing (KNL). Compared with the first-generation Xeon Phi coprocessor (codenamed Knights Corner, KNC), KNL has many new hardware features such as a bootable processor, high-performance in-package memory and ISA compatibility with Intel Xeon processors. In particular, we describe the five optimisations we applied to the key modules of GNAQPMS, including the CBM-Z gas-phase chemistry, advection, convection and wet deposition modules. These optimisations work well on both the KNL 7250 processor and the Intel Xeon E5-2697 V4 processor. They include (1) updating the pure Message Passing Interface (MPI) parallel mode to the hybrid parallel mode with MPI and OpenMP in the emission, advection, convection and gas-phase chemistry modules; (2) fully employing the 512 bit wide vector processing units (VPUs) on the KNL platform; (3) reducing unnecessary memory access to improve cache efficiency; (4) reducing the thread local storage (TLS) in the CBM-Z gas-phase chemistry module to improve its OpenMP performance; and (5) changing the global communication from writing/reading interface files to MPI functions to improve the performance and the parallel scalability. These optimisations greatly improved the GNAQPMS performance. The same optimisations also work well for the Intel Xeon Broadwell processor, specifically E5-2697 v4. Compared with the baseline version of GNAQPMS, the optimised version was 3.51 × faster on KNL and 2.77 × faster on the CPU. Moreover, the optimised version ran at 26 % lower average power on KNL than on the CPU. With the combined performance and energy improvement, the KNL platform was 37.5 % more efficient on power consumption compared with the CPU platform. The optimisations also enabled much further parallel scalability on both the CPU cluster and the KNL cluster scaled to 40 CPU nodes and 30 KNL nodes, with a parallel efficiency of 70.4 and 42.2 %, respectively.

Advanced treatment planning using direct 4D optimisation for pencil-beam scanned particle therapy

NASA Astrophysics Data System (ADS)

Bernatowicz, Kinga; Zhang, Ye; Perrin, Rosalind; Weber, Damien C.; Lomax, Antony J.

2017-08-01

We report on development of a new four-dimensional (4D) optimisation approach for scanned proton beams, which incorporates both irregular motion patterns and the delivery dynamics of the treatment machine into the plan optimiser. Furthermore, we assess the effectiveness of this technique to reduce dose to critical structures in proximity to moving targets, while maintaining effective target dose homogeneity and coverage. The proposed approach has been tested using both a simulated phantom and a clinical liver cancer case, and allows for realistic 4D calculations and optimisation using irregular breathing patterns extracted from e.g. 4DCT-MRI (4D computed tomography-magnetic resonance imaging). 4D dose distributions resulting from our 4D optimisation can achieve almost the same quality as static plans, independent of the studied geometry/anatomy or selected motion (regular and irregular). Additionally, current implementation of the 4D optimisation approach requires less than 3 min to find the solution for a single field planned on 4DCT of a liver cancer patient. Although 4D optimisation allows for realistic calculations using irregular breathing patterns, it is very sensitive to variations from the planned motion. Based on a sensitivity analysis, target dose homogeneity comparable to static plans (D5-D95  <5%) has been found only for differences in amplitude of up to 1 mm, for changes in respiratory phase  <200 ms and for changes in the breathing period of  <20 ms in comparison to the motions used during optimisation. As such, methods to robustly deliver 4D optimised plans employing 4D intensity-modulated delivery are discussed.

The optimization of treatment and management of schizophrenia in Europe (OPTiMiSE) trial: rationale for its methodology and a review of the effectiveness of switching antipsychotics.

PubMed

Leucht, Stefan; Winter-van Rossum, Inge; Heres, Stephan; Arango, Celso; Fleischhacker, W Wolfgang; Glenthøj, Birte; Leboyer, Marion; Leweke, F Markus; Lewis, Shôn; McGuire, Phillip; Meyer-Lindenberg, Andreas; Rujescu, Dan; Kapur, Shitij; Kahn, René S; Sommer, Iris E

2015-05-01

Most of the 13 542 trials contained in the Cochrane Schizophrenia Group's register just tested the general efficacy of pharmacological or psychosocial interventions. Studies on the subsequent treatment steps, which are essential to guide clinicians, are largely missing. This knowledge gap leaves important questions unanswered. For example, when a first antipsychotic failed, is switching to another drug effective? And when should we use clozapine? The aim of this article is to review the efficacy of switching antipsychotics in case of nonresponse. We also present the European Commission sponsored "Optimization of Treatment and Management of Schizophrenia in Europe" (OPTiMiSE) trial which aims to provide a treatment algorithm for patients with a first episode of schizophrenia. We searched Pubmed (October 29, 2014) for randomized controlled trials (RCTs) that examined switching the drug in nonresponders to another antipsychotic. We described important methodological choices of the OPTiMiSE trial. We found 10 RCTs on switching antipsychotic drugs. No trial was conclusive and none was concerned with first-episode schizophrenia. In OPTiMiSE, 500 first episode patients are treated with amisulpride for 4 weeks, followed by a 6-week double-blind RCT comparing continuation of amisulpride with switching to olanzapine and ultimately a 12-week clozapine treatment in nonremitters. A subsequent 1-year RCT validates psychosocial interventions to enhance adherence. Current literature fails to provide basic guidance for the pharmacological treatment of schizophrenia. The OPTiMiSE trial is expected to provide a basis for clinical guidelines to treat patients with a first episode of schizophrenia. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Economic impact of optimising antiretroviral treatment in human immunodeficiency virus-infected adults with suppressed viral load in Spain, by implementing the grade A-1 evidence recommendations of the 2015 GESIDA/National AIDS Plan.

PubMed

Ribera, Esteban; Martínez-Sesmero, José Manuel; Sánchez-Rubio, Javier; Rubio, Rafael; Pasquau, Juan; Poveda, José Luis; Pérez-Mitru, Alejandro; Roldán, Celia; Hernández-Novoa, Beatriz

2018-03-01

The objective of this study is to estimate the economic impact associated with the optimisation of triple antiretroviral treatment (ART) in patients with undetectable viral load according to the recommendations from the GeSIDA/PNS (2015) Consensus and their applicability in the Spanish clinical practice. A pharmacoeconomic model was developed based on data from a National Hospital Prescription Survey on ART (2014) and the A-I evidence recommendations for the optimisation of ART from the GeSIDA/PNS (2015) consensus. The optimisation model took into account the willingness to optimise a particular regimen and other assumptions, and the results were validated by an expert panel in HIV infection (Infectious Disease Specialists and Hospital Pharmacists). The analysis was conducted from the NHS perspective, considering the annual wholesale price and accounting for deductions stated in the RD-Law 8/2010 and the VAT. The expert panel selected six optimisation strategies, and estimated that 10,863 (13.4%) of the 80,859 patients in Spain currently on triple ART, would be candidates to optimise their ART, leading to savings of €15.9M/year (2.4% of total triple ART drug cost). The most feasible strategies (>40% of patients candidates for optimisation, n=4,556) would be optimisations to ATV/r+3TC therapy. These would produce savings between €653 and €4,797 per patient per year depending on baseline triple ART. Implementation of the main optimisation strategies recommended in the GeSIDA/PNS (2015) Consensus into Spanish clinical practice would lead to considerable savings, especially those based in dual therapy with ATV/r+3TC, thus contributing to the control of pharmaceutical expenditure and NHS sustainability. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

Optimisation of confinement in a fusion reactor using a nonlinear turbulence model

NASA Astrophysics Data System (ADS)

Highcock, E. G.; Mandell, N. R.; Barnes, M.

2018-04-01

The confinement of heat in the core of a magnetic fusion reactor is optimised using a multidimensional optimisation algorithm. For the first time in such a study, the loss of heat due to turbulence is modelled at every stage using first-principles nonlinear simulations which accurately capture the turbulent cascade and large-scale zonal flows. The simulations utilise a novel approach, with gyrofluid treatment of the small-scale drift waves and gyrokinetic treatment of the large-scale zonal flows. A simple near-circular equilibrium with standard parameters is chosen as the initial condition. The figure of merit, fusion power per unit volume, is calculated, and then two control parameters, the elongation and triangularity of the outer flux surface, are varied, with the algorithm seeking to optimise the chosen figure of merit. A twofold increase in the plasma power per unit volume is achieved by moving to higher elongation and strongly negative triangularity.

Prediction of road traffic death rate using neural networks optimised by genetic algorithm.

PubMed

Jafari, Seyed Ali; Jahandideh, Sepideh; Jahandideh, Mina; Asadabadi, Ebrahim Barzegari

2015-01-01

Road traffic injuries (RTIs) are realised as a main cause of public health problems at global, regional and national levels. Therefore, prediction of road traffic death rate will be helpful in its management. Based on this fact, we used an artificial neural network model optimised through Genetic algorithm to predict mortality. In this study, a five-fold cross-validation procedure on a data set containing total of 178 countries was used to verify the performance of models. The best-fit model was selected according to the root mean square errors (RMSE). Genetic algorithm, as a powerful model which has not been introduced in prediction of mortality to this extent in previous studies, showed high performance. The lowest RMSE obtained was 0.0808. Such satisfactory results could be attributed to the use of Genetic algorithm as a powerful optimiser which selects the best input feature set to be fed into the neural networks. Seven factors have been known as the most effective factors on the road traffic mortality rate by high accuracy. The gained results displayed that our model is very promising and may play a useful role in developing a better method for assessing the influence of road traffic mortality risk factors.

Optimisation study of a vehicle bumper subsystem with fuzzy parameters

NASA Astrophysics Data System (ADS)

Farkas, L.; Moens, D.; Donders, S.; Vandepitte, D.

2012-10-01

This paper deals with the design and optimisation for crashworthiness of a vehicle bumper subsystem, which is a key scenario for vehicle component design. The automotive manufacturers and suppliers have to find optimal design solutions for such subsystems that comply with the conflicting requirements of the regulatory bodies regarding functional performance (safety and repairability) and regarding the environmental impact (mass). For the bumper design challenge, an integrated methodology for multi-attribute design engineering of mechanical structures is set up. The integrated process captures the various tasks that are usually performed manually, this way facilitating the automated design iterations for optimisation. Subsequently, an optimisation process is applied that takes the effect of parametric uncertainties into account, such that the system level of failure possibility is acceptable. This optimisation process is referred to as possibility-based design optimisation and integrates the fuzzy FE analysis applied for the uncertainty treatment in crash simulations. This process is the counterpart of the reliability-based design optimisation used in a probabilistic context with statistically defined parameters (variabilities).

Predicting emergency coronary artery bypass graft following PCI: application of a computational model to refer patients to hospitals with and without onsite surgical backup

PubMed Central

Syed, Zeeshan; Moscucci, Mauro; Share, David; Gurm, Hitinder S

2015-01-01

Background Clinical tools to stratify patients for emergency coronary artery bypass graft (ECABG) after percutaneous coronary intervention (PCI) create the opportunity to selectively assign patients undergoing procedures to hospitals with and without onsite surgical facilities for dealing with potential complications while balancing load across providers. The goal of our study was to investigate the feasibility of a computational model directly optimised for cohort-level performance to predict ECABG in PCI patients for this application. Methods Blue Cross Blue Shield of Michigan Cardiovascular Consortium registry data with 69 pre-procedural and angiographic risk variables from 68 022 PCI procedures in 2004–2007 were used to develop a support vector machine (SVM) model for ECABG. The SVM model was optimised for the area under the receiver operating characteristic curve (AUROC) at the level of the training cohort and validated on 42 310 PCI procedures performed in 2008–2009. Results There were 87 cases of ECABG (0.21%) in the validation cohort. The SVM model achieved an AUROC of 0.81 (95% CI 0.76 to 0.86). Patients in the predicted top decile were at a significantly increased risk relative to the remaining patients (OR 9.74, 95% CI 6.39 to 14.85, p<0.001) for ECABG. The SVM model optimised for the AUROC on the training cohort significantly improved discrimination, net reclassification and calibration over logistic regression and traditional SVM classification optimised for univariate performance. Conclusions Computational risk stratification directly optimising cohort-level performance holds the potential of high levels of discrimination for ECABG following PCI. This approach has value in selectively referring PCI patients to hospitals with and without onsite surgery. PMID:26688738

Terminal spacecraft rendezvous and capture with LASSO model predictive control

NASA Astrophysics Data System (ADS)

Hartley, Edward N.; Gallieri, Marco; Maciejowski, Jan M.

2013-11-01

The recently investigated ℓasso model predictive control (MPC) is applied to the terminal phase of a spacecraft rendezvous and capture mission. The interaction between the cost function and the treatment of minimum impulse bit is also investigated. The propellant consumption with ℓasso MPC for the considered scenario is noticeably less than with a conventional quadratic cost and control actions are sparser in time. Propellant consumption and sparsity are competitive with those achieved using a zone-based ℓ1 cost function, whilst requiring fewer decision variables in the optimisation problem than the latter. The ℓasso MPC is demonstrated to meet tighter specifications on control precision and also avoids the risk of undesirable behaviours often associated with pure ℓ1 stage costs.

Optimization of upcyte® human hepatocytes for the in vitro micronucleus assay.

PubMed

Nörenberg, Astrid; Heinz, Stefan; Scheller, Katharina; Hewitt, Nicola J; Braspenning, Joris; Ott, Michael

2013-12-12

"Upcyte(®) human hepatocytes" have the unique property of combining proliferation with the expression of drug metabolising activities. In our current study, we evaluated whether these cells would be suitable for early in vitro micronucleus (MN) tests. A treatment period of 96 h without a recovery period was most reliable for detecting MN formation in upcyte(®) hepatocytes from Donor 740. The basal MN rate in upcyte(®) hepatocytes varied considerably between donors (7-28%); therefore, modifications to the assay medium were tested to determine whether they could decrease inherent MN formation. Optimal medium supplements were 10 ng/ml oncostatin M for the pre-culture and recovery periods and 25 ng/ml epidermal growth factor and 10 ng/ml oncostatin M for the treatment period. Using the optimised conditions and outcome criteria, the upcyte(®) hepatocyte MN assay could correctly identify directly acting (e.g. mitomycin C, etoposide) and metabolically activated genotoxins (e.g. benzo[a]pyrene, cyclophosphamide). "True negative" and "false positive" compounds were also correctly identified as negative. The basal %MN in upcyte(®) hepatocytes from Donor 740 treated with DMSO, cyclophosphamide or MMC, was essentially unaffected by the growth stage ranging from population doublings of 14-61, suggesting that billions of cells could be produced from a single donor for standardised drug toxicity testing. In conclusion, we have established and optimised an in vitro MN test by using upcyte(®) hepatocytes to correctly identify known direct and metabolically activated genotoxicants as well as "false positives" and true negative compounds. The almost unlimited supply of cells from a single donor and optimised test conditions increase reproducibility in early and more predictive in vitro MN tests. Copyright © 2013 Elsevier B.V. All rights reserved.

Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation.

PubMed

Chisholm, Rebecca H; Lorenzi, Tommaso; Clairambault, Jean

2016-11-01

Drug-induced drug resistance in cancer has been attributed to diverse biological mechanisms at the individual cell or cell population scale, relying on stochastically or epigenetically varying expression of phenotypes at the single cell level, and on the adaptability of tumours at the cell population level. We focus on intra-tumour heterogeneity, namely between-cell variability within cancer cell populations, to account for drug resistance. To shed light on such heterogeneity, we review evolutionary mechanisms that encompass the great evolution that has designed multicellular organisms, as well as smaller windows of evolution on the time scale of human disease. We also present mathematical models used to predict drug resistance in cancer and optimal control methods that can circumvent it in combined therapeutic strategies. Plasticity in cancer cells, i.e., partial reversal to a stem-like status in individual cells and resulting adaptability of cancer cell populations, may be viewed as backward evolution making cancer cell populations resistant to drug insult. This reversible plasticity is captured by mathematical models that incorporate between-cell heterogeneity through continuous phenotypic variables. Such models have the benefit of being compatible with optimal control methods for the design of optimised therapeutic protocols involving combinations of cytotoxic and cytostatic treatments with epigenetic drugs and immunotherapies. Gathering knowledge from cancer and evolutionary biology with physiologically based mathematical models of cell population dynamics should provide oncologists with a rationale to design optimised therapeutic strategies to circumvent drug resistance, that still remains a major pitfall of cancer therapeutics. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. Copyright © 2016 Elsevier B.V. All rights reserved.

A new early cognitive screening measure to detect cognitive side-effects of electroconvulsive therapy?

PubMed

Martin, Donel M; Katalinic, Natalie; Ingram, Anna; Schweitzer, Isaac; Smith, Deidre J; Hadzi-Pavlovic, Dusan; Loo, Colleen K

2013-12-01

Cognitive side-effects from electroconvulsive therapy (ECT) can be distressing for patients and early detection may have an important role in guiding treatment decisions over the ECT course. This prospective study examined the utility of an early cognitive screening battery for predicting cognitive side-effects which develop later in the ECT course. The screening battery, together with the Mini Mental Status Examination (MMSE), was administered to 123 patients at baseline and after 3 ECT treatments. A more detailed cognitive battery was administered at baseline, after six treatments (post ECT 6) and after the last ECT treatment (post treatment) to assess cognitive side-effects across several domains: global cognition, anterograde memory, executive function, speed and concentration, and retrograde memory. Multivariate analyses examined the predictive utility of change on items from the screening battery for later cognitive changes at post ECT 6 and post treatment. Results showed that changes on a combination of items from the screening battery were predictive of later cognitive changes at post treatment, particularly for anterograde memory (p < 0.01), after controlling for patient and treatment factors. Change on the MMSE predicted cognitive changes at post ECT 6 but not at post treatment. A scoring method for the new screening battery was tested for discriminative ability in a sub-sample of patients. This study provides preliminary evidence that a simple and easy-to-administer measure may potentially be used to help guide clinical treatment decisions to optimise efficacy and cognitive outcomes. Further development of this measure and validation in a more representative ECT clinical population is required. Copyright © 2013 Elsevier Ltd. All rights reserved.

A simulation and optimisation procedure to model daily suppression resource transfers during a fire season in Colorado

Treesearch

Yu Wei; Erin J. Belval; Matthew P. Thompson; Dave E. Calkin; Crystal S. Stonesifer

2016-01-01

Sharing fire engines and crews between fire suppression dispatch zones may help improve the utilisation of fire suppression resources. Using the Resource Ordering and Status System, the Predictive Services’ Fire Potential Outlooks and the Rocky Mountain Region Preparedness Levels from 2010 to 2013, we tested a simulation and optimisation procedure to transfer crews and...

A comparison of optimisation methods and knee joint degrees of freedom on muscle force predictions during single-leg hop landings.

PubMed

Mokhtarzadeh, Hossein; Perraton, Luke; Fok, Laurence; Muñoz, Mario A; Clark, Ross; Pivonka, Peter; Bryant, Adam L

2014-09-22

The aim of this paper was to compare the effect of different optimisation methods and different knee joint degrees of freedom (DOF) on muscle force predictions during a single legged hop. Nineteen subjects performed single-legged hopping manoeuvres and subject-specific musculoskeletal models were developed to predict muscle forces during the movement. Muscle forces were predicted using static optimisation (SO) and computed muscle control (CMC) methods using either 1 or 3 DOF knee joint models. All sagittal and transverse plane joint angles calculated using inverse kinematics or CMC in a 1 DOF or 3 DOF knee were well-matched (RMS error<3°). Biarticular muscles (hamstrings, rectus femoris and gastrocnemius) showed more differences in muscle force profiles when comparing between the different muscle prediction approaches where these muscles showed larger time delays for many of the comparisons. The muscle force magnitudes of vasti, gluteus maximus and gluteus medius were not greatly influenced by the choice of muscle force prediction method with low normalised root mean squared errors (<48%) observed in most comparisons. We conclude that SO and CMC can be used to predict lower-limb muscle co-contraction during hopping movements. However, care must be taken in interpreting the magnitude of force predicted in the biarticular muscles and the soleus, especially when using a 1 DOF knee. Despite this limitation, given that SO is a more robust and computationally efficient method for predicting muscle forces than CMC, we suggest that SO can be used in conjunction with musculoskeletal models that have a 1 or 3 DOF knee joint to study the relative differences and the role of muscles during hopping activities in future studies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Fast and fuzzy multi-objective radiotherapy treatment plan generation for head and neck cancer patients with the lexicographic reference point method (LRPM)

NASA Astrophysics Data System (ADS)

van Haveren, Rens; Ogryczak, Włodzimierz; Verduijn, Gerda M.; Keijzer, Marleen; Heijmen, Ben J. M.; Breedveld, Sebastiaan

2017-06-01

Previously, we have proposed Erasmus-iCycle, an algorithm for fully automated IMRT plan generation based on prioritised (lexicographic) multi-objective optimisation with the 2-phase ɛ-constraint (2pɛc) method. For each patient, the output of Erasmus-iCycle is a clinically favourable, Pareto optimal plan. The 2pɛc method uses a list of objective functions that are consecutively optimised, following a strict, user-defined prioritisation. The novel lexicographic reference point method (LRPM) is capable of solving multi-objective problems in a single optimisation, using a fuzzy prioritisation of the objectives. Trade-offs are made globally, aiming for large favourable gains for lower prioritised objectives at the cost of only slight degradations for higher prioritised objectives, or vice versa. In this study, the LRPM is validated for 15 head and neck cancer patients receiving bilateral neck irradiation. The generated plans using the LRPM are compared with the plans resulting from the 2pɛc method. Both methods were capable of automatically generating clinically relevant treatment plans for all patients. For some patients, the LRPM allowed large favourable gains in some treatment plan objectives at the cost of only small degradations for the others. Moreover, because of the applied single optimisation instead of multiple optimisations, the LRPM reduced the average computation time from 209.2 to 9.5 min, a speed-up factor of 22 relative to the 2pɛc method.

The role of predictive uncertainty in the operational management of reservoirs

NASA Astrophysics Data System (ADS)

Todini, E.

2014-09-01

The present work deals with the operational management of multi-purpose reservoirs, whose optimisation-based rules are derived, in the planning phase, via deterministic (linear and nonlinear programming, dynamic programming, etc.) or via stochastic (generally stochastic dynamic programming) approaches. In operation, the resulting deterministic or stochastic optimised operating rules are then triggered based on inflow predictions. In order to fully benefit from predictions, one must avoid using them as direct inputs to the reservoirs, but rather assess the "predictive knowledge" in terms of a predictive probability density to be operationally used in the decision making process for the estimation of expected benefits and/or expected losses. Using a theoretical and extremely simplified case, it will be shown why directly using model forecasts instead of the full predictive density leads to less robust reservoir management decisions. Moreover, the effectiveness and the tangible benefits for using the entire predictive probability density instead of the model predicted values will be demonstrated on the basis of the Lake Como management system, operational since 1997, as well as on the basis of a case study on the lake of Aswan.

The robust model predictive control based on mixed H2/H∞ approach with separated performance formulations and its ISpS analysis

NASA Astrophysics Data System (ADS)

Li, Dewei; Li, Jiwei; Xi, Yugeng; Gao, Furong

2017-12-01

In practical applications, systems are always influenced by parameter uncertainties and external disturbance. Both the H2 performance and the H∞ performance are important for the real applications. For a constrained system, the previous designs of mixed H2/H∞ robust model predictive control (RMPC) optimise one performance with the other performance requirement as a constraint. But the two performances cannot be optimised at the same time. In this paper, an improved design of mixed H2/H∞ RMPC for polytopic uncertain systems with external disturbances is proposed to optimise them simultaneously. In the proposed design, the original uncertain system is decomposed into two subsystems by the additive character of linear systems. Two different Lyapunov functions are used to separately formulate the two performance indices for the two subsystems. Then, the proposed RMPC is designed to optimise both the two performances by the weighting method with the satisfaction of the H∞ performance requirement. Meanwhile, to make the design more practical, a simplified design is also developed. The recursive feasible conditions of the proposed RMPC are discussed and the closed-loop input state practical stable is proven. The numerical examples reflect the enlarged feasible region and the improved performance of the proposed design.

Crystal structure optimisation using an auxiliary equation of state

NASA Astrophysics Data System (ADS)

Jackson, Adam J.; Skelton, Jonathan M.; Hendon, Christopher H.; Butler, Keith T.; Walsh, Aron

2015-11-01

Standard procedures for local crystal-structure optimisation involve numerous energy and force calculations. It is common to calculate an energy-volume curve, fitting an equation of state around the equilibrium cell volume. This is a computationally intensive process, in particular, for low-symmetry crystal structures where each isochoric optimisation involves energy minimisation over many degrees of freedom. Such procedures can be prohibitive for non-local exchange-correlation functionals or other "beyond" density functional theory electronic structure techniques, particularly where analytical gradients are not available. We present a simple approach for efficient optimisation of crystal structures based on a known equation of state. The equilibrium volume can be predicted from one single-point calculation and refined with successive calculations if required. The approach is validated for PbS, PbTe, ZnS, and ZnTe using nine density functionals and applied to the quaternary semiconductor Cu2ZnSnS4 and the magnetic metal-organic framework HKUST-1.

International Study to Predict Optimized Treatment for Depression (iSPOT-D), a randomized clinical trial: rationale and protocol.

PubMed

Williams, Leanne M; Rush, A John; Koslow, Stephen H; Wisniewski, Stephen R; Cooper, Nicholas J; Nemeroff, Charles B; Schatzberg, Alan F; Gordon, Evian

2011-01-05

Clinically useful treatment moderators of Major Depressive Disorder (MDD) have not yet been identified, though some baseline predictors of treatment outcome have been proposed. The aim of iSPOT-D is to identify pretreatment measures that predict or moderate MDD treatment response or remission to escitalopram, sertraline or venlafaxine; and develop a model that incorporates multiple predictors and moderators. The International Study to Predict Optimized Treatment - in Depression (iSPOT-D) is a multi-centre, international, randomized, prospective, open-label trial. It is enrolling 2016 MDD outpatients (ages 18-65) from primary or specialty care practices (672 per treatment arm; 672 age-, sex- and education-matched healthy controls). Study-eligible patients are antidepressant medication (ADM) naïve or willing to undergo a one-week wash-out of any non-protocol ADM, and cannot have had an inadequate response to protocol ADM. Baseline assessments include symptoms; distress; daily function; cognitive performance; electroencephalogram and event-related potentials; heart rate and genetic measures. A subset of these baseline assessments are repeated after eight weeks of treatment. Outcomes include the 17-item Hamilton Rating Scale for Depression (primary) and self-reported depressive symptoms, social functioning, quality of life, emotional regulation, and side-effect burden (secondary). Participants may then enter a naturalistic telephone follow-up at weeks 12, 16, 24 and 52. The first half of the sample will be used to identify potential predictors and moderators, and the second half to replicate and confirm. First enrolment was in December 2008, and is ongoing. iSPOT-D evaluates clinical and biological predictors of treatment response in the largest known sample of MDD collected worldwide. International Study to Predict Optimised Treatment - in Depression (iSPOT-D) ClinicalTrials.gov Identifier: NCT00693849. URL: http://clinicaltrials.gov/ct2/show/NCT00693849?term=International+Study+to+Predict+Optimized+Treatment+for+Depression&rank=1

Systematic review: predicting and optimising response to anti-TNF therapy in Crohn's disease - algorithm for practical management.

PubMed

Ding, N S; Hart, A; De Cruz, P

2016-01-01

Nonresponse and loss of response to anti-TNF therapies in Crohn's disease represent significant clinical problems for which clear management guidelines are lacking. To review the incidence, mechanisms and predictors of primary nonresponse and secondary loss of response to formulate practical clinical algorithms to guide management. Through a systematic literature review, 503 articles were identified which fit the inclusion criteria. Primary nonresponse to anti-TNF treatment affects 13-40% of patients. Secondary loss of response to anti-TNF occurs in 23-46% of patients when determined according to dose intensification, and 5-13% of patients when gauged by drug discontinuation rates. Recent evidence suggests that the mechanisms underlying primary nonresponse and secondary loss of response are multifactorial and include disease characteristics (phenotype, location, severity); drug (pharmacokinetic, pharmacodynamic or immunogenicity) and treatment strategy (dosing regimen) related factors. Clinical algorithms that employ therapeutic drug monitoring (using anti-TNF tough levels and anti-drug antibody levels) may be used to determine the underlying cause of primary nonresponse and secondary loss of response respectively and guide clinicians as to which patients are most likely to respond to anti-TNF therapy and help optimise drug therapy for those who are losing response to anti-TNF therapy. Nonresponse or loss of response to anti-TNF occurs commonly in Crohn's disease. Clinical algorithms utilising therapeutic drug monitoring may establish the mechanisms for treatment failure and help guide the subsequent therapeutic approach. © 2015 John Wiley & Sons Ltd.

Total knee replacement plus physical and medical therapy or treatment with physical and medical therapy alone: a randomised controlled trial in patients with knee osteoarthritis (the MEDIC-study).

PubMed

Skou, Soren T; Roos, Ewa M; Laursen, Mogens B; Rathleff, Michael S; Arendt-Nielsen, Lars; Simonsen, Ole H; Rasmussen, Sten

2012-05-09

There is a lack of high quality evidence concerning the efficacy of total knee arthroplasty (TKA). According to international evidence-based guidelines, treatment of knee osteoarthritis (KOA) should include patient education, exercise and weight loss. Insoles and pharmacological treatment can be included as supplementary treatments. If the combination of these non-surgical treatment modalities is ineffective, TKA may be indicated. The purpose of this randomised controlled trial is to examine whether TKA provides further improvement in pain, function and quality of life in addition to optimised non-surgical treatment in patients with KOA defined as definite radiographic OA and up to moderate pain. The study will be conducted in The North Denmark Region. 100 participants with radiographic KOA (K-L grade ≥2) and mean pain during the previous week of ≤ 60 mm (0-100, best to worst scale) who are considered eligible for TKA by an orthopaedic surgeon will be included. The treatment will consist of 12 weeks of optimised non-surgical treatment consisting of patient education, exercise, diet, insoles, analgesics and/or NSAIDs. Patients will be randomised to either receiving or not receiving a TKA in addition to the optimised non-surgical treatment. The primary outcome will be the change from baseline to 12 months on the Knee Injury and Osteoarthritis Outcome Score (KOOS)(4) defined as the average score for the subscale scores for pain, symptoms, activities of daily living, and quality of life. Secondary outcomes include the five individual KOOS subscale scores, EQ-5D, pain on a 100 mm Visual Analogue Scale, self-efficacy, pain pressure thresholds, and isometric knee flexion and knee extension strength. This is the first randomised controlled trial to investigate the efficacy of TKA as an adjunct treatment to optimised non-surgical treatment in patients with KOA. The results will significantly contribute to evidence-based recommendations for the treatment of patients with KOA. Clinicaltrials.gov reference: NCT01410409.

Total knee replacement plus physical and medical therapy or treatment with physical and medical therapy alone: a randomised controlled trial in patients with knee osteoarthritis (the MEDIC-study)

PubMed Central

2012-01-01

Background There is a lack of high quality evidence concerning the efficacy of total knee arthroplasty (TKA). According to international evidence-based guidelines, treatment of knee osteoarthritis (KOA) should include patient education, exercise and weight loss. Insoles and pharmacological treatment can be included as supplementary treatments. If the combination of these non-surgical treatment modalities is ineffective, TKA may be indicated. The purpose of this randomised controlled trial is to examine whether TKA provides further improvement in pain, function and quality of life in addition to optimised non-surgical treatment in patients with KOA defined as definite radiographic OA and up to moderate pain. Methods/Design The study will be conducted in The North Denmark Region. 100 participants with radiographic KOA (K-L grade ≥2) and mean pain during the previous week of ≤ 60 mm (0–100, best to worst scale) who are considered eligible for TKA by an orthopaedic surgeon will be included. The treatment will consist of 12 weeks of optimised non-surgical treatment consisting of patient education, exercise, diet, insoles, analgesics and/or NSAIDs. Patients will be randomised to either receiving or not receiving a TKA in addition to the optimised non-surgical treatment. The primary outcome will be the change from baseline to 12 months on the Knee Injury and Osteoarthritis Outcome Score (KOOS)4 defined as the average score for the subscale scores for pain, symptoms, activities of daily living, and quality of life. Secondary outcomes include the five individual KOOS subscale scores, EQ-5D, pain on a 100 mm Visual Analogue Scale, self-efficacy, pain pressure thresholds, and isometric knee flexion and knee extension strength. Discussion This is the first randomised controlled trial to investigate the efficacy of TKA as an adjunct treatment to optimised non-surgical treatment in patients with KOA. The results will significantly contribute to evidence-based recommendations for the treatment of patients with KOA. Trial registration Clinicaltrials.gov reference: NCT01410409 PMID:22571284

Multi-objective optimisation of wastewater treatment plant control to reduce greenhouse gas emissions.

PubMed

Sweetapple, Christine; Fu, Guangtao; Butler, David

2014-05-15

This study investigates the potential of control strategy optimisation for the reduction of operational greenhouse gas emissions from wastewater treatment in a cost-effective manner, and demonstrates that significant improvements can be realised. A multi-objective evolutionary algorithm, NSGA-II, is used to derive sets of Pareto optimal operational and control parameter values for an activated sludge wastewater treatment plant, with objectives including minimisation of greenhouse gas emissions, operational costs and effluent pollutant concentrations, subject to legislative compliance. Different problem formulations are explored, to identify the most effective approach to emissions reduction, and the sets of optimal solutions enable identification of trade-offs between conflicting objectives. It is found that multi-objective optimisation can facilitate a significant reduction in greenhouse gas emissions without the need for plant redesign or modification of the control strategy layout, but there are trade-offs to consider: most importantly, if operational costs are not to be increased, reduction of greenhouse gas emissions is likely to incur an increase in effluent ammonia and total nitrogen concentrations. Design of control strategies for a high effluent quality and low costs alone is likely to result in an inadvertent increase in greenhouse gas emissions, so it is of key importance that effects on emissions are considered in control strategy development and optimisation. Copyright © 2014 Elsevier Ltd. All rights reserved.

One-year results of the use of endovenous radiofrequency ablation utilising an optimised radiofrequency-induced thermotherapy protocol for the treatment of truncal superficial venous reflux.

PubMed

Badham, George E; Dos Santos, Scott J; Lloyd, Lucinda Ba; Holdstock, Judy M; Whiteley, Mark S

2018-06-01

Background In previous in vitro and ex vivo studies, we have shown increased thermal spread can be achieved with radiofrequency-induced thermotherapy when using a low power and slower, discontinuous pullback. We aimed to determine the clinical success rate of radiofrequency-induced thermotherapy using this optimised protocol for the treatment of superficial venous reflux in truncal veins. Methods Sixty-three patients were treated with radiofrequency-induced thermotherapy using the optimised protocol and were followed up after one year (mean 16.3 months). Thirty-five patients returned for audit, giving a response rate of 56%. Duplex ultrasonography was employed to check for truncal reflux and compared to initial scans. Results In the 35 patients studied, there were 48 legs, with 64 truncal veins treated by radiofrequency-induced thermotherapy (34 great saphenous, 15 small saphenous and 15 anterior accessory saphenous veins). One year post-treatment, complete closure of all previously refluxing truncal veins was demonstrated on ultrasound, giving a success rate of 100%. Conclusions Using a previously reported optimised, low power/slow pullback radiofrequency-induced thermotherapy protocol, we have shown it is possible to achieve a 100% ablation at one year. This compares favourably with results reported at one year post-procedure using the high power/fast pullback protocols that are currently recommended for this device.

Erectile dysfunction in patients with cardiovascular disease

PubMed Central

Ophuis, A.J.M. Oude; Nijeholt, A.A.B. Lycklama à

2006-01-01

Erectile dysfunction is a highly prevalent disease, especially in cardiovascular-compromised men. Many of the well-established risk factors for cardiovascular disease are also risk factors for erectile dysfunction. A correlation between erectile dysfunction and endothelial dysfunction is well established. It is postulated that erectile dysfunction with an arteriovascular aetiology can predate and be an indicator of potential coronary artery disease. In this paper we will attempt to increase awareness among cardiologists for the predictive value of erectile dysfunction for future cardiovascular disease in order to optimise cardiovascular risk management. The treatment of erectile dysfunction and cardiovascular interactions is also discussed in detail. ImagesFigure 1AFigure 1B PMID:25696612

Optimisation of the supercritical extraction of toxic elements in fish oil.

PubMed

Hajeb, P; Jinap, S; Shakibazadeh, Sh; Afsah-Hejri, L; Mohebbi, G H; Zaidul, I S M

2014-01-01

This study aims to optimise the operating conditions for the supercritical fluid extraction (SFE) of toxic elements from fish oil. The SFE operating parameters of pressure, temperature, CO2 flow rate and extraction time were optimised using a central composite design (CCD) of response surface methodology (RSM). High coefficients of determination (R²) (0.897-0.988) for the predicted response surface models confirmed a satisfactory adjustment of the polynomial regression models with the operation conditions. The results showed that the linear and quadratic terms of pressure and temperature were the most significant (p < 0.05) variables affecting the overall responses. The optimum conditions for the simultaneous elimination of toxic elements comprised a pressure of 61 MPa, a temperature of 39.8ºC, a CO₂ flow rate of 3.7 ml min⁻¹ and an extraction time of 4 h. These optimised SFE conditions were able to produce fish oil with the contents of lead, cadmium, arsenic and mercury reduced by up to 98.3%, 96.1%, 94.9% and 93.7%, respectively. The fish oil extracted under the optimised SFE operating conditions was of good quality in terms of its fatty acid constituents.

Optimisation of synergistic biomass-degrading enzyme systems for efficient rice straw hydrolysis using an experimental mixture design.

PubMed

Suwannarangsee, Surisa; Bunterngsook, Benjarat; Arnthong, Jantima; Paemanee, Atchara; Thamchaipenet, Arinthip; Eurwilaichitr, Lily; Laosiripojana, Navadol; Champreda, Verawat

2012-09-01

Synergistic enzyme system for the hydrolysis of alkali-pretreated rice straw was optimised based on the synergy of crude fungal enzyme extracts with a commercial cellulase (Celluclast™). Among 13 enzyme extracts, the enzyme preparation from Aspergillus aculeatus BCC 199 exhibited the highest level of synergy with Celluclast™. This synergy was based on the complementary cellulolytic and hemicellulolytic activities of the BCC 199 enzyme extract. A mixture design was used to optimise the ternary enzyme complex based on the synergistic enzyme mixture with Bacillus subtilis expansin. Using the full cubic model, the optimal formulation of the enzyme mixture was predicted to the percentage of Celluclast™: BCC 199: expansin=41.4:37.0:21.6, which produced 769 mg reducing sugar/g biomass using 2.82 FPU/g enzymes. This work demonstrated the use of a systematic approach for the design and optimisation of a synergistic enzyme mixture of fungal enzymes and expansin for lignocellulosic degradation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Towards optimised information about clinical trials; identification and validation of key issues in collaboration with cancer patient advocates.

PubMed

Dellson, P; Nilbert, M; Bendahl, P-O; Malmström, P; Carlsson, C

2011-07-01

Clinical trials are crucial to improve cancer treatment but recruitment is difficult. Optimised patient information has been recognised as a key issue. In line with the increasing focus on patients' perspectives in health care, we aimed to study patients' opinions about the written information used in three clinical trials for breast cancer. Primary data collection was done in focus group interviews with breast cancer patient advocates. Content analysis identified three major themes: comprehensibility, emotions and associations, and decision making. Based on the advocates' suggestions for improvements, 21 key issues were defined and validated through a questionnaire in an independent group of breast cancer patient advocates. Clear messages, emotionally neutral expressions, careful descriptions of side effects, clear comparisons between different treatment alternatives and information about the possibility to discontinue treatment were perceived as the most important issues. Patients' views of the information in clinical trials provide new insights and identify key issues to consider in optimising future written information and may improve recruitment to clinical cancer trials. © 2010 Blackwell Publishing Ltd.

Treatment planning optimisation in proton therapy

PubMed Central

McGowan, S E; Burnet, N G; Lomax, A J

2013-01-01

ABSTRACT. The goal of radiotherapy is to achieve uniform target coverage while sparing normal tissue. In proton therapy, the same sources of geometric uncertainty are present as in conventional radiotherapy. However, an important and fundamental difference in proton therapy is that protons have a finite range, highly dependent on the electron density of the material they are traversing, resulting in a steep dose gradient at the distal edge of the Bragg peak. Therefore, an accurate knowledge of the sources and magnitudes of the uncertainties affecting the proton range is essential for producing plans which are robust to these uncertainties. This review describes the current knowledge of the geometric uncertainties and discusses their impact on proton dose plans. The need for patient-specific validation is essential and in cases of complex intensity-modulated proton therapy plans the use of a planning target volume (PTV) may fail to ensure coverage of the target. In cases where a PTV cannot be used, other methods of quantifying plan quality have been investigated. A promising option is to incorporate uncertainties directly into the optimisation algorithm. A further development is the inclusion of robustness into a multicriteria optimisation framework, allowing a multi-objective Pareto optimisation function to balance robustness and conformity. The question remains as to whether adaptive therapy can become an integral part of a proton therapy, to allow re-optimisation during the course of a patient's treatment. The challenge of ensuring that plans are robust to range uncertainties in proton therapy remains, although these methods can provide practical solutions. PMID:23255545

Hepatitis C virus treatment in the real world: optimising treatment and access to therapies

PubMed Central

Zoulim, Fabien; Liang, T Jake; Gerbes, Alexander L; Aghemo, Alessio; Deuffic-Burban, Sylvie; Dusheiko, Geoffrey; Fried, Michael W; Pol, Stanislas; Rockstroh, Jürgen Kurt; Terrault, Norah A; Wiktor, Stefan

2018-01-01

Chronic HCV infections represent a major worldwide public health problem and are responsible for a large proportion of liver related deaths, mostly because of HCV-associated hepatocellular carcinoma and cirrhosis. The treatment of HCV has undergone a rapid and spectacular revolution. In the past 5 years, the launch of direct acting antiviral drugs has seen sustained virological response rates reach 90% and above for many patient groups. The new treatments are effective, well tolerated, allow for shorter treatment regimens and offer new opportunities for previously excluded groups. This therapeutic revolution has changed the rules for treatment of HCV, moving the field towards an interferon-free era and raising the prospect of HCV eradication. This manuscript addresses the new challenges regarding treatment optimisation in the real world, improvement of antiviral efficacy in ‘hard-to-treat’ groups, the management of patients whose direct acting antiviral drug treatment was unsuccessful, and access to diagnosis and treatment in different parts of the world. PMID:26449729

Choosing the appropriate forecasting model for predictive parameter control.

PubMed

Aleti, Aldeida; Moser, Irene; Meedeniya, Indika; Grunske, Lars

2014-01-01

All commonly used stochastic optimisation algorithms have to be parameterised to perform effectively. Adaptive parameter control (APC) is an effective method used for this purpose. APC repeatedly adjusts parameter values during the optimisation process for optimal algorithm performance. The assignment of parameter values for a given iteration is based on previously measured performance. In recent research, time series prediction has been proposed as a method of projecting the probabilities to use for parameter value selection. In this work, we examine the suitability of a variety of prediction methods for the projection of future parameter performance based on previous data. All considered prediction methods have assumptions the time series data has to conform to for the prediction method to provide accurate projections. Looking specifically at parameters of evolutionary algorithms (EAs), we find that all standard EA parameters with the exception of population size conform largely to the assumptions made by the considered prediction methods. Evaluating the performance of these prediction methods, we find that linear regression provides the best results by a very small and statistically insignificant margin. Regardless of the prediction method, predictive parameter control outperforms state of the art parameter control methods when the performance data adheres to the assumptions made by the prediction method. When a parameter's performance data does not adhere to the assumptions made by the forecasting method, the use of prediction does not have a notable adverse impact on the algorithm's performance.

A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers.

PubMed

Fogliata, Antonella; Nicolini, Giorgia; Clivio, Alessandro; Vanetti, Eugenio; Laksar, Sarbani; Tozzi, Angelo; Scorsetti, Marta; Cozzi, Luca

2015-10-31

To evaluate the performance of a broad scope model-based optimisation process for volumetric modulated arc therapy applied to esophageal cancer. A set of 70 previously treated patients in two different institutions, were selected to train a model for the prediction of dose-volume constraints. The model was built with a broad-scope purpose, aiming to be effective for different dose prescriptions and tumour localisations. It was validated on three groups of patients from the same institution and from another clinic not providing patients for the training phase. Comparison of the automated plans was done against reference cases given by the clinically accepted plans. Quantitative improvements (statistically significant for the majority of the analysed dose-volume parameters) were observed between the benchmark and the test plans. Of 624 dose-volume objectives assessed for plan evaluation, in 21 cases (3.3 %) the reference plans failed to respect the constraints while the model-based plans succeeded. Only in 3 cases (<0.5 %) the reference plans passed the criteria while the model-based failed. In 5.3 % of the cases both groups of plans failed and in the remaining cases both passed the tests. Plans were optimised using a broad scope knowledge-based model to determine the dose-volume constraints. The results showed dosimetric improvements when compared to the benchmark data. Particularly the plans optimised for patients from the third centre, not participating to the training, resulted in superior quality. The data suggests that the new engine is reliable and could encourage its application to clinical practice.

Optimising the Encapsulation of an Aqueous Bitter Melon Extract by Spray-Drying

PubMed Central

Tan, Sing Pei; Kha, Tuyen Chan; Parks, Sophie; Stathopoulos, Costas; Roach, Paul D.

2015-01-01

Our aim was to optimise the encapsulation of an aqueous bitter melon extract by spray-drying with maltodextrin (MD) and gum Arabic (GA). The response surface methodology models accurately predicted the process yield and retentions of bioactive concentrations and activity (R2 > 0.87). The optimal formulation was predicted and validated as 35% (w/w) stock solution (MD:GA, 1:1) and a ratio of 1.5:1 g/g of the extract to the stock solution. The spray-dried powder had a high process yield (66.2% ± 9.4%) and high retention (>79.5% ± 8.4%) and the quality of the powder was high. Therefore, the bitter melon extract was well encapsulated into a powder using MD/GA and spray-drying. PMID:28231214

Robust distributed model predictive control of linear systems with structured time-varying uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Langwen; Xie, Wei; Wang, Jingcheng

2017-11-01

In this work, synthesis of robust distributed model predictive control (MPC) is presented for a class of linear systems subject to structured time-varying uncertainties. By decomposing a global system into smaller dimensional subsystems, a set of distributed MPC controllers, instead of a centralised controller, are designed. To ensure the robust stability of the closed-loop system with respect to model uncertainties, distributed state feedback laws are obtained by solving a min-max optimisation problem. The design of robust distributed MPC is then transformed into solving a minimisation optimisation problem with linear matrix inequality constraints. An iterative online algorithm with adjustable maximum iteration is proposed to coordinate the distributed controllers to achieve a global performance. The simulation results show the effectiveness of the proposed robust distributed MPC algorithm.

Physiologically-Based Pharmacokinetic Modelling to Inform Development of Intramuscular Long Acting Nanoformulations for HIV

PubMed Central

Rajoli, Rajith KR; Back, David J; Rannard, Steve; Meyers, Caren Freel; Flexner, Charles; Owen, Andrew; Siccardi, Marco

2014-01-01

Background and Objectives Antiretrovirals (ARVs) are currently used for the treatment and prevention of HIV infection. Poor adherence and low tolerability of some existing oral formulations can hinder their efficacy. Long-acting (LA) injectable nanoformulations could help address these complications by simplifying ARV administration. The aim of this study is to inform the optimisation of intramuscular LA formulations for eight ARVs through physiologically-based pharmacokinetic (PBPK) modelling. Methods A whole-body PBPK model was constructed using mathematical descriptions of molecular, physiological and anatomical processes defining pharmacokinetics. These models were validated against available clinical data and subsequently used to predict the pharmacokinetics of injectable LA formulations Results The predictions suggest that monthly intramuscular injections are possible for dolutegravir, efavirenz, emtricitabine, raltegravir, rilpivirine and tenofovir provided that technological challenges to control release rate can be addressed. Conclusions These data may help inform the target product profiles for LA ARV reformulation strategies. PMID:25523214

Optimisation of industrial wastes reuse as construction materials.

PubMed

Collivignarelli, C; Sorlini, S

2001-12-01

This study concerns the reuse of two inorganic wastes, foundry residues and fly ashes from municipal solid waste incineration, as "recycled aggregate" in concrete production. This kind of reuse was optimised by waste treatment with the following steps: waste washing with water; waste stabilisation-solidification treatment with inorganic reagents; final grinding of the stabilised waste after curing for about 10-20 days. Both the treated wastes were reused in concrete production with different mix-designs. Concrete specimens were characterised by means of conventional physical-mechanical tests (compression, elasticity modulus, shrinkage) and different leaching tests. Experimental results showed that a good structural and environmental quality of "recycled concrete" is due both to a correct waste treatment and to a correct mix-design for concrete mixture.

Cost optimisation and minimisation of the environmental impact through life cycle analysis of the waste water treatment plant of Bree (Belgium).

PubMed

De Gussem, K; Wambecq, T; Roels, J; Fenu, A; De Gueldre, G; Van De Steene, B

2011-01-01

An ASM2da model of the full-scale waste water plant of Bree (Belgium) has been made. It showed very good correlation with reference operational data. This basic model has been extended to include an accurate calculation of environmental footprint and operational costs (energy consumption, dosing of chemicals and sludge treatment). Two optimisation strategies were compared: lowest cost meeting the effluent consent versus lowest environmental footprint. Six optimisation scenarios have been studied, namely (i) implementation of an online control system based on ammonium and nitrate sensors, (ii) implementation of a control on MLSS concentration, (iii) evaluation of internal recirculation flow, (iv) oxygen set point, (v) installation of mixing in the aeration tank, and (vi) evaluation of nitrate setpoint for post denitrification. Both an environmental impact or Life Cycle Assessment (LCA) based approach for optimisation are able to significantly lower the cost and environmental footprint. However, the LCA approach has some advantages over cost minimisation of an existing full-scale plant. LCA tends to chose control settings that are more logic: it results in a safer operation of the plant with less risks regarding the consents. It results in a better effluent at a slightly increased cost.

Optimising design, operation and energy consumption of biological aerated filters (BAF) for nitrogen removal of municipal wastewater.

PubMed

Rother, E; Cornel, P

2004-01-01

The Biofiltration process in wastewater treatment combines filtration and biological processes in one reactor. In Europe it is meanwhile an accepted technology in advanced wastewater treatment, whenever space is scarce and a virtually suspended solids-free effluent is demanded. Although more than 500 plants are in operation world-wide there is still a lack of published operational experiences to help planners and operators to identify potentials for optimisation, e.g. energy consumption or the vulnerability against peakloads. Examples from pilot trials are given how the nitrification and denitrification can be optimised. Nitrification can be quickly increased by adjusting DO content of the water. Furthermore carrier materials like zeolites can store surplus ammonia during peak loads and release afterwards. Pre-denitrification in biofilters is normally limited by the amount of easily degradable organic substrate, resulting in relatively high requirements for external carbon. The combination of pre-DN, N and post-DN filters is much more advisable for most municipal wastewaters, because the recycle rate can be reduced and external carbon can be saved. Exemplarily it is shown for a full scale preanoxic-DN/N/postanoxic-DN plant of 130,000 p.e. how 15% energy could be saved by optimising internal recycling and some control strategies.

Warpage analysis on thin shell part using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Zulhasif, Z.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Hazwan, M. H. M.

2017-09-01

The optimisation of moulding parameters appropriate to reduce warpage defects produce using Autodesk Moldflow Insight (AMI) 2012 software The product is injected by using Acrylonitrile-Butadiene-Styrene (ABS) materials. This analysis has processing parameter that varies in melting temperature, mould temperature, packing pressure and packing time. Design of Experiments (DOE) has been integrated to obtain a polynomial model using Response Surface Methodology (RSM). The Glowworm Swarm Optimisation (GSO) method is used to predict a best combination parameters to minimise warpage defect in order to produce high quality parts.

Improving target coverage and organ-at-risk sparing in intensity-modulated radiotherapy for cervical oesophageal cancer using a simple optimisation method.

PubMed

Lu, Jia-Yang; Cheung, Michael Lok-Man; Huang, Bao-Tian; Wu, Li-Li; Xie, Wen-Jia; Chen, Zhi-Jian; Li, De-Rui; Xie, Liang-Xi

2015-01-01

To assess the performance of a simple optimisation method for improving target coverage and organ-at-risk (OAR) sparing in intensity-modulated radiotherapy (IMRT) for cervical oesophageal cancer. For 20 selected patients, clinically acceptable original IMRT plans (Original plans) were created, and two optimisation methods were adopted to improve the plans: 1) a base dose function (BDF)-based method, in which the treatment plans were re-optimised based on the original plans, and 2) a dose-controlling structure (DCS)-based method, in which the original plans were re-optimised by assigning additional constraints for hot and cold spots. The Original, BDF-based and DCS-based plans were compared with regard to target dose homogeneity, conformity, OAR sparing, planning time and monitor units (MUs). Dosimetric verifications were performed and delivery times were recorded for the BDF-based and DCS-based plans. The BDF-based plans provided significantly superior dose homogeneity and conformity compared with both the DCS-based and Original plans. The BDF-based method further reduced the doses delivered to the OARs by approximately 1-3%. The re-optimisation time was reduced by approximately 28%, but the MUs and delivery time were slightly increased. All verification tests were passed and no significant differences were found. The BDF-based method for the optimisation of IMRT for cervical oesophageal cancer can achieve significantly better dose distributions with better planning efficiency at the expense of slightly more MUs.

Optimization of physical conditions for the production of thermostable T1 lipase in Pichia guilliermondii strain SO using response surface methodology.

PubMed

Abu, Mary Ladidi; Nooh, Hisham Mohd; Oslan, Siti Nurbaya; Salleh, Abu Bakar

2017-11-10

Pichia guilliermondii was found capable of expressing the recombinant thermostable lipase without methanol under the control of methanol dependent alcohol oxidase 1 promoter (AOXp 1). In this study, statistical approaches were employed for the screening and optimisation of physical conditions for T1 lipase production in P. guilliermondii. The screening of six physical conditions by Plackett-Burman Design has identified pH, inoculum size and incubation time as exerting significant effects on lipase production. These three conditions were further optimised using, Box-Behnken Design of Response Surface Methodology, which predicted an optimum medium comprising pH 6, 24 h incubation time and 2% inoculum size. T1 lipase activity of 2.0 U/mL was produced with a biomass of OD 600 23.0. The process of using RSM for optimisation yielded a 3-fold increase of T1 lipase over medium before optimisation. Therefore, this result has proven that T1 lipase can be produced at a higher yield in P. guilliermondii.

Controlled hydrostatic pressure stress downregulates the expression of ribosomal genes in preimplantation embryos: a possible protection mechanism?

PubMed

Bock, I; Raveh-Amit, H; Losonczi, E; Carstea, A C; Feher, A; Mashayekhi, K; Matyas, S; Dinnyes, A; Pribenszky, C

2016-04-01

The efficiency of various assisted reproductive techniques can be improved by preconditioning the gametes and embryos with sublethal hydrostatic pressure treatment. However, the underlying molecular mechanism responsible for this protective effect remains unknown and requires further investigation. Here, we studied the effect of optimised hydrostatic pressure treatment on the global gene expression of mouse oocytes after embryonic genome activation. Based on a gene expression microarray analysis, a significant effect of treatment was observed in 4-cell embryos derived from treated oocytes, revealing a transcriptional footprint of hydrostatic pressure-affected genes. Functional analysis identified numerous genes involved in protein synthesis that were downregulated in 4-cell embryos in response to hydrostatic pressure treatment, suggesting that regulation of translation has a major role in optimised hydrostatic pressure-induced stress tolerance. We present a comprehensive microarray analysis and further delineate a potential mechanism responsible for the protective effect of hydrostatic pressure treatment.

Design of a compact antenna with flared groundplane for a wearable breast hyperthermia system.

PubMed

Curto, Sergio; Prakash, Punit

2015-01-01

Currently available microwave hyperthermia systems for breast cancer treatment do not conform to the intact breast and provide limited control of heating patterns, thereby hindering an effective treatment. A compact patch antenna with a flared groundplane that may be integrated within a wearable hyperthermia system for the treatment of the intact breast disease is proposed. A 3D simulation-based approach was employed to optimise the antenna design with the objective of maximising the hyperthermia treatment volume (41 °C iso-therm) while maintaining good impedance matching. The optimised antenna design was fabricated and experimentally evaluated with ex vivo tissue measurements. The optimised compact antenna yielded a -10 dB bandwidth of 90 MHz centred at 915 MHz, and was capable of creating hyperthermia treatment volumes up to 14.4 cm(3) (31 mm × 28 mm × 32 mm) with an input power of 15 W. Experimentally measured reflection coefficient and transient temperature profiles were in good agreement with simulated profiles. Variations of + 50% in blood perfusion yielded variations in the treatment volume up to 11.5%. When compared to an antenna with a similar patch element employing a conventional rectangular groundplane, the antenna with flared groundplane afforded 22.3% reduction in required power levels to reach the same temperature, and yielded 2.4 times larger treatment volumes. The proposed patch antenna with a flared groundplane may be integrated within a wearable applicator for hyperthermia treatment of intact breast targets and has the potential to improve efficiency, increase patient comfort, and ultimately clinical outcomes.

A radiobiology-based inverse treatment planning method for optimisation of permanent l-125 prostate implants in focal brachytherapy.

PubMed

Haworth, Annette; Mears, Christopher; Betts, John M; Reynolds, Hayley M; Tack, Guido; Leo, Kevin; Williams, Scott; Ebert, Martin A

2016-01-07

Treatment plans for ten patients, initially treated with a conventional approach to low dose-rate brachytherapy (LDR, 145 Gy to entire prostate), were compared with plans for the same patients created with an inverse-optimisation planning process utilising a biologically-based objective. The 'biological optimisation' considered a non-uniform distribution of tumour cell density through the prostate based on known and expected locations of the tumour. Using dose planning-objectives derived from our previous biological-model validation study, the volume of the urethra receiving 125% of the conventional prescription (145 Gy) was reduced from a median value of 64% to less than 8% whilst maintaining high values of TCP. On average, the number of planned seeds was reduced from 85 to less than 75. The robustness of plans to random seed displacements needs to be carefully considered when using contemporary seed placement techniques. We conclude that an inverse planning approach to LDR treatments, based on a biological objective, has the potential to maintain high rates of tumour control whilst minimising dose to healthy tissue. In future, the radiobiological model will be informed using multi-parametric MRI to provide a personalised medicine approach.

Infrastructure optimisation via MBR retrofit: a design guide.

PubMed

Bagg, W K

2009-01-01

Wastewater management is continually evolving with the development and implementation of new, more efficient technologies. One of these is the Membrane Bioreactor (MBR). Although a relatively new technology in Australia, MBR wastewater treatment has been widely used elsewhere for over 20 years, with thousands of MBRs now in operation worldwide. Over the past 5 years, MBR technology has been enthusiastically embraced in Australia as a potential treatment upgrade option, and via retrofit typically offers two major benefits: (1) more capacity using mostly existing facilities, and (2) very high quality treated effluent. However, infrastructure optimisation via MBR retrofit is not a simple or low-cost solution and there are many factors which should be carefully evaluated before deciding on this method of plant upgrade. The paper reviews a range of design parameters which should be carefully evaluated when considering an MBR retrofit solution. Several actual and conceptual case studies are considered to demonstrate both advantages and disadvantages. Whilst optimising existing facilities and production of high quality water for reuse are powerful drivers, it is suggested that MBRs are perhaps not always the most sustainable Whole-of-Life solution for a wastewater treatment plant upgrade, especially by way of a retrofit.

Validation and optimisation of an ICD-10-coded case definition for sepsis using administrative health data

PubMed Central

Jolley, Rachel J; Jetté, Nathalie; Sawka, Keri Jo; Diep, Lucy; Goliath, Jade; Roberts, Derek J; Yipp, Bryan G; Doig, Christopher J

2015-01-01

Objective Administrative health data are important for health services and outcomes research. We optimised and validated in intensive care unit (ICU) patients an International Classification of Disease (ICD)-coded case definition for sepsis, and compared this with an existing definition. We also assessed the definition's performance in non-ICU (ward) patients. Setting and participants All adults (aged ≥18 years) admitted to a multisystem ICU with general medicosurgical ICU care from one of three tertiary care centres in the Calgary region in Alberta, Canada, between 1 January 2009 and 31 December 2012 were included. Research design Patient medical records were randomly selected and linked to the discharge abstract database. In ICU patients, we validated the Canadian Institute for Health Information (CIHI) ICD-10-CA (Canadian Revision)-coded definition for sepsis and severe sepsis against a reference standard medical chart review, and optimised this algorithm through examination of other conditions apparent in sepsis. Measures Sensitivity (Sn), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) were calculated. Results Sepsis was present in 604 of 1001 ICU patients (60.4%). The CIHI ICD-10-CA-coded definition for sepsis had Sn (46.4%), Sp (98.7%), PPV (98.2%) and NPV (54.7%); and for severe sepsis had Sn (47.2%), Sp (97.5%), PPV (95.3%) and NPV (63.2%). The optimised ICD-coded algorithm for sepsis increased Sn by 25.5% and NPV by 11.9% with slightly lowered Sp (85.4%) and PPV (88.2%). For severe sepsis both Sn (65.1%) and NPV (70.1%) increased, while Sp (88.2%) and PPV (85.6%) decreased slightly. Conclusions This study demonstrates that sepsis is highly undercoded in administrative data, thus under-ascertaining the true incidence of sepsis. The optimised ICD-coded definition has a higher validity with higher Sn and should be preferentially considered if used for surveillance purposes. PMID:26700284

Analysis and simulation of wireless signal propagation applying geostatistical interpolation techniques

NASA Astrophysics Data System (ADS)

Kolyaie, S.; Yaghooti, M.; Majidi, G.

2011-12-01

This paper is a part of an ongoing research to examine the capability of geostatistical analysis for mobile networks coverage prediction, simulation and tuning. Mobile network coverage predictions are used to find network coverage gaps and areas with poor serviceability. They are essential data for engineering and management in order to make better decision regarding rollout, planning and optimisation of mobile networks.The objective of this research is to evaluate different interpolation techniques in coverage prediction. In method presented here, raw data collected from drive testing a sample of roads in study area is analysed and various continuous surfaces are created using different interpolation methods. Two general interpolation methods are used in this paper with different variables; first, Inverse Distance Weighting (IDW) with various powers and number of neighbours and second, ordinary kriging with Gaussian, spherical, circular and exponential semivariogram models with different number of neighbours. For the result comparison, we have used check points coming from the same drive test data. Prediction values for check points are extracted from each surface and the differences with actual value are computed. The output of this research helps finding an optimised and accurate model for coverage prediction.

Targeted flock/herd and individual ruminant treatment approaches.

PubMed

Kenyon, F; Jackson, F

2012-05-04

In Europe, most nematodoses are subclinical involving morbid rather than mortal effects and control is largely achieved using anthelmintics. In cattle, the genera most associated with sub-optimal performance are Ostertagia and Cooperia whereas in sheep and goats, subclinical losses are most often caused by Teladorsagia and Trichostrongylus. In some regions, at certain times, other species such as Nematodirus and Haemonchus also cause disease in sheep and goats. Unfortunately, anthelmintic resistance has now become an issue for European small ruminant producers. One of the key aims of the EU-funded PARASOL project was to identify low input and sustainable approaches to control nematode parasites in ruminants using refugia-based strategies. Two approaches to optimise anthelmintic treatments in sheep and cattle were studied; targeted treatments (TT) - whole-group treatments optimised on the basis of a marker of infection e.g. faecal egg count (FEC), and targeted selected treatment (TST) - treatments given to identified individuals to provide epidemiological and/or production benefits. A number of indicators for TT and TST were assessed to define parasitological and production-system specific indicators for treatment that best suited the regions where the PARASOL studies were conducted. These included liveweight gain, production efficiency, FEC, body condition score and diarrhoea score in small ruminants, and pepsinogen levels and Ostertagia bulk milk tank ELISA in cattle. The PARASOL studies confirmed the value of monitoring FEC as a means of targeting whole-flock treatments in small ruminants. In cattle, bulk milk tank ELISA and serum pepsinogen assays could be used retrospectively to determine the levels of exposure and hence, in the next season to optimise anthelmintic usage. TST approaches in sheep and goats examined production efficiency and liveweight gain as indicators for treatment and confirmed the value of this approach in maintaining performance and anthelmintic susceptibility in the predominant gastrointestinal nematodes. There is good evidence that the TST approach selected less heavily for the development of resistance in comparison to routine monthly treatments. Further research is required to optimise markers for TT and TST but it is also crucial to encourage producers/advisors to adapt these refugia-based strategies to maintain drug susceptible parasites in order to provide sustainable control. Copyright © 2011 Elsevier B.V. All rights reserved.

Preclinical screening for retinopathy of prematurity risk using IGF1 levels at 3 weeks post-partum.

PubMed

Pérez-Muñuzuri, Alejandro; Couce-Pico, Maria Luz; Baña-Souto, Ana; López-Suárez, Olalla; Iglesias-Deus, Alicia; Blanco-Teijeiro, José; Fernández-Lorenzo, José Ramón; Fraga-Bermúdez, José María

2014-01-01

Following current recommendations for preventing retinopathy of prematurity (ROP) involves screening a large number of patients. We performed a prospective study to establish a useful screening system for ROP prediction and we have determined that measuring serum levels of IGF1 at week three and the presence of sepsis have a high predictive value for the subsequent development of ROP. A total of 145 premature newborn, with birthweight <1500 g and/or <32 weeks gestational age, were enrolled. 26.9% of them showed some form of retinopathy. A significant association was found between the development of retinopathy and each of the following variables: early gestational age, low birthweight, requiring mechanical ventilation, oxygen treatment, intracranial haemorrhage, sepsis during the first three weeks, bronchopulmonary dysplasia, the need for erythrocyte transfusion, erythropoietin treatment, and low levels of serum IGF1 in the third week. A multiple logistic regression analysis was used to obtain curves for the probability of developing ROP, based on the main factors linked with ROP, namely serum levels of IGF1 and presence of sepsis. Such preclinical screening has the ability to identify patients with high-risk of developing retinopathy and should lead to better prediction for ROP, while at the same time optimising the use of clinical resources, both human and material.

Optimal pharmacological therapy in ST-elevation myocardial infarction-a review : A review of antithrombotic therapies in STEMI.

PubMed

Hermanides, R S; Kilic, S; van 't Hof, A W J

2018-04-23

Antithrombotic therapy is an essential component in the optimisation of clinical outcomes in patients with ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention. There are currently several intravenous anticoagulant drugs available for primary percutaneous coronary intervention. Dual antiplatelet therapy comprising aspirin and P2Y12 inhibitor represents the cornerstone treatment for STEMI. However, these effective treatment strategies may be associated with bleeding complications. Compared with clopidogrel, prasugrel and ticagrelor are more potent and predictable, which translates into better clinical outcomes. Therefore, these agents are the first-line treatment in primary percutaneous coronary intervention. However, patients can still experience adverse ischaemic events, which might be in part attributed to alternative pathways triggering thrombosis. In this review, we provide a critical and updated review of currently available antithrombotic therapies used in patients with STEMI undergoing primary PCI. Finding a balance that minimises both thrombotic and bleeding risk is difficult, but crucial. Further randomised trials for this optimal balance are needed.

Modelling pathogen log10 reduction values achieved by activated sludge treatment using naïve and semi naïve Bayes network models.

PubMed

Carvajal, Guido; Roser, David J; Sisson, Scott A; Keegan, Alexandra; Khan, Stuart J

2015-11-15

Risk management for wastewater treatment and reuse have led to growing interest in understanding and optimising pathogen reduction during biological treatment processes. However, modelling pathogen reduction is often limited by poor characterization of the relationships between variables and incomplete knowledge of removal mechanisms. The aim of this paper was to assess the applicability of Bayesian belief network models to represent associations between pathogen reduction, and operating conditions and monitoring parameters and predict AS performance. Naïve Bayes and semi-naïve Bayes networks were constructed from an activated sludge dataset including operating and monitoring parameters, and removal efficiencies for two pathogens (native Giardia lamblia and seeded Cryptosporidium parvum) and five native microbial indicators (F-RNA bacteriophage, Clostridium perfringens, Escherichia coli, coliforms and enterococci). First we defined the Bayesian network structures for the two pathogen log10 reduction values (LRVs) class nodes discretized into two states (< and ≥ 1 LRV) using two different learning algorithms. Eight metrics, such as Prediction Accuracy (PA) and Area Under the receiver operating Curve (AUC), provided a comparison of model prediction performance, certainty and goodness of fit. This comparison was used to select the optimum models. The optimum Tree Augmented naïve models predicted removal efficiency with high AUC when all system parameters were used simultaneously (AUCs for C. parvum and G. lamblia LRVs of 0.95 and 0.87 respectively). However, metrics for individual system parameters showed only the C. parvum model was reliable. By contrast individual parameters for G. lamblia LRV prediction typically obtained low AUC scores (AUC < 0.81). Useful predictors for C. parvum LRV included solids retention time, turbidity and total coliform LRV. The methodology developed appears applicable for predicting pathogen removal efficiency in water treatment systems generally. Copyright © 2015 Elsevier Ltd. All rights reserved.

Optimisation of the Management of Higher Activity Waste in the UK - 13537

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walsh, Ciara; Buckley, Matthew

2013-07-01

The Upstream Optioneering project was created in the Nuclear Decommissioning Authority (UK) to support the development and implementation of significant opportunities to optimise activities across all the phases of the Higher Activity Waste management life cycle (i.e. retrieval, characterisation, conditioning, packaging, storage, transport and disposal). The objective of the Upstream Optioneering project is to work in conjunction with other functions within NDA and the waste producers to identify and deliver solutions to optimise the management of higher activity waste. Historically, optimisation may have occurred on aspects of the waste life cycle (considered here to include retrieval, conditioning, treatment, packaging, interimmore » storage, transport to final end state, which may be geological disposal). By considering the waste life cycle as a whole, critical analysis of assumed constraints may lead to cost savings for the UK Tax Payer. For example, it may be possible to challenge the requirements for packaging wastes for disposal to deliver an optimised waste life cycle. It is likely that the challenges faced in the UK are shared in other countries. It is therefore likely that the opportunities identified may also apply elsewhere, with the potential for sharing information to enable value to be shared. (authors)« less

Optimisation and validation of a rapid and efficient microemulsion liquid chromatographic (MELC) method for the determination of paracetamol (acetaminophen) content in a suppository formulation.

PubMed

McEvoy, Eamon; Donegan, Sheila; Power, Joe; Altria, Kevin

2007-05-09

A rapid and efficient oil-in-water microemulsion liquid chromatographic method has been optimised and validated for the analysis of paracetamol in a suppository formulation. Excellent linearity, accuracy, precision and assay results were obtained. Lengthy sample pre-treatment/extraction procedures were eliminated due to the solubilising power of the microemulsion and rapid analysis times were achieved. The method was optimised to achieve rapid analysis time and relatively high peak efficiencies. A standard microemulsion composition of 33 g SDS, 66 g butan-1-ol, 8 g n-octane in 1l of 0.05% TFA modified with acetonitrile has been shown to be suitable for the rapid analysis of paracetamol in highly hydrophobic preparations under isocratic conditions. Validated assay results and overall analysis time of the optimised method was compared to British Pharmacopoeia reference methods. Sample preparation and analysis times for the MELC analysis of paracetamol in a suppository were extremely rapid compared to the reference method and similar assay results were achieved. A gradient MELC method using the same microemulsion has been optimised for the resolution of paracetamol and five of its related substances in approximately 7 min.

Optimisation of novel method for the extraction of steviosides from Stevia rebaudiana leaves.

PubMed

Puri, Munish; Sharma, Deepika; Barrow, Colin J; Tiwary, A K

2012-06-01

Stevioside, a diterpene glycoside, is well known for its intense sweetness and is used as a non-caloric sweetener. Its potential widespread use requires an easy and effective extraction method. Enzymatic extraction of stevioside from Stevia rebaudiana leaves with cellulase, pectinase and hemicellulase, using various parameters, such as concentration of enzyme, incubation time and temperature, was optimised. Hemicellulase was observed to give the highest stevioside yield (369.23±0.11μg) in 1h in comparison to cellulase (359±0.30μg) and pectinases (333±0.55μg). Extraction from leaves under optimised conditions showed a remarkable increase in the yield (35 times) compared with a control experiment. The extraction conditions were further optimised using response surface methodology (RSM). A central composite design (CCD) was used for experimental design and analysis of the results to obtain optimal extraction conditions. Based on RSM analysis, temperature of 51-54°C, time of 36-45min and the cocktail of pectinase, cellulase and hemicellulase, set at 2% each, gave the best results. Under the optimised conditions, the experimental values were in close agreement with the prediction model and resulted in a three times yield enhancement of stevioside. The isolated stevioside was characterised through 1 H-NMR spectroscopy, by comparison with a stevioside standard. Copyright © 2011 Elsevier Ltd. All rights reserved.

Lap time simulation and design optimisation of a brushed DC electric motorcycle for the Isle of Man TT Zero Challenge

NASA Astrophysics Data System (ADS)

Dal Bianco, N.; Lot, R.; Matthys, K.

2018-01-01

This works regards the design of an electric motorcycle for the annual Isle of Man TT Zero Challenge. Optimal control theory was used to perform lap time simulation and design optimisation. A bespoked model was developed, featuring 3D road topology, vehicle dynamics and electric power train, composed of a lithium battery pack, brushed DC motors and motor controller. The model runs simulations over the entire ? or ? of the Snaefell Mountain Course. The work is validated using experimental data from the BX chassis of the Brunel Racing team, which ran during the 2009 to 2015 TT Zero races. Optimal control is used to improve drive train and power train configurations. Findings demonstrate computational efficiency, good lap time prediction and design optimisation potential, achieving a 2 minutes reduction of the reference lap time through changes in final drive gear ratio, battery pack size and motor configuration.

A target recognition method for maritime surveillance radars based on hybrid ensemble selection

NASA Astrophysics Data System (ADS)

Fan, Xueman; Hu, Shengliang; He, Jingbo

2017-11-01

In order to improve the generalisation ability of the maritime surveillance radar, a novel ensemble selection technique, termed Optimisation and Dynamic Selection (ODS), is proposed. During the optimisation phase, the non-dominated sorting genetic algorithm II for multi-objective optimisation is used to find the Pareto front, i.e. a set of ensembles of classifiers representing different tradeoffs between the classification error and diversity. During the dynamic selection phase, the meta-learning method is used to predict whether a candidate ensemble is competent enough to classify a query instance based on three different aspects, namely, feature space, decision space and the extent of consensus. The classification performance and time complexity of ODS are compared against nine other ensemble methods using a self-built full polarimetric high resolution range profile data-set. The experimental results clearly show the effectiveness of ODS. In addition, the influence of the selection of diversity measures is studied concurrently.

Optimisation techniques in vaginal cuff brachytherapy.

PubMed

Tuncel, N; Garipagaoglu, M; Kizildag, A U; Andic, F; Toy, A

2009-11-01

The aim of this study was to explore whether an in-house dosimetry protocol and optimisation method are able to produce a homogeneous dose distribution in the target volume, and how often optimisation is required in vaginal cuff brachytherapy. Treatment planning was carried out for 109 fractions in 33 patients who underwent high dose rate iridium-192 (Ir(192)) brachytherapy using Fletcher ovoids. Dose prescription and normalisation were performed to catheter-oriented lateral dose points (dps) within a range of 90-110% of the prescribed dose. The in-house vaginal apex point (Vk), alternative vaginal apex point (Vk'), International Commission on Radiation Units and Measurements (ICRU) rectal point (Rg) and bladder point (Bl) doses were calculated. Time-position optimisations were made considering dps, Vk and Rg doses. Keeping the Vk dose higher than 95% and the Rg dose less than 85% of the prescribed dose was intended. Target dose homogeneity, optimisation frequency and the relationship between prescribed dose, Vk, Vk', Rg and ovoid diameter were investigated. The mean target dose was 99+/-7.4% of the prescription dose. Optimisation was required in 92 out of 109 (83%) fractions. Ovoid diameter had a significant effect on Rg (p = 0.002), Vk (p = 0.018), Vk' (p = 0.034), minimum dps (p = 0.021) and maximum dps (p<0.001). Rg, Vk and Vk' doses with 2.5 cm diameter ovoids were significantly higher than with 2 cm and 1.5 cm ovoids. Catheter-oriented dose point normalisation provided a homogeneous dose distribution with a 99+/-7.4% mean dose within the target volume, requiring time-position optimisation.

Optimisation of composite bone plates for ulnar transverse fractures.

PubMed

Chakladar, N D; Harper, L T; Parsons, A J

2016-04-01

Metallic bone plates are commonly used for arm bone fractures where conservative treatment (casts) cannot provide adequate support and compression at the fracture site. These plates, made of stainless steel or titanium alloys, tend to shield stress transfer at the fracture site and delay the bone healing rate. This study investigates the feasibility of adopting advanced composite materials to overcome stress shielding effects by optimising the geometry and mechanical properties of the plate to match more closely to the bone. An ulnar transverse fracture is characterised and finite element techniques are employed to investigate the feasibility of a composite-plated fractured bone construct over a stainless steel equivalent. Numerical models of intact and fractured bones are analysed and the mechanical behaviour is found to agree with experimental data. The mechanical properties are tailored to produce an optimised composite plate, offering a 25% reduction in length and a 70% reduction in mass. The optimised design may help to reduce stress shielding and increase bone healing rates. Copyright © 2016 Elsevier Ltd. All rights reserved.

Model fitting for small skin permeability data sets: hyperparameter optimisation in Gaussian Process Regression.

PubMed

Ashrafi, Parivash; Sun, Yi; Davey, Neil; Adams, Roderick G; Wilkinson, Simon C; Moss, Gary Patrick

2018-03-01

The aim of this study was to investigate how to improve predictions from Gaussian Process models by optimising the model hyperparameters. Optimisation methods, including Grid Search, Conjugate Gradient, Random Search, Evolutionary Algorithm and Hyper-prior, were evaluated and applied to previously published data. Data sets were also altered in a structured manner to reduce their size, which retained the range, or 'chemical space' of the key descriptors to assess the effect of the data range on model quality. The Hyper-prior Smoothbox kernel results in the best models for the majority of data sets, and they exhibited significantly better performance than benchmark quantitative structure-permeability relationship (QSPR) models. When the data sets were systematically reduced in size, the different optimisation methods generally retained their statistical quality, whereas benchmark QSPR models performed poorly. The design of the data set, and possibly also the approach to validation of the model, is critical in the development of improved models. The size of the data set, if carefully controlled, was not generally a significant factor for these models and that models of excellent statistical quality could be produced from substantially smaller data sets. © 2018 Royal Pharmaceutical Society.

Application of response surface methodology (RSM) for optimisation of COD, NH3-N and 2,4-DCP removal from recycled paper wastewater in a pilot-scale granular activated carbon sequencing batch biofilm reactor (GAC-SBBR).

PubMed

Muhamad, Mohd Hafizuddin; Sheikh Abdullah, Siti Rozaimah; Mohamad, Abu Bakar; Abdul Rahman, Rakmi; Hasan Kadhum, Abdul Amir

2013-05-30

In this study, the potential of a pilot-scale granular activated carbon sequencing batch biofilm reactor (GAC-SBBR) for removing chemical oxygen demand (COD), ammoniacal nitrogen (NH3-N) and 2,4-dichlorophenol (2,4-DCP) from recycled paper wastewater was assessed. For this purpose, the response surface methodology (RSM) was employed, using a central composite face-centred design (CCFD), to optimise three of the most important operating variables, i.e., hydraulic retention time (HRT), aeration rate (AR) and influent feed concentration (IFC), in the pilot-scale GAC-SBBR process for recycled paper wastewater treatment. Quadratic models were developed for the response variables, i.e., COD, NH3-N and 2,4-DCP removal, based on the high value (>0.9) of the coefficient of determination (R(2)) obtained from the analysis of variance (ANOVA). The optimal conditions were established at 750 mg COD/L IFC, 3.2 m(3)/min AR and 1 day HRT, corresponding to predicted COD, NH3-N and 2,4-DCP removal percentages of 94.8, 100 and 80.9%, respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

Prediction of mean circulation velocity in oxidation ditch.

PubMed

Simon, S; Roustan, M; Audic, J M; Chatellier, P

2001-02-01

In wastewater treatment, oxidation ditches are used for the removal of carbon and nitrogen of activated sludge. The control of the single-phase flow is essential to the optimisation of the whole process. Among the two global functioning parameters (mean liquid velocity Uc, power dissipated per unit of volume P/V), the mean circulation velocity can be recommended. Indeed, the values of the power dissipated per unit of volume P/V obtained in different scale plant show that the industrial criterion on P/V leads to an overdesign of channel. Therefore a mean liquid circulation velocity Uc created by horizontal impellers must be maintained inside the ditch. In order to predict the velocity Uc, a model has been proposed based on the Equations of the continuity and motion and using a few simple parameters. Experiments were carried out on pilot plant (1 m3) and full scale ditches (860, 1400 and 2800 m3) in which the characteristics of the mixing system and the dimensions of channels were varied. A good agreement was observed between the model predictions and experimental data for the mean circulation velocity Uc.

Improved packing of protein side chains with parallel ant colonies.

PubMed

Quan, Lijun; Lü, Qiang; Li, Haiou; Xia, Xiaoyan; Wu, Hongjie

2014-01-01

The accurate packing of protein side chains is important for many computational biology problems, such as ab initio protein structure prediction, homology modelling, and protein design and ligand docking applications. Many of existing solutions are modelled as a computational optimisation problem. As well as the design of search algorithms, most solutions suffer from an inaccurate energy function for judging whether a prediction is good or bad. Even if the search has found the lowest energy, there is no certainty of obtaining the protein structures with correct side chains. We present a side-chain modelling method, pacoPacker, which uses a parallel ant colony optimisation strategy based on sharing a single pheromone matrix. This parallel approach combines different sources of energy functions and generates protein side-chain conformations with the lowest energies jointly determined by the various energy functions. We further optimised the selected rotamers to construct subrotamer by rotamer minimisation, which reasonably improved the discreteness of the rotamer library. We focused on improving the accuracy of side-chain conformation prediction. For a testing set of 442 proteins, 87.19% of X1 and 77.11% of X12 angles were predicted correctly within 40° of the X-ray positions. We compared the accuracy of pacoPacker with state-of-the-art methods, such as CIS-RR and SCWRL4. We analysed the results from different perspectives, in terms of protein chain and individual residues. In this comprehensive benchmark testing, 51.5% of proteins within a length of 400 amino acids predicted by pacoPacker were superior to the results of CIS-RR and SCWRL4 simultaneously. Finally, we also showed the advantage of using the subrotamers strategy. All results confirmed that our parallel approach is competitive to state-of-the-art solutions for packing side chains. This parallel approach combines various sources of searching intelligence and energy functions to pack protein side chains. It provides a frame-work for combining different inaccuracy/usefulness objective functions by designing parallel heuristic search algorithms.

Identification of the contribution of contact and aerial biomechanical parameters in acrobatic performance

PubMed Central

Haering, Diane; Huchez, Aurore; Barbier, Franck; Holvoët, Patrice; Begon, Mickaël

2017-01-01

Introduction Teaching acrobatic skills with a minimal amount of repetition is a major challenge for coaches. Biomechanical, statistical or computer simulation tools can help them identify the most determinant factors of performance. Release parameters, change in moment of inertia and segmental momentum transfers were identified in the prediction of acrobatics success. The purpose of the present study was to evaluate the relative contribution of these parameters in performance throughout expertise or optimisation based improvements. The counter movement forward in flight (CMFIF) was chosen for its intrinsic dichotomy between the accessibility of its attempt and complexity of its mastery. Methods Three repetitions of the CMFIF performed by eight novice and eight advanced female gymnasts were recorded using a motion capture system. Optimal aerial techniques that maximise rotation potential at regrasp were also computed. A 14-segment-multibody-model defined through the Rigid Body Dynamics Library was used to compute recorded and optimal kinematics, and biomechanical parameters. A stepwise multiple linear regression was used to determine the relative contribution of these parameters in novice recorded, novice optimised, advanced recorded and advanced optimised trials. Finally, fixed effects of expertise and optimisation were tested through a mixed-effects analysis. Results and discussion Variation in release state only contributed to performances in novice recorded trials. Moment of inertia contribution to performance increased from novice recorded, to novice optimised, advanced recorded, and advanced optimised trials. Contribution to performance of momentum transfer to the trunk during the flight prevailed in all recorded trials. Although optimisation decreased transfer contribution, momentum transfer to the arms appeared. Conclusion Findings suggest that novices should be coached on both contact and aerial technique. Inversely, mainly improved aerial technique helped advanced gymnasts increase their performance. For both, reduction of the moment of inertia should be focused on. The method proposed in this article could be generalized to any aerial skill learning investigation. PMID:28422954

Optimal bioprocess design through a gene regulatory network - growth kinetic hybrid model: Towards Replacing Monod kinetics.

PubMed

Tsipa, Argyro; Koutinas, Michalis; Usaku, Chonlatep; Mantalaris, Athanasios

2018-05-02

Currently, design and optimisation of biotechnological bioprocesses is performed either through exhaustive experimentation and/or with the use of empirical, unstructured growth kinetics models. Whereas, elaborate systems biology approaches have been recently explored, mixed-substrate utilisation is predominantly ignored despite its significance in enhancing bioprocess performance. Herein, bioprocess optimisation for an industrially-relevant bioremediation process involving a mixture of highly toxic substrates, m-xylene and toluene, was achieved through application of a novel experimental-modelling gene regulatory network - growth kinetic (GRN-GK) hybrid framework. The GRN model described the TOL and ortho-cleavage pathways in Pseudomonas putida mt-2 and captured the transcriptional kinetics expression patterns of the promoters. The GRN model informed the formulation of the growth kinetics model replacing the empirical and unstructured Monod kinetics. The GRN-GK framework's predictive capability and potential as a systematic optimal bioprocess design tool, was demonstrated by effectively predicting bioprocess performance, which was in agreement with experimental values, when compared to four commonly used models that deviated significantly from the experimental values. Significantly, a fed-batch biodegradation process was designed and optimised through the model-based control of TOL Pr promoter expression resulting in 61% and 60% enhanced pollutant removal and biomass formation, respectively, compared to the batch process. This provides strong evidence of model-based bioprocess optimisation at the gene level, rendering the GRN-GK framework as a novel and applicable approach to optimal bioprocess design. Finally, model analysis using global sensitivity analysis (GSA) suggests an alternative, systematic approach for model-driven strain modification for synthetic biology and metabolic engineering applications. Copyright © 2018. Published by Elsevier Inc.

Identification, optimisation and in vivo evaluation of oxadiazole DGAT-1 inhibitors for the treatment of obesity and diabetes.

PubMed

McCoull, William; Addie, Matthew S; Birch, Alan M; Birtles, Susan; Buckett, Linda K; Butlin, Roger J; Bowker, Suzanne S; Boyd, Scott; Chapman, Stephen; Davies, Robert D M; Donald, Craig S; Green, Clive P; Jenner, Chloe; Kemmitt, Paul D; Leach, Andrew G; Moody, Graeme C; Gutierrez, Pablo Morentin; Newcombe, Nicholas J; Nowak, Thorsten; Packer, Martin J; Plowright, Alleyn T; Revill, John; Schofield, Paul; Sheldon, Chris; Stokes, Steve; Turnbull, Andrew V; Wang, Steven J Y; Whalley, David P; Wood, J Matthew

2012-06-15

A novel series of DGAT-1 inhibitors was discovered from an oxadiazole amide high throughput screening (HTS) hit. Optimisation of potency and ligand lipophilicity efficiency (LLE) resulted in a carboxylic acid containing clinical candidate 53 (AZD3988), which demonstrated excellent DGAT-1 potency (0.6 nM), good pharmacokinetics and pre-clinical in vivo efficacy that could be rationalised through a PK/PD relationship. Copyright © 2012 Elsevier Ltd. All rights reserved.

Variational Bayesian identification and prediction of stochastic nonlinear dynamic causal models.

PubMed

Daunizeau, J; Friston, K J; Kiebel, S J

2009-11-01

In this paper, we describe a general variational Bayesian approach for approximate inference on nonlinear stochastic dynamic models. This scheme extends established approximate inference on hidden-states to cover: (i) nonlinear evolution and observation functions, (ii) unknown parameters and (precision) hyperparameters and (iii) model comparison and prediction under uncertainty. Model identification or inversion entails the estimation of the marginal likelihood or evidence of a model. This difficult integration problem can be finessed by optimising a free-energy bound on the evidence using results from variational calculus. This yields a deterministic update scheme that optimises an approximation to the posterior density on the unknown model variables. We derive such a variational Bayesian scheme in the context of nonlinear stochastic dynamic hierarchical models, for both model identification and time-series prediction. The computational complexity of the scheme is comparable to that of an extended Kalman filter, which is critical when inverting high dimensional models or long time-series. Using Monte-Carlo simulations, we assess the estimation efficiency of this variational Bayesian approach using three stochastic variants of chaotic dynamic systems. We also demonstrate the model comparison capabilities of the method, its self-consistency and its predictive power.

Protocol for a multicentred randomised controlled trial investigating the use of personalised golimumab dosing tailored to inflammatory load in ulcerative colitis: the GOAL-ARC study (GLM dose Optimisation to Adequate Levels to Achieve Response in Colitis) led by the INITIAtive group (NCT 0268772)

PubMed Central

Sheridan, Juliette; Coe, Carol Ann; Doran, Peter; Egan, Laurence; Cullen, Garret; Kevans, David; Leyden, Jan; Galligan, Marie; O’Toole, Aoibhlinn; McCarthy, Jane; Doherty, Glen

2018-01-01

Introduction Ulcerative colitis (UC) is a chronic inflammatory bowel disease (IBD), often leading to an impaired quality of life in affected patients. Current treatment modalities include antitumour necrosis factor (anti-TNF) monoclonal antibodies (mABs) including infliximab, adalimumab and golimumab (GLM). Several recent retrospective and prospective studies have demonstrated that fixed dosing schedules of anti-TNF agents often fails to consistently achieve adequate circulating therapeutic drug levels (DL) with consequent risk of immunogenicity treatment failure and potential risk of hospitalisation and colectomy in patients with UC. The design of GLM dose Optimisation to Adequate Levels to Achieve Response in Colitis aims to address the impact of dose escalation of GLM immediately following induction and during the subsequent maintenance phase in response to suboptimal DL or persisting inflammatory burden as represented by raised faecal calprotectin (FCP). Aim The primary aim of the study is to ascertain if monitoring of FCP and DL of GLM to guide dose optimisation (during maintenance) improves rates of patient continuous clinical response and reduces disease activity in UC. Methods and analysis A randomised, multicentred two-arm trial studying the effect of dose optimisation of GLM based on FCP and DL versus treatment as per SMPC. Eligible patients will be randomised in a 1:1 ratio to 1 of 2 treatment groups and shall be treated over a period of 46 weeks. Ethics and dissemination The study protocol was approved by the Research Ethics committee of St. Vincent’s University Hospital. The results will be published in a peer-reviewed journal and shared with the worldwide medical community. Trial registration numbers EudraCT number: 2015-004724-62; Clinicaltrials.gov Identifier: NCT0268772; Pre-results. PMID:29379609

HIFU scattering by the ribs: constrained optimisation with a complex surface impedance boundary condition

NASA Astrophysics Data System (ADS)

Gélat, P.; ter Haar, G.; Saffari, N.

2014-04-01

High intensity focused ultrasound (HIFU) enables highly localised, non-invasive tissue ablation and its efficacy has been demonstrated in the treatment of a range of cancers, including those of the kidney, prostate and breast. HIFU offers the ability to treat deep-seated tumours locally, and potentially bears fewer side effects than more established treatment modalities such as resection, chemotherapy and ionising radiation. There remains however a number of significant challenges which currently hinder its widespread clinical application. One of these challenges is the need to transmit sufficient energy through the ribcage to ablate tissue at the required foci whilst minimising the formation of side lobes and sparing healthy tissue. Ribs both absorb and reflect ultrasound strongly. This sometimes results in overheating of bone and overlying tissue during treatment, leading to skin burns. Successful treatment of a patient with tumours in the upper abdomen therefore requires a thorough understanding of the way acoustic and thermal energy is deposited. Previously, a boundary element (BE) approach based on a Generalised Minimal Residual (GMRES) implementation of the Burton-Miller formulation was developed to predict the field of a multi-element HIFU array scattered by human ribs, the topology of which was obtained from CT scan data [1]. Dissipative mechanisms inside the propagating medium have since been implemented, together with a complex surface impedance condition at the surface of the ribs. A reformulation of the boundary element equations as a constrained optimisation problem was carried out to determine the complex surface velocities of a multi-element HIFU array which generated the acoustic pressure field that best fitted a required acoustic pressure distribution in a least-squares sense. This was done whilst ensuring that an acoustic dose rate parameter at the surface of the ribs was kept below a specified threshold. The methodology was tested at an excitation frequency of 1 MHz on a spherical multi-element array in the presence of anatomical ribs.

Application and optimisation of air-steam cooking on selected vegetables: impact on physical and antioxidant properties.

PubMed

Paciulli, Maria; Dall'Asta, Chiara; Rinaldi, Massimiliano; Pellegrini, Nicoletta; Pugliese, Alessandro; Chiavaro, Emma

2018-04-01

Several studies investigated the impact of different cooking techniques on the quality of vegetables. However, the use of the combined air-steam cooking is still scarcely debated, despite the advantages informally referred by professional catering workers. In this study, its optimisation was studied on Brussels sprouts and pumpkin cubes to obtain the best physical (texture, colour) and antioxidant (FRAP, total phenols) response, in comparison to a conventional steaming treatment. Increasing the strength of the air-steam treatment, Brussels sprouts resulted to be softer, less green (higher a* value), richer in phenols and exhibited lower FRAP values than the steamed ones. The air-steamed pumpkin cubes exhibited an equivalent softening degree to that of steamed ones and, under the strongest cooking conditions, a higher antioxidant quality and a yellow darkening (lower b* value). Varying the cooking time and/or temperature, a linear change of force/compression hardness and a* (negative a*: greenness) for Brussels sprouts, b* (yellowness) and total phenol content for pumpkin cubes was observed. A predictive model for these variables was obtained by response surface methodology. The best process conditions to achieve the optimal desirability were also identified. The application of air-steam cooking under suitable time/temperature conditions could be proposed as an alternative method to a traditional steam cooking on Brussels sprouts and pumpkin cubes, being able to preserve or improve their quality. The best air-steam cooking conditions were 25 min at 90 °C for Brussels sprouts and 10 min at 110 °C for pumpkin. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Biological effective dose evaluation in gynaecological brachytherapy: LDR and HDR treatments, dependence on radiobiological parameters, and treatment optimisation.

PubMed

Bianchi, C; Botta, F; Conte, L; Vanoli, P; Cerizza, L

2008-10-01

This study was undertaken to compare the biological efficacy of different high-dose-rate (HDR) and low-dose-rate (LDR) treatments of gynaecological lesions, to identify the causes of possible nonuniformity and to optimise treatment through customised calculation. The study considered 110 patients treated between 2001 and 2006 with external beam radiation therapy and/or brachytherapy with either LDR (afterloader Selectron, (137)Cs) or HDR (afterloader microSelectron Classic, (192)Ir). The treatments were compared in terms of biologically effective dose (BED) to the tumour and to the rectum (linear-quadratic model) by using statistical tests for comparisons between independent samples. The difference between the two treatments was statistically significant in one case only. However, within each technique, we identified considerable nonuniformity in therapeutic efficacy due to differences in fractionation schemes and overall treatment time. To solve this problem, we created a Microsoft Excel spreadsheet allowing calculation of the optimal treatment for each patient: best efficacy (BED(tumour)) without exceeding toxicity threshold (BED(rectum)). The efficacy of a treatment may vary as a result of several factors. Customised radiobiological evaluation is a useful adjunct to clinical evaluation in planning equivalent treatments that satisfy all dosimetric constraints.

Global reaction mechanism for the auto-ignition of full boiling range gasoline and kerosene fuels

NASA Astrophysics Data System (ADS)

Vandersickel, A.; Wright, Y. M.; Boulouchos, K.

2013-12-01

Compact reaction schemes capable of predicting auto-ignition are a prerequisite for the development of strategies to control and optimise homogeneous charge compression ignition (HCCI) engines. In particular for full boiling range fuels exhibiting two stage ignition a tremendous demand exists in the engine development community. The present paper therefore meticulously assesses a previous 7-step reaction scheme developed to predict auto-ignition for four hydrocarbon blends and proposes an important extension of the model constant optimisation procedure, allowing for the model to capture not only ignition delays, but also the evolutions of representative intermediates and heat release rates for a variety of full boiling range fuels. Additionally, an extensive validation of the later evolutions by means of various detailed n-heptane reaction mechanisms from literature has been presented; both for perfectly homogeneous, as well as non-premixed/stratified HCCI conditions. Finally, the models potential to simulate the auto-ignition of various full boiling range fuels is demonstrated by means of experimental shock tube data for six strongly differing fuels, containing e.g. up to 46.7% cyclo-alkanes, 20% napthalenes or complex branched aromatics such as methyl- or ethyl-napthalene. The good predictive capability observed for each of the validation cases as well as the successful parameterisation for each of the six fuels, indicate that the model could, in principle, be applied to any hydrocarbon fuel, providing suitable adjustments to the model parameters are carried out. Combined with the optimisation strategy presented, the model therefore constitutes a major step towards the inclusion of real fuel kinetics into full scale HCCI engine simulations.

Near infrared spectrometric technique for testing fruit quality: optimisation of regression models using genetic algorithms

NASA Astrophysics Data System (ADS)

Isingizwe Nturambirwe, J. Frédéric; Perold, Willem J.; Opara, Umezuruike L.

2016-02-01

Near infrared (NIR) spectroscopy has gained extensive use in quality evaluation. It is arguably one of the most advanced spectroscopic tools in non-destructive quality testing of food stuff, from measurement to data analysis and interpretation. NIR spectral data are interpreted through means often involving multivariate statistical analysis, sometimes associated with optimisation techniques for model improvement. The objective of this research was to explore the extent to which genetic algorithms (GA) can be used to enhance model development, for predicting fruit quality. Apple fruits were used, and NIR spectra in the range from 12000 to 4000 cm-1 were acquired on both bruised and healthy tissues, with different degrees of mechanical damage. GAs were used in combination with partial least squares regression methods to develop bruise severity prediction models, and compared to PLS models developed using the full NIR spectrum. A classification model was developed, which clearly separated bruised from unbruised apple tissue. GAs helped improve prediction models by over 10%, in comparison with full spectrum-based models, as evaluated in terms of error of prediction (Root Mean Square Error of Cross-validation). PLS models to predict internal quality, such as sugar content and acidity were developed and compared to the versions optimized by genetic algorithm. Overall, the results highlighted the potential use of GA method to improve speed and accuracy of fruit quality prediction.

Systems oncology: towards patient-specific treatment regimes informed by multiscale mathematical modelling.

PubMed

Powathil, Gibin G; Swat, Maciej; Chaplain, Mark A J

2015-02-01

The multiscale complexity of cancer as a disease necessitates a corresponding multiscale modelling approach to produce truly predictive mathematical models capable of improving existing treatment protocols. To capture all the dynamics of solid tumour growth and its progression, mathematical modellers need to couple biological processes occurring at various spatial and temporal scales (from genes to tissues). Because effectiveness of cancer therapy is considerably affected by intracellular and extracellular heterogeneities as well as by the dynamical changes in the tissue microenvironment, any model attempt to optimise existing protocols must consider these factors ultimately leading to improved multimodal treatment regimes. By improving existing and building new mathematical models of cancer, modellers can play important role in preventing the use of potentially sub-optimal treatment combinations. In this paper, we analyse a multiscale computational mathematical model for cancer growth and spread, incorporating the multiple effects of radiation therapy and chemotherapy in the patient survival probability and implement the model using two different cell based modelling techniques. We show that the insights provided by such multiscale modelling approaches can ultimately help in designing optimal patient-specific multi-modality treatment protocols that may increase patients quality of life. Copyright © 2014 Elsevier Ltd. All rights reserved.

Understanding the role of monolayers in retarding evaporation from water storage bodies

NASA Astrophysics Data System (ADS)

Fellows, Christopher M.; Coop, Paul A.; Lamb, David W.; Bradbury, Ronald C.; Schiretz, Helmut F.; Woolley, Andrew J.

2015-03-01

Retardation of evaporation by monomolecular films by a 'barrier model' does not explain the effect of air velocity on relative evaporation rates in the presence and absence of such films. An alternative mechanism for retardation of evaporation attributes reduced evaporation to a reduction of surface roughness, which in turn increases the effective vapour pressure of water above the surface. Evaporation suppression effectiveness under field conditions should be predictable from measurements of the surface dilational modulus of monolayers and research directed to optimising this mechanism should be more fruitful than research aimed at optimising a monolayer to provide an impermeable barrier.

The 5C Concept and 5S Principles in Inflammatory Bowel Disease Management

PubMed Central

Hibi, Toshifumi; Panaccione, Remo; Katafuchi, Miiko; Yokoyama, Kaoru; Watanabe, Kenji; Matsui, Toshiyuki; Matsumoto, Takayuki; Travis, Simon; Suzuki, Yasuo

2017-01-01

Abstract Background and Aims The international Inflammatory Bowel Disease [IBD] Expert Alliance initiative [2012–2015] served as a platform to define and support areas of best practice in IBD management to help improve outcomes for all patients with IBD. Methods During the programme, IBD specialists from around the world established by consensus two best practice charters: the 5S Principles and the 5C Concept. Results The 5S Principles were conceived to provide health care providers with key guidance for improving clinical practice based on best management approaches. They comprise the following categories: Stage the disease; Stratify patients; Set treatment goals; Select appropriate treatment; and Supervise therapy. Optimised management of patients with IBD based on the 5S Principles can be achieved most effectively within an optimised clinical care environment. Guidance on optimising the clinical care setting in IBD management is provided through the 5C Concept, which encompasses: Comprehensive IBD care; Collaboration; Communication; Clinical nurse specialists; and Care pathways. Together, the 5C Concept and 5S Principles provide structured recommendations on organising the clinical care setting and developing best-practice approaches in IBD management. Conclusions Consideration and application of these two dimensions could help health care providers optimise their IBD centres and collaborate more effectively with their multidisciplinary team colleagues and patients, to provide improved IBD care in daily clinical practice. Ultimately, this could lead to improved outcomes for patients with IBD. PMID:28981622

Association between anxiety and depression in patients with acute coronary syndromes due to financial crisis.

PubMed

Lampropoulos, Kostandinos; Kavvouras, Charalampos; Megalou, Aikaterini; Tsikouri, Pinelopi; Kafkala, Chrysanthi; Derka, Dimitra; Bonou, Maria; Barbetseas, John

2016-01-01

The effect of anxiety and depression on patients with acute coronary syndromes (ACS) warrants investigation, especially during periods of economic crisis. To investigate the relation between anxiety and depression in patients presenting with ACS due to financial crisis and to investigate whether these two entities could predict long-term cardiovascular mortality. Anxiety and depression symptoms were assessed in 350 patients (210 men) presenting with ACS, with 70 (20%) patients showing elevated scores (Hellenic Heart Failure Protocol). Over a mean follow-up of 48 months there were 36 (10%) cardiovascular deaths. Cox proportional hazards models adjusted for other prognostic factors (including age, sex, marital status, creatinine levels, left ventricular ejection fraction, heart failure, atrial fibrillation, previous hospitalisation, and baseline medications) showed that elevated anxiety and depression scores significantly predicted cardiovascular mortality (primary outcome) and all-cause mortality. Elevated anxiety and depression symptoms are related to cardiovascular mortality due probably to financial crisis, even after adjustment for other prognostic indicators in patients with ACS, who received optimised medical treatment.

Validation and optimisation of an ICD-10-coded case definition for sepsis using administrative health data.

PubMed

Jolley, Rachel J; Quan, Hude; Jetté, Nathalie; Sawka, Keri Jo; Diep, Lucy; Goliath, Jade; Roberts, Derek J; Yipp, Bryan G; Doig, Christopher J

2015-12-23

Administrative health data are important for health services and outcomes research. We optimised and validated in intensive care unit (ICU) patients an International Classification of Disease (ICD)-coded case definition for sepsis, and compared this with an existing definition. We also assessed the definition's performance in non-ICU (ward) patients. All adults (aged ≥ 18 years) admitted to a multisystem ICU with general medicosurgical ICU care from one of three tertiary care centres in the Calgary region in Alberta, Canada, between 1 January 2009 and 31 December 2012 were included. Patient medical records were randomly selected and linked to the discharge abstract database. In ICU patients, we validated the Canadian Institute for Health Information (CIHI) ICD-10-CA (Canadian Revision)-coded definition for sepsis and severe sepsis against a reference standard medical chart review, and optimised this algorithm through examination of other conditions apparent in sepsis. Sensitivity (Sn), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) were calculated. Sepsis was present in 604 of 1001 ICU patients (60.4%). The CIHI ICD-10-CA-coded definition for sepsis had Sn (46.4%), Sp (98.7%), PPV (98.2%) and NPV (54.7%); and for severe sepsis had Sn (47.2%), Sp (97.5%), PPV (95.3%) and NPV (63.2%). The optimised ICD-coded algorithm for sepsis increased Sn by 25.5% and NPV by 11.9% with slightly lowered Sp (85.4%) and PPV (88.2%). For severe sepsis both Sn (65.1%) and NPV (70.1%) increased, while Sp (88.2%) and PPV (85.6%) decreased slightly. This study demonstrates that sepsis is highly undercoded in administrative data, thus under-ascertaining the true incidence of sepsis. The optimised ICD-coded definition has a higher validity with higher Sn and should be preferentially considered if used for surveillance purposes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction.

PubMed

O'Boyle, Noel M; Palmer, David S; Nigsch, Florian; Mitchell, John Bo

2008-10-29

We present a novel feature selection algorithm, Winnowing Artificial Ant Colony (WAAC), that performs simultaneous feature selection and model parameter optimisation for the development of predictive quantitative structure-property relationship (QSPR) models. The WAAC algorithm is an extension of the modified ant colony algorithm of Shen et al. (J Chem Inf Model 2005, 45: 1024-1029). We test the ability of the algorithm to develop a predictive partial least squares model for the Karthikeyan dataset (J Chem Inf Model 2005, 45: 581-590) of melting point values. We also test its ability to perform feature selection on a support vector machine model for the same dataset. Starting from an initial set of 203 descriptors, the WAAC algorithm selected a PLS model with 68 descriptors which has an RMSE on an external test set of 46.6 degrees C and R2 of 0.51. The number of components chosen for the model was 49, which was close to optimal for this feature selection. The selected SVM model has 28 descriptors (cost of 5, epsilon of 0.21) and an RMSE of 45.1 degrees C and R2 of 0.54. This model outperforms a kNN model (RMSE of 48.3 degrees C, R2 of 0.47) for the same data and has similar performance to a Random Forest model (RMSE of 44.5 degrees C, R2 of 0.55). However it is much less prone to bias at the extremes of the range of melting points as shown by the slope of the line through the residuals: -0.43 for WAAC/SVM, -0.53 for Random Forest. With a careful choice of objective function, the WAAC algorithm can be used to optimise machine learning and regression models that suffer from overfitting. Where model parameters also need to be tuned, as is the case with support vector machine and partial least squares models, it can optimise these simultaneously. The moving probabilities used by the algorithm are easily interpreted in terms of the best and current models of the ants, and the winnowing procedure promotes the removal of irrelevant descriptors.

A novel soft tissue prediction methodology for orthognathic surgery based on probabilistic finite element modelling

PubMed Central

Borghi, Alessandro; Ruggiero, Federica; Badiali, Giovanni; Bianchi, Alberto; Marchetti, Claudio; Rodriguez-Florez, Naiara; Breakey, Richard W. F.; Jeelani, Owase; Dunaway, David J.; Schievano, Silvia

2018-01-01

Repositioning of the maxilla in orthognathic surgery is carried out for functional and aesthetic purposes. Pre-surgical planning tools can predict 3D facial appearance by computing the response of the soft tissue to the changes to the underlying skeleton. The clinical use of commercial prediction software remains controversial, likely due to the deterministic nature of these computational predictions. A novel probabilistic finite element model (FEM) for the prediction of postoperative facial soft tissues is proposed in this paper. A probabilistic FEM was developed and validated on a cohort of eight patients who underwent maxillary repositioning and had pre- and postoperative cone beam computed tomography (CBCT) scans taken. Firstly, a variables correlation assessed various modelling parameters. Secondly, a design of experiments (DOE) provided a range of potential outcomes based on uniformly distributed input parameters, followed by an optimisation. Lastly, the second DOE iteration provided optimised predictions with a probability range. A range of 3D predictions was obtained using the probabilistic FEM and validated using reconstructed soft tissue surfaces from the postoperative CBCT data. The predictions in the nose and upper lip areas accurately include the true postoperative position, whereas the prediction under-estimates the position of the cheeks and lower lip. A probabilistic FEM has been developed and validated for the prediction of the facial appearance following orthognathic surgery. This method shows how inaccuracies in the modelling and uncertainties in executing surgical planning influence the soft tissue prediction and it provides a range of predictions including a minimum and maximum, which may be helpful for patients in understanding the impact of surgery on the face. PMID:29742139

A novel soft tissue prediction methodology for orthognathic surgery based on probabilistic finite element modelling.

PubMed

Knoops, Paul G M; Borghi, Alessandro; Ruggiero, Federica; Badiali, Giovanni; Bianchi, Alberto; Marchetti, Claudio; Rodriguez-Florez, Naiara; Breakey, Richard W F; Jeelani, Owase; Dunaway, David J; Schievano, Silvia

2018-01-01

Repositioning of the maxilla in orthognathic surgery is carried out for functional and aesthetic purposes. Pre-surgical planning tools can predict 3D facial appearance by computing the response of the soft tissue to the changes to the underlying skeleton. The clinical use of commercial prediction software remains controversial, likely due to the deterministic nature of these computational predictions. A novel probabilistic finite element model (FEM) for the prediction of postoperative facial soft tissues is proposed in this paper. A probabilistic FEM was developed and validated on a cohort of eight patients who underwent maxillary repositioning and had pre- and postoperative cone beam computed tomography (CBCT) scans taken. Firstly, a variables correlation assessed various modelling parameters. Secondly, a design of experiments (DOE) provided a range of potential outcomes based on uniformly distributed input parameters, followed by an optimisation. Lastly, the second DOE iteration provided optimised predictions with a probability range. A range of 3D predictions was obtained using the probabilistic FEM and validated using reconstructed soft tissue surfaces from the postoperative CBCT data. The predictions in the nose and upper lip areas accurately include the true postoperative position, whereas the prediction under-estimates the position of the cheeks and lower lip. A probabilistic FEM has been developed and validated for the prediction of the facial appearance following orthognathic surgery. This method shows how inaccuracies in the modelling and uncertainties in executing surgical planning influence the soft tissue prediction and it provides a range of predictions including a minimum and maximum, which may be helpful for patients in understanding the impact of surgery on the face.

Optimised isolation of polysaccharides from Lentinula edodes strain NCBI JX915793 using response surface methodology and their antibacterial activities.

PubMed

Sharma, Shivani; Khanna, P K; Kapoor, S

2016-01-01

Mycelial growth in a defined medium by submerged fermentation is a rapid and alternative method for obtaining fungal biomass of consistent quality. Biomass, exopolysaccharides (EPS) and intracellular polysaccharides (IPS) production were optimised by response surface methodology in Lentinula edodes strain LeS (NCBI JX915793). The optimised conditions were pH 5.0, temperature 26°C, incubation period of 25 days and agitation rate of 52 r/min for L. edodes strain LeS. Under the calculated optimal culture conditions, biomass production (5.88 mg mL(-1)), EPS production (0.40 mg mL(-1)) and IPS production (12.45 mg g(-1)) were in agreement with the predicted values for biomass (5.93 mg mL(-1)), EPS (0.55 mg mL(-1)) and IPS production (12.64 mg g(-1)). Crude lentinan exhibited highest antibacterial effects followed by alcoholic, crude and aqueous extracts. The results obtained may be useful for highly effective yield of biomass and bioactive metabolites.

Optimisation of substrate blends in anaerobic co-digestion using adaptive linear programming.

PubMed

García-Gen, Santiago; Rodríguez, Jorge; Lema, Juan M

2014-12-01

Anaerobic co-digestion of multiple substrates has the potential to enhance biogas productivity by making use of the complementary characteristics of different substrates. A blending strategy based on a linear programming optimisation method is proposed aiming at maximising COD conversion into methane, but simultaneously maintaining a digestate and biogas quality. The method incorporates experimental and heuristic information to define the objective function and the linear restrictions. The active constraints are continuously adapted (by relaxing the restriction boundaries) such that further optimisations in terms of methane productivity can be achieved. The feasibility of the blends calculated with this methodology was previously tested and accurately predicted with an ADM1-based co-digestion model. This was validated in a continuously operated pilot plant, treating for several months different mixtures of glycerine, gelatine and pig manure at organic loading rates from 1.50 to 4.93 gCOD/Ld and hydraulic retention times between 32 and 40 days at mesophilic conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cosmos caudatus as a potential source of polyphenolic compounds: optimisation of oven drying conditions and characterisation of its functional properties.

PubMed

Mediani, Ahmed; Abas, Faridah; Khatib, Alfi; Tan, Chin Ping

2013-08-29

The aim of the study was to analyze the influence of oven thermal processing of Cosmos caudatus on the total polyphenolic content (TPC) and antioxidant capacity (DPPH) of two different solvent extracts (80% methanol, and 80% ethanol). Sonication was used to extract bioactive compounds from this herb. The results showed that the optimised conditions for the oven drying method for 80% methanol and 80% ethanol were 44.5 °C for 4 h with an IC₅₀ of 0.045 mg/mL and 43.12 °C for 4.05 h with an IC₅₀ of 0.055 mg/mL, respectively. The predicted values for TPC under the optimised conditions for 80% methanol and 80% ethanol were 16.5 and 15.8 mg GAE/100 g DW, respectively. The results obtained from this study demonstrate that Cosmos caudatus can be used as a potential source of antioxidants for food and medicinal applications.

An optimisation methodology of artificial neural network models for predicting solar radiation: a case study

NASA Astrophysics Data System (ADS)

Rezrazi, Ahmed; Hanini, Salah; Laidi, Maamar

2016-02-01

The right design and the high efficiency of solar energy systems require accurate information on the availability of solar radiation. Due to the cost of purchase and maintenance of the radiometers, these data are not readily available. Therefore, there is a need to develop alternative ways of generating such data. Artificial neural networks (ANNs) are excellent and effective tools for learning, pinpointing or generalising data regularities, as they have the ability to model nonlinear functions; they can also cope with complex `noisy' data. The main objective of this paper is to show how to reach an optimal model of ANNs for applying in prediction of solar radiation. The measured data of the year 2007 in Ghardaïa city (Algeria) are used to demonstrate the optimisation methodology. The performance evaluation and the comparison of results of ANN models with measured data are made on the basis of mean absolute percentage error (MAPE). It is found that MAPE in the ANN optimal model reaches 1.17 %. Also, this model yields a root mean square error (RMSE) of 14.06 % and an MBE of 0.12. The accuracy of the outputs exceeded 97 % and reached up 99.29 %. Results obtained indicate that the optimisation strategy satisfies practical requirements. It can successfully be generalised for any location in the world and be used in other fields than solar radiation estimation.

A knowledge-based control system for air-scour optimisation in membrane bioreactors.

PubMed

Ferrero, G; Monclús, H; Sancho, L; Garrido, J M; Comas, J; Rodríguez-Roda, I

2011-01-01

Although membrane bioreactors (MBRs) technology is still a growing sector, its progressive implementation all over the world, together with great technical achievements, has allowed it to reach a mature degree, just comparable to other more conventional wastewater treatment technologies. With current energy requirements around 0.6-1.1 kWh/m3 of treated wastewater and investment costs similar to conventional treatment plants, main market niche for MBRs can be areas with very high restrictive discharge limits, where treatment plants have to be compact or where water reuse is necessary. Operational costs are higher than for conventional treatments; consequently there is still a need and possibilities for energy saving and optimisation. This paper presents the development of a knowledge-based decision support system (DSS) for the integrated operation and remote control of the biological and physical (filtration and backwashing or relaxation) processes in MBRs. The core of the DSS is a knowledge-based control module for air-scour consumption automation and energy consumption minimisation.

Modelling multi-phase liquid-sediment scour and resuspension induced by rapid flows using Smoothed Particle Hydrodynamics (SPH) accelerated with a Graphics Processing Unit (GPU)

NASA Astrophysics Data System (ADS)

Fourtakas, G.; Rogers, B. D.

2016-06-01

A two-phase numerical model using Smoothed Particle Hydrodynamics (SPH) is applied to two-phase liquid-sediments flows. The absence of a mesh in SPH is ideal for interfacial and highly non-linear flows with changing fragmentation of the interface, mixing and resuspension. The rheology of sediment induced under rapid flows undergoes several states which are only partially described by previous research in SPH. This paper attempts to bridge the gap between the geotechnics, non-Newtonian and Newtonian flows by proposing a model that combines the yielding, shear and suspension layer which are needed to predict accurately the global erosion phenomena, from a hydrodynamics prospective. The numerical SPH scheme is based on the explicit treatment of both phases using Newtonian and the non-Newtonian Bingham-type Herschel-Bulkley-Papanastasiou constitutive model. This is supplemented by the Drucker-Prager yield criterion to predict the onset of yielding of the sediment surface and a concentration suspension model. The multi-phase model has been compared with experimental and 2-D reference numerical models for scour following a dry-bed dam break yielding satisfactory results and improvements over well-known SPH multi-phase models. With 3-D simulations requiring a large number of particles, the code is accelerated with a graphics processing unit (GPU) in the open-source DualSPHysics code. The implementation and optimisation of the code achieved a speed up of x58 over an optimised single thread serial code. A 3-D dam break over a non-cohesive erodible bed simulation with over 4 million particles yields close agreement with experimental scour and water surface profiles.

Statistical optimisation of diclofenac sustained release pellets coated with polymethacrylic films.

PubMed

Kramar, A; Turk, S; Vrecer, F

2003-04-30

The objective of the present study was to evaluate three formulation parameters for the application of polymethacrylic films from aqueous dispersions in order to obtain multiparticulate sustained release of diclofenac sodium. Film coating of pellet cores was performed in a laboratory fluid bed apparatus. The chosen independent variables, i.e. the concentration of plasticizer (triethyl citrate), methacrylate polymers ratio (Eudragit RS:Eudragit RL) and the quantity of coating dispersion were optimised with a three-factor, three-level Box-Behnken design. The chosen dependent variables were cumulative percentage values of diclofenac dissolved in 3, 4 and 6 h. Based on the experimental design, different diclofenac release profiles were obtained. Response surface plots were used to relate the dependent and the independent variables. The optimisation procedure generated an optimum of 40% release in 3 h. The levels of plasticizer concentration, quantity of coating dispersion and polymer to polymer ratio (Eudragit RS:Eudragit RL) were 25% w/w, 400 g and 3/1, respectively. The optimised formulation prepared according to computer-determined levels provided a release profile, which was close to the predicted values. We also studied thermal and surface characteristics of the polymethacrylic films to understand the influence of plasticizer concentration on the drug release from the pellets.

Optimisation of near-infrared reflectance model in measuring protein and amylose content of rice flour.

PubMed

Xie, L H; Tang, S Q; Chen, N; Luo, J; Jiao, G A; Shao, G N; Wei, X J; Hu, P S

2014-01-01

Near-infrared reflectance spectroscopy (NIRS) has been used to predict the cooking quality parameters of rice, such as the protein (PC) and amylose content (AC). Using brown and milled flours from 519 rice samples representing a wide range of grain qualities, this study was to compare the calibration models generated by different mathematical, preprocessing treatments, and combinations of different regression algorithm. A modified partial least squares model (MPLS) with the mathematic treatment "2, 8, 8, 2" (2nd order derivative computed based on 8 data points, and 8 and 2 data points in the 1st and 2nd smoothing, respectively) and inverse multiplicative scattering correction preprocessing treatment was identified as the best model for simultaneously measurement of PC and AC in brown flours. MPLS/"2, 8, 8, 2"/detrend preprocessing was identified as the best model for milled flours. The results indicated that NIRS could be useful in estimation of PC and AC of breeding lines in early generations of the breeding programs, and for the purposes of quality control in the food industry. Copyright © 2013 Elsevier Ltd. All rights reserved.

Optimising resource management in neurorehabilitation.

PubMed

Wood, Richard M; Griffiths, Jeff D; Williams, Janet E; Brouwers, Jakko

2014-01-01

To date, little research has been published regarding the effective and efficient management of resources (beds and staff) in neurorehabilitation, despite being an expensive service in limited supply. To demonstrate how mathematical modelling can be used to optimise service delivery, by way of a case study at a major 21 bed neurorehabilitation unit in the UK. An automated computer program for assigning weekly treatment sessions is developed. Queue modelling is used to construct a mathematical model of the hospital in terms of referral submissions to a waiting list, admission and treatment, and ultimately discharge. This is used to analyse the impact of hypothetical strategic decisions on a variety of performance measures and costs. The project culminates in a hybridised model of these two approaches, since a relationship is found between the number of therapy hours received each week (scheduling output) and length of stay (queuing model input). The introduction of the treatment scheduling program has substantially improved timetable quality (meaning a better and fairer service to patients) and has reduced employee time expended in its creation by approximately six hours each week (freeing up time for clinical work). The queuing model has been used to assess the effect of potential strategies, such as increasing the number of beds or employing more therapists. The use of mathematical modelling has not only optimised resources in the short term, but has allowed the optimality of longer term strategic decisions to be assessed.

Temporal optimisation of fuel treatment design in blue gum (Eucalyptus globulus) plantations

Treesearch

Ana Martin; Brigite Botequim; Tiago M. Oliveira; Alan Ager; Francesco Pirotti

2016-01-01

This study was conducted to support fire and forest management planning in eucalypt plantations based on economic, ecological and fire prevention criteria, with a focus on strategic prioritisation of fuel treatments over time. The central objective was to strategically locate fuel treatments to minimise losses from wildfire while meeting budget constraints and demands...

Ranibizumab (Lucentis) in neovascular age-related macular degeneration: evidence from clinical trials.

PubMed

Mitchell, P; Korobelnik, J-F; Lanzetta, P; Holz, F G; Prünte, C; Schmidt-Erfurth, U; Tano, Y; Wolf, S

2010-01-01

Neovascular age-related macular degeneration (AMD) has a poor prognosis if left untreated, frequently resulting in legal blindness. Ranibizumab is approved for treating neovascular AMD. However, further guidance is needed to assist ophthalmologists in clinical practice to optimise treatment outcomes. An international retina expert panel assessed evidence available from prospective, multicentre studies evaluating different ranibizumab treatment schedules (ANCHOR, MARINA, PIER, SAILOR, SUSTAIN and EXCITE) and a literature search to generate evidence-based and consensus recommendations for treatment indication and assessment, retreatment and monitoring. Ranibizumab is indicated for choroidal neovascular lesions with active disease, the clinical parameters of which are outlined. Treatment initiation with three consecutive monthly injections, followed by continued monthly injections, has provided the best visual-acuity outcomes in pivotal clinical trials. If continued monthly injections are not feasible after initiation, a flexible strategy appears viable, with monthly monitoring of lesion activity recommended. Initiation regimens of fewer than three injections have not been assessed. Continuous careful monitoring with flexible retreatment may help avoid vision loss recurring. Standardised biomarkers need to be determined. Evidence-based guidelines will help to optimise treatment outcomes with ranibizumab in neovascular AMD.

Reservoir optimisation using El Niño information. Case study of Daule Peripa (Ecuador)

NASA Astrophysics Data System (ADS)

Gelati, Emiliano; Madsen, Henrik; Rosbjerg, Dan

2010-05-01

The optimisation of water resources systems requires the ability to produce runoff scenarios that are consistent with available climatic information. We approach stochastic runoff modelling with a Markov-modulated autoregressive model with exogenous input, which belongs to the class of Markov-switching models. The model assumes runoff parameterisation to be conditioned on a hidden climatic state following a Markov chain, whose state transition probabilities depend on climatic information. This approach allows stochastic modeling of non-stationary runoff, as runoff anomalies are described by a mixture of autoregressive models with exogenous input, each one corresponding to a climate state. We calibrate the model on the inflows of the Daule Peripa reservoir located in western Ecuador, where the occurrence of El Niño leads to anomalously heavy rainfall caused by positive sea surface temperature anomalies along the coast. El Niño - Southern Oscillation (ENSO) information is used to condition the runoff parameterisation. Inflow predictions are realistic, especially at the occurrence of El Niño events. The Daule Peripa reservoir serves a hydropower plant and a downstream water supply facility. Using historical ENSO records, synthetic monthly inflow scenarios are generated for the period 1950-2007. These scenarios are used as input to perform stochastic optimisation of the reservoir rule curves with a multi-objective Genetic Algorithm (MOGA). The optimised rule curves are assumed to be the reservoir base policy. ENSO standard indices are currently forecasted at monthly time scale with nine-month lead time. These forecasts are used to perform stochastic optimisation of reservoir releases at each monthly time step according to the following procedure: (i) nine-month inflow forecast scenarios are generated using ENSO forecasts; (ii) a MOGA is set up to optimise the upcoming nine monthly releases; (iii) the optimisation is carried out by simulating the releases on the inflow forecasts, and by applying the base policy on a subsequent synthetic inflow scenario in order to account for long-term costs; (iv) the optimised release for the first month is implemented; (v) the state of the system is updated and (i), (ii), (iii), and (iv) are iterated for the following time step. The results highlight the advantages of using a climate-driven stochastic model to produce inflow scenarios and forecasts for reservoir optimisation, showing potential improvements with respect to the current management. Dynamic programming was used to find the best possible release time series given the inflow observations, in order to benchmark any possible operational improvement.

[Population pharmacokinetics applied to optimising cisplatin doses in cancer patients].

PubMed

Ramón-López, A; Escudero-Ortiz, V; Carbonell, V; Pérez-Ruixo, J J; Valenzuela, B

2012-01-01

To develop and internally validate a population pharmacokinetics model for cisplatin and assess its prediction capacity for personalising doses in cancer patients. Cisplatin plasma concentrations in forty-six cancer patients were used to determine the pharmacokinetic parameters of a two-compartment pharmacokinetic model implemented in NONMEN VI software. Pharmacokinetic parameter identification capacity was assessed using the parametric bootstrap method and the model was validated using the nonparametric bootstrap method and standardised visual and numerical predictive checks. The final model's prediction capacity was evaluated in terms of accuracy and precision during the first (a priori) and second (a posteriori) chemotherapy cycles. Mean population cisplatin clearance is 1.03 L/h with an interpatient variability of 78.0%. Estimated distribution volume at steady state was 48.3 L, with inter- and intrapatient variabilities of 31,3% and 11,7%, respectively. Internal validation confirmed that the population pharmacokinetics model is appropriate to describe changes over time in cisplatin plasma concentrations, as well as its variability in the study population. The accuracy and precision of a posteriori prediction of cisplatin concentrations improved by 21% and 54% compared to a priori prediction. The population pharmacokinetic model developed adequately described the changes in cisplatin plasma concentrations in cancer patients and can be used to optimise cisplatin dosing regimes accurately and precisely. Copyright © 2011 SEFH. Published by Elsevier Espana. All rights reserved.

Thermal time constant: optimising the skin temperature predictive modelling in lower limb prostheses using Gaussian processes

PubMed Central

Buis, Arjan

2016-01-01

Elevated skin temperature at the body/device interface of lower-limb prostheses is one of the major factors that affect tissue health. The heat dissipation in prosthetic sockets is greatly influenced by the thermal conductive properties of the hard socket and liner material employed. However, monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used which requires consistent positioning of sensors during donning and doffing. Predicting the residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. To predict the residual limb temperature, a machine learning algorithm – Gaussian processes is employed, which utilizes the thermal time constant values of commonly used socket and liner materials. This Letter highlights the relevance of thermal time constant of prosthetic materials in Gaussian processes technique which would be useful in addressing the challenge of non-invasively monitoring the residual limb skin temperature. With the introduction of thermal time constant, the model can be optimised and generalised for a given prosthetic setup, thereby making the predictions more reliable. PMID:27695626

Thermal time constant: optimising the skin temperature predictive modelling in lower limb prostheses using Gaussian processes.

PubMed

Mathur, Neha; Glesk, Ivan; Buis, Arjan

2016-06-01

Elevated skin temperature at the body/device interface of lower-limb prostheses is one of the major factors that affect tissue health. The heat dissipation in prosthetic sockets is greatly influenced by the thermal conductive properties of the hard socket and liner material employed. However, monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used which requires consistent positioning of sensors during donning and doffing. Predicting the residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. To predict the residual limb temperature, a machine learning algorithm - Gaussian processes is employed, which utilizes the thermal time constant values of commonly used socket and liner materials. This Letter highlights the relevance of thermal time constant of prosthetic materials in Gaussian processes technique which would be useful in addressing the challenge of non-invasively monitoring the residual limb skin temperature. With the introduction of thermal time constant, the model can be optimised and generalised for a given prosthetic setup, thereby making the predictions more reliable.

Predictive Detection of Tuberculosis using Electronic Nose Technology

NASA Astrophysics Data System (ADS)

Gibson, Tim; Kolk, Arend; Reither, Klaus; Kuipers, Sjoukje; Hallam, Viv; Chandler, Rob; Dutta, Ritaban; Maboko, Leonard; Jung, Jutta; Klatser, Paul

2009-05-01

The adaptation and use of a Bloodhound® ST214 electronic nose to rapidly detect TB in sputum samples has been discussed in the past, with some promising results being obtained in 2007. Some of the specific VOC's associated with Mycobacteria tuberculosis organisms are now being discovered and a paper was published in 2008, but the method of predicting the presence of TB in sputum samples using the VOC biomarkers has yet to be fully optimised. Nevertheless, with emphasis on the sampling techniques and with new data processing techniques to obtain consistent results progress is being made Sensitivity and specificity levels for field detection of TB have been set by WHO at a minimum level of 85% and 95% respectively, and the e-nose technique is working towards these figures. In a series of experiments carried out in Mbeya, Tanzania, Africa, data from a full 5 days of sampling was combined giving a total of 248 sputum samples analysed. From the data obtained we can report results that show specificities and sensitivities in the 70-80% region when actually predicting the presence of TB in unknown sputum samples. The results are a further step forward in the rapid detection of TB in the clinics in developing countries and show continued promise for future development of an optimised instrument for TB prediction.

Acid-base and copper-binding properties of three organic matter fractions isolated from a forest floor soil solution

NASA Astrophysics Data System (ADS)

van Schaik, Joris W. J.; Kleja, Dan B.; Gustafsson, Jon Petter

2010-02-01

Vast amounts of knowledge about the proton- and metal-binding properties of dissolved organic matter (DOM) in natural waters have been obtained in studies on isolated humic and fulvic (hydrophobic) acids. Although macromolecular hydrophilic acids normally make up about one-third of DOM, their proton- and metal-binding properties are poorly known. Here, we investigated the acid-base and Cu-binding properties of the hydrophobic (fulvic) acid fraction and two hydrophilic fractions isolated from a soil solution. Proton titrations revealed a higher total charge for the hydrophilic acid fractions than for the hydrophobic acid fraction. The most hydrophilic fraction appeared to be dominated by weak acid sites, as evidenced by increased slope of the curve of surface charge versus pH at pH values above 6. The titration curves were poorly predicted by both Stockholm Humic Model (SHM) and NICA-Donnan model calculations using generic parameter values, but could be modelled accurately after optimisation of the proton-binding parameters (pH ⩽ 9). Cu-binding isotherms for the three fractions were determined at pH values of 4, 6 and 9. With the optimised proton-binding parameters, the SHM model predictions for Cu binding improved, whereas the NICA-Donnan predictions deteriorated. After optimisation of Cu-binding parameters, both models described the experimental data satisfactorily. Iron(III) and aluminium competed strongly with Cu for binding sites at both pH 4 and pH 6. The SHM model predicted this competition reasonably well, but the NICA-Donnan model underestimated the effects significantly at pH 6. Overall, the Cu-binding behaviour of the two hydrophilic acid fractions was very similar to that of the hydrophobic acid fraction, despite the differences observed in proton-binding characteristics. These results show that for modelling purposes, it is essential to include the hydrophilic acid fraction in the pool of 'active' humic substances.

Evaluation and optimisation of current milrinone prescribing for the treatment and prevention of low cardiac output syndrome in paediatric patients after open heart surgery using a physiology-based pharmacokinetic drug-disease model.

PubMed

Vogt, Winnie

2014-01-01

Milrinone is the drug of choice for the treatment and prevention of low cardiac output syndrome (LCOS) in paediatric patients after open heart surgery across Europe. Discrepancies, however, among prescribing guidance, clinical studies and practice pattern require clarification to ensure safe and effective prescribing. However, the clearance prediction equations derived from classical pharmacokinetic modelling provide limited support as they have recently failed a clinical practice evaluation. Therefore, the objective of this study was to evaluate current milrinone dosing using physiology-based pharmacokinetic (PBPK) modelling and simulation to complement the existing pharmacokinetic knowledge and propose optimised dosing regimens as a basis for improving the standard of care for paediatric patients. A PBPK drug-disease model using a population approach was developed in three steps from healthy young adults to adult patients and paediatric patients with and without LCOS after open heart surgery. Pre- and postoperative organ function values from adult and paediatric patients were collected from literature and integrated into a disease model as factorial changes from the reference values in healthy adults aged 20-40 years. The disease model was combined with the PBPK drug model and evaluated against existing pharmacokinetic data. Model robustness was assessed by parametric sensitivity analysis. In the next step, virtual patient populations were created, each with 1,000 subjects reflecting the average adult and paediatric patient characteristics with regard to age, sex, bodyweight and height. They were integrated into the PBPK drug-disease model to evaluate the effectiveness of current milrinone dosing in achieving the therapeutic target range of 100-300 ng/mL milrinone in plasma. Optimised dosing regimens were subsequently developed. The pharmacokinetics of milrinone in healthy young adults as well as adult and paediatric patients were accurately described with an average fold error of 1.1 ± 0.1 (mean ± standard deviation) and mean relative deviation of 1.5 ± 0.3 as measures of bias and precision, respectively. Normalised maximum sensitivity coefficients for model input parameters ranged from -0.84 to 0.71, which indicated model robustness. The evaluation of milrinone dosing across different paediatric age groups showed a non-linear age dependence of total plasma clearance and exposure differences of a factor 1.4 between patients with and without LCOS for a fixed dosing regimen. None of the currently used dosing regimens for milrinone achieved the therapeutic target range across all paediatric age groups and adult patients, so optimised dosing regimens were developed that considered the age-dependent and pathophysiological differences. The PBPK drug-disease model for milrinone in paediatric patients with and without LCOS after open heart surgery highlights that age, disease and surgery differently impact the pharmacokinetics of milrinone, and that current milrinone dosing for LCOS is suboptimal to maintain the therapeutic target range across the entire paediatric age range. Thus, optimised dosing strategies are proposed to ensure safe and effective prescribing.

Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques.

PubMed

Illias, Hazlee Azil; Chai, Xin Rui; Abu Bakar, Ab Halim; Mokhlis, Hazlie

2015-01-01

It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works.

Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques

PubMed Central

2015-01-01

It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works. PMID:26103634

The 5C Concept and 5S Principles in Inflammatory Bowel Disease Management.

PubMed

Hibi, Toshifumi; Panaccione, Remo; Katafuchi, Miiko; Yokoyama, Kaoru; Watanabe, Kenji; Matsui, Toshiyuki; Matsumoto, Takayuki; Travis, Simon; Suzuki, Yasuo

2017-10-27

The international Inflammatory Bowel Disease [IBD] Expert Alliance initiative [2012-2015] served as a platform to define and support areas of best practice in IBD management to help improve outcomes for all patients with IBD. During the programme, IBD specialists from around the world established by consensus two best practice charters: the 5S Principles and the 5C Concept. The 5S Principles were conceived to provide health care providers with key guidance for improving clinical practice based on best management approaches. They comprise the following categories: Stage the disease; Stratify patients; Set treatment goals; Select appropriate treatment; and Supervise therapy. Optimised management of patients with IBD based on the 5S Principles can be achieved most effectively within an optimised clinical care environment. Guidance on optimising the clinical care setting in IBD management is provided through the 5C Concept, which encompasses: Comprehensive IBD care; Collaboration; Communication; Clinical nurse specialists; and Care pathways. Together, the 5C Concept and 5S Principles provide structured recommendations on organising the clinical care setting and developing best-practice approaches in IBD management. Consideration and application of these two dimensions could help health care providers optimise their IBD centres and collaborate more effectively with their multidisciplinary team colleagues and patients, to provide improved IBD care in daily clinical practice. Ultimately, this could lead to improved outcomes for patients with IBD. Copyright © 2017 European Crohn’s and Colitis Organisation (ECCO). Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com

Variations of leaf longevity in tropical moist forests predicted by a trait-driven carbon optimality model

DOE PAGES

Xu, Xiangtao; Medvigy, David; Wright, Stuart Joseph; ...

2017-07-04

Leaf longevity (LL) varies more than 20-fold in tropical evergreen forests, but it remains unclear how to capture these variations using predictive models. Current theories of LL that are based on carbon optimisation principles are challenging to quantitatively assess because of uncertainty across species in the ‘ageing rate:’ the rate at which leaf photosynthetic capacity declines with age. Here in this paper, we present a meta-analysis of 49 species across temperate and tropical biomes, demonstrating that the ageing rate of photosynthetic capacity is positively correlated with the mass-based carboxylation rate of mature leaves. We assess an improved trait-driven carbon optimalitymore » model with in situLL data for 105 species in two Panamanian forests. Additionally, we show that our model explains over 40% of the cross-species variation in LL under contrasting light environment. Collectively, our results reveal how variation in LL emerges from carbon optimisation constrained by both leaf structural traits and abiotic environment.« less

Variations of leaf longevity in tropical moist forests predicted by a trait-driven carbon optimality model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Xiangtao; Medvigy, David; Wright, Stuart Joseph

Leaf longevity (LL) varies more than 20-fold in tropical evergreen forests, but it remains unclear how to capture these variations using predictive models. Current theories of LL that are based on carbon optimisation principles are challenging to quantitatively assess because of uncertainty across species in the ‘ageing rate:’ the rate at which leaf photosynthetic capacity declines with age. Here in this paper, we present a meta-analysis of 49 species across temperate and tropical biomes, demonstrating that the ageing rate of photosynthetic capacity is positively correlated with the mass-based carboxylation rate of mature leaves. We assess an improved trait-driven carbon optimalitymore » model with in situLL data for 105 species in two Panamanian forests. Additionally, we show that our model explains over 40% of the cross-species variation in LL under contrasting light environment. Collectively, our results reveal how variation in LL emerges from carbon optimisation constrained by both leaf structural traits and abiotic environment.« less

Optimisation of surfactant decontamination and pre-treatment of waste chicken feathers by using response surface methodology.

PubMed

Tesfaye, Tamrat; Sithole, Bruce; Ramjugernath, Deresh; Ndlela, Luyanda

2018-02-01

Commercially processed, untreated chicken feathers are biologically hazardous due to the presence of blood-borne pathogens. Prior to valorisation, it is crucial that they are decontaminated to remove the microbial contamination. The present study focuses on evaluating the best technologies to decontaminate and pre-treat chicken feathers in order to make them suitable for valorisation. Waste chicken feathers were washed with three surfactants (sodium dodecyl sulphate) dimethyl dioctadecyl ammonium chloride, and polyoxyethylene (40) stearate) using statistically designed experiments. Process conditions were optimised using response surface methodology with a Box-Behnken experimental design. The data were compared with decontamination using an autoclave. Under optimised conditions, the microbial counts of the decontaminated and pre-treated chicken feathers were significantly reduced making them safe for handling and use for valorisation applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mammalian cell culture monitoring using in situ spectroscopy: Is your method really optimised?

PubMed

André, Silvère; Lagresle, Sylvain; Hannas, Zahia; Calvosa, Éric; Duponchel, Ludovic

2017-03-01

In recent years, as a result of the process analytical technology initiative of the US Food and Drug Administration, many different works have been carried out on direct and in situ monitoring of critical parameters for mammalian cell cultures by Raman spectroscopy and multivariate regression techniques. However, despite interesting results, it cannot be said that the proposed monitoring strategies, which will reduce errors of the regression models and thus confidence limits of the predictions, are really optimized. Hence, the aim of this article is to optimize some critical steps of spectroscopic acquisition and data treatment in order to reach a higher level of accuracy and robustness of bioprocess monitoring. In this way, we propose first an original strategy to assess the most suited Raman acquisition time for the processes involved. In a second part, we demonstrate the importance of the interbatch variability on the accuracy of the predictive models with a particular focus on the optical probes adjustment. Finally, we propose a methodology for the optimization of the spectral variables selection in order to decrease prediction errors of multivariate regressions. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:308-316, 2017. © 2017 American Institute of Chemical Engineers.

CEINMS: a toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks

PubMed Central

Pizzolato, Claudio; Lloyd, David G.; Sartori, Massimo; Ceseracciu, Elena; Besier, Thor F.; Fregly, Benjamin J.; Reggiani, Monica

2015-01-01

Personalized neuromusculoskeletal (NMS) models can represent the neurological, physiological, and anatomical characteristics of an individual and can be used to estimate the forces generated inside the human body. Currently, publicly available software to calculate muscle forces are restricted to static and dynamic optimisation methods, or limited to isometric tasks only. We have created and made freely available for the research community the Calibrated EMG-Informed NMS Modelling Toolbox (CEINMS), an OpenSim plug-in that enables investigators to predict different neural control solutions for the same musculoskeletal geometry and measured movements. CEINMS comprises EMG-driven and EMG-informed algorithms that have been previously published and tested. It operates on dynamic skeletal models possessing any number of degrees of freedom and musculotendon units and can be calibrated to the individual to predict measured joint moments and EMG patterns. In this paper we describe the components of CEINMS and its integration with OpenSim. We then analyse how EMG-driven, EMG-assisted, and static optimisation neural control solutions affect the estimated joint moments, muscle forces, and muscle excitations, including muscle co-contraction. PMID:26522621

Improved packing of protein side chains with parallel ant colonies

PubMed Central

2014-01-01

Introduction The accurate packing of protein side chains is important for many computational biology problems, such as ab initio protein structure prediction, homology modelling, and protein design and ligand docking applications. Many of existing solutions are modelled as a computational optimisation problem. As well as the design of search algorithms, most solutions suffer from an inaccurate energy function for judging whether a prediction is good or bad. Even if the search has found the lowest energy, there is no certainty of obtaining the protein structures with correct side chains. Methods We present a side-chain modelling method, pacoPacker, which uses a parallel ant colony optimisation strategy based on sharing a single pheromone matrix. This parallel approach combines different sources of energy functions and generates protein side-chain conformations with the lowest energies jointly determined by the various energy functions. We further optimised the selected rotamers to construct subrotamer by rotamer minimisation, which reasonably improved the discreteness of the rotamer library. Results We focused on improving the accuracy of side-chain conformation prediction. For a testing set of 442 proteins, 87.19% of X1 and 77.11% of X12 angles were predicted correctly within 40° of the X-ray positions. We compared the accuracy of pacoPacker with state-of-the-art methods, such as CIS-RR and SCWRL4. We analysed the results from different perspectives, in terms of protein chain and individual residues. In this comprehensive benchmark testing, 51.5% of proteins within a length of 400 amino acids predicted by pacoPacker were superior to the results of CIS-RR and SCWRL4 simultaneously. Finally, we also showed the advantage of using the subrotamers strategy. All results confirmed that our parallel approach is competitive to state-of-the-art solutions for packing side chains. Conclusions This parallel approach combines various sources of searching intelligence and energy functions to pack protein side chains. It provides a frame-work for combining different inaccuracy/usefulness objective functions by designing parallel heuristic search algorithms. PMID:25474164

Neural network feedforward control of a closed-circuit wind tunnel

NASA Astrophysics Data System (ADS)

Sutcliffe, Peter

Accurate control of wind-tunnel test conditions can be dramatically enhanced using feedforward control architectures which allow operating conditions to be maintained at a desired setpoint through the use of mathematical models as the primary source of prediction. However, as the desired accuracy of the feedforward prediction increases, the model complexity also increases, so that an ever increasing computational load is incurred. This drawback can be avoided by employing a neural network that is trained offline using the output of a high fidelity wind-tunnel mathematical model, so that the neural network can rapidly reproduce the predictions of the model with a greatly reduced computational overhead. A novel neural network database generation method, developed through the use of fractional factorial arrays, was employed such that a neural network can accurately predict wind-tunnel parameters across a wide range of operating conditions whilst trained upon a highly efficient database. The subsequent network was incorporated into a Neural Network Model Predictive Control (NNMPC) framework to allow an optimised output schedule capable of providing accurate control of the wind-tunnel operating parameters. Facilitation of an optimised path through the solution space is achieved through the use of a chaos optimisation algorithm such that a more globally optimum solution is likely to be found with less computational expense than the gradient descent method. The parameters associated with the NNMPC such as the control horizon are determined through the use of a Taguchi methodology enabling the minimum number of experiments to be carried out to determine the optimal combination. The resultant NNMPC scheme was employed upon the Hessert Low Speed Wind Tunnel at the University of Notre Dame to control the test-section temperature such that it follows a pre-determined reference trajectory during changes in the test-section velocity. Experimental testing revealed that the derived NNMPC controller provided an excellent level of control over the test-section temperature in adherence to a reference trajectory even when faced with unforeseen disturbances such as rapid changes in the operating environment.

Vectra DA for the objective measurement of disease activity in patients with rheumatoid arthritis.

PubMed

Segurado, O G; Sasso, E H

2014-01-01

Quantitative and regular assessment of disease activity in rheumatoid arthritis (RA) is required to achieve treatment targets such as remission and to optimize clinical outcomes. To assess inflammation accurately, predict joint damage and monitor treatment response, a measure of disease activity in RA should reflect the pathological processes resulting in irreversible joint damage and functional disability. The Vectra DA blood test is an objective measure of disease activity for patients with RA. Vectra DA provides an accurate, reproducible score on a scale of 1 to 100 based on the concentrations of 12 biomarkers that reflect the pathophysiologic diversity of RA. The analytical validity, clinical validity, and clinical utility of Vectra DA have been evaluated for patients with RA in registries and prospective and retrospective clinical studies. As a biomarker-based instrument for assessing disease activity in RA, the Vectra DA test can help monitor therapeutic response to methotrexate and biologic agents and assess clinically challenging situations, such as when clinical measures are confounded by non-inflammatory pain from fibromyalgia. Vectra DA scores correlate with imaging of joint inflammation and are predictive for radiographic progression, with high Vectra DA scores being associated with more frequent and severe progression and low scores being predictive for non-progression. In summary, the Vectra DA score is an objective measure of RA disease activity that quantifies inflammatory status. By predicting risk for joint damage more effectively than conventional clinical and laboratory measures, it has the potential to complement these measures and optimise clinical decision making.

Implementation of the multi-channel monolith reactor in an optimisation procedure for heterogeneous oxidation catalysts based on genetic algorithms.

PubMed

Breuer, Christian; Lucas, Martin; Schütze, Frank-Walter; Claus, Peter

2007-01-01

A multi-criteria optimisation procedure based on genetic algorithms is carried out in search of advanced heterogeneous catalysts for total oxidation. Simple but flexible software routines have been created to be applied within a search space of more then 150,000 individuals. The general catalyst design includes mono-, bi- and trimetallic compositions assembled out of 49 different metals and depleted on an Al2O3 support in up to nine amount levels. As an efficient tool for high-throughput screening and perfectly matched to the requirements of heterogeneous gas phase catalysis - especially for applications technically run in honeycomb structures - the multi-channel monolith reactor is implemented to evaluate the catalyst performances. Out of a multi-component feed-gas, the conversion rates of carbon monoxide (CO) and a model hydrocarbon (HC) are monitored in parallel. In combination with further restrictions to preparation and pre-treatment a primary screening can be conducted, promising to provide results close to technically applied catalysts. Presented are the resulting performances of the optimisation process for the first catalyst generations and the prospect of its auto-adaptation to specified optimisation goals.

A Closed-Loop Optimal Neural-Network Controller to Optimize Rotorcraft Aeromechanical Behaviour. Volume 1; Theory and Methodology

NASA Technical Reports Server (NTRS)

Leyland, Jane Anne

2001-01-01

Given the predicted growth in air transportation, the potential exists for significant market niches for rotary wing subsonic vehicles. Technological advances which optimise rotorcraft aeromechanical behaviour can contribute significantly to both their commercial and military development, acceptance, and sales. Examples of the optimisation of rotorcraft aeromechanical behaviour which are of interest include the minimisation of vibration and/or loads. The reduction of rotorcraft vibration and loads is an important means to extend the useful life of the vehicle and to improve its ride quality. Although vibration reduction can be accomplished by using passive dampers and/or tuned masses, active closed-loop control has the potential to reduce vibration and loads throughout a.wider flight regime whilst requiring less additional weight to the aircraft man that obtained by using passive methads. It is ernphasised that the analysis described herein is applicable to all those rotorcraft aeromechanical behaviour optimisation problems for which the relationship between the harmonic control vector and the measurement vector can be adequately described by a neural-network model.

Determination of optimal ultrasound planes for the initialisation of image registration during endoscopic ultrasound-guided procedures.

PubMed

Bonmati, Ester; Hu, Yipeng; Gibson, Eli; Uribarri, Laura; Keane, Geri; Gurusami, Kurinchi; Davidson, Brian; Pereira, Stephen P; Clarkson, Matthew J; Barratt, Dean C

2018-06-01

Navigation of endoscopic ultrasound (EUS)-guided procedures of the upper gastrointestinal (GI) system can be technically challenging due to the small fields-of-view of ultrasound and optical devices, as well as the anatomical variability and limited number of orienting landmarks during navigation. Co-registration of an EUS device and a pre-procedure 3D image can enhance the ability to navigate. However, the fidelity of this contextual information depends on the accuracy of registration. The purpose of this study was to develop and test the feasibility of a simulation-based planning method for pre-selecting patient-specific EUS-visible anatomical landmark locations to maximise the accuracy and robustness of a feature-based multimodality registration method. A registration approach was adopted in which landmarks are registered to anatomical structures segmented from the pre-procedure volume. The predicted target registration errors (TREs) of EUS-CT registration were estimated using simulated visible anatomical landmarks and a Monte Carlo simulation of landmark localisation error. The optimal planes were selected based on the 90th percentile of TREs, which provide a robust and more accurate EUS-CT registration initialisation. The method was evaluated by comparing the accuracy and robustness of registrations initialised using optimised planes versus non-optimised planes using manually segmented CT images and simulated ([Formula: see text]) or retrospective clinical ([Formula: see text]) EUS landmarks. The results show a lower 90th percentile TRE when registration is initialised using the optimised planes compared with a non-optimised initialisation approach (p value [Formula: see text]). The proposed simulation-based method to find optimised EUS planes and landmarks for EUS-guided procedures may have the potential to improve registration accuracy. Further work will investigate applying the technique in a clinical setting.

Calibration and simulation of two large wastewater treatment plants operated for nutrient removal.

PubMed

Ferrer, J; Morenilla, J J; Bouzas, A; García-Usach, F

2004-01-01

Control and optimisation of plant processes has become a priority for WWTP managers. The calibration and verification of a mathematical model provides an important tool for the investigation of advanced control strategies that may assist in the design or optimization of WWTPs. This paper describes the calibration of the ASM2d model for two full scale biological nitrogen and phosphorus removal plants in order to characterize the biological process and to upgrade the plants' performance. Results from simulation showed a good correspondence with experimental data demonstrating that the model and the calibrated parameters were able to predict the behaviour of both WWTPs. Once the calibration and simulation process was finished, a study for each WWTP was done with the aim of improving its performance. Modifications focused on reactor configuration and operation strategies were proposed.

[The role of multidisciplinary tumor board discussions in treatment decisions].

PubMed

Jerusalem, G; Coucke, P

2011-01-01

The diagnosis and treatment of cancer is complex. Multidisciplinary tumor board discussions optimise the care of patients suffering from cancer. The most promising and rational treatment is chosen taking into account the opinion from all participants. Quality of life is important if only a palliative approach can be offered. The final decision concerning the treatment will be taken by the patient because he/she has the right to refuse the best treatment for personal reasons.

Efficacy of an Optimised Bacteriophage Cocktail to Clear Clostridium difficile in a Batch Fermentation Model

PubMed Central

Nale, Janet Y.; Redgwell, Tamsin A.; Millard, Andrew; Clokie, Martha R. J.

2018-01-01

Clostridium difficile infection (CDI) is a major cause of infectious diarrhea. Conventional antibiotics are not universally effective for all ribotypes, and can trigger dysbiosis, resistance and recurrent infection. Thus, novel therapeutics are needed to replace and/or supplement the current antibiotics. Here, we describe the activity of an optimised 4-phage cocktail to clear cultures of a clinical ribotype 014/020 strain in fermentation vessels spiked with combined fecal slurries from four healthy volunteers. After 5 h, we observed ~6-log reductions in C. difficile abundance in the prophylaxis regimen and complete C. difficile eradication after 24 h following prophylactic or remedial regimens. Viability assays revealed that commensal enterococci, bifidobacteria, lactobacilli, total anaerobes, and enterobacteria were not affected by either regimens, but a ~2-log increase in the enterobacteria, lactobacilli, and total anaerobe abundance was seen in the phage-only-treated vessel compared to other treatments. The impact of the phage treatments on components of the microbiota was further assayed using metagenomic analysis. Together, our data supports the therapeutic application of our optimised phage cocktail to treat CDI. Also, the increase in specific commensals observed in the phage-treated control could prevent further colonisation of C. difficile, and thus provide protection from infection being able to establish. PMID:29438355

Simulation studies promote technological development of radiofrequency phased array hyperthermia.

PubMed

Wust, P; Seebass, M; Nadobny, J; Deuflhard, P; Mönich, G; Felix, R

1996-01-01

A treatment planning program package for radiofrequency hyperthermia has been developed. It consists of software modules for processing three-dimensional computerized tomography (CT) data sets, manual segmentation, generation of tetrahedral grids, numerical calculation and optimisation of three-dimensional E field distributions using a volume surface integral equation algorithm as well as temperature distributions using an adaptive multilevel finite-elements code, and graphical tools for simultaneous representation of CT data and simulation results. Heat treatments are limited by hot spots in healthy tissues caused by E field maxima at electrical interfaces (bone/muscle). In order to reduce or avoid hot spots suitable objective functions are derived from power deposition patterns and temperature distributions, and are utilised to optimise antenna parameters (phases, amplitudes). The simulation and optimisation tools have been applied to estimate the improvements that could be reached by upgrades of the clinically used SIGMA-60 applicator (consisting of a single ring of four antenna pairs). The investigated upgrades are increased number of antennas and channels (triple-ring of 3 x 8 antennas and variation of antenna inclination. Significant improvement of index temperatures (1-2 degrees C) is achieved by upgrading the single ring to a triple ring with free phase selection for every antenna or antenna pair. Antenna amplitudes and inclinations proved as less important parameters.

Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction

PubMed Central

O'Boyle, Noel M; Palmer, David S; Nigsch, Florian; Mitchell, John BO

2008-01-01

Background We present a novel feature selection algorithm, Winnowing Artificial Ant Colony (WAAC), that performs simultaneous feature selection and model parameter optimisation for the development of predictive quantitative structure-property relationship (QSPR) models. The WAAC algorithm is an extension of the modified ant colony algorithm of Shen et al. (J Chem Inf Model 2005, 45: 1024–1029). We test the ability of the algorithm to develop a predictive partial least squares model for the Karthikeyan dataset (J Chem Inf Model 2005, 45: 581–590) of melting point values. We also test its ability to perform feature selection on a support vector machine model for the same dataset. Results Starting from an initial set of 203 descriptors, the WAAC algorithm selected a PLS model with 68 descriptors which has an RMSE on an external test set of 46.6°C and R2 of 0.51. The number of components chosen for the model was 49, which was close to optimal for this feature selection. The selected SVM model has 28 descriptors (cost of 5, ε of 0.21) and an RMSE of 45.1°C and R2 of 0.54. This model outperforms a kNN model (RMSE of 48.3°C, R2 of 0.47) for the same data and has similar performance to a Random Forest model (RMSE of 44.5°C, R2 of 0.55). However it is much less prone to bias at the extremes of the range of melting points as shown by the slope of the line through the residuals: -0.43 for WAAC/SVM, -0.53 for Random Forest. Conclusion With a careful choice of objective function, the WAAC algorithm can be used to optimise machine learning and regression models that suffer from overfitting. Where model parameters also need to be tuned, as is the case with support vector machine and partial least squares models, it can optimise these simultaneously. The moving probabilities used by the algorithm are easily interpreted in terms of the best and current models of the ants, and the winnowing procedure promotes the removal of irrelevant descriptors. PMID:18959785

Mixing characterisation of full-scale membrane bioreactors: CFD modelling with experimental validation.

PubMed

Brannock, M; Wang, Y; Leslie, G

2010-05-01

Membrane Bioreactors (MBRs) have been successfully used in aerobic biological wastewater treatment to solve the perennial problem of effective solids-liquid separation. The optimisation of MBRs requires knowledge of the membrane fouling, biokinetics and mixing. However, research has mainly concentrated on the fouling and biokinetics (Ng and Kim, 2007). Current methods of design for a desired flow regime within MBRs are largely based on assumptions (e.g. complete mixing of tanks) and empirical techniques (e.g. specific mixing energy). However, it is difficult to predict how sludge rheology and vessel design in full-scale installations affects hydrodynamics, hence overall performance. Computational Fluid Dynamics (CFD) provides a method for prediction of how vessel features and mixing energy usage affect the hydrodynamics. In this study, a CFD model was developed which accounts for aeration, sludge rheology and geometry (i.e. bioreactor and membrane module). This MBR CFD model was then applied to two full-scale MBRs and was successfully validated against experimental results. The effect of sludge settling and rheology was found to have a minimal impact on the bulk mixing (i.e. the residence time distribution).

[Comparison of predictive models for the selection of high-complexity patients].

PubMed

Estupiñán-Ramírez, Marcos; Tristancho-Ajamil, Rita; Company-Sancho, María Consuelo; Sánchez-Janáriz, Hilda

2017-08-18

To compare the concordance of complexity weights between Clinical Risk Groups (CRG) and Adjusted Morbidity Groups (AMG). To determine which one is the best predictor of patient admission. To optimise the method used to select the 0.5% of patients of higher complexity that will be included in an intervention protocol. Cross-sectional analytical study in 18 Canary Island health areas, 385,049 citizens were enrolled, using sociodemographic variables from health cards; diagnoses and use of healthcare resources obtained from primary health care electronic records (PCHR) and the basic minimum set of hospital data; the functional status recorded in the PCHR, and the drugs prescribed through the electronic prescription system. The correlation between stratifiers was estimated from these data. The ability of each stratifier to predict patient admissions was evaluated and prediction optimisation models were constructed. Concordance between weights complexity stratifiers was strong (rho = 0.735) and the correlation between categories of complexity was moderate (weighted kappa = 0.515). AMG complexity weight predicts better patient admission than CRG (AUC: 0.696 [0.695-0.697] versus 0.692 [0.691-0.693]). Other predictive variables were added to the AMG weight, obtaining the best AUC (0.708 [0.707-0.708]) the model composed by AMG, sex, age, Pfeiffer and Barthel scales, re-admissions and number of prescribed therapeutic groups. strong concordance was found between stratifiers, and higher predictive capacity for admission from AMG, which can be increased by adding other dimensions. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Developing a musculoskeletal model of the primate skull: predicting muscle activations, bite force, and joint reaction forces using multibody dynamics analysis and advanced optimisation methods.

PubMed

Shi, Junfen; Curtis, Neil; Fitton, Laura C; O'Higgins, Paul; Fagan, Michael J

2012-10-07

An accurate, dynamic, functional model of the skull that can be used to predict muscle forces, bite forces, and joint reaction forces would have many uses across a broad range of disciplines. One major issue however with musculoskeletal analyses is that of muscle activation pattern indeterminacy. A very large number of possible muscle force combinations will satisfy a particular functional task. This makes predicting physiological muscle recruitment patterns difficult. Here we describe in detail the process of development of a complex multibody computer model of a primate skull (Macaca fascicularis), that aims to predict muscle recruitment patterns during biting. Using optimisation criteria based on minimisation of muscle stress we predict working to balancing side muscle force ratios, peak bite forces, and joint reaction forces during unilateral biting. Validation of such models is problematic; however we have shown comparable working to balancing muscle activity and TMJ reaction ratios during biting to those observed in vivo and that peak predicted bite forces compare well to published experimental data. To our knowledge the complexity of the musculoskeletal model is greater than any previously reported for a primate. This complexity, when compared to more simple representations provides more nuanced insights into the functioning of masticatory muscles. Thus, we have shown muscle activity to vary throughout individual muscle groups, which enables them to function optimally during specific masticatory tasks. This model will be utilised in future studies into the functioning of the masticatory apparatus. Copyright © 2012 Elsevier Ltd. All rights reserved.

The ALTTO Breast Cancer Trial

Cancer.gov

A collection of material about the Adjuvant Lapatinib And/Or Trastuzumab Treatment Optimisation, or ALTTO, study that will compare the targeted agents lapatinib and trastuzumab alone, in sequence, or in combination as adjuvant therapy for HER2-positive br

Hypertrophic scarring: the greatest unmet challenge following burn injury

PubMed Central

Finnerty, Celeste C; Jeschke, Marc G; Branski, Ludwik K; Barret, Juan P.; Dziewulski, Peter; Herndon, David N

2017-01-01

Summary Improvements in acute burn care have enabled patients to survive massive burns which would have once been fatal. Now up to 70% of patients develop hypertrophic scars following burns. The functional and psychosocial sequelae remain a major rehabilitative challenge, decreasing quality of life and delaying reintegration into society. The current approach is to optimise the healing potential of the burn wound using targeted wound care and surgery in order to minimise the development of hypertrophic scarring. This approach often fails, and modulation of established scar is continued although the optimal indication, timing, and combination of therapies have yet to be established. The need for novel treatments is paramount, and future efforts to improve outcomes and quality of life should include optimisation of wound healing to attenuate or prevent hypertrophic scarring, well-designed trials to confirm treatment efficacy, and further elucidation of molecular mechanisms to allow development of new preventative and therapeutic strategies. PMID:27707499

[Treatment of pubic osteomyelitis secondary to pressure sores].

PubMed

Brunel, Anne-Sophie; Téot, Luc; Lamy, Brigitte; Masson, Raphaël; Morquin, David; Reynes, Jacques; Le Moing, Vincent

2014-01-01

There is no consensus regarding the diagnostic and therapeutic strategy for pubic osteomyelitis secondary to pelvic pressure sores. Diagnosis is often difficult and bone biopsies with microbiological and anatomical-pathological examination remain the gold standard. The rate of cicatrisation of pressure sores is low. Cleansing and negative pressure treatment are key elements of the treatment. Optimising the care management with medical-surgical collaboration is being studied in the Ostear protocol.

Optimising molecular diagnostic capacity for effective control of tuberculosis in high-burden settings.

PubMed

Sabiiti, W; Mtafya, B; Kuchaka, D; Azam, K; Viegas, S; Mdolo, A; Farmer, E C W; Khonga, M; Evangelopoulos, D; Honeyborne, I; Rachow, A; Heinrich, N; Ntinginya, N E; Bhatt, N; Davies, G R; Jani, I V; McHugh, T D; Kibiki, G; Hoelscher, M; Gillespie, S H

2016-08-01

The World Health Organization's 2035 vision is to reduce tuberculosis (TB) associated mortality by 95%. While low-burden, well-equipped industrialised economies can expect to see this goal achieved, it is challenging in the low- and middle-income countries that bear the highest burden of TB. Inadequate diagnosis leads to inappropriate treatment and poor clinical outcomes. The roll-out of the Xpert(®) MTB/RIF assay has demonstrated that molecular diagnostics can produce rapid diagnosis and treatment initiation. Strong molecular services are still limited to regional or national centres. The delay in implementation is due partly to resources, and partly to the suggestion that such techniques are too challenging for widespread implementation. We have successfully implemented a molecular tool for rapid monitoring of patient treatment response to anti-tuberculosis treatment in three high TB burden countries in Africa. We discuss here the challenges facing TB diagnosis and treatment monitoring, and draw from our experience in establishing molecular treatment monitoring platforms to provide practical insights into successful optimisation of molecular diagnostic capacity in resource-constrained, high TB burden settings. We recommend a holistic health system-wide approach for molecular diagnostic capacity development, addressing human resource training, institutional capacity development, streamlined procurement systems, and engagement with the public, policy makers and implementers of TB control programmes.

Optimised mounting conditions for poly (ether sulfone) in radiation detection.

PubMed

Nakamura, Hidehito; Shirakawa, Yoshiyuki; Sato, Nobuhiro; Yamada, Tatsuya; Kitamura, Hisashi; Takahashi, Sentaro

2014-09-01

Poly (ether sulfone) (PES) is a candidate for use as a scintillation material in radiation detection. Its characteristics, such as its emission spectrum and its effective refractive index (based on the emission spectrum), directly affect the propagation of light generated to external photodetectors. It is also important to examine the presence of background radiation sources in manufactured PES. Here, we optimise the optical coupling and surface treatment of the PES, and characterise its background. Optical grease was used to enhance the optical coupling between the PES and the photodetector; absorption by the grease of short-wavelength light emitted from PES was negligible. Diffuse reflection induced by surface roughening increased the light yield for PES, despite the high effective refractive index. Background radiation derived from the PES sample and its impurities was negligible above the ambient, natural level. Overall, these results serve to optimise the mounting conditions for PES in radiation detection. Copyright © 2014 Elsevier Ltd. All rights reserved.

Optimising physical activity engagement during youth sport: a self-determination theory approach.

PubMed

Fenton, Sally A M; Duda, Joan L; Barrett, Timothy

2016-10-01

Research suggests participation in youth sport does not guarantee physical activity (PA) guidelines are met. Studies indicate few children achieve recommended levels of moderate-to-vigorous physical activity (MVPA) during their youth sport involvement, and habitual levels of MVPA are below the recommended 60 min per day. Informed by self-determination theory, this study examined whether the coach-created social environment and related player motivation predict variability in objectively measured MVPA within the youth sport setting. Seventy three male youth sport footballers (Mean age = 11.66 ± 1.62) completed a multisection questionnaire assessing their perceptions of the social environment created in youth sport (autonomy supportive and controlling) and motivation towards their football participation (autonomous and controlled). Intensity of PA during youth sport was measured using accelerometers (GT3X, ActiGraph). Results supported a model in which perceptions of autonomy support significantly and positively predicted autonomous motivation towards football, which in turn significantly and positively predicted youth sport MVPA (% time). A significant indirect effect was observed for perceptions of autonomy support on youth sport %MVPA via autonomous motivation. Results have implications for optimising MVPA engagement during youth sport and increasing daily MVPA towards recommended and health-enhancing levels on youth sport days.

CEINMS: A toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks.

PubMed

Pizzolato, Claudio; Lloyd, David G; Sartori, Massimo; Ceseracciu, Elena; Besier, Thor F; Fregly, Benjamin J; Reggiani, Monica

2015-11-05

Personalized neuromusculoskeletal (NMS) models can represent the neurological, physiological, and anatomical characteristics of an individual and can be used to estimate the forces generated inside the human body. Currently, publicly available software to calculate muscle forces are restricted to static and dynamic optimisation methods, or limited to isometric tasks only. We have created and made freely available for the research community the Calibrated EMG-Informed NMS Modelling Toolbox (CEINMS), an OpenSim plug-in that enables investigators to predict different neural control solutions for the same musculoskeletal geometry and measured movements. CEINMS comprises EMG-driven and EMG-informed algorithms that have been previously published and tested. It operates on dynamic skeletal models possessing any number of degrees of freedom and musculotendon units and can be calibrated to the individual to predict measured joint moments and EMG patterns. In this paper we describe the components of CEINMS and its integration with OpenSim. We then analyse how EMG-driven, EMG-assisted, and static optimisation neural control solutions affect the estimated joint moments, muscle forces, and muscle excitations, including muscle co-contraction. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Scenario-based, closed-loop model predictive control with application to emergency vehicle scheduling

NASA Astrophysics Data System (ADS)

Goodwin, Graham. C.; Medioli, Adrian. M.

2013-08-01

Model predictive control has been a major success story in process control. More recently, the methodology has been used in other contexts, including automotive engine control, power electronics and telecommunications. Most applications focus on set-point tracking and use single-sequence optimisation. Here we consider an alternative class of problems motivated by the scheduling of emergency vehicles. Here disturbances are the dominant feature. We develop a novel closed-loop model predictive control strategy aimed at this class of problems. We motivate, and illustrate, the ideas via the problem of fluid deployment of ambulance resources.

Development of a Gas Dynamic and Thermodynamic Simulation Model of the Lontra Blade Compressor™

NASA Astrophysics Data System (ADS)

Karlovsky, Jerome

2015-08-01

The Lontra Blade Compressor™ is a patented double acting, internally compressing, positive displacement rotary compressor of innovative design. The Blade Compressor is in production for waste-water treatment, and will soon be launched for a range of applications at higher pressure ratios. In order to aid the design and development process, a thermodynamic and gas dynamic simulation program has been written in house. The software has been successfully used to optimise geometries and running conditions of current designs, and is also being used to evaluate future designs for different applications and markets. The simulation code has three main elements. A positive displacement chamber model, a leakage model and a gas dynamic model to simulate gas flow through ports and to track pressure waves in the inlet and outlet pipes. All three of these models are interlinked in order to track mass and energy flows within the system. A correlation study has been carried out to verify the software. The main correlation markers used were mass flow, chamber pressure, pressure wave tracking in the outlet pipe, and volumetric efficiency. It will be shown that excellent correlation has been achieved between measured and simulated data. Mass flow predictions were to within 2% of measured data, and the timings and magnitudes of all major gas dynamic effects were well replicated. The simulation will be further developed in the near future to help with the optimisation of exhaust and inlet silencers.

A Demonstration using Low-kt Fatigue Specimens of a Method for Predicting the Fatigue Behaviour of Corroded Aircraft Components

DTIC Science & Technology

2013-03-01

This third random variable, with some optimisation, means that the second model can predict the mean and scatter of the observed fatigue lives. KIDS...Barishpolsky [65] studied this effect using a FE model of ellipsoidal voids and cracked or decohered ellipsoidal inclusions in an elastic body . They...Specifically, the first strike is long and thin, the second is square and the third is short and wide. Five centroid positions (d = 0, 30, 38 and

Application of response surface methodology to optimise microbial inactivation of shrimp and conch by supercritical carbon dioxide.

PubMed

Chen, Manhua; Sui, Xiao; Ma, Xixiu; Feng, Xiaomei; Han, Yuqian

2015-03-30

Supercritical carbon dioxide (SC-CO2 ) has been shown to have a good pasteurising effect on food. However, very few research papers have investigated the possibility to exploit this treatment for solid foods, particularly for seafood. Considering the microbial safety of raw seafood consumption, the study aimed to explore the feasibility of microbial inactivation of shrimp (Metapenaeus ensis) and conch (Rapana venosa) by SC-CO2 treatment. Response surface methodology (RSM) models were established to predict and analyse the SC-CO2 process. A 3.69-log reduction in the total aerobic plate count (TPC) of shrimp was observed by SC-CO2 treatment at 53°C, 15 MPa for 40 min, and the logarithmic reduction in TPC of conch was 3.31 at 55°C, 14 MPa for 42 min. Sensory scores of the products achieved approximately 8 (desirable). The optimal parameters for microbial inactivation of shrimp and conch by SC-CO2 might be 55°C, 15 MPa and 40 min. SC-CO2 exerted a strong bactericidal effect on the TPC of shrimp and conch, and the products maintained good organoleptic properties. This study verified the feasibility of microbial inactivation of shrimp and conch by SC-CO2 treatment. © 2014 Society of Chemical Industry.

Predicting the timing of second praziquantel treatment and its effect on reduction of egg counts in southern Ghana.

PubMed

Nsowah-Nuamah, N N N; Aryeetey, M E; Jolayemi, E T; Wagatsuma, Y; Mensah, G; Dontwi, I K; Nkrumah, F K; Kojima, S

2004-05-01

Schistosoma haematobium infection could be associated with morbidity. Generally, the cost of schistosomiasis control is high and it becomes a burden for governments or non-governmental organisations to repeat control programs so as to reduce morbidity. There is therefore, the need to optimise the available meagre resources for its control. From 1993 to 1997 the Noguchi Memorial Institute for Medical Research of the University of Ghana carried out a schistosomiasis control program in southern Ghana. Using the generated data, an attempt is made to determine the timing of the second praziquantel treatment and the period needed after the second chemotherapy to have egg counts reduced to low levels in southern Ghana. It was revealed that the second praziquantel treatment in areas 1, 2, and 3 should be administered latest at 13.8, 11.8 and 13.2 months, respectively after the first one. Most importantly, it takes 24.4 months to bring egg counts to zero in area 3 while in area 1, it takes about 29 months after the second praziquantel treatment. Egg counts were not reduced to zero in area 2 after the second chemotherapy. At least passive health education and continuous safe water supply should support the chemotherapy in addition to weed removal at the water contact sites.

Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses.

PubMed

Bisele, Maria; Bencsik, Martin; Lewis, Martin G C; Barnett, Cleveland T

2017-01-01

Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a specific machine learning algorithm for processing human locomotion data. Twenty participants ran at a self-selected speed across a 15m runway in barefoot and shod conditions. Ground reaction forces (BW) and kinematics were measured at 1000 Hz and 100 Hz, respectively from which joint angles (°), joint moments (N.m.kg-1) and joint powers (W.kg-1) for the hip, knee and ankle joints were calculated in all three anatomical planes. Using PCA and DFA, power spectra of the kinematic and kinetic variables were used as a training database for the development of a machine learning algorithm. All possible combinations of 10 out of 20 participants were explored to find the iteration of individuals that would optimise the machine learning algorithm. The results showed that the algorithm was able to successfully predict whether a participant ran shod or barefoot in 93.5% of cases. To the authors' knowledge, this is the first study to optimise the development of a machine learning algorithm.

Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses

PubMed Central

Bisele, Maria; Bencsik, Martin; Lewis, Martin G. C.

2017-01-01

Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a specific machine learning algorithm for processing human locomotion data. Twenty participants ran at a self-selected speed across a 15m runway in barefoot and shod conditions. Ground reaction forces (BW) and kinematics were measured at 1000 Hz and 100 Hz, respectively from which joint angles (°), joint moments (N.m.kg-1) and joint powers (W.kg-1) for the hip, knee and ankle joints were calculated in all three anatomical planes. Using PCA and DFA, power spectra of the kinematic and kinetic variables were used as a training database for the development of a machine learning algorithm. All possible combinations of 10 out of 20 participants were explored to find the iteration of individuals that would optimise the machine learning algorithm. The results showed that the algorithm was able to successfully predict whether a participant ran shod or barefoot in 93.5% of cases. To the authors’ knowledge, this is the first study to optimise the development of a machine learning algorithm. PMID:28886059

Optimisation of dispersion parameters of Gaussian plume model for CO₂ dispersion.

PubMed

Liu, Xiong; Godbole, Ajit; Lu, Cheng; Michal, Guillaume; Venton, Philip

2015-11-01

The carbon capture and storage (CCS) and enhanced oil recovery (EOR) projects entail the possibility of accidental release of carbon dioxide (CO2) into the atmosphere. To quantify the spread of CO2 following such release, the 'Gaussian' dispersion model is often used to estimate the resulting CO2 concentration levels in the surroundings. The Gaussian model enables quick estimates of the concentration levels. However, the traditionally recommended values of the 'dispersion parameters' in the Gaussian model may not be directly applicable to CO2 dispersion. This paper presents an optimisation technique to obtain the dispersion parameters in order to achieve a quick estimation of CO2 concentration levels in the atmosphere following CO2 blowouts. The optimised dispersion parameters enable the Gaussian model to produce quick estimates of CO2 concentration levels, precluding the necessity to set up and run much more complicated models. Computational fluid dynamics (CFD) models were employed to produce reference CO2 dispersion profiles in various atmospheric stability classes (ASC), different 'source strengths' and degrees of ground roughness. The performance of the CFD models was validated against the 'Kit Fox' field measurements, involving dispersion over a flat horizontal terrain, both with low and high roughness regions. An optimisation model employing a genetic algorithm (GA) to determine the best dispersion parameters in the Gaussian plume model was set up. Optimum values of the dispersion parameters for different ASCs that can be used in the Gaussian plume model for predicting CO2 dispersion were obtained.

A meta-model based approach for rapid formability estimation of continuous fibre reinforced components

NASA Astrophysics Data System (ADS)

Zimmerling, Clemens; Dörr, Dominik; Henning, Frank; Kärger, Luise

2018-05-01

Due to their high mechanical performance, continuous fibre reinforced plastics (CoFRP) become increasingly important for load bearing structures. In many cases, manufacturing CoFRPs comprises a forming process of textiles. To predict and optimise the forming behaviour of a component, numerical simulations are applied. However, for maximum part quality, both the geometry and the process parameters must match in mutual regard, which in turn requires numerous numerically expensive optimisation iterations. In both textile and metal forming, a lot of research has focused on determining optimum process parameters, whilst regarding the geometry as invariable. In this work, a meta-model based approach on component level is proposed, that provides a rapid estimation of the formability for variable geometries based on pre-sampled, physics-based draping data. Initially, a geometry recognition algorithm scans the geometry and extracts a set of doubly-curved regions with relevant geometry parameters. If the relevant parameter space is not part of an underlying data base, additional samples via Finite-Element draping simulations are drawn according to a suitable design-table for computer experiments. Time saving parallel runs of the physical simulations accelerate the data acquisition. Ultimately, a Gaussian Regression meta-model is built from the data base. The method is demonstrated on a box-shaped generic structure. The predicted results are in good agreement with physics-based draping simulations. Since evaluations of the established meta-model are numerically inexpensive, any further design exploration (e.g. robustness analysis or design optimisation) can be performed in short time. It is expected that the proposed method also offers great potential for future applications along virtual process chains: For each process step along the chain, a meta-model can be set-up to predict the impact of design variations on manufacturability and part performance. Thus, the method is considered to facilitate a lean and economic part and process design under consideration of manufacturing effects.

A proteinuria cut-off level of 0.7 g/day after 12 months of treatment best predicts long-term renal outcome in lupus nephritis: data from the MAINTAIN Nephritis Trial

PubMed Central

Tamirou, Farah; Lauwerys, Bernard R; Dall'Era, Maria; Mackay, Meggan; Rovin, Brad; Cervera, Ricard; Houssiau, Frédéric A

2015-01-01

Background Although an early decrease in proteinuria has been correlated with good long-term renal outcome in lupus nephritis (LN), studies aimed at defining a cut-off proteinuria value are missing, except a recent analysis performed on patients randomised in the Euro-Lupus Nephritis Trial, demonstrating that a target value of 0.8 g/day at month 12 optimised sensitivity and specificity for the prediction of good renal outcome. The objective of the current work is to validate this target in another LN study, namely the MAINTAIN Nephritis Trial (MNT). Methods Long-term (at least 7 years) renal function data were available for 90 patients randomised in the MNT. Receiver operating characteristic curves were built to test the performance of proteinuria measured within the 1st year as short-term predictor of long-term renal outcome. We calculated the positive and negative predictive values (PPV, NPV). Results After 12 months of treatment, achievement of a proteinuria <0.7 g/day best predicted good renal outcome, with a sensitivity and a specificity of 71% and 75%, respectively. The PPV was high (94%) but the NPV low (29%). Addition of the requirement of urine red blood cells ≤5/hpf as response criteria at month 12 reduced sensitivity from 71% to 41%. Conclusions In this cohort of mainly Caucasian patients suffering from a first episode of LN in most cases, achievement of a proteinuria <0.7 g/day at month 12 best predicts good outcome at 7 years and inclusion of haematuria in the set of criteria at month 12 undermines the sensitivity of early proteinuria decrease for the prediction of good outcome. The robustness of these conclusions stems from the very similar results obtained in two distinct LN cohorts. Trial registration number: NCT00204022. PMID:26629352

Computational prediction of multidisciplinary team decision-making for adjuvant breast cancer drug therapies: a machine learning approach.

PubMed

Lin, Frank P Y; Pokorny, Adrian; Teng, Christina; Dear, Rachel; Epstein, Richard J

2016-12-01

Multidisciplinary team (MDT) meetings are used to optimise expert decision-making about treatment options, but such expertise is not digitally transferable between centres. To help standardise medical decision-making, we developed a machine learning model designed to predict MDT decisions about adjuvant breast cancer treatments. We analysed MDT decisions regarding adjuvant systemic therapy for 1065 breast cancer cases over eight years. Machine learning classifiers with and without bootstrap aggregation were correlated with MDT decisions (recommended, not recommended, or discussable) regarding adjuvant cytotoxic, endocrine and biologic/targeted therapies, then tested for predictability using stratified ten-fold cross-validations. The predictions so derived were duly compared with those based on published (ESMO and NCCN) cancer guidelines. Machine learning more accurately predicted adjuvant chemotherapy MDT decisions than did simple application of guidelines. No differences were found between MDT- vs. ESMO/NCCN- based decisions to prescribe either adjuvant endocrine (97%, p = 0.44/0.74) or biologic/targeted therapies (98%, p = 0.82/0.59). In contrast, significant discrepancies were evident between MDT- and guideline-based decisions to prescribe chemotherapy (87%, p < 0.01, representing 43% and 53% variations from ESMO/NCCN guidelines, respectively). Using ten-fold cross-validation, the best classifiers achieved areas under the receiver operating characteristic curve (AUC) of 0.940 for chemotherapy (95% C.I., 0.922-0.958), 0.899 for the endocrine therapy (95% C.I., 0.880-0.918), and 0.977 for trastuzumab therapy (95% C.I., 0.955-0.999) respectively. Overall, bootstrap aggregated classifiers performed better among all evaluated machine learning models. A machine learning approach based on clinicopathologic characteristics can predict MDT decisions about adjuvant breast cancer drug therapies. The discrepancy between MDT- and guideline-based decisions regarding adjuvant chemotherapy implies that certain non-clincopathologic criteria, such as patient preference and resource availability, are factored into clinical decision-making by local experts but not captured by guidelines.

Improving linear transport infrastructure efficiency by automated learning and optimised predictive maintenance techniques (INFRALERT)

NASA Astrophysics Data System (ADS)

Jiménez-Redondo, Noemi; Calle-Cordón, Alvaro; Kandler, Ute; Simroth, Axel; Morales, Francisco J.; Reyes, Antonio; Odelius, Johan; Thaduri, Aditya; Morgado, Joao; Duarte, Emmanuele

2017-09-01

The on-going H2020 project INFRALERT aims to increase rail and road infrastructure capacity in the current framework of increased transportation demand by developing and deploying solutions to optimise maintenance interventions planning. It includes two real pilots for road and railways infrastructure. INFRALERT develops an ICT platform (the expert-based Infrastructure Management System, eIMS) which follows a modular approach including several expert-based toolkits. This paper presents the methodologies and preliminary results of the toolkits for i) nowcasting and forecasting of asset condition, ii) alert generation, iii) RAMS & LCC analysis and iv) decision support. The results of these toolkits in a meshed road network in Portugal under the jurisdiction of Infraestruturas de Portugal (IP) are presented showing the capabilities of the approaches.

An intelligent factory-wide optimal operation system for continuous production process

NASA Astrophysics Data System (ADS)

Ding, Jinliang; Chai, Tianyou; Wang, Hongfeng; Wang, Junwei; Zheng, Xiuping

2016-03-01

In this study, a novel intelligent factory-wide operation system for a continuous production process is designed to optimise the entire production process, which consists of multiple units; furthermore, this system is developed using process operational data to avoid the complexity of mathematical modelling of the continuous production process. The data-driven approach aims to specify the structure of the optimal operation system; in particular, the operational data of the process are used to formulate each part of the system. In this context, the domain knowledge of process engineers is utilised, and a closed-loop dynamic optimisation strategy, which combines feedback, performance prediction, feed-forward, and dynamic tuning schemes into a framework, is employed. The effectiveness of the proposed system has been verified using industrial experimental results.

[Cheyne-Stokes respiration and cardiovascular risk].

PubMed

Duchna, H-W; Schultze-Werninghaus, G

2009-07-01

Due to its high prevalence in patients with heart failure and its negative predictive value concerning morbidity and mortality, Cheyne-Stokes respiration (CSR) is a sleep disorders of major interest. CSR correlates with the degree of heart failure and is characterised by a typical crescendo/decrescendo breathing pattern combined with phases of central sleep apnoea, caused by pulmonary oedema and oscillation of ventilatory control. Thus, CSR is a marker of the severity of heart failure. Treatment of CSR first involves optimisation of heart failure therapy by cardiologists and then application of non-invasive means of ventilatory support. Treatment of patients with severe heart failure with non-invasive positive pressure ventilatory support leads to a significant reduction of CSR, sympathetic activity, and daytime sleepiness and improves cardiac output and 6-minute walking distance. At present, a prospective randomised, controlled intervention-study (Serve-HF study) is being conducted in order to show if therapy of CSR can improve patient survival. This review describes the pathophysiology, epidemiology, and therapeutic options of CSR with a special focus on the elevated cardiovascular risk of patients with CSR.

Extraction of gelatin from salmon (Salmo salar) fish skin using trypsin-aided process: optimization by Plackett-Burman and response surface methodological approaches.

PubMed

Fan, HuiYin; Dumont, Marie-Josée; Simpson, Benjamin K

2017-11-01

Gelatin from salmon ( Salmo salar ) skin with high molecular weight protein chains ( α -chains) was extracted using trypsin-aided process. Response surface methodology was used to optimise the extraction parameters. Yield, hydroxyproline content and protein electrophoretic profile via sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis of gelatin were used as responses in the optimization study. The optimum conditions were determined as: trypsin concentration at 1.49 U/g; extraction temperature at 45 °C; and extraction time at 6 h 16 min. This response surface optimized model was significant and produced an experimental value (202.04 ± 8.64%) in good agreement with the predicted value (204.19%). Twofold higher yields of gelatin with high molecular weight protein chains were achieved in the optimized process with trypsin treatment when compared to the process without trypsin.

Treatment options for moderate-to-very severe chronic obstructive pulmonary disease.

PubMed

Cazzola, Mario; Rogliani, Paola; Ora, Josuel; Matera, Maria Gabriella

2016-01-01

The appropriate drug management of COPD is still based on the use of bronchodilators, possibly associated with an anti-inflammatory agent. However, there are still fundamental questions that require clarification to optimise their use and major unmet clinical needs that must be addressed. The advances obtained with the pharmacological options currently consolidated and the different approaches that are often used in an attempt to respond to unmet therapeutic needs are reviewed Expert opinion: In view of the unsatisfactory status of current treatments for COPD, there is an urgent need for alternative and more effective therapeutic approaches that will help to relieve patient symptoms and affect the natural course of COPD, inhibiting chronic inflammation and reversing the disease process or preventing its progression. However, new pharmacologic options have proved difficult to develop. Therefore, it is mandatory to optimize the use of the treatment options at our disposal. However, there are still fundamental questions regarding their use, including the step-up and step-down pharmacological approach, that require clarification to optimise the use of these drugs. It is likely that phenotyping COPD patients would help in identifying the right treatment for each COPD patient and improve the effectiveness of therapies.

CONTRACT Study - CONservative TReatment of Appendicitis in Children (feasibility): study protocol for a randomised controlled Trial.

PubMed

Hutchings, Natalie; Wood, Wendy; Reading, Isabel; Walker, Erin; Blazeby, Jane M; Van't Hoff, William; Young, Bridget; Crawley, Esther M; Eaton, Simon; Chorozoglou, Maria; Sherratt, Frances C; Beasant, Lucy; Corbett, Harriet; Stanton, Michael P; Grist, Simon; Dixon, Elizabeth; Hall, Nigel J

2018-03-02

Currently, the routine treatment for acute appendicitis in the United Kingdom is an appendicectomy. However, there is increasing scientific interest and research into non-operative treatment of appendicitis in adults and children. While a number of studies have investigated non-operative treatment of appendicitis in adults, this research cannot be applied to the paediatric population. Ultimately, we aim to perform a UK-based multicentre randomised controlled trial (RCT) to test the clinical and cost effectiveness of non-operative treatment of acute uncomplicated appendicitis in children, as compared with appendicectomy. First, we will undertake a feasibility study to assess the feasibility of performing such a trial. The study involves a feasibility RCT with a nested qualitative research to optimise recruitment as well as a health economic substudy. Children (aged 4-15 years inclusive) diagnosed with acute uncomplicated appendicitis that would normally be treated with an appendicectomy are eligible for the RCT. Exclusion criteria include clinical/radiological suspicion of perforated appendicitis, appendix mass or previous non-operative treatment of appendicitis. Participants will be randomised into one of two arms. Participants in the intervention arm are treated with antibiotics and regular clinical assessment to ensure clinical improvement. Participants in the control arm will receive appendicectomy. Randomisation will be minimised by age, sex, duration of symptoms and centre. Children and families who are approached for the RCT will be invited to participate in the embedded qualitative substudy, which includes recording of recruitment consultants and subsequent interviews with participants and non-participants and their families and recruiters. Analyses of these will inform interventions to optimise recruitment. The main study outcomes include recruitment rate (primary outcome), identification of strategies to optimise recruitment, performance of trial treatment pathways, clinical outcomes and safety of non-operative treatment. We have involved children, young people and parents in study design and delivery. In this study we will explore the feasibility of performing a full efficacy RCT comparing non-operative treatment with appendicectomy in children with acute uncomplicated appendicitis. Factors determining success of the present study include recruitment rate, safety of non-operative treatment and adequate interest in the future RCT. Ultimately this feasibility study will form the foundation of the main RCT and reinforce its design. ISRCTN15830435 . Registered on 8 February 2017.

[Global management of patients with ebola viral disease, experience of the Healthcare workers Treatment of Conakry, Guinea].

PubMed

Savini, H; Maugey, N; Aletti, M; Facon, A; Koulibaly, F; Cotte, J; Janvier, F; Cordier, P Y; Dampierre, H; Ramade, S; Foissaud, V; Granier, H; Sagui, E; Carmoi, T

2016-10-01

The Healthcare Workers Treatment Center of Conakry, Guinea, was inaugurated in january 2015. It is dedicated to the diagnosis and the treatment of healthcare workers with probable or confirmed Ebola viral disease. It is staffed by the french army medical service. The french military team may reconcile their medical practice and the ethno-cultural imperatives to optimise the patient adherence during his hospitalization.

Using genetic algorithms to optimise current and future health planning--the example of ambulance locations.

PubMed

Sasaki, Satoshi; Comber, Alexis J; Suzuki, Hiroshi; Brunsdon, Chris

2010-01-28

Ambulance response time is a crucial factor in patient survival. The number of emergency cases (EMS cases) requiring an ambulance is increasing due to changes in population demographics. This is decreasing ambulance response times to the emergency scene. This paper predicts EMS cases for 5-year intervals from 2020, to 2050 by correlating current EMS cases with demographic factors at the level of the census area and predicted population changes. It then applies a modified grouping genetic algorithm to compare current and future optimal locations and numbers of ambulances. Sets of potential locations were evaluated in terms of the (current and predicted) EMS case distances to those locations. Future EMS demands were predicted to increase by 2030 using the model (R2 = 0.71). The optimal locations of ambulances based on future EMS cases were compared with current locations and with optimal locations modelled on current EMS case data. Optimising the location of ambulance stations locations reduced the average response times by 57 seconds. Current and predicted future EMS demand at modelled locations were calculated and compared. The reallocation of ambulances to optimal locations improved response times and could contribute to higher survival rates from life-threatening medical events. Modelling EMS case 'demand' over census areas allows the data to be correlated to population characteristics and optimal 'supply' locations to be identified. Comparing current and future optimal scenarios allows more nuanced planning decisions to be made. This is a generic methodology that could be used to provide evidence in support of public health planning and decision making.

On the Performance of Alternate Conceptual Ecohydrological Models for Streamflow Prediction

NASA Astrophysics Data System (ADS)

Naseem, Bushra; Ajami, Hoori; Cordery, Ian; Sharma, Ashish

2016-04-01

A merging of a lumped conceptual hydrological model with two conceptual dynamic vegetation models is presented to assess the performance of these models for simultaneous simulations of streamflow and leaf area index (LAI). Two conceptual dynamic vegetation models with differing representation of ecological processes are merged with a lumped conceptual hydrological model (HYMOD) to predict catchment scale streamflow and LAI. The merged RR-LAI-I model computes relative leaf biomass based on transpiration rates while the RR-LAI-II model computes above ground green and dead biomass based on net primary productivity and water use efficiency in response to soil moisture dynamics. To assess the performance of these models, daily discharge and 8-day MODIS LAI product for 27 catchments of 90 - 1600km2 in size located in the Murray - Darling Basin in Australia are used. Our results illustrate that when single-objective optimisation was focussed on maximizing the objective function for streamflow or LAI, the other un-calibrated predicted outcome (LAI if streamflow is the focus) was consistently compromised. Thus, single-objective optimization cannot take into account the essence of all processes in the conceptual ecohydrological models. However, multi-objective optimisation showed great strength for streamflow and LAI predictions. Both response outputs were better simulated by RR-LAI-II than RR-LAI-I due to better representation of physical processes such as net primary productivity (NPP) in RR-LAI-II. Our results highlight that simultaneous calibration of streamflow and LAI using a multi-objective algorithm proves to be an attractive tool for improved streamflow predictions.

A general structure-property relationship to predict the enthalpy of vaporisation at ambient temperatures.

PubMed

Oberg, T

2007-01-01

The vapour pressure is the most important property of an anthropogenic organic compound in determining its partitioning between the atmosphere and the other environmental media. The enthalpy of vaporisation quantifies the temperature dependence of the vapour pressure and its value around 298 K is needed for environmental modelling. The enthalpy of vaporisation can be determined by different experimental methods, but estimation methods are needed to extend the current database and several approaches are available from the literature. However, these methods have limitations, such as a need for other experimental results as input data, a limited applicability domain, a lack of domain definition, and a lack of predictive validation. Here we have attempted to develop a quantitative structure-property relationship (QSPR) that has general applicability and is thoroughly validated. Enthalpies of vaporisation at 298 K were collected from the literature for 1835 pure compounds. The three-dimensional (3D) structures were optimised and each compound was described by a set of computationally derived descriptors. The compounds were randomly assigned into a calibration set and a prediction set. Partial least squares regression (PLSR) was used to estimate a low-dimensional QSPR model with 12 latent variables. The predictive performance of this model, within the domain of application, was estimated at n=560, q2Ext=0.968 and s=0.028 (log transformed values). The QSPR model was subsequently applied to a database of 100,000+ structures, after a similar 3D optimisation and descriptor generation. Reliable predictions can be reported for compounds within the previously defined applicability domain.

Building in efficacy: developing solutions to combat drug-resistant S. pneumoniae.

PubMed

Jacobs, M R

2004-04-01

The development of our understanding of the pharmacokinetic (PK) and pharmacodynamic (PD) principles that determine antimicrobial efficacy has advanced substantially over the last 10 years. We are now in a position to use PK/PD principles to set targets for antimicrobial design and optimisation so that we can predict eradication of specific pathogens or resistant variants when agents are used clinically. Optimisation of PK/PD parameters to enable the treatment of resistant pathogens with oral agents may not be possible with many current agents, such as some cephalosporins, macrolides and fluoroquinolones. Aminopenicillins, however, such as amoxicillin, have linear PK and have a good safety profile even at high doses. The new pharmacokinetically enhanced oral formulation of amoxicillin/clavulanate, 2000/125 mg twice daily, was designed using PK/PD principles to be able to eradicate Streptococcus pneumoniae with amoxicillin MICs of up to and including 4 mg/L, which includes most penicillin-resistant isolates. For amoxicillin and amoxicillin/clavulanate, a time above MIC (T > MIC) of 35-40% of the dosing interval (based on blood levels) is predictive of high bacteriological efficacy. This target was met by the design of a unique bilayer tablet incorporating 437.5 mg of sustained-release sodium amoxicillin in one layer plus 562.5 mg of immediate-release amoxicillin trihydrate and 62.5 mg of clavulanate potassium in the second layer, with two tablets administered for each dose. This unique design extends the bacterial killing time by increasing the T > MIC to 49% of the dosing interval against pathogens with MICs of 4 mg/L, and 60% of the dosing interval against pathogens with MICs of 2 mg/L. Based on these results, this new amoxicillin/clavulanate formulation should be highly effective in treating respiratory tract infections due to drug-resistant S. pneumoniae as well as beta-lactamase-producing pathogens, such as Haemophilus influenzae and Moraxella catarrhalis.

Optimising the production of succinate and lactate in Escherichia coli using a hybrid of artificial bee colony algorithm and minimisation of metabolic adjustment.

PubMed

Tang, Phooi Wah; Choon, Yee Wen; Mohamad, Mohd Saberi; Deris, Safaai; Napis, Suhaimi

2015-03-01

Metabolic engineering is a research field that focuses on the design of models for metabolism, and uses computational procedures to suggest genetic manipulation. It aims to improve the yield of particular chemical or biochemical products. Several traditional metabolic engineering methods are commonly used to increase the production of a desired target, but the products are always far below their theoretical maximums. Using numeral optimisation algorithms to identify gene knockouts may stall at a local minimum in a multivariable function. This paper proposes a hybrid of the artificial bee colony (ABC) algorithm and the minimisation of metabolic adjustment (MOMA) to predict an optimal set of solutions in order to optimise the production rate of succinate and lactate. The dataset used in this work was from the iJO1366 Escherichia coli metabolic network. The experimental results include the production rate, growth rate and a list of knockout genes. From the comparative analysis, ABCMOMA produced better results compared to previous works, showing potential for solving genetic engineering problems. Copyright © 2014 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Formulation of multiparticulate systems as lyophilised orally disintegrating tablets.

PubMed

Alhusban, Farhan; Perrie, Yvonne; Mohammed, Afzal R

2011-11-01

The current study aimed to exploit the electrostatic associative interaction between carrageenan and gelatin to optimise a formulation of lyophilised orally disintegrating tablets (ODTs) suitable for multiparticulate delivery. A central composite face centred (CCF) design was applied to study the influence of formulation variables (gelatin, carrageenan and alanine concentrations) on the crucial responses of the formulation (disintegration time, hardness, viscosity and pH). The disintegration time and viscosity were controlled by the associative interaction between gelatin and carrageenan upon hydration which forms a strong complex that increases the viscosity of the stock solution and forms tablet with higher resistant to disintegration in aqueous medium. Therefore, the levels of carrageenan, gelatin and their interaction in the formulation were the significant factors. In terms of hardness, increasing gelatin and alanine concentration was the most effective way to improve tablet hardness. Accordingly, optimum concentrations of these excipients were needed to find the best balance that fulfilled all formulation requirements. The revised model showed high degree of predictability and optimisation reliability and therefore was successful in developing an ODT formulation with optimised properties that were able deliver enteric coated multiparticulates of omeprazole without compromising their functionality. Copyright © 2011 Elsevier B.V. All rights reserved.

A novel probabilistic approach to generating PTV with partial voxel contributions

NASA Astrophysics Data System (ADS)

Tsang, H. S.; Kamerling, C. P.; Ziegenhein, P.; Nill, S.; Oelfke, U.

2017-06-01

Radiotherapy treatment planning for use with high-energy photon beams currently employs a binary approach in defining the planning target volume (PTV). We propose a margin concept that takes the beam directions into account, generating beam-dependent PTVs (bdPTVs) on a beam-by-beam basis. The resulting degree of overlaps between the bdPTVs are used within the optimisation process; the optimiser effectively considers the same voxel to be both target and organ at risk (OAR) with fractional contributions. We investigate the impact of this novel approach when applied to prostate radiotherapy treatments, and compare treatment plans generated using beam dependent margins to conventional margins. Five prostate patients were used in this planning study, and plans using beam dependent margins improved the sparing of high doses to target-surrounding OARs, though a trade-off in delivering additional low dose to the OARs can be observed. Plans using beam dependent margins are observed to have a slightly reduced target coverage. Nevertheless, all plans are able to satisfy 90% population coverage with the target receiving at least 95% of the prescribed dose to D98% .

Optimising the dichotomy limit for left ventricular ejection fraction in selecting patients for defibrillator therapy after myocardial infarction.

PubMed

Yap, Yee Guan; Duong, Trinh; Bland, J Martin; Malik, Marek; Torp-Pedersen, Christian; Køber, Lars; Gallagher, Mark M; Camm, A John

2007-07-01

The selection of patients for prophylactic implantable cardioverter-defibrilator (ICD) treatment after myocardial infarction (MI) remains controversial. To determine the optimum left ventricular ejection fraction (LVEF) dichotomy limit for ICD treatment in patients with a history of MI. Data from the placebo arms of four randomised trials were pooled to create a cohort of 2828 patients (2206 men, mean (SD) age 65 (11) years) with reduced left ventricular function after MI. The median LVEF was 33% (range 6-40%). LVEF significantly predicted mortality. Each 10% reduction in LVEF <40% conferred a 42% increase in all-cause mortality, a 39% increase in arrhythmic cardiac mortality and a 49% increase in non-arrhythmic cardiac mortality over the 2-year period of follow-up (p<0.001 for all modes of mortality). As the LVEF progressively decreased from < or =40% to < or =10%, the data show a U-shaped relationship between the dichotomy limit for LVEF used and the number of patients who must be treated to prevent one arrhythmic death in 2 years. At an LVEF of 16-20%, more patients are likely to die from arrhythmic than non-arrhythmic cardiac deaths, whereas in those with LVEF < or =10% all deaths were non-arrhythmic. However, the total number of deaths substantially decreased with lower LVEF. A trade-off exists between the sensitivity and positive predictive accuracy across a range of LVEF, and no single dichotomy limit is completely satisfactory. In patients with LVEF < or =10% ICD treatment was not beneficial as all patients in this subgroup died from non-arrhythmic causes. The use of a single dichotomy limit for LVEF alone is not sufficient in selecting patients for ICD treatment in the primary prevention of cardiac arrest.

Formulation and optimisation of raft-forming chewable tablets containing H2 antagonist

PubMed Central

Prajapati, Shailesh T; Mehta, Anant P; Modhia, Ishan P; Patel, Chhagan N

2012-01-01

Purpose: The purpose of this research work was to formulate raft-forming chewable tablets of H2 antagonist (Famotidine) using a raft-forming agent along with an antacid- and gas-generating agent. Materials and Methods: Tablets were prepared by wet granulation and evaluated for raft strength, acid neutralisation capacity, weight variation, % drug content, thickness, hardness, friability and in vitro drug release. Various raft-forming agents were used in preliminary screening. A 23 full-factorial design was used in the present study for optimisation. The amount of sodium alginate, amount of calcium carbonate and amount sodium bicarbonate were selected as independent variables. Raft strength, acid neutralisation capacity and drug release at 30 min were selected as responses. Results: Tablets containing sodium alginate were having maximum raft strength as compared with other raft-forming agents. Acid neutralisation capacity and in vitro drug release of all factorial batches were found to be satisfactory. The F5 batch was optimised based on maximum raft strength and good acid neutralisation capacity. Drug–excipient compatibility study showed no interaction between the drug and excipients. Stability study of the optimised formulation showed that the tablets were stable at accelerated environmental conditions. Conclusion: It was concluded that raft-forming chewable tablets prepared using an optimum amount of sodium alginate, calcium carbonate and sodium bicarbonate could be an efficient dosage form in the treatment of gastro oesophageal reflux disease. PMID:23580933

Formulation and optimisation of raft-forming chewable tablets containing H2 antagonist.

PubMed

Prajapati, Shailesh T; Mehta, Anant P; Modhia, Ishan P; Patel, Chhagan N

2012-10-01

The purpose of this research work was to formulate raft-forming chewable tablets of H2 antagonist (Famotidine) using a raft-forming agent along with an antacid- and gas-generating agent. Tablets were prepared by wet granulation and evaluated for raft strength, acid neutralisation capacity, weight variation, % drug content, thickness, hardness, friability and in vitro drug release. Various raft-forming agents were used in preliminary screening. A 2(3) full-factorial design was used in the present study for optimisation. The amount of sodium alginate, amount of calcium carbonate and amount sodium bicarbonate were selected as independent variables. Raft strength, acid neutralisation capacity and drug release at 30 min were selected as responses. Tablets containing sodium alginate were having maximum raft strength as compared with other raft-forming agents. Acid neutralisation capacity and in vitro drug release of all factorial batches were found to be satisfactory. The F5 batch was optimised based on maximum raft strength and good acid neutralisation capacity. Drug-excipient compatibility study showed no interaction between the drug and excipients. Stability study of the optimised formulation showed that the tablets were stable at accelerated environmental conditions. It was concluded that raft-forming chewable tablets prepared using an optimum amount of sodium alginate, calcium carbonate and sodium bicarbonate could be an efficient dosage form in the treatment of gastro oesophageal reflux disease.

Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions

PubMed Central

Lim, Kian Sheng; Ibrahim, Zuwairie; Buyamin, Salinda; Ahmad, Anita; Naim, Faradila; Ghazali, Kamarul Hawari; Mokhtar, Norrima

2013-01-01

The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm. PMID:23737718

Improving Vector Evaluated Particle Swarm Optimisation by incorporating nondominated solutions.

PubMed

Lim, Kian Sheng; Ibrahim, Zuwairie; Buyamin, Salinda; Ahmad, Anita; Naim, Faradila; Ghazali, Kamarul Hawari; Mokhtar, Norrima

2013-01-01

The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm.

Optimising intratumoral treatment of head and neck squamous cell carcinoma models with the diterpene ester Tigilanol tiglate.

PubMed

Barnett, Catherine M E; Broit, Natasa; Yap, Pei-Yi; Cullen, Jason K; Parsons, Peter G; Panizza, Benedict J; Boyle, Glen M

2018-04-18

The five-year survival rate for patients with head and neck squamous cell carcinoma (HNSCC) has remained at ~50% for the past 30 years despite advances in treatment. Tigilanol tiglate (TT, also known as EBC-46) is a novel diterpene ester that induces cell death in HNSCC in vitro and in mouse models, and has recently completed Phase I human clinical trials. The aim of this study was to optimise efficacy of TT treatment by altering different administration parameters. The tongue SCC cell line (SCC-15) was identified as the line with the lowest efficacy to treatment. Subcutaneous xenografts of SCC-15 cells were grown in BALB/c Foxn1 nu and NOD/SCID mice and treated with intratumoral injection of 30 μg TT or a vehicle only control (40% propylene glycol (PG)). Greater efficacy of TT treatment was found in the BALB/c Foxn1 nu mice compared to NOD/SCID mice. Immunohistochemical analysis indicated a potential role of the host's innate immune system in this difference, specifically neutrophil infiltration. Neither fractionated doses of TT nor the use of a different excipiant led to significantly increased efficacy. This study confirmed that TT in 40% PG given intratumorally as a single bolus dose was the most efficacious treatment for a tongue SCC mouse model.

Updated systematic review and meta-analysis of the performance of risk prediction rules in children and young people with febrile neutropenia.

PubMed

Phillips, Robert S; Lehrnbecher, Thomas; Alexander, Sarah; Sung, Lillian

2012-01-01

Febrile neutropenia is a common and potentially life-threatening complication of treatment for childhood cancer, which has increasingly been subject to targeted treatment based on clinical risk stratification. Our previous meta-analysis demonstrated 16 rules had been described and 2 of them subject to validation in more than one study. We aimed to advance our knowledge of evidence on the discriminatory ability and predictive accuracy of such risk stratification clinical decision rules (CDR) for children and young people with cancer by updating our systematic review. The review was conducted in accordance with Centre for Reviews and Dissemination methods, searching multiple electronic databases, using two independent reviewers, formal critical appraisal with QUADAS and meta-analysis with random effects models where appropriate. It was registered with PROSPERO: CRD42011001685. We found 9 new publications describing a further 7 new CDR, and validations of 7 rules. Six CDR have now been subject to testing across more than two data sets. Most validations demonstrated the rule to be less efficient than when initially proposed; geographical differences appeared to be one explanation for this. The use of clinical decision rules will require local validation before widespread use. Considerable uncertainty remains over the most effective rule to use in each population, and an ongoing individual-patient-data meta-analysis should develop and test a more reliable CDR to improve stratification and optimise therapy. Despite current challenges, we believe it will be possible to define an internationally effective CDR to harmonise the treatment of children with febrile neutropenia.

Updated Systematic Review and Meta-Analysis of the Performance of Risk Prediction Rules in Children and Young People with Febrile Neutropenia

PubMed Central

Phillips, Robert S.; Lehrnbecher, Thomas; Alexander, Sarah; Sung, Lillian

2012-01-01

Introduction Febrile neutropenia is a common and potentially life-threatening complication of treatment for childhood cancer, which has increasingly been subject to targeted treatment based on clinical risk stratification. Our previous meta-analysis demonstrated 16 rules had been described and 2 of them subject to validation in more than one study. We aimed to advance our knowledge of evidence on the discriminatory ability and predictive accuracy of such risk stratification clinical decision rules (CDR) for children and young people with cancer by updating our systematic review. Methods The review was conducted in accordance with Centre for Reviews and Dissemination methods, searching multiple electronic databases, using two independent reviewers, formal critical appraisal with QUADAS and meta-analysis with random effects models where appropriate. It was registered with PROSPERO: CRD42011001685. Results We found 9 new publications describing a further 7 new CDR, and validations of 7 rules. Six CDR have now been subject to testing across more than two data sets. Most validations demonstrated the rule to be less efficient than when initially proposed; geographical differences appeared to be one explanation for this. Conclusion The use of clinical decision rules will require local validation before widespread use. Considerable uncertainty remains over the most effective rule to use in each population, and an ongoing individual-patient-data meta-analysis should develop and test a more reliable CDR to improve stratification and optimise therapy. Despite current challenges, we believe it will be possible to define an internationally effective CDR to harmonise the treatment of children with febrile neutropenia. PMID:22693615

Development of a perfusion reversed-phase high performance liquid chromatography method for the characterisation of maize products using multivariate analysis.

PubMed

Rodriguez-Nogales, J M; Garcia, M C; Marina, M L

2006-02-03

A perfusion reversed-phase high performance liquid chromatography (RP-HPLC) method has been designed to allow rapid (3.4 min) separations of maize proteins with high resolution. Several factors, such as extraction conditions, temperature, detection wavelength and type and concentration of ion-pairing agent were optimised. A fine optimisation of the gradient elution was also performed by applying experimental design. Commercial maize products for human consumption (flours, precocked flours, fried snacks and extruded snacks) were characterised for the first time by perfusion RP-HPLC and their chromatographic profiles allowed a differentiation among products relating the different technological process used for their preparation. Furthermore, applying discriminant analysis makes it possible to group the samples according with the technological process suffered by maize products, obtaining a good prediction in 92% of the samples.

Metric optimisation for analogue forecasting by simulated annealing

NASA Astrophysics Data System (ADS)

Bliefernicht, J.; Bárdossy, A.

2009-04-01

It is well known that weather patterns tend to recur from time to time. This property of the atmosphere is used by analogue forecasting techniques. They have a long history in weather forecasting and there are many applications predicting hydrological variables at the local scale for different lead times. The basic idea of the technique is to identify past weather situations which are similar (analogue) to the predicted one and to take the local conditions of the analogues as forecast. But the forecast performance of the analogue method depends on user-defined criteria like the choice of the distance function and the size of the predictor domain. In this study we propose a new methodology of optimising both criteria by minimising the forecast error with simulated annealing. The performance of the methodology is demonstrated for the probability forecast of daily areal precipitation. It is compared with a traditional analogue forecasting algorithm, which is used operational as an element of a hydrological forecasting system. The study is performed for several meso-scale catchments located in the Rhine basin in Germany. The methodology is validated by a jack-knife method in a perfect prognosis framework for a period of 48 years (1958-2005). The predictor variables are derived from the NCEP/NCAR reanalysis data set. The Brier skill score and the economic value are determined to evaluate the forecast skill and value of the technique. In this presentation we will present the concept of the optimisation algorithm and the outcome of the comparison. It will be also demonstrated how a decision maker should apply a probability forecast to maximise the economic benefit from it.

Variability estimation of urban wastewater biodegradable fractions by respirometry.

PubMed

Lagarde, Fabienne; Tusseau-Vuillemin, Marie-Hélène; Lessard, Paul; Héduit, Alain; Dutrop, François; Mouchel, Jean-Marie

2005-11-01

This paper presents a methodology for assessing the variability of biodegradable chemical oxygen demand (COD) fractions in urban wastewaters. Thirteen raw wastewater samples from combined and separate sewers feeding the same plant were characterised, and two optimisation procedures were applied in order to evaluate the variability in biodegradable fractions and related kinetic parameters. Through an overall optimisation on all the samples, a unique kinetic parameter set was obtained with a three-substrate model including an adsorption stage. This method required powerful numerical treatment, but improved the identifiability problem compared to the usual sample-to-sample optimisation. The results showed that the fractionation of samples collected in the combined sewer was much more variable (standard deviation of 70% of the mean values) than the fractionation of the separate sewer samples, and the slowly biodegradable COD fraction was the most significant fraction (45% of the total COD on average). Because these samples were collected under various rain conditions, the standard deviations obtained here on the combined sewer biodegradable fractions could be used as a first estimation of the variability of this type of sewer system.

Optimising text messaging to improve adherence to web-based smoking cessation treatment: a randomised control trial protocol

PubMed Central

Graham, Amanda L; Jacobs, Megan A; Cohn, Amy M; Cha, Sarah; Abroms, Lorien C; Papandonatos, George D; Whittaker, Robyn

2016-01-01

Introduction Millions of smokers use the Internet for smoking cessation assistance each year; however, most smokers engage minimally with even the best designed websites. The ubiquity of mobile devices and their effectiveness in promoting adherence in other areas of health behaviour change make them a promising tool to address adherence in Internet smoking cessation interventions. Text messaging is used by most adults, and messages can proactively encourage use of a web-based intervention. Text messaging can also be integrated with an Internet intervention to facilitate the use of core Internet intervention components. Methods and analysis We identified four aspects of a text message intervention that may enhance its effectiveness in promoting adherence to a web-based smoking cessation programme: personalisation, integration, dynamic tailoring and message intensity. Phase I will use a two-level full factorial design to test the impact of these four experimental features on adherence to a web-based intervention. The primary outcome is a composite metric of adherence that incorporates general utilisation metrics (eg, logins, page views) and specific feature utilisation shown to predict abstinence. Participants will be N=860 adult smokers who register on an established Internet cessation programme and enrol in its text message programme. Phase II will be a two-arm randomised trial to compare the efficacy of the web-based cessation programme alone and in conjunction with the optimised text messaging intervention on 30-day point prevalence abstinence at 9 months. Phase II participants will be N=600 adult smokers who register to use an established Internet cessation programme and enrol in text messaging. Secondary analyses will explore whether adherence mediates the effect of treatment condition on outcome. Ethics and dissemination This protocol was approved by Chesapeake IRB. We will disseminate study results through peer-reviewed manuscripts and conference presentations related to the methods and design, outcomes and exploratory analyses. Trial registration number NCT02585206. PMID:27029775

Rapid diagnostic pathways for suspected colorectal cancer: views of primary and secondary care clinicians on challenges and their potential solutions

PubMed Central

Redaniel, Maria Theresa; Ridd, Matthew; Martin, Richard M; Coxon, Fareeda; Jeffreys, Mona; Wade, Julia

2015-01-01

Objectives To ascertain the challenges associated with implementation of the 2-week wait referral criteria and waiting time targets for colorectal cancer and to identify recommendations for improvements to the pathway. Design Qualitative research using semistructured interviews and applying thematic analysis using the method of constant comparison. Setting 10 primary care surgeries and 6 secondary care centres from 3 geographical areas in the England. Participants Purposive sample of 24 clinicians (10 general practitioners (GPs), 7 oncologists and 7 colorectal surgeons). Results GPs and specialists highlighted delays in patient help-seeking, difficulties applying the colorectal cancer referral criteria due to their low predictive value, and concerns about the stringent application of targets because of potential impact on individual care and associated penalties for breaching. Promoting patient awareness and early presentation, clarifying predictive symptoms, allowing flexibility, optimising resources and maximising care coordination were suggested as improvements. Conclusions Challenges during diagnosis and treatment persist, with guidelines and waiting time targets producing the perception of unintended harms at individual and organisational levels. This has led to variations in how guidelines are implemented. These require urgent evaluation, so that effective practices can be adopted more widely. PMID:26493457

Artemether-lumefantrine dosing for malaria treatment in young children and pregnant women: A pharmacokinetic-pharmacodynamic meta-analysis.

PubMed

Kloprogge, Frank; Workman, Lesley; Borrmann, Steffen; Tékété, Mamadou; Lefèvre, Gilbert; Hamed, Kamal; Piola, Patrice; Ursing, Johan; Kofoed, Poul Erik; Mårtensson, Andreas; Ngasala, Billy; Björkman, Anders; Ashton, Michael; Friberg Hietala, Sofia; Aweeka, Francesca; Parikh, Sunil; Mwai, Leah; Davis, Timothy M E; Karunajeewa, Harin; Salman, Sam; Checchi, Francesco; Fogg, Carole; Newton, Paul N; Mayxay, Mayfong; Deloron, Philippe; Faucher, Jean François; Nosten, François; Ashley, Elizabeth A; McGready, Rose; van Vugt, Michele; Proux, Stephane; Price, Ric N; Karbwang, Juntra; Ezzet, Farkad; Bakshi, Rajesh; Stepniewska, Kasia; White, Nicholas J; Guerin, Philippe J; Barnes, Karen I; Tarning, Joel

2018-06-01

The fixed dose combination of artemether-lumefantrine (AL) is the most widely used treatment for uncomplicated Plasmodium falciparum malaria. Relatively lower cure rates and lumefantrine levels have been reported in young children and in pregnant women during their second and third trimester. The aim of this study was to investigate the pharmacokinetic and pharmacodynamic properties of lumefantrine and the pharmacokinetic properties of its metabolite, desbutyl-lumefantrine, in order to inform optimal dosing regimens in all patient populations. A search in PubMed, Embase, ClinicalTrials.gov, Google Scholar, conference proceedings, and the WorldWide Antimalarial Resistance Network (WWARN) pharmacology database identified 31 relevant clinical studies published between 1 January 1990 and 31 December 2012, with 4,546 patients in whom lumefantrine concentrations were measured. Under the auspices of WWARN, relevant individual concentration-time data, clinical covariates, and outcome data from 4,122 patients were made available and pooled for the meta-analysis. The developed lumefantrine population pharmacokinetic model was used for dose optimisation through in silico simulations. Venous plasma lumefantrine concentrations 7 days after starting standard AL treatment were 24.2% and 13.4% lower in children weighing <15 kg and 15-25 kg, respectively, and 20.2% lower in pregnant women compared with non-pregnant adults. Lumefantrine exposure decreased with increasing pre-treatment parasitaemia, and the dose limitation on absorption of lumefantrine was substantial. Simulations using the lumefantrine pharmacokinetic model suggest that, in young children and pregnant women beyond the first trimester, lengthening the dose regimen (twice daily for 5 days) and, to a lesser extent, intensifying the frequency of dosing (3 times daily for 3 days) would be more efficacious than using higher individual doses in the current standard treatment regimen (twice daily for 3 days). The model was developed using venous plasma data from patients receiving intact tablets with fat, and evaluations of alternative dosing regimens were consequently only representative for venous plasma after administration of intact tablets with fat. The absence of artemether-dihydroartemisinin data limited the prediction of parasite killing rates and recrudescent infections. Thus, the suggested optimised dosing schedule was based on the pharmacokinetic endpoint of lumefantrine plasma exposure at day 7. Our findings suggest that revised AL dosing regimens for young children and pregnant women would improve drug exposure but would require longer or more complex schedules. These dosing regimens should be evaluated in prospective clinical studies to determine whether they would improve cure rates, demonstrate adequate safety, and thereby prolong the useful therapeutic life of this valuable antimalarial treatment.

Design of optimised backstepping controller for the synchronisation of chaotic Colpitts oscillator using shark smell algorithm

NASA Astrophysics Data System (ADS)

Fouladi, Ehsan; Mojallali, Hamed

2018-01-01

In this paper, an adaptive backstepping controller has been tuned to synchronise two chaotic Colpitts oscillators in a master-slave configuration. The parameters of the controller are determined using shark smell optimisation (SSO) algorithm. Numerical results are presented and compared with those of particle swarm optimisation (PSO) algorithm. Simulation results show better performance in terms of accuracy and convergence for the proposed optimised method compared to PSO optimised controller or any non-optimised backstepping controller.

Identification of Trypanocidal Activity for Known Clinical Compounds Using a New Trypanosoma cruzi Hit-Discovery Screening Cascade.

PubMed

De Rycker, Manu; Thomas, John; Riley, Jennifer; Brough, Stephen J; Miles, Tim J; Gray, David W

2016-04-01

Chagas disease is a significant health problem in Latin America and the available treatments have significant issues in terms of toxicity and efficacy. There is thus an urgent need to develop new treatments either via a repurposing strategy or through the development of new chemical entities. A key first step is the identification of compounds with anti-Trypanosoma cruzi activity from compound libraries. Here we describe a hit discovery screening cascade designed to specifically identify hits that have the appropriate anti-parasitic properties to warrant further development. The cascade consists of a primary imaging-based assay followed by newly developed and appropriately scaled secondary assays to predict the cidality and rate-of-kill of the compounds. Finally, we incorporated a cytochrome P450 CYP51 biochemical assay to remove compounds that owe their phenotypic response to inhibition of this enzyme. We report the use of the cascade in profiling two small libraries containing clinically tested compounds and identify Clemastine, Azelastine, Ifenprodil, Ziprasidone and Clofibrate as molecules having appropriate profiles. Analysis of clinical derived pharmacokinetic and toxicity data indicates that none of these are appropriate for repurposing but they may represent suitable start points for further optimisation for the treatment of Chagas disease.

Energy efficiency in membrane bioreactors.

PubMed

Barillon, B; Martin Ruel, S; Langlais, C; Lazarova, V

2013-01-01

Energy consumption remains the key factor for the optimisation of the performance of membrane bioreactors (MBRs). This paper presents the results of the detailed energy audits of six full-scale MBRs operated by Suez Environnement in France, Spain and the USA based on on-site energy measurement and analysis of plant operation parameters and treatment performance. Specific energy consumption is compared for two different MBR configurations (flat sheet and hollow fibre membranes) and for plants with different design, loads and operation parameters. The aim of this project was to understand how the energy is consumed in MBR facilities and under which operating conditions, in order to finally provide guidelines and recommended practices for optimisation of MBR operation and design to reduce energy consumption and environmental impacts.

Investigating the Trade-Off Between Power Generation and Environmental Impact of Tidal-Turbine Arrays Using Array Layout Optimisation and Habitat Sustainability Modelling.

NASA Astrophysics Data System (ADS)

du Feu, R. J.; Funke, S. W.; Kramer, S. C.; Hill, J.; Piggott, M. D.

2016-12-01

The installation of tidal turbines into the ocean will inevitably affect the environment around them. However, due to the relative infancy of this sector the extent and severity of such effects is unknown. The layout of an array of turbines is an important factor in determining not only the array's final yield but also how it will influence regional hydrodynamics. This in turn could affect, for example, sediment transportation or habitat suitability. The two potentially competing objectives of extracting energy from the tidal current, and of limiting any environmental impact consequent to influencing that current, are investigated here. This relationship is posed as a multi-objective optimisation problem. OpenTidalFarm, an array layout optimisation tool, and MaxEnt, habitat sustainability modelling software, are used to evaluate scenarios off the coast of the UK. MaxEnt is used to estimate the likelihood of finding a species in a given location based upon environmental input data and presence data of the species. Environmental features which are known to impact habitat, specifically those affected by the presence of an array, such as bed shear stress, are chosen as inputs. MaxEnt then uses a maximum-entropy modelling approach to estimate population distribution across the modelled area. OpenTidalFarm is used to maximise the power generated by an array, or multiple arrays, through adjusting the position and number of turbines within them. It uses a 2D shallow water model with turbine arrays represented as adjustable friction fields. It has the capability to also optimise for user created functionals that can be expressed mathematically. This work uses two functionals; power extracted by the array, and the suitability of habitat as predicted by MaxEnt. A gradient-based local optimisation is used to adjust the array layout at each iteration. This work presents arrays that are optimised for both yield and the viability of habitat for chosen species. In each scenario studied, a range of array formations is found expressing varying preferences for either functional. Further analyses then allow for the identification of trade-offs between the two key societal objectives of energy production and conservation. This in turn produces information valuable to stakeholders and policymakers when making decisions on array design.

Voxel-wise prostate cell density prediction using multiparametric magnetic resonance imaging and machine learning.

PubMed

Sun, Yu; Reynolds, Hayley M; Wraith, Darren; Williams, Scott; Finnegan, Mary E; Mitchell, Catherine; Murphy, Declan; Haworth, Annette

2018-04-26

There are currently no methods to estimate cell density in the prostate. This study aimed to develop predictive models to estimate prostate cell density from multiparametric magnetic resonance imaging (mpMRI) data at a voxel level using machine learning techniques. In vivo mpMRI data were collected from 30 patients before radical prostatectomy. Sequences included T2-weighted imaging, diffusion-weighted imaging and dynamic contrast-enhanced imaging. Ground truth cell density maps were computed from histology and co-registered with mpMRI. Feature extraction and selection were performed on mpMRI data. Final models were fitted using three regression algorithms including multivariate adaptive regression spline (MARS), polynomial regression (PR) and generalised additive model (GAM). Model parameters were optimised using leave-one-out cross-validation on the training data and model performance was evaluated on test data using root mean square error (RMSE) measurements. Predictive models to estimate voxel-wise prostate cell density were successfully trained and tested using the three algorithms. The best model (GAM) achieved a RMSE of 1.06 (± 0.06) × 10 3 cells/mm 2 and a relative deviation of 13.3 ± 0.8%. Prostate cell density can be quantitatively estimated non-invasively from mpMRI data using high-quality co-registered data at a voxel level. These cell density predictions could be used for tissue classification, treatment response evaluation and personalised radiotherapy.

Improving primary treatment of urban wastewater with lime-induced coagulation.

PubMed

Marani, Dario; Ramadori, Roberto; Braguglia, Camilla Maria

2004-01-01

The enhancement of primary treatment efficiency through the coagulation process may yield several advantages, including lower aeration energy in the subsequent biological unit and higher recovery of biogas from sludge digestion. In this work sewage coagulation with lime was studied at pilot plant level, using degritted sewage from the city of Rome. The work aimed at optimising the operating conditions (coagulant dosage or treatment pH, and mixing conditions in the coagulation and flocculation tanks), in order to maximise the efficiency of suspended Chemical Oxygen Demand (COD) removal and to minimise sludge production. Lime dosage optimisation resulted in an optimal treatment pH of 9. Lime addition up to pH 9 may increase COD removal rate in the primary treatment from typical 30-35% of plain sedimentation up to 55-70%. Within the velocity gradients experimented in this work (314-795 s(-1) for the coagulation tank and 13-46 s(-1) for the flocculation tank), mixing conditions did not significantly affect the lime-enhanced process, which seems to be controlled by slow lime dissolution. Sludge produced in the lime-enhanced process settled and compacted easily, inducing an average 36% decrease in sludge volume with respect to plain settling. However excess sludge was produced, which was not accounted for by the amount of suspended solids removed. This is probably due to incomplete dissolution of lime, which may be partially incorporated in the sludge.

Challenges and Potential Solutions – Individualised Antibiotic Dosing at the Bedside for Critically Ill Patients: a structured review

PubMed Central

Roberts, Jason A.; Aziz, Mohd Hafiz Abdul; Lipman, Jeffrey; Mouton, Johan W.; Vinks, Alexander A.; Felton, Timothy W.; Hope, William W.; Farkas, Andras; Neely, Michael N.; Schentag, Jerome J.; Drusano, George; Frey, Otto R.; Theuretzbacher, Ursula; Kuti, Joseph L.

2014-01-01

Summary Infections in critically ill patients are associated with persistently poor clinical outcomes. These patients have severely altered and variable antibiotic pharmacokinetics and are infected by less susceptible pathogens. Antibiotic dosing that does not account for these features is likely to result in sub-optimal outcomes. In this paper, we review the patient- and pathogen-related challenges that contribute to inadequate antibiotic dosing and discuss how a process for individualised antibiotic therapy, that increases the accuracy of dosing, can be implemented to further optimise care for the critically ill patient. The process for optimised antibiotic dosing firstly requires determination of the physiological derangements in the patient that can alter antibiotic concentrations including altered fluid status, microvascular failure, serum albumin concentrations as well as altered renal and hepatic function. Secondly, knowledge of the susceptibility of the infecting pathogen should be determined through liaison with the microbiology laboratory. The patient and pathogen challenges can then be solved by combining susceptibility data with measured antibiotic concentration data (where possible) into a clinical dosing software. Such software uses pharmacokinetic-pharmacodynamic (PK/PD) models from critically ill patients to accurately predict the dosing requirements for the individual patient with the aim of optimising antibiotic exposure and maximising effectiveness. PMID:24768475

Optimisation of ultrasound-assisted osmotic dehydration of sweet potato (Ipomea batatas) using response surface methodology.

PubMed

Oladejo, Ayobami Olayemi; Ma, Haile

2016-08-01

Sweet potato is a highly nutritious tuber crop that is rich in β-carotene. Osmotic dehydration is a pretreatment method for drying of fruit and vegetables. Recently, ultrasound technology has been applied in food processing because of its numerous advantages which include time saving, little damage to the quality of the food. Thus, there is need to investigate and optimise the process parameters [frequency (20-50 kHz), time (10-30 min) and sucrose concentration (20-60% w/v)] for ultrasound-assisted osmotic dehydration of sweet potato using response surface methodology. The optimised values obtained were frequency of 33.93 kHz, time of 30 min and sucrose concentration of 35.69% (w/v) to give predicted values of 21.62, 4.40 and 17.23% for water loss, solid gain and weight reduction, respectively. The water loss and weight reduction increased when the ultrasound frequency increased from 20 to 35 kHz and then decreased as the frequency increased from 35 to 50 kHz. The results from this work show that low ultrasound frequency favours the osmotic dehydration of sweet potato and also reduces the use of raw material (sucrose) needed for the osmotic dehydration of sweet potato. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Optimisation of preparation conditions and properties of phytosterol liposome-encapsulating nattokinase.

PubMed

Dong, Xu-Yan; Kong, Fan-Pi; Yuan, Gang-You; Wei, Fang; Jiang, Mu-Lan; Li, Guang-Ming; Wang, Zhan; Zhao, Yuan-Di; Chen, Hong

2012-01-01

Phytosterol liposomes were prepared using the thin film method and used to encapsulate nattokinase (NK). In order to obtain a high encapsulation efficiency within the liposome, an orthogonal experiment (L9 (3)(4)) was applied to optimise the preparation conditions. The molar ratio of lecithin to phytosterols, NK activity and mass ratio of mannite to lecithin were the main factors that influenced the encapsulation efficiency of the liposomes. Based on the results of a single-factor test, these three factors were chosen for this study. We determined the optimum extraction conditions to be as follows: a molar ratio of lecithin to phytosterol of 2 : 1, NK activity of 2500 U mL⁻¹ and a mass ratio of mannite to lecithin of 3 : 1. Under these optimised conditions, an encapsulation efficiency of 65.25% was achieved, which agreed closely with the predicted result. Moreover, the zeta potential, size distribution and microstructure of the liposomes prepared were measured, and we found that the zeta potential was -51 ± 3 mV and the mean diameter was 194.1 nm. From the results of the scanning electron microscopy, we observed that the phytosterol liposomes were round and regular in shape and showed no aggregation.

A review of predictive coding algorithms.

PubMed

Spratling, M W

2017-03-01

Predictive coding is a leading theory of how the brain performs probabilistic inference. However, there are a number of distinct algorithms which are described by the term "predictive coding". This article provides a concise review of these different predictive coding algorithms, highlighting their similarities and differences. Five algorithms are covered: linear predictive coding which has a long and influential history in the signal processing literature; the first neuroscience-related application of predictive coding to explaining the function of the retina; and three versions of predictive coding that have been proposed to model cortical function. While all these algorithms aim to fit a generative model to sensory data, they differ in the type of generative model they employ, in the process used to optimise the fit between the model and sensory data, and in the way that they are related to neurobiology. Copyright © 2016 Elsevier Inc. All rights reserved.

A radiobiology-based inverse treatment planning method for optimisation of permanent l-125 prostate implants in focal brachytherapy

NASA Astrophysics Data System (ADS)

Haworth, Annette; Mears, Christopher; Betts, John M.; Reynolds, Hayley M.; Tack, Guido; Leo, Kevin; Williams, Scott; Ebert, Martin A.

2016-01-01

Treatment plans for ten patients, initially treated with a conventional approach to low dose-rate brachytherapy (LDR, 145 Gy to entire prostate), were compared with plans for the same patients created with an inverse-optimisation planning process utilising a biologically-based objective. The ‘biological optimisation’ considered a non-uniform distribution of tumour cell density through the prostate based on known and expected locations of the tumour. Using dose planning-objectives derived from our previous biological-model validation study, the volume of the urethra receiving 125% of the conventional prescription (145 Gy) was reduced from a median value of 64% to less than 8% whilst maintaining high values of TCP. On average, the number of planned seeds was reduced from 85 to less than 75. The robustness of plans to random seed displacements needs to be carefully considered when using contemporary seed placement techniques. We conclude that an inverse planning approach to LDR treatments, based on a biological objective, has the potential to maintain high rates of tumour control whilst minimising dose to healthy tissue. In future, the radiobiological model will be informed using multi-parametric MRI to provide a personalised medicine approach.

Quantitative structure activity relationships from optimised ab initio bond lengths: steroid binding affinity and antibacterial activity of nitrofuran derivatives

NASA Astrophysics Data System (ADS)

Smith, P. J.; Popelier, P. L. A.

2004-02-01

The present day abundance of cheap computing power enables the use of quantum chemical ab initio data in Quantitative Structure-Activity Relationships (QSARs). Optimised bond lengths are a new such class of descriptors, which we have successfully used previously in representing electronic effects in medicinal and ecological QSARs (enzyme inhibitory activity, hydrolysis rate constants and pKas). Here we use AM1 and HF/3-21G* bond lengths in conjunction with Partial Least Squares (PLS) and a Genetic Algorithm (GA) to predict the Corticosteroid-Binding Globulin (CBG) binding activity of the classic steroid data set, and the antibacterial activity of nitrofuran derivatives. The current procedure, which does not require molecular alignment, produces good r2 and q2 values. Moreover, it highlights regions in the common steroid skeleton deemed relevant to the active regions of the steroids and nitrofuran derivatives.

Simplex-centroid mixture formulation for optimised composting of kitchen waste.

PubMed

Abdullah, N; Chin, N L

2010-11-01

Composting is a good recycling method to fully utilise all the organic wastes present in kitchen waste due to its high nutritious matter within the waste. In this present study, the optimised mixture proportions of kitchen waste containing vegetable scraps (V), fish processing waste (F) and newspaper (N) or onion peels (O) were determined by applying the simplex-centroid mixture design method to achieve the desired initial moisture content and carbon-to-nitrogen (CN) ratio for effective composting process. The best mixture was at 48.5% V, 17.7% F and 33.7% N for blends with newspaper while for blends with onion peels, the mixture proportion was 44.0% V, 19.7% F and 36.2% O. The predicted responses from these mixture proportions fall in the acceptable limits of moisture content of 50% to 65% and CN ratio of 20-40 and were also validated experimentally. Copyright 2010 Elsevier Ltd. All rights reserved.

Kinetics in the real world: linking molecules, processes, and systems.

PubMed

Kohse-Höinghaus, Katharina; Troe, Jürgen; Grabow, Jens-Uwe; Olzmann, Matthias; Friedrichs, Gernot; Hungenberg, Klaus-Dieter

2018-04-25

Unravelling elementary steps, reaction pathways, and kinetic mechanisms is key to understanding the behaviour of many real-world chemical systems that span from the troposphere or even interstellar media to engines and process reactors. Recent work in chemical kinetics provides detailed information on the reactive changes occurring in chemical systems, often on the atomic or molecular scale. The optimisation of practical processes, for instance in combustion, catalysis, battery technology, polymerisation, and nanoparticle production, can profit from a sound knowledge of the underlying fundamental chemical kinetics. Reaction mechanisms can combine information gained from theory and experiments to enable the predictive simulation and optimisation of the crucial process variables and influences on the system's behaviour that may be exploited for both monitoring and control. Chemical kinetics, as one of the pillars of Physical Chemistry, thus contributes importantly to understanding and describing natural environments and technical processes and is becoming increasingly relevant for interactions in and with the real world.

Predictive Array Design. A method for sampling combinatorial chemistry library space.

PubMed

Lipkin, M J; Rose, V S; Wood, J

2002-01-01

A method, Predictive Array Design, is presented for sampling combinatorial chemistry space and selecting a subarray for synthesis based on the experimental design method of Latin Squares. The method is appropriate for libraries with three sites of variation. Libraries with four sites of variation can be designed using the Graeco-Latin Square. Simulated annealing is used to optimise the physicochemical property profile of the sub-array. The sub-array can be used to make predictions of the activity of compounds in the all combinations array if we assume each monomer has a relatively constant contribution to activity and that the activity of a compound is composed of the sum of the activities of its constitutive monomers.

AntiArthritis Therapies 2005.

PubMed

Braddock, Martin

2005-04-01

This meeting, hosted by Visiongain and B2B conferences, comprised approximately 35 delegates, predominantly from the pharmaceutical industry, and promoted interactive discussion. It covered a broad range of drug discovery and development activities, ranging from preclinical studies with compounds requiring further optimisation, through to launched drugs used in the treatment of arthritis today.

A Cluster-Randomised, Controlled Trial of the Impact of Cogmed Working Memory Training on Both Academic Performance and Regulation of Social, Emotional and Behavioural Challenges

ERIC Educational Resources Information Center

Hitchcock, Caitlin; Westwell, Martin S.

2017-01-01

Background: We explored whether school-based Cogmed Working Memory Training (CWMT) may optimise both academic and psychological outcomes at school. Training of executive control skills may form a novel approach to enhancing processes that predict academic achievement, such as task-related attention, and thereby academic performance, but also has…

Simultaneous data pre-processing and SVM classification model selection based on a parallel genetic algorithm applied to spectroscopic data of olive oils.

PubMed

Devos, Olivier; Downey, Gerard; Duponchel, Ludovic

2014-04-01

Classification is an important task in chemometrics. For several years now, support vector machines (SVMs) have proven to be powerful for infrared spectral data classification. However such methods require optimisation of parameters in order to control the risk of overfitting and the complexity of the boundary. Furthermore, it is established that the prediction ability of classification models can be improved using pre-processing in order to remove unwanted variance in the spectra. In this paper we propose a new methodology based on genetic algorithm (GA) for the simultaneous optimisation of SVM parameters and pre-processing (GENOPT-SVM). The method has been tested for the discrimination of the geographical origin of Italian olive oil (Ligurian and non-Ligurian) on the basis of near infrared (NIR) or mid infrared (FTIR) spectra. Different classification models (PLS-DA, SVM with mean centre data, GENOPT-SVM) have been tested and statistically compared using McNemar's statistical test. For the two datasets, SVM with optimised pre-processing give models with higher accuracy than the one obtained with PLS-DA on pre-processed data. In the case of the NIR dataset, most of this accuracy improvement (86.3% compared with 82.8% for PLS-DA) occurred using only a single pre-processing step. For the FTIR dataset, three optimised pre-processing steps are required to obtain SVM model with significant accuracy improvement (82.2%) compared to the one obtained with PLS-DA (78.6%). Furthermore, this study demonstrates that even SVM models have to be developed on the basis of well-corrected spectral data in order to obtain higher classification rates. Copyright © 2013 Elsevier Ltd. All rights reserved.

A novel specimen-specific methodology to optimise the alignment of long bones for experimental testing.

PubMed

Cheong, Vee San; Bull, Anthony M J

2015-12-16

The choice of coordinate system and alignment of bone will affect the quantification of mechanical properties obtained during in-vitro biomechanical testing. Where these are used in predictive models, such as finite element analysis, the fidelic description of these properties is paramount. Currently in bending and torsional tests, bones are aligned on a pre-defined fixed span based on the reference system marked out. However, large inter-specimen differences have been reported. This suggests a need for the development of a specimen-specific alignment system for use in experimental work. Eleven ovine tibiae were used in this study and three-dimensional surface meshes were constructed from micro-Computed Tomography scan images. A novel, semi-automated algorithm was developed and applied to the surface meshes to align the whole bone based on its calculated principal directions. Thereafter, the code isolates the optimised location and length of each bone for experimental testing. This resulted in a lowering of the second moment of area about the chosen bending axis in the central region. More importantly, the optimisation method decreases the irregularity of the shape of the cross-sectional slices as the unbiased estimate of the population coefficient of variation of the second moment of area decreased from a range of (0.210-0.435) to (0.145-0.317) in the longitudinal direction, indicating a minimisation of the product moment, which causes eccentric loading. Thus, this methodology serves as an important pre-step to align the bone for mechanical tests or simulation work, is optimised for each specimen, ensures repeatability, and is general enough to be applied to any long bone. Copyright © 2015 Elsevier Ltd. All rights reserved.

Assessing behavioural and cognitive domains of autism spectrum disorders in rodents: current status and future perspectives.

PubMed

Kas, Martien J; Glennon, Jeffrey C; Buitelaar, Jan; Ey, Elodie; Biemans, Barbara; Crawley, Jacqueline; Ring, Robert H; Lajonchere, Clara; Esclassan, Frederic; Talpos, John; Noldus, Lucas P J J; Burbach, J Peter H; Steckler, Thomas

2014-03-01

The establishment of robust and replicable behavioural testing paradigms with translational value for psychiatric diseases is a major step forward in developing and testing etiology-directed treatment for these complex disorders. Based on the existing literature, we have generated an inventory of applied rodent behavioural testing paradigms relevant to autism spectrum disorders (ASD). This inventory focused on previously used paradigms that assess behavioural domains that are affected in ASD, such as social interaction, social communication, repetitive behaviours and behavioural inflexibility, cognition as well as anxiety behaviour. A wide range of behavioural testing paradigms for rodents were identified. However, the level of face and construct validity is highly variable. The predictive validity of these paradigms is unknown, as etiology-directed treatments for ASD are currently not on the market. To optimise these studies, future efforts should address aspects of reproducibility and take into account data about the neurodevelopmental underpinnings and trajectory of ASD. In addition, with the increasing knowledge of processes underlying ASD, such as sensory information processes and synaptic plasticity, phenotyping efforts should include multi-level automated analysis of, for example, representative task-related behavioural and electrophysiological read-outs.

Modelling the influence of inulin as a fat substitute in comminuted meat products on their physico-chemical characteristics and eating quality using a mixture design approach.

PubMed

Keenan, Derek F; Resconi, Virginia C; Kerry, Joseph P; Hamill, Ruth M

2014-03-01

The effects of fat substitution using two commercial inulin products on the physico-chemical properties and eating quality of a comminuted meat product (breakfast sausage) were modelled using a specialised response surface experiment specially developed for mixtures. 17 treatments were assigned representing a different substitution level for fat with inulin. Sausages were formulated to contain pork shoulder, back fat/inulin, water, rusk and seasoning (44.3, 18.7, 27.5, 7 and 2.5% w/w). Composition, sensory, instrumental texture and colour characteristics were assessed. Fructan analysis showed that inulin was unaffected by heat or processing treatments. Models showed increasing inulin inclusions decreased cook loss (p<0.0017) and improved emulsion stability (p<0.0001) but also resulted in greater textural and eating quality modification of sausages. Hardness values increased (p<0.0001) with increasing inulin concentration, with panellists also scoring products containing inulin as less tender (p<0.0112). Optimisation predicted two acceptable sausage formulations with significantly lower fat levels than the control, which would contain sufficient inulin to deliver a prebiotic health effect. Copyright © 2013 Elsevier Ltd. All rights reserved.

Warpage optimisation on the moulded part with straight-drilled and conformal cooling channels using response surface methodology (RSM) and glowworm swarm optimisation (GSO)

NASA Astrophysics Data System (ADS)

Hazwan, M. H. M.; Shayfull, Z.; Sharif, S.; Nasir, S. M.; Zainal, N.

2017-09-01

In injection moulding process, quality and productivity are notably important and must be controlled for each product type produced. Quality is measured as the extent of warpage of moulded parts while productivity is measured as a duration of moulding cycle time. To control the quality, many researchers have introduced various of optimisation approaches which have been proven enhanced the quality of the moulded part produced. In order to improve the productivity of injection moulding process, some of researches have proposed the application of conformal cooling channels which have been proven reduced the duration of moulding cycle time. Therefore, this paper presents an application of alternative optimisation approach which is Response Surface Methodology (RSM) with Glowworm Swarm Optimisation (GSO) on the moulded part with straight-drilled and conformal cooling channels mould. This study examined the warpage condition of the moulded parts before and after optimisation work applied for both cooling channels. A front panel housing have been selected as a specimen and the performance of proposed optimisation approach have been analysed on the conventional straight-drilled cooling channels compared to the Milled Groove Square Shape (MGSS) conformal cooling channels by simulation analysis using Autodesk Moldflow Insight (AMI) 2013. Based on the results, melt temperature is the most significant factor contribute to the warpage condition and warpage have optimised by 39.1% after optimisation for straight-drilled cooling channels and cooling time is the most significant factor contribute to the warpage condition and warpage have optimised by 38.7% after optimisation for MGSS conformal cooling channels. In addition, the finding shows that the application of optimisation work on the conformal cooling channels offers the better quality and productivity of the moulded part produced.

Using Optimisation Techniques to Granulise Rough Set Partitions

NASA Astrophysics Data System (ADS)

Crossingham, Bodie; Marwala, Tshilidzi

2007-11-01

This paper presents an approach to optimise rough set partition sizes using various optimisation techniques. Three optimisation techniques are implemented to perform the granularisation process, namely, genetic algorithm (GA), hill climbing (HC) and simulated annealing (SA). These optimisation methods maximise the classification accuracy of the rough sets. The proposed rough set partition method is tested on a set of demographic properties of individuals obtained from the South African antenatal survey. The three techniques are compared in terms of their computational time, accuracy and number of rules produced when applied to the Human Immunodeficiency Virus (HIV) data set. The optimised methods results are compared to a well known non-optimised discretisation method, equal-width-bin partitioning (EWB). The accuracies achieved after optimising the partitions using GA, HC and SA are 66.89%, 65.84% and 65.48% respectively, compared to the accuracy of EWB of 59.86%. In addition to rough sets providing the plausabilities of the estimated HIV status, they also provide the linguistic rules describing how the demographic parameters drive the risk of HIV.

Sugeno-Fuzzy Expert System Modeling for Quality Prediction of Non-Contact Machining Process

NASA Astrophysics Data System (ADS)

Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.

2018-03-01

Modeling can be categorised into four main domains: prediction, optimisation, estimation and calibration. In this paper, the Takagi-Sugeno-Kang (TSK) fuzzy logic method is examined as a prediction modelling method to investigate the taper quality of laser lathing, which seeks to replace traditional lathe machines with 3D laser lathing in order to achieve the desired cylindrical shape of stock materials. Three design parameters were selected: feed rate, cutting speed and depth of cut. A total of twenty-four experiments were conducted with eight sequential runs and replicated three times. The results were found to be 99% of accuracy rate of the TSK fuzzy predictive model, which suggests that the model is a suitable and practical method for non-linear laser lathing process.

Tablet potency of Tianeptine in coated tablets by near infrared spectroscopy: model optimisation, calibration transfer and confidence intervals.

PubMed

Boiret, Mathieu; Meunier, Loïc; Ginot, Yves-Michel

2011-02-20

A near infrared (NIR) method was developed for determination of tablet potency of active pharmaceutical ingredient (API) in a complex coated tablet matrix. The calibration set contained samples from laboratory and production scale batches. The reference values were obtained by high performance liquid chromatography (HPLC) and partial least squares (PLS) regression was used to establish a model. The model was challenged by calculating tablet potency of two external test sets. Root mean square errors of prediction were respectively equal to 2.0% and 2.7%. To use this model with a second spectrometer from the production field, a calibration transfer method called piecewise direct standardisation (PDS) was used. After the transfer, the root mean square error of prediction of the first test set was 2.4% compared to 4.0% without transferring the spectra. A statistical technique using bootstrap of PLS residuals was used to estimate confidence intervals of tablet potency calculations. This method requires an optimised PLS model, selection of the bootstrap number and determination of the risk. In the case of a chemical analysis, the tablet potency value will be included within the confidence interval calculated by the bootstrap method. An easy to use graphical interface was developed to easily determine if the predictions, surrounded by minimum and maximum values, are within the specifications defined by the regulatory organisation. Copyright © 2010 Elsevier B.V. All rights reserved.

Simultaneous nutrient removal, optimised CO2 mitigation and biofuel feedstock production by Chlorogonium sp. grown in secondary treated non-sterile saline sewage effluent.

PubMed

Lee, Kwan Yin; Ng, Tsz Wai; Li, Guiying; An, Taicheng; Kwan, Ka Ki; Chan, King Ming; Huang, Guocheng; Yip, Ho Yin; Wong, Po Keung

2015-10-30

The phycoremediation process has great potential for effectively addressing environmental pollution. To explore the capabilities of simultaneous algal nutrient removal, CO2 mitigation and biofuel feedstock production from spent water resources, a Chlorogonium sp. isolated from a tilapia pond in Hong Kong was grown in non-sterile saline sewage effluent for a bioremediation study. With high removal efficiencies of NH3-N (88.35±14.39%), NO3(-)-N (85.39±14.96%), TN (93.34±6.47%) and PO4(3-)-P (91.80±17.44%), Chlorogonium sp. achieved a CO2 consumption rate of 58.96 mg L(-1) d(-1), which was optimised by the response surface methodology. Under optimised conditions, the lipid content of the algal biomass reached 24.26±2.67%. Overall, the isolated Chlorogonium sp. showed promising potential in the simultaneous purification of saline sewage effluent in terms of tertiary treatment and CO2 sequestration while delivering feedstock for potential biofuel production in a waste-recycling manner. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimisation of microwave-assisted processing in production of pineapple jam

NASA Astrophysics Data System (ADS)

Ismail, Nur Aisyah Mohd; Abdullah, Norazlin; Muhammad, Norhayati

2017-10-01

Pineapples are available all year round since they are unseasonal fruits. Due to the continuous harvesting of the fruit, the retailers and farmers had to find a solution such as the processing of pineapple into jam, to treat the unsuccessfully sold pineapples. The direct heating of pineapple puree during the production of pineapple jam can cause over degradation of quality of the fresh pineapple. Thus, this study aims to optimise the microwave-assisted processing conditions for producing pineapple jam which could reduce water activity and meets minimum requirement for pH and total soluble solids contents of fruit jam. The power and time of the microwave processing were chosen as the factors, while the water activity, pH and total soluble solids (TSS) content of the pineapple jam were determined as responses to be optimised. The microwave treatment on the pineapple jam was able to give significant effect on the water activity and TSS content of the pineapple jam. The optimum power and time for the microwave processing of pineapple jam is 800 Watt and 8 minutes, respectively. The use of domestic microwave oven for the pineapple jam production results in acceptable pineapple jam same as conventional fruit jam sold in the marketplace.

Development and validation of a rapid capillary zone electrophoresis method for the determination of aconite alkaloids in aconite roots.

PubMed

Song, Jing-Zheng; Han, Quan-Bin; Qiao, Chun-Feng; But, Paul Pui-Hay; Xu, Hong-Xi

2010-01-01

Aconites, with aconite alkaloids as the major therapeutic and toxic components, are used for the treatment of analgesic, antirheumatic and neurological symptoms. Quantification of the aconite alkaloids is important for the quality control of aconite-containing drugs. To establish a validated capillary zone electrophoresis (CZE) method for the simultaneous determination of six major alkaloids, namely aconitine, mesaconitine, hypaconitine, benzoylaconine, benzoylmesaconine and benzoylhypaconine, in crude and processed aconite roots. The CZE method was optimised and validated using a stability-indicating method. The optimised running buffer was a mixture of 200 mm Tris, 150 mm perchloric acid and 40% 1,4-dioxane (pH 7.8) with the capillary thermostated at 25 degrees C. Using the optimised method, six aconite alkaloids were well separated. The established method showed good precision, accuracy and recovery. Contents of these alkaloids in crude and processed aconites were determined and it was observed that the levels of individual alkaloids varied between samples. The developed CZE method was reliable for the quality control of aconites contained in herbal medicines. The method could also be used as an approach for toxicological studies.

Optimal type 2 diabetes mellitus management: the randomised controlled OPTIMISE benchmarking study: baseline results from six European countries.

PubMed

Hermans, Michel P; Brotons, Carlos; Elisaf, Moses; Michel, Georges; Muls, Erik; Nobels, Frank

2013-12-01

Micro- and macrovascular complications of type 2 diabetes have an adverse impact on survival, quality of life and healthcare costs. The OPTIMISE (OPtimal Type 2 dIabetes Management Including benchmarking and Standard trEatment) trial comparing physicians' individual performances with a peer group evaluates the hypothesis that benchmarking, using assessments of change in three critical quality indicators of vascular risk: glycated haemoglobin (HbA1c), low-density lipoprotein-cholesterol (LDL-C) and systolic blood pressure (SBP), may improve quality of care in type 2 diabetes in the primary care setting. This was a randomised, controlled study of 3980 patients with type 2 diabetes. Six European countries participated in the OPTIMISE study (NCT00681850). Quality of care was assessed by the percentage of patients achieving pre-set targets for the three critical quality indicators over 12 months. Physicians were randomly assigned to receive either benchmarked or non-benchmarked feedback. All physicians received feedback on six of their patients' modifiable outcome indicators (HbA1c, fasting glycaemia, total cholesterol, high-density lipoprotein-cholesterol (HDL-C), LDL-C and triglycerides). Physicians in the benchmarking group additionally received information on levels of control achieved for the three critical quality indicators compared with colleagues. At baseline, the percentage of evaluable patients (N = 3980) achieving pre-set targets was 51.2% (HbA1c; n = 2028/3964); 34.9% (LDL-C; n = 1350/3865); 27.3% (systolic blood pressure; n = 911/3337). OPTIMISE confirms that target achievement in the primary care setting is suboptimal for all three critical quality indicators. This represents an unmet but modifiable need to revisit the mechanisms and management of improving care in type 2 diabetes. OPTIMISE will help to assess whether benchmarking is a useful clinical tool for improving outcomes in type 2 diabetes.

Analysis of optimisation method for a two-stroke piston ring using the Finite Element Method and the Simulated Annealing Method

NASA Astrophysics Data System (ADS)

Kaliszewski, M.; Mazuro, P.

2016-09-01

Simulated Annealing Method of optimisation for the sealing piston ring geometry is tested. The aim of optimisation is to develop ring geometry which would exert demanded pressure on a cylinder just while being bended to fit the cylinder. Method of FEM analysis of an arbitrary piston ring geometry is applied in an ANSYS software. The demanded pressure function (basing on formulae presented by A. Iskra) as well as objective function are introduced. Geometry definition constructed by polynomials in radial coordinate system is delivered and discussed. Possible application of Simulated Annealing Method in a piston ring optimisation task is proposed and visualised. Difficulties leading to possible lack of convergence of optimisation are presented. An example of an unsuccessful optimisation performed in APDL is discussed. Possible line of further optimisation improvement is proposed.

Sequencing batch-reactor control using Gaussian-process models.

PubMed

Kocijan, Juš; Hvala, Nadja

2013-06-01

This paper presents a Gaussian-process (GP) model for the design of sequencing batch-reactor (SBR) control for wastewater treatment. The GP model is a probabilistic, nonparametric model with uncertainty predictions. In the case of SBR control, it is used for the on-line optimisation of the batch-phases duration. The control algorithm follows the course of the indirect process variables (pH, redox potential and dissolved oxygen concentration) and recognises the characteristic patterns in their time profile. The control algorithm uses GP-based regression to smooth the signals and GP-based classification for the pattern recognition. When tested on the signals from an SBR laboratory pilot plant, the control algorithm provided a satisfactory agreement between the proposed completion times and the actual termination times of the biodegradation processes. In a set of tested batches the final ammonia and nitrate concentrations were below 1 and 0.5 mg L(-1), respectively, while the aeration time was shortened considerably. Copyright © 2013 Elsevier Ltd. All rights reserved.

Optimising predictor domains for spatially coherent precipitation downscaling

NASA Astrophysics Data System (ADS)

Radanovics, S.; Vidal, J.-P.; Sauquet, E.; Ben Daoud, A.; Bontron, G.

2013-10-01

Statistical downscaling is widely used to overcome the scale gap between predictors from numerical weather prediction models or global circulation models and predictands like local precipitation, required for example for medium-term operational forecasts or climate change impact studies. The predictors are considered over a given spatial domain which is rarely optimised with respect to the target predictand location. In this study, an extended version of the growing rectangular domain algorithm is proposed to provide an ensemble of near-optimum predictor domains for a statistical downscaling method. This algorithm is applied to find five-member ensembles of near-optimum geopotential predictor domains for an analogue downscaling method for 608 individual target zones covering France. Results first show that very similar downscaling performances based on the continuous ranked probability score (CRPS) can be achieved by different predictor domains for any specific target zone, demonstrating the need for considering alternative domains in this context of high equifinality. A second result is the large diversity of optimised predictor domains over the country that questions the commonly made hypothesis of a common predictor domain for large areas. The domain centres are mainly distributed following the geographical location of the target location, but there are apparent differences between the windward and the lee side of mountain ridges. Moreover, domains for target zones located in southeastern France are centred more east and south than the ones for target locations on the same longitude. The size of the optimised domains tends to be larger in the southeastern part of the country, while domains with a very small meridional extent can be found in an east-west band around 47° N. Sensitivity experiments finally show that results are rather insensitive to the starting point of the optimisation algorithm except for zones located in the transition area north of this east-west band. Results also appear generally robust with respect to the archive length considered for the analogue method, except for zones with high interannual variability like in the Cévennes area. This study paves the way for defining regions with homogeneous geopotential predictor domains for precipitation downscaling over France, and therefore de facto ensuring the spatial coherence required for hydrological applications.

Noise in NC-AFM measurements with significant tip–sample interaction

PubMed Central

Lübbe, Jannis; Temmen, Matthias

2016-01-01

The frequency shift noise in non-contact atomic force microscopy (NC-AFM) imaging and spectroscopy consists of thermal noise and detection system noise with an additional contribution from amplitude noise if there are significant tip–sample interactions. The total noise power spectral density D Δ f(f m) is, however, not just the sum of these noise contributions. Instead its magnitude and spectral characteristics are determined by the strongly non-linear tip–sample interaction, by the coupling between the amplitude and tip–sample distance control loops of the NC-AFM system as well as by the characteristics of the phase locked loop (PLL) detector used for frequency demodulation. Here, we measure D Δ f(f m) for various NC-AFM parameter settings representing realistic measurement conditions and compare experimental data to simulations based on a model of the NC-AFM system that includes the tip–sample interaction. The good agreement between predicted and measured noise spectra confirms that the model covers the relevant noise contributions and interactions. Results yield a general understanding of noise generation and propagation in the NC-AFM and provide a quantitative prediction of noise for given experimental parameters. We derive strategies for noise-optimised imaging and spectroscopy and outline a full optimisation procedure for the instrumentation and control loops. PMID:28144538

Noise in NC-AFM measurements with significant tip-sample interaction.

PubMed

Lübbe, Jannis; Temmen, Matthias; Rahe, Philipp; Reichling, Michael

2016-01-01

The frequency shift noise in non-contact atomic force microscopy (NC-AFM) imaging and spectroscopy consists of thermal noise and detection system noise with an additional contribution from amplitude noise if there are significant tip-sample interactions. The total noise power spectral density D Δ f ( f m ) is, however, not just the sum of these noise contributions. Instead its magnitude and spectral characteristics are determined by the strongly non-linear tip-sample interaction, by the coupling between the amplitude and tip-sample distance control loops of the NC-AFM system as well as by the characteristics of the phase locked loop (PLL) detector used for frequency demodulation. Here, we measure D Δ f ( f m ) for various NC-AFM parameter settings representing realistic measurement conditions and compare experimental data to simulations based on a model of the NC-AFM system that includes the tip-sample interaction. The good agreement between predicted and measured noise spectra confirms that the model covers the relevant noise contributions and interactions. Results yield a general understanding of noise generation and propagation in the NC-AFM and provide a quantitative prediction of noise for given experimental parameters. We derive strategies for noise-optimised imaging and spectroscopy and outline a full optimisation procedure for the instrumentation and control loops.

Multidisciplinary design optimisation of a recurve bow based on applications of the autogenetic design theory and distributed computing

NASA Astrophysics Data System (ADS)

Fritzsche, Matthias; Kittel, Konstantin; Blankenburg, Alexander; Vajna, Sándor

2012-08-01

The focus of this paper is to present a method of multidisciplinary design optimisation based on the autogenetic design theory (ADT) that provides methods, which are partially implemented in the optimisation software described here. The main thesis of the ADT is that biological evolution and the process of developing products are mainly similar, i.e. procedures from biological evolution can be transferred into product development. In order to fulfil requirements and boundary conditions of any kind (that may change at any time), both biological evolution and product development look for appropriate solution possibilities in a certain area, and try to optimise those that are actually promising by varying parameters and combinations of these solutions. As the time necessary for multidisciplinary design optimisations is a critical aspect in product development, ways to distribute the optimisation process with the effective use of unused calculating capacity, can reduce the optimisation time drastically. Finally, a practical example shows how ADT methods and distributed optimising are applied to improve a product.

Optimising the Inflammatory Bowel Disease Unit to Improve Quality of Care: Expert Recommendations.

PubMed

Louis, Edouard; Dotan, Iris; Ghosh, Subrata; Mlynarsky, Liat; Reenaers, Catherine; Schreiber, Stefan

2015-08-01

The best care setting for patients with inflammatory bowel disease [IBD] may be in a dedicated unit. Whereas not all gastroenterology units have the same resources to develop dedicated IBD facilities and services, there are steps that can be taken by any unit to optimise patients' access to interdisciplinary expert care. A series of pragmatic recommendations relating to IBD unit optimisation have been developed through discussion among a large panel of international experts. Suggested recommendations were extracted through systematic search of published evidence and structured requests for expert opinion. Physicians [n = 238] identified as IBD specialists by publications or clinical focus on IBD were invited for discussion and recommendation modification [Barcelona, Spain; 2014]. Final recommendations were voted on by the group. Participants also completed an online survey to evaluate their own experience related to IBD units. A total of 60% of attendees completed the survey, with 15% self-classifying their centre as a dedicated IBD unit. Only half of respondents indicated that they had a defined IBD treatment algorithm in place. Key recommendations included the need to develop a multidisciplinary team covering specifically-defined specialist expertise in IBD, to instil processes that facilitate cross-functional communication and to invest in shared care models of IBD management. Optimising the setup of IBD units will require progressive leadership and willingness to challenge the status quo in order to provide better quality of care for our patients. IBD units are an important step towards harmonising care for IBD across Europe and for establishing standards for disease management programmes. © European Crohn’s and Colitis Organisation 2015.

Optimising the Inflammatory Bowel Disease Unit to Improve Quality of Care: Expert Recommendations

PubMed Central

Dotan, Iris; Ghosh, Subrata; Mlynarsky, Liat; Reenaers, Catherine; Schreiber, Stefan

2015-01-01

Introduction: The best care setting for patients with inflammatory bowel disease [IBD] may be in a dedicated unit. Whereas not all gastroenterology units have the same resources to develop dedicated IBD facilities and services, there are steps that can be taken by any unit to optimise patients’ access to interdisciplinary expert care. A series of pragmatic recommendations relating to IBD unit optimisation have been developed through discussion among a large panel of international experts. Methods: Suggested recommendations were extracted through systematic search of published evidence and structured requests for expert opinion. Physicians [n = 238] identified as IBD specialists by publications or clinical focus on IBD were invited for discussion and recommendation modification [Barcelona, Spain; 2014]. Final recommendations were voted on by the group. Participants also completed an online survey to evaluate their own experience related to IBD units. Results: A total of 60% of attendees completed the survey, with 15% self-classifying their centre as a dedicated IBD unit. Only half of respondents indicated that they had a defined IBD treatment algorithm in place. Key recommendations included the need to develop a multidisciplinary team covering specifically-defined specialist expertise in IBD, to instil processes that facilitate cross-functional communication and to invest in shared care models of IBD management. Conclusions: Optimising the setup of IBD units will require progressive leadership and willingness to challenge the status quo in order to provide better quality of care for our patients. IBD units are an important step towards harmonising care for IBD across Europe and for establishing standards for disease management programmes. PMID:25987349

A TPS kernel for calculating survival vs. depth: distributions in a carbon radiotherapy beam, based on Katz's cellular Track Structure Theory.

PubMed

Waligórski, M P R; Grzanka, L; Korcyl, M; Olko, P

2015-09-01

An algorithm was developed of a treatment planning system (TPS) kernel for carbon radiotherapy in which Katz's Track Structure Theory of cellular survival (TST) is applied as its radiobiology component. The physical beam model is based on available tabularised data, prepared by Monte Carlo simulations of a set of pristine carbon beams of different input energies. An optimisation tool developed for this purpose is used to find the composition of pristine carbon beams of input energies and fluences which delivers a pre-selected depth-dose distribution profile over the spread-out Bragg peak (SOBP) region. Using an extrapolation algorithm, energy-fluence spectra of the primary carbon ions and of all their secondary fragments are obtained over regular steps of beam depths. To obtain survival vs. depth distributions, the TST calculation is applied to the energy-fluence spectra of the mixed field of primary ions and of their secondary products at the given beam depths. Katz's TST offers a unique analytical and quantitative prediction of cell survival in such mixed ion fields. By optimising the pristine beam composition to a published depth-dose profile over the SOBP region of a carbon beam and using TST model parameters representing the survival of CHO (Chinese Hamster Ovary) cells in vitro, it was possible to satisfactorily reproduce a published data set of CHO cell survival vs. depth measurements after carbon ion irradiation. The authors also show by a TST calculation that 'biological dose' is neither linear nor additive. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Value of the dorsal cutaneous guinea pig model in selecting topical antiviral formulations for the treatment of recurrent herpes simplex type 1 disease.

PubMed

Poli, G; Dall'Ara, P; Binda, S; Santus, G; Poli, A; Cocilovo, A; Ponti, W

2001-01-01

Recurrent herpes simplex labialis represents a disease still difficult to treat, despite the availability of many established antiviral drugs used in clinical research since 30 years ago. Although differences between the human disease and that obtained in experimental animal suggest caution in predicting an effective clinical response from the experimental results, some of the animal models seem to be useful in optimising the topical formulation of single antiviral drugs. In the present work the dorsal cutaneous guinea pig model was used to compare 5 different topical antiviral formulations with clinical promise (active molecule: 5% w/w micronized aciclovir, CAS 59277-89-3), using both roll-on and lipstick application systems. The aim being to evaluate which vehicle (water, oil, low melting and high melting fatty base) and application system (roll-on, lipstick) enhances the skin penetration and the antiviral activity of the drug, after an experimental intradermal infection with Herpes simplex virus type 1 (HSV-1). As reference, a commercial formulation (5% aciclovir ointment) was used. The cumulative results of this study showed that the formulation A, containing 5% aciclovir in an aqueous base in a roll-on application system, has the better antiviral efficacy in reducing the severity of cutaneous lesions and the viral titer; among the lipsticks preparations, the formulation D, containing 5% aciclovir in a low melting fatty base, demonstrates a very strong antiviral activity, though slightly less than formulation A. This experimental work confirms the validity of the dorsal cutaneous guinea pig model as a rapid and efficient method to compare the antiviral efficacy of new formulations, with clinical promise, to optimise the topical formulation of the active antiviral drugs.

Modelling soil water retention using support vector machines with genetic algorithm optimisation.

PubMed

Lamorski, Krzysztof; Sławiński, Cezary; Moreno, Felix; Barna, Gyöngyi; Skierucha, Wojciech; Arrue, José L

2014-01-01

This work presents point pedotransfer function (PTF) models of the soil water retention curve. The developed models allowed for estimation of the soil water content for the specified soil water potentials: -0.98, -3.10, -9.81, -31.02, -491.66, and -1554.78 kPa, based on the following soil characteristics: soil granulometric composition, total porosity, and bulk density. Support Vector Machines (SVM) methodology was used for model development. A new methodology for elaboration of retention function models is proposed. Alternative to previous attempts known from literature, the ν-SVM method was used for model development and the results were compared with the formerly used the C-SVM method. For the purpose of models' parameters search, genetic algorithms were used as an optimisation framework. A new form of the aim function used for models parameters search is proposed which allowed for development of models with better prediction capabilities. This new aim function avoids overestimation of models which is typically encountered when root mean squared error is used as an aim function. Elaborated models showed good agreement with measured soil water retention data. Achieved coefficients of determination values were in the range 0.67-0.92. Studies demonstrated usability of ν-SVM methodology together with genetic algorithm optimisation for retention modelling which gave better performing models than other tested approaches.

Optimising cluster survey design for planning schistosomiasis preventive chemotherapy.

PubMed

Knowles, Sarah C L; Sturrock, Hugh J W; Turner, Hugo; Whitton, Jane M; Gower, Charlotte M; Jemu, Samuel; Phillips, Anna E; Meite, Aboulaye; Thomas, Brent; Kollie, Karsor; Thomas, Catherine; Rebollo, Maria P; Styles, Ben; Clements, Michelle; Fenwick, Alan; Harrison, Wendy E; Fleming, Fiona M

2017-05-01

The cornerstone of current schistosomiasis control programmes is delivery of praziquantel to at-risk populations. Such preventive chemotherapy requires accurate information on the geographic distribution of infection, yet the performance of alternative survey designs for estimating prevalence and converting this into treatment decisions has not been thoroughly evaluated. We used baseline schistosomiasis mapping surveys from three countries (Malawi, Côte d'Ivoire and Liberia) to generate spatially realistic gold standard datasets, against which we tested alternative two-stage cluster survey designs. We assessed how sampling different numbers of schools per district (2-20) and children per school (10-50) influences the accuracy of prevalence estimates and treatment class assignment, and we compared survey cost-efficiency using data from Malawi. Due to the focal nature of schistosomiasis, up to 53% simulated surveys involving 2-5 schools per district failed to detect schistosomiasis in low endemicity areas (1-10% prevalence). Increasing the number of schools surveyed per district improved treatment class assignment far more than increasing the number of children sampled per school. For Malawi, surveys of 15 schools per district and 20-30 children per school reliably detected endemic schistosomiasis and maximised cost-efficiency. In sensitivity analyses where treatment costs and the country considered were varied, optimal survey size was remarkably consistent, with cost-efficiency maximised at 15-20 schools per district. Among two-stage cluster surveys for schistosomiasis, our simulations indicated that surveying 15-20 schools per district and 20-30 children per school optimised cost-efficiency and minimised the risk of under-treatment, with surveys involving more schools of greater cost-efficiency as treatment costs rose.

Optimised anaerobic treatment of house-sorted biodegradable waste and slaughterhouse waste in a high loaded half technical scale digester.

PubMed

Resch, C; Grasmug, M; Smeets, W; Braun, R; Kirchmayr, R

2006-01-01

Anaerobic co-digestion of organic wastes from households, slaughterhouses and meat processing industries was optimised in a half technical scale plant. The plant was operated for 130 days using two different substrates under organic loading rates of 10 and 12 kgCOD.m(-3).d(-1). Since the substrates were rich in fat and protein components (TKN: 12 g.kg(-1) the treatment was challenging. The process was monitored on-line and in the laboratory. It was demonstrated that an intensive and stable co-digestion of partly hydrolysed organic waste and protein rich slaughterhouse waste can be achieved in the balance of inconsistent pH and buffering NH4-N. In the first experimental period the reduction of the substrate COD was almost complete in an overall stable process (COD reduction >82%). In the second period methane productivity increased, but certain intermediate products accumulated constantly. Process design options for a second digestion phase for advanced degradation were investigated. Potential causes for slow and reduced propionic and valeric acid degradation were assessed. Recommendations for full-scale process implementation can be made from the experimental results reported. The highly loaded and stable codigestion of these substrates may be a good technical and economic treatment alternative.

Dosimetric accuracy of a treatment planning system for actively scanned proton beams and small target volumes: Monte Carlo and experimental validation

NASA Astrophysics Data System (ADS)

Magro, G.; Molinelli, S.; Mairani, A.; Mirandola, A.; Panizza, D.; Russo, S.; Ferrari, A.; Valvo, F.; Fossati, P.; Ciocca, M.

2015-09-01

This study was performed to evaluate the accuracy of a commercial treatment planning system (TPS), in optimising proton pencil beam dose distributions for small targets of different sizes (5-30 mm side) located at increasing depths in water. The TPS analytical algorithm was benchmarked against experimental data and the FLUKA Monte Carlo (MC) code, previously validated for the selected beam-line. We tested the Siemens syngo® TPS plan optimisation module for water cubes fixing the configurable parameters at clinical standards, with homogeneous target coverage to a 2 Gy (RBE) dose prescription as unique goal. Plans were delivered and the dose at each volume centre was measured in water with a calibrated PTW Advanced Markus® chamber. An EBT3® film was also positioned at the phantom entrance window for the acquisition of 2D dose maps. Discrepancies between TPS calculated and MC simulated values were mainly due to the different lateral spread modeling and resulted in being related to the field-to-spot size ratio. The accuracy of the TPS was proved to be clinically acceptable in all cases but very small and shallow volumes. In this contest, the use of MC to validate TPS results proved to be a reliable procedure for pre-treatment plan verification.

Dosimetric accuracy of a treatment planning system for actively scanned proton beams and small target volumes: Monte Carlo and experimental validation.

PubMed

Magro, G; Molinelli, S; Mairani, A; Mirandola, A; Panizza, D; Russo, S; Ferrari, A; Valvo, F; Fossati, P; Ciocca, M

2015-09-07

This study was performed to evaluate the accuracy of a commercial treatment planning system (TPS), in optimising proton pencil beam dose distributions for small targets of different sizes (5-30 mm side) located at increasing depths in water. The TPS analytical algorithm was benchmarked against experimental data and the FLUKA Monte Carlo (MC) code, previously validated for the selected beam-line. We tested the Siemens syngo(®) TPS plan optimisation module for water cubes fixing the configurable parameters at clinical standards, with homogeneous target coverage to a 2 Gy (RBE) dose prescription as unique goal. Plans were delivered and the dose at each volume centre was measured in water with a calibrated PTW Advanced Markus(®) chamber. An EBT3(®) film was also positioned at the phantom entrance window for the acquisition of 2D dose maps. Discrepancies between TPS calculated and MC simulated values were mainly due to the different lateral spread modeling and resulted in being related to the field-to-spot size ratio. The accuracy of the TPS was proved to be clinically acceptable in all cases but very small and shallow volumes. In this contest, the use of MC to validate TPS results proved to be a reliable procedure for pre-treatment plan verification.

Employing the therapeutic operating characteristic (TOC) graph for individualised dose prescription.

PubMed

Hoffmann, Aswin L; Huizenga, Henk; Kaanders, Johannes H A M

2013-03-07

In current practice, patients scheduled for radiotherapy are treated according to 'rigid' protocols with predefined dose prescriptions that do not consider risk-taking preferences of individuals. The therapeutic operating characteristic (TOC) graph is applied as a decision-aid to assess the trade-off between treatment benefit and morbidity to facilitate dose prescription customisation. Historical dose-response data from prostate cancer patient cohorts treated with 3D-conformal radiotherapy is used to construct TOC graphs. Next, intensity-modulated (IMRT) plans are generated by optimisation based on dosimetric criteria and dose-response relationships. TOC graphs are constructed for dose-scaling of the optimised IMRT plan and individualised dose prescription. The area under the TOC curve (AUC) is estimated to measure the therapeutic power of these plans. On a continuous scale, the TOC graph directly visualises treatment benefit and morbidity risk of physicians' or patients' choices for dose (de-)escalation. The trade-off between these probabilities facilitates the selection of an individualised dose prescription. TOC graphs show broader therapeutic window and higher AUCs with increasing target dose heterogeneity. The TOC graph gives patients and physicians access to a decision-aid and read-out of the trade-off between treatment benefit and morbidity risks for individualised dose prescription customisation over a continuous range of dose levels.

Employing the therapeutic operating characteristic (TOC) graph for individualised dose prescription

PubMed Central

2013-01-01

Background In current practice, patients scheduled for radiotherapy are treated according to ‘rigid’ protocols with predefined dose prescriptions that do not consider risk-taking preferences of individuals. The therapeutic operating characteristic (TOC) graph is applied as a decision-aid to assess the trade-off between treatment benefit and morbidity to facilitate dose prescription customisation. Methods Historical dose-response data from prostate cancer patient cohorts treated with 3D-conformal radiotherapy is used to construct TOC graphs. Next, intensity-modulated (IMRT) plans are generated by optimisation based on dosimetric criteria and dose-response relationships. TOC graphs are constructed for dose-scaling of the optimised IMRT plan and individualised dose prescription. The area under the TOC curve (AUC) is estimated to measure the therapeutic power of these plans. Results On a continuous scale, the TOC graph directly visualises treatment benefit and morbidity risk of physicians’ or patients’ choices for dose (de-)escalation. The trade-off between these probabilities facilitates the selection of an individualised dose prescription. TOC graphs show broader therapeutic window and higher AUCs with increasing target dose heterogeneity. Conclusions The TOC graph gives patients and physicians access to a decision-aid and read-out of the trade-off between treatment benefit and morbidity risks for individualised dose prescription customisation over a continuous range of dose levels. PMID:23497640

Optimisation in radiotherapy. III: Stochastic optimisation algorithms and conclusions.

PubMed

Ebert, M

1997-12-01

This is the final article in a three part examination of optimisation in radiotherapy. Previous articles have established the bases and form of the radiotherapy optimisation problem, and examined certain types of optimisation algorithm, namely, those which perform some form of ordered search of the solution space (mathematical programming), and those which attempt to find the closest feasible solution to the inverse planning problem (deterministic inversion). The current paper examines algorithms which search the space of possible irradiation strategies by stochastic methods. The resulting iterative search methods move about the solution space by sampling random variates, which gradually become more constricted as the algorithm converges upon the optimal solution. This paper also discusses the implementation of optimisation in radiotherapy practice.

Effects of benchmarking on the quality of type 2 diabetes care: results of the OPTIMISE (Optimal Type 2 Diabetes Management Including Benchmarking and Standard Treatment) study in Greece

PubMed Central

Tsimihodimos, Vasilis; Kostapanos, Michael S.; Moulis, Alexandros; Nikas, Nikos; Elisaf, Moses S.

2015-01-01

Objectives: To investigate the effect of benchmarking on the quality of type 2 diabetes (T2DM) care in Greece. Methods: The OPTIMISE (Optimal Type 2 Diabetes Management Including Benchmarking and Standard Treatment) study [ClinicalTrials.gov identifier: NCT00681850] was an international multicenter, prospective cohort study. It included physicians randomized 3:1 to either receive benchmarking for glycated hemoglobin (HbA1c), systolic blood pressure (SBP) and low-density lipoprotein cholesterol (LDL-C) treatment targets (benchmarking group) or not (control group). The proportions of patients achieving the targets of the above-mentioned parameters were compared between groups after 12 months of treatment. Also, the proportions of patients achieving those targets at 12 months were compared with baseline in the benchmarking group. Results: In the Greek region, the OPTIMISE study included 797 adults with T2DM (570 in the benchmarking group). At month 12 the proportion of patients within the predefined targets for SBP and LDL-C was greater in the benchmarking compared with the control group (50.6 versus 35.8%, and 45.3 versus 36.1%, respectively). However, these differences were not statistically significant. No difference between groups was noted in the percentage of patients achieving the predefined target for HbA1c. At month 12 the increase in the percentage of patients achieving all three targets was greater in the benchmarking (5.9–15.0%) than in the control group (2.7–8.1%). In the benchmarking group more patients were on target regarding SBP (50.6% versus 29.8%), LDL-C (45.3% versus 31.3%) and HbA1c (63.8% versus 51.2%) at 12 months compared with baseline (p < 0.001 for all comparisons). Conclusion: Benchmarking may comprise a promising tool for improving the quality of T2DM care. Nevertheless, target achievement rates of each, and of all three, quality indicators were suboptimal, indicating there are still unmet needs in the management of T2DM. PMID:26445642

Structure-activity relationships for serotonin transporter and dopamine receptor selectivity.

PubMed

Agatonovic-Kustrin, Snezana; Davies, Paul; Turner, Joseph V

2009-05-01

Antipsychotic medications have a diverse pharmacology with affinity for serotonergic, dopaminergic, adrenergic, histaminergic and cholinergic receptors. Their clinical use now also includes the treatment of mood disorders, thought to be mediated by serotonergic receptor activity. The aim of our study was to characterise the molecular properties of antipsychotic agents, and to develop a model that would indicate molecular specificity for the dopamine (D(2)) receptor and the serotonin (5-HT) transporter. Back-propagation artificial neural networks (ANNs) were trained on a dataset of 47 ligands categorically assigned antidepressant or antipsychotic utility. The structure of each compound was encoded with 63 calculated molecular descriptors. ANN parameters including hidden neurons and input descriptors were optimised based on sensitivity analyses, with optimum models containing between four and 14 descriptors. Predicted binding preferences were in excellent agreement with clinical antipsychotic or antidepressant utility. Validated models were further tested by use of an external prediction set of five drugs with unknown mechanism of action. The SAR models developed revealed the importance of simple molecular characteristics for differential binding to the D(2) receptor and the 5-HT transporter. These included molecular size and shape, solubility parameters, hydrogen donating potential, electrostatic parameters, stereochemistry and presence of nitrogen. The developed models and techniques employed are expected to be useful in the rational design of future therapeutic agents.

Pathway activity inference for multiclass disease classification through a mathematical programming optimisation framework.

PubMed

Yang, Lingjian; Ainali, Chrysanthi; Tsoka, Sophia; Papageorgiou, Lazaros G

2014-12-05

Applying machine learning methods on microarray gene expression profiles for disease classification problems is a popular method to derive biomarkers, i.e. sets of genes that can predict disease state or outcome. Traditional approaches where expression of genes were treated independently suffer from low prediction accuracy and difficulty of biological interpretation. Current research efforts focus on integrating information on protein interactions through biochemical pathway datasets with expression profiles to propose pathway-based classifiers that can enhance disease diagnosis and prognosis. As most of the pathway activity inference methods in literature are either unsupervised or applied on two-class datasets, there is good scope to address such limitations by proposing novel methodologies. A supervised multiclass pathway activity inference method using optimisation techniques is reported. For each pathway expression dataset, patterns of its constituent genes are summarised into one composite feature, termed pathway activity, and a novel mathematical programming model is proposed to infer this feature as a weighted linear summation of expression of its constituent genes. Gene weights are determined by the optimisation model, in a way that the resulting pathway activity has the optimal discriminative power with regards to disease phenotypes. Classification is then performed on the resulting low-dimensional pathway activity profile. The model was evaluated through a variety of published gene expression profiles that cover different types of disease. We show that not only does it improve classification accuracy, but it can also perform well in multiclass disease datasets, a limitation of other approaches from the literature. Desirable features of the model include the ability to control the maximum number of genes that may participate in determining pathway activity, which may be pre-specified by the user. Overall, this work highlights the potential of building pathway-based multi-phenotype classifiers for accurate disease diagnosis and prognosis problems.

Artemether-lumefantrine dosing for malaria treatment in young children and pregnant women: A pharmacokinetic-pharmacodynamic meta-analysis

PubMed Central

Borrmann, Steffen; Tékété, Mamadou; Lefèvre, Gilbert; Hamed, Kamal; Piola, Patrice; Ursing, Johan; Kofoed, Poul Erik; Mårtensson, Andreas; Ngasala, Billy; Björkman, Anders; Friberg Hietala, Sofia; Aweeka, Francesca; Parikh, Sunil; Mwai, Leah; Davis, Timothy M. E.; Karunajeewa, Harin; Newton, Paul N.; Mayxay, Mayfong; Deloron, Philippe; van Vugt, Michele; Karbwang, Juntra; Ezzet, Farkad; Bakshi, Rajesh; Stepniewska, Kasia; Barnes, Karen I.

2018-01-01

Background The fixed dose combination of artemether-lumefantrine (AL) is the most widely used treatment for uncomplicated Plasmodium falciparum malaria. Relatively lower cure rates and lumefantrine levels have been reported in young children and in pregnant women during their second and third trimester. The aim of this study was to investigate the pharmacokinetic and pharmacodynamic properties of lumefantrine and the pharmacokinetic properties of its metabolite, desbutyl-lumefantrine, in order to inform optimal dosing regimens in all patient populations. Methods and findings A search in PubMed, Embase, ClinicalTrials.gov, Google Scholar, conference proceedings, and the WorldWide Antimalarial Resistance Network (WWARN) pharmacology database identified 31 relevant clinical studies published between 1 January 1990 and 31 December 2012, with 4,546 patients in whom lumefantrine concentrations were measured. Under the auspices of WWARN, relevant individual concentration-time data, clinical covariates, and outcome data from 4,122 patients were made available and pooled for the meta-analysis. The developed lumefantrine population pharmacokinetic model was used for dose optimisation through in silico simulations. Venous plasma lumefantrine concentrations 7 days after starting standard AL treatment were 24.2% and 13.4% lower in children weighing <15 kg and 15–25 kg, respectively, and 20.2% lower in pregnant women compared with non-pregnant adults. Lumefantrine exposure decreased with increasing pre-treatment parasitaemia, and the dose limitation on absorption of lumefantrine was substantial. Simulations using the lumefantrine pharmacokinetic model suggest that, in young children and pregnant women beyond the first trimester, lengthening the dose regimen (twice daily for 5 days) and, to a lesser extent, intensifying the frequency of dosing (3 times daily for 3 days) would be more efficacious than using higher individual doses in the current standard treatment regimen (twice daily for 3 days). The model was developed using venous plasma data from patients receiving intact tablets with fat, and evaluations of alternative dosing regimens were consequently only representative for venous plasma after administration of intact tablets with fat. The absence of artemether-dihydroartemisinin data limited the prediction of parasite killing rates and recrudescent infections. Thus, the suggested optimised dosing schedule was based on the pharmacokinetic endpoint of lumefantrine plasma exposure at day 7. Conclusions Our findings suggest that revised AL dosing regimens for young children and pregnant women would improve drug exposure but would require longer or more complex schedules. These dosing regimens should be evaluated in prospective clinical studies to determine whether they would improve cure rates, demonstrate adequate safety, and thereby prolong the useful therapeutic life of this valuable antimalarial treatment. PMID:29894518

Epidemiological and partial budget analysis for treatment of subclinical Staphylococcus aureus intramammary infections considering microbiological and cytological scenarios.

PubMed

Petzer, Inge-Marié; Etter, Eric M C; Donkin, Edward F; Webb, Edward C; Karzis, Joanne

2017-12-01

An innovative method was investigated to aid in the elimination of Staphylococcus aureus (S. aureus) intramammary infections (IMI) from dairy herds. A stochastic model explore the economic benefit of three-day or eight-day treatment of subclinical IMI in all S. aureus infected cows or in only those with a somatic cell count (SCC) exceeding 200,000 cells/ml. An epidemiological model was developed to run parallel to the economic model that would predict the S. aureus IMI likely to persist, develop new infections and clinical mastitis. In the economic model a first algorithm was used to consider the low prevalence (LP) scenario and made use of S. aureus prevalence information provided by retrospective analysis of microbiological and cytological results in South Africa (2008-2012). The data used considered Staphylococcus aureus prevalence from [1.495; 1.595] 95% to [6.72; 6.95] 95% for SCC≤200,000 and SCC>200,000 cells/ml respectively. A second algorithm considered the high prevalence (HP) scenario to evaluate a simulated situation with a 5[U1] [R12] to 25% prevalence. Scenarios of low or high transmission ratio (TR) were included in the model according to the hygiene management on the farm. Probabilities and costs were calculated over 255days. The economic models predicted average cost indices for low S. aureus IMI and low TR to vary from -3179 ZAR (South African Rands) when subclinical cases with SCC higher than 200,000 cell/ml were treated for eight days, to -3663 ZAR when all subclinical S. aureus IMI were treated for three days. With a HP and high TR of S. aureus the average cost indices changed from -18,042 ZAR when none to -5433 ZAR per 255days when all S. aureus IMI were treated for eight days. The epidemiological model in this study predicted substantial benefit of treatment mainly in high TR scenarios. New IMI decreased up to77% in the three-day and up to 91% in the eight-day treatment scenarios. In the HP scenarios, persistent IMI were reduced by 94%. The number of clinical cases predicted with no treatment for subclinical infections was higher than the total number of clinical and subclinical cases in scenarios where cows were treated three or eight days. Initial prudent treatment of subclinical IMI resulted in less overall treatments and less new, persistent and clinical cases. Combined results of economic and epidemiological models indicated that the option that cost the least did not always have the best epidemiological outcome. Models may assist in optimising and balancing decisions relating to financial and IMI. Copyright © 2017. Published by Elsevier B.V.

Effect of heat treatment on the microstructure of a 2CrMoNiWV rotor steel

NASA Astrophysics Data System (ADS)

Li, Cheng

A wide range of experiments have been carried out on a 2CrMoNiWV low alloy steel to investigate the effect of various heat treatment conditions on microstructural change, alloy carbide transformation mechanism and mechanical properties.Two complete continuous cooling transformation (CCT) diagrams were constructed for this steel on the basis of experimental dilatometry thermal analysis, metallographic examination and current phase transformation theory. The significance of these two diagrams is in that they can be directly utilised in industrial practice as a reference during heat treatment for this material. Meanwhile it was confirmed that this 2CrMoNiWV steel can be transformed to a fully bainitic microstructure over a wide range of cooling rates and this feature proved this steel suitable for large diameter steam turbine rotor application.An innovative carbide extraction technique for the XRD identification of carbide phase has been developed. The detailed description of this new technique and its advantages are discussed in this thesis. The extensive work using TEM/EDX has set up essential "finger prints" for the quick examination of large amounts of individual carbide existing at various heat treated conditions. Simultaneous measurements and determinations were made on particle composition, morphological change, the type, amount and distribution of these carbide phases. Thus the sequence of carbide transformation for this 2CrMoNiWV steel during tempering has been established.The characteristic microstructures of various heat treated specimens were carefully examined and discussed. Theoretical thermodynamic equilibria predictions were calculated using MTDATA. A very good agreement was found between experimental results and theoretical predictions on those critical transformation temperatures and a good correlation of carbide evolution sequences was obtained. Based on experimental results and theoretical predictions, the role of tungsten in promoting creep resistance to the material is elucidated.The usefulness of equilibrium thermodynamic calculations using MTDATA in predicting the microstructural changes and carbide evolution has been demonstrated in this work, particularly the separate effect of composition on the stable carbide dispersion where a thermodynamic approach offers great benefits.A possibly optimised heat treatment route is suggested for the large diameter rotor forgings which involves austenitising at 980°C for 10 hours following by oil quenching and then tempering at 675°C for 20 hours following by air cooling.Some general conclusions are drawn from this study, especially with regard to the effect of heat treatment on the microstructure of this 2CrMoNiWV steel and suggestions for further work are made.

Optimisation on processing parameters for minimising warpage on side arm using response surface methodology (RSM) and particle swarm optimisation (PSO)

NASA Astrophysics Data System (ADS)

Rayhana, N.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.; Sazli, M.; Yahya, Z. R.

2017-09-01

This study presents the application of optimisation method to reduce the warpage of side arm part. Autodesk Moldflow Insight software was integrated into this study to analyse the warpage. The design of Experiment (DOE) for Response Surface Methodology (RSM) was constructed and by using the equation from RSM, Particle Swarm Optimisation (PSO) was applied. The optimisation method will result in optimised processing parameters with minimum warpage. Mould temperature, melt temperature, packing pressure, packing time and cooling time was selected as the variable parameters. Parameters selection was based on most significant factor affecting warpage stated by previous researchers. The results show that warpage was improved by 28.16% for RSM and 28.17% for PSO. The warpage improvement in PSO from RSM is only by 0.01 %. Thus, the optimisation using RSM is already efficient to give the best combination parameters and optimum warpage value for side arm part. The most significant parameters affecting warpage are packing pressure.

Metaheuristic optimisation methods for approximate solving of singular boundary value problems

NASA Astrophysics Data System (ADS)

Sadollah, Ali; Yadav, Neha; Gao, Kaizhou; Su, Rong

2017-07-01

This paper presents a novel approximation technique based on metaheuristics and weighted residual function (WRF) for tackling singular boundary value problems (BVPs) arising in engineering and science. With the aid of certain fundamental concepts of mathematics, Fourier series expansion, and metaheuristic optimisation algorithms, singular BVPs can be approximated as an optimisation problem with boundary conditions as constraints. The target is to minimise the WRF (i.e. error function) constructed in approximation of BVPs. The scheme involves generational distance metric for quality evaluation of the approximate solutions against exact solutions (i.e. error evaluator metric). Four test problems including two linear and two non-linear singular BVPs are considered in this paper to check the efficiency and accuracy of the proposed algorithm. The optimisation task is performed using three different optimisers including the particle swarm optimisation, the water cycle algorithm, and the harmony search algorithm. Optimisation results obtained show that the suggested technique can be successfully applied for approximate solving of singular BVPs.

The Thistle Field - Analysis of its past performance and optimisation of its future development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bayat, M.G.; Tehrani, D.H.

1985-01-01

The Thistle Field geology and its reservoir performance over the past six years have been reviewed. The latest reservoir simulation study of the field, covering the performance history-matching, and the conclusions of various prediction cases are reported. The special features of PORES, Britoil in-house 3D 3-phase fully implicit numerical simulator and its modeling aids as applied to the Thistle Field are presented.

Predictive and prognostic biomarkers in colorectal cancer: A systematic review of recent advances and challenges.

PubMed

Das, Vishal; Kalita, Jatin; Pal, Mintu

2017-03-01

Colorectal cancer (CRC) is one of the leading cause of cancer deaths worldwide. Since CRC is largely asymptomatic until alarm features develop to advanced stages, the implementation of the screening programme is very much essential to reduce cancer incidence and mortality rates. CRC occurs predominantly from accumulation of genetic and epigenetic changes in colon epithelial cells, which later gets transformed into adenocarcinomas. The current challenges of screening paradigm and diagnostic ranges are from semi-invasive methods like colonoscopy to non-invasive stool-based test, have resulted in over-diagnosis and over-treatment of CRC. Hence, new screening initiatives and deep studies are required for early diagnosis of CRC. In this regard, we not only summarise current predictive and prognostic biomarkers with their potential for diagnostic and therapeutic applications, but also describe current limitations, future perspectives and challenges associated with the progression of CRC. Currently many potential biomarkers have already been successfully translated into clinical practice eg. Fecal haemoglobin, Carcinoembryonic antigen (CEA) and CA19.9, although these are not highly promising diagnostic target for personalized medicine. So there is a critical need for reliable, minimally invasive, highly sensitive and specific genetic markers of an individualised and optimised patient treatment at the earliest disease stage possible. Identification of a new biomarker, or a set of biomarkers to the development of a valid, and clinical sensible assay that can be served as an alternative tool for early diagnosis of CRC and open up promising new targets in therapeutic intervention strategies. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Delivering an Optimised Behavioural Intervention (OBI) to people with low back pain with high psychological risk; results and lessons learnt from a feasibility randomised controlled trial of Contextual Cognitive Behavioural Therapy (CCBT) vs. Physiotherapy.

PubMed

Pincus, Tamar; Anwar, Shamaila; McCracken, Lance M; McGregor, Alison; Graham, Liz; Collinson, Michelle; McBeth, John; Watson, Paul; Morley, Stephen; Henderson, Juliet; Farrin, Amanda J

2015-06-16

Low Back Pain (LBP) remains a common and costly problem. Psychological obstacles to recovery have been identified, but psychological and behavioural interventions have produced only moderate improvements. Reviews of trials have suggested that the interventions lack clear theoretical basis, are often compromised by low dose, lack of fidelity, and delivery by non-experts. In addition, interventions do not directly target known risk mechanisms. We identified a theory driven intervention (Contexual Cognitive Behavioural Therapy, CCBT) that directly targets an evidence-based risk mechanism (avoidance and ensured dose and delivery were optimised. This feasibility study was designed to test the credibility and acceptability of optimised CCBT against physiotherapy for avoidant LBP patients, and to test recruitment, delivery of the intervention and response rates prior to moving to a full definitive trial. A randomised controlled feasibility trial with patients randomised to receive CCBT or physiotherapy. CCBT was delivered by trained supervised psychologists on a one to one basis and comprised up to 8 one-hour sessions. Physiotherapy comprised back to fitness group exercises with at least 60 % of content exercise-based. Patients were eligible to take part if they had back pain for more than 3 months, and scored above a threshold indicating fear avoidance, catastrophic beliefs and distress. 89 patients were recruited. Uptake rates were above those predicted. Scores for credibility and acceptability of the interventions met the set criteria. Response rates at three and six months fell short of the 75 % target. Problems associated with poor response rates were identified and successfully resolved, rates increased to 77 % at 3 months, and 68 % at 6 months. Independent ratings of treatment sessions indicated that CCBT was delivered to fidelity. Numbers were too small for formal analysis. Although average scores for acceptance were higher in the CCBT group than in the group attending physiotherapy (increase of 7.9 versus 5.1) and change in disability and pain from baseline to 6 months were greater in the CCBT group than in the physiotherapy group, these findings should be interpreted with caution. CCBT is a credible and acceptable intervention for LBP patients who exhibit psychological obstacles to recovery. ISRCTN43733490 , registered 15/12/2010.

Regulation of Monoclonal Antibody Immunotherapy by FcγRIIB.

PubMed

Stopforth, Richard J; Cleary, Kirstie L S; Cragg, Mark S

2016-05-01

Monoclonal antibodies (mAb) are revolutionising the treatment of many different diseases. Given their differing mode of action compared to most conventional chemotherapeutics and small molecule inhibitors, they possess the potential to be independent of common modes of treatment resistance and can typically be combined readily with existing treatments without dose-limiting toxicity. However, treatments with mAb rarely result in cure and so a full understanding of how these reagents work and can be optimised is key for their subsequent improvement. Here we review how an understanding of the biology of the inhibitory Fc receptor, FcγRIIB (CD32B), is leading to the development of improved mAb treatments.

Ex vivo optimisation of a heterogeneous speed of sound model of the human skull for non-invasive transcranial focused ultrasound at 1 MHz.

PubMed

Marsac, L; Chauvet, D; La Greca, R; Boch, A-L; Chaumoitre, K; Tanter, M; Aubry, J-F

2017-09-01

Transcranial brain therapy has recently emerged as a non-invasive strategy for the treatment of various neurological diseases, such as essential tremor or neurogenic pain. However, treatments require millimetre-scale accuracy. The use of high frequencies (typically ≥1 MHz) decreases the ultrasonic wavelength to the millimetre scale, thereby increasing the clinical accuracy and lowering the probability of cavitation, which improves the safety of the technique compared with the use of low-frequency devices that operate at 220 kHz. Nevertheless, the skull produces greater distortions of high-frequency waves relative to low-frequency waves. High-frequency waves require high-performance adaptive focusing techniques, based on modelling the wave propagation through the skull. This study sought to optimise the acoustical modelling of the skull based on computed tomography (CT) for a 1 MHz clinical brain therapy system. The best model tested in this article corresponded to a maximum speed of sound of 4000 m.s -1 in the skull bone, and it restored 86% of the optimal pressure amplitude on average in a collection of six human skulls. Compared with uncorrected focusing, the optimised non-invasive correction led to an average increase of 99% in the maximum pressure amplitude around the target and an average decrease of 48% in the distance between the peak pressure and the selected target. The attenuation through the skulls was also assessed within the bandwidth of the transducers, and it was found to vary in the range of 10 ± 3 dB at 800 kHz and 16 ± 3 dB at 1.3 MHz.

Development and in vitro/in vivo evaluation of a novel benznidazole liquid dosage form using a quality-by-design approach.

PubMed

Santos Souza, Higo Fernando; Real, Daniel; Leonardi, Darío; Rocha, Sandra Carla; Alonso, Victoria; Serra, Esteban; Silber, Ariel Mariano; Salomon, Claudio Javier

2017-12-01

To develop an alcohol-free solution suitable for children of benznidazole, the drug of choice for treatment of Chagas disease. In a quality-by-design approach, a systematic optimisation procedure was carried out to estimate the values of the factors leading to the maximum drug concentration. The formulations were analysed in terms of chemical and physical stability and drug content. The final preparation was subjected to an in vivo palatability assay. Mice were infected and treated orally in a murine model. The results showed that benznidazole solubility increased up to 18.38 mg/ml in the optimised co-solvent system. The final formulation remained stable at all three temperatures tested, with suitable drug content and no significant variability. Palatability of the preparation was improved by taste masking of BZL. In vivo studies showed that both parasitaemia and mortality diminished, particularly at a dose of 40 mg/kg/day. Quality by design was a suitable approach to formulate a co-solvent system of benznidazole. The in vivo studies confirmed the suitability of the optimised such solutions to diminish both parasitaemia and mortality. Thus, this novel alternative should be taken into account for further clinical evaluation in all age ranges. © 2017 John Wiley & Sons Ltd.

Fractures in sport: Optimising their management and outcome

PubMed Central

Robertson, Greg AJ; Wood, Alexander M

2015-01-01

Fractures in sport are a specialised cohort of fracture injuries, occurring in a high functioning population, in which the goals are rapid restoration of function and return to play with the minimal symptom profile possible. While the general principles of fracture management, namely accurate fracture reduction, appropriate immobilisation and timely rehabilitation, guide the treatment of these injuries, management of fractures in athletic populations can differ significantly from those in the general population, due to the need to facilitate a rapid return to high demand activities. However, despite fractures comprising up to 10% of all of sporting injuries, dedicated research into the management and outcome of sport-related fractures is limited. In order to assess the optimal methods of treating such injuries, and so allow optimisation of their outcome, the evidence for the management of each specific sport-related fracture type requires assessment and analysis. We present and review the current evidence directing management of fractures in athletes with an aim to promote valid innovative methods and optimise the outcome of such injuries. From this, key recommendations are provided for the management of the common fracture types seen in the athlete. Six case reports are also presented to illustrate the management planning and application of sport-focussed fracture management in the clinical setting. PMID:26716081

Enzymatic extraction of pectin from artichoke (Cynara scolymus L.) by-products using Celluclast®1.5L.

PubMed

Sabater, Carlos; Corzo, Nieves; Olano, Agustín; Montilla, Antonia

2018-06-15

The aim of this study was to optimise pectin extraction from artichoke by-products with Celluclast ® 1.5L using an experimental design analysed by response-surface methodology (RSM). The variables optimised were artichoke by-product powder concentration (2-7%, X 1 ), enzyme dose (2.2-13.3 U g -1 , X 2 ) and extraction time (6-24 h, X 3 ). The variables studied were galacturonic acid (GalA) (R 2 93.9) and pectic neutral sugars (R 2 92.8) content and pectin yield (R 2 88.6). In the optimum extraction conditions (X 1  = 6.5%; X 2  = 10.1 U g -1 ; X 3  = 27.2 h), pectin yield was 176 mgg -1 dry matter (DM). Considering 27.2 h of treatment as the +α value given by the design, the extraction time was increased up to 48 h obtaining a yield of 221 mg g -1 DM. The enzymatic method optimised allows obtaining artichoke pectin with good yield, high GalA (720 mg g -1 DM) and arabinose (127.6mgg -1 DM) contents and degree of methylation of 19.5%. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimising text messaging to improve adherence to web-based smoking cessation treatment: a randomised control trial protocol.

PubMed

Graham, Amanda L; Jacobs, Megan A; Cohn, Amy M; Cha, Sarah; Abroms, Lorien C; Papandonatos, George D; Whittaker, Robyn

2016-03-30

Millions of smokers use the Internet for smoking cessation assistance each year; however, most smokers engage minimally with even the best designed websites. The ubiquity of mobile devices and their effectiveness in promoting adherence in other areas of health behaviour change make them a promising tool to address adherence in Internet smoking cessation interventions. Text messaging is used by most adults, and messages can proactively encourage use of a web-based intervention. Text messaging can also be integrated with an Internet intervention to facilitate the use of core Internet intervention components. We identified four aspects of a text message intervention that may enhance its effectiveness in promoting adherence to a web-based smoking cessation programme: personalisation, integration, dynamic tailoring and message intensity. Phase I will use a two-level full factorial design to test the impact of these four experimental features on adherence to a web-based intervention. The primary outcome is a composite metric of adherence that incorporates general utilisation metrics (eg, logins, page views) and specific feature utilisation shown to predict abstinence. Participants will be N=860 adult smokers who register on an established Internet cessation programme and enrol in its text message programme. Phase II will be a two-arm randomised trial to compare the efficacy of the web-based cessation programme alone and in conjunction with the optimised text messaging intervention on 30-day point prevalence abstinence at 9 months. Phase II participants will be N=600 adult smokers who register to use an established Internet cessation programme and enrol in text messaging. Secondary analyses will explore whether adherence mediates the effect of treatment condition on outcome. This protocol was approved by Chesapeake IRB. We will disseminate study results through peer-reviewed manuscripts and conference presentations related to the methods and design, outcomes and exploratory analyses. NCT02585206. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

CAMELOT: Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox

NASA Astrophysics Data System (ADS)

Di Carlo, Marilena; Romero Martin, Juan Manuel; Vasile, Massimiliano

2018-03-01

Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox (CAMELOT) is a toolbox for the fast preliminary design and optimisation of low-thrust trajectories. It solves highly complex combinatorial problems to plan multi-target missions characterised by long spirals including different perturbations. To do so, CAMELOT implements a novel multi-fidelity approach combining analytical surrogate modelling and accurate computational estimations of the mission cost. Decisions are then made using two optimisation engines included in the toolbox, a single-objective global optimiser, and a combinatorial optimisation algorithm. CAMELOT has been applied to a variety of case studies: from the design of interplanetary trajectories to the optimal de-orbiting of space debris and from the deployment of constellations to on-orbit servicing. In this paper, the main elements of CAMELOT are described and two examples, solved using the toolbox, are presented.

Boundary element based multiresolution shape optimisation in electrostatics

NASA Astrophysics Data System (ADS)

Bandara, Kosala; Cirak, Fehmi; Of, Günther; Steinbach, Olaf; Zapletal, Jan

2015-09-01

We consider the shape optimisation of high-voltage devices subject to electrostatic field equations by combining fast boundary elements with multiresolution subdivision surfaces. The geometry of the domain is described with subdivision surfaces and different resolutions of the same geometry are used for optimisation and analysis. The primal and adjoint problems are discretised with the boundary element method using a sufficiently fine control mesh. For shape optimisation the geometry is updated starting from the coarsest control mesh with increasingly finer control meshes. The multiresolution approach effectively prevents the appearance of non-physical geometry oscillations in the optimised shapes. Moreover, there is no need for mesh regeneration or smoothing during the optimisation due to the absence of a volume mesh. We present several numerical experiments and one industrial application to demonstrate the robustness and versatility of the developed approach.

Tail mean and related robust solution concepts

NASA Astrophysics Data System (ADS)

Ogryczak, Włodzimierz

2014-01-01

Robust optimisation might be viewed as a multicriteria optimisation problem where objectives correspond to the scenarios although their probabilities are unknown or imprecise. The simplest robust solution concept represents a conservative approach focused on the worst-case scenario results optimisation. A softer concept allows one to optimise the tail mean thus combining performances under multiple worst scenarios. We show that while considering robust models allowing the probabilities to vary only within given intervals, the tail mean represents the robust solution for only upper bounded probabilities. For any arbitrary intervals of probabilities the corresponding robust solution may be expressed by the optimisation of appropriately combined mean and tail mean criteria thus remaining easily implementable with auxiliary linear inequalities. Moreover, we use the tail mean concept to develope linear programming implementable robust solution concepts related to risk averse optimisation criteria.

A CONCEPTUAL FRAMEWORK FOR MANAGING RADIATION DOSE TO PATIENTS IN DIAGNOSTIC RADIOLOGY USING REFERENCE DOSE LEVELS.

PubMed

Almén, Anja; Båth, Magnus

2016-06-01

The overall aim of the present work was to develop a conceptual framework for managing radiation dose in diagnostic radiology with the intention to support optimisation. An optimisation process was first derived. The framework for managing radiation dose, based on the derived optimisation process, was then outlined. The outset of the optimisation process is four stages: providing equipment, establishing methodology, performing examinations and ensuring quality. The optimisation process comprises a series of activities and actions at these stages. The current system of diagnostic reference levels is an activity in the last stage, ensuring quality. The system becomes a reactive activity only to a certain extent engaging the core activity in the radiology department, performing examinations. Three reference dose levels-possible, expected and established-were assigned to the three stages in the optimisation process, excluding ensuring quality. A reasonably achievable dose range is also derived, indicating an acceptable deviation from the established dose level. A reasonable radiation dose for a single patient is within this range. The suggested framework for managing radiation dose should be regarded as one part of the optimisation process. The optimisation process constitutes a variety of complementary activities, where managing radiation dose is only one part. This emphasises the need to take a holistic approach integrating the optimisation process in different clinical activities. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Nurse strategies for optimising patient participation in nursing care.

PubMed

Sahlsten, Monika J M; Larsson, Inga E; Sjöström, Björn; Plos, Kaety A E

2009-09-01

THE STUDY'S RATIONALE: Patient participation is an essential factor in nursing care and medical treatment and a legal right in many countries. Despite this, patients have experienced insufficient participation, inattention and neglect regarding their problems and may respond with dependence, passivity or taciturnity. Accordingly, nurses strategies for optimising patient participation in nursing care is an important question for the nursing profession. The aim was to explore Registered Nurses' strategies to stimulate and optimise patient participation in nursing care. The objective was to identify ward nurses' supporting practices. A qualitative research approach was applied. Three focus groups with experienced Registered Nurses providing inpatient somatic care (n = 16) were carried out. These nurses were recruited from three hospitals in West Sweden. The data were analysed using content analysis technique. The ethics of scientific work was adhered to. According to national Swedish legislation, no formal permit from an ethics committee was required. The participants gave informed consent after verbal and written information. Nurse strategies for optimising patient participation in nursing care were identified as three categories: 'Building close co-operation', 'Getting to know the person' and 'Reinforcing self-care capacity' and their 10 subcategories. The strategies point to a process of emancipation of the patient's potential by finding his/her own inherent knowledge, values, motivation and goals and linking these to actions. Nurses need to strive for guiding the patient towards attaining meaningful experiences, discoveries, learning and development. The strategies are important and useful to balance the asymmetry in the nurse-patient relationship in daily nursing practice and also in quality assurance to evaluate and improve patient participation and in education. However, further verification of the findings is recommended by means of replication or other studies in different clinical settings. © 2009 The Authors. Journal compilation © 2009 Nordic College of Caring Science.

BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience.

PubMed

Van Geit, Werner; Gevaert, Michael; Chindemi, Giuseppe; Rössert, Christian; Courcol, Jean-Denis; Muller, Eilif B; Schürmann, Felix; Segev, Idan; Markram, Henry

2016-01-01

At many scales in neuroscience, appropriate mathematical models take the form of complex dynamical systems. Parameterizing such models to conform to the multitude of available experimental constraints is a global non-linear optimisation problem with a complex fitness landscape, requiring numerical techniques to find suitable approximate solutions. Stochastic optimisation approaches, such as evolutionary algorithms, have been shown to be effective, but often the setting up of such optimisations and the choice of a specific search algorithm and its parameters is non-trivial, requiring domain-specific expertise. Here we describe BluePyOpt, a Python package targeted at the broad neuroscience community to simplify this task. BluePyOpt is an extensible framework for data-driven model parameter optimisation that wraps and standardizes several existing open-source tools. It simplifies the task of creating and sharing these optimisations, and the associated techniques and knowledge. This is achieved by abstracting the optimisation and evaluation tasks into various reusable and flexible discrete elements according to established best-practices. Further, BluePyOpt provides methods for setting up both small- and large-scale optimisations on a variety of platforms, ranging from laptops to Linux clusters and cloud-based compute infrastructures. The versatility of the BluePyOpt framework is demonstrated by working through three representative neuroscience specific use cases.

Optimisation of biocide dose as a function of residual biocide in a heat exchanger pilot plant effluent.

PubMed

Eguía, Emilio; Trueba, Alfredo; Girón, Alfredo; Río-Calonge, Belén; Otero, Félix; Bielva, Carlos

2007-01-01

Biofouling is one of the most serious problems facing numerous industrial processes. In the case of a heat exchanger unit, biological deposits adhering to the inside surface of its tubes reduce heat transfer and, thus, the thermal performance of the cycle. Control of this phenomenon is proving fundamental for both land and marine equipment to operate in optimum working conditions. Hence, it is necessary to apply antifouling methods capable of keeping surfaces free of any kind of biofouling. This paper reports on the behaviour resulting from use of the flow inversion method vs that obtained by using various chemical treatments. The study compares the effectiveness of certain chemical treatments (Na hypochlorite, peracetic acid and a compound formed by Na bromide + Na hypochlorite) for removing a biofouling film that has already formed on the inside surfaces of tubes in a heat exchanger pilot plant. The paper also addresses the issue of optimising the concentration of biocide dose as a function of the residual biocide in order minimise the environmental impact caused by effluent from industrial plants. The results indicate that it is possible to eliminate a biofilm formed on the inside surfaces of tubes by the use of intermittent doses of chemical treatments at low concentrations and over long application times. Furthermore, once the stabilisation phase is reached 6 d after starting the treatment, it is possible to maintain the conditions achieved using only 20% of the initial dosage.

Optimised management of orphan wastes in the UK

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doudou, Slimane; McTeer, Jennifer; Wickham, Stephen

2013-07-01

Orphan wastes have properties preventing them from being managed according to existing or currently planned management routes, or lack characterisation so that their management is uncertain. The identification of new management opportunities for orphan wastes could realise significant benefits by reducing the number of processing facilities required, reducing waste volumes, reducing hazard or leading to the development of centres of excellence for the processing of certain types of orphan wastes. Information on the characteristics of orphan waste existing at nuclear licensed sites across the UK has been collated and a database developed to act as a repository for the informationmore » gathered. The database provides a capability to analyse the data and to explore possible treatment technologies for each orphan waste type. Thirty five distinct orphan waste types have been defined and possible treatment options considered. Treatment technologies (including chemical, high temperature, immobilisation and physical technologies) that could be applied to one or more of the generic orphan waste streams have been identified. Wiring diagrams have been used to highlight the waste treatment / lifecycle management options that are available for each of the generic orphan groups as well as identifying areas for further research and development. This work has identified the potential for optimising the management of orphan wastes in a number of areas, and many potential opportunities were identified. Such opportunities could be investigated by waste managers at waste producing nuclear sites, to facilitate the development of new management routes for orphan wastes. (authors)« less

[Optimising azathioprine treatment: determination of thiopurine methyltransferase activity and thiopurine metabolites].

PubMed

Alvarez Beltran, M; Infante Pina, D; Tormo Carnicé, R; Segarra Cantón, O; Redecillas Ferreiro, S

2009-02-01

Individualised doses of azathioprine (AZA) may be prescribed by monitoring the levels of the enzyme thiopurine methyltransferase (TPMT). The measurements of thiopurine metabolites of AZA, 6-thioguanine (6-TGN) and 6-methylmercaptopurine (6-MMP), have also been reported as new markers of AZA activity. To describe TPMT phenotype in our population and to establish a relationship between thiopurine metabolites,and therapeutic activity and adverse effects. Data on TPMT were retrospectively collected from 107 patients, and 6-TGN and 6-MMP levels in 18 patients currently on treatment with AZA (Crohn's disease 5, ulcerative colitis 5, autoimmune hepatitis 5). Mean value of TPMT was 20.19U/ml. None of the patients had a TPMT activity<5U/ml. Of the 18 patients on treatment, 13 showed sub-therapeutic levels of 6-TGN (<235pmol/8x10(8) red blood cells). Clinical remission was maintained in 45% of patients. Mean levels of 6-TGN in patients with clinical remission were 259pmol/8x10(8) red blood cells versus 209pmol/8x10(8) red blood cells in non-responders (p=0.37). There was an inverse relationship (r=-0.28) between TPMT and 6-TGN levels. Toxic effects occurred in 6 of 18 patients, with leukopenia in 5 and hyperamylasemia in 1. Determination of TPMT and monitoring of thiopurine metabolites allows AZA treatment to be optimised, although further studies are necessary to establish therapeutic effectiveness and toxicity ranges.

Nursing implications: symptom presentation and quality of life in rectal cancer patients.

PubMed

O'Gorman, Claire; Barry, Amanda; Denieffe, Suzanne; Sasiadek, Wojciech; Gooney, Martina

2016-05-01

To determine the changes in symptoms experienced by rectal cancer patients during preoperative chemoradiotherapy, with a specific focus on fatigue and to explore how symptoms impact the quality of life. Rectal cancer continues to be a healthcare issue internationally, despite advances in management strategies, which includes the administration of preoperative chemoradiotherapy to improve locoregional control. It is known that this treatment may cause adverse effects; however, there is a paucity of literature that specifically examines fatigue, symptoms and quality of life in this patient cohort. A prospective, quantitative correlational design using purposive sampling was adopted. Symptoms and quality of life were measured with validated questionnaires in 35 patients at four time points. Symptoms that changed significantly over time as examined using rm-anova include fatigue, bowel function issues, nutritional issues, pain, dermatological issues and urinary function issues. Findings indicate that fatigue leads to poorer quality of life, with constipation, bloating, stool frequency, appetite loss, weight worry, nausea and vomiting, dry mouth and pain also identified as influencing factors on quality of life. Findings have highlighted the importance of thorough symptom assessment and management of patients receiving preoperative chemoradiotherapy, particularly midway through treatment, in order to optimise quality of life and minimise interruptions to treatment. Close monitoring of symptoms during preoperative chemoradiotherapy, particularly at week 4, will enable the implementation of timely interventions so that interruptions to treatment are prevented and the quality of life is optimised, which may hasten postoperative recovery times. © 2016 John Wiley & Sons Ltd.

Psychedelics and the essential importance of context.

PubMed

Carhart-Harris, Robin Lester; Roseman, Leor; Haijen, Eline; Erritzoe, David; Watts, Rosalind; Branchi, Igor; Kaelen, Mendel

2018-02-01

Psychedelic drugs are making waves as modern trials support their therapeutic potential and various media continue to pique public interest. In this opinion piece, we draw attention to a long-recognised component of the psychedelic treatment model, namely ‘set’ and ‘setting’ – subsumed here under the umbrella term ‘context’. We highlight: (a) the pharmacological mechanisms of classic psychedelics (5-HT2A receptor agonism and associated plasticity) that we believe render their effects exceptionally sensitive to context, (b) a study design for testing assumptions regarding positive interactions between psychedelics and context, and (c) new findings from our group regarding contextual determinants of the quality of a psychedelic experience and how acute experience predicts subsequent long-term mental health outcomes. We hope that this article can: (a) inform on good practice in psychedelic research, (b) provide a roadmap for optimising treatment models, and(c) help tackle unhelpful stigma still surrounding these compounds, while developing an evidence base for long-held assumptions about the critical importance of context in relation to psychedelic use that can help minimise harms and maximise potential benefits. (c) help tackle unhelpful stigma still surrounding these compounds, while developing an evidence base for long-held assumptions about the critical importance of context in relation to psychedelic use that can help minimise harms and maximise potential benefits.

Development and optimisation of atorvastatin calcium loaded self-nanoemulsifying drug delivery system (SNEDDS) for enhancing oral bioavailability: in vitro and in vivo evaluation.

PubMed

Kassem, Abdulsalam M; Ibrahim, Hany M; Samy, Ahmed M

2017-05-01

The objective of this study was to develop and optimise self-nanoemulsifying drug delivery system (SNEDDS) of atorvastatin calcium (ATC) for improving dissolution rate and eventually oral bioavailability. Ternary phase diagrams were constructed on basis of solubility and emulsification studies. The composition of ATC-SNEDDS was optimised using the Box-Behnken optimisation design. Optimised ATC-SNEDDS was characterised for various physicochemical properties. Pharmacokinetic, pharmacodynamic and histological findings were performed in rats. Optimised ATC-SNEDDS resulted in droplets size of 5.66 nm, zeta potential of -19.52 mV, t 90 of 5.43 min and completely released ATC within 30 min irrespective of pH of the medium. Area under the curve of optimised ATC-SNEDDS in rats was 2.34-folds higher than ATC suspension. Pharmacodynamic studies revealed significant reduction in serum lipids of rats with fatty liver. Photomicrographs showed improvement in hepatocytes structure. In this study, we confirmed that ATC-SNEDDS would be a promising approach for improving oral bioavailability of ATC.

Methodology for the Randomised Injecting Opioid Treatment Trial (RIOTT): evaluating injectable methadone and injectable heroin treatment versus optimised oral methadone treatment in the UK

PubMed Central

Lintzeris, Nicholas; Strang, John; Metrebian, Nicola; Byford, Sarah; Hallam, Christopher; Lee, Sally; Zador, Deborah

2006-01-01

Whilst unsupervised injectable methadone and diamorphine treatment has been part of the British treatment system for decades, the numbers receiving injectable opioid treatment (IOT) has been steadily diminishing in recent years. In contrast, there has been a recent expansion of supervised injectable diamorphine programs under trial conditions in a number of European and North American cities, although the evidence regarding the safety, efficacy and cost effectiveness of this treatment approach remains equivocal. Recent British clinical guidance indicates that IOT should be a second-line treatment for those patients in high-quality oral methadone treatment who continue to regularly inject heroin, and that treatment be initiated in newly-developed supervised injecting clinics. The Randomised Injectable Opioid Treatment Trial (RIOTT) is a multisite, prospective open-label randomised controlled trial (RCT) examining the role of treatment with injected opioids (methadone and heroin) for the management of heroin dependence in patients not responding to conventional substitution treatment. Specifically, the study examines whether efforts should be made to optimise methadone treatment for such patients (e.g. regular attendance, supervised dosing, high oral doses, access to psychosocial services), or whether such patients should be treated with injected methadone or heroin. Eligible patients (in oral substitution treatment and injecting illicit heroin on a regular basis) are randomised to one of three conditions: (1) optimized oral methadone treatment (Control group); (2) injected methadone treatment; or (3) injected heroin treatment (with access to oral methadone doses). Subjects are followed up for 6-months, with between-group comparisons on an intention-to-treat basis across a range of outcome measures. The primary outcome is the proportion of patients who discontinue regular illicit heroin use (operationalised as providing >50% urine drug screens negative for markers of illicit heroin in months 4 to 6). Secondary outcomes include measures of other drug use, injecting practices, health and psychosocial functioning, criminal activity, patient satisfaction and incremental cost effectiveness. The study aims to recruit 150 subjects, with 50 patients per group, and is to be conducted in supervised injecting clinics across England. PMID:17002810

Minimising the development of anthelmintic resistance, and optimising the use of the novel anthelmintic monepantel, for the sustainable control of nematode parasites in Australian sheep grazing systems.

PubMed

Dobson, R J; Hosking, B C; Besier, R B; Love, S; Larsen, J W A; Rolfe, P F; Bailey, J N

2011-05-01

To compare the risk of different treatment scenarios on selecting for anthelmintic resistance on Australian sheep farms. A computer simulation model predicted populations of Trichostrongylus colubriformis, Haemonchus contortus or Teladorsagia (Ostertagia) circumcincta, and the frequency of anthelmintic resistance genes. Nematode populations and the progression of drug resistance for a variety of treatment options and management practices in sheep-rearing areas of Western Australia (WA), Victoria (VIC) and New South Wales (NSW) were simulated. A scoring system was devised to measure the success of each option in delaying resistance to each anthelmintic and in controlling nematode populations. The best option at all sites was combining the new anthelmintic (monepantel) with a triple mixture of benzimidazole, levamisole and abamectin (COM). The next best option was: in NSW, rotation at each treatment between monepantel, moxidectin and COM; in VIC, rotation at each treatment between monepantel and COM; and in WA, rotation at each treatment between monepantel (used in winter) and COM or moxidectin (used in summer-autumn). In WA, rapid selection for resistance occurred as a consequence of summer-autumn treatments; however, if a small percentage of adult stock were left untreated then this selection could be greatly reduced. Despite purposely assuming relatively high resistance to benzimidazole and levamisole, COM was still effective in controlling worms and delaying resistance. Because of cost constraints, it may not be feasible or profitable for producers to always use the combination of all drugs. However, the second- and third-best options still considerably slowed the development of anthelmintic resistance. © 2011 The Authors. Australian Veterinary Journal © 2011 Australian Veterinary Association.

Application of Three Existing Stope Boundary Optimisation Methods in an Operating Underground Mine

NASA Astrophysics Data System (ADS)

Erdogan, Gamze; Yavuz, Mahmut

2017-12-01

The underground mine planning and design optimisation process have received little attention because of complexity and variability of problems in underground mines. Although a number of optimisation studies and software tools are available and some of them, in special, have been implemented effectively to determine the ultimate-pit limits in an open pit mine, there is still a lack of studies for optimisation of ultimate stope boundaries in underground mines. The proposed approaches for this purpose aim at maximizing the economic profit by selecting the best possible layout under operational, technical and physical constraints. In this paper, the existing three heuristic techniques including Floating Stope Algorithm, Maximum Value Algorithm and Mineable Shape Optimiser (MSO) are examined for optimisation of stope layout in a case study. Each technique is assessed in terms of applicability, algorithm capabilities and limitations considering the underground mine planning challenges. Finally, the results are evaluated and compared.

Design Optimisation of a Magnetic Field Based Soft Tactile Sensor

PubMed Central

Raske, Nicholas; Kow, Junwai; Alazmani, Ali; Ghajari, Mazdak; Culmer, Peter; Hewson, Robert

2017-01-01

This paper investigates the design optimisation of a magnetic field based soft tactile sensor, comprised of a magnet and Hall effect module separated by an elastomer. The aim was to minimise sensitivity of the output force with respect to the input magnetic field; this was achieved by varying the geometry and material properties. Finite element simulations determined the magnetic field and structural behaviour under load. Genetic programming produced phenomenological expressions describing these responses. Optimisation studies constrained by a measurable force and stable loading conditions were conducted; these produced Pareto sets of designs from which the optimal sensor characteristics were selected. The optimisation demonstrated a compromise between sensitivity and the measurable force, a fabricated version of the optimised sensor validated the improvements made using this methodology. The approach presented can be applied in general for optimising soft tactile sensor designs over a range of applications and sensing modes. PMID:29099787

Freeze-dried, mucoadhesive system for vaginal delivery of the HIV microbicide, dapivirine: optimisation by an artificial neural network.

PubMed

Woolfson, A David; Umrethia, Manish L; Kett, Victoria L; Malcolm, R Karl

2010-03-30

Dapivirine mucoadhesive gels and freeze-dried tablets were prepared using a 3x3x2 factorial design. An artificial neural network (ANN) with multi-layer perception was used to investigate the effect of hydroxypropyl-methylcellulose (HPMC): polyvinylpyrrolidone (PVP) ratio (X1), mucoadhesive concentration (X2) and delivery system (gel or freeze-dried mucoadhesive tablet, X3) on response variables; cumulative release of dapivirine at 24h (Q(24)), mucoadhesive force (F(max)) and zero-rate viscosity. Optimisation was performed by minimising the error between the experimental and predicted values of responses by ANN. The method was validated using check point analysis by preparing six formulations of gels and their corresponding freeze-dried tablets randomly selected from within the design space of contour plots. Experimental and predicted values of response variables were not significantly different (p>0.05, two-sided paired t-test). For gels, Q(24) values were higher than their corresponding freeze-dried tablets. F(max) values for freeze-dried tablets were significantly different (2-4 times greater, p>0.05, two-sided paired t-test) compared to equivalent gels. Freeze-dried tablets having lower values for X1 and higher values for X2 components offered the best compromise between effective dapivirine release, mucoadhesion and viscosity such that increased vaginal residence time was likely to be achieved. Copyright (c) 2009 Elsevier B.V. All rights reserved.

Probabilistic Seeking Prediction in P2P VoD Systems

NASA Astrophysics Data System (ADS)

Wang, Weiwei; Xu, Tianyin; Gao, Yang; Lu, Sanglu

In P2P VoD streaming systems, user behavior modeling is critical to help optimise user experience as well as system throughput. However, it still remains a challenging task due to the dynamic characteristics of user viewing behavior. In this paper, we consider the problem of user seeking prediction which is to predict the user's next seeking position so that the system can proactively make response. We present a novel method for solving this problem. In our method, frequent sequential patterns mining is first performed to extract abstract states which are not overlapped and cover the whole video file altogether. After mapping the raw training dataset to state transitions according to the abstract states, we use a simpel probabilistic contingency table to build the prediction model. We design an experiment on the synthetic P2P VoD dataset. The results demonstrate the effectiveness of our method.

Optimising cluster survey design for planning schistosomiasis preventive chemotherapy

PubMed Central

Sturrock, Hugh J. W.; Turner, Hugo; Whitton, Jane M.; Gower, Charlotte M.; Jemu, Samuel; Phillips, Anna E.; Meite, Aboulaye; Thomas, Brent; Kollie, Karsor; Thomas, Catherine; Rebollo, Maria P.; Styles, Ben; Clements, Michelle; Fenwick, Alan; Harrison, Wendy E.; Fleming, Fiona M.

2017-01-01

Background The cornerstone of current schistosomiasis control programmes is delivery of praziquantel to at-risk populations. Such preventive chemotherapy requires accurate information on the geographic distribution of infection, yet the performance of alternative survey designs for estimating prevalence and converting this into treatment decisions has not been thoroughly evaluated. Methodology/Principal findings We used baseline schistosomiasis mapping surveys from three countries (Malawi, Côte d’Ivoire and Liberia) to generate spatially realistic gold standard datasets, against which we tested alternative two-stage cluster survey designs. We assessed how sampling different numbers of schools per district (2–20) and children per school (10–50) influences the accuracy of prevalence estimates and treatment class assignment, and we compared survey cost-efficiency using data from Malawi. Due to the focal nature of schistosomiasis, up to 53% simulated surveys involving 2–5 schools per district failed to detect schistosomiasis in low endemicity areas (1–10% prevalence). Increasing the number of schools surveyed per district improved treatment class assignment far more than increasing the number of children sampled per school. For Malawi, surveys of 15 schools per district and 20–30 children per school reliably detected endemic schistosomiasis and maximised cost-efficiency. In sensitivity analyses where treatment costs and the country considered were varied, optimal survey size was remarkably consistent, with cost-efficiency maximised at 15–20 schools per district. Conclusions/Significance Among two-stage cluster surveys for schistosomiasis, our simulations indicated that surveying 15–20 schools per district and 20–30 children per school optimised cost-efficiency and minimised the risk of under-treatment, with surveys involving more schools of greater cost-efficiency as treatment costs rose. PMID:28552961

Predictive value of stroke discharge diagnoses in the Danish National Patient Register.

PubMed

Lühdorf, Pernille; Overvad, Kim; Schmidt, Erik B; Johnsen, Søren P; Bach, Flemming W

2017-08-01

To determine the positive predictive values for stroke discharge diagnoses, including subarachnoidal haemorrhage, intracerebral haemorrhage and cerebral infarction in the Danish National Patient Register. Participants in the Danish cohort study Diet, Cancer and Health with a stroke discharge diagnosis in the National Patient Register between 1993 and 2009 were identified and their medical records were retrieved for validation of the diagnoses. A total of 3326 records of possible cases of stroke were reviewed. The overall positive predictive value for stroke was 69.3% (95% confidence interval (CI) 67.8-70.9%). The predictive values differed according to hospital characteristics, with the highest predictive value of 87.8% (95% CI 85.5-90.1%) found in departments of neurology and the lowest predictive value of 43.0% (95% CI 37.6-48.5%) found in outpatient clinics. The overall stroke diagnosis in the Danish National Patient Register had a limited predictive value. We therefore recommend the critical use of non-validated register data for research on stroke. The possibility of optimising the predictive values based on more advanced algorithms should be considered.

The Tungsten Inert GAS (TIG) Process of Welding Aluminium in Microgravity: Technical and Economic Considerations

NASA Astrophysics Data System (ADS)

Ferretti, S.; Amadori, K.; Boccalatte, A.; Alessandrini, M.; Freddi, A.; Persiani, F.; Poli, G.

2002-01-01

The UNIBO team composed of students and professors of the University of Bologna along with technicians and engineers from Alenia Space Division and Siad Italargon Division, took part in the 3rd Student Parabolic Flight Campaign of the European Space Agency in 2000. It won the student competition and went on to take part in the Professional Parabolic Flight Campaign of May 2001. The experiment focused on "dendritic growth in aluminium alloy weldings", and investigated topics related to the welding process of aluminium in microgravity. The purpose of the research is to optimise the process and to define the areas of interest that could be improved by new conceptual designs. The team performed accurate tests in microgravity to determine which phenomena have the greatest impact on the quality of the weldings with respect to penetration, surface roughness and the microstructures that are formed during the solidification. Various parameters were considered in the economic-technical optimisation, such as the type of electrode and its tip angle. Ground and space tests have determined the optimum chemical composition of the electrodes to offer longest life while maintaining the shape of the point. Additionally, the power consumption has been optimised; this offers opportunities for promoting the product to the customer as well as being environmentally friendly. Tests performed on the Al-Li alloys showed a significant influence of some physical phenomena such as the Marangoni effect and thermal diffusion; predictions have been made on the basis of observations of the thermal flux seen in the stereophotos. Space transportation today is a key element in the construction of space stations and future planetary bases, because the volumes available for launch to space are directly related to the payload capacity of rockets or the Space Shuttle. The research performed gives engineers the opportunity to consider completely new concepts for designing structures for space applications. In fact, once the optimised parameters are defined for welding in space, it could be possible to weld different parts directly in orbit to obtain much larger sizes and volumes, for example for space tourism habitation modules. The second relevant aspect is technology transfer obtained by the optimisation of the TIG process on aluminium which is often used in the automotive industry as well as in mass production markets.

Patient information, education and self-management in bronchiectasis: facilitating improvements to optimise health outcomes.

PubMed

Hester, Katy L M; Newton, Julia; Rapley, Tim; De Soyza, Anthony

2018-05-22

Bronchiectasis is an incurable lung disease characterised by irreversible airway dilatation. It causes symptoms including chronic productive cough, dyspnoea, and recurrent respiratory infections often requiring hospital admission. Fatigue and reductions in quality of life are also reported in bronchiectasis. Patients often require multi-modal treatments that can be burdensome, leading to issues with adherence. In this article we review the provision of, and requirement for, education and information in bronchiectasis. To date, little research has been undertaken to improve self-management in bronchiectasis in comparison to other chronic conditions, such as COPD, for which there has been a wealth of recent developments. Qualitative work has begun to establish that information deficit is one of the potential barriers to self-management, and that patients feel having credible information is fundamental when learning to live with and manage bronchiectasis. Emerging research offers some insights into ways of improving treatment adherence and approaches to self-management education; highlighting ways of addressing the specific unmet information needs of patients and their families who are living with bronchiectasis. We propose non-pharmacological recommendations to optimise patient self-management and symptom recognition; with the aim of facilitating measurable improvements in health outcomes for patients with bronchiectasis.

Subnanomolar indazole-5-carboxamide inhibitors of monoamine oxidase B (MAO-B) continued: indications of iron binding, experimental evidence for optimised solubility and brain penetration.

PubMed

Tzvetkov, Nikolay T; Antonov, Liudmil

2017-12-01

Pharmacological and physicochemical studies of N-unsubstituted indazole-5-carboxamides (subclass I) and their structurally optimised N1-methylated analogues (subclass II), initially developed as drug and radioligand candidates for the treatment and diagnosis of Parkinson's disease (PD), are presented. The compounds are highly brain permeable, selective, reversible, and competitive monoamine oxidase B (MAO-B) inhibitors with improved water-solubility and subnanomolar potency (pIC 50  >8.8). Using a well-validated, combined X-ray/modelling technology platform, we performed a semi-quantitative analysis of the binding modes of all compounds and investigated the role of the indazole N1 position for their MAO-B inhibitory activity. Moreover, compounds NTZ-1006, 1032, and 1441 were investigated for their ability to bind Fe 2+ and Fe 3+ ions using UV-visible spectroscopy.

Subcritical water liquefaction of oil palm fruit press fiber in the presence of sodium hydroxide: an optimisation study using response surface methodology.

PubMed

Mazaheri, Hossein; Lee, Keat Teong; Bhatia, Subhash; Mohamed, Abdul Rahman

2010-12-01

Thermal decomposition of oil palm fruit press fiber (FPF) into a liquid product (LP) was achieved using subcritical water treatment in the presence of sodium hydroxide in a high pressure batch reactor. This study uses experimental design and process optimisation tools to maximise the LP yield using response surface methodology (RSM) with central composite rotatable design (CCRD). The independent variables were temperature, residence time, particle size, specimen loading, and additive loading. The mathematical model that was developed fit the experimental results well for all of the response variables that were studied. The optimal conditions were found to be a temperature of 551 K, a residence time of 40 min, a particle size of 710-1000 microm, a specimen loading of 5 g, and a additive loading of 9 wt.% to achieve a LP yield of 76.16%. 2010 Elsevier Ltd. All rights reserved.

[Inappropriate ICD therapies: All problems solved with MADIT-RIT?].

PubMed

Kolb, Christof

2015-06-01

The MADIT-RIT study represents a major trial in implantable cardioverter-defibrillator (ICD) therapy that was recently published. It highlights that different programming strategies (high rate cut-off or delayed therapy versus conventional) reduce inappropriate ICD therapies, leave syncope rates unaltered and can improve patient's survival. The study should motivate cardiologist and electrophysiologists to reconsider their individual programming strategies. However, as the study represents largely patients with ischemic or dilated cardiomyopathy for primary prevention of sudden cardiac death supplied with a dual chamber or cardiac resynchronisation therapy ICD, the results may not easily be transferable to other entities or other device types. Despite the success of the MADIT-RIT study efforts still need to be taken to further optimise device algorithms to avert inappropriate therapies. Optimised ICD therapy also includes the avoidance of unnecessary ICD shocks as well as the treatment of all aspects of the underlying cardiac disease.

BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience

PubMed Central

Van Geit, Werner; Gevaert, Michael; Chindemi, Giuseppe; Rössert, Christian; Courcol, Jean-Denis; Muller, Eilif B.; Schürmann, Felix; Segev, Idan; Markram, Henry

2016-01-01

At many scales in neuroscience, appropriate mathematical models take the form of complex dynamical systems. Parameterizing such models to conform to the multitude of available experimental constraints is a global non-linear optimisation problem with a complex fitness landscape, requiring numerical techniques to find suitable approximate solutions. Stochastic optimisation approaches, such as evolutionary algorithms, have been shown to be effective, but often the setting up of such optimisations and the choice of a specific search algorithm and its parameters is non-trivial, requiring domain-specific expertise. Here we describe BluePyOpt, a Python package targeted at the broad neuroscience community to simplify this task. BluePyOpt is an extensible framework for data-driven model parameter optimisation that wraps and standardizes several existing open-source tools. It simplifies the task of creating and sharing these optimisations, and the associated techniques and knowledge. This is achieved by abstracting the optimisation and evaluation tasks into various reusable and flexible discrete elements according to established best-practices. Further, BluePyOpt provides methods for setting up both small- and large-scale optimisations on a variety of platforms, ranging from laptops to Linux clusters and cloud-based compute infrastructures. The versatility of the BluePyOpt framework is demonstrated by working through three representative neuroscience specific use cases. PMID:27375471

Optimisation of the hybrid renewable energy system by HOMER, PSO and CPSO for the study area

NASA Astrophysics Data System (ADS)

Khare, Vikas; Nema, Savita; Baredar, Prashant

2017-04-01

This study is based on simulation and optimisation of the renewable energy system of the police control room at Sagar in central India. To analyse this hybrid system, the meteorological data of solar insolation and hourly wind speeds of Sagar in central India (longitude 78°45‧ and latitude 23°50‧) have been considered. The pattern of load consumption is studied and suitably modelled for optimisation of the hybrid energy system using HOMER software. The results are compared with those of the particle swarm optimisation and the chaotic particle swarm optimisation algorithms. The use of these two algorithms to optimise the hybrid system leads to a higher quality result with faster convergence. Based on the optimisation result, it has been found that replacing conventional energy sources by the solar-wind hybrid renewable energy system will be a feasible solution for the distribution of electric power as a stand-alone application at the police control room. This system is more environmentally friendly than the conventional diesel generator. The fuel cost reduction is approximately 70-80% more than that of the conventional diesel generator.

Physiologically based pharmacokinetic modelling of methotrexate and 6-mercaptopurine in adults and children. Part 2: 6-mercaptopurine and its interaction with methotrexate.

PubMed

Ogungbenro, Kayode; Aarons, Leon

2014-04-01

6-mercaptopurine (6-MP) is a purine antimetabolite and prodrug that undergoes extensive intracellular metabolism to produce thionucleotides, active metabolites which have cytotoxic and immunosuppressive properties. Combination therapies involving 6-MP and methotrexate have shown remarkable results in the cure of childhood acute lymphoblastic leukaemia (ALL) in the last 30 years. 6-MP undergoes very extensive intestinal and hepatic metabolism following oral dosing due to the activity of xanthine oxidase leading to very low and highly variable bioavailability and methotrexate has been demonstrated as an inhibitor of xanthine oxidase. Despite the success recorded in the use of 6-MP in ALL, there is still lack of effect and life threatening toxicity in some patients due to variability in the pharmacokinetics of 6-MP. Also, dose adjustment during treatment is still based on toxicity. The aim of the current work was to develop a mechanistic model that can be used to simulate trial outcomes and help to improve dose individualisation and dosage regimen optimisation. A physiological based pharmacokinetic model was proposed for 6-MP, this model has compartments for stomach, gut lumen, enterocyte, gut tissue, spleen, liver vascular, liver tissue, kidney vascular, kidney tissue, skin, bone marrow, thymus, muscle, rest of body and red blood cells. The model was based on the assumption of the same elimination pathways in adults and children. Parameters of the model include physiological parameters and drug-specific parameter which were obtained from the literature or estimated using plasma and red blood cell concentration data. Age-dependent changes in parameters were implemented for scaling and variability was also introduced on the parameters for prediction. Inhibition of 6-MP first-pass effect by methotrexate was implemented to predict observed clinical interaction between the two drugs. The model was developed successfully and plasma and red blood cell concentrations were adequately predicted both in terms of mean prediction and variability. The predicted interaction between 6-MP and methotrexate was slightly lower than the reported clinical interaction between the two drugs. The model can be used to predict plasma and tissue concentration in adults and children following oral and intravenous dosing and may ultimately help to improve treatment outcome in childhood ALL patients.

Aquatic therapy for boys with Duchenne muscular dystrophy (DMD): an external pilot randomised controlled trial.

PubMed

Hind, Daniel; Parkin, James; Whitworth, Victoria; Rex, Saleema; Young, Tracey; Hampson, Lisa; Sheehan, Jennie; Maguire, Chin; Cantrill, Hannah; Scott, Elaine; Epps, Heather; Main, Marion; Geary, Michelle; McMurchie, Heather; Pallant, Lindsey; Woods, Daniel; Freeman, Jennifer; Lee, Ellen; Eagle, Michelle; Willis, Tracey; Muntoni, Francesco; Baxter, Peter

2017-01-01

Standard treatment of Duchenne muscular dystrophy (DMD) includes regular physiotherapy. There are no data to show whether adding aquatic therapy (AT) to land-based exercises helps maintain motor function. We assessed the feasibility of recruiting and collecting data from boys with DMD in a parallel-group pilot randomised trial (primary objective), also assessing how intervention and trial procedures work. Ambulant boys with DMD aged 7-16 years established on steroids, with North Star Ambulatory Assessment (NSAA) score ≥8, who were able to complete a 10-m walk test without aids or assistance, were randomly allocated (1:1) to 6 months of either optimised land-based exercises 4 to 6 days/week, defined by local community physiotherapists, or the same 4 days/week plus AT 2 days/week. Those unable to commit to a programme, with >20% variation between NSAA scores 4 weeks apart, or contraindications to AT were excluded. The main outcome measures included feasibility of recruiting 40 participants in 6 months from six UK centres, clinical outcomes including NSAA, independent assessment of treatment optimisation, participant/therapist views on acceptability of intervention and research protocols, value of information (VoI) analysis and cost-impact analysis. Over 6 months, 348 boys were screened: most lived too far from centres or were enrolled in other trials; 12 (30% of the targets) were randomised to AT ( n  = 8) or control ( n  = 4). The mean change in NSAA at 6 months was -5.5 (SD 7.8) in the control arm and -2.8 (SD 4.1) in the AT arm. Harms included fatigue in two boys, pain in one. Physiotherapists and parents valued AT but believed it should be delivered in community settings. Randomisation was unattractive to families, who had already decided that AT was useful and who often preferred to enrol in drug studies. The AT prescription was considered to be optimised for three boys, with other boys given programmes that were too extensive and insufficiently focused. Recruitment was insufficient for VoI analysis. Neither a UK-based RCT of AT nor a twice weekly AT therapy delivered at tertiary centres is feasible. Our study will help in the optimisation of AT service provision and the design of future research. ISRCTN41002956.

Multiobjective optimisation of bogie suspension to boost speed on curves

NASA Astrophysics Data System (ADS)

Milad Mousavi-Bideleh, Seyed; Berbyuk, Viktor

2016-01-01

To improve safety and maximum admissible speed on different operational scenarios, multiobjective optimisation of bogie suspension components of a one-car railway vehicle model is considered. The vehicle model has 50 degrees of freedom and is developed in multibody dynamics software SIMPACK. Track shift force, running stability, and risk of derailment are selected as safety objective functions. The improved maximum admissible speeds of the vehicle on curves are determined based on the track plane accelerations up to 1.5 m/s2. To attenuate the number of design parameters for optimisation and improve the computational efficiency, a global sensitivity analysis is accomplished using the multiplicative dimensional reduction method (M-DRM). A multistep optimisation routine based on genetic algorithm (GA) and MATLAB/SIMPACK co-simulation is executed at three levels. The bogie conventional secondary and primary suspension components are chosen as the design parameters in the first two steps, respectively. In the last step semi-active suspension is in focus. The input electrical current to magnetorheological yaw dampers is optimised to guarantee an appropriate safety level. Semi-active controllers are also applied and the respective effects on bogie dynamics are explored. The safety Pareto optimised results are compared with those associated with in-service values. The global sensitivity analysis and multistep approach significantly reduced the number of design parameters and improved the computational efficiency of the optimisation. Furthermore, using the optimised values of design parameters give the possibility to run the vehicle up to 13% faster on curves while a satisfactory safety level is guaranteed. The results obtained can be used in Pareto optimisation and active bogie suspension design problems.

Rapid biochemical methane potential prediction of urban organic waste with near-infrared reflectance spectroscopy.

PubMed

Fitamo, T; Triolo, J M; Boldrin, A; Scheutz, C

2017-08-01

The anaerobic digestibility of various biomass feedstocks in biogas plants is determined with biochemical methane potential (BMP) assays. However, experimental BMP analysis is time-consuming, costly and challenging to optimise stock management and feeding to achieve improved biogas production. The aim of the present study is to develop a fast and reliable model based on near-infrared reflectance spectroscopy (NIRS) for the BMP prediction of urban organic waste (UOW). The model comprised 87 UOW samples. Additionally, 88 plant biomass samples were included, to develop a combined model predicting BMP. The coefficient of determination (R 2 ) and root mean square error in prediction (RMSE P ) of the UOW model were 0.88 and 44 mL CH 4 /g VS, while the combined model was 0.89 and 50 mL CH 4 /g VS. Improved model performance was obtained for the two individual models compared to the combined version. The BMP prediction with NIRS was satisfactory and moderately successful. Copyright © 2017 Elsevier Ltd. All rights reserved.

4th Annual Predictive Toxicology Summit 2012.

PubMed

Cui, Zhanfeng

2013-08-01

This meeting report presents a brief summary on the 4th Annual Predictive Toxicology Summit 2012, which was held on 15 - 16 February 2012 in London. The majority of presentations came from global pharmaceutical companies, although small and medium enterprise (SME) and academic researchers were represented too. Major regulatory bodies were also present. The article highlights the summit, which was considered a good learning opportunity to catch up on the recent advances in predictive toxicology. Predictive toxicology has become more and more important due to social and economic pressure and scientific reasons. Technological developments are rapid, but there is a gulf between the technology developers and the pharmaceutical end users; hence, early engagement is desirable. Stem cell-derived cell-based assays as well as three-dimensional in vitro tissue/organ model development are within the reach now, but a lot needs to be done to optimise and validate the developed protocols and products. The field of predictive toxicology needs fundamental research of interdisciplinary nature, which requires much needed trained personnel and funding.

An improved predictive functional control method with application to PMSM systems

NASA Astrophysics Data System (ADS)

Li, Shihua; Liu, Huixian; Fu, Wenshu

2017-01-01

In common design of prediction model-based control method, usually disturbances are not considered in the prediction model as well as the control design. For the control systems with large amplitude or strong disturbances, it is difficult to precisely predict the future outputs according to the conventional prediction model, and thus the desired optimal closed-loop performance will be degraded to some extent. To this end, an improved predictive functional control (PFC) method is developed in this paper by embedding disturbance information into the system model. Here, a composite prediction model is thus obtained by embedding the estimated value of disturbances, where disturbance observer (DOB) is employed to estimate the lumped disturbances. So the influence of disturbances on system is taken into account in optimisation procedure. Finally, considering the speed control problem for permanent magnet synchronous motor (PMSM) servo system, a control scheme based on the improved PFC method is designed to ensure an optimal closed-loop performance even in the presence of disturbances. Simulation and experimental results based on a hardware platform are provided to confirm the effectiveness of the proposed algorithm.

Preface of the "Symposium on Mathematical Models and Methods to investigate Heterogeneity in Cell and Cell Population Biology"

NASA Astrophysics Data System (ADS)

Clairambault, Jean

2016-06-01

This session investigates hot topics related to mathematical representations of cell and cell population dynamics in biology and medicine, in particular, but not only, with applications to cancer. Methods in mathematical modelling and analysis, and in statistical inference using single-cell and cell population data, should contribute to focus this session on heterogeneity in cell populations. Among other methods are proposed: a) Intracellular protein dynamics and gene regulatory networks using ordinary/partial/delay differential equations (ODEs, PDEs, DDEs); b) Representation of cell population dynamics using agent-based models (ABMs) and/or PDEs; c) Hybrid models and multiscale models to integrate single-cell dynamics into cell population behaviour; d) Structured cell population dynamics and asymptotic evolution w.r.t. relevant traits; e) Heterogeneity in cancer cell populations: origin, evolution, phylogeny and methods of reconstruction; f) Drug resistance as an evolutionary phenotype: predicting and overcoming it in therapeutics; g) Theoretical therapeutic optimisation of combined drug treatments in cancer cell populations and in populations of other organisms, such as bacteria.

Optimisation of insect cell growth in deep-well blocks: development of a high-throughput insect cell expression screen.

PubMed

Bahia, Daljit; Cheung, Robert; Buchs, Mirjam; Geisse, Sabine; Hunt, Ian

2005-01-01

This report describes a method to culture insects cells in 24 deep-well blocks for the routine small-scale optimisation of baculovirus-mediated protein expression experiments. Miniaturisation of this process provides the necessary reduction in terms of resource allocation, reagents, and labour to allow extensive and rapid optimisation of expression conditions, with the concomitant reduction in lead-time before commencement of large-scale bioreactor experiments. This therefore greatly simplifies the optimisation process and allows the use of liquid handling robotics in much of the initial optimisation stages of the process, thereby greatly increasing the throughput of the laboratory. We present several examples of the use of deep-well block expression studies in the optimisation of therapeutically relevant protein targets. We also discuss how the enhanced throughput offered by this approach can be adapted to robotic handling systems and the implications this has on the capacity to conduct multi-parallel protein expression studies.

Mutual information-based LPI optimisation for radar network

NASA Astrophysics Data System (ADS)

Shi, Chenguang; Zhou, Jianjiang; Wang, Fei; Chen, Jun

2015-07-01

Radar network can offer significant performance improvement for target detection and information extraction employing spatial diversity. For a fixed number of radars, the achievable mutual information (MI) for estimating the target parameters may extend beyond a predefined threshold with full power transmission. In this paper, an effective low probability of intercept (LPI) optimisation algorithm is presented to improve LPI performance for radar network. Based on radar network system model, we first provide Schleher intercept factor for radar network as an optimisation metric for LPI performance. Then, a novel LPI optimisation algorithm is presented, where for a predefined MI threshold, Schleher intercept factor for radar network is minimised by optimising the transmission power allocation among radars in the network such that the enhanced LPI performance for radar network can be achieved. The genetic algorithm based on nonlinear programming (GA-NP) is employed to solve the resulting nonconvex and nonlinear optimisation problem. Some simulations demonstrate that the proposed algorithm is valuable and effective to improve the LPI performance for radar network.

A novel global Harmony Search method based on Ant Colony Optimisation algorithm

NASA Astrophysics Data System (ADS)

Fouad, Allouani; Boukhetala, Djamel; Boudjema, Fares; Zenger, Kai; Gao, Xiao-Zhi

2016-03-01

The Global-best Harmony Search (GHS) is a stochastic optimisation algorithm recently developed, which hybridises the Harmony Search (HS) method with the concept of swarm intelligence in the particle swarm optimisation (PSO) to enhance its performance. In this article, a new optimisation algorithm called GHSACO is developed by incorporating the GHS with the Ant Colony Optimisation algorithm (ACO). Our method introduces a novel improvisation process, which is different from that of the GHS in the following aspects. (i) A modified harmony memory (HM) representation and conception. (ii) The use of a global random switching mechanism to monitor the choice between the ACO and GHS. (iii) An additional memory consideration selection rule using the ACO random proportional transition rule with a pheromone trail update mechanism. The proposed GHSACO algorithm has been applied to various benchmark functions and constrained optimisation problems. Simulation results demonstrate that it can find significantly better solutions when compared with the original HS and some of its variants.

A simple randomisation procedure for validating discriminant analysis: a methodological note.

PubMed

Wastell, D G

1987-04-01

Because the goal of discriminant analysis (DA) is to optimise classification, it designedly exaggerates between-group differences. This bias complicates validation of DA. Jack-knifing has been used for validation but is inappropriate when stepwise selection (SWDA) is employed. A simple randomisation test is presented which is shown to give correct decisions for SWDA. The general superiority of randomisation tests over orthodox significance tests is discussed. Current work on non-parametric methods of estimating the error rates of prediction rules is briefly reviewed.

Bioremediation of industrial effluents containing heavy metals using brewing cells of Saccharomyces cerevisiae as a green technology: a review.

PubMed

Soares, Eduardo V; Soares, Helena M V M

2012-05-01

The release of heavy metals into the environment, mainly as a consequence of anthropogenic activities, constitutes a worldwide environmental pollution problem. Unlike organic pollutants, heavy metals are not degraded and remain indefinitely in the ecosystem, which poses a different kind of challenge for remediation. It seems that the "best treatment technologies" available may not be completely effective for metal removal or can be expensive; therefore, new methodologies have been proposed for the detoxification of metal-bearing wastewaters. The present work reviews and discusses the advantages of using brewing yeast cells of Saccharomyces cerevisiae in the detoxification of effluents containing heavy metals. The current knowledge of the mechanisms of metal removal by yeast biomass is presented. The use of live or dead biomass and the influence of biomass inactivation on the metal accumulation characteristics are outlined. The role of chemical speciation for predicting and optimising the efficiency of metal removal is highlighted. The problem of biomass separation, after treatment of the effluents, and the use of flocculent characteristics, as an alternative process of cell-liquid separation, are also discussed. The use of yeast cells in the treatment of real effluents to bridge the gap between fundamental and applied studies is presented and updated. The convenient management of the contaminated biomass and the advantages of the selective recovery of heavy metals in the development of a closed cycle without residues (green technology) are critically reviewed.

Developing a scalable model of recombinant protein yield from Pichia pastoris: the influence of culture conditions, biomass and induction regime

PubMed Central

Holmes, William J; Darby, Richard AJ; Wilks, Martin DB; Smith, Rodney; Bill, Roslyn M

2009-01-01

Background The optimisation and scale-up of process conditions leading to high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences. Typical experiments rely on varying selected parameters through repeated rounds of trial-and-error optimisation. To rationalise this, several groups have recently adopted the 'design of experiments' (DoE) approach frequently used in industry. Studies have focused on parameters such as medium composition, nutrient feed rates and induction of expression in shake flasks or bioreactors, as well as oxygen transfer rates in micro-well plates. In this study we wanted to generate a predictive model that described small-scale screens and to test its scalability to bioreactors. Results Here we demonstrate how the use of a DoE approach in a multi-well mini-bioreactor permitted the rapid establishment of high yielding production phase conditions that could be transferred to a 7 L bioreactor. Using green fluorescent protein secreted from Pichia pastoris, we derived a predictive model of protein yield as a function of the three most commonly-varied process parameters: temperature, pH and the percentage of dissolved oxygen in the culture medium. Importantly, when yield was normalised to culture volume and density, the model was scalable from mL to L working volumes. By increasing pre-induction biomass accumulation, model-predicted yields were further improved. Yield improvement was most significant, however, on varying the fed-batch induction regime to minimise methanol accumulation so that the productivity of the culture increased throughout the whole induction period. These findings suggest the importance of matching the rate of protein production with the host metabolism. Conclusion We demonstrate how a rational, stepwise approach to recombinant protein production screens can reduce process development time. PMID:19570229

Smart strategies for doctors and doctors-in-training: heuristics in medicine.

PubMed

Wegwarth, Odette; Gaissmaier, Wolfgang; Gigerenzer, Gerd

2009-08-01

How do doctors make sound decisions when confronted with probabilistic data, time pressures and a heavy workload? One theory that has been embraced by many researchers is based on optimisation, which emphasises the need to integrate all information in order to arrive at sound decisions. This notion makes heuristics, which use less than complete information, appear as second-best strategies. In this article, we challenge this pessimistic view of heuristics. We introduce two medical problems that involve decision making to the reader: one concerns coronary care issues and the other macrolide prescriptions. In both settings, decision-making tools grounded in the principles of optimisation and heuristics, respectively, have been developed to assist doctors in making decisions. We explain the structure of each of these tools and compare their performance in terms of their facilitation of correct predictions. For decisions concerning both the coronary care unit and the prescribing of macrolides, we demonstrate that sacrificing information does not necessarily imply a forfeiting of predictive accuracy, but can sometimes even lead to better decisions. Subsequently, we discuss common misconceptions about heuristics and explain when and why ignoring parts of the available information can lead to the making of more robust predictions. Heuristics are neither good nor bad per se, but, if applied in situations to which they have been adapted, can be helpful companions for doctors and doctors-in-training. This, however, requires that heuristics in medicine be openly discussed, criticised, refined and then taught to doctors-in-training rather than being simply dismissed as harmful or irrelevant. A more uniform use of explicit and accepted heuristics has the potential to reduce variations in diagnoses and to improve medical care for patients.

A model for nematode locomotion in soil

USGS Publications Warehouse

Hunt, H. William; Wall, Diana H.; DeCrappeo, Nicole; Brenner, John S.

2001-01-01

Locomotion of nematodes in soil is important for both practical and theoretical reasons. We constructed a model for rate of locomotion. The first model component is a simple simulation of nematode movement among finite cells by both random and directed behaviours. Optimisation procedures were used to fit the simulation output to data from published experiments on movement along columns of soil or washed sand, and thus to estimate the values of the model's movement coefficients. The coefficients then provided an objective means to compare rates of locomotion among studies done under different experimental conditions. The second component of the model is an equation to predict the movement coefficients as a function of controlling factors that have been addressed experimentally: soil texture, bulk density, water potential, temperature, trophic group of nematode, presence of an attractant or physical gradient and the duration of the experiment. Parameters of the equation were estimated by optimisation to achieve a good fit to the estimated movement coefficients. Bulk density, which has been reported in a minority of published studies, is predicted to have an important effect on rate of locomotion, at least in fine-textured soils. Soil sieving, which appears to be a universal practice in laboratory studies of nematode movement, is predicted to negatively affect locomotion. Slower movement in finer textured soils would be expected to increase isolation among local populations, and thus to promote species richness. Future additions to the model that might improve its utility include representing heterogeneity within populations in rate of movement, development of gradients of chemical attractants, trade-offs between random and directed components of movement, species differences in optimal temperature and water potential, and interactions among factors controlling locomotion.

Visual grading characteristics and ordinal regression analysis during optimisation of CT head examinations.

PubMed

Zarb, Francis; McEntee, Mark F; Rainford, Louise

2015-06-01

To evaluate visual grading characteristics (VGC) and ordinal regression analysis during head CT optimisation as a potential alternative to visual grading assessment (VGA), traditionally employed to score anatomical visualisation. Patient images (n = 66) were obtained using current and optimised imaging protocols from two CT suites: a 16-slice scanner at the national Maltese centre for trauma and a 64-slice scanner in a private centre. Local resident radiologists (n = 6) performed VGA followed by VGC and ordinal regression analysis. VGC alone indicated that optimised protocols had similar image quality as current protocols. Ordinal logistic regression analysis provided an in-depth evaluation, criterion by criterion allowing the selective implementation of the protocols. The local radiology review panel supported the implementation of optimised protocols for brain CT examinations (including trauma) in one centre, achieving radiation dose reductions ranging from 24 % to 36 %. In the second centre a 29 % reduction in radiation dose was achieved for follow-up cases. The combined use of VGC and ordinal logistic regression analysis led to clinical decisions being taken on the implementation of the optimised protocols. This improved method of image quality analysis provided the evidence to support imaging protocol optimisation, resulting in significant radiation dose savings. • There is need for scientifically based image quality evaluation during CT optimisation. • VGC and ordinal regression analysis in combination led to better informed clinical decisions. • VGC and ordinal regression analysis led to dose reductions without compromising diagnostic efficacy.

Feasibility of on-line temperature-based hyperthermia treatment planning to improve tumour temperatures during locoregional hyperthermia.

PubMed

Kok, H P; Korshuize-van Straten, L; Bakker, A; de Kroon-Oldenhof, R; Westerveld, G H; Versteijne, E; Stalpers, L J A; Crezee, J

2017-11-16

The effectiveness of hyperthermia is strongly dependent on the achieved tumour temperatures. Phased-array systems allow flexible power steering to realise good tumour heating while avoiding excessive heating in normal tissue, but the limited quantitative accuracy of pre-treatment planning complicates realising optimal tumour heating. On-line hyperthermia treatment planning could help to improve the heating quality. This paper demonstrates the feasibility of using on-line temperature-based treatment planning to improve the heating quality during hyperthermia in three patients. Hyperthermia treatment planning was performed using the Plan2Heat software package combined with a dedicated graphical user interface for on-line application. Electric fields were pre-calculated to allow instant update and visualisation of the predicted temperature distribution for user-selected phase-amplitude settings during treatment. On-line treatment planning using manual variation of system settings for the AMC-8 hyperthermia system was applied in one patient with a deep-seated pelvic melanoma metastasis and two cervical cancer patients. For a clinically relevant improvement the increase in average target temperature should be at least 0.2 °C. With the assistance of on-line treatment planning a substantial improvement in tumour temperatures was realised for all three patients. In the melanoma patient, the average measured target temperature increased from 38.30 °C to 39.15 °C (i.e. +0.85 °C). In the cervical cancer patients, the average measured target temperature increased from 41.30 °C to 42.05 °C (i.e. +0.75 °C) and from 41.70 °C to 42.80 °C (i.e. +1.1 °C), respectively. On-line temperature-based treatment planning is clinically feasible to improve tumour temperatures. A next, worthwhile step is automatic optimisation for a larger number of patients.

Clinical benefit of 1-year certolizumab pegol (CZP) add-on therapy to methotrexate treatment in patients with early rheumatoid arthritis was observed following CZP discontinuation: 2-year results of the C-OPERA study, a phase III randomised trial.

PubMed

Atsumi, Tatsuya; Tanaka, Yoshiya; Yamamoto, Kazuhiko; Takeuchi, Tsutomu; Yamanaka, Hisashi; Ishiguro, Naoki; Eguchi, Katsumi; Watanabe, Akira; Origasa, Hideki; Yasuda, Shinsuke; Yamanishi, Yuji; Kita, Yasuhiko; Matsubara, Tsukasa; Iwamoto, Masahiro; Shoji, Toshiharu; Togo, Osamu; Okada, Toshiyuki; van der Heijde, Désirée; Miyasaka, Nobuyuki; Koike, Takao

2017-08-01

To investigate the clinical impact of 1-year certolizumab pegol (CZP) therapy added to the first year of 2-year methotrexate (MTX) therapy, compared with 2-year therapy with MTX alone. MTX-naïve patients with early rheumatoid arthritis (RA) with poor prognostic factors were eligible to enter Certolizumab-Optimal Prevention of joint damage for Early RA (C-OPERA), a multicentre, randomised, controlled study, which consisted of a 52-week double-blind (DB) period and subsequent 52-week post treatment (PT) period. Patients were randomised to optimised MTX+CZP (n=159) or optimised MTX+placebo (PBO; n=157). Following the DB period, patients entered the PT period, receiving MTX alone (CZP+MTX→MTX; n=108, PBO+MTX→MTX; n=71). Patients who flared could receive rescue treatment with open-label CZP. 34 CZP+MTX→MTX patients and 14 PBO+MTX→MTX patients discontinued during the PT period. From week 52 through week 104, significant inhibition of total modified total Sharp score progression was observed for CZP+MTX versus PBO+MTX (week 104: 84.2% vs 67.5% (p<0.001)). Remission rates decreased after CZP discontinuation; however, higher rates were maintained through week 104 in CZP+MTX→MTX versus PBO+MTX→MTX (41.5% vs 29.3% (p=0.026), 34.6% vs 24.2% (p=0.049) and 41.5% vs 33.1% (p=0.132) at week 104 in SDAI, Boolean and DAS28(erythrocyte sedimentation rate) remission. CZP retreated patients due to flare (n=28) showed rapid clinical improvement. The incidence of overall adverse events was similar between groups. In MTX-naïve patients with early RA with poor prognostic factors, an initial 1 year of add-on CZP to 2-year optimised MTX therapy brings radiographic and clinical benefit through 2 years, even after stopping CZP. NCT01451203. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Clinical benefit of 1-year certolizumab pegol (CZP) add-on therapy to methotrexate treatment in patients with early rheumatoid arthritis was observed following CZP discontinuation: 2-year results of the C-OPERA study, a phase III randomised trial

PubMed Central

Atsumi, Tatsuya; Tanaka, Yoshiya; Yamamoto, Kazuhiko; Takeuchi, Tsutomu; Yamanaka, Hisashi; Ishiguro, Naoki; Eguchi, Katsumi; Watanabe, Akira; Origasa, Hideki; Yasuda, Shinsuke; Yamanishi, Yuji; Kita, Yasuhiko; Matsubara, Tsukasa; Iwamoto, Masahiro; Shoji, Toshiharu; Togo, Osamu; Okada, Toshiyuki; Miyasaka, Nobuyuki; Koike, Takao

2017-01-01

Objectives To investigate the clinical impact of 1-year certolizumab pegol (CZP) therapy added to the first year of 2-year methotrexate (MTX) therapy, compared with 2-year therapy with MTX alone. Methods MTX-naïve patients with early rheumatoid arthritis (RA) with poor prognostic factors were eligible to enter Certolizumab-Optimal Prevention of joint damage for Early RA (C-OPERA), a multicentre, randomised, controlled study, which consisted of a 52-week double-blind (DB) period and subsequent 52-week post treatment (PT) period. Patients were randomised to optimised MTX+CZP (n=159) or optimised MTX+placebo (PBO; n=157). Following the DB period, patients entered the PT period, receiving MTX alone (CZP+MTX→MTX; n=108, PBO+MTX→MTX; n=71). Patients who flared could receive rescue treatment with open-label CZP. Results 34 CZP+MTX→MTX patients and 14 PBO+MTX→MTX patients discontinued during the PT period. From week 52 through week 104, significant inhibition of total modified total Sharp score progression was observed for CZP+MTX versus PBO+MTX (week 104: 84.2% vs 67.5% (p<0.001)). Remission rates decreased after CZP discontinuation; however, higher rates were maintained through week 104 in CZP+MTX→MTX versus PBO+MTX→MTX (41.5% vs 29.3% (p=0.026), 34.6% vs 24.2% (p=0.049) and 41.5% vs 33.1% (p=0.132) at week 104 in SDAI, Boolean and DAS28(erythrocyte sedimentation rate) remission. CZP retreated patients due to flare (n=28) showed rapid clinical improvement. The incidence of overall adverse events was similar between groups. Conclusions In MTX-naïve patients with early RA with poor prognostic factors, an initial 1 year of add-on CZP to 2-year optimised MTX therapy brings radiographic and clinical benefit through 2 years, even after stopping CZP. Trial registration number NCT01451203. PMID:28153828

Potential of biogenic hydrogen production for hydrogen driven remediation strategies in marine environments.

PubMed

Hosseinkhani, Baharak; Hennebel, Tom; Boon, Nico

2014-09-25

Fermentative production of bio-hydrogen (bio-H2) from organic residues has emerged as a promising alternative for providing the required electron source for hydrogen driven remediation strategies. Unlike the widely used production of H2 by bacteria in fresh water systems, few reports are available regarding the generation of biogenic H2 and optimisation processes in marine systems. The present research aims to optimise the capability of an indigenous marine bacterium for the production of bio-H2 in marine environments and subsequently develop this process for hydrogen driven remediation strategies. Fermentative conversion of organics in marine media to H2 using a marine isolate, Pseudoalteromonas sp. BH11, was determined. A Taguchi design of experimental methodology was employed to evaluate the optimal nutritional composition in batch tests to improve bio-H2 yields. Further optimisation experiments showed that alginate-immobilised bacterial cells were able to produce bio-H2 at the same rate as suspended cells over a period of several weeks. Finally, bio-H2 was used as electron donor to successfully dehalogenate trichloroethylene (TCE) using biogenic palladium nanoparticles as a catalyst. Fermentative production of bio-H2 can be a promising technique for concomitant generation of an electron source for hydrogen driven remediation strategies and treatment of organic residue in marine ecosystems. Copyright © 2014 Elsevier B.V. All rights reserved.

Modification of gelatin-DNA interaction for optimised DNA extraction from gelatin and gelatin capsule.

PubMed

Mohamad, Nurhidayatul Asma; Mustafa, Shuhaimi; El Sheikha, Aly Farag; Khairil Mokhtar, Nur Fadhilah; Ismail, Amin; Ali, Md Eaqub

2016-05-01

Poor quality and quantity of DNA extracted from gelatin and gelatin capsules often causes failure in the determination of animal species using PCR. Gelatin, which is mainly derived from porcine and bovine, has been a matter of concern among customers in order to fulfill religious obligation and safety precaution against several transmissible infectious diseases associated with bovine species. Thus, optimised DNA extraction from gelatin is very important for successful real-time PCR detection of gelatin species. In this work, the DNA extraction method was optimised in terms of lysis incubation period and inclusion of pre-treatment pH modification of samples. The yield of DNA extracted from porcine gelatin was significantly increased when the pH of the samples was adjusted to pH 8.5 prior to DNA precipitation with isopropanol. The optimal pH for DNA precipitation from bovine gelatin solution was then determined at the original pH range of solution: pH 7.6 to 8. A DNA fragment of approximately 300 base pairs was available for PCR amplification. DNA extracted from gelatin and commercially available capsules has been successfully utilised for species detection using real-time PCR assay. However, significant adulterations of porcine and bovine in pure gelatin and capsules have been detected, which require further analytical techniques for validation. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

An improved prognostic model for stage T1a and T1b prostate cancer by assessments of cancer extent

PubMed Central

Rajab, Ramzi; Fisher, Gabrielle; Kattan, Michael W; Foster, Christopher S; Møller, Henrik; Oliver, Tim; Reuter, Victor; Scardino, Peter T; Cuzick, Jack; Berney, Daniel M

2013-01-01

Treatment decisions on prostate cancer diagnosed by trans-urethral resection (TURP) of the prostate are difficult. The current TNM staging system for pT1 prostate cancer has not been re-evaluated for 25 years. Our objective was to optimise the predictive power of tumor extent measurements in TURP of the prostate specimens. A total of 914 patients diagnosed by TURP of the prostate between 1990 and 1996, managed conservatively were identified. The clinical end point was death from prostate cancer. Diagnostic serum prostate-specific antigen (PSA) and contemporary Gleason grading was available. Cancer extent was measured by the percentage of chips infiltrated by cancer. Death rates were compared by univariate and multivariate proportional hazards models, including baseline PSA and Gleason score. The percentage of positive chips was highly predictive of prostate cancer death when assessed as a continuous variable or as a grouped variable on the basis of and including the quintiles, quartiles, tertiles and median groups. In the univariate model, the most informative variable was a four group-split (≤ 10%, >10–25%, > 25–75% and > 75%); (HR = 2.08, 95% CI = 1.8–2.4, P < 0.0001). The same was true in a multivariate model (ΔX2 (1 d.f.) = 15.0, P = 0.0001). The current cutoff used by TNM (< = 5%) was sub-optimal (ΔX2 (1 d.f.) = 4.8, P = 0.023). The current TNM staging results in substantial loss of information. Staging by a four-group subdivision would substantially improve prognostication in patients with early stage disease and also may help to refine management decisions in patients who would do well with conservative treatments. PMID:20834240

Multi-objective optimization of radiotherapy: distributed Q-learning and agent-based simulation

NASA Astrophysics Data System (ADS)

Jalalimanesh, Ammar; Haghighi, Hamidreza Shahabi; Ahmadi, Abbas; Hejazian, Hossein; Soltani, Madjid

2017-09-01

Radiotherapy (RT) is among the regular techniques for the treatment of cancerous tumours. Many of cancer patients are treated by this manner. Treatment planning is the most important phase in RT and it plays a key role in therapy quality achievement. As the goal of RT is to irradiate the tumour with adequately high levels of radiation while sparing neighbouring healthy tissues as much as possible, it is a multi-objective problem naturally. In this study, we propose an agent-based model of vascular tumour growth and also effects of RT. Next, we use multi-objective distributed Q-learning algorithm to find Pareto-optimal solutions for calculating RT dynamic dose. We consider multiple objectives and each group of optimizer agents attempt to optimise one of them, iteratively. At the end of each iteration, agents compromise the solutions to shape the Pareto-front of multi-objective problem. We propose a new approach by defining three schemes of treatment planning created based on different combinations of our objectives namely invasive, conservative and moderate. In invasive scheme, we enforce killing cancer cells and pay less attention about irradiation effects on normal cells. In conservative scheme, we take more care of normal cells and try to destroy cancer cells in a less stressed manner. The moderate scheme stands in between. For implementation, each of these schemes is handled by one agent in MDQ-learning algorithm and the Pareto optimal solutions are discovered by the collaboration of agents. By applying this methodology, we could reach Pareto treatment plans through building different scenarios of tumour growth and RT. The proposed multi-objective optimisation algorithm generates robust solutions and finds the best treatment plan for different conditions.

On the design and optimisation of new fractal antenna using PSO

NASA Astrophysics Data System (ADS)

Rani, Shweta; Singh, A. P.

2013-10-01

An optimisation technique for newly shaped fractal structure using particle swarm optimisation with curve fitting is presented in this article. The aim of particle swarm optimisation is to find the geometry of the antenna for the required user-defined frequency. To assess the effectiveness of the presented method, a set of representative numerical simulations have been done and the results are compared with the measurements from experimental prototypes built according to the design specifications coming from the optimisation procedure. The proposed fractal antenna resonates at the 5.8 GHz industrial, scientific and medical band which is suitable for wireless telemedicine applications. The antenna characteristics have been studied using extensive numerical simulations and are experimentally verified. The antenna exhibits well-defined radiation patterns over the band.

Determinants of virological outcome and adverse events in African children treated with paediatric nevirapine fixed-dose-combination tablets

PubMed Central

BIENCZAK, Andrzej; DENTI, Paolo; Adrian, COOK; WIESNER, Lubbe; MULENGA, Veronica; KITYO, Cissy; KEKITIINWA, Addy; GIBB, Diana M.; BURGER, David; WALKER, A. Sarah; MCILLERON, Helen

2017-01-01

Background Nevirapine is the only non-nucleoside reverse transcriptase inhibitor currently available as a paediatric fixed-dose combination tablet and is widely used in African children. Nonetheless, the number of investigations into pharmacokinetic determinants of virological suppression in African children is limited and the predictive power of the current therapeutic range was never evaluated in this population, thereby limiting treatment optimisation. Methods We analysed data from 322 African children (aged 0.3–13 years) treated with nevirapine, lamivudine, and either abacavir, stavudine, or zidovudine, and followed up to 144 weeks. Nevirapine trough concentration (Cmin) and other factors were tested for associations with viral load (VL)>100 copies/mL and transaminase increases >grade 1 using proportional hazard and logistic models in 219 initially antiretroviral treatment(ART)-naïve children. Results Pre-ART VL, adherence, and nevirapine Cmin were associated with VL non-suppression (hazard-ratio [HR]=2.08 [95% CI: 1.50–2.90, p<0.001] for 10-fold higher pre-ART VL, HR=0.78 [95% CI: 0.68–0.90, p<0.001] for 10% improvement in adherence and HR=0.94 [95% CI: 0.90–0.99, p=0.014] for a 1mg/L increase in nevirapine Cmin). There were additional effects of pre-ART CD4% and clinical site. The risk of virological non-suppression decreased with increasing nevirapine Cmin and there was no clear Cmin threshold predictive of virological non-suppression. Transient transaminase elevations >grade 1 were associated with high Cmin (>12.4 mg/L), HR=5.18 (95%CI 1.95–13.80, p<0.001). Conclusions Treatment initiation at lower pre-ART VL and higher pre-ART CD4%, increased adherence, and maintaining average Cmin higher than current target could improve virological suppression of African children treated with nevirapine without increasing toxicity. PMID:28060017

A time-dependent search for high-energy neutrinos from bright GRBs with ANTARES

NASA Astrophysics Data System (ADS)

Celli, Silvia

2017-03-01

Astrophysical point-like neutrino sources, like Gamma-Ray Bursts (GRBs), are one of the main targets for neutrino telescopes, since they are among the best candidates for Ultra-High-Energy Cosmic Ray (UHECR) acceleration. From the interaction between the accelerated protons and the intense radiation fields of the source jet, charged mesons are produced, which then decay into neutrinos. The methods and the results of a search for high-energy neutrinos in spatial and temporal correlation with the detected gamma-ray emission are presented for four bright GRBs observed between 2008 and 2013: a time-dependent analysis, optimised for each flare of the selected bursts, is performed to predict detailed neutrino spectra. The internal shock scenario of the fireball model is investigated, relying on the neutrino spectra computed through the numerical code NeuCosmA. The analysis is optimized on a per burst basis, through the maximization of the signal discovery probability. Since no events in ANTARES data passed the optimised cuts, 90% C.L. upper limits are derived on the expected neutrino fluences.

Optimisation of Copper Oxide Impregnation on Carbonised Oil Palm Empty Fruit Bunch for Nitric Oxide Removal using Response Surface Methodology

NASA Astrophysics Data System (ADS)

Ahmad, Norhidayah; Yong, Sing Hung; Ibrahim, Naimah; Ali, Umi Fazara Md; Ridwan, Fahmi Muhammad; Ahmad, Razi

2018-03-01

Oil palm empty fruit bunch (EFB) was successfully modified with phosphoric acid hydration followed by impregnation with copper oxide (CuO) to synthesize CuO modified catalytic carbon (CuO/EFBC) for low-temperature removal of nitric oxide (NO) from gas streams. CuO impregnation was optimised through response surface methodology (RSM) using Box-Behnken Design (BBD) in terms of metal loading (5-20%), sintering temperature (200-800˚C) and sintering time (2-6 hours). The model response for the variables was NO adsorption capacity, which was obtained from an up-flow column adsorption experiment with 100 mL/min flow of 500 ppm NO/He at different operating conditions. The optimum operating variables suggested by the model were 20% metal loading, 200˚C sintering temperature and 6 hours sintering time. A good agreement (R2 = 0.9625) was achieved between the experimental data and model prediction. ANOVA analysis indicated that the model terms (metal loading and sintering temperature) are significant (Prob.>F less than 0.05).

Blind column selection protocol for two-dimensional high performance liquid chromatography.

PubMed

Burns, Niki K; Andrighetto, Luke M; Conlan, Xavier A; Purcell, Stuart D; Barnett, Neil W; Denning, Jacquie; Francis, Paul S; Stevenson, Paul G

2016-07-01

The selection of two orthogonal columns for two-dimensional high performance liquid chromatography (LC×LC) separation of natural product extracts can be a labour intensive and time consuming process and in many cases is an entirely trial-and-error approach. This paper introduces a blind optimisation method for column selection of a black box of constituent components. A data processing pipeline, created in the open source application OpenMS®, was developed to map the components within the mixture of equal mass across a library of HPLC columns; LC×LC separation space utilisation was compared by measuring the fractional surface coverage, fcoverage. It was found that for a test mixture from an opium poppy (Papaver somniferum) extract, the combination of diphenyl and C18 stationary phases provided a predicted fcoverage of 0.48 and was matched with an actual usage of 0.43. OpenMS®, in conjunction with algorithms designed in house, have allowed for a significantly quicker selection of two orthogonal columns, which have been optimised for a LC×LC separation of crude extractions of plant material. Copyright © 2016 Elsevier B.V. All rights reserved.

Relative electronic and free energies of octane's unique conformations

NASA Astrophysics Data System (ADS)

Kirschner, Karl N.; Heiden, Wolfgang; Reith, Dirk

2017-06-01

This study reports the geometries and electronic energies of n-octane's unique conformations using perturbation methods that best mimic CCSD(T) results. In total, the fully optimised minima of n-butane (2 conformations), n-pentane (4 conformations), n-hexane (12 conformations) and n-octane (96 conformations) were investigated at several different theory levels and basis sets. We find that DF-MP2.5/aug-cc-pVTZ is in very good agreement with the more expensive CCSD(T) results. At this level, we can clearly confirm the 96 stable minima which were previously found using a reparameterised density functional theory (DFT). Excellent agreement was found between their DFT results and our DF-MP2.5 perturbation results. Subsequent Gibbs free energy calculations, using scaled MP2/aug-cc-pVTZ zero-point vibrational energy and frequencies, indicate a significant temperature dependency of the relative energies, with a change in the predicted global minimum. The results of this work will be important for future computational investigations of fuel-related octane reactions and for optimisation of molecular force fields (e.g. lipids).

Effectiveness of an implementation optimisation intervention aimed at increasing parent engagement in HENRY, a childhood obesity prevention programme - the Optimising Family Engagement in HENRY (OFTEN) trial: study protocol for a randomised controlled trial.

PubMed

Bryant, Maria; Burton, Wendy; Cundill, Bonnie; Farrin, Amanda J; Nixon, Jane; Stevens, June; Roberts, Kim; Foy, Robbie; Rutter, Harry; Hartley, Suzanne; Tubeuf, Sandy; Collinson, Michelle; Brown, Julia

2017-01-24

Family-based interventions to prevent childhood obesity depend upon parents' taking action to improve diet and other lifestyle behaviours in their families. Programmes that attract and retain high numbers of parents provide an enhanced opportunity to improve public health and are also likely to be more cost-effective than those that do not. We have developed a theory-informed optimisation intervention to promote parent engagement within an existing childhood obesity prevention group programme, HENRY (Health Exercise Nutrition for the Really Young). Here, we describe a proposal to evaluate the effectiveness of this optimisation intervention in regard to the engagement of parents and cost-effectiveness. The Optimising Family Engagement in HENRY (OFTEN) trial is a cluster randomised controlled trial being conducted across 24 local authorities (approximately 144 children's centres) which currently deliver HENRY programmes. The primary outcome will be parental enrolment and attendance at the HENRY programme, assessed using routinely collected process data. Cost-effectiveness will be presented in terms of primary outcomes using acceptability curves and through eliciting the willingness to pay for the optimisation from HENRY commissioners. Secondary outcomes include the longitudinal impact of the optimisation, parent-reported infant intake of fruits and vegetables (as a proxy to compliance) and other parent-reported family habits and lifestyle. This innovative trial will provide evidence on the implementation of a theory-informed optimisation intervention to promote parent engagement in HENRY, a community-based childhood obesity prevention programme. The findings will be generalisable to other interventions delivered to parents in other community-based environments. This research meets the expressed needs of commissioners, children's centres and parents to optimise the potential impact that HENRY has on obesity prevention. A subsequent cluster randomised controlled pilot trial is planned to determine the practicality of undertaking a definitive trial to robustly evaluate the effectiveness and cost-effectiveness of the optimised intervention on childhood obesity prevention. ClinicalTrials.gov identifier: NCT02675699 . Registered on 4 February 2016.

Molecular simulation of the thermophysical properties and phase behaviour of impure CO2 relevant to CCS.

PubMed

Cresswell, Alexander J; Wheatley, Richard J; Wilkinson, Richard D; Graham, Richard S

2016-10-20

Impurities from the CCS chain can greatly influence the physical properties of CO 2 . This has important design, safety and cost implications for the compression, transport and storage of CO 2 . There is an urgent need to understand and predict the properties of impure CO 2 to assist with CCS implementation. However, CCS presents demanding modelling requirements. A suitable model must both accurately and robustly predict CO 2 phase behaviour over a wide range of temperatures and pressures, and maintain that predictive power for CO 2 mixtures with numerous, mutually interacting chemical species. A promising technique to address this task is molecular simulation. It offers a molecular approach, with foundations in firmly established physical principles, along with the potential to predict the wide range of physical properties required for CCS. The quality of predictions from molecular simulation depends on accurate force-fields to describe the interactions between CO 2 and other molecules. Unfortunately, there is currently no universally applicable method to obtain force-fields suitable for molecular simulation. In this paper we present two methods of obtaining force-fields: the first being semi-empirical and the second using ab initio quantum-chemical calculations. In the first approach we optimise the impurity force-field against measurements of the phase and pressure-volume behaviour of CO 2 binary mixtures with N 2 , O 2 , Ar and H 2 . A gradient-free optimiser allows us to use the simulation itself as the underlying model. This leads to accurate and robust predictions under conditions relevant to CCS. In the second approach we use quantum-chemical calculations to produce ab initio evaluations of the interactions between CO 2 and relevant impurities, taking N 2 as an exemplar. We use a modest number of these calculations to train a machine-learning algorithm, known as a Gaussian process, to describe these data. The resulting model is then able to accurately predict a much broader set of ab initio force-field calculations at comparatively low numerical cost. Although our method is not yet ready to be implemented in a molecular simulation, we outline the necessary steps here. Such simulations have the potential to deliver first-principles simulation of the thermodynamic properties of impure CO 2 , without fitting to experimental data.

Radiation dose optimisation for conventional imaging in infants and newborns using automatic dose management software: an application of the new 2013/59 EURATOM directive.

PubMed

Alejo, L; Corredoira, E; Sánchez-Muñoz, F; Huerga, C; Aza, Z; Plaza-Núñez, R; Serrada, A; Bret-Zurita, M; Parrón, M; Prieto-Areyano, C; Garzón-Moll, G; Madero, R; Guibelalde, E

2018-04-09

Objective: The new 2013/59 EURATOM Directive (ED) demands dosimetric optimisation procedures without undue delay. The aim of this study was to optimise paediatric conventional radiology examinations applying the ED without compromising the clinical diagnosis. Automatic dose management software (ADMS) was used to analyse 2678 studies of children from birth to 5 years of age, obtaining local diagnostic reference levels (DRLs) in terms of entrance surface air kerma. Given local DRL for infants and chest examinations exceeded the European Commission (EC) DRL, an optimisation was performed decreasing the kVp and applying the automatic control exposure. To assess the image quality, an analysis of high-contrast resolution (HCSR), signal-to-noise ratio (SNR) and figure of merit (FOM) was performed, as well as a blind test based on the generalised estimating equations method. For newborns and chest examinations, the local DRL exceeded the EC DRL by 113%. After the optimisation, a reduction of 54% was obtained. No significant differences were found in the image quality blind test. A decrease in SNR (-37%) and HCSR (-68%), and an increase in FOM (42%), was observed. ADMS allows the fast calculation of local DRLs and the performance of optimisation procedures in babies without delay. However, physical and clinical analyses of image quality remain to be needed to ensure the diagnostic integrity after the optimisation process. Advances in knowledge: ADMS are useful to detect radiation protection problems and to perform optimisation procedures in paediatric conventional imaging without undue delay, as ED requires.

Aircraft noise prediction

NASA Astrophysics Data System (ADS)

Filippone, Antonio

2014-07-01

This contribution addresses the state-of-the-art in the field of aircraft noise prediction, simulation and minimisation. The point of view taken in this context is that of comprehensive models that couple the various aircraft systems with the acoustic sources, the propagation and the flight trajectories. After an exhaustive review of the present predictive technologies in the relevant fields (airframe, propulsion, propagation, aircraft operations, trajectory optimisation), the paper addresses items for further research and development. Examples are shown for several airplanes, including the Airbus A319-100 (CFM engines), the Bombardier Dash8-Q400 (PW150 engines, Dowty R408 propellers) and the Boeing B737-800 (CFM engines). Predictions are done with the flight mechanics code FLIGHT. The transfer function between flight mechanics and the noise prediction is discussed in some details, along with the numerical procedures for validation and verification. Some code-to-code comparisons are shown. It is contended that the field of aircraft noise prediction has not yet reached a sufficient level of maturity. In particular, some parametric effects cannot be investigated, issues of accuracy are not currently addressed, and validation standards are still lacking.

Towards single embryo transfer? Modelling clinical outcomes of potential treatment choices using multiple data sources: predictive models and patient perspectives.

PubMed

Roberts, Sa; McGowan, L; Hirst, Wm; Brison, Dr; Vail, A; Lieberman, Ba

2010-07-01

In vitro fertilisation (IVF) treatments involve an egg retrieval process, fertilisation and culture of the resultant embryos in the laboratory, and the transfer of embryos back to the mother over one or more transfer cycles. The first transfer is usually of fresh embryos and the remainder may be cryopreserved for future frozen cycles. Most commonly in UK practice two embryos are transferred (double embryo transfer, DET). IVF techniques have led to an increase in the number of multiple births, carrying an increased risk of maternal and infant morbidity. The UK Human Fertilisation and Embryology Authority (HFEA) has adopted a multiple birth minimisation strategy. One way of achieving this would be by increased use of single embryo transfer (SET). To collate cohort data from treatment centres and the HFEA; to develop predictive models for live birth and twinning probabilities from fresh and frozen embryo transfers and predict outcomes from treatment scenarios; to understand patients' perspectives and use the modelling results to investigate the acceptability of twin reduction policies. A multidisciplinary approach was adopted, combining statistical modelling with qualitative exploration of patients' perspectives: interviews were conducted with 27 couples at various stages of IVF treatment at both UK NHS and private clinics; datasets were collated of over 90,000 patients from the HFEA registry and nearly 9000 patients from five clinics, both over the period 2000-5; models were developed to determine live birth and twin outcomes and predict the outcomes of policies for selecting patients for SET or DET in the fresh cycle following egg retrieval and fertilisation, and the predictions were used in simulations of treatments; two focus groups were convened, one NHS and one web based on a patient organisation's website, to present the results of the statistical analyses and explore potential treatment policies. The statistical analysis revealed no characteristics that specifically predicted multiple birth outcomes beyond those that predicted treatment success. In the fresh transfer following egg retrieval, SET would lead to a reduction of approximately one-third in the live birth probability compared with DET, a result consistent with the limited data from clinical trials. From the population or clinic perspective, selection of patients based on prognostic indicators might mitigate about half of the loss in live births associated with SET in the initial fresh transfer while achieving a twin rate of 10% or less. Data-based simulations suggested that, if all good-quality embryos are replaced over multiple frozen embryo transfers, repeated SET has the potential to produce more live birth events than repeated DET. However, this would depend on optimising cryopreservation procedures. Universal SET could both reduce the number of twin births and lead to more couples having a child, but at an average cost of one more embryo transfer procedure per egg retrieval. The interview and focus group data suggest that, despite the potential to maintain overall success rates, patients would prefer DET: the potential for twins was seen as positive, while additional transfer procedures can be emotionally, physically and financially draining. For any one transfer, SET has about a one-third loss of success rate relative to DET. This can be only partially mitigated by patient and treatment cycle selection, which may be criticised as unfair as all patients receiving SET will have a lower chance of success than they would with DET. However, considering complete cycles (fresh plus frozen transfers), it is possible for repeat SET to produce more live births than repeat DET. Such a strategy would require support from funders and acceptance by patients of both cryopreservation and the burden of additional transfer cycles. Future work should include development of improved clinical and regulatory database systems, surveys to quantify the extent of patients' beliefs and experiences and develop approaches to meet their information needs, and, ideally, randomised controlled trials comparing policies of repeated SET with repeated DET.

Optimisation of immunofluorescence methods to determine MCT1 and MCT4 expression in circulating tumour cells.

PubMed

Kershaw, Stephen; Cummings, Jeffrey; Morris, Karen; Tugwood, Jonathan; Dive, Caroline

2015-05-10

The monocarboxylate transporter-1 (MCT1) represents a novel target in rational anticancer drug design while AZD3965 was developed as an inhibitor of this transporter and is undergoing Phase I clinical trials ( http://www.clinicaltrials.gov/show/NCT01791595 ). We describe the optimisation of an immunofluorescence (IF) method for determination of MCT1 and MCT4 in circulating tumour cells (CTC) as potential prognostic and predictive biomarkers of AZD3965 in cancer patients. Antibody selectivity was investigated by western blotting (WB) in K562 and MDAMB231 cell lines acting as positive controls for MCT1 and MCT4 respectively and by flow cytometry also employing the control cell lines. Ability to detect MCT1 and MCT4 in CTC as a 4(th) channel marker utilising the Veridex™ CellSearch system was conducted in both human volunteer blood spiked with control cells and in samples collected from small cell lung cancer (SCLC) patients. Experimental conditions were established which yielded a 10-fold dynamic range (DR) for detection of MCT1 over MCT4 (antibody concentration 6.25 μg/mL; integration time 0.4 seconds) and a 5-fold DR of MCT4 over MCT 1 (8 μg/100 μL and 0.8 seconds). The IF method was sufficiently sensitive to detect both MCT1 and MCT4 in CTCs harvested from cancer patients. The first IF method has been developed and optimised for detection of MCT 1 and MCT4 in cancer patient CTC.

A novel artificial immune clonal selection classification and rule mining with swarm learning model

NASA Astrophysics Data System (ADS)

Al-Sheshtawi, Khaled A.; Abdul-Kader, Hatem M.; Elsisi, Ashraf B.

2013-06-01

Metaheuristic optimisation algorithms have become popular choice for solving complex problems. By integrating Artificial Immune clonal selection algorithm (CSA) and particle swarm optimisation (PSO) algorithm, a novel hybrid Clonal Selection Classification and Rule Mining with Swarm Learning Algorithm (CS2) is proposed. The main goal of the approach is to exploit and explore the parallel computation merit of Clonal Selection and the speed and self-organisation merits of Particle Swarm by sharing information between clonal selection population and particle swarm. Hence, we employed the advantages of PSO to improve the mutation mechanism of the artificial immune CSA and to mine classification rules within datasets. Consequently, our proposed algorithm required less training time and memory cells in comparison to other AIS algorithms. In this paper, classification rule mining has been modelled as a miltiobjective optimisation problem with predictive accuracy. The multiobjective approach is intended to allow the PSO algorithm to return an approximation to the accuracy and comprehensibility border, containing solutions that are spread across the border. We compared our proposed algorithm classification accuracy CS2 with five commonly used CSAs, namely: AIRS1, AIRS2, AIRS-Parallel, CLONALG, and CSCA using eight benchmark datasets. We also compared our proposed algorithm classification accuracy CS2 with other five methods, namely: Naïve Bayes, SVM, MLP, CART, and RFB. The results show that the proposed algorithm is comparable to the 10 studied algorithms. As a result, the hybridisation, built of CSA and PSO, can develop respective merit, compensate opponent defect, and make search-optimal effect and speed better.

Integration of Monte-Carlo ray tracing with a stochastic optimisation method: application to the design of solar receiver geometry.

PubMed

Asselineau, Charles-Alexis; Zapata, Jose; Pye, John

2015-06-01

A stochastic optimisation method adapted to illumination and radiative heat transfer problems involving Monte-Carlo ray-tracing is presented. A solar receiver shape optimisation case study illustrates the advantages of the method and its potential: efficient receivers are identified using a moderate computational cost.

Comparison of NOM character in selected Australian and Norwegian drinking waters.

PubMed

Fabris, Rolando; Chow, Christopher W K; Drikas, Mary; Eikebrokk, Bjørnar

2008-09-01

Observations from many countries around the world during the past 10-20 years indicate increasing natural organic matter (NOM) concentration levels in water sources, due to issues such as global warming, changes in soil acidification, increased drought severity and more intensive rain events. In addition to the trend towards increasing NOM concentration, the character of NOM can vary with source and time (season). The great seasonal variability and the trend towards elevated NOM concentration levels impose challenges to the water industry and the water treatment facilities in terms of operational optimisation and proper process control. The aim of this investigation was to compare selected raw and conventionally treated drinking water sources from different hemispheres with regard to NOM character which may lead to better understanding of the impact of source water on water treatment. Results from the analyses of selected Norwegian and Australian water samples showed that Norwegian NOM exhibited greater humic nature, indicating a stronger bias of allochthonous versus autochthonous organic origin. Similarly, Norwegian source waters had higher average molecular weights than Australian waters. Following coagulation treatment, the organic character of the recalcitrant NOM in both countries was similar. Differences in organic character of these source waters after treatment were found to be related to treatment practice rather than origin of the source water. The characterisation techniques employed also enabled identification of the coagulation processes which were not necessarily optimised for dissolved organic carbon (DOC) removal. The reactivity with chlorine as well as trihalomethane formation potential (THMFP) of the treated waters showed differences in behaviour between Norwegian and Australian sources that appeared to be related to residual higher molecular weight organic material. By evaluation of changes in specific molecular weight regions and disinfection parameters before and after treatment, correlations were found that relate treatment strategy to chlorine demand and DBP formation.

Optimising adherence to childhood pneumonia treatment: the design and development of patient instructions and a job aid for amoxicillin dispersible tablets.

PubMed

Ebels, Kelly; Faulx, Dunia; Gerth-Guyette, Emily; Murunga, Peninah; Mahapatro, Samarendra; Das, Manoja Kumar; Ginsburg, Amy Sarah

2016-01-01

Pneumonia is the leading cause of death from infection in children worldwide. Despite global treatment recommendations that call for children with pneumonia to receive amoxicillin dispersible tablets, only one-third of children with pneumonia receive any antibiotics and many do not complete the full course of treatment. Poor adherence to antibiotics may be driven in part by a lack of user-friendly treatment instructions. In order to optimise childhood pneumonia treatment adherence at the community level, we developed a user-friendly product presentation for caregivers and a job aid for healthcare providers (HCPs). This paper aims to document the development process and offers a model for future health communication tools. We employed an iterative design process that included document review, key stakeholder interviews, engagement with a graphic designer and pre-testing design concepts among target users in India and Kenya. The consolidated criteria for reporting qualitative research were used in the description of results. Though resources for pneumonia treatment are available in some countries, their content is incomplete and inconsistent with global recommendations. Document review and stakeholder interviews provided the information necessary to convey to caregivers and recommendations for how to present this information. Target users in India and Kenya confirmed the need to support better treatment adherence, recommended specific modifications to design concepts and suggested the development of a companion job aid. There was a consensus among caregivers and HCPs that these tools would be helpful and improve adherence behaviours. The development of user-friendly instructions for medications for use in low-resource settings is a critically important but time-intensive and resource-intensive process that should involve engagement with target audiences. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Identification and characterisation of midbrain nuclei using optimised functional magnetic resonance imaging

PubMed Central

Limbrick-Oldfield, Eve H.; Brooks, Jonathan C.W.; Wise, Richard J.S.; Padormo, Francesco; Hajnal, Jo V.; Beckmann, Christian F.; Ungless, Mark A.

2012-01-01

Localising activity in the human midbrain with conventional functional MRI (fMRI) is challenging because the midbrain nuclei are small and located in an area that is prone to physiological artefacts. Here we present a replicable and automated method to improve the detection and localisation of midbrain fMRI signals. We designed a visual fMRI task that was predicted would activate the superior colliculi (SC) bilaterally. A limited number of coronal slices were scanned, orientated along the long axis of the brainstem, whilst simultaneously recording cardiac and respiratory traces. A novel anatomical registration pathway was used to optimise the localisation of the small midbrain nuclei in stereotactic space. Two additional structural scans were used to improve registration between functional and structural T1-weighted images: an echo-planar image (EPI) that matched the functional data but had whole-brain coverage, and a whole-brain T2-weighted image. This pathway was compared to conventional registration pathways, and was shown to significantly improve midbrain registration. To reduce the physiological artefacts in the functional data, we estimated and removed structured noise using a modified version of a previously described physiological noise model (PNM). Whereas a conventional analysis revealed only unilateral SC activity, the PNM analysis revealed the predicted bilateral activity. We demonstrate that these methods improve the measurement of a biologically plausible fMRI signal. Moreover they could be used to investigate the function of other midbrain nuclei. PMID:21867762

Topology optimisation for natural convection problems

NASA Astrophysics Data System (ADS)

Alexandersen, Joe; Aage, Niels; Andreasen, Casper Schousboe; Sigmund, Ole

2014-12-01

This paper demonstrates the application of the density-based topology optimisation approach for the design of heat sinks and micropumps based on natural convection effects. The problems are modelled under the assumptions of steady-state laminar flow using the incompressible Navier-Stokes equations coupled to the convection-diffusion equation through the Boussinesq approximation. In order to facilitate topology optimisation, the Brinkman approach is taken to penalise velocities inside the solid domain and the effective thermal conductivity is interpolated in order to accommodate differences in thermal conductivity of the solid and fluid phases. The governing equations are discretised using stabilised finite elements and topology optimisation is performed for two different problems using discrete adjoint sensitivity analysis. The study shows that topology optimisation is a viable approach for designing heat sink geometries cooled by natural convection and micropumps powered by natural convection.

A supportive architecture for CFD-based design optimisation

NASA Astrophysics Data System (ADS)

Li, Ni; Su, Zeya; Bi, Zhuming; Tian, Chao; Ren, Zhiming; Gong, Guanghong

2014-03-01

Multi-disciplinary design optimisation (MDO) is one of critical methodologies to the implementation of enterprise systems (ES). MDO requiring the analysis of fluid dynamics raises a special challenge due to its extremely intensive computation. The rapid development of computational fluid dynamic (CFD) technique has caused a rise of its applications in various fields. Especially for the exterior designs of vehicles, CFD has become one of the three main design tools comparable to analytical approaches and wind tunnel experiments. CFD-based design optimisation is an effective way to achieve the desired performance under the given constraints. However, due to the complexity of CFD, integrating with CFD analysis in an intelligent optimisation algorithm is not straightforward. It is a challenge to solve a CFD-based design problem, which is usually with high dimensions, and multiple objectives and constraints. It is desirable to have an integrated architecture for CFD-based design optimisation. However, our review on existing works has found that very few researchers have studied on the assistive tools to facilitate CFD-based design optimisation. In the paper, a multi-layer architecture and a general procedure are proposed to integrate different CFD toolsets with intelligent optimisation algorithms, parallel computing technique and other techniques for efficient computation. In the proposed architecture, the integration is performed either at the code level or data level to fully utilise the capabilities of different assistive tools. Two intelligent algorithms are developed and embedded with parallel computing. These algorithms, together with the supportive architecture, lay a solid foundation for various applications of CFD-based design optimisation. To illustrate the effectiveness of the proposed architecture and algorithms, the case studies on aerodynamic shape design of a hypersonic cruising vehicle are provided, and the result has shown that the proposed architecture and developed algorithms have performed successfully and efficiently in dealing with the design optimisation with over 200 design variables.

Optimisation of SOA-REAMs for hybrid DWDM-TDMA PON applications.

PubMed

Naughton, Alan; Antony, Cleitus; Ossieur, Peter; Porto, Stefano; Talli, Giuseppe; Townsend, Paul D

2011-12-12

We demonstrate how loss-optimised, gain-saturated SOA-REAM based reflective modulators can reduce the burst to burst power variations due to differential access loss in the upstream path in carrier distributed passive optical networks by 18 dB compared to fixed linear gain modulators. We also show that the loss optimised device has a high tolerance to input power variations and can operate in deep saturation with minimal patterning penalties. Finally, we demonstrate that an optimised device can operate across the C-Band and also over a transmission distance of 80 km. © 2011 Optical Society of America

Fabrication of anti-adhesion surfaces on aluminium substrates of rubber plastic moulds using electrolysis plasma treatment

NASA Astrophysics Data System (ADS)

Meng, Jianbing; Dong, Xiaojuan; Wei, Xiuting; Yin, Zhanmin

2015-04-01

An anti-adhesion surface with a water contact angle of 167° was fabricated on aluminium samples of rubber plastic moulds by electrolysis plasma treatment using mixed electrolytes of C6H5O7(NH4)3 and Na2SO4, followed by fluorination. To optimise the fabrication conditions, several important processing parameters such as the discharge voltage, discharge time, concentrations of supporting electrolyte and stearic acid ethanol solution were examined systematically. Using scanning electron microscopy (SEM) to analyse surfaces morphology, micrometer scale pits, and protrusions were found on the surface, with numerous nanometer mastoids contained in the protrusions. These binary micro/nano-scale structures, which are similar to the micro-structures of soil-burrowing animals, play a critical role in achieving low adhesion properties. Otherwise, the anti-adhesion behaviours of the resulting samples were analysed by the atomic force microscope (AFM), Fourier-transform infrared spectrophotometer (FTIR), electrons probe micro-analyzer (EPMA), optical contact angle meter, digital Vickers microhardness (Hv) tester, and electronic universal testing. The results show that the electrolysis plasma treatment does not require complex processing parameters, using a simple device, and is an environment-friendly and effective method. Under the optimised conditions, the contact angle (CA) for the modified anti-adhesion surface is up to 167°, the sliding angle (SA) is less than 2°, roughness of the sample surface is only 0.409μm. Moreover, the adhesion force and Hv are 0. 9KN and 385, respectively.

Optimisation of Deacetylation Process for Chitosan Production from Red Snapper (Lutjanus sp.) Scale Wastes

NASA Astrophysics Data System (ADS)

Takarina, N. D.; Indah, A. B.; Nasrul, A. A.; Nurmarina, A.; Saefumillah, A.; Fanani, A. A.; Loka, K. D. P.

2017-02-01

Red snapper (Lutjanus sp.) is common tropical fish that known as important source of marine product in particular Indonesia. This research aimed to optimise the chitosan synthesis from the red snapper scale waste through deacetylation process. Method in this research was divided into three stages which were deproteination, demineralization, and deacetylation. Deproteination stage was done with solution containing 4.2% w/v NaOH and heated at 60° C for 5 hours and followed by the demineralization stage with solution containing 52% v/v 2 N HCl at room temperature for 6 hours. The comparison between fish scales and solutions was 1: 6. After that, process continued with the deacetylation. Several treatment during the deacetylation process were taken into consideration to determine the effective concentration for yielding optimum chitosan output. Chitosan produced were having moisture content of 2.88%, ash content of 1.10%, and nitrogen content of 0.0136%. Optimal Degree of Deacetylation (DDA) was up to 90.83% that obtained by heating treatment at a temperature of 110° C with solution containing 80% NaOH for 4 hours, and comparison between chitin : solution was 1 : 3. This result indicated that chitosan extracted from red snapper scale is very potential and can be applied to industry.

Biobutanol production from apple pomace: the importance of pretreatment methods on the fermentability of lignocellulosic agro-food wastes.

PubMed

Hijosa-Valsero, María; Paniagua-García, Ana I; Díez-Antolínez, Rebeca

2017-11-01

Apple pomace was studied as a possible raw material for biobutanol production. Five different soft physicochemical pretreatments (autohydrolysis, acids, alkalis, organic solvents and surfactants) were compared in a high-pressure reactor, whose working parameters (temperature, time and reagent concentration) were optimised to maximise the amount of simple sugars released and to minimise inhibitor generation. The pretreated biomass was subsequently subjected to a conventional enzymatic treatment to complete the hydrolysis. A thermal analysis (DSC) of the solid biomass indicated that lignin was mainly degraded during the enzymatic treatment. The hydrolysate obtained with the surfactant polyethylene glycol 6000 (PEG 6000) (1.96% w/w) contained less inhibitors than any other pretreatment, yet providing 42 g/L sugars at relatively mild conditions (100 °C, 5 min), and was readily fermented by Clostridium beijerinckii CECT 508 in 96 h (3.55 g/L acetone, 9.11 g/L butanol, 0.26 g/L ethanol; 0.276 g B /g S yield; 91% sugar consumption). Therefore, it is possible to optimise pretreatment conditions of lignocellulosic apple pomace to reduce inhibitor concentrations in the final hydrolysate and perform successful ABE fermentations without the need of a detoxification stage.

Application of an automation system and a supervisory control and data acquisition (SCADA) system for the optimal operation of a membrane adsorption hybrid system.

PubMed

Smith, P J; Vigneswaran, S; Ngo, H H; Nguyen, H T; Ben-Aim, R

2006-01-01

The application of automation and supervisory control and data acquisition (SCADA) systems to municipal water and wastewater treatment plants is rapidly increasing. However, the application of these systems is less frequent in the research and development phases of emerging treatment technologies used in these industries. This study involved the implementation of automation and a SCADA system to the submerged membrane adsorption hybrid system for use in a semi-pilot scale research project. An incremental approach was used in the development of the automation and SCADA systems, leading to the development of two new control systems. The first system developed involved closed loop control of the backwash initiation, based upon a pressure increase, leading to productivity improvements as the backwash is only activated when required, not at a fixed time. This system resulted in a 40% reduction in the number of backwashes required and also enabled optimised operations under unsteady concentrations of wastewater. The second system developed involved closed loop control of the backwash duration, whereby the backwash was terminated when the pressure reached a steady state. This system resulted in a reduction of the duration of the backwash of up to 25% and enabled optimised operations as the foulant build-up within the reactor increased.

Response surface methodology investigation into the interactions between arsenic and humic acid in water during the coagulation process.

PubMed

Watson, Malcolm Alexander; Tubić, Aleksandra; Agbaba, Jasmina; Nikić, Jasmina; Maletić, Snežana; Molnar Jazić, Jelena; Dalmacija, Božo

2016-07-15

Interactions between arsenic and natural organic matter (NOM) are key limiting factors during the optimisation of drinking water treatment when significant amounts of both must be removed. This work uses Response Surface Methodology (RSM) to investigate how they interact during their simultaneous removal by iron chloride coagulation, using humic acid (HA) as a model NOM substance. Using a three factor Box-Behnken experimental design, As and HA removals were modelled, as well as a combined removal response. ANOVA results showed the significance of the coagulant dose for all three responses. At high initial arsenic concentrations (200μg/l), As removal was significantly hindered by the presence of HA. In contrast, the HA removal response was found to be largely independent of the initial As concentration, with the optimum coagulant dose increasing at increasing HA concentrations. The combined response was similar to the HA removal response, and the interactions evident are most interesting in terms of optimising treatment processes during the preparation of drinking water, highlighting the importance of utilizing RSM for such investigations. The combined response model was successfully validated with two different groundwaters used for drinking water supply in the Republic of Serbia, showing excellent agreement under similar experimental conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

Optimising the combination dosing strategy of abemaciclib and vemurafenib in BRAF-mutated melanoma xenograft tumours.

PubMed

Tate, Sonya C; Burke, Teresa F; Hartman, Daisy; Kulanthaivel, Palaniappan; Beckmann, Richard P; Cronier, Damien M

2016-03-15

Resistance to BRAF inhibition is a major cause of treatment failure for BRAF-mutated metastatic melanoma patients. Abemaciclib, a cyclin-dependent kinase 4 and 6 inhibitor, overcomes this resistance in xenograft tumours and offers a promising drug combination. The present work aims to characterise the quantitative pharmacology of the abemaciclib/vemurafenib combination using a semimechanistic pharmacokinetic/pharmacodynamic modelling approach and to identify an optimum dosing regimen for potential clinical evaluation. A PK/biomarker model was developed to connect abemaciclib/vemurafenib concentrations to changes in MAPK and cell cycle pathway biomarkers in A375 BRAF-mutated melanoma xenografts. Resultant tumour growth inhibition was described by relating (i) MAPK pathway inhibition to apoptosis, (ii) mitotic cell density to tumour growth and, under resistant conditions, (iii) retinoblastoma protein inhibition to cell survival. The model successfully described vemurafenib/abemaciclib-mediated changes in MAPK pathway and cell cycle biomarkers. Initial tumour shrinkage by vemurafenib, acquisition of resistance and subsequent abemaciclib-mediated efficacy were successfully captured and externally validated. Model simulations illustrate the benefit of intermittent vemurafenib therapy over continuous treatment, and indicate that continuous abemaciclib in combination with intermittent vemurafenib offers the potential for considerable tumour regression. The quantitative pharmacology of the abemaciclib/vemurafenib combination was successfully characterised and an optimised, clinically-relevant dosing strategy was identified.

Multi-Objectivising Combinatorial Optimisation Problems by Means of Elementary Landscape Decompositions.

PubMed

Ceberio, Josu; Calvo, Borja; Mendiburu, Alexander; Lozano, Jose A

2018-02-15

In the last decade, many works in combinatorial optimisation have shown that, due to the advances in multi-objective optimisation, the algorithms from this field could be used for solving single-objective problems as well. In this sense, a number of papers have proposed multi-objectivising single-objective problems in order to use multi-objective algorithms in their optimisation. In this article, we follow up this idea by presenting a methodology for multi-objectivising combinatorial optimisation problems based on elementary landscape decompositions of their objective function. Under this framework, each of the elementary landscapes obtained from the decomposition is considered as an independent objective function to optimise. In order to illustrate this general methodology, we consider four problems from different domains: the quadratic assignment problem and the linear ordering problem (permutation domain), the 0-1 unconstrained quadratic optimisation problem (binary domain), and the frequency assignment problem (integer domain). We implemented two widely known multi-objective algorithms, NSGA-II and SPEA2, and compared their performance with that of a single-objective GA. The experiments conducted on a large benchmark of instances of the four problems show that the multi-objective algorithms clearly outperform the single-objective approaches. Furthermore, a discussion on the results suggests that the multi-objective space generated by this decomposition enhances the exploration ability, thus permitting NSGA-II and SPEA2 to obtain better results in the majority of the tested instances.

Wind energy resource modelling in Portugal and its future large-scale alteration due to anthropogenic induced climate changes =

NASA Astrophysics Data System (ADS)

Carvalho, David Joao da Silva

The high dependence of Portugal from foreign energy sources (mainly fossil fuels), together with the international commitments assumed by Portugal and the national strategy in terms of energy policy, as well as resources sustainability and climate change issues, inevitably force Portugal to invest in its energetic self-sufficiency. The 20/20/20 Strategy defined by the European Union defines that in 2020 60% of the total electricity consumption must come from renewable energy sources. Wind energy is currently a major source of electricity generation in Portugal, producing about 23% of the national total electricity consumption in 2013. The National Energy Strategy 2020 (ENE2020), which aims to ensure the national compliance of the European Strategy 20/20/20, states that about half of this 60% target will be provided by wind energy. This work aims to implement and optimise a numerical weather prediction model in the simulation and modelling of the wind energy resource in Portugal, both in offshore and onshore areas. The numerical model optimisation consisted in the determination of which initial and boundary conditions and planetary boundary layer physical parameterizations options provide wind power flux (or energy density), wind speed and direction simulations closest to in situ measured wind data. Specifically for offshore areas, it is also intended to evaluate if the numerical model, once optimised, is able to produce power flux, wind speed and direction simulations more consistent with in situ measured data than wind measurements collected by satellites. This work also aims to study and analyse possible impacts that anthropogenic climate changes may have on the future wind energetic resource in Europe. The results show that the ECMWF reanalysis ERA-Interim are those that, among all the forcing databases currently available to drive numerical weather prediction models, allow wind power flux, wind speed and direction simulations more consistent with in situ wind measurements. It was also found that the Pleim-Xiu and ACM2 planetary boundary layer parameterizations are the ones that showed the best performance in terms of wind power flux, wind speed and direction simulations. This model optimisation allowed a significant reduction of the wind power flux, wind speed and direction simulations errors and, specifically for offshore areas, wind power flux, wind speed and direction simulations more consistent with in situ wind measurements than data obtained from satellites, which is a very valuable and interesting achievement. This work also revealed that future anthropogenic climate changes can negatively impact future European wind energy resource, due to tendencies towards a reduction in future wind speeds especially by the end of the current century and under stronger radiative forcing conditions.

Optimising ICT Effectiveness in Instruction and Learning: Multilevel Transformation Theory and a Pilot Project in Secondary Education

ERIC Educational Resources Information Center

Mooij, Ton

2004-01-01

Specific combinations of educational and ICT conditions including computer use may optimise learning processes, particularly for learners at risk. This position paper asks which curricular, instructional, and ICT characteristics can be expected to optimise learning processes and outcomes, and how to best achieve this optimization. A theoretical…

Design and Development of ChemInfoCloud: An Integrated Cloud Enabled Platform for Virtual Screening.

PubMed

Karthikeyan, Muthukumarasamy; Pandit, Deepak; Bhavasar, Arvind; Vyas, Renu

2015-01-01

The power of cloud computing and distributed computing has been harnessed to handle vast and heterogeneous data required to be processed in any virtual screening protocol. A cloud computing platorm ChemInfoCloud was built and integrated with several chemoinformatics and bioinformatics tools. The robust engine performs the core chemoinformatics tasks of lead generation, lead optimisation and property prediction in a fast and efficient manner. It has also been provided with some of the bioinformatics functionalities including sequence alignment, active site pose prediction and protein ligand docking. Text mining, NMR chemical shift (1H, 13C) prediction and reaction fingerprint generation modules for efficient lead discovery are also implemented in this platform. We have developed an integrated problem solving cloud environment for virtual screening studies that also provides workflow management, better usability and interaction with end users using container based virtualization, OpenVz.

Mining nutrigenetics patterns related to obesity: use of parallel multifactor dimensionality reduction.

PubMed

Karayianni, Katerina N; Grimaldi, Keith A; Nikita, Konstantina S; Valavanis, Ioannis K

2015-01-01

This paper aims to enlighten the complex etiology beneath obesity by analysing data from a large nutrigenetics study, in which nutritional and genetic factors associated with obesity were recorded for around two thousand individuals. In our previous work, these data have been analysed using artificial neural network methods, which identified optimised subsets of factors to predict one's obesity status. These methods did not reveal though how the selected factors interact with each other in the obtained predictive models. For that reason, parallel Multifactor Dimensionality Reduction (pMDR) was used here to further analyse the pre-selected subsets of nutrigenetic factors. Within pMDR, predictive models using up to eight factors were constructed, further reducing the input dimensionality, while rules describing the interactive effects of the selected factors were derived. In this way, it was possible to identify specific genetic variations and their interactive effects with particular nutritional factors, which are now under further study.

Prediction of multi performance characteristics of wire EDM process using grey ANFIS

NASA Astrophysics Data System (ADS)

Kumanan, Somasundaram; Nair, Anish

2017-09-01

Super alloys are used to fabricate components in ultra-supercritical power plants. These hard to machine materials are processed using non-traditional machining methods like Wire cut electrical discharge machining and needs attention. This paper details about multi performance optimization of wire EDM process using Grey ANFIS. Experiments are designed to establish the performance characteristics of wire EDM such as surface roughness, material removal rate, wire wear rate and geometric tolerances. The control parameters are pulse on time, pulse off time, current, voltage, flushing pressure, wire tension, table feed and wire speed. Grey relational analysis is employed to optimise the multi objectives. Analysis of variance of the grey grades is used to identify the critical parameters. A regression model is developed and used to generate datasets for the training of proposed adaptive neuro fuzzy inference system. The developed prediction model is tested for its prediction ability.

Prediction-based sampled-data H∞ controller design for attitude stabilisation of a rigid spacecraft with disturbances

NASA Astrophysics Data System (ADS)

Zhu, Baolong; Zhang, Zhiping; Zhou, Ding; Ma, Jie; Li, Shunli

2017-08-01

This paper investigates the H∞ control problem of the attitude stabilisation of a rigid spacecraft with external disturbances using prediction-based sampled-data control strategy. Aiming to achieve a 'virtual' closed-loop system, a type of parameterised sampled-data controller is designed by introducing a prediction mechanism. The resultant closed-loop system is equivalent to a hybrid system featured by a continuous-time and an impulsive differential system. By using a time-varying Lyapunov functional, a generalised bounded real lemma (GBRL) is first established for a kind of impulsive differential system. Based on this GBRL and Lyapunov functional approach, a sufficient condition is derived to guarantee the closed-loop system to be asymptotically stable and to achieve a prescribed H∞ performance. In addition, the controller parameter tuning is cast into a convex optimisation problem. Simulation and comparative results are provided to illustrate the effectiveness of the developed control scheme.

Development of a physiologically based pharmacokinetic model to predict the effects of flavin-containing monooxygenase 3 (FMO3) polymorphisms on itopride exposure.

PubMed

Zhou, Wangda; Humphries, Helen; Neuhoff, Sibylle; Gardner, Iain; Masson, Eric; Al-Huniti, Nidal; Zhou, Diansong

2017-09-01

Itopride, a substrate of FMO3, has been used for the symptomatic treatment of various gastrointestinal disorders. Physiologically based pharmacokinetic (PBPK) modeling was applied to evaluate the impact of FMO3 polymorphism on itopride pharmacokinetics (PK). The Asian populations within the Simcyp simulator were updated to incorporate information on the frequency, activity and abundance of FMO3 enzyme with different phenotypes. A meta-analysis of relative enzyme activities suggested that FMO3 activity in subjects with homozygous Glu158Lys and Glu308Gly mutations (Lys158 and Gly308) in both alleles is ~47% lower than those carrying two wild-type FMO3 alleles. Individuals with homozygous Lys158 and Gly308 mutations account for about 5% of the total population in Asian populations. A CL int of 9 μl/min/pmol was optimised for itopride via a retrograde approach as human liver microsomal results would under-predict its clearance by ~7.9-fold. The developed itopride PBPK model was first verified with three additional clinical studies in Korean and Japanese subjects resulting in a predicted clearance of 52 to 69 l/h, which was comparable to those observed (55 to 88 l/h). The model was then applied to predict plasma concentration-time profiles of itopride in Chinese subjects with wild type or homozygous Lys158 and Gly308 FMO3 genotypes. The ratios of predicted to observed AUC of itopride in subjects with each genotype were 1.23 and 0.94, respectively. In addition, the results also suggested that for FMO3 metabolised drugs with a safety margin of 2 or more, proactive genotyping FMO3 to exclude subjects with homozygous Lys158/Gly308 alleles may not be necessary. Copyright © 2017 John Wiley & Sons, Ltd.

Understanding the Models of Community Hospital rehabilitation Activity (MoCHA): a mixed-methods study

PubMed Central

Gladman, John; Buckell, John; Young, John; Smith, Andrew; Hulme, Clare; Saggu, Satti; Godfrey, Mary; Enderby, Pam; Teale, Elizabeth; Longo, Roberto; Gannon, Brenda; Holditch, Claire; Eardley, Heather; Tucker, Helen

2017-01-01

Introduction To understand the variation in performance between community hospitals, our objectives are: to measure the relative performance (cost efficiency) of rehabilitation services in community hospitals; to identify the characteristics of community hospital rehabilitation that optimise performance; to investigate the current impact of community hospital inpatient rehabilitation for older people on secondary care and the potential impact if community hospital rehabilitation was optimised to best practice nationally; to examine the relationship between the configuration of intermediate care and secondary care bed use; and to develop toolkits for commissioners and community hospital providers to optimise performance. Methods and analysis 4 linked studies will be performed. Study 1: cost efficiency modelling will apply econometric techniques to data sets from the National Health Service (NHS) Benchmarking Network surveys of community hospital and intermediate care. This will identify community hospitals' performance and estimate the gap between high and low performers. Analyses will determine the potential impact if the performance of all community hospitals nationally was optimised to best performance, and examine the association between community hospital configuration and secondary care bed use. Study 2: a national community hospital survey gathering detailed cost data and efficiency variables will be performed. Study 3: in-depth case studies of 3 community hospitals, 2 high and 1 low performing, will be undertaken. Case studies will gather routine hospital and local health economy data. Ward culture will be surveyed. Content and delivery of treatment will be observed. Patients and staff will be interviewed. Study 4: co-designed web-based quality improvement toolkits for commissioners and providers will be developed, including indicators of performance and the gap between local and best community hospitals performance. Ethics and dissemination Publications will be in peer-reviewed journals, reports will be distributed through stakeholder organisations. Ethical approval was obtained from the Bradford Research Ethics Committee (reference: 15/YH/0062). PMID:28242766

Assessing potential modifications to the activated sludge process to improve simultaneous removal of a diverse range of micropollutants.

PubMed

Petrie, Bruce; McAdam, Ewan J; Lester, John N; Cartmell, Elise

2014-10-01

It is proposed that wastewater treatment facilities meet legislated discharge limits for a range of micropollutants. However, the heterogeneity of these micropollutants in wastewaters make removal difficult to predict since their chemistry is so diverse. In this study, a range of organic and inorganic micropollutants known to be preferentially removed via different mechanisms were selected to challenge the activated sludge process (ASP) and determine its potential to achieve simultaneous micropollutant removal. At a fixed hydraulic retention time (HRT) of 8 h, the influence of an increase in solids retention time (SRT) on removal was evaluated. Maximum achievable micropollutant removal was recorded for all chemicals (estrogens, nonylphenolics and metals) at the highest SRT studied (27 days). Also, optimisation of HRT by extension to 24 h further augmented organic biodegradation. Most notable was the enhancement in removal of the considerably recalcitrant synthetic estrogen 17α-ethinylestradiol which increased to 65 ± 19%. Regression analysis indicates that this enhanced micropollutant behaviour is ostensibly related to the concomitant reduction in food: microorganism ratio. Interestingly, extended HRT also initiated nonylphenol biodegradation which has not been consistently observed previously in real wastewaters. However, extending HRT increased the solubilisation of particulate bound metals, increasing effluent aqueous metals concentrations (i.e., 0.45 μm filtered) by >100%. This is significant as only the aqueous metal phase is to be considered for environmental compliance. Consequently, identification of an optimum process condition for generic micropollutant removal is expected to favour a more integrated approach where upstream process unit optimisation (i.e., primary sedimentation) is demanded to reduce loading of the particle bound metal phase onto the ASP, thereby enabling longer HRT in the ASP to be considered for optimum removal of organic micropollutants. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Automated model optimisation using the Cylc workflow engine (Cyclops v1.0)

NASA Astrophysics Data System (ADS)

Gorman, Richard M.; Oliver, Hilary J.

2018-06-01

Most geophysical models include many parameters that are not fully determined by theory, and can be tuned to improve the model's agreement with available data. We might attempt to automate this tuning process in an objective way by employing an optimisation algorithm to find the set of parameters that minimises a cost function derived from comparing model outputs with measurements. A number of algorithms are available for solving optimisation problems, in various programming languages, but interfacing such software to a complex geophysical model simulation presents certain challenges. To tackle this problem, we have developed an optimisation suite (Cyclops) based on the Cylc workflow engine that implements a wide selection of optimisation algorithms from the NLopt Python toolbox (Johnson, 2014). The Cyclops optimisation suite can be used to calibrate any modelling system that has itself been implemented as a (separate) Cylc model suite, provided it includes computation and output of the desired scalar cost function. A growing number of institutions are using Cylc to orchestrate complex distributed suites of interdependent cycling tasks within their operational forecast systems, and in such cases application of the optimisation suite is particularly straightforward. As a test case, we applied the Cyclops to calibrate a global implementation of the WAVEWATCH III (v4.18) third-generation spectral wave model, forced by ERA-Interim input fields. This was calibrated over a 1-year period (1997), before applying the calibrated model to a full (1979-2016) wave hindcast. The chosen error metric was the spatial average of the root mean square error of hindcast significant wave height compared with collocated altimeter records. We describe the results of a calibration in which up to 19 parameters were optimised.

Reliability of clinical impact grading by healthcare professionals of common prescribing error and optimisation cases in critical care patients.

PubMed

Bourne, Richard S; Shulman, Rob; Tomlin, Mark; Borthwick, Mark; Berry, Will; Mills, Gary H

2017-04-01

To identify between and within profession-rater reliability of clinical impact grading for common critical care prescribing error and optimisation cases. To identify representative clinical impact grades for each individual case. Electronic questionnaire. 5 UK NHS Trusts. 30 Critical care healthcare professionals (doctors, pharmacists and nurses). Participants graded severity of clinical impact (5-point categorical scale) of 50 error and 55 optimisation cases. Case between and within profession-rater reliability and modal clinical impact grading. Between and within profession rater reliability analysis used linear mixed model and intraclass correlation, respectively. The majority of error and optimisation cases (both 76%) had a modal clinical severity grade of moderate or higher. Error cases: doctors graded clinical impact significantly lower than pharmacists (-0.25; P < 0.001) and nurses (-0.53; P < 0.001), with nurses significantly higher than pharmacists (0.28; P < 0.001). Optimisation cases: doctors graded clinical impact significantly lower than nurses and pharmacists (-0.39 and -0.5; P < 0.001, respectively). Within profession reliability grading was excellent for pharmacists (0.88 and 0.89; P < 0.001) and doctors (0.79 and 0.83; P < 0.001) but only fair to good for nurses (0.43 and 0.74; P < 0.001), for optimisation and error cases, respectively. Representative clinical impact grades for over 100 common prescribing error and optimisation cases are reported for potential clinical practice and research application. The between professional variability highlights the importance of multidisciplinary perspectives in assessment of medication error and optimisation cases in clinical practice and research. © The Author 2017. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Free energy, precision and learning: the role of cholinergic neuromodulation

PubMed Central

Moran, Rosalyn J.; Campo, Pablo; Symmonds, Mkael; Stephan, Klaas E.; Dolan, Raymond J.; Friston, Karl J.

2014-01-01

Acetylcholine (ACh) is a neuromodulatory transmitter implicated in perception and learning under uncertainty. This study combined computational simulations and pharmaco-electroencephalography in humans, to test a formulation of perceptual inference based upon the free energy principle. This formulation suggests that acetylcholine enhances the precision of bottom-up synaptic transmission in cortical hierarchies by optimising the gain of supragranular pyramidal cells. Simulations of a mismatch negativity paradigm predicted a rapid trial-by-trial suppression of evoked sensory prediction error (PE) responses that is attenuated by cholinergic neuromodulation. We confirmed this prediction empirically with a placebo-controlled study of cholinesterase inhibition. Furthermore – using dynamic causal modelling – we found that drug-induced differences in PE responses could be explained by gain modulation in supragranular pyramidal cells in primary sensory cortex. This suggests that acetylcholine adaptively enhances sensory precision by boosting bottom-up signalling when stimuli are predictable, enabling the brain to respond optimally under different levels of environmental uncertainty. PMID:23658161

Statistical modelling coupled with LC-MS analysis to predict human upper intestinal absorption of phytochemical mixtures.

PubMed

Selby-Pham, Sophie N B; Howell, Kate S; Dunshea, Frank R; Ludbey, Joel; Lutz, Adrian; Bennett, Louise

2018-04-15

A diet rich in phytochemicals confers benefits for health by reducing the risk of chronic diseases via regulation of oxidative stress and inflammation (OSI). For optimal protective bio-efficacy, the time required for phytochemicals and their metabolites to reach maximal plasma concentrations (T max ) should be synchronised with the time of increased OSI. A statistical model has been reported to predict T max of individual phytochemicals based on molecular mass and lipophilicity. We report the application of the model for predicting the absorption profile of an uncharacterised phytochemical mixture, herein referred to as the 'functional fingerprint'. First, chemical profiles of phytochemical extracts were acquired using liquid chromatography mass spectrometry (LC-MS), then the molecular features for respective components were used to predict their plasma absorption maximum, based on molecular mass and lipophilicity. This method of 'functional fingerprinting' of plant extracts represents a novel tool for understanding and optimising the health efficacy of plant extracts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fish swarm intelligent to optimize real time monitoring of chips drying using machine vision

NASA Astrophysics Data System (ADS)

Hendrawan, Y.; Hawa, L. C.; Damayanti, R.

2018-03-01

This study attempted to apply machine vision-based chips drying monitoring system which is able to optimise the drying process of cassava chips. The objective of this study is to propose fish swarm intelligent (FSI) optimization algorithms to find the most significant set of image features suitable for predicting water content of cassava chips during drying process using artificial neural network model (ANN). Feature selection entails choosing the feature subset that maximizes the prediction accuracy of ANN. Multi-Objective Optimization (MOO) was used in this study which consisted of prediction accuracy maximization and feature-subset size minimization. The results showed that the best feature subset i.e. grey mean, L(Lab) Mean, a(Lab) energy, red entropy, hue contrast, and grey homogeneity. The best feature subset has been tested successfully in ANN model to describe the relationship between image features and water content of cassava chips during drying process with R2 of real and predicted data was equal to 0.9.

Optimisation of lateral car dynamics taking into account parameter uncertainties

NASA Astrophysics Data System (ADS)

Busch, Jochen; Bestle, Dieter

2014-02-01

Simulation studies on an active all-wheel-steering car show that disturbance of vehicle parameters have high influence on lateral car dynamics. This motivates the need of robust design against such parameter uncertainties. A specific parametrisation is established combining deterministic, velocity-dependent steering control parameters with partly uncertain, velocity-independent vehicle parameters for simultaneous use in a numerical optimisation process. Model-based objectives are formulated and summarised in a multi-objective optimisation problem where especially the lateral steady-state behaviour is improved by an adaption strategy based on measurable uncertainties. The normally distributed uncertainties are generated by optimal Latin hypercube sampling and a response surface based strategy helps to cut down time consuming model evaluations which offers the possibility to use a genetic optimisation algorithm. Optimisation results are discussed in different criterion spaces and the achieved improvements confirm the validity of the proposed procedure.

Distributed optimisation problem with communication delay and external disturbance

NASA Astrophysics Data System (ADS)

Tran, Ngoc-Tu; Xiao, Jiang-Wen; Wang, Yan-Wu; Yang, Wu

2017-12-01

This paper investigates the distributed optimisation problem for the multi-agent systems (MASs) with the simultaneous presence of external disturbance and the communication delay. To solve this problem, a two-step design scheme is introduced. In the first step, based on the internal model principle, the internal model term is constructed to compensate the disturbance asymptotically. In the second step, a distributed optimisation algorithm is designed to solve the distributed optimisation problem based on the MASs with the simultaneous presence of disturbance and communication delay. Moreover, in the proposed algorithm, each agent interacts with its neighbours through the connected topology and the delay occurs during the information exchange. By utilising Lyapunov-Krasovskii functional, the delay-dependent conditions are derived for both slowly and fast time-varying delay, respectively, to ensure the convergence of the algorithm to the optimal solution of the optimisation problem. Several numerical simulation examples are provided to illustrate the effectiveness of the theoretical results.

An effective pseudospectral method for constraint dynamic optimisation problems with characteristic times

NASA Astrophysics Data System (ADS)

Xiao, Long; Liu, Xinggao; Ma, Liang; Zhang, Zeyin

2018-03-01

Dynamic optimisation problem with characteristic times, widely existing in many areas, is one of the frontiers and hotspots of dynamic optimisation researches. This paper considers a class of dynamic optimisation problems with constraints that depend on the interior points either fixed or variable, where a novel direct pseudospectral method using Legendre-Gauss (LG) collocation points for solving these problems is presented. The formula for the state at the terminal time of each subdomain is derived, which results in a linear combination of the state at the LG points in the subdomains so as to avoid the complex nonlinear integral. The sensitivities of the state at the collocation points with respect to the variable characteristic times are derived to improve the efficiency of the method. Three well-known characteristic time dynamic optimisation problems are solved and compared in detail among the reported literature methods. The research results show the effectiveness of the proposed method.

Medicines optimisation: priorities and challenges.

PubMed

Kaufman, Gerri

2016-03-23

Medicines optimisation is promoted in a guideline published in 2015 by the National Institute for Health and Care Excellence. Four guiding principles underpin medicines optimisation: aim to understand the patient's experience; ensure evidence-based choice of medicines; ensure medicines use is as safe as possible; and make medicines optimisation part of routine practice. Understanding the patient experience is important to improve adherence to medication regimens. This involves communication, shared decision making and respect for patient preferences. Evidence-based choice of medicines is important for clinical and cost effectiveness. Systems and processes for the reporting of medicines-related safety incidents have to be improved if medicines use is to be as safe as possible. Ensuring safe practice in medicines use when patients are transferred between organisations, and managing the complexities of polypharmacy are imperative. A medicines use review can help to ensure that medicines optimisation forms part of routine practice.

Determination of somatropin charged variants by capillary zone electrophoresis - optimisation, verification and implementation of the European pharmacopoeia method.

PubMed

Storms, S M; Feltus, A; Barker, A R; Joly, M-A; Girard, M

2009-03-01

Measurement of somatropin charged variants by isoelectric focusing was replaced with capillary zone electrophoresis in the January 2006 European Pharmacopoeia Supplement 5.3, based on results from an interlaboratory collaborative study. Due to incompatibilities and method-robustness issues encountered prior to verification, a number of method parameters required optimisation. As the use of a diode array detector at 195 nm or 200 nm led to a loss of resolution, a variable wavelength detector using a 200 nm filter was employed. Improved injection repeatability was obtained by increasing the injection time and pressure, and changing the sample diluent from water to running buffer. Finally, definition of capillary pre-treatment and rinse procedures resulted in more consistent separations over time. Method verification data are presented demonstrating linearity, specificity, repeatability, intermediate precision, limit of quantitation, sample stability, solution stability, and robustness. Based on these experiments, several modifications to the current method have been recommended and incorporated into the European Pharmacopoeia to help improve method performance across laboratories globally.

Optimization of Process Parameters for High Efficiency Laser Forming of Advanced High Strength Steels within Metallurgical Constraints

NASA Astrophysics Data System (ADS)

Sheikholeslami, Ghazal; Griffiths, Jonathan; Dearden, Geoff; Edwardson, Stuart P.

Laser forming (LF) has been shown to be a viable alternative to form automotive grade advanced high strength steels (AHSS). Due to their high strength, heat sensitivity and low conventional formability show early fractures, larger springback, batch-to-batch inconsistency and high tool wear. In this paper, optimisation of the LF process parameters has been conducted to further understand the impact of a surface heat treatment on DP1000. A FE numerical simulation has been developed to analyse the dynamic thermo-mechanical effects. This has been verified against empirical data. The goal of the optimisation has been to develop a usable process window for the LF of AHSS within strict metallurgical constraints. Results indicate it is possible to LF this material, however a complex relationship has been found between the generation and maintenance of hardness values in the heated zone. A laser surface hardening effect has been observed that could be beneficial to the efficiency of the process.

Towards Automatic Image Segmentation Using Optimised Region Growing Technique

NASA Astrophysics Data System (ADS)

Alazab, Mamoun; Islam, Mofakharul; Venkatraman, Sitalakshmi

Image analysis is being adopted extensively in many applications such as digital forensics, medical treatment, industrial inspection, etc. primarily for diagnostic purposes. Hence, there is a growing interest among researches in developing new segmentation techniques to aid the diagnosis process. Manual segmentation of images is labour intensive, extremely time consuming and prone to human errors and hence an automated real-time technique is warranted in such applications. There is no universally applicable automated segmentation technique that will work for all images as the image segmentation is quite complex and unique depending upon the domain application. Hence, to fill the gap, this paper presents an efficient segmentation algorithm that can segment a digital image of interest into a more meaningful arrangement of regions and objects. Our algorithm combines region growing approach with optimised elimination of false boundaries to arrive at more meaningful segments automatically. We demonstrate this using X-ray teeth images that were taken for real-life dental diagnosis.

Continuous subcutaneous insulin infusion therapy for Type 1 diabetes mellitus in children.

PubMed

Mavinkurve, M; Quinn, A; O'Gorman, C S

2016-05-01

Continuous subcutaneous insulin pump therapy (CSII or pump therapy) is a well-recognised treatment option for Type 1 diabetes mellitus (T1DM) in paediatrics. It is especially suited to children because it optimises control by improving flexibility across age-specific lifestyles. The NICE guidelines (2008) recognise that pump therapy is advantageous and that it should be utilised to deliver best practice. In Ireland, the National Clinical Program for Diabetes will increase the availability and uptake of CSII in children and thus more clinicians are likely to encounter children using CSII therapy. This is a narrative review which discusses the basic principles of pump therapy and focuses on aspects of practical management. Insulin pump management involves some basic yet important principles which optimise the care of diabetes in children. This review addresses the principles of insulin pump management in children which all health care professionals involved in caring for the child with diabetes, shoud be familiar with.

Development of an optimised key worker framework for people with dementia, their family and caring unit living in the community.

PubMed

Renehan, Emma; Goeman, Dianne; Koch, Susan

2017-07-20

In Australia, dementia is a national health priority. With the rising number of people living with dementia and shortage of formal and informal carers predicted in the near future, developing approaches to coordinating services in quality-focused ways is considered an urgent priority. Key worker support models are one approach that have been used to assist people living with dementia and their caring unit coordinate services and navigate service systems; however, there is limited literature outlining comprehensive frameworks for the implementation of community dementia key worker roles in practice. In this paper an optimised key worker framework for people with dementia, their family and caring unit living in the community is developed and presented. A number of processes were undertaken to inform the development of a co-designed optimised key worker framework: an expert working and reference group; a systematic review of the literature; and a qualitative evaluation of 14 dementia key worker models operating in Australia involving 14 interviews with organisation managers, 19 with key workers and 15 with people living with dementia and/or their caring unit. Data from the systematic review and evaluation of dementia key worker models were analysed by the researchers and the expert working and reference group using a constant comparative approach to define the essential components of the optimised framework. The developed framework consisted of four main components: overarching philosophies; organisational context; role definition; and key worker competencies. A number of more clearly defined sub-themes sat under each component. Reflected in the framework is the complexity of the dementia journey and the difficulty in trying to develop a 'one size fits all' approach. This co-designed study led to the development of an evidence based framework which outlines a comprehensive synthesis of components viewed as being essential to the implementation of a dementia key worker model of care in the community. The framework was informed and endorsed by people living with dementia and their caring unit, key workers, managers, Australian industry experts, policy makers and researchers. An evaluation of its effectiveness and relevance for practice within the dementia care space is required.

The use of genomic coancestry matrices in the optimisation of contributions to maintain genetic diversity at specific regions of the genome.

PubMed

Gómez-Romano, Fernando; Villanueva, Beatriz; Fernández, Jesús; Woolliams, John A; Pong-Wong, Ricardo

2016-01-13

Optimal contribution methods have proved to be very efficient for controlling the rates at which coancestry and inbreeding increase and therefore, for maintaining genetic diversity. These methods have usually relied on pedigree information for estimating genetic relationships between animals. However, with the large amount of genomic information now available such as high-density single nucleotide polymorphism (SNP) chips that contain thousands of SNPs, it becomes possible to calculate more accurate estimates of relationships and to target specific regions in the genome where there is a particular interest in maximising genetic diversity. The objective of this study was to investigate the effectiveness of using genomic coancestry matrices for: (1) minimising the loss of genetic variability at specific genomic regions while restricting the overall loss in the rest of the genome; or (2) maximising the overall genetic diversity while restricting the loss of diversity at specific genomic regions. Our study shows that the use of genomic coancestry was very successful at minimising the loss of diversity and outperformed the use of pedigree-based coancestry (genetic diversity even increased in some scenarios). The results also show that genomic information allows a targeted optimisation to maintain diversity at specific genomic regions, whether they are linked or not. The level of variability maintained increased when the targeted regions were closely linked. However, such targeted management leads to an important loss of diversity in the rest of the genome and, thus, it is necessary to take further actions to constrain this loss. Optimal contribution methods also proved to be effective at restricting the loss of diversity in the rest of the genome, although the resulting rate of coancestry was higher than the constraint imposed. The use of genomic matrices when optimising contributions permits the control of genetic diversity and inbreeding at specific regions of the genome through the minimisation of partial genomic coancestry matrices. The formula used to predict coancestry in the next generation produces biased results and therefore it is necessary to refine the theory of genetic contributions when genomic matrices are used to optimise contributions.

Optimising stocking rate and grazing management to enhance environmental and production outcomes for native temperate grasslands

NASA Astrophysics Data System (ADS)

Badgery, Warwick; Zhang, Yingjun; Huang, Ding; Broadfoot, Kim; Kemp, David; Mitchell, David

2015-04-01

Stocking rate and grazing management can be altered to enhance the sustainable production of grasslands but the relative influence of each has not often been determined for native temperate grasslands. Grazing management can range from seasonal rests through to intensive rotational grazing involving >30 paddocks. In large scale grazing, it can be difficult to segregate the influence of grazing pressure from the timing of utilisation. Moreover, relative grazing pressure can change between years as seasonal conditions influence grassland production compared to the relative constant requirements of animals. This paper reports on two studies in temperate native grasslands of northern China and south eastern Australia that examined stocking rate and regionally relevant grazing management strategies. In China, the grazing experiment involved combinations of a rest, moderate or heavy grazing pressure of sheep in spring, then moderate or heavy grazing in summer and autumn. Moderate grazing pressure at 50% of the current district average, resulted in the better balance between maintaining productive and diverse grasslands, a profitable livestock system, and mitigation of greenhouse gases through increased soil carbon, methane uptake by the soil, and efficient methane emissions per unit of weight gain. Spring rests best maintained a desirable grassland composition, but had few other benefits and reduced livestock productivity due to lower feed quality from grazing later in the season. In Australia, the grazing experiment compared continuous grazing to flexible 4- and 20-paddock rotational grazing systems with sheep. Stocking rates were adjusted between systems biannually based on the average herbage mass of the grassland. No treatment degraded the perennial pasture composition, but ground cover was maintained at higher levels in the 20-paddock system even though this treatment had a higher stocking rate. Overall there was little difference in livestock production (e.g. kg lamb/ha), because individual animal performance was greater for continuous grazing than higher intensity grazing systems (4-Paddock and 20-Paddock). Differences in SOC, CO2 flux and erosion were determined by landscape position rather than grazing treatment. To remove the confounding influences of stocking rate and grazing management, the Ausfarm biophysical model, calibrated to the experimental treatments, examined the interaction between grazing management and stocking rates. Ground cover and profitability were similar between grazing systems at lower stocking rates (3 ewes per ha), but continuous grazing had higher profitability and lower ground cover above the optimum stocking rate of 4 ewes per ha. The findings of these two studies suggest that optimising stocking rate is more important than grazing management for a sustainable and profitable grazing system. Grazing management can further enhance environmental outcomes for an optimal stocking rate, but the findings from the Chinese study particularly highlight the need to look at multiple ecosystem services, when optimising systems. The Australian study also suggests the optimum stocking rate is dependent on the intensity of grazing management. Further work is required to understand the influence of landscape on grassland production and how stocking rates and grazing management can be sustainably optimised for different landscape areas to utilise this variation more effectively.

Multi-Optimisation Consensus Clustering

NASA Astrophysics Data System (ADS)

Li, Jian; Swift, Stephen; Liu, Xiaohui

Ensemble Clustering has been developed to provide an alternative way of obtaining more stable and accurate clustering results. It aims to avoid the biases of individual clustering algorithms. However, it is still a challenge to develop an efficient and robust method for Ensemble Clustering. Based on an existing ensemble clustering method, Consensus Clustering (CC), this paper introduces an advanced Consensus Clustering algorithm called Multi-Optimisation Consensus Clustering (MOCC), which utilises an optimised Agreement Separation criterion and a Multi-Optimisation framework to improve the performance of CC. Fifteen different data sets are used for evaluating the performance of MOCC. The results reveal that MOCC can generate more accurate clustering results than the original CC algorithm.

Optimised collision avoidance for an ultra-close rendezvous with a failed satellite based on the Gauss pseudospectral method

NASA Astrophysics Data System (ADS)

Chu, Xiaoyu; Zhang, Jingrui; Lu, Shan; Zhang, Yao; Sun, Yue

2016-11-01

This paper presents a trajectory planning algorithm to optimise the collision avoidance of a chasing spacecraft operating in an ultra-close proximity to a failed satellite. The complex configuration and the tumbling motion of the failed satellite are considered. The two-spacecraft rendezvous dynamics are formulated based on the target body frame, and the collision avoidance constraints are detailed, particularly concerning the uncertainties. An optimisation solution of the approaching problem is generated using the Gauss pseudospectral method. A closed-loop control is used to track the optimised trajectory. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms.

Optimisation of groundwater level monitoring networks using geostatistical modelling based on the Spartan family variogram and a genetic algorithm method

NASA Astrophysics Data System (ADS)

Parasyris, Antonios E.; Spanoudaki, Katerina; Kampanis, Nikolaos A.

2016-04-01

Groundwater level monitoring networks provide essential information for water resources management, especially in areas with significant groundwater exploitation for agricultural and domestic use. Given the high maintenance costs of these networks, development of tools, which can be used by regulators for efficient network design is essential. In this work, a monitoring network optimisation tool is presented. The network optimisation tool couples geostatistical modelling based on the Spartan family variogram with a genetic algorithm method and is applied to Mires basin in Crete, Greece, an area of high socioeconomic and agricultural interest, which suffers from groundwater overexploitation leading to a dramatic decrease of groundwater levels. The purpose of the optimisation tool is to determine which wells to exclude from the monitoring network because they add little or no beneficial information to groundwater level mapping of the area. Unlike previous relevant investigations, the network optimisation tool presented here uses Ordinary Kriging with the recently-established non-differentiable Spartan variogram for groundwater level mapping, which, based on a previous geostatistical study in the area leads to optimal groundwater level mapping. Seventy boreholes operate in the area for groundwater abstraction and water level monitoring. The Spartan variogram gives overall the most accurate groundwater level estimates followed closely by the power-law model. The geostatistical model is coupled to an integer genetic algorithm method programmed in MATLAB 2015a. The algorithm is used to find the set of wells whose removal leads to the minimum error between the original water level mapping using all the available wells in the network and the groundwater level mapping using the reduced well network (error is defined as the 2-norm of the difference between the original mapping matrix with 70 wells and the mapping matrix of the reduced well network). The solution to the optimization problem (the best wells to retain in the monitoring network) depends on the total number of wells removed; this number is a management decision. The water level monitoring network of Mires basin has been optimized 6 times by removing 5, 8, 12, 15, 20 and 25 wells from the original network. In order to achieve the optimum solution in the minimum possible computational time, a stall generations criterion was set for each optimisation scenario. An improvement made to the classic genetic algorithm was the change of the mutation and crossover fraction in respect to the change of the mean fitness value. This results to a randomness in reproduction, if the solution converges, to avoid local minima, or, in a more educated reproduction (higher crossover ratio) when there is higher change in the mean fitness value. The choice of integer genetic algorithm in MATLAB 2015a poses the restriction of adding custom selection and crossover-mutation functions. Therefore, custom population and crossover-mutation-selection functions have been created to set the initial population type to custom and have the ability to change the mutation crossover probability in respect to the convergence of the genetic algorithm, achieving thus higher accuracy. The application of the network optimisation tool to Mires basin indicates that 25 wells can be removed with a relatively small deterioration of the groundwater level map. The results indicate the robustness of the network optimisation tool: Wells were removed from high well-density areas while preserving the spatial pattern of the original groundwater level map. Varouchakis, E. A. and D. T. Hristopulos (2013). "Improvement of groundwater level prediction in sparsely gauged basins using physical laws and local geographic features as auxiliary variables." Advances in Water Resources 52: 34-49.

Circuit-level optimisation of a:Si TFT-based AMOLED pixel circuits for maximum hold current

NASA Astrophysics Data System (ADS)

Foroughi, Aidin; Mehrpoo, Mohammadreza; Ashtiani, Shahin J.

2013-11-01

Design of AMOLED pixel circuits has manifold constraints and trade-offs which provides incentive for circuit designers to seek optimal solutions for different objectives. In this article, we present a discussion on the viability of an optimal solution to achieve the maximum hold current. A compact formula for component sizing in a conventional 2T1C pixel is, therefore, derived. Compared to SPICE simulation results, for several pixel sizes, our predicted optimum sizing yields maximum currents with errors less than 0.4%.

Selective batch crushing in the coal-preparation shop at OAO NTMK

DOE Office of Scientific and Technical Information (OSTI.GOV)

N.A. Berkutov; Yu.V. Stepanov; P.V. Shtark

In September 2004, after reconstruction at OAO Nizhnetagil'skii Metallurgicheskii Kombinat (NTMK), blast furnace 6 went into operation for the production of vanadium from hot metal. At the startup of furnace 6, besides optimising its composition; it was decided to restore selective crushing of the coal batch using pneumatic and mechanical separation in the third unit of the coal preparation shop. Additional increase in the mechanical strength of coke by 1.5-2.0% was predicted with a 0.5-1.0% decrease in wear.

Stably engineered nanobubbles and ultrasound - An effective platform for enhanced macromolecular delivery to representative cells of the retina.

PubMed

Thakur, Sachin S; Ward, Micheal S; Popat, Amirali; Flemming, Nicole B; Parat, Marie-Odile; Barnett, Nigel L; Parekh, Harendra S

2017-01-01

Herein we showcase the potential of ultrasound-responsive nanobubbles in enhancing macromolecular permeation through layers of the retina, ultimately leading to significant and direct intracellular delivery; this being effectively demonstrated across three relevant and distinct retinal cell lines. Stably engineered nanobubbles of a highly homogenous and echogenic nature were fully characterised using dynamic light scattering, B-scan ultrasound and transmission electron microscopy (TEM). The nanobubbles appeared as spherical liposome-like structures under TEM, accompanied by an opaque luminal core and darkened corona around their periphery, with both features indicative of efficient gas entrapment and adsorption, respectively. A nanobubble +/- ultrasound sweeping study was conducted next, which determined the maximum tolerated dose for each cell line. Detection of underlying cellular stress was verified using the biomarker heat shock protein 70, measured before and after treatment with optimised ultrasound. Next, with safety to nanobubbles and optimised ultrasound demonstrated, each human or mouse-derived cell population was incubated with biotinylated rabbit-IgG in the presence and absence of ultrasound +/- nanobubbles. Intracellular delivery of antibody in each cell type was then quantified using Cy3-streptavidin. Nanobubbles and optimised ultrasound were found to be negligibly toxic across all cell lines tested. Macromolecular internalisation was achieved to significant, yet varying degrees in all three cell lines. The results of this study pave the way towards better understanding mechanisms underlying cellular responsiveness to ultrasound-triggered drug delivery in future ex vivo and in vivo models of the posterior eye.

Stably engineered nanobubbles and ultrasound - An effective platform for enhanced macromolecular delivery to representative cells of the retina

PubMed Central

Thakur, Sachin S.; Ward, Micheal S.; Popat, Amirali; Flemming, Nicole B.; Parat, Marie-Odile; Barnett, Nigel L.

2017-01-01

Herein we showcase the potential of ultrasound-responsive nanobubbles in enhancing macromolecular permeation through layers of the retina, ultimately leading to significant and direct intracellular delivery; this being effectively demonstrated across three relevant and distinct retinal cell lines. Stably engineered nanobubbles of a highly homogenous and echogenic nature were fully characterised using dynamic light scattering, B-scan ultrasound and transmission electron microscopy (TEM). The nanobubbles appeared as spherical liposome-like structures under TEM, accompanied by an opaque luminal core and darkened corona around their periphery, with both features indicative of efficient gas entrapment and adsorption, respectively. A nanobubble +/- ultrasound sweeping study was conducted next, which determined the maximum tolerated dose for each cell line. Detection of underlying cellular stress was verified using the biomarker heat shock protein 70, measured before and after treatment with optimised ultrasound. Next, with safety to nanobubbles and optimised ultrasound demonstrated, each human or mouse-derived cell population was incubated with biotinylated rabbit-IgG in the presence and absence of ultrasound +/- nanobubbles. Intracellular delivery of antibody in each cell type was then quantified using Cy3-streptavidin. Nanobubbles and optimised ultrasound were found to be negligibly toxic across all cell lines tested. Macromolecular internalisation was achieved to significant, yet varying degrees in all three cell lines. The results of this study pave the way towards better understanding mechanisms underlying cellular responsiveness to ultrasound-triggered drug delivery in future ex vivo and in vivo models of the posterior eye. PMID:28542473

Rethinking non-inferiority: a practical trial design for optimising treatment duration.

PubMed

Quartagno, Matteo; Walker, A Sarah; Carpenter, James R; Phillips, Patrick Pj; Parmar, Mahesh Kb

2018-06-01

Background Trials to identify the minimal effective treatment duration are needed in different therapeutic areas, including bacterial infections, tuberculosis and hepatitis C. However, standard non-inferiority designs have several limitations, including arbitrariness of non-inferiority margins, choice of research arms and very large sample sizes. Methods We recast the problem of finding an appropriate non-inferior treatment duration in terms of modelling the entire duration-response curve within a pre-specified range. We propose a multi-arm randomised trial design, allocating patients to different treatment durations. We use fractional polynomials and spline-based methods to flexibly model the duration-response curve. We call this a 'Durations design'. We compare different methods in terms of a scaled version of the area between true and estimated prediction curves. We evaluate sensitivity to key design parameters, including sample size, number and position of arms. Results A total sample size of ~ 500 patients divided into a moderate number of equidistant arms (5-7) is sufficient to estimate the duration-response curve within a 5% error margin in 95% of the simulations. Fractional polynomials provide similar or better results than spline-based methods in most scenarios. Conclusion Our proposed practical randomised trial 'Durations design' shows promising performance in the estimation of the duration-response curve; subject to a pending careful investigation of its inferential properties, it provides a potential alternative to standard non-inferiority designs, avoiding many of their limitations, and yet being fairly robust to different possible duration-response curves. The trial outcome is the whole duration-response curve, which may be used by clinicians and policymakers to make informed decisions, facilitating a move away from a forced binary hypothesis testing paradigm.

TACD: a transportable ant colony discrimination model for corporate bankruptcy prediction

NASA Astrophysics Data System (ADS)

Lalbakhsh, Pooia; Chen, Yi-Ping Phoebe

2017-05-01

This paper presents a transportable ant colony discrimination strategy (TACD) to predict corporate bankruptcy, a topic of vital importance that is attracting increasing interest in the field of economics. The proposed algorithm uses financial ratios to build a binary prediction model for companies with the two statuses of bankrupt and non-bankrupt. The algorithm takes advantage of an improved version of continuous ant colony optimisation (CACO) at the core, which is used to create an accurate, simple and understandable linear model for discrimination. This also enables the algorithm to work with continuous values, leading to more efficient learning and adaption by avoiding data discretisation. We conduct a comprehensive performance evaluation on three real-world data sets under a stratified cross-validation strategy. In three different scenarios, TACD is compared with 11 other bankruptcy prediction strategies. We also discuss the efficiency of the attribute selection methods used in the experiments. In addition to its simplicity and understandability, statistical significance tests prove the efficiency of TACD against the other prediction algorithms in both measures of AUC and accuracy.

Early warnings of hazardous thunderstorms over Lake Victoria

NASA Astrophysics Data System (ADS)

Thiery, Wim; Gudmundsson, Lukas; Bedka, Kristopher; Semazzi, Fredrick H. M.; Lhermitte, Stef; Willems, Patrick; van Lipzig, Nicole P. M.; Seneviratne, Sonia I.

2017-07-01

Weather extremes have harmful impacts on communities around Lake Victoria in East Africa. Every year, intense nighttime thunderstorms cause numerous boating accidents on the lake, resulting in thousands of deaths among fishermen. Operational storm warning systems are therefore crucial. Here we complement ongoing early warning efforts based on numerical weather prediction, by presenting a new satellite data-driven storm prediction system, the prototype Lake Victoria Intense storm Early Warning System (VIEWS). VIEWS derives predictability from the correlation between afternoon land storm activity and nighttime storm intensity on Lake Victoria, and relies on logistic regression techniques to forecast extreme thunderstorms from satellite observations. Evaluation of the statistical model reveals that predictive power is high and independent of the type of input dataset. We then optimise the configuration and show that false alarms also contain valuable information. Our results suggest that regression-based models that are motivated through process understanding have the potential to reduce the vulnerability of local fishing communities around Lake Victoria. The experimental prediction system is publicly available under the MIT licence at http://github.com/wthiery/VIEWS.

Rivastigmine in apathetic but dementia and depression-free patients with Parkinson's disease: a double-blind, placebo-controlled, randomised clinical trial.

PubMed

Devos, David; Moreau, Caroline; Maltête, David; Lefaucheur, Romain; Kreisler, Alexandre; Eusebio, Alexandre; Defer, Gilles; Ouk, Thavarak; Azulay, Jean-Philippe; Krystkowiak, Pierre; Witjas, Tatiana; Delliaux, Marie; Destée, Alain; Duhamel, Alain; Bordet, Régis; Defebvre, Luc; Dujardin, Kathy

2014-06-01

Even with optimal dopaminergic treatments, many patients with Parkinson's disease (PD) are frequently incapacitated by apathy prior to the development of dementia. We sought to establish whether rivastigmine's ability to inhibit acetyl- and butyrylcholinesterases could relieve the symptoms of apathy in dementia-free, non-depressed patients with advanced PD. We performed a multicentre, parallel, double-blind, placebo-controlled, randomised clinical trial (Protocol ID: 2008-002578-36; clinicaltrials.gov reference: NCT00767091) in patients with PD with moderate to severe apathy (despite optimised dopaminergic treatment) and without dementia. Patients from five French university hospitals were randomly assigned 1:1 to rivastigmine (transdermal patch of 9.5 mg/day) or placebo for 6 months. The primary efficacy criterion was the change over time in the Lille Apathy Rating Scale (LARS) score. 101 consecutive patients were screened, 31 were eligible and 16 and 14 participants were randomised into the rivastigmine and placebo groups, respectively. Compared with placebo, rivastigmine improved the LARS score (from -11.5 (-15/-7) at baseline to -20 (-25/-12) after treatment; F(1, 25)=5.2; p=0.031; adjusted size effect: -0.9). Rivastigmine also improved the caregiver burden and instrumental activities of daily living but failed to improve quality of life. No severe adverse events occurred in the rivastigmine group. Rivastigmine may represent a new therapeutic option for moderate to severe apathy in advanced PD patients with optimised dopaminergic treatment and without depression dementia. These findings require confirmation in a larger clinical trial. Our results also confirmed that the presence of apathy can herald a pre-dementia state in PD. Clinicaltrials.gov reference: NCT00767091.

Dose- and LET-painting with particle therapy.

PubMed

Bassler, Niels; Jäkel, Oliver; Søndergaard, Christian Skou; Petersen, Jørgen B

2010-10-01

Tumour hypoxia is one of the limiting factors in obtaining tumour control in radiotherapy. The high-LET region of a beam of heavy charged particles such as carbon ions is located in the distal part of the Bragg peak. A modulated or spread out Bragg peak (SOBP) is a weighted function of several Bragg peaks at various energies, which however results in a dilution of the dose-average LET in the target volume. Here, we investigate the possibility to redistribute the LET by dedicated treatment plan optimisation, in order to maximise LET in the target volume. This may be a strategy to potentially overcome hypoxia along with dose escalation or dose painting. The high-LET region can be shaped in very different ways, while maintaining the distribution of the absorbed dose or biological effective dose. Treatment plans involving only carbon ion beams, show very different LET distributions depending on how the fields are arranged. Alternatively, a LET boost can be applied in multi-modal treatment planning, such as combining carbon ions with protons and/or photons. For such mixed radiation modalities, significant "LET boosts" can be achieved at nearly arbitrary positions within the target volume. Following the general understanding of the relationship between hypoxia, LET and the oxygen enhancement ratio (OER), we conclude, that an additional therapeutic advantage can be achieved by confining the high-LET part of the radiation in hypoxic compartments of the tumour, and applying low-LET radiation to the normoxic tissue. We also anticipate that additional advantages may be achieved by deliberate sparing of normal tissue from high LET regions. Consequently, treatment planning based on simultaneous dose and LET optimisation has a potential to achieve higher tumour control and/or reduced normal tissue control probability (NTCP).

Optimising mechanical properties of hot forged nickel superalloy 625 components

NASA Astrophysics Data System (ADS)

Singo, Nthambe; Coles, John; Rosochowska, Malgorzata; Lalvani, Himanshu; Hernandez, Jose; Ion, William

2018-05-01

Hot forging and subsequent heat treatment were resulting in substandard mechanical properties of nickel superalloy, Alloy 625, components. The low strength was found to be due to inadequate deformation during forging, excessive grain growth and precipitation of carbides during subsequent heat treatment. Experimentation in a drop forging company and heat treatment facility led to the establishment of optimal parameters to minimise grain size and mitigate the adverse effects of carbide precipitation, leading to successful fulfilment of mechanical property specifications. This was achieved by reducing the number of operations, maximising the extent of deformation by changing the slug dimensions and its orientation in the die, and minimising the time of exposure to elevated temperatures in both the forging and subsequent heat treatment processes to avoid grain growth.

Novel anti-malarial combinations and their toxicity.

PubMed

Angus, Brian

2014-05-01

Artemisinin combination therapy for the treatment of uncomplicated malaria includes artemether plus lumefantrine, artesunate plus amodiaquine, artesunate plus mefloquine, artesunate plus sulfadoxine-pyrimethamine and dihydroartemisinin plus piperaquine. These drugs are safe and efficacious at present. The emergence of artemisinin resistant parasites in SE Asia means that there is a need to optimise drug dosing and investigate novel therapies to maintain the impressive reduction in malaria mortality which has been seen in the past decade.

Design and optimisation of orally active TLR7 agonists for the treatment of hepatitis C virus infection.

PubMed

Tran, Thien-Duc; Pryde, David C; Jones, Peter; Adam, Fiona M; Benson, Neil; Bish, Gerwyn; Calo, Frederick; Ciaramella, Guiseppe; Dixon, Rachel; Duckworth, Jonathan; Fox, David N A; Hay, Duncan A; Hitchin, James; Horscroft, Nigel; Howard, Martin; Gardner, Iain; Jones, Hannah M; Laxton, Carl; Parkinson, Tanya; Parsons, Gemma; Proctor, Katie; Smith, Mya C; Smith, Nicholas; Thomas, Amy

2011-04-15

The synthesis and structure-activity relationships of a series of novel interferon inducers are described. Pharmacokinetic studies and efficacy assessment of a series of 8-oxo-3-deazapurine analogues led to the identification of compound 33, a potent and selective agonist of the TLR7 receptor with an excellent in vivo efficacy profile in a mouse model. Copyright © 2011 Elsevier Ltd. All rights reserved.

Fabrication of Organic Radar Absorbing Materials: A Report on the TIF Project

DTIC Science & Technology

2005-05-01

thickness, permittivity and permeability. The ability to measure the permittivity and permeability is an essential requirement for designing an optimised...absorber. And good optimisations codes are required in order to achieve the best possible absorber designs . In this report, the results from a...through measurement of their conductivity and permittivity at microwave frequencies. Methods were then developed for optimising the design of

Outcomes and prognostic factors of multimodality treatment for locally recurrent rectal cancer with curative intent.

PubMed

Bird, Thomas G; Ngan, Samuel Y; Chu, Julie; Kroon, René; Lynch, Andrew C; Heriot, Alexander G

2018-04-01

Radical management of locally recurrent rectal cancer (LRRC) can lead to prolonged survival. This study aims to assess outcomes and identify prognostic factors for patients with LRRC treated using a multimodality treatment protocol. An analysis of a prospectively maintained institutional database of consecutive patients who underwent radical surgical resection for LRRC was performed. Potential prognostic factors were investigated using a Cox proportional hazards model. Ninety-eight patients were included in this study. A multimodality approach was taken in the majority, including preoperative chemoradiation (78%), intraoperative radiation therapy (47%) and adjuvant chemotherapy (41%). Extended resection was performed where required: bone resection (34%) and lateral pelvic sidewall dissection (31%). The rate of R0 resection was 66%. Estimated rates of 5-year overall survival (OS) and progression-free survival (PFS) were 41.8% (95% CI 32.5-53.7) and 22.5% (95% CI 15.3-33.1). On multivariate analysis, stage III disease at initial primary surgery, a positive margin at initial primary surgery, synchronous or previously resected oligometastases, a lateral or sacral invasive-type pelvic recurrence and the requirement for IORT all predicted for inferior PFS (p < 0.05). Eleven percent of patients subsequently underwent further pelvic surgery for pelvic re-recurrence and had an estimated 5-year OS rate of 54.5% (95% CI 29.0-100.0) from repeat surgery. Radical multimodality management of LRRC leads to prolonged survival in approximately 40% of patients. Those with sacral or lateral invasive-type recurrence or oligometastatic disease have inferior outcomes and further research is needed to optimise treatment for these groups.

A Method for Decentralised Optimisation in Networks

NASA Astrophysics Data System (ADS)

Saramäki, Jari

2005-06-01

We outline a method for distributed Monte Carlo optimisation of computational problems in networks of agents, such as peer-to-peer networks of computers. The optimisation and messaging procedures are inspired by gossip protocols and epidemic data dissemination, and are decentralised, i.e. no central overseer is required. In the outlined method, each agent follows simple local rules and seeks for better solutions to the optimisation problem by Monte Carlo trials, as well as by querying other agents in its local neighbourhood. With proper network topology, good solutions spread rapidly through the network for further improvement. Furthermore, the system retains its functionality even in realistic settings where agents are randomly switched on and off.

Thermal buckling optimisation of composite plates using firefly algorithm

NASA Astrophysics Data System (ADS)

Kamarian, S.; Shakeri, M.; Yas, M. H.

2017-07-01

Composite plates play a very important role in engineering applications, especially in aerospace industry. Thermal buckling of such components is of great importance and must be known to achieve an appropriate design. This paper deals with stacking sequence optimisation of laminated composite plates for maximising the critical buckling temperature using a powerful meta-heuristic algorithm called firefly algorithm (FA) which is based on the flashing behaviour of fireflies. The main objective of present work was to show the ability of FA in optimisation of composite structures. The performance of FA is compared with the results reported in the previous published works using other algorithms which shows the efficiency of FA in stacking sequence optimisation of laminated composite structures.

Distributed convex optimisation with event-triggered communication in networked systems

NASA Astrophysics Data System (ADS)

Liu, Jiayun; Chen, Weisheng

2016-12-01

This paper studies the distributed convex optimisation problem over directed networks. Motivated by practical considerations, we propose a novel distributed zero-gradient-sum optimisation algorithm with event-triggered communication. Therefore, communication and control updates just occur at discrete instants when some predefined condition satisfies. Thus, compared with the time-driven distributed optimisation algorithms, the proposed algorithm has the advantages of less energy consumption and less communication cost. Based on Lyapunov approaches, we show that the proposed algorithm makes the system states asymptotically converge to the solution of the problem exponentially fast and the Zeno behaviour is excluded. Finally, simulation example is given to illustrate the effectiveness of the proposed algorithm.

Modelling predicts that tolerance to drought during reproductive development will be required for high yield potential and stability of wheat in Europe

NASA Astrophysics Data System (ADS)

Semenov, Mikhail A.; Stratonovitch, Pierre; Paul, Matthew J.

2017-04-01

Short periods of extreme weather, such as a spell of high temperature or drought during a sensitive stage of development, could result in substantial yield losses due to reduction in grain number and grain size. In a modelling study (Stratonovitch & Semenov 2015), heat tolerance around flowering in wheat was identified as a key trait for increased yield potential in Europe under climate change. Ji et all (Ji et al. 2010) demonstrated cultivar specific responses of yield to drought stress around flowering in wheat. They hypothesised that carbohydrate supply to anthers may be the key in maintaining pollen fertility and grain number in wheat. It was shown in (Nuccio et al. 2015) that genetically modified varieties of maize that increase the concentration of sucrose in ear spikelets, performed better under non-drought and drought conditions in field experiments. The objective of this modelling study was to assess potential benefits of tolerance to drought during reproductive development for wheat yield potential and yield stability across Europe. We used the Sirius wheat model to optimise wheat ideotypes for 2050 (HadGEM2, RCP8.5) climate scenarios at selected European sites. Eight cultivar parameters were optimised to maximise mean yields, including parameters controlling phenology, canopy growth and water limitation. At those sites where water could be limited, ideotypes sensitive to drought produced substantially lower mean yields and higher yield variability compare with tolerant ideotypes. Therefore, tolerance to drought during reproductive development is likely to be required for wheat cultivars optimised for the future climate in Europe in order to achieve high yield potential and yield stability.

Optimization of microwave-assisted extraction of polyphenols from Myrtus communis L. leaves.

PubMed

Dahmoune, Farid; Nayak, Balunkeswar; Moussi, Kamal; Remini, Hocine; Madani, Khodir

2015-01-01

Phytochemicals, such as phenolic compounds, are of great interest due to their health-benefitting antioxidant properties and possible protection against inflammation, cardiovascular diseases and certain types of cancer. Maximum retention of these phytochemicals during extraction requires optimised process parameter conditions. A microwave-assisted extraction (MAE) method was investigated for extraction of total phenolics from Myrtus communis leaves. The total phenolic capacity (TPC) of leaf extracts at optimised MAE conditions was compared with ultrasound-assisted extraction (UAE) and conventional solvent extraction (CSE). The influence of extraction parameters including ethanol concentration, microwave power, irradiation time and solvent-to-solid ratio on the extraction of TPC was modeled by using a second-order regression equation. The optimal MAE conditions were 42% ethanol concentration, 500 W microwave power, 62 s irradiation time and 32 mL/g solvent to material ratio. Ethanol concentration and liquid-to-solid ratio were the significant parameters for the extraction process (p<0.01). Under the MAE optimised conditions, the recovery of TPC was 162.49 ± 16.95 mg gallic acidequivalent/gdry weight(DW), approximating the predicted content (166.13 mg GAE/g DW). When bioactive phytochemicals extracted from Myrtus leaves using MAE compared with UAE and CSE, it was also observed that tannins (32.65 ± 0.01 mg/g), total flavonoids (5.02 ± 0.05 mg QE/g) and antioxidant activities (38.20 ± 1.08 μg GAE/mL) in MAE extracts were higher than the other two extracts. These findings further illustrate that extraction of bioactive phytochemicals from plant materials using MAE method consumes less extraction solvent and saves time. Copyright © 2014 Elsevier Ltd. All rights reserved.

Optimisation and Characterisation of Lipase-Catalysed Synthesis of a Kojic Monooleate Ester in a Solvent-Free System by Response Surface Methodology.

PubMed

Jumbri, Khairulazhar; Al-Haniff Rozy, Mohd Fahruddin; Ashari, Siti Efliza; Mohamad, Rosfarizan; Basri, Mahiran; Fard Masoumi, Hamid Reza

2015-01-01

Kojic acid is widely used to inhibit the browning effect of tyrosinase in cosmetic and food industries. In this work, synthesis of kojic monooleate ester (KMO) was carried out using lipase-catalysed esterification of kojic acid and oleic acid in a solvent-free system. Response Surface Methodology (RSM) based on central composite rotatable design (CCRD) was used to optimise the main important reaction variables, such as enzyme amount, reaction temperature, substrate molar ratio, and reaction time along with immobilised lipase from Candida Antarctica (Novozym 435) as a biocatalyst. The RSM data indicated that the reaction temperature was less significant in comparison to other factors for the production of a KMO ester. By using this statistical analysis, a quadratic model was developed in order to correlate the preparation variable to the response (reaction yield). The optimum conditions for the enzymatic synthesis of KMO were as follows: an enzyme amount of 2.0 wt%, reaction temperature of 83.69°C, substrate molar ratio of 1:2.37 (mmole kojic acid:oleic acid) and a reaction time of 300.0 min. Under these conditions, the actual yield percentage obtained was 42.09%, which is comparably well with the maximum predicted value of 44.46%. Under the optimal conditions, Novozym 435 could be reused for 5 cycles for KMO production percentage yield of at least 40%. The results demonstrated that statistical analysis using RSM can be used efficiently to optimise the production of a KMO ester. Moreover, the optimum conditions obtained can be applied to scale-up the process and minimise the cost.

Optimisation and Characterisation of Lipase-Catalysed Synthesis of a Kojic Monooleate Ester in a Solvent-Free System by Response Surface Methodology

PubMed Central

Jumbri, Khairulazhar; Al-Haniff Rozy, Mohd Fahruddin; Ashari, Siti Efliza; Mohamad, Rosfarizan; Basri, Mahiran; Fard Masoumi, Hamid Reza

2015-01-01

Kojic acid is widely used to inhibit the browning effect of tyrosinase in cosmetic and food industries. In this work, synthesis of kojic monooleate ester (KMO) was carried out using lipase-catalysed esterification of kojic acid and oleic acid in a solvent-free system. Response Surface Methodology (RSM) based on central composite rotatable design (CCRD) was used to optimise the main important reaction variables, such as enzyme amount, reaction temperature, substrate molar ratio, and reaction time along with immobilised lipase from Candida Antarctica (Novozym 435) as a biocatalyst. The RSM data indicated that the reaction temperature was less significant in comparison to other factors for the production of a KMO ester. By using this statistical analysis, a quadratic model was developed in order to correlate the preparation variable to the response (reaction yield). The optimum conditions for the enzymatic synthesis of KMO were as follows: an enzyme amount of 2.0 wt%, reaction temperature of 83.69°C, substrate molar ratio of 1:2.37 (mmole kojic acid:oleic acid) and a reaction time of 300.0 min. Under these conditions, the actual yield percentage obtained was 42.09%, which is comparably well with the maximum predicted value of 44.46%. Under the optimal conditions, Novozym 435 could be reused for 5 cycles for KMO production percentage yield of at least 40%. The results demonstrated that statistical analysis using RSM can be used efficiently to optimise the production of a KMO ester. Moreover, the optimum conditions obtained can be applied to scale-up the process and minimise the cost. PMID:26657030

Material model of pelvic bone based on modal analysis: a study on the composite bone.

PubMed

Henyš, Petr; Čapek, Lukáš

2017-02-01

Digital models based on finite element (FE) analysis are widely used in orthopaedics to predict the stress or strain in the bone due to bone-implant interaction. The usability of the model depends strongly on the bone material description. The material model that is most commonly used is based on a constant Young's modulus or on the apparent density of bone obtained from computer tomography (CT) data. The Young's modulus of bone is described in many experimental works with large variations in the results. The concept of measuring and validating the material model of the pelvic bone based on modal analysis is introduced in this pilot study. The modal frequencies, damping, and shapes of the composite bone were measured precisely by an impact hammer at 239 points. An FE model was built using the data pertaining to the geometry and apparent density obtained from the CT of the composite bone. The isotropic homogeneous Young's modulus and Poisson's ratio of the cortical and trabecular bone were estimated from the optimisation procedure including Gaussian statistical properties. The performance of the updated model was investigated through the sensitivity analysis of the natural frequencies with respect to the material parameters. The maximal error between the numerical and experimental natural frequencies of the bone reached 1.74 % in the first modal shape. Finally, the optimised parameters were matched with the data sheets of the composite bone. The maximal difference between the calibrated material properties and that obtained from the data sheet was 34 %. The optimisation scheme of the FE model based on the modal analysis data provides extremely useful calibration of the FE models with the uncertainty bounds and without the influence of the boundary conditions.

Analytical formulation of impulsive collision avoidance dynamics

NASA Astrophysics Data System (ADS)

Bombardelli, Claudio

2014-02-01

The paper deals with the problem of impulsive collision avoidance between two colliding objects in three dimensions and assuming elliptical Keplerian orbits. Closed-form analytical expressions are provided that accurately predict the relative dynamics of the two bodies in the encounter b-plane following an impulsive delta-V manoeuvre performed by one object at a given orbit location prior to the impact and with a generic three-dimensional orientation. After verifying the accuracy of the analytical expressions for different orbital eccentricities and encounter geometries the manoeuvre direction that maximises the miss distance is obtained numerically as a function of the arc length separation between the manoeuvre point and the predicted collision point. The provided formulas can be used for high-accuracy instantaneous estimation of the outcome of a generic impulsive collision avoidance manoeuvre and its optimisation.

Optimising operational amplifiers by evolutionary algorithms and gm/Id method

NASA Astrophysics Data System (ADS)

Tlelo-Cuautle, E.; Sanabria-Borbon, A. C.

2016-10-01

The evolutionary algorithm called non-dominated sorting genetic algorithm (NSGA-II) is applied herein in the optimisation of operational transconductance amplifiers. NSGA-II is accelerated by applying the gm/Id method to estimate reduced search spaces associated to widths (W) and lengths (L) of the metal-oxide-semiconductor field-effect-transistor (MOSFETs), and to guarantee their appropriate bias levels conditions. In addition, we introduce an integer encoding for the W/L sizes of the MOSFETs to avoid a post-processing step for rounding-off their values to be multiples of the integrated circuit fabrication technology. Finally, from the feasible solutions generated by NSGA-II, we introduce a second optimisation stage to guarantee that the final feasible W/L sizes solutions support process, voltage and temperature (PVT) variations. The optimisation results lead us to conclude that the gm/Id method and integer encoding are quite useful to accelerate the convergence of the evolutionary algorithm NSGA-II, while the second optimisation stage guarantees robustness of the feasible solutions to PVT variations.

A Bayesian Approach for Sensor Optimisation in Impact Identification

PubMed Central

Mallardo, Vincenzo; Sharif Khodaei, Zahra; Aliabadi, Ferri M. H.

2016-01-01

This paper presents a Bayesian approach for optimizing the position of sensors aimed at impact identification in composite structures under operational conditions. The uncertainty in the sensor data has been represented by statistical distributions of the recorded signals. An optimisation strategy based on the genetic algorithm is proposed to find the best sensor combination aimed at locating impacts on composite structures. A Bayesian-based objective function is adopted in the optimisation procedure as an indicator of the performance of meta-models developed for different sensor combinations to locate various impact events. To represent a real structure under operational load and to increase the reliability of the Structural Health Monitoring (SHM) system, the probability of malfunctioning sensors is included in the optimisation. The reliability and the robustness of the procedure is tested with experimental and numerical examples. Finally, the proposed optimisation algorithm is applied to a composite stiffened panel for both the uniform and non-uniform probability of impact occurrence. PMID:28774064

Optimisation of active suspension control inputs for improved vehicle handling performance

NASA Astrophysics Data System (ADS)

Čorić, Mirko; Deur, Joško; Kasać, Josip; Tseng, H. Eric; Hrovat, Davor

2016-11-01

Active suspension is commonly considered under the framework of vertical vehicle dynamics control aimed at improvements in ride comfort. This paper uses a collocation-type control variable optimisation tool to investigate to which extent the fully active suspension (FAS) application can be broaden to the task of vehicle handling/cornering control. The optimisation approach is firstly applied to solely FAS actuator configurations and three types of double lane-change manoeuvres. The obtained optimisation results are used to gain insights into different control mechanisms that are used by FAS to improve the handling performance in terms of path following error reduction. For the same manoeuvres the FAS performance is compared with the performance of different active steering and active differential actuators. The optimisation study is finally extended to combined FAS and active front- and/or rear-steering configurations to investigate if they can use their complementary control authorities (over the vertical and lateral vehicle dynamics, respectively) to further improve the handling performance.

Structural-electrical coupling optimisation for radiating and scattering performances of active phased array antenna

NASA Astrophysics Data System (ADS)

Wang, Congsi; Wang, Yan; Wang, Zhihai; Wang, Meng; Yuan, Shuai; Wang, Weifeng

2018-04-01

It is well known that calculating and reducing of radar cross section (RCS) of the active phased array antenna (APAA) are both difficult and complicated. It remains unresolved to balance the performance of the radiating and scattering when the RCS is reduced. Therefore, this paper develops a structure and scattering array factor coupling model of APAA based on the phase errors of radiated elements generated by structural distortion and installation error of the array. To obtain the optimal radiating and scattering performance, an integrated optimisation model is built to optimise the installation height of all the radiated elements in normal direction of the array, in which the particle swarm optimisation method is adopted and the gain loss and scattering array factor are selected as the fitness function. The simulation indicates that the proposed coupling model and integrated optimisation method can effectively decrease the RCS and that the necessary radiating performance can be simultaneously guaranteed, which demonstrate an important application value in engineering design and structural evaluation of APAA.

DryLab® optimised two-dimensional high performance liquid chromatography for differentiation of ephedrine and pseudoephedrine based methamphetamine samples.

PubMed

Andrighetto, Luke M; Stevenson, Paul G; Pearson, James R; Henderson, Luke C; Conlan, Xavier A

2014-11-01

In-silico optimised two-dimensional high performance liquid chromatographic (2D-HPLC) separations of a model methamphetamine seizure sample are described, where an excellent match between simulated and real separations was observed. Targeted separation of model compounds was completed with significantly reduced method development time. This separation was completed in the heart-cutting mode of 2D-HPLC where C18 columns were used in both dimensions taking advantage of the selectivity difference of methanol and acetonitrile as the mobile phases. This method development protocol is most significant when optimising the separation of chemically similar chemical compounds as it eliminates potentially hours of trial and error injections to identify the optimised experimental conditions. After only four screening injections the gradient profile for both 2D-HPLC dimensions could be optimised via simulations, ensuring the baseline resolution of diastereomers (ephedrine and pseudoephedrine) in 9.7 min. Depending on which diastereomer is present the potential synthetic pathway can be categorized.

Comprehensive ecosystem model-experiment synthesis using multiple datasets at two temperate forest free-air CO2 enrichment experiments: model performance and compensating biases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walker, Anthony P; Hanson, Paul J; DeKauwe, Martin G

2014-01-01

Free Air CO2 Enrichment (FACE) experiments provide a remarkable wealth of data to test the sensitivities of terrestrial ecosystem models (TEMs). In this study, a broad set of 11 TEMs were compared to 22 years of data from two contrasting FACE experiments in temperate forests of the south eastern US the evergreen Duke Forest and the deciduous Oak Ridge forest. We evaluated the models' ability to reproduce observed net primary productivity (NPP), transpiration and Leaf Area index (LAI) in ambient CO2 treatments. Encouragingly, many models simulated annual NPP and transpiration within observed uncertainty. Daily transpiration model errors were often relatedmore » to errors in leaf area phenology and peak LAI. Our analysis demonstrates that the simulation of LAI often drives the simulation of transpiration and hence there is a need to adopt the most appropriate of hypothesis driven methods to simulate and predict LAI. Of the three competing hypotheses determining peak LAI (1) optimisation to maximise carbon export, (2) increasing SLA with canopy depth and (3) the pipe model the pipe model produced LAI closest to the observations. Modelled phenology was either prescribed or based on broader empirical calibrations to climate. In some cases, simulation accuracy was achieved through compensating biases in component variables. For example, NPP accuracy was sometimes achieved with counter-balancing biases in nitrogen use efficiency and nitrogen uptake. Combined analysis of parallel measurements aides the identification of offsetting biases; without which over-confidence in model abilities to predict ecosystem function may emerge, potentially leading to erroneous predictions of change under future climates.« less

Proof of concept: performance testing in models.

PubMed

Craig, W A

2004-04-01

Pharmacokinetic (PK) and pharmacodynamic (PD) principles that predict antimicrobial efficacy can be used to set targets for antimicrobial design and optimisation. Although current formulations of amoxicillin and amoxicillin/clavulanate have retained their efficacy against many, but not all, penicillin-nonsusceptible Streptococcus pneumoniae, additional coverage is required to address the growing problem of drug-resistant strains. Accordingly, two new oral formulations of amoxicillin/clavulanate, a paediatric formulation at 90/6.4 mg/kg/day and a pharmacokinetically enhanced formulation at 2000/125 mg twice daily for adults, were designed using PK/PD principles. These principles indicate that for amoxicillin and amoxicillin/clavulanate, a time above MIC of 35-40% of the dosing interval is predictive of high bacterial efficacy. In line with PK/PD predictions, simulation of human pharmacokinetics in in-vitro kinetic models and in a rat model of pneumonia, amoxicillin/clavulanate 2000/125 mg twice daily was highly effective against S. pneumoniae strains with amoxicillin MICs of 4 or 8 mg/L. Against strains with amoxicillin MICs of 4 mg/L, amoxicillin/clavulanate 2000/125 mg twice daily was significantly more effective than the conventional 875/125 mg twice daily formulation, azithromycin and levofloxacin, even though all levofloxacin MICs were < or = 1 mg/L. Following infection with S. pneumoniae strains with amoxicillin MICs of 8 mg/L, the amoxicillin/clavulanate 2000/125 mg twice daily formulation was more effective than the conventional amoxicillin/clavulanate formulations of 875/125 mg twice daily and three times daily and 1000/125 mg three times daily, and had similar or better efficacy than azithromycin and levofloxacin, depending on the strain. These data indicate the potential benefit of therapy with amoxicillin/clavulanate 2000/125 mg twice daily compared with conventional formulations and other marketed antimicrobials in the treatment of respiratory tract infection.

Shape Optimisation of Holes in Loaded Plates by Minimisation of Multiple Stress Peaks

DTIC Science & Technology

2015-04-01

UNCLASSIFIED UNCLASSIFIED Shape Optimisation of Holes in Loaded Plates by Minimisation of Multiple Stress Peaks Witold Waldman and Manfred...minimising the peak tangential stresses on multiple segments around the boundary of a hole in a uniaxially-loaded or biaxially-loaded plate . It is based...RELEASE UNCLASSIFIED UNCLASSIFIED Shape Optimisation of Holes in Loaded Plates by Minimisation of Multiple Stress Peaks Executive Summary Aerospace

Navigating catastrophes: Local but not global optimisation allows for macro-economic navigation of crises

NASA Astrophysics Data System (ADS)

Harré, Michael S.

2013-02-01

Two aspects of modern economic theory have dominated the recent discussion on the state of the global economy: Crashes in financial markets and whether or not traditional notions of economic equilibrium have any validity. We have all seen the consequences of market crashes: plummeting share prices, businesses collapsing and considerable uncertainty throughout the global economy. This seems contrary to what might be expected of a system in equilibrium where growth dominates the relatively minor fluctuations in prices. Recent work from within economics as well as by physicists, psychologists and computational scientists has significantly improved our understanding of the more complex aspects of these systems. With this interdisciplinary approach in mind, a behavioural economics model of local optimisation is introduced and three general properties are proven. The first is that under very specific conditions local optimisation leads to a conventional macro-economic notion of a global equilibrium. The second is that if both global optimisation and economic growth are required then under very mild assumptions market catastrophes are an unavoidable consequence. Third, if only local optimisation and economic growth are required then there is sufficient parametric freedom for macro-economic policy makers to steer an economy around catastrophes without overtly disrupting local optimisation.

Optimising the therapeutic ratio of radioimmunotherapy; an investigation of the roles of chimerisation, fractionation and radiation dosimetry

NASA Astrophysics Data System (ADS)

Violet, John Albert

2007-12-01

Radioimmunotherapy (RIT) is a targeted form of treatment for cancer which uses tumour-associated antibodies to selectively deliver a therapeutic radionuclide to sites of disease. In lymphoma, radioimmunotherapy has proved a remarkably effective agent due to the high radiosensitivity of the tumour and its propensity to undergo apoptosis following irradiation. However, success in the treatment of the more radioresistant common solid tumours has been less successful, and for these patients RIT remains investigative. The effectiveness of RIT is limited by non-specific irradiation of normal tissues whilst antibody remains in the circulation, in particular bone marrow, and also by immunogenicity of antibody which does not allow for repeated therapy. In the first chapter I have hypothesised that lymphomas expressing the interleukin-2 receptor might be effectively treated using a radiolabeled antibody to this receptor. In a phase I/II clinical study, 131I labelled CHT-25, a chimeric antibody against the IL-2Ra chain, has shown encouraging evidence of efficacy in the 9 patients with multiply- relapsed lymphomas treated so far. In addition, use of this antibody has been associated with low immunogenicity allowing for repeated therapies to be given. In the second chapter I have hypothesised that dosimetry led, individual patient therapy, might further optimise 1311 CHT-25 treatment. To investigate this I have used marrow toxicity as a biological assay of absorbed dose and shown that simple, but individual, patient biodistribution indices correlate better with observed toxicity than the population-based dose estimates currently employed. I have proposed that adoption of individual patient dosimetry using tracer studies is worthy of further investigation for the future development of 131I- CHT-25. In the third chapter I have hypothesised that dose fractionation might improve the therapeutic ratio of RIT. This has been investigated in a pre-clinical human colorectal xenograft model in nude mice using 131I-A5B7, a murine antibody against CEA. In this setting fractionation neither reduces normal tissue toxicity nor increases the effectiveness of therapy. This thesis demonstrates, using both pre-clinical and clinical data, how the therapeutic ratio of RIT might be improved through antibody design, leading to reduced immunogenicity, dose fractionation and radiation dosimetry, and proposes how these approaches might be used to optimise the effectiveness of RIT in the clinic.

Numerical Modelling of Effects of Biphasic Layers of Corrosion Products to the Degradation of Magnesium Metal In Vitro

PubMed Central

Ahmed, Safia K.; Ward, John P.; Liu, Yang

2017-01-01

Magnesium (Mg) is becoming increasingly popular for orthopaedic implant materials. Its mechanical properties are closer to bone than other implant materials, allowing for more natural healing under stresses experienced during recovery. Being biodegradable, it also eliminates the requirement of further surgery to remove the hardware. However, Mg rapidly corrodes in clinically relevant aqueous environments, compromising its use. This problem can be addressed by alloying the Mg, but challenges remain at optimising the properties of the material for clinical use. In this paper, we present a mathematical model to provide a systematic means of quantitatively predicting Mg corrosion in aqueous environments, providing a means of informing standardisation of in vitro investigation of Mg alloy corrosion to determine implant design parameters. The model describes corrosion through reactions with water, to produce magnesium hydroxide Mg(OH)2, and subsequently with carbon dioxide to form magnesium carbonate MgCO3. The corrosion products produce distinct protective layers around the magnesium block that are modelled as porous media. The resulting model of advection–diffusion equations with multiple moving boundaries was solved numerically using asymptotic expansions to deal with singular cases. The model has few free parameters, and it is shown that these can be tuned to predict a full range of corrosion rates, reflecting differences between pure magnesium or magnesium alloys. Data from practicable in vitro experiments can be used to calibrate the model’s free parameters, from which model simulations using in vivo relevant geometries provide a cheap first step in optimising Mg-based implant materials. PMID:29267244

Crohn's disease in adolescence: presentation and treatment.

PubMed

Cullen, Mick; Barnes, Claire

2015-05-13

Crohn's disease is a chronic inflammatory bowel condition that affects more than 115,000 people in the UK. This article focuses on Crohn's disease in adolescents. Management of the condition in this group should address adolescent-specific characteristics and treatment goals. Key elements include optimising growth, pubertal development and social functioning, including education. The condition can affect an individual's mental and emotional wellbeing significantly, as well as their physical health. As adolescence is a time of great change, the additional burden of a chronic illness can prove difficult to manage. The authors provide information on the presentation of Crohn's disease in adolescence and insights into the particular issues encountered by this group.

Comparison of the genetic algorithm and incremental optimisation routines for a Bayesian inverse modelling based network design

NASA Astrophysics Data System (ADS)

Nickless, A.; Rayner, P. J.; Erni, B.; Scholes, R. J.

2018-05-01

The design of an optimal network of atmospheric monitoring stations for the observation of carbon dioxide (CO2) concentrations can be obtained by applying an optimisation algorithm to a cost function based on minimising posterior uncertainty in the CO2 fluxes obtained from a Bayesian inverse modelling solution. Two candidate optimisation methods assessed were the evolutionary algorithm: the genetic algorithm (GA), and the deterministic algorithm: the incremental optimisation (IO) routine. This paper assessed the ability of the IO routine in comparison to the more computationally demanding GA routine to optimise the placement of a five-member network of CO2 monitoring sites located in South Africa. The comparison considered the reduction in uncertainty of the overall flux estimate, the spatial similarity of solutions, and computational requirements. Although the IO routine failed to find the solution with the global maximum uncertainty reduction, the resulting solution had only fractionally lower uncertainty reduction compared with the GA, and at only a quarter of the computational resources used by the lowest specified GA algorithm. The GA solution set showed more inconsistency if the number of iterations or population size was small, and more so for a complex prior flux covariance matrix. If the GA completed with a sub-optimal solution, these solutions were similar in fitness to the best available solution. Two additional scenarios were considered, with the objective of creating circumstances where the GA may outperform the IO. The first scenario considered an established network, where the optimisation was required to add an additional five stations to an existing five-member network. In the second scenario the optimisation was based only on the uncertainty reduction within a subregion of the domain. The GA was able to find a better solution than the IO under both scenarios, but with only a marginal improvement in the uncertainty reduction. These results suggest that the best use of resources for the network design problem would be spent in improvement of the prior estimates of the flux uncertainties rather than investing these resources in running a complex evolutionary optimisation algorithm. The authors recommend that, if time and computational resources allow, that multiple optimisation techniques should be used as a part of a comprehensive suite of sensitivity tests when performing such an optimisation exercise. This will provide a selection of best solutions which could be ranked based on their utility and practicality.

Fabrication of anti-adhesion surfaces on aluminium substrates of rubber plastic moulds using electrolysis plasma treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meng, Jianbing, E-mail: jianbingmeng@126.com; Dong, Xiaojuan; Wei, Xiuting

An anti-adhesion surface with a water contact angle of 167° was fabricated on aluminium samples of rubber plastic moulds by electrolysis plasma treatment using mixed electrolytes of C{sub 6}H{sub 5}O{sub 7}(NH{sub 4}){sub 3} and Na{sub 2}SO{sub 4}, followed by fluorination. To optimise the fabrication conditions, several important processing parameters such as the discharge voltage, discharge time, concentrations of supporting electrolyte and stearic acid ethanol solution were examined systematically. Using scanning electron microscopy (SEM) to analyse surfaces morphology, micrometer scale pits, and protrusions were found on the surface, with numerous nanometer mastoids contained in the protrusions. These binary micro/nano-scale structures, whichmore » are similar to the micro-structures of soil-burrowing animals, play a critical role in achieving low adhesion properties. Otherwise, the anti-adhesion behaviours of the resulting samples were analysed by the atomic force microscope (AFM), Fourier-transform infrared spectrophotometer (FTIR), electrons probe micro-analyzer (EPMA), optical contact angle meter, digital Vickers microhardness (Hv) tester, and electronic universal testing. The results show that the electrolysis plasma treatment does not require complex processing parameters, using a simple device, and is an environment-friendly and effective method. Under the optimised conditions, the contact angle (CA) for the modified anti-adhesion surface is up to 167°, the sliding angle (SA) is less than 2°, roughness of the sample surface is only 0.409μm. Moreover, the adhesion force and H{sub v} are 0. 9KN and 385, respectively.« less

First in situ evidence of wakes in the far field behind offshore wind farms.

PubMed

Platis, Andreas; Siedersleben, Simon K; Bange, Jens; Lampert, Astrid; Bärfuss, Konrad; Hankers, Rudolf; Cañadillas, Beatriz; Foreman, Richard; Schulz-Stellenfleth, Johannes; Djath, Bughsin; Neumann, Thomas; Emeis, Stefan

2018-02-01

More than 12 GW of offshore wind turbines are currently in operation in European waters. To optimise the use of the marine areas, wind farms are typically clustered in units of several hundred turbines. Understanding wakes of wind farms, which is the region of momentum and energy deficit downwind, is important for optimising the wind farm layouts and operation to minimize costs. While in most weather situations (unstable atmospheric stratification), the wakes of wind turbines are only a local effect within the wind farm, satellite imagery reveals wind-farm wakes to be several tens of kilometres in length under certain conditions (stable atmospheric stratification), which is also predicted by numerical models. The first direct in situ measurements of the existence and shape of large wind farm wakes by a specially equipped research aircraft in 2016 and 2017 confirm wake lengths of more than tens of kilometres under stable atmospheric conditions, with maximum wind speed deficits of 40%, and enhanced turbulence. These measurements were the first step in a large research project to describe and understand the physics of large offshore wakes using direct measurements, together with the assessment of satellite imagery and models.

Vibration isolation design for periodically stiffened shells by the wave finite element method

NASA Astrophysics Data System (ADS)

Hong, Jie; He, Xueqing; Zhang, Dayi; Zhang, Bing; Ma, Yanhong

2018-04-01

Periodically stiffened shell structures are widely used due to their excellent specific strength, in particular for aeronautical and astronautical components. This paper presents an improved Wave Finite Element Method (FEM) that can be employed to predict the band-gap characteristics of stiffened shell structures efficiently. An aero-engine casing, which is a typical periodically stiffened shell structure, was employed to verify the validation and efficiency of the Wave FEM. Good agreement has been found between the Wave FEM and the classical FEM for different boundary conditions. One effective wave selection method based on the Wave FEM has thus been put forward to filter the radial modes of a shell structure. Furthermore, an optimisation strategy by the combination of the Wave FEM and genetic algorithm was presented for periodically stiffened shell structures. The optimal out-of-plane band gap and the mass of the whole structure can be achieved by the optimisation strategy under an aerodynamic load. Results also indicate that geometric parameters of stiffeners can be properly selected that the out-of-plane vibration attenuates significantly in the frequency band of interest. This study can provide valuable references for designing the band gaps of vibration isolation.

Optimisation of Microwave-Assisted Extraction of Pomegranate (Punica granatum L.) Seed Oil and Evaluation 
of Its Physicochemical and Bioactive Properties.

PubMed

Çavdar, Hasene Keskin; Yanık, Derya Koçak; Gök, Uğur; Göğüş, Fahrettin

2017-03-01

Pomegranate seed oil was extracted in a closed-vessel high-pressure microwave system. The characteristics of the obtained oil, such as fatty acid composition, free fatty acidity, total phenolic content, antioxidant activity and colour, were compared to those of the oil obtained by cold solvent extraction. Response surface methodology was applied to optimise extraction conditions: power (176-300 W), time (5-20 min), particle size ( d =0.125-0.800 mm) and solvent to sample ratio (2:1, 6:1 and 10:1, by mass). The predicted highest extraction yield (35.19%) was obtained using microwave power of 220 W, particle size in the range of d =0.125-0.450 mm and solvent-to-sample ratio of 10:1 (by mass) in 5 min extraction time. Microwave-assisted solvent extraction (MASE) resulted in higher extraction yield than that of Soxhlet (34.70% in 8 h) or cold (17.50% in 8 h) extraction. The dominant fatty acid of pomegranate seed oil was punicic acid (86%) irrespective of the extraction method. Oil obtained by MASE had better physicochemical properties, total phenolic content and antioxidant activity than the oil obtained by cold solvent extraction.

Stability and optimised H∞ control of tripped and untripped vehicle rollover

NASA Astrophysics Data System (ADS)

Jin, Zhilin; Zhang, Lei; Zhang, Jiale; Khajepour, Amir

2016-10-01

Vehicle rollover is a serious traffic accident. In order to accurately evaluate the possibility of untripped and some special tripped vehicle rollovers, and to prevent vehicle rollover under unpredictable variations of parameters and harsh driving conditions, a new rollover index and an anti-roll control strategy are proposed in this paper. Taking deflections of steering and suspension induced by the roll at the axles into consideration, a six degrees of freedom dynamic model is established, including lateral, yaw, roll, and vertical motions of sprung and unsprung masses. From the vehicle dynamics theory, a new rollover index is developed to predict vehicle rollover risk under both untripped and special tripped situations. This new rollover index is validated by Carsim simulations. In addition, an H-infinity controller with electro hydraulic brake system is optimised by genetic algorithm to improve the anti-rollover performance of the vehicle. The stability and robustness of the active rollover prevention control system are analysed by some numerical simulations. The results show that the control system can improve the critical speed of vehicle rollover obviously, and has a good robustness for variations in the number of passengers and longitude position of the centre of gravity.

Protocol for a national blood transfusion data warehouse from donor to recipient

PubMed Central

van Hoeven, Loan R; Hooftman, Babette H; Janssen, Mart P; de Bruijne, Martine C; de Vooght, Karen M K; Kemper, Peter; Koopman, Maria M W

2016-01-01

Introduction Blood transfusion has health-related, economical and safety implications. In order to optimise the transfusion chain, comprehensive research data are needed. The Dutch Transfusion Data warehouse (DTD) project aims to establish a data warehouse where data from donors and transfusion recipients are linked. This paper describes the design of the data warehouse, challenges and illustrative applications. Study design and methods Quantitative data on blood donors (eg, age, blood group, antibodies) and products (type of product, processing, storage time) are obtained from the national blood bank. These are linked to data on the transfusion recipients (eg, transfusions administered, patient diagnosis, surgical procedures, laboratory parameters), which are extracted from hospital electronic health records. Applications Expected scientific contributions are illustrated for 4 applications: determine risk factors, predict blood use, benchmark blood use and optimise process efficiency. For each application, examples of research questions are given and analyses planned. Conclusions The DTD project aims to build a national, continuously updated transfusion data warehouse. These data have a wide range of applications, on the donor/production side, recipient studies on blood usage and benchmarking and donor–recipient studies, which ultimately can contribute to the efficiency and safety of blood transfusion. PMID:27491665

Optimisation for subcritical fluid extraction of 17-methyltestosterone with 1,1,1,2-tetrafluoroethane for HPLC analysis.

PubMed

Han, Yuqian; Ma, Qinchuan; Lu, Jie; Xue, Yong; Xue, Changhu

2012-12-15

A simple, rapid and sensitive method was developed for determination of 17α-methyltestosterone in aquatic products by extraction with subcritical 1,1,1,2-tetrafluoroethane (R134a) extraction and high performance liquid chromatography (HPLC). Response surface methodology (RSM) was adopted to optimise extraction pressure, temperature and co-solvent volume. The optimum extraction conditions predicted within the experimental ranges were as follows: pressure 5 MPa, temperature 31°C, and co-solvent volume 3.35ml. The analysis was carried out on XDB-C(18) column (4.6 mm × 250 mm, 5 μm) with the mobile phase acetonitrile-water (55:45, v/v), flow rate 0.8 ml/min, temperature 30°C and wavelength 245 nm. Good linearity of detection was obtained for 17α-methyltestosterone between concentrations of 50-250 ng/ml, r(2)=0.999. The method was validated using samples fortified with 17α-methyltestosterone at levels of 10, 30 and 50 ng/g, the mean recovery exceeds 90%, and the RSD values were less than 10%. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

[Shortage of doctors in psychiatric hospitals--providing for the future by reorganizing medical services].

PubMed

Jordan, Wolfgang; Adler, Lothar; Bleich, Stefan; von Einsiedel, Regina; Falkai, Peter; Grosskopf, Volker; Hauth, Iris; Steiner, Johann; Cohrs, Stefan

2011-11-01

Increasing psychiatric disorder treatment need, increased work load, changes in the working hour regulations, the nation-wide shortage of physicians, efficiency principle and economisation can necessitate a reorganisation of medical services. The essential steps and instruments of process optimisation in medical services for a psychiatric clinic are elucidated and discussed in the context of demographic changes, generation change, and a new concept of values. © Georg Thieme Verlag KG Stuttgart · New York.

Optimisation of wire-cut EDM process parameter by Grey-based response surface methodology

NASA Astrophysics Data System (ADS)

Kumar, Amit; Soota, Tarun; Kumar, Jitendra

2018-03-01

Wire electric discharge machining (WEDM) is one of the advanced machining processes. Response surface methodology coupled with Grey relation analysis method has been proposed and used to optimise the machining parameters of WEDM. A face centred cubic design is used for conducting experiments on high speed steel (HSS) M2 grade workpiece material. The regression model of significant factors such as pulse-on time, pulse-off time, peak current, and wire feed is considered for optimising the responses variables material removal rate (MRR), surface roughness and Kerf width. The optimal condition of the machining parameter was obtained using the Grey relation grade. ANOVA is applied to determine significance of the input parameters for optimising the Grey relation grade.

[Improving pre- and perioperative hospital care : Major elective surgery].

PubMed

Punt, Ilona M; van der Most, Roel; Bongers, Bart C; Didden, Anouk; Hulzebos, Erik H J; Dronkers, Jaap J; van Meeteren, Nico L U

2017-04-01

Surgery is aimed at improving a patient's health. However, surgery is plagued with a risk of negative consequences, such as perioperative complications and prolonged hospitalization. Also, achieving preoperative levels of physical functionality may be delayed. Above all, the "waiting" period before the operation and the period of hospitalisation endanger the state of health, especially in frail patients.The Better in Better out™ (BiBo™) strategy is aimed at reducing the risk of a complicated postoperative course through the optimisation and professionalisation of perioperative treatment strategies in a physiotherapy activating context. BiBo™ includes four steps towards optimising personalised health care in patients scheduled for elective surgery: 1) preoperative risk assessment, 2) preoperative patient education, 3) preoperative exercise therapy for high-risk patients (prehabilitation) and 4) postoperative mobilisation and functional exercise therapy.Preoperative screening is aimed at identifying frail, high-risk patients at an early stage, and advising these high-risk patients to participate in outpatient exercise training (prehabilitation) as soon as possible. By improving preoperative physical fitness, a patient is able to better withstand the impact of major surgery and this will lead to both a reduced risk of negative side effects and better short-term outcomes as a result. Besides prehabilitation, treatment culture and infrastructure should be inherently changing in such a way that patients stay as active as they can, socially, mentally and physically after discharge.

Use of anti-TNF drug levels to optimise patient management

PubMed Central

Papamichael, Konstantinos; Cheifetz, Adam S

2016-01-01

Anti-tumour necrosis factor (TNF) therapies, such as infliximab, adalimumab, certolizumab pegol and golimumab, have been proven to be effective for the treatment of patients with Crohn's disease and ulcerative colitis. However, 10%–30% of patients with inflammatory bowel disease (IBD) show no initial clinical benefit to anti-TNF therapy (primary non-response), and over 50% after an initial favourable outcome will lose response over time (secondary loss of response (SLR)). Numerous recent studies in IBD have revealed an exposure–response relationship suggesting a positive correlation between high serum anti-TNF concentrations and favourable therapeutic outcomes including clinical, biomarker and endoscopic remission, whereas antidrug antibodies have been associated with SLR and infusion reactions. Currently, therapeutic drug monitoring (TDM) is typically performed when treatment failure occurs either for SLR, drug intolerance (potential immune-mediated reaction) or infusion reaction (reactive TDM). Nevertheless, recent data demonstrate that proactive TDM and a treat-to-target (trough) therapeutic approach may more effectively optimise anti-TNF therapy efficacy, safety and cost. However, implementing TDM in real-life clinical practice is currently limited by the diversity in study design, therapeutic outcomes and assays used, which have hindered the identification of robust clinically relevant concentration thresholds. This review will focus mainly on the pharmacodynamic properties of anti-TNF therapy and the role of TDM in guiding therapeutic decisions in IBD. PMID:28839870

To examine the effectiveness of a hospital-based nurse-led secondary prevention clinic.

PubMed

Mainie, Paula M; Moore, Gillian; Riddell, John W; Adgey, A A Jennifer

2005-12-01

Modification of cardiovascular risk factors can reduce the incidence of myocardial infarction (MI), effectively extend survival, decrease the need for interventional procedures, and improve quality of life in persons with known cardiovascular disease. Pharmacological treatments and important lifestyle changes reduce people's risks substantially (by 1/3 to 2/3) and can slow and perhaps reverse progression of established coronary disease. When used appropriately, these interventions are more cost-effective than many other treatments, currently provided by the National Health Service [Department of Health National Service Frameworks: coronary heart disease. Preventing coronary heart disease in high risk patients. 2000. HMSO.] Secondary prevention clinics are effective means by which to ensure targets are achieved and assist primary care in long-term maintenance of lifestyle change and drug optimisation. A 2-year hospital-based pilot project was established at the Royal Hospitals, April 2001-April 2003. The aim of the project was to target patients with coronary heart disease, post-MI and/or coronary artery bypass grafting and/or percutaneous coronary intervention, 6 months following their cardiac event. The plan was to assess patient risk factors and medication a minimum of 6 months following their cardiac event to ascertain if government targets were being achieved; secondly, to examine the effectiveness of a hospital-based nurse-led secondary prevention clinic on modifying risk factors and optimising drug therapies.

Parent, patient and health professional perspectives regarding enteral nutrition in paediatric oncology.

PubMed

Cohen, Jennifer; Wakefield, Claire E; Tapsell, Linda C; Walton, Karen; Cohn, Richard J

2017-11-01

Enteral tube feeding (ETF) is an important part of treatment for paediatric cancer patients. Without nutritional therapy, the prevalence of under-nutrition during treatment for childhood cancer may be as high as 50%. To ensure that the appropriate initiation of ETF is optimised, information on the views of key stakeholders regarding ETF is needed. In total, 48 interviews were conducted with parents of paediatric cancer patients (n = 20), patients (n = 10) and members of the paediatric oncology health-care team (n = 18). Semistructured interviews were used to elicit information from participants, and the data were analysed using a content analysis approach. The interviews focused on views regarding: (i) attitude toward, and impact of, ETF; (ii) information and support regarding ETF; and (iii) clinical management of ETF. There was agreement between stakeholders on the impact of ETF on patients, both positive (good nutrition, weight gain and decreased anxiety) and negative (physical appearance, invasive insertion procedure and comfort). There were discordant perceptions regarding the timing and type of information provided on the use of ETF, as well as the decision-making process used. By standardising the information given to parents and enhancing understanding of parent, patient and health-care worker perceptions about ETF, the initiation of tube feeding may be optimised. This may positively impact patient outcomes in the future. © 2017 Dietitians Association of Australia.

Optimising the manufacture, formulation, and dose of antiretroviral drugs for more cost-efficient delivery in resource-limited settings: a consensus statement.

PubMed

Crawford, Keith W; Ripin, David H Brown; Levin, Andrew D; Campbell, Jennifer R; Flexner, Charles

2012-07-01

It is expected that funding limitations for worldwide HIV treatment and prevention in resource-limited settings will continue, and, because the need for treatment scale-up is urgent, the emphasis on value for money has become an increasing priority. The Conference on Antiretroviral Drug Optimization--a collaborative project between the Clinton Health Access Initiative, the Johns Hopkins University School of Medicine, and the Bill & Melinda Gates Foundation--brought together process chemists, clinical pharmacologists, pharmaceutical scientists, physicians, pharmacists, and regulatory specialists to explore strategies for the reduction of antiretroviral drug costs. The antiretroviral drugs discussed were prioritised for consideration on the basis of their market impact, and the objectives of the conference were framed as discussion questions generated to guide scientific assessment of potential strategies. These strategies included modifications to the synthesis of the active pharmaceutical ingredient (API) and use of cheaper sources of raw materials in synthesis of these ingredients. Innovations in product formulation could improve bioavailability thus needing less API. For several antiretroviral drugs, studies show efficacy is maintained at doses below the approved dose (eg, efavirenz, lopinavir plus ritonavir, atazanavir, and darunavir). Optimising pharmacoenhancement and extending shelf life are additional strategies. The conference highlighted a range of interventions; optimum cost savings could be achieved through combining approaches. Copyright © 2012 Elsevier Ltd. All rights reserved.

Optimising the combination dosing strategy of abemaciclib and vemurafenib in BRAF-mutated melanoma xenograft tumours

PubMed Central

Tate, Sonya C; Burke, Teresa F; Hartman, Daisy; Kulanthaivel, Palaniappan; Beckmann, Richard P; Cronier, Damien M

2016-01-01

Background: Resistance to BRAF inhibition is a major cause of treatment failure for BRAF-mutated metastatic melanoma patients. Abemaciclib, a cyclin-dependent kinase 4 and 6 inhibitor, overcomes this resistance in xenograft tumours and offers a promising drug combination. The present work aims to characterise the quantitative pharmacology of the abemaciclib/vemurafenib combination using a semimechanistic pharmacokinetic/pharmacodynamic modelling approach and to identify an optimum dosing regimen for potential clinical evaluation. Methods: A PK/biomarker model was developed to connect abemaciclib/vemurafenib concentrations to changes in MAPK and cell cycle pathway biomarkers in A375 BRAF-mutated melanoma xenografts. Resultant tumour growth inhibition was described by relating (i) MAPK pathway inhibition to apoptosis, (ii) mitotic cell density to tumour growth and, under resistant conditions, (iii) retinoblastoma protein inhibition to cell survival. Results: The model successfully described vemurafenib/abemaciclib-mediated changes in MAPK pathway and cell cycle biomarkers. Initial tumour shrinkage by vemurafenib, acquisition of resistance and subsequent abemaciclib-mediated efficacy were successfully captured and externally validated. Model simulations illustrate the benefit of intermittent vemurafenib therapy over continuous treatment, and indicate that continuous abemaciclib in combination with intermittent vemurafenib offers the potential for considerable tumour regression. Conclusions: The quantitative pharmacology of the abemaciclib/vemurafenib combination was successfully characterised and an optimised, clinically-relevant dosing strategy was identified. PMID:26978007

Optimising the utility of pleural fluid adenosine deaminase for the diagnosis of adult tuberculous pleural effusion in Hong Kong.

PubMed

Chang, K C; Chan, M C; Leung, W M; Kong, F Y; Mak, C M; Chen, S Pl; Yu, W C

2018-02-01

Pleural fluid adenosine deaminase level can be applied to rapidly detect tuberculous pleural effusion. We aimed to establish a local diagnostic cut-off value for pleural fluid adenosine deaminase to identify patients with tuberculous pleural effusion, and optimise its utility. We retrospectively reviewed the medical records of consecutive adults with pleural fluid adenosine deaminase level measured by the Diazyme commercial kit (Diazyme Laboratories, San Diego [CA], United States) during 1 January to 31 December 2011 in a cluster of public hospitals in Hong Kong. We considered its level alongside early (within 2 weeks) findings in pleural fluid and pleural biopsy, with and without applying Light's criteria in multiple scenarios. For each scenario, we used the receiver operating characteristic curve to identify a diagnostic cut-off value for pleural fluid adenosine deaminase, and estimated its positive and negative predictive values. A total of 860 medical records were reviewed. Pleural effusion was caused by congestive heart failure, chronic renal failure, or hypoalbuminaemia caused by liver or kidney diseases in 246 (28.6%) patients, malignancy in 198 (23.0%), non-tuberculous infection in 168 (19.5%), tuberculous pleural effusion in 157 (18.3%), and miscellaneous causes in 91 (10.6%). All those with tuberculous pleural effusion had a pleural fluid adenosine deaminase level of ≤100 U/L. When analysis was restricted to 689 patients with pleural fluid adenosine deaminase level of ≤100 U/L and early negative findings for malignancy and non-tuberculous infection in pleural fluid, the positive predictive value was significantly increased and the negative predictive value non-significantly reduced. Using this approach, neither additionally restricting analysis to exudates by Light's criteria nor adding closed pleural biopsy would further enhance predictive values. As such, the diagnostic cut-off value for pleural fluid adenosine deaminase is 26.5 U/L, with a sensitivity of 87.3%, specificity of 93.2%, positive predictive value of 79.2%, negative predictive value of 96.1%, and accuracy of 91.9%. Sex, age, and co-morbidity did not significantly affect prediction of tuberculous pleural effusion using the cut-off value. We have established a diagnostic cut-off level for pleural fluid adenosine deaminase in the diagnosis of tuberculous pleural effusion by restricting analysis to a level of ≤100 U/L, and considering early pleural fluid findings for malignancy and non-tuberculous infection, but not Light's criteria.

2012 European guideline on the diagnosis and treatment of gonorrhoea in adults.

PubMed

Bignell, C; Unemo, M

2013-02-01

Gonorrhoea is a major public health concern globally. Of particularly grave concern is that resistance to the extended-spectrum cephalosporins has emerged during the most recent years. This guideline provides recommendations regarding the diagnosis and treatment of gonorrhoea in Europe. Compared to the outdated 2009 European gonorrhoea guideline, this 2012 European gonorrhoea guideline provides up-to-date guidance on, broader indications for testing and treatment of gonorrhoea;the introduction of dual antimicrobial therapy (ceftriaxone 500 mg and azithromycin 2 g) for uncomplicated gonorrhoea when the antimicrobial sensitivity is unknown; recommendation of test of cure in all gonorrhoea cases to ensure eradication of infection and identify emerging resistance; and recommendations to identify, verify and report failures with recommended treatment regimens. Optimisations of the testing, diagnostics, antimicrobial treatment and follow-up of gonorrhoea patients are crucial in controlling the emergent spread of cephalosporin-resistant and multidrug-resistant gonorrhoea.

[Comparative efficiency of nootropic drugs in complex treatment of patients with remote consequences of closed craniocereberal trauma].

PubMed

Hliebova, O S; Tkachenko, O V

2008-01-01

Main data of the research were data obtained after a complex treatment of 120 persons with late consequences of closed craniocereberal trauma (CCRCT). The treatment included administration of one of nootropic agents (noophen, aminolon or entropil), magnesium sulfate, group B vitamins. All patients have passed a complex examination: specially developed questionnaire, anamnesis gathering, neurologic status, neuropsychological status with the use of multiple-aspect scales and questionnaires, examination of fundus of eye, rheoencephalography, echoencephalography, brain MRT. Results of a complex examination proved positive effect of the use of nootropic agents, in particular noophen, entropil and aminolon in complex treatment of late consequences of closed craniocereberal trauma. For optimisation of the use of nootropic agents in the treatment of late consequences of closed craniocereberal trauma it is recommended to consider features of influence of nootropic agents on certain clinical aspects of the disease.

On the performances of different IMRT Treatment Planning Systems for selected paediatric cases.

PubMed

Fogliata, Antonella; Nicolini, Giorgia; Alber, Markus; Asell, Mats; Clivio, Alessandro; Dobler, Barbara; Larsson, Malin; Lohr, Frank; Lorenz, Friedlieb; Muzik, Jan; Polednik, Martin; Vanetti, Eugenio; Wolff, Dirk; Wyttenbach, Rolf; Cozzi, Luca

2007-02-15

To evaluate the performance of seven different TPS (Treatment Planning Systems: Corvus, Eclipse, Hyperion, KonRad, Oncentra Masterplan, Pinnacle and PrecisePLAN) when intensity modulated (IMRT) plans are designed for paediatric tumours. Datasets (CT images and volumes of interest) of four patients were used to design IMRT plans. The tumour types were: one extraosseous, intrathoracic Ewing Sarcoma; one mediastinal Rhabdomyosarcoma; one metastatic Rhabdomyosarcoma of the anus; one Wilm's tumour of the left kidney with multiple liver metastases. Prescribed doses ranged from 18 to 54.4 Gy. To minimise variability, the same beam geometry and clinical goals were imposed on all systems for every patient. Results were analysed in terms of dose distributions and dose volume histograms. For all patients, IMRT plans lead to acceptable treatments in terms of conformal avoidance since most of the dose objectives for Organs At Risk (OARs) were met, and the Conformity Index (averaged over all TPS and patients) ranged from 1.14 to 1.58 on primary target volumes and from 1.07 to 1.37 on boost volumes. The healthy tissue involvement was measured in terms of several parameters, and the average mean dose ranged from 4.6 to 13.7 Gy. A global scoring method was developed to evaluate plans according to their degree of success in meeting dose objectives (lower scores are better than higher ones). For OARs the range of scores was between 0.75 +/- 0.15 (Eclipse) to 0.92 +/- 0.18 (Pinnacle(3) with physical optimisation). For target volumes, the score ranged from 0.05 +/- 0.05 (Pinnacle(3) with physical optimisation) to 0.16 +/- 0.07 (Corvus). A set of complex paediatric cases presented a variety of individual treatment planning challenges. Despite the large spread of results, inverse planning systems offer promising results for IMRT delivery, hence widening the treatment strategies for this very sensitive class of patients.

On the performances of different IMRT treatment planning systems for selected paediatric cases

PubMed Central

Fogliata, Antonella; Nicolini, Giorgia; Alber, Markus; Åsell, Mats; Clivio, Alessandro; Dobler, Barbara; Larsson, Malin; Lohr, Frank; Lorenz, Friedlieb; Muzik, Jan; Polednik, Martin; Vanetti, Eugenio; Wolff, Dirk; Wyttenbach, Rolf; Cozzi, Luca

2007-01-01

Background To evaluate the performance of seven different TPS (Treatment Planning Systems: Corvus, Eclipse, Hyperion, KonRad, Oncentra Masterplan, Pinnacle and PrecisePLAN) when intensity modulated (IMRT) plans are designed for paediatric tumours. Methods Datasets (CT images and volumes of interest) of four patients were used to design IMRT plans. The tumour types were: one extraosseous, intrathoracic Ewing Sarcoma; one mediastinal Rhabdomyosarcoma; one metastatic Rhabdomyosarcoma of the anus; one Wilm's tumour of the left kidney with multiple liver metastases. Prescribed doses ranged from 18 to 54.4 Gy. To minimise variability, the same beam geometry and clinical goals were imposed on all systems for every patient. Results were analysed in terms of dose distributions and dose volume histograms. Results For all patients, IMRT plans lead to acceptable treatments in terms of conformal avoidance since most of the dose objectives for Organs At Risk (OARs) were met, and the Conformity Index (averaged over all TPS and patients) ranged from 1.14 to 1.58 on primary target volumes and from 1.07 to 1.37 on boost volumes. The healthy tissue involvement was measured in terms of several parameters, and the average mean dose ranged from 4.6 to 13.7 Gy. A global scoring method was developed to evaluate plans according to their degree of success in meeting dose objectives (lower scores are better than higher ones). For OARs the range of scores was between 0.75 ± 0.15 (Eclipse) to 0.92 ± 0.18 (Pinnacle3 with physical optimisation). For target volumes, the score ranged from 0.05 ± 0.05 (Pinnacle3 with physical optimisation) to 0.16 ± 0.07 (Corvus). Conclusion A set of complex paediatric cases presented a variety of individual treatment planning challenges. Despite the large spread of results, inverse planning systems offer promising results for IMRT delivery, hence widening the treatment strategies for this very sensitive class of patients. PMID:17302972

Treatment concept of chronic subdural haematoma according to an algorithm using evidence-based medicine-derived key factors: A prospective controlled study.

PubMed

Weigel, Ralf; Schlickum, Linda; Weisser, Gerald; Krauss, Joachim K

2015-01-01

Surgical treatment for chronic subdural haematoma (CSH) has been analysed by applying evidence-based medicine (EBM) criteria earlier. Whether implementation of EBM-derived key factors into an optimised treatment algorithm would improve outcome, however, needs to be clarified. Symptomatic patients with CSH who fulfilled the inclusion criteria were either assigned to an optimised treatment algorithm (OA-EBM group) or to a control group treated by the standard departmental surgical technique (SDST group) in a prospective design. For the OA-EBM algorithm only one burr hole, extensive intraoperative irrigation and a closed system drainage with meticulous avoidance of entry of air was mandatory. A two-catheter technique was used to reduce intracavital air. Final endpoints were neurological outcome (Markwalder Score), recurrence and the amount of intracranial air. A total of 93 out of 117 patients were evaluated accounting for 113 cases because 20 patients had bilateral haematomas. Demographic data of 68 cases in the SDST group did not differ from 45 cases in the OA-EBM group. The Markwalder Score showed greater improvement in the OA-EBM group (0.5 ± 0.6 vs. 1.0 ± 1.0, p = 0.003). The recurrence rate was 18% (12 patients) in the SDST group versus 2% (1 patient) in the OA-EBM group (p < 0.05). The amount of intracranial air was significantly lower in the OA-EBM group (3.3 ± 5.0 cm(3) vs. 5.2 ± 7.7 cm(3)) with p = 0.04. In the standard group computerised tomography scanning was performed slightly earlier (3 ± 1.7 days vs. 3.6 ± 1.4 days). When comparing only non-recurrent cases in both groups no significant difference was apparent. Implementation of EBM key factors into a treatment algorithm for CSH can improve neurological outcome in a typical neurosurgical department, reduce recurrence and minimise the amount of postoperative air within the haematoma cavity.

Modelling and evaluating municipal solid waste management strategies in a mega-city: the case of Ho Chi Minh City.

PubMed

ThiKimOanh, Le; Bloemhof-Ruwaard, Jacqueline M; van Buuren, Joost Cl; van der Vorst, Jack Gaj; Rulkens, Wim H

2015-04-01

Ho Chi Minh City is a large city that will become a mega-city in the near future. The city struggles with a rapidly increasing flow of municipal solid waste and a foreseeable scarcity of land to continue landfilling, the main treatment of municipal solid waste up to now. Therefore, additional municipal solid waste treatment technologies are needed. The objective of this article is to support decision-making towards more sustainable and cost-effective municipal solid waste strategies in developing countries, in particular Vietnam. A quantitative decision support model is developed to optimise the distribution of municipal solid waste from population areas to treatment plants, the treatment technologies and their capacities for the near future given available infrastructure and cost factors. © The Author(s) 2015.

Systemic solutions for multi-benefit water and environmental management.

PubMed

Everard, Mark; McInnes, Robert

2013-09-01

The environmental and financial costs of inputs to, and unintended consequences arising from narrow consideration of outputs from, water and environmental management technologies highlight the need for low-input solutions that optimise outcomes across multiple ecosystem services. Case studies examining the inputs and outputs associated with several ecosystem-based water and environmental management technologies reveal a range from those that differ little from conventional electro-mechanical engineering techniques through methods, such as integrated constructed wetlands (ICWs), designed explicitly as low-input systems optimising ecosystem service outcomes. All techniques present opportunities for further optimisation of outputs, and hence for greater cumulative public value. We define 'systemic solutions' as "…low-input technologies using natural processes to optimise benefits across the spectrum of ecosystem services and their beneficiaries". They contribute to sustainable development by averting unintended negative impacts and optimising benefits to all ecosystem service beneficiaries, increasing net economic value. Legacy legislation addressing issues in a fragmented way, associated 'ring-fenced' budgets and established management assumptions represent obstacles to implementing 'systemic solutions'. However, flexible implementation of legacy regulations recognising their primary purpose, rather than slavish adherence to detailed sub-clauses, may achieve greater overall public benefit through optimisation of outcomes across ecosystem services. Systemic solutions are not a panacea if applied merely as 'downstream' fixes, but are part of, and a means to accelerate, broader culture change towards more sustainable practice. This necessarily entails connecting a wider network of interests in the formulation and design of mutually-beneficial systemic solutions, including for example spatial planners, engineers, regulators, managers, farming and other businesses, and researchers working on ways to quantify and optimise delivery of ecosystem services. Copyright © 2013 Elsevier B.V. All rights reserved.

Topology optimisation of micro fluidic mixers considering fluid-structure interactions with a coupled Lattice Boltzmann algorithm

NASA Astrophysics Data System (ADS)

Munk, David J.; Kipouros, Timoleon; Vio, Gareth A.; Steven, Grant P.; Parks, Geoffrey T.

2017-11-01

Recently, the study of micro fluidic devices has gained much interest in various fields from biology to engineering. In the constant development cycle, the need to optimise the topology of the interior of these devices, where there are two or more optimality criteria, is always present. In this work, twin physical situations, whereby optimal fluid mixing in the form of vorticity maximisation is accompanied by the requirement that the casing in which the mixing takes place has the best structural performance in terms of the greatest specific stiffness, are considered. In the steady state of mixing this also means that the stresses in the casing are as uniform as possible, thus giving a desired operating life with minimum weight. The ultimate aim of this research is to couple two key disciplines, fluids and structures, into a topology optimisation framework, which shows fast convergence for multidisciplinary optimisation problems. This is achieved by developing a bi-directional evolutionary structural optimisation algorithm that is directly coupled to the Lattice Boltzmann method, used for simulating the flow in the micro fluidic device, for the objectives of minimum compliance and maximum vorticity. The needs for the exploration of larger design spaces and to produce innovative designs make meta-heuristic algorithms, such as genetic algorithms, particle swarms and Tabu Searches, less efficient for this task. The multidisciplinary topology optimisation framework presented in this article is shown to increase the stiffness of the structure from the datum case and produce physically acceptable designs. Furthermore, the topology optimisation method outperforms a Tabu Search algorithm in designing the baffle to maximise the mixing of the two fluids.

Person-centred medicines optimisation policy in England: an agenda for research on polypharmacy.

PubMed

Heaton, Janet; Britten, Nicky; Krska, Janet; Reeve, Joanne

2017-01-01

Aim To examine how patient perspectives and person-centred care values have been represented in documents on medicines optimisation policy in England. There has been growing support in England for a policy of medicines optimisation as a response to the rise of problematic polypharmacy. Conceptually, medicines optimisation differs from the medicines management model of prescribing in being based around the patient rather than processes and systems. This critical examination of current official and independent policy documents questions how central the patient is in them and whether relevant evidence has been utilised in their development. A documentary analysis of reports on medicines optimisation published by the Royal Pharmaceutical Society (RPS), The King's Fund and National Institute for Health and Social Care Excellence since 2013. The analysis draws on a non-systematic review of research on patient experiences of using medicines. Findings The reports varied in their inclusion of patient perspectives and person-centred care values, and in the extent to which they drew on evidence from research on patients' experiences of polypharmacy and medicines use. In the RPS report, medicines optimisation is represented as being a 'step change' from medicines management, in contrast to the other documents which suggest that it is facilitated by the systems and processes that comprise the latter model. Only The King's Fund report considered evidence from qualitative studies of people's use of medicines. However, these studies are not without their limitations. We suggest five ways in which researchers could improve this evidence base and so inform the development of future policy: by facilitating reviews of existing research; conducting studies of patient experiences of polypharmacy and multimorbidity; evaluating medicines optimisation interventions; making better use of relevant theories, concepts and tools; and improving patient and public involvement in research and in guideline development.

Postoperative nomogram to predict cancer-specific survival after radical nephroureterectomy in patients with localised and/or locally advanced upper tract urothelial carcinoma without metastasis.

PubMed

Seisen, Thomas; Colin, Pierre; Hupertan, Vincent; Yates, David R; Xylinas, Evanguelos; Nison, Laurent; Cussenot, Olivier; Neuzillet, Yann; Bensalah, Karim; Novara, Giacomo; Montorsi, Francesco; Zigeuner, Richard; Remzi, Mesut; Shariat, Shahrokh F; Rouprêt, Morgan

2014-11-01

To propose and validate a nomogram to predict cancer-specific survival (CSS) after radical nephroureterectomy (RNU) in patients with pT1-3/N0-x upper tract urothelial carcinoma (UTUC). The international and the French national collaborative groups on UTUC pooled data from 3387 patients treated with RNU. Only 2233 chemotherapy naïve pT1-3/N0-x patients were included in the present study. The population was randomly split into the development cohort (1563) and the external validation cohort (670). To build the nomogram, logistic regressions were used for univariable and multivariable analyses. Different models were generated. The most accurate model was assessed using Harrell's concordance index and decision curve analysis (DCA). Internal validation was then performed by bootstrapping. Finally, the nomogram was calibrated and externally validated in the external dataset. Of the 1563 patients in the nomogram development cohort, 309 (19.7%) died during follow-up from UTUC. The actuarial CSS probability at 5 years was 75.7% (95% confidence interval [CI] 73.2-78.6%). DCA revealed that the use of the best model was associated with benefit gains relative to prediction of CSS. The optimised nomogram included only six variables associated with CSS in multivariable analysis: age (P < 0.001), pT stage (P < 0.001), grade (P < 0.02), location (P < 0.001), architecture (P < 0.001) and lymphovascular invasion (P < 0.001). The accuracy of the nomogram was 0.81 (95% CI, 0.78-0.85). Limitations included the retrospective study design and the lack of a central pathological review. An accurate postoperative nomogram was developed to predict CSS after RNU only in locally and/or locally advanced UTUC without metastasis, where the decision for adjuvant treatment is controversial but crucial for the oncological outcome. © 2014 The Authors. BJU International © 2014 BJU International.

A brief understanding of process optimisation in microwave-assisted extraction of botanical materials: options and opportunities with chemometric tools.

PubMed

Das, Anup Kumar; Mandal, Vivekananda; Mandal, Subhash C

2014-01-01

Extraction forms the very basic step in research on natural products for drug discovery. A poorly optimised and planned extraction methodology can jeopardise the entire mission. To provide a vivid picture of different chemometric tools and planning for process optimisation and method development in extraction of botanical material, with emphasis on microwave-assisted extraction (MAE) of botanical material. A review of studies involving the application of chemometric tools in combination with MAE of botanical materials was undertaken in order to discover what the significant extraction factors were. Optimising a response by fine-tuning those factors, experimental design or statistical design of experiment (DoE), which is a core area of study in chemometrics, was then used for statistical analysis and interpretations. In this review a brief explanation of the different aspects and methodologies related to MAE of botanical materials that were subjected to experimental design, along with some general chemometric tools and the steps involved in the practice of MAE, are presented. A detailed study on various factors and responses involved in the optimisation is also presented. This article will assist in obtaining a better insight into the chemometric strategies of process optimisation and method development, which will in turn improve the decision-making process in selecting influential extraction parameters. Copyright © 2013 John Wiley & Sons, Ltd.

The removal of the trivalent chromium from the leather tannery wastewater: the optimisation of the electro-coagulation process parameters.

PubMed

GilPavas, E; Dobrosz-Gómez, I; Gómez-García, M Á

2011-01-01

The capacity of the electro-coagulation (EC) process for the treatment of the wastewater containing Cr3+, resulting from a leather tannery industry placed in Medellin (Colombia), was evaluated. In order to assess the effect of some parameters, such as: the electrode type (Al and/or Fe), the distance between electrodes, the current density, the stirring velocity, and the initial Cr3+ concentration on its efficiency of removal (%RCr+3), a multifactorial experimental design was used. The %RCr3+ was defined as the response variable for the statistical analysis. In order to optimise the operational values for the chosen parameters, the response surface method (RSM) was applied. Additionally, the Biological Oxygen Demand (BOD5), the Chemical Oxygen Demand (COD), and the Total Organic Carbon (TOC) were monitored during the EC process. The electrodes made of aluminium appeared to be the most effective in the chromium removal from the wastewater under study. At pH equal to 4.52 and at 28°C, the optimal conditions of Cr3+ removal using the EC process were found, as follows: the initial Cr3+ concentration=3,596 mg/L, the electrode gap=0.5 cm, the stirring velocity=382.3 rpm, and the current density=57.87 mA/cm2. At those conditions, it was possible to reach 99.76% of Cr3+ removal, and 64% and 61% of mineralisation (TOC) and COD removal, respectively. A kinetic analysis was performed in order to verify the response capacity of the EC process at optimised parameter values.

Implementation and comparative analysis of the optimisations produced by evolutionary algorithms for the parameter extraction of PSP MOSFET model

NASA Astrophysics Data System (ADS)

Hadia, Sarman K.; Thakker, R. A.; Bhatt, Kirit R.

2016-05-01

The study proposes an application of evolutionary algorithms, specifically an artificial bee colony (ABC), variant ABC and particle swarm optimisation (PSO), to extract the parameters of metal oxide semiconductor field effect transistor (MOSFET) model. These algorithms are applied for the MOSFET parameter extraction problem using a Pennsylvania surface potential model. MOSFET parameter extraction procedures involve reducing the error between measured and modelled data. This study shows that ABC algorithm optimises the parameter values based on intelligent activities of honey bee swarms. Some modifications have also been applied to the basic ABC algorithm. Particle swarm optimisation is a population-based stochastic optimisation method that is based on bird flocking activities. The performances of these algorithms are compared with respect to the quality of the solutions. The simulation results of this study show that the PSO algorithm performs better than the variant ABC and basic ABC algorithm for the parameter extraction of the MOSFET model; also the implementation of the ABC algorithm is shown to be simpler than that of the PSO algorithm.

Reference voltage calculation method based on zero-sequence component optimisation for a regional compensation DVR

NASA Astrophysics Data System (ADS)

Jian, Le; Cao, Wang; Jintao, Yang; Yinge, Wang

2018-04-01

This paper describes the design of a dynamic voltage restorer (DVR) that can simultaneously protect several sensitive loads from voltage sags in a region of an MV distribution network. A novel reference voltage calculation method based on zero-sequence voltage optimisation is proposed for this DVR to optimise cost-effectiveness in compensation of voltage sags with different characteristics in an ungrounded neutral system. Based on a detailed analysis of the characteristics of voltage sags caused by different types of faults and the effect of the wiring mode of the transformer on these characteristics, the optimisation target of the reference voltage calculation is presented with several constraints. The reference voltages under all types of voltage sags are calculated by optimising the zero-sequence component, which can reduce the degree of swell in the phase-to-ground voltage after compensation to the maximum extent and can improve the symmetry degree of the output voltages of the DVR, thereby effectively increasing the compensation ability. The validity and effectiveness of the proposed method are verified by simulation and experimental results.

Optimisation of GaN LEDs and the reduction of efficiency droop using active machine learning

DOE PAGES

Rouet-Leduc, Bertrand; Barros, Kipton Marcos; Lookman, Turab; ...

2016-04-26

A fundamental challenge in the design of LEDs is to maximise electro-luminescence efficiency at high current densities. We simulate GaN-based LED structures that delay the onset of efficiency droop by spreading carrier concentrations evenly across the active region. Statistical analysis and machine learning effectively guide the selection of the next LED structure to be examined based upon its expected efficiency as well as model uncertainty. This active learning strategy rapidly constructs a model that predicts Poisson-Schrödinger simulations of devices, and that simultaneously produces structures with higher simulated efficiencies.

[Systemic Treatment of Metastatic Renal Cell Cancer--Back to the Future?].

PubMed

Ivanyi, P; Grünwald, V

2015-11-01

A variety of therapeutic agents are currently available for the systemic treatment of metastatic renal cell carcinoma (mRCC). It was only when targeted treatment was developed in the past decade that a significant improvement was achieved in tumour therapy. This also led to the development of sequential treatment for mRCC.7 molecular targeted agents are available today (axitinib, bevacizumab/ IFNα, everolimus, pazopanib, sorafenib, sunitinib, and temsirolimus). Due to the individualisation of treatment it remains a challenge to choose the most appropriate drug in a given setting, with the choice being based on the knowledge of the relevant clinical data as well as individual patient parameters.During the recent past, efforts have been made to test different inhibitors or combinations without a major breakthrough. Instead, the development of novel specific immunotherapeutic approaches now heralds the next level of treatment in mRCC. The first significant trial results will be expected this year, and further trials for optimisation of treatment are warranted. © Georg Thieme Verlag KG Stuttgart · New York.

The Lake Victoria Intense Storm Early Warning System (VIEWS)

NASA Astrophysics Data System (ADS)

Thiery, Wim; Gudmundsson, Lukas; Bedka, Kristopher; Semazzi, Fredrick; Lhermitte, Stef; Willems, Patrick; van Lipzig, Nicole; Seneviratne, Sonia I.

2017-04-01

Weather extremes have harmful impacts on communities around Lake Victoria in East Africa. Every year, intense nighttime thunderstorms cause numerous boating accidents on the lake, resulting in thousands of deaths among fishermen. Operational storm warning systems are therefore crucial. Here we complement ongoing early warning efforts based on NWP, by presenting a new satellite data-driven storm prediction system, the prototype Lake Victoria Intense storm Early Warning System (VIEWS). VIEWS derives predictability from the correlation between afternoon land storm activity and nighttime storm intensity on Lake Victoria, and relies on logistic regression techniques to forecast extreme thunderstorms from satellite observations. Evaluation of the statistical model reveals that predictive power is high and independent of the input dataset. We then optimise the configuration and show that also false alarms contain valuable information. Our results suggest that regression-based models that are motivated through process understanding have the potential to reduce the vulnerability of local fishing communities around Lake Victoria. The experimental prediction system is publicly available under the MIT licence at http://github.com/wthiery/VIEWS.

Optimisation of intradermal DNA electrotransfer for immunisation.

PubMed

Vandermeulen, Gaëlle; Staes, Edith; Vanderhaeghen, Marie Lise; Bureau, Michel Francis; Scherman, Daniel; Préat, Véronique

2007-12-04

The development of DNA vaccines requires appropriate delivery technologies. Electrotransfer is one of the most efficient methods of non-viral gene transfer. In the present study, intradermal DNA electrotransfer was first optimised. Strong effects of the injection method and the dose of DNA on luciferase expression were demonstrated. Pre-treatments were evaluated to enhance DNA diffusion in the skin but neither hyaluronidase injection nor iontophoresis improved efficiency of intradermal DNA electrotransfer. Then, DNA immunisation with a weakly immunogenic model antigen, luciferase, was investigated. After intradermal injection of the plasmid encoding luciferase, electrotransfer (HV 700 V/cm 100 micros, LV 200 V/cm 400 ms) was required to induce immune response. The response was Th1-shifted compared to immunisation with the luciferase recombinant protein. Finally, DNA electrotransfer in the skin, the muscle or the ear pinna was compared. Muscle DNA electrotransfer resulted in the highest luciferase expression and the best IgG response. Nevertheless electrotransfer into the skin, the muscle and the ear pinna all resulted in IFN-gamma secretion by luciferase-stimulated splenocytes suggesting that an efficient Th1 response was induced in all case.

Total centralisation and optimisation of an oncology management suite via Citrix®

NASA Astrophysics Data System (ADS)

James, C.; Frantzis, J.; Ripps, L.; Fenton, P.

2014-03-01

The management of patient information and treatment planning is traditionally an intra-departmental requirement of a radiation oncology service. Epworth Radiation Oncology systems must support the transient nature of Visiting Medical Officers (VMOs). This unique work practice created challenges when implementing the vision of a completely paperless solution that allows for a responsive and efficient service delivery. ARIA® and EclipseTM (Varian Medical Systems, Palo Alto, CA, USA) have been deployed across four dedicated Citrix® (Citrix Systems, Santa Clara, CA, USA) servers allowing VMOs to access these applications remotely. A range of paperless solutions were developed within ARIA® to facilitate clinical and organisational management whilst optimising efficient work practices. The IT infrastructure and paperless workflow has enabled VMOs to securely access the VarianTM (Varian Medical Systems, Palo Alto, CA, USA) oncology software and experience full functionality from any location on multiple devices. This has enhanced access to patient information and improved the responsiveness of the service. Epworth HealthCare has developed a unique solution to enable remote access to a centralised oncology management suite, while maintaining a secure and paperless working environment.

Comparison of the phenolic composition of fruit juices by single step gradient HPLC analysis of multiple components versus multiple chromatographic runs optimised for individual families.

PubMed

Bremner, P D; Blacklock, C J; Paganga, G; Mullen, W; Rice-Evans, C A; Crozier, A

2000-06-01

After minimal sample preparation, two different HPLC methodologies, one based on a single gradient reversed-phase HPLC step, the other on multiple HPLC runs each optimised for specific components, were used to investigate the composition of flavonoids and phenolic acids in apple and tomato juices. The principal components in apple juice were identified as chlorogenic acid, phloridzin, caffeic acid and p-coumaric acid. Tomato juice was found to contain chlorogenic acid, caffeic acid, p-coumaric acid, naringenin and rutin. The quantitative estimates of the levels of these compounds, obtained with the two HPLC procedures, were very similar, demonstrating that either method can be used to analyse accurately the phenolic components of apple and tomato juices. Chlorogenic acid in tomato juice was the only component not fully resolved in the single run study and the multiple run analysis prior to enzyme treatment. The single run system of analysis is recommended for the initial investigation of plant phenolics and the multiple run approach for analyses where chromatographic resolution requires improvement.

How to assess vision.

PubMed

Marsden, Janet

2016-09-21

Rationale and key points An objective assessment of the patient's vision is important to assess variation from 'normal' vision in acute and community settings, to establish a baseline before examination and treatment in the emergency department, and to assess any changes during ophthalmic outpatient appointments. » Vision is one of the essential senses that permits people to make sense of the world. » Visual assessment does not only involve measuring central visual acuity, it also involves assessing the consequences of reduced vision. » Assessment of vision in children is crucial to identify issues that might affect vision and visual development, and to optimise lifelong vision. » Untreatable loss of vision is not an inevitable consequence of ageing. » Timely and repeated assessment of vision over life can reduce the incidence of falls, prevent injury and optimise independence. Reflective activity 'How to' articles can help update you practice and ensure it remains evidence based. Apply this article to your practice. Reflect on and write a short account of: 1. How this article might change your practice when assessing people holistically. 2. How you could use this article to educate your colleagues in the assessment of vision.

Advanced data management for optimising the operation of a full-scale WWTP.

PubMed

Beltrán, Sergio; Maiza, Mikel; de la Sota, Alejandro; Villanueva, José María; Ayesa, Eduardo

2012-01-01

The lack of appropriate data management tools is presently a limiting factor for a broader implementation and a more efficient use of sensors and analysers, monitoring systems and process controllers in wastewater treatment plants (WWTPs). This paper presents a technical solution for advanced data management of a full-scale WWTP. The solution is based on an efficient and intelligent use of the plant data by a standard centralisation of the heterogeneous data acquired from different sources, effective data processing to extract adequate information, and a straightforward connection to other emerging tools focused on the operational optimisation of the plant such as advanced monitoring and control or dynamic simulators. A pilot study of the advanced data manager tool was designed and implemented in the Galindo-Bilbao WWTP. The results of the pilot study showed its potential for agile and intelligent plant data management by generating new enriched information combining data from different plant sources, facilitating the connection of operational support systems, and developing automatic plots and trends of simulated results and actual data for plant performance and diagnosis.

Self-adaptive MOEA feature selection for classification of bankruptcy prediction data.

PubMed

Gaspar-Cunha, A; Recio, G; Costa, L; Estébanez, C

2014-01-01

Bankruptcy prediction is a vast area of finance and accounting whose importance lies in the relevance for creditors and investors in evaluating the likelihood of getting into bankrupt. As companies become complex, they develop sophisticated schemes to hide their real situation. In turn, making an estimation of the credit risks associated with counterparts or predicting bankruptcy becomes harder. Evolutionary algorithms have shown to be an excellent tool to deal with complex problems in finances and economics where a large number of irrelevant features are involved. This paper provides a methodology for feature selection in classification of bankruptcy data sets using an evolutionary multiobjective approach that simultaneously minimise the number of features and maximise the classifier quality measure (e.g., accuracy). The proposed methodology makes use of self-adaptation by applying the feature selection algorithm while simultaneously optimising the parameters of the classifier used. The methodology was applied to four different sets of data. The obtained results showed the utility of using the self-adaptation of the classifier.

Efficient embedding of complex networks to hyperbolic space via their Laplacian

PubMed Central

Alanis-Lobato, Gregorio; Mier, Pablo; Andrade-Navarro, Miguel A.

2016-01-01

The different factors involved in the growth process of complex networks imprint valuable information in their observable topologies. How to exploit this information to accurately predict structural network changes is the subject of active research. A recent model of network growth sustains that the emergence of properties common to most complex systems is the result of certain trade-offs between node birth-time and similarity. This model has a geometric interpretation in hyperbolic space, where distances between nodes abstract this optimisation process. Current methods for network hyperbolic embedding search for node coordinates that maximise the likelihood that the network was produced by the afore-mentioned model. Here, a different strategy is followed in the form of the Laplacian-based Network Embedding, a simple yet accurate, efficient and data driven manifold learning approach, which allows for the quick geometric analysis of big networks. Comparisons against existing embedding and prediction techniques highlight its applicability to network evolution and link prediction. PMID:27445157

Reference governors for controlled belt restraint systems

NASA Astrophysics Data System (ADS)

van der Laan, E. P.; Heemels, W. P. M. H.; Luijten, H.; Veldpaus, F. E.; Steinbuch, M.

2010-07-01

Today's restraint systems typically include a number of airbags, and a three-point seat belt with load limiter and pretensioner. For the class of real-time controlled restraint systems, the restraint actuator settings are continuously manipulated during the crash. This paper presents a novel control strategy for these systems. The control strategy developed here is based on a combination of model predictive control and reference management, in which a non-linear device - a reference governor (RG) - is added to a primal closed-loop controlled system. This RG determines an optimal setpoint in terms of injury reduction and constraint satisfaction by solving a constrained optimisation problem. Prediction of the vehicle motion, required to predict future constraint violation, is included in the design and is based on past crash data, using linear regression techniques. Simulation results with MADYMO models show that, with ideal sensors and actuators, a significant reduction (45%) of the peak chest acceleration can be achieved, without prior knowledge of the crash. Furthermore, it is shown that the algorithms are sufficiently fast to be implemented online.

Efficient embedding of complex networks to hyperbolic space via their Laplacian

NASA Astrophysics Data System (ADS)

Alanis-Lobato, Gregorio; Mier, Pablo; Andrade-Navarro, Miguel A.

2016-07-01

The different factors involved in the growth process of complex networks imprint valuable information in their observable topologies. How to exploit this information to accurately predict structural network changes is the subject of active research. A recent model of network growth sustains that the emergence of properties common to most complex systems is the result of certain trade-offs between node birth-time and similarity. This model has a geometric interpretation in hyperbolic space, where distances between nodes abstract this optimisation process. Current methods for network hyperbolic embedding search for node coordinates that maximise the likelihood that the network was produced by the afore-mentioned model. Here, a different strategy is followed in the form of the Laplacian-based Network Embedding, a simple yet accurate, efficient and data driven manifold learning approach, which allows for the quick geometric analysis of big networks. Comparisons against existing embedding and prediction techniques highlight its applicability to network evolution and link prediction.

Application of seepage flow models to a drainage project in fractured rock

NASA Astrophysics Data System (ADS)

Gmünder, Ch.; Arn, Th.

1993-04-01

Various theoretical approaches are used to model groundwater flow in fractured rock. This paper presents the application of several approaches to the restoration of the drainage of Rofla tunnel, Grisons, Switzerland. In this tunnel it became necessary to take measures against the washing out of calcium carbonates from the tunnel lining cement, because the calcium carbonate clogged up the existing drainage tubes leading to increased rock water pressures on the inside arch of the tunnel. Drainage boreholes were drilled on a section of the tunnel and their influence on the water pressures was monitored. On the basis of the geological survey different seepage flow models were established to reproduce the measured water pressures. The models were then used to predict the future water pressures acting on the tunnel lining after restoration. Thus, the efficacy of the different drainage proposals could be predicted and therefore optimised. Finally, the accuracy of the predictions is discussed and illustrated using the measurements in the test section.

Development and Validation of a Weather-Based Model for Predicting Infection of Loquat Fruit by Fusicladium eriobotryae

PubMed Central

González-Domínguez, Elisa; Armengol, Josep; Rossi, Vittorio

2014-01-01

A mechanistic, dynamic model was developed to predict infection of loquat fruit by conidia of Fusicladium eriobotryae, the causal agent of loquat scab. The model simulates scab infection periods and their severity through the sub-processes of spore dispersal, infection, and latency (i.e., the state variables); change from one state to the following one depends on environmental conditions and on processes described by mathematical equations. Equations were developed using published data on F. eriobotryae mycelium growth, conidial germination, infection, and conidial dispersion pattern. The model was then validated by comparing model output with three independent data sets. The model accurately predicts the occurrence and severity of infection periods as well as the progress of loquat scab incidence on fruit (with concordance correlation coefficients >0.95). Model output agreed with expert assessment of the disease severity in seven loquat-growing seasons. Use of the model for scheduling fungicide applications in loquat orchards may help optimise scab management and reduce fungicide applications. PMID:25233340

Self-Adaptive MOEA Feature Selection for Classification of Bankruptcy Prediction Data

PubMed Central

Gaspar-Cunha, A.; Recio, G.; Costa, L.; Estébanez, C.

2014-01-01

Bankruptcy prediction is a vast area of finance and accounting whose importance lies in the relevance for creditors and investors in evaluating the likelihood of getting into bankrupt. As companies become complex, they develop sophisticated schemes to hide their real situation. In turn, making an estimation of the credit risks associated with counterparts or predicting bankruptcy becomes harder. Evolutionary algorithms have shown to be an excellent tool to deal with complex problems in finances and economics where a large number of irrelevant features are involved. This paper provides a methodology for feature selection in classification of bankruptcy data sets using an evolutionary multiobjective approach that simultaneously minimise the number of features and maximise the classifier quality measure (e.g., accuracy). The proposed methodology makes use of self-adaptation by applying the feature selection algorithm while simultaneously optimising the parameters of the classifier used. The methodology was applied to four different sets of data. The obtained results showed the utility of using the self-adaptation of the classifier. PMID:24707201

A Novel approach for predicting monthly water demand by combining singular spectrum analysis with neural networks

NASA Astrophysics Data System (ADS)

Zubaidi, Salah L.; Dooley, Jayne; Alkhaddar, Rafid M.; Abdellatif, Mawada; Al-Bugharbee, Hussein; Ortega-Martorell, Sandra

2018-06-01

Valid and dependable water demand prediction is a major element of the effective and sustainable expansion of municipal water infrastructures. This study provides a novel approach to quantifying water demand through the assessment of climatic factors, using a combination of a pretreatment signal technique, a hybrid particle swarm optimisation algorithm and an artificial neural network (PSO-ANN). The Singular Spectrum Analysis (SSA) technique was adopted to decompose and reconstruct water consumption in relation to six weather variables, to create a seasonal and stochastic time series. The results revealed that SSA is a powerful technique, capable of decomposing the original time series into many independent components including trend, oscillatory behaviours and noise. In addition, the PSO-ANN algorithm was shown to be a reliable prediction model, outperforming the hybrid Backtracking Search Algorithm BSA-ANN in terms of fitness function (RMSE). The findings of this study also support the view that water demand is driven by climatological variables.

Activated sludge pilot plant: comparison between experimental and predicted concentration profiles using three different modelling approaches.

PubMed

Le Moullec, Y; Potier, O; Gentric, C; Leclerc, J P

2011-05-01

This paper presents an experimental and numerical study of an activated sludge channel pilot plant. Concentration profiles of oxygen, COD, NO(3) and NH(4) have been measured for several operating conditions. These profiles have been compared to the simulated ones with three different modelling approaches, namely a systemic approach, CFD and compartmental modelling. For these three approaches, the kinetics model was the ASM-1 model (Henze et al., 2001). The three approaches allowed a reasonable simulation of all the concentration profiles except for ammonium for which the simulations results were far from the experimental ones. The analysis of the results showed that the role of the kinetics model is of primary importance for the prediction of activated sludge reactors performance. The fact that existing kinetics parameters in the literature have been determined by parametric optimisation using a systemic model limits the reliability of the prediction of local concentrations and of the local design of activated sludge reactors. Copyright © 2011 Elsevier Ltd. All rights reserved.

A fuzzy logic approach to control anaerobic digestion.

PubMed

Domnanovich, A M; Strik, D P; Zani, L; Pfeiffer, B; Karlovits, M; Braun, R; Holubar, P

2003-01-01

One of the goals of the EU-Project AMONCO (Advanced Prediction, Monitoring and Controlling of Anaerobic Digestion Process Behaviour towards Biogas Usage in Fuel Cells) is to create a control tool for the anaerobic digestion process, which predicts the volumetric organic loading rate (Bv) for the next day, to obtain a high biogas quality and production. The biogas should contain a high methane concentration (over 50%) and a low concentration of components toxic for fuel cells, e.g. hydrogen sulphide, siloxanes, ammonia and mercaptanes. For producing data to test the control tool, four 20 l anaerobic Continuously Stirred Tank Reactors (CSTR) are operated. For controlling two systems were investigated: a pure fuzzy logic system and a hybrid-system which contains a fuzzy based reactor condition calculation and a hierachial neural net in a cascade of optimisation algorithms.

Collisionless Weibel shocks: Full formation mechanism and timing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bret, A.; Instituto de Investigaciones Energéticas y Aplicaciones Industriales, Campus Universitario de Ciudad Real, 13071 Ciudad Real; Stockem, A.

2014-07-15

Collisionless shocks in plasmas play an important role in space physics (Earth's bow shock) and astrophysics (supernova remnants, relativistic jets, gamma-ray bursts, high energy cosmic rays). While the formation of a fluid shock through the steepening of a large amplitude sound wave has been understood for long, there is currently no detailed picture of the mechanism responsible for the formation of a collisionless shock. We unravel the physical mechanism at work and show that an electromagnetic Weibel shock always forms when two relativistic collisionless, initially unmagnetized, plasma shells encounter. The predicted shock formation time is in good agreement with 2Dmore » and 3D particle-in-cell simulations of counterstreaming pair plasmas. By predicting the shock formation time, experimental setups aiming at producing such shocks can be optimised to favourable conditions.« less

Acute severe asthma presenting in late pregnancy.

PubMed

Holland, S M; Thomson, K D

2006-01-01

Asthma is the commonest pre-existing medical condition to complicate pregnancy. Acute severe asthma in pregnancy is rare, but poses difficult problems. In particular, the decision about when and where to deliver the fetus is complex, since maternal response to asthma treatment is unpredictable. We report the successful management of a parturient presenting with acute severe asthma at 37 weeks' gestation. The controversies involved and the importance of adopting a multi-disciplinary team approach to optimise maternal and neonatal outcomes are discussed.

Management of patients with risk factors

PubMed Central

Waldfahrer, Frank

2013-01-01

This review addresses concomitant diseases and risk factors in patients treated for diseases of the ears, nose and throat in outpatient and hospital services. Besides heart disease, lung disease, liver disease and kidney disease, this article also covers disorders of coagulation (including therapy with new oral anticoagulants) and electrolyte imbalance. Special attention is paid to the prophylaxis, diagnosis and treatment of perioperative delirium. It is also intended to help optimise the preparation for surgical procedures and pharmacotherapy during the hospital stay. PMID:24403970

Is ICRP guidance on the use of reference levels consistent?

PubMed

Hedemann-Jensen, Per; McEwan, Andrew C

2011-12-01

In ICRP 103, which has replaced ICRP 60, it is stated that no fundamental changes have been introduced compared with ICRP 60. This is true except that the application of reference levels in emergency and existing exposure situations seems to be applied inconsistently, and also in the related publications ICRP 109 and ICRP 111. ICRP 103 emphasises that focus should be on the residual doses after the implementation of protection strategies in emergency and existing exposure situations. If possible, the result of an optimised protection strategy should bring the residual dose below the reference level. Thus the reference level represents the maximum acceptable residual dose after an optimised protection strategy has been implemented. It is not an 'off-the-shelf item' that can be set free of the prevailing situation. It should be determined as part of the process of optimising the protection strategy. If not, protection would be sub-optimised. However, in ICRP 103 some inconsistent concepts have been introduced, e.g. in paragraph 279 which states: 'All exposures above or below the reference level should be subject to optimisation of protection, and particular attention should be given to exposures above the reference level'. If, in fact, all exposures above and below reference levels are subject to the process of optimisation, reference levels appear superfluous. It could be considered that if optimisation of protection below a fixed reference level is necessary, then the reference level has been set too high at the outset. Up until the last phase of the preparation of ICRP 103 the concept of a dose constraint was recommended to constrain the optimisation of protection in all types of exposure situations. In the final phase, the term 'dose constraint' was changed to 'reference level' for emergency and existing exposure situations. However, it seems as if in ICRP 103 it was not fully recognised that dose constraints and reference levels are conceptually different. The use of reference levels in radiological protection is reviewed. It is concluded that the recommendations in ICRP 103 and related ICRP publications seem to be inconsistent regarding the use of reference levels in existing and emergency exposure situations.

Use of the 22C3 anti-PD-L1 antibody to determine PD-L1 expression in multiple automated immunohistochemistry platforms.

PubMed

Ilie, Marius; Khambata-Ford, Shirin; Copie-Bergman, Christiane; Huang, Lingkang; Juco, Jonathan; Hofman, Veronique; Hofman, Paul

2017-01-01

For non-small cell lung cancer (NSCLC), treatment with pembrolizumab is limited to patients with tumours expressing PD-L1 assessed by immunohistochemistry (IHC) using the PD-L1 IHC 22C3 pharmDx (Dako, Inc.) companion diagnostic test, on the Dako Autostainer Link 48 (ASL48) platform. Optimised protocols are urgently needed for use of the 22C3 antibody concentrate to test PD-L1 expression on more widely available IHC autostainers. We evaluated PD-L1 expression using the 22C3 antibody concentrate in the three main commercially available autostainers Dako ASL48, BenchMark ULTRA (Ventana Medical Systems, Inc.), and Bond-III (Leica Biosystems) and compared the staining results with the PD-L1 IHC 22C3 pharmDx kit on the Dako ASL48 platform. Several technical conditions for laboratory-developed tests (LDTs) were evaluated in tonsil specimens and a training set of three NSCLC samples. Optimised protocols were then validated in 120 NSCLC specimens. Optimised protocols were obtained on both the VENTANA BenchMark ULTRA and Dako ASL48 platforms. Significant expression of PD-L1 was obtained on tissue controls with the Leica Bond-III autostainer when high concentrations of the 22C3 antibody were used. It therefore was not tested on the 120 NSCLC specimens. An almost 100% concordance rate for dichotomized tumour proportion score (TPS) results was observed between TPS ratings using the 22C3 antibody concentrate on the Dako ASL48 and VENTANA BenchMark ULTRA platforms relative to the PD-L1 IHC 22C3 pharmDx kit on the Dako ASL48 platform. Interpathologist agreement was high on both LDTs and the PD-L1 IHC 22C3 pharmDx kit on the Dako ASL48 platform. Availability of standardized protocols for determining PD-L1 expression using the 22C3 antibody concentrate on the widely available Dako ASL48 and VENTANA BenchMark ULTRA IHC platforms will expand the number of laboratories able to determine eligibility of patients with NSCLC for treatment with pembrolizumab in a reliable and concordant manner.

Technical modification of the Balb/c 3T3 cell transformation assay: the use of serum-reduced medium to optimise the practicability of the protocol.

PubMed

Hayashi, Kumiko; Sasaki, Kiyoshi; Asada, Shin; Tsuchiya, Toshiyuki; Hayashi, Makoto; Yoshimura, Isao; Tanaka, Noriho; Umeda, Makoto

2008-12-01

The two-stage Balb/c 3T3 model of cell transformation can mimic the two-stage carcinogenicity bioassay, and has been recognised as a screening method for detecting potential tumour initiators and promoters. A technical modification to the original protocol (which involved the use of M10F medium, consisting of MEM plus 10% fetal bovine serum [FBS]) has been previously proposed, in order to increase its efficacy, namely: the introduction of enriched, serum-reduced medium (DF2F medium, comprising DMEM/F12 plus 2% FBS and other supplements). The aim of this study was to further modify the protocol, so as to attain higher practicability for the assay. The protocol was further optimised by: a) reducing the number of plates required, through the use of larger plates; b) reducing the cost of the assay by retaining the reduced serum concentration and by using 2microg/ml insulin, rather than the more-complex insulin-transferrin-ethanolamine-sodium selenite (ITES) supplement (i.e. DF2F2I medium); and c) extending the culture period from 24-25 days to 31-32 days, resulting in clearer foci (the number of medium changes did not increase, as less-frequent medium changes were performed during the extended culture period). Growth curve construction revealed that variations in the saturation densities of the parental Balb/c 3T3 cell line and its three transformed clones were highest when M10F medium was replaced with DF2F2I medium just before cells reached confluence. We applied this newly-optimised protocol to the assessment of: a) the tumour initiating activity of 3-methylcholanthrene (MCA), N-methyl-N'-nitro-N-nitrosoguanidine, mitomycin C, methylmethane sulphonate, CdCl(2) and phenacetin, combining a post-treatment of 100ng/ml 12-O-tetradecanoylphorbol-13-acetate at the promotion stage; and b) the tumour promoting activity of insulin, lithocholic acid, CdCl(2) and phenobarbital, with pre-treatment of 0.2microg/ml MCA at the initiation stage. In the present study, only phenobarbital was negative when tested by using the modified protocol. 2008 FRAME.

Discovery and process development of a novel TACE inhibitor for the topical treatment of psoriasis.

PubMed

Boiteau, Jean-Guy; Ouvry, Gilles; Arlabosse, Jean-Marie; Astri, Stéphanie; Beillard, Audrey; Bhurruth-Alcor, Yushma; Bonnary, Laetitia; Bouix-Peter, Claire; Bouquet, Karine; Bourotte, Marilyne; Cardinaud, Isabelle; Comino, Catherine; Deprez, Benoît; Duvert, Denis; Féret, Angélique; Hacini-Rachinel, Feriel; Harris, Craig S; Luzy, Anne-Pascale; Mathieu, Arnaud; Millois, Corinne; Orsini, Nicolas; Pascau, Jonathan; Pinto, Artur; Piwnica, David; Polge, Gaëlle; Reitz, Arnaud; Reversé, Kevin; Rodeville, Nicolas; Rossio, Patricia; Spiesse, Delphine; Tabet, Samuel; Taquet, Nathalie; Tomas, Loïc; Vial, Emmanuel; Hennequin, Laurent F

2018-02-15

Targeting the TNFα pathway is a validated approach to the treatment of psoriasis. In this pathway, TACE stands out as a druggable target and has been the focus of in-house research programs. In this article, we present the discovery of clinical candidate 26a. Starting from hits plagued with poor solubility or genotoxicity, 26a was identified through thorough multiparameter optimisation. Showing robust in vivo activity in an oxazolone-mediated inflammation model, the compound was selected for development. Following a polymorph screen, the hydrochloride salt was selected and the synthesis was efficiently developed to yield the API in 47% overall yield. Copyright © 2017. Published by Elsevier Ltd.

Baseline quantitative hepatitis B core antibody titre alone strongly predicts HBeAg seroconversion across chronic hepatitis B patients treated with peginterferon or nucleos(t)ide analogues

PubMed Central

Fan, Rong; Sun, Jian; Yuan, Quan; Xie, Qing; Bai, Xuefan; Ning, Qin; Cheng, Jun; Yu, Yanyan; Niu, Junqi; Shi, Guangfeng; Wang, Hao; Tan, Deming; Wan, Mobin; Chen, Shijun; Xu, Min; Chen, Xinyue; Tang, Hong; Sheng, Jifang; Lu, Fengmin; Jia, Jidong; Zhuang, Hui; Xia, Ningshao; Hou, Jinlin

2016-01-01

Objective The investigation regarding the clinical significance of quantitative hepatitis B core antibody (anti-HBc) during chronic hepatitis B (CHB) treatment is limited. The aim of this study was to determine the performance of anti-HBc as a predictor for hepatitis B e antigen (HBeAg) seroconversion in HBeAg-positive CHB patients treated with peginterferon (Peg-IFN) or nucleos(t)ide analogues (NUCs), respectively. Design This was a retrospective cohort study consisting of 231 and 560 patients enrolled in two phase IV, multicentre, randomised, controlled trials treated with Peg-IFN or NUC-based therapy for up to 2 years, respectively. Quantitative anti-HBc evaluation was conducted for all the available samples in the two trials by using a newly developed double-sandwich anti-HBc immunoassay. Results At the end of trials, 99 (42.9%) and 137 (24.5%) patients achieved HBeAg seroconversion in the Peg-IFN and NUC cohorts, respectively. We defined 4.4 log10 IU/mL, with a maximum sum of sensitivity and specificity, as the optimal cut-off value of baseline anti-HBc level to predict HBeAg seroconversion for both Peg-IFN and NUC. Patients with baseline anti-HBc ≥4.4 log10 IU/mL and baseline HBV DNA <9 log10 copies/mL had 65.8% (50/76) and 37.1% (52/140) rates of HBeAg seroconversion in the Peg-IFN and NUC cohorts, respectively. In pooled analysis, other than treatment strategy, the baseline anti-HBc level was the best independent predictor for HBeAg seroconversion (OR 2.178; 95% CI 1.577 to 3.009; p<0.001). Conclusions Baseline anti-HBc titre is a useful predictor of Peg-IFN and NUC therapy efficacy in HBeAg-positive CHB patients, which could be used for optimising the antiviral therapy of CHB. PMID:25586058

Development of the hard and soft constraints based optimisation model for unit sizing of the hybrid renewable energy system designed for microgrid applications

NASA Astrophysics Data System (ADS)

Sundaramoorthy, Kumaravel

2017-02-01

The hybrid energy systems (HESs) based electricity generation system has become a more attractive solution for rural electrification nowadays. Economically feasible and technically reliable HESs are solidly based on an optimisation stage. This article discusses about the optimal unit sizing model with the objective function to minimise the total cost of the HES. Three typical rural sites from southern part of India have been selected for the application of the developed optimisation methodology. Feasibility studies and sensitivity analysis on the optimal HES are discussed elaborately in this article. A comparison has been carried out with the Hybrid Optimization Model for Electric Renewable optimisation model for three sites. The optimal HES is found with less total net present rate and rate of energy compared with the existing method

Optimisation of a Generic Ionic Model of Cardiac Myocyte Electrical Activity

PubMed Central

Guo, Tianruo; Al Abed, Amr; Lovell, Nigel H.; Dokos, Socrates

2013-01-01

A generic cardiomyocyte ionic model, whose complexity lies between a simple phenomenological formulation and a biophysically detailed ionic membrane current description, is presented. The model provides a user-defined number of ionic currents, employing two-gate Hodgkin-Huxley type kinetics. Its generic nature allows accurate reconstruction of action potential waveforms recorded experimentally from a range of cardiac myocytes. Using a multiobjective optimisation approach, the generic ionic model was optimised to accurately reproduce multiple action potential waveforms recorded from central and peripheral sinoatrial nodes and right atrial and left atrial myocytes from rabbit cardiac tissue preparations, under different electrical stimulus protocols and pharmacological conditions. When fitted simultaneously to multiple datasets, the time course of several physiologically realistic ionic currents could be reconstructed. Model behaviours tend to be well identified when extra experimental information is incorporated into the optimisation. PMID:23710254

Load-sensitive dynamic workflow re-orchestration and optimisation for faster patient healthcare.

PubMed

Meli, Christopher L; Khalil, Ibrahim; Tari, Zahir

2014-01-01

Hospital waiting times are considerably long, with no signs of reducing any-time soon. A number of factors including population growth, the ageing population and a lack of new infrastructure are expected to further exacerbate waiting times in the near future. In this work, we show how healthcare services can be modelled as queueing nodes, together with healthcare service workflows, such that these workflows can be optimised during execution in order to reduce patient waiting times. Services such as X-ray, computer tomography, and magnetic resonance imaging often form queues, thus, by taking into account the waiting times of each service, the workflow can be re-orchestrated and optimised. Experimental results indicate average waiting time reductions are achievable by optimising workflows using dynamic re-orchestration. Crown Copyright © 2013. Published by Elsevier Ireland Ltd. All rights reserved.

Optimal integrated management of groundwater resources and irrigated agriculture in arid coastal regions

NASA Astrophysics Data System (ADS)

Grundmann, J.; Schütze, N.; Heck, V.

2014-09-01

Groundwater systems in arid coastal regions are particularly at risk due to limited potential for groundwater replenishment and increasing water demand, caused by a continuously growing population. For ensuring a sustainable management of those regions, we developed a new simulation-based integrated water management system. The management system unites process modelling with artificial intelligence tools and evolutionary optimisation techniques for managing both water quality and water quantity of a strongly coupled groundwater-agriculture system. Due to the large number of decision variables, a decomposition approach is applied to separate the original large optimisation problem into smaller, independent optimisation problems which finally allow for faster and more reliable solutions. It consists of an analytical inner optimisation loop to achieve a most profitable agricultural production for a given amount of water and an outer simulation-based optimisation loop to find the optimal groundwater abstraction pattern. Thereby, the behaviour of farms is described by crop-water-production functions and the aquifer response, including the seawater interface, is simulated by an artificial neural network. The methodology is applied exemplarily for the south Batinah re-gion/Oman, which is affected by saltwater intrusion into a coastal aquifer system due to excessive groundwater withdrawal for irrigated agriculture. Due to contradicting objectives like profit-oriented agriculture vs aquifer sustainability, a multi-objective optimisation is performed which can provide sustainable solutions for water and agricultural management over long-term periods at farm and regional scales in respect of water resources, environment, and socio-economic development.

Optimisation of Fabric Reinforced Polymer Composites Using a Variant of Genetic Algorithm

NASA Astrophysics Data System (ADS)

Axinte, Andrei; Taranu, Nicolae; Bejan, Liliana; Hudisteanu, Iuliana

2017-12-01

Fabric reinforced polymeric composites are high performance materials with a rather complex fabric geometry. Therefore, modelling this type of material is a cumbersome task, especially when an efficient use is targeted. One of the most important issue of its design process is the optimisation of the individual laminae and of the laminated structure as a whole. In order to do that, a parametric model of the material has been defined, emphasising the many geometric variables needed to be correlated in the complex process of optimisation. The input parameters involved in this work, include: widths or heights of the tows and the laminate stacking sequence, which are discrete variables, while the gaps between adjacent tows and the height of the neat matrix are continuous variables. This work is one of the first attempts of using a Genetic Algorithm ( GA) to optimise the geometrical parameters of satin reinforced multi-layer composites. Given the mixed type of the input parameters involved, an original software called SOMGA (Satin Optimisation with a Modified Genetic Algorithm) has been conceived and utilised in this work. The main goal is to find the best possible solution to the problem of designing a composite material which is able to withstand to a given set of external, in-plane, loads. The optimisation process has been performed using a fitness function which can analyse and compare mechanical behaviour of different fabric reinforced composites, the results being correlated with the ultimate strains, which demonstrate the efficiency of the composite structure.

Robustness analysis of bogie suspension components Pareto optimised values

NASA Astrophysics Data System (ADS)

Mousavi Bideleh, Seyed Milad

2017-08-01

Bogie suspension system of high speed trains can significantly affect vehicle performance. Multiobjective optimisation problems are often formulated and solved to find the Pareto optimised values of the suspension components and improve cost efficiency in railway operations from different perspectives. Uncertainties in the design parameters of suspension system can negatively influence the dynamics behaviour of railway vehicles. In this regard, robustness analysis of a bogie dynamics response with respect to uncertainties in the suspension design parameters is considered. A one-car railway vehicle model with 50 degrees of freedom and wear/comfort Pareto optimised values of bogie suspension components is chosen for the analysis. Longitudinal and lateral primary stiffnesses, longitudinal and vertical secondary stiffnesses, as well as yaw damping are considered as five design parameters. The effects of parameter uncertainties on wear, ride comfort, track shift force, stability, and risk of derailment are studied by varying the design parameters around their respective Pareto optimised values according to a lognormal distribution with different coefficient of variations (COVs). The robustness analysis is carried out based on the maximum entropy concept. The multiplicative dimensional reduction method is utilised to simplify the calculation of fractional moments and improve the computational efficiency. The results showed that the dynamics response of the vehicle with wear/comfort Pareto optimised values of bogie suspension is robust against uncertainties in the design parameters and the probability of failure is small for parameter uncertainties with COV up to 0.1.

Cardiac Side-effects From Breast Cancer Radiotherapy.

PubMed

Taylor, C W; Kirby, A M

2015-11-01

Breast cancer radiotherapy reduces the risk of cancer recurrence and death. However, it usually involves some radiation exposure of the heart and analyses of randomised trials have shown that it can increase the risk of heart disease. Estimates of the absolute risks of radiation-related heart disease are needed to help oncologists plan each individual woman's treatment. The risk for an individual woman varies according to her estimated cardiac radiation dose and her background risk of ischaemic heart disease in the absence of radiotherapy. When it is known, this risk can then be compared with the absolute benefit of the radiotherapy. At present, many UK cancer centres are already giving radiotherapy with mean heart doses of less than 3 Gy and for most women the benefits of the radiotherapy will probably far outweigh the risks. Technical approaches to minimising heart dose in breast cancer radiotherapy include optimisation of beam angles, use of multileaf collimator shielding, intensity-modulated radiotherapy, treatment in a prone position, treatment in deep inspiration (including the use of breath-hold and gating techniques), proton therapy and partial breast irradiation. The multileaf collimator is suitable for many women with upper pole left breast cancers, but for women with central or lower pole cancers, breath-holding techniques are now recommended in national UK guidelines. Ongoing work aims to identify ways of irradiating pan-regional lymph nodes that are effective, involve minimal exposure of organs at risk and are feasible to plan, deliver and verify. These will probably include wide tangent-based field-in-field intensity-modulated radiotherapy or arc radiotherapy techniques in combination with deep inspiratory breath-hold, and proton beam irradiation for women who have a high predicted heart dose from intensity-modulated radiotherapy. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Optimization of Chitosan and Cellulose Acetate Phthalate Controlled Delivery of Methylprednisolone for Treatment of Inflammatory Bowel Disease.

PubMed

Jagdale, Swati; Chandekar, Apoorva

2017-06-01

Purpose: Inflammatory bowel disease (IBD) is a chronic, relapsing and often life-long disorder. The best way to tackle IBD is to develop a site targeted drug delivery. Methylprednisolone is a potent anti-inflammatory steroid. The relative potency of methylprednisolone to hydrocortisone is at least four is to one. The aim of the present research was to develop a colon targeted drug delivery for treatment of IBD. Methods: Compression coated drug delivery system was designed and optimised. Core tablet contained drug, croscarmellose sodium (CCS-superdisintegrant), avicel (binder) and dicalcium phosphate (diluent). Design of experiment with 3 2 factorial design was applied for optimization of compression coated delivery. Chitosan and cellulose acetate phthalate were chosen as independent variables. Swelling index, hardness and % drug release were dependant variables. Results: Core tablet (C5 batch) containing 2.15% CCS showed disintegration in less than 10sec. FTIR, UV and DSC study had shown absence of any significant physical and chemical interaction between drug and polymers. F8 was found to be optimised formulation. F8 contained 35% chitosan and 17.5% cellulose acetate phthalate. It showed drug release of 86.3% ± 6.1%, hardness 6.5 ± 1.5 and lag time 7 hrs. Simulated media drug release was 97.51 ± 8.6% with 7.5 hrs lag time. The results confirmed that the lag time was highly affected by the coating of the polymers as well as the concentration of the superdisintegrant used in core tablet. Conclusion: In-vitro and in-vivo results confirmed a potential colon targeted drug therapy for treatment of IBD.

Optimization of Chitosan and Cellulose Acetate Phthalate Controlled Delivery of Methylprednisolone for Treatment of Inflammatory Bowel Disease

PubMed Central

Jagdale, Swati; Chandekar, Apoorva

2017-01-01

Purpose: Inflammatory bowel disease (IBD) is a chronic, relapsing and often life-long disorder. The best way to tackle IBD is to develop a site targeted drug delivery. Methylprednisolone is a potent anti-inflammatory steroid. The relative potency of methylprednisolone to hydrocortisone is at least four is to one. The aim of the present research was to develop a colon targeted drug delivery for treatment of IBD. Methods: Compression coated drug delivery system was designed and optimised. Core tablet contained drug, croscarmellose sodium (CCS-superdisintegrant), avicel (binder) and dicalcium phosphate (diluent). Design of experiment with 32 factorial design was applied for optimization of compression coated delivery. Chitosan and cellulose acetate phthalate were chosen as independent variables. Swelling index, hardness and % drug release were dependant variables. Results: Core tablet (C5 batch) containing 2.15% CCS showed disintegration in less than 10sec. FTIR, UV and DSC study had shown absence of any significant physical and chemical interaction between drug and polymers. F8 was found to be optimised formulation. F8 contained 35% chitosan and 17.5% cellulose acetate phthalate. It showed drug release of 86.3% ± 6.1%, hardness 6.5 ± 1.5 and lag time 7 hrs. Simulated media drug release was 97.51 ± 8.6% with 7.5 hrs lag time. The results confirmed that the lag time was highly affected by the coating of the polymers as well as the concentration of the superdisintegrant used in core tablet. Conclusion: In-vitro and in-vivo results confirmed a potential colon targeted drug therapy for treatment of IBD. PMID:28761822

Investigation of power and frequency for 3D conformal MRI-controlled transurethral ultrasound therapy with a dual frequency multi-element transducer.

PubMed

N'djin, William Apoutou; Burtnyk, Mathieu; Bronskill, Michael; Chopra, Rajiv

2012-01-01

Transurethral ultrasound therapy uses real-time magnetic resonance (MR) temperature feedback to enable the 3D control of thermal therapy accurately in a region within the prostate. Previous canine studies showed the feasibility of this method in vivo. The aim of this study was to reduce the procedure time, while maintaining targeting accuracy, by investigating new combinations of treatment parameters. Simulations and validation experiments in gel phantoms were used, with a collection of nine 3D realistic target prostate boundaries obtained from previous preclinical studies, where multi-slice MR images were acquired with the transurethral device in place. Acoustic power and rotation rate were varied based on temperature feedback at the prostate boundary. Maximum acoustic power and rotation rate were optimised interdependently, as a function of prostate radius and transducer operating frequency. The concept of dual frequency transducers was studied, using the fundamental frequency or the third harmonic component depending on the prostate radius. Numerical modelling enabled assessment of the effects of several acoustic parameters on treatment outcomes. The range of treatable prostate radii extended with increasing power, and tended to narrow with decreasing frequency. Reducing the frequency from 8 MHz to 4 MHz or increasing the surface acoustic power from 10 to 20 W/cm(2) led to treatment times shorter by up to 50% under appropriate conditions. A dual frequency configuration of 4/12 MHz with 20 W/cm(2) ultrasound intensity exposure can treat entire prostates up to 40 cm(3) in volume within 30 min. The interdependence between power and frequency may, however, require integrating multi-parametric functions in the controller for future optimisations.

HPLC-DAD method development and validation for the quantification of hydroxymethylfurfural in corn chips by means of response surface optimisation.

PubMed

Salvatierra Virgen, Sara; Ceballos-Magaña, Silvia Guillermina; Salvatierra-Stamp, Vilma Del Carmen; Sumaya-Martínez, Maria Teresa; Martínez-Martínez, Francisco Javier; Muñiz-Valencia, Roberto

2017-12-01

In recent years, there has been an increased concern about the presence of toxic compounds derived from the Maillard reaction produced during food cooking at high temperatures. The main toxic compounds derived from this reaction are acrylamide and hydroxymethylfurfural (HMF). The majority of analytical methods require sample treatments using solvents which are highly polluting for the environment. The difficulty of quantifying HMF in complex fried food matrices encourages the development of new analytical methods. This paper provides a rapid, sensitive and environmentally-friendly analytical method for the quantification of HMF in corn chips using HPLC-DAD. Chromatographic separation resulted in a baseline separation for HMF in 3.7 min. Sample treatment for corn chip samples first involved a leaching process using water and afterwards a solid-phase extraction (SPE) using HLB-Oasis polymeric cartridges. Sample treatment optimisation was carried out by means of Box-Behnken fractional factorial design and Response Surface Methodolog y to examine the effects of four variables (sample weight, pH, sonication time and elution volume) on HMF extraction from corn chips. The SPE-HPLC-DAD method was validated. The limits of detection and quantification were 0.82 and 2.20 mg kg -1 , respectively. Method precision was evaluated in terms of repeatability and reproducibility as relative standard deviations (RSDs) using three concentration levels. For repeatability, RSD values were 6.9, 3.6 and 2.0%; and for reproducibility 18.8, 7.9 and 2.9%. For a ruggedness study the Yuden test was applied and the result demonstrated the method as robust. The method was successfully applied to different corn chip samples.

Accelerated enhanced Recovery following Minimally Invasive colorectal cancer surgery (RecoverMI): a study protocol for a novel randomised controlled trial

PubMed Central

Price, Brandee A; Bednarski, Brian K; You, Y Nancy; Manandhar, Meryna; Dean, E Michelle; Alawadi, Zeinab M; Bryce Speer, B; Gottumukkala, Vijaya; Weldon, Marla; Massey, Robert L; Wang, Xuemei; Qiao, Wei; Chang, George J

2017-01-01

Introduction Definitive treatment of localised colorectal cancer involves surgical resection of the primary tumour. Short-stay colectomies (eg, 23-hours) would have important implications for optimising the efficiency of inpatient care with reduced resource utilisation while improving the overall recovery experience with earlier return to normalcy. It could permit surgical treatment of colorectal cancer in a wider variety of settings, including hospital-based ambulatory surgery environments. While a few studies have shown that discharge within the first 24 hours after minimally invasive colectomy is possible, the safety, feasibility and patient acceptability of a protocol for short-stay colectomy for colorectal cancer have not previously been evaluated in a prospective randomised study. Moreover, given the potential for some patients to experience a delay in recovery of bowel function after colectomy, close outpatient monitoring may be necessary to ensure safe implementation. Methods and analysis In order to address this gap, we propose a prospective randomised trial of accelerated enhanced Recovery following Minimally Invasive colorectal cancer surgery (RecoverMI) that leverages the combination of minimally invasive surgery with enhanced recovery protocols and early coordinated outpatient remote televideo conferencing technology (TeleRecovery) to improve postoperative patien-provider communication, enhance postoperative treatment navigation and optimise postdischarge care. We hypothesise that RecoverMI can be safely incorporated into multidisciplinary practice to improve patient outcomes and reduce the overall 30-day duration of hospitalisation while preserving the quality of the patient experience. Ethics and dissemination RecoverMI has received institutional review board approval and funding from the American Society of Colorectal Surgeons (ASCRS; LPG103). Results from RecoverMI will be published in a peer-reviewed publication and be used to inform a multisite trial. Trial registration number NCT02613728; Pre-results. PMID:28729319

Genetic testing in women with breast cancer: implications for treatment.

PubMed

Paterson, Robin; Phillips, Kelly-Anne

2017-11-01

Mutations in either the BRCA1 or BRCA2 genes are responsible for approximately 42,000 cases of breast cancer annually. Identifying these germline mutations in a woman with breast cancer is important because it can influence her immediate and long-term management and has important implications for other family members. Areas covered: This review highlights how treatment-focussed genetic testing for BRCA1 and BRCA2 mutations can potentially influence cancer treatment and secondary prevention decisions in women with breast cancer. Expert commentary: Testing women with breast cancer for BRCA1 and BRCA2 germline mutations has the potential to decrease cancer burden and improve cancer outcomes. It can help optimise surgical and systemic therapy approaches. Clinicians should actively consider whether genetic testing is appropriate for each woman with breast cancer, and if so should instigate it early in the treatment trajectory when it can most influence cancer care.

Efficiency, costs and benefits of AOPs for removal of pharmaceuticals from the water cycle.

PubMed

Tuerk, J; Sayder, B; Boergers, A; Vitz, H; Kiffmeyer, T K; Kabasci, S

2010-01-01

Different advanced oxidation processes (AOP) were developed for the treatment of highly loaded wastewater streams. Optimisation of removal and improvement of efficiency were carried out on a laboratory, semiworks and pilot plant scale. The persistent cytostatic drug cyclophosphamide was selected as a reference substance regarding elimination and evaluation of the various oxidation processes because of its low degradability rate. The investigated processes are cost-efficient and suitable regarding the treatment of wastewater streams since they lead to efficient elimination of antibiotics and antineoplastics. A total reduction of toxicity was proven by means of the umuC-test. However, in order to reduce pharmaceuticals from the water cycle, it must be considered that the input of more than 80 % of the pharmaceuticals entering wastewater treatment systems results from private households. Therefore, advanced technologies should also be installed at wastewater treatment plants.

Physical-chemical treatment of rainwater runoff in recovery and recycling companies: Pilot-scale optimization.

PubMed

Blondeel, Evelyne; Depuydt, Veerle; Cornelis, Jasper; Chys, Michael; Verliefde, Arne; Van Hulle, Stijin Wim Henk

2015-01-01

Pilot-scale optimisation of different possible physical-chemical water treatment techniques was performed on the wastewater originating from three different recovery and recycling companies in order to select a (combination of) technique(s) for further full-scale implementation. This implementation is necessary to reduce the concentration of both common pollutants (such as COD, nutrients and suspended solids) and potentially toxic metals, polyaromatic hydrocarbons and poly-chlorinated biphenyls frequently below the discharge limits. The pilot-scale tests (at 250 L h(-1) scale) demonstrate that sand anthracite filtration or coagulation/flocculation are interesting as first treatment techniques with removal efficiencies of about 19% to 66% (sand anthracite filtration), respectively 18% to 60% (coagulation/flocculation) for the above mentioned pollutants (metals, polyaromatic hydrocarbons and poly chlorinated biphenyls). If a second treatment step is required, the implementation of an activated carbon filter is recommended (about 46% to 86% additional removal is obtained).

Proteomic diversity of high-density lipoprotein explains its association with clinical outcome in patients with heart failure.

PubMed

Emmens, Johanna Elisabeth; Jones, Donald J L; Cao, Thong H; Chan, Daniel C S; Romaine, Simon P R; Quinn, Paulene A; Anker, Stefan D; Cleland, John G; Dickstein, Kenneth; Filippatos, Gerasimos; Hillege, Hans L; Lang, Chim C; Ponikowski, Piotr; Samani, Nilesh J; van Veldhuisen, Dirk J; Zannad, Faiz; Zwinderman, Aeilko H; Metra, Marco; de Boer, Rudolf A; Voors, Adriaan A; Ng, Leong L

2018-02-01

Previously, low high-density lipoprotein (HDL) cholesterol was found to be one of the strongest predictors of mortality and/or heart failure (HF) hospitalisation in patients with HF. We therefore performed in-depth investigation of the multifunctional HDL proteome to reveal underlying pathophysiological mechanisms explaining the association between HDL and clinical outcome. We selected a cohort of 90 HF patients with 1:1 cardiovascular death/survivor ratio from BIOSTAT-CHF. A novel optimised protocol for selective enrichment of lipoproteins was used to prepare plasma. Enriched lipoprotein content of samples was analysed using high resolution nanoscale liquid chromatography-mass spectrometry-based proteomics, utilising a label free approach. Within the HDL proteome, 49 proteins significantly differed between deaths and survivors. An optimised model of 12 proteins predicted death with 76% accuracy (Nagelkerke R 2 =0.37, P < 0.001). The strongest contributors to this model were filamin-A (related to crosslinking of actin filaments) [odds ratio (OR) 0.31, 95% confidence interval (CI) 0.15-0.61, P = 0.001] and pulmonary surfactant-associated protein B (related to alveolar capillary membrane function) (OR 2.50, 95% CI 1.57-3.98, P < 0.001). The model predicted mortality with an area under the curve of 0.82 (95% CI 0.77-0.87, P < 0.001). Internal cross validation resulted in 73.3 ± 7.2% accuracy. This study shows marked differences in composition of the HDL proteome between HF survivors and deaths. The strongest differences were seen in proteins reflecting crosslinking of actin filaments and alveolar capillary membrane function, posing potential pathophysiological mechanisms underlying the association between HDL and clinical outcome in HF. © 2017 The Authors. European Journal of Heart Failure © 2017 European Society of Cardiology.

Design of experiment approach for the process optimisation of microwave assisted extraction of lupeol from Ficus racemosa leaves using response surface methodology.

PubMed

Das, Anup Kumar; Mandal, Vivekananda; Mandal, Subhash C

2013-01-01

Triterpenoids are a group of important phytocomponents from Ficus racemosa (syn. Ficus glomerata Roxb.) that are known to possess diverse pharmacological activities and which have prompted the development of various extraction techniques and strategies for its better utilisation. To develop an effective, rapid and ecofriendly microwave-assisted extraction (MAE) strategy to optimise the extraction of a potent bioactive triterpenoid compound, lupeol, from young leaves of Ficus racemosa using response surface methodology (RSM) for industrial scale-up. Initially a Plackett-Burman design matrix was applied to identify the most significant extraction variables amongst microwave power, irradiation time, particle size, solvent:sample ratio loading, varying solvent strength and pre-leaching time on lupeol extraction. Among the six variables tested, microwave power, irradiation time and solvent-sample/loading ratio were found to have a significant effect (P < 0.05) on lupeol extraction and were fitted to a Box-Behnken-design-generated quadratic polynomial equation to predict optimal extraction conditions as well as to locate operability regions with maximum yield. The optimal conditions were microwave power of 65.67% of 700 W, extraction time of 4.27 min and solvent-sample ratio loading of 21.33 mL/g. Confirmation trials under the optimal conditions gave an experimental yield (18.52 µg/g of dry leaves) close to the RSM predicted value of 18.71 µg/g. Under the optimal conditions the mathematical model was found to be well fitted with the experimental data. The MAE was found to be a more rapid, convenient and appropriate extraction method, with a higher yield and lower solvent consumption when compared with conventional extraction techniques. Copyright © 2012 John Wiley & Sons, Ltd.

On the dynamic rounding-off in analogue and RF optimal circuit sizing

NASA Astrophysics Data System (ADS)

Kotti, Mouna; Fakhfakh, Mourad; Fino, Maria Helena

2014-04-01

Frequently used approaches to solve discrete multivariable optimisation problems consist of computing solutions using a continuous optimisation technique. Then, using heuristics, the variables are rounded-off to their nearest available discrete values to obtain a discrete solution. Indeed, in many engineering problems, and particularly in analogue circuit design, component values, such as the geometric dimensions of the transistors, the number of fingers in an integrated capacitor or the number of turns in an integrated inductor, cannot be chosen arbitrarily since they have to obey to some technology sizing constraints. However, rounding-off the variables values a posteriori and can lead to infeasible solutions (solutions that are located too close to the feasible solution frontier) or degradation of the obtained results (expulsion from the neighbourhood of a 'sharp' optimum) depending on how the added perturbation affects the solution. Discrete optimisation techniques, such as the dynamic rounding-off technique (DRO) are, therefore, needed to overcome the previously mentioned situation. In this paper, we deal with an improvement of the DRO technique. We propose a particle swarm optimisation (PSO)-based DRO technique, and we show, via some analog and RF-examples, the necessity to implement such a routine into continuous optimisation algorithms.

PGA/MOEAD: a preference-guided evolutionary algorithm for multi-objective decision-making problems with interval-valued fuzzy preferences

NASA Astrophysics Data System (ADS)

Luo, Bin; Lin, Lin; Zhong, ShiSheng

2018-02-01

In this research, we propose a preference-guided optimisation algorithm for multi-criteria decision-making (MCDM) problems with interval-valued fuzzy preferences. The interval-valued fuzzy preferences are decomposed into a series of precise and evenly distributed preference-vectors (reference directions) regarding the objectives to be optimised on the basis of uniform design strategy firstly. Then the preference information is further incorporated into the preference-vectors based on the boundary intersection approach, meanwhile, the MCDM problem with interval-valued fuzzy preferences is reformulated into a series of single-objective optimisation sub-problems (each sub-problem corresponds to a decomposed preference-vector). Finally, a preference-guided optimisation algorithm based on MOEA/D (multi-objective evolutionary algorithm based on decomposition) is proposed to solve the sub-problems in a single run. The proposed algorithm incorporates the preference-vectors within the optimisation process for guiding the search procedure towards a more promising subset of the efficient solutions matching the interval-valued fuzzy preferences. In particular, lots of test instances and an engineering application are employed to validate the performance of the proposed algorithm, and the results demonstrate the effectiveness and feasibility of the algorithm.

Optimisation of active suspension control inputs for improved performance of active safety systems

NASA Astrophysics Data System (ADS)

Čorić, Mirko; Deur, Joško; Xu, Li; Tseng, H. Eric; Hrovat, Davor

2018-01-01

A collocation-type control variable optimisation method is used to investigate the extent to which the fully active suspension (FAS) can be applied to improve the vehicle electronic stability control (ESC) performance and reduce the braking distance. First, the optimisation approach is applied to the scenario of vehicle stabilisation during the sine-with-dwell manoeuvre. The results are used to provide insights into different FAS control mechanisms for vehicle performance improvements related to responsiveness and yaw rate error reduction indices. The FAS control performance is compared to performances of the standard ESC system, optimal active brake system and combined FAS and ESC configuration. Second, the optimisation approach is employed to the task of FAS-based braking distance reduction for straight-line vehicle motion. Here, the scenarios of uniform and longitudinally or laterally non-uniform tyre-road friction coefficient are considered. The influences of limited anti-lock braking system (ABS) actuator bandwidth and limit-cycle ABS behaviour are also analysed. The optimisation results indicate that the FAS can provide competitive stabilisation performance and improved agility when compared to the ESC system, and that it can reduce the braking distance by up to 5% for distinctively non-uniform friction conditions.

Design optimisation of powers-of-two FIR filter using self-organising random immigrants GA

NASA Astrophysics Data System (ADS)

Chandra, Abhijit; Chattopadhyay, Sudipta

2015-01-01

In this communication, we propose a novel design strategy of multiplier-less low-pass finite impulse response (FIR) filter with the aid of a recent evolutionary optimisation technique, known as the self-organising random immigrants genetic algorithm. Individual impulse response coefficients of the proposed filter have been encoded as sum of signed powers-of-two. During the formulation of the cost function for the optimisation algorithm, both the frequency response characteristic and the hardware cost of the discrete coefficient FIR filter have been considered. The role of crossover probability of the optimisation technique has been evaluated on the overall performance of the proposed strategy. For this purpose, the convergence characteristic of the optimisation technique has been included in the simulation results. In our analysis, two design examples of different specifications have been taken into account. In order to substantiate the efficiency of our proposed structure, a number of state-of-the-art design strategies of multiplier-less FIR filter have also been included in this article for the purpose of comparison. Critical analysis of the result unambiguously establishes the usefulness of our proposed approach for the hardware efficient design of digital filter.

A New Multiconstraint Method for Determining the Optimal Cable Stresses in Cable-Stayed Bridges

PubMed Central

Asgari, B.; Osman, S. A.; Adnan, A.

2014-01-01

Cable-stayed bridges are one of the most popular types of long-span bridges. The structural behaviour of cable-stayed bridges is sensitive to the load distribution between the girder, pylons, and cables. The determination of pretensioning cable stresses is critical in the cable-stayed bridge design procedure. By finding the optimum stresses in cables, the load and moment distribution of the bridge can be improved. In recent years, different research works have studied iterative and modern methods to find optimum stresses of cables. However, most of the proposed methods have limitations in optimising the structural performance of cable-stayed bridges. This paper presents a multiconstraint optimisation method to specify the optimum cable forces in cable-stayed bridges. The proposed optimisation method produces less bending moments and stresses in the bridge members and requires shorter simulation time than other proposed methods. The results of comparative study show that the proposed method is more successful in restricting the deck and pylon displacements and providing uniform deck moment distribution than unit load method (ULM). The final design of cable-stayed bridges can be optimised considerably through proposed multiconstraint optimisation method. PMID:25050400

A new multiconstraint method for determining the optimal cable stresses in cable-stayed bridges.

PubMed

Asgari, B; Osman, S A; Adnan, A

2014-01-01

Cable-stayed bridges are one of the most popular types of long-span bridges. The structural behaviour of cable-stayed bridges is sensitive to the load distribution between the girder, pylons, and cables. The determination of pretensioning cable stresses is critical in the cable-stayed bridge design procedure. By finding the optimum stresses in cables, the load and moment distribution of the bridge can be improved. In recent years, different research works have studied iterative and modern methods to find optimum stresses of cables. However, most of the proposed methods have limitations in optimising the structural performance of cable-stayed bridges. This paper presents a multiconstraint optimisation method to specify the optimum cable forces in cable-stayed bridges. The proposed optimisation method produces less bending moments and stresses in the bridge members and requires shorter simulation time than other proposed methods. The results of comparative study show that the proposed method is more successful in restricting the deck and pylon displacements and providing uniform deck moment distribution than unit load method (ULM). The final design of cable-stayed bridges can be optimised considerably through proposed multiconstraint optimisation method.

Group search optimiser-based optimal bidding strategies with no Karush-Kuhn-Tucker optimality conditions

NASA Astrophysics Data System (ADS)

Yadav, Naresh Kumar; Kumar, Mukesh; Gupta, S. K.

2017-03-01

General strategic bidding procedure has been formulated in the literature as a bi-level searching problem, in which the offer curve tends to minimise the market clearing function and to maximise the profit. Computationally, this is complex and hence, the researchers have adopted Karush-Kuhn-Tucker (KKT) optimality conditions to transform the model into a single-level maximisation problem. However, the profit maximisation problem with KKT optimality conditions poses great challenge to the classical optimisation algorithms. The problem has become more complex after the inclusion of transmission constraints. This paper simplifies the profit maximisation problem as a minimisation function, in which the transmission constraints, the operating limits and the ISO market clearing functions are considered with no KKT optimality conditions. The derived function is solved using group search optimiser (GSO), a robust population-based optimisation algorithm. Experimental investigation is carried out on IEEE 14 as well as IEEE 30 bus systems and the performance is compared against differential evolution-based strategic bidding, genetic algorithm-based strategic bidding and particle swarm optimisation-based strategic bidding methods. The simulation results demonstrate that the obtained profit maximisation through GSO-based bidding strategies is higher than the other three methods.

Non-pharmacological treatment options for refractory epilepsy: an overview of human treatment modalities and their potential utility in dogs.

PubMed

Martlé, Valentine; Van Ham, Luc; Raedt, Robrecht; Vonck, Kristl; Boon, Paul; Bhatti, Sofie

2014-03-01

Refractory epilepsy is a common disorder both in humans and dogs and treatment protocols are difficult to optimise. In humans, different non-pharmacological treatment modalities currently available include surgery, the ketogenic diet and neurostimulation. Surgery leads to freedom from seizures in 50-75% of patients, but requires strict patient selection. The ketogenic diet is indicated in severe childhood epilepsies, but efficacy is limited and long-term compliance can be problematic. In the past decade, various types of neurostimulation have emerged as promising treatment modalities for humans with refractory epilepsy. Currently, none of these treatment options are used in routine daily clinical practice to treat dogs with the condition. Since many dogs with poorly controlled seizures do not survive, the search for alternative treatment options for canine refractory epilepsy should be prioritised. This review provides an overview of non-pharmacological treatment options for human refractory epilepsy. The current knowledge and limitations of these treatments in canine refractory epilepsy is also discussed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evolving aerodynamic airfoils for wind turbines through a genetic algorithm

NASA Astrophysics Data System (ADS)

Hernández, J. J.; Gómez, E.; Grageda, J. I.; Couder, C.; Solís, A.; Hanotel, C. L.; Ledesma, JI

2017-01-01

Nowadays, genetic algorithms stand out for airfoil optimisation, due to the virtues of mutation and crossing-over techniques. In this work we propose a genetic algorithm with arithmetic crossover rules. The optimisation criteria are taken to be the maximisation of both aerodynamic efficiency and lift coefficient, while minimising drag coefficient. Such algorithm shows greatly improvements in computational costs, as well as a high performance by obtaining optimised airfoils for Mexico City's specific wind conditions from generic wind turbines designed for higher Reynolds numbers, in few iterations.

Exemples d’utilisation des techniques d’optimisation en calcul de structures de reacteurs

DTIC Science & Technology

2003-03-01

34~ optimisation g~om~trique (architecture fig~e) A la difference du secteur automobile et des avionneurs, la plupart des composants des r~acteurs n...utilise des lois de comportement mat~riaux non lin~aires ainsi que des hypotheses de grands d~placements. L𔄀tude d’optimisation consiste ý minimiser...un disque simple et d~cid6 de s~lectionner trois param~tes qui influent sur la rupture : 1𔄀paisseur de la toile du disque ElI, la hauteur L3 et la

Self-optimisation and model-based design of experiments for developing a C-H activation flow process.

PubMed

Echtermeyer, Alexander; Amar, Yehia; Zakrzewski, Jacek; Lapkin, Alexei

2017-01-01

A recently described C(sp 3 )-H activation reaction to synthesise aziridines was used as a model reaction to demonstrate the methodology of developing a process model using model-based design of experiments (MBDoE) and self-optimisation approaches in flow. The two approaches are compared in terms of experimental efficiency. The self-optimisation approach required the least number of experiments to reach the specified objectives of cost and product yield, whereas the MBDoE approach enabled a rapid generation of a process model.

Fractionation of wastewater characteristics for modelling of Firle Sewage Treatment Works, Harare, Zimbabwe

NASA Astrophysics Data System (ADS)

Muserere, Simon Takawira; Hoko, Zvikomborero; Nhapi, Innocent

Varying conditions are required for different species of microorganisms for the complex biological processes taking place within the activated sludge treatment system. It is against the requirement to manage this complex dynamic system that computer simulators were developed to aid in optimising activated sludge treatment processes. These computer simulators require calibration with quality data input that include wastewater fractionation among others. Thus, this research fractionated raw sewage, at Firle Sewage Treatment Works (STW), for calibration of the BioWin simulation model. Firle STW is a 3-stage activated sludge system. Wastewater characteristics of importance for activated sludge process design can be grouped into carbonaceous, nitrogenous and phosphorus compounds. Division of the substrates and compounds into their constituent fractions is called fractionation and is a valuable tool for process assessment. Fractionation can be carried out using bioassay methods or much simpler physico-chemical methods. The bioassay methods require considerable experience with experimental activated sludge systems and associated measurement techniques while the physico-chemical methods are straight forward. Plant raw wastewater fractionation was carried out through two 14-day campaign periods, the first being from 3 to 16 July 2013 and the second was from 1 to 14 October 2013. According to the Zimbabwean Environmental Management Act, and based on the sensitivity of its catchment, Firle STW effluent discharge regulatory standards in mg/L are COD (<60), TN (<10), ammonia (<0.2), and TP (<1). On the other hand Firle STW Unit 4 effluent quality results based on City of Harare records in mg/L during the period of study were COD (90 ± 35), TN (9.0 ± 3.0), ammonia (0.2 ± 0.4) and TP (3.0 ± 1.0). The raw sewage parameter concentrations measured during the study in mg/L and fractions for raw sewage respectively were as follows total COD (680 ± 37), slowly biodegradable COD (456 ± 23), (0.7), readily biodegradable COD (131 ± 11), (0.2), soluble unbiodegradable COD (40 ± 3), (0.06), particulate unbiodegradable COD (53 ± 3) (0.08), total TKN (40 ± 4) mg/L, ammonia (28 ± 6), (0.68), organically bound nitrogen (12 ± 2), (0.32), TP (15 ± 1.4), orthophosphates (9.6 ± 1.4), (0.64), and organically bound TP (5.4 ± 1.4), (0.36), soluble unbiodegradable TP (0.4 ± 0), (0.03), particulate unbiodegradable TP (0.05 ± 0), (0.003). Thus, wastewater at Firle STW was found to be highly biodegradable suggesting optimisation of biological nutrient removal process will generally achieve effluent regulatory standards compliance. Thus, opportunities for plant optimisation do exist of which modelling with the use of a simulator is recommended to achieve recommended effluent standards in addition to reduction of operating costs.

WE-H-BRA-07: Mechanistic Modelling of the Relative Biological Effectiveness of Heavy Charged Particles

DOE Office of Scientific and Technical Information (OSTI.GOV)

McMahon, S; Queen’s University, Belfast, Belfast; McNamara, A

2016-06-15

Purpose Uncertainty in the Relative Biological Effectiveness (RBE) of heavy charged particles compared to photons remains one of the major uncertainties in particle therapy. As RBEs depend strongly on clinical variables such as tissue type, dose, and radiation quality, more accurate individualised models are needed to fully optimise treatments. MethodsWe have developed a model of DNA damage and repair following X-ray irradiation in a number of settings, incorporating mechanistic descriptions of DNA repair pathways, geometric effects on DNA repair, cell cycle effects and cell death. Our model has previously been shown to accurately predict a range of biological endpoints includingmore » chromosome aberrations, mutations, and cell death. This model was combined with nanodosimetric models of individual ion tracks to calculate the additional probability of lethal damage forming within a single track. These lethal damage probabilities can be used to predict survival and RBE for cells irradiated with ions of different Linear Energy Transfer (LET). ResultsBy combining the X-ray response model with nanodosimetry information, predictions of RBE can be made without cell-line specific fitting. The model’s RBE predictions were found to agree well with empirical proton RBE models (Mean absolute difference between models of 1.9% and 1.8% for cells with α/β ratios of 9 and 1.4, respectively, for LETs between 0 and 15 keV/µm). The model also accurately recovers the impact of high-LET carbon ion exposures, showing both the reduced efficacy of ions at extremely high LET, as well as the impact of defects in non-homologous end joining on RBE values in Chinese Hamster Ovary cells.ConclusionOur model is predicts RBE without the inclusion of empirical LET fitting parameters for a range of experimental conditions. This approach has the potential to deliver improved personalisation of particle therapy, with future developments allowing for the calculation of individualised RBEs. SJM is supported by a Marie Curie International Outgoing Fellowship from the European Commission’s FP7 program (EC FP7 MC-IOF-623630)« less

Age at disease onset and peak ammonium level rather than interventional variables predict the neurological outcome in urea cycle disorders.

PubMed

Posset, Roland; Garcia-Cazorla, Angeles; Valayannopoulos, Vassili; Teles, Elisa Leão; Dionisi-Vici, Carlo; Brassier, Anaïs; Burlina, Alberto B; Burgard, Peter; Cortès-Saladelafont, Elisenda; Dobbelaere, Dries; Couce, Maria L; Sykut-Cegielska, Jolanta; Häberle, Johannes; Lund, Allan M; Chakrapani, Anupam; Schiff, Manuel; Walter, John H; Zeman, Jiri; Vara, Roshni; Kölker, Stefan

2016-09-01

Patients with urea cycle disorders (UCDs) have an increased risk of neurological disease manifestation. Determining the effect of diagnostic and therapeutic interventions on the neurological outcome. Evaluation of baseline, regular follow-up and emergency visits of 456 UCD patients prospectively followed between 2011 and 2015 by the E-IMD patient registry. About two-thirds of UCD patients remained asymptomatic until age 12 days [i.e. the median age at diagnosis of patients identified by newborn screening (NBS)] suggesting a potential benefit of NBS. In fact, NBS lowered the age at diagnosis in patients with late onset of symptoms (>28 days), and a trend towards improved long-term neurological outcome was found for patients with argininosuccinate synthetase and lyase deficiency as well as argininemia identified by NBS. Three to 17 different drug combinations were used for maintenance therapy, but superiority of any single drug or specific drug combination above other combinations was not demonstrated. Importantly, non-interventional variables of disease severity, such as age at disease onset and peak ammonium level of the initial hyperammonemic crisis (cut-off level: 500 μmol/L) best predicted the neurological outcome. Promising results of NBS for late onset UCD patients are reported and should be re-evaluated in a larger and more advanced age group. However, non-interventional variables affect the neurological outcome of UCD patients. Available evidence-based guideline recommendations are currently heterogeneously implemented into practice, leading to a high variability of drug combinations that hamper our understanding of optimised long-term and emergency treatment.

Dosimetry of ionising radiation in modern radiation oncology

NASA Astrophysics Data System (ADS)

Kron, Tomas; Lehmann, Joerg; Greer, Peter B.

2016-07-01

Dosimetry of ionising radiation is a well-established and mature branch of physical sciences with many applications in medicine and biology. In particular radiotherapy relies on dosimetry for optimisation of cancer treatment and avoidance of severe toxicity for patients. Several novel developments in radiotherapy have introduced new challenges for dosimetry with small and dynamically changing radiation fields being central to many of these applications such as stereotactic ablative body radiotherapy and intensity modulated radiation therapy. There is also an increasing awareness of low doses given to structures not in the target region and the associated risk of secondary cancer induction. Here accurate dosimetry is important not only for treatment optimisation but also for the generation of data that can inform radiation protection approaches in the future. The article introduces some of the challenges and highlights the interdependence of dosimetric calculations and measurements. Dosimetric concepts are explored in the context of six application fields: reference dosimetry, small fields, low dose out of field, in vivo dosimetry, brachytherapy and auditing of radiotherapy practice. Recent developments of dosimeters that can be used for these purposes are discussed using spatial resolution and number of dimensions for measurement as sorting criteria. While dosimetry is ever evolving to address the needs of advancing applications of radiation in medicine two fundamental issues remain: the accuracy of the measurement from a scientific perspective and the importance to link the measurement to a clinically relevant question. This review aims to provide an update on both of these.

Impact of field number and beam angle on functional image-guided lung cancer radiotherapy planning

NASA Astrophysics Data System (ADS)

Tahir, Bilal A.; Bragg, Chris M.; Wild, Jim M.; Swinscoe, James A.; Lawless, Sarah E.; Hart, Kerry A.; Hatton, Matthew Q.; Ireland, Rob H.

2017-09-01

To investigate the effect of beam angles and field number on functionally-guided intensity modulated radiotherapy (IMRT) normal lung avoidance treatment plans that incorporate hyperpolarised helium-3 magnetic resonance imaging (3He MRI) ventilation data. Eight non-small cell lung cancer patients had pre-treatment 3He MRI that was registered to inspiration breath-hold radiotherapy planning computed tomography. IMRT plans that minimised the volume of total lung receiving  ⩾20 Gy (V20) were compared with plans that minimised 3He MRI defined functional lung receiving  ⩾20 Gy (fV20). Coplanar IMRT plans using 5-field manually optimised beam angles and 9-field equidistant plans were also evaluated. For each pair of plans, the Wilcoxon signed ranks test was used to compare fV20 and the percentage of planning target volume (PTV) receiving 90% of the prescription dose (PTV90). Incorporation of 3He MRI led to median reductions in fV20 of 1.3% (range: 0.2-9.3% p  =  0.04) and 0.2% (range: 0 to 4.1%; p  =  0.012) for 5- and 9-field arrangements, respectively. There was no clinically significant difference in target coverage. Functionally-guided IMRT plans incorporating hyperpolarised 3He MRI information can reduce the dose received by ventilated lung without comprising PTV coverage. The effect was greater for optimised beam angles rather than uniformly spaced fields.

Highly polygenic architecture of antidepressant treatment response: Comparative analysis of SSRI and NRI treatment in an animal model of depression.

PubMed

Malki, Karim; Tosto, Maria Grazia; Mouriño-Talín, Héctor; Rodríguez-Lorenzo, Sabela; Pain, Oliver; Jumhaboy, Irfan; Liu, Tina; Parpas, Panos; Newman, Stuart; Malykh, Artem; Carboni, Lucia; Uher, Rudolf; McGuffin, Peter; Schalkwyk, Leonard C; Bryson, Kevin; Herbster, Mark

2017-04-01

Response to antidepressant (AD) treatment may be a more polygenic trait than previously hypothesized, with many genetic variants interacting in yet unclear ways. In this study we used methods that can automatically learn to detect patterns of statistical regularity from a sparsely distributed signal across hippocampal transcriptome measurements in a large-scale animal pharmacogenomic study to uncover genomic variations associated with AD. The study used four inbred mouse strains of both sexes, two drug treatments, and a control group (escitalopram, nortriptyline, and saline). Multi-class and binary classification using Machine Learning (ML) and regularization algorithms using iterative and univariate feature selection methods, including InfoGain, mRMR, ANOVA, and Chi Square, were used to uncover genomic markers associated with AD response. Relevant genes were selected based on Jaccard distance and carried forward for gene-network analysis. Linear association methods uncovered only one gene associated with drug treatment response. The implementation of ML algorithms, together with feature reduction methods, revealed a set of 204 genes associated with SSRI and 241 genes associated with NRI response. Although only 10% of genes overlapped across the two drugs, network analysis shows that both drugs modulated the CREB pathway, through different molecular mechanisms. Through careful implementation and optimisations, the algorithms detected a weak signal used to predict whether an animal was treated with nortriptyline (77%) or escitalopram (67%) on an independent testing set. The results from this study indicate that the molecular signature of AD treatment may include a much broader range of genomic markers than previously hypothesized, suggesting that response to medication may be as complex as the pathology. The search for biomarkers of antidepressant treatment response could therefore consider a higher number of genetic markers and their interactions. Through predominately different molecular targets and mechanisms of action, the two drugs modulate the same Creb1 pathway which plays a key role in neurotrophic responses and in inflammatory processes. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

The relation between treatment outcome and efavirenz, atazanavir or lopinavir exposure in the NORTHIV trial of treatment-naïve HIV-1 infected patients.

PubMed

Josephson, Filip; Andersson, Maria C H; Flamholc, Leo; Gisslén, Magnus; Hagberg, Lars; Ormaasen, Vidar; Sönnerborg, Anders; Vesterbacka, Jan; Böttiger, Ylva

2010-04-01

The relation between treatment outcome and trough plasma concentrations of efavirenz (EFV), atazanavir (ATV) and lopinavir (LPV) was studied in a pharmacokinetic/pharmacodynamic substudy of the NORTHIV trial-a randomised phase IV efficacy trial comparing antiretroviral-naïve human immunodeficiency virus-1-infected patients treated with (1) EFV + 2 nucleoside reverse transcriptase inhibitors (2NRTI) once daily, (2) ritonavir-boosted ATV + 2NRTI once daily or (3) ritonavir-boosted LPV + 2NRTI twice daily. The findings were related to the generally cited minimum effective concentration levels for the respective drugs (EFV 1,000 ng/ml, ATV 150 ng/ml, LPV 1,000 ng/ml). The relation between atazanavir-induced hyperbilirubinemia and virological efficacy was also studied. Drug concentrations were sampled at weeks 4 and 48 and optionally at week 12 and analysed by high-performance liquid chromatography with UV detector. When necessary, trough values were imputed by assuming the reported average half-lives for the respective drugs. Outcomes up to week 48 are reported. No relation between plasma concentrations of EFV, ATV or LPV and virological failure, treatment withdrawal due to adverse effects or antiviral potency (viral load decline from baseline to week 4) was demonstrated. Very few samples were below the suggested minimum efficacy cut-offs, and their predictive value for treatment failure could not be validated. There was a trend toward an increased risk of virological failure in patients on ATV who had an average increase of serum bilirubin from baseline of <25 micromol/l. The great majority of treatment-naïve and adherent patients on standard doses of EFV, ritonavir-boosted ATV and ritonavir-boosted LPV have drug concentrations above that considered to deliver the maximum effect for the respective drug. The results do not support the use of routine therapeutic drug monitoring (TDM) for efficacy optimisation in treatment-naïve patients on these drugs, although TDM may still be of value in some cases of altered pharmacokinetics, adverse events or drug interactions. Serum bilirubin may be a useful marker of adherence to ATV therapy.

Multi-objective optimisation and decision-making of space station logistics strategies

NASA Astrophysics Data System (ADS)

Zhu, Yue-he; Luo, Ya-zhong

2016-10-01

Space station logistics strategy optimisation is a complex engineering problem with multiple objectives. Finding a decision-maker-preferred compromise solution becomes more significant when solving such a problem. However, the designer-preferred solution is not easy to determine using the traditional method. Thus, a hybrid approach that combines the multi-objective evolutionary algorithm, physical programming, and differential evolution (DE) algorithm is proposed to deal with the optimisation and decision-making of space station logistics strategies. A multi-objective evolutionary algorithm is used to acquire a Pareto frontier and help determine the range parameters of the physical programming. Physical programming is employed to convert the four-objective problem into a single-objective problem, and a DE algorithm is applied to solve the resulting physical programming-based optimisation problem. Five kinds of objective preference are simulated and compared. The simulation results indicate that the proposed approach can produce good compromise solutions corresponding to different decision-makers' preferences.

Cultural-based particle swarm for dynamic optimisation problems

NASA Astrophysics Data System (ADS)

Daneshyari, Moayed; Yen, Gary G.

2012-07-01

Many practical optimisation problems are with the existence of uncertainties, among which a significant number belong to the dynamic optimisation problem (DOP) category in which the fitness function changes through time. In this study, we propose the cultural-based particle swarm optimisation (PSO) to solve DOP problems. A cultural framework is adopted incorporating the required information from the PSO into five sections of the belief space, namely situational, temporal, domain, normative and spatial knowledge. The stored information will be adopted to detect the changes in the environment and assists response to the change through a diversity-based repulsion among particles and migration among swarms in the population space, and also helps in selecting the leading particles in three different levels, personal, swarm and global levels. Comparison of the proposed heuristics over several difficult dynamic benchmark problems demonstrates the better or equal performance with respect to most of other selected state-of-the-art dynamic PSO heuristics.

A shrinking hypersphere PSO for engineering optimisation problems

NASA Astrophysics Data System (ADS)

Yadav, Anupam; Deep, Kusum

2016-03-01

Many real-world and engineering design problems can be formulated as constrained optimisation problems (COPs). Swarm intelligence techniques are a good approach to solve COPs. In this paper an efficient shrinking hypersphere-based particle swarm optimisation (SHPSO) algorithm is proposed for constrained optimisation. The proposed SHPSO is designed in such a way that the movement of the particle is set to move under the influence of shrinking hyperspheres. A parameter-free approach is used to handle the constraints. The performance of the SHPSO is compared against the state-of-the-art algorithms for a set of 24 benchmark problems. An exhaustive comparison of the results is provided statistically as well as graphically. Moreover three engineering design problems namely welded beam design, compressed string design and pressure vessel design problems are solved using SHPSO and the results are compared with the state-of-the-art algorithms.

Achieving optimal SERS through enhanced experimental design

PubMed Central

Fisk, Heidi; Westley, Chloe; Turner, Nicholas J.

2016-01-01

One of the current limitations surrounding surface‐enhanced Raman scattering (SERS) is the perceived lack of reproducibility. SERS is indeed challenging, and for analyte detection, it is vital that the analyte interacts with the metal surface. However, as this is analyte dependent, there is not a single set of SERS conditions that are universal. This means that experimental optimisation for optimum SERS response is vital. Most researchers optimise one factor at a time, where a single parameter is altered first before going onto optimise the next. This is a very inefficient way of searching the experimental landscape. In this review, we explore the use of more powerful multivariate approaches to SERS experimental optimisation based on design of experiments and evolutionary computational methods. We particularly focus on colloidal‐based SERS rather than thin film preparations as a result of their popularity. © 2015 The Authors. Journal of Raman Spectroscopy published by John Wiley & Sons, Ltd. PMID:27587905

Microfluidic converging/diverging channels optimised for homogeneous extensional deformation.

PubMed

Zografos, K; Pimenta, F; Alves, M A; Oliveira, M S N

2016-07-01

In this work, we optimise microfluidic converging/diverging geometries in order to produce constant strain-rates along the centreline of the flow, for performing studies under homogeneous extension. The design is examined for both two-dimensional and three-dimensional flows where the effects of aspect ratio and dimensionless contraction length are investigated. Initially, pressure driven flows of Newtonian fluids under creeping flow conditions are considered, which is a reasonable approximation in microfluidics, and the limits of the applicability of the design in terms of Reynolds numbers are investigated. The optimised geometry is then used for studying the flow of viscoelastic fluids and the practical limitations in terms of Weissenberg number are reported. Furthermore, the optimisation strategy is also applied for electro-osmotic driven flows, where the development of a plug-like velocity profile allows for a wider region of homogeneous extensional deformation in the flow field.

Topology Optimisation of Wideband Coaxial-to-Waveguide Transitions

NASA Astrophysics Data System (ADS)

Hassan, Emadeldeen; Noreland, Daniel; Wadbro, Eddie; Berggren, Martin

2017-03-01

To maximize the matching between a coaxial cable and rectangular waveguides, we present a computational topology optimisation approach that decides for each point in a given domain whether to hold a good conductor or a good dielectric. The conductivity is determined by a gradient-based optimisation method that relies on finite-difference time-domain solutions to the 3D Maxwell’s equations. Unlike previously reported results in the literature for this kind of problems, our design algorithm can efficiently handle tens of thousands of design variables that can allow novel conceptual waveguide designs. We demonstrate the effectiveness of the approach by presenting optimised transitions with reflection coefficients lower than -15 dB over more than a 60% bandwidth, both for right-angle and end-launcher configurations. The performance of the proposed transitions is cross-verified with a commercial software, and one design case is validated experimentally.

Topology Optimisation of Wideband Coaxial-to-Waveguide Transitions.

PubMed

Hassan, Emadeldeen; Noreland, Daniel; Wadbro, Eddie; Berggren, Martin

2017-03-23

To maximize the matching between a coaxial cable and rectangular waveguides, we present a computational topology optimisation approach that decides for each point in a given domain whether to hold a good conductor or a good dielectric. The conductivity is determined by a gradient-based optimisation method that relies on finite-difference time-domain solutions to the 3D Maxwell's equations. Unlike previously reported results in the literature for this kind of problems, our design algorithm can efficiently handle tens of thousands of design variables that can allow novel conceptual waveguide designs. We demonstrate the effectiveness of the approach by presenting optimised transitions with reflection coefficients lower than -15 dB over more than a 60% bandwidth, both for right-angle and end-launcher configurations. The performance of the proposed transitions is cross-verified with a commercial software, and one design case is validated experimentally.

Strategic optimisation of microgrid by evolving a unitised regenerative fuel cell system operational criterion

NASA Astrophysics Data System (ADS)

Bhansali, Gaurav; Singh, Bhanu Pratap; Kumar, Rajesh

2016-09-01

In this paper, the problem of microgrid optimisation with storage has been addressed in an unaccounted way rather than confining it to loss minimisation. Unitised regenerative fuel cell (URFC) systems have been studied and employed in microgrids to store energy and feed it back into the system when required. A value function-dependent on line losses, URFC system operational cost and stored energy at the end of the day are defined here. The function is highly complex, nonlinear and multi dimensional in nature. Therefore, heuristic optimisation techniques in combination with load flow analysis are used here to resolve the network and time domain complexity related with the problem. Particle swarm optimisation with the forward/backward sweep algorithm ensures optimal operation of microgrid thereby minimising the operational cost of the microgrid. Results are shown and are found to be consistently improving with evolution of the solution strategy.

Optimal design and operation of a photovoltaic-electrolyser system using particle swarm optimisation

NASA Astrophysics Data System (ADS)

Sayedin, Farid; Maroufmashat, Azadeh; Roshandel, Ramin; Khavas, Sourena Sattari

2016-07-01

In this study, hydrogen generation is maximised by optimising the size and the operating conditions of an electrolyser (EL) directly connected to a photovoltaic (PV) module at different irradiance. Due to the variations of maximum power points of the PV module during a year and the complexity of the system, a nonlinear approach is considered. A mathematical model has been developed to determine the performance of the PV/EL system. The optimisation methodology presented here is based on the particle swarm optimisation algorithm. By this method, for the given number of PV modules, the optimal sizeand operating condition of a PV/EL system areachieved. The approach can be applied for different sizes of PV systems, various ambient temperatures and different locations with various climaticconditions. The results show that for the given location and the PV system, the energy transfer efficiency of PV/EL system can reach up to 97.83%.

Assessment of grid optimisation measures for the German transmission grid using open source grid data

NASA Astrophysics Data System (ADS)

Böing, F.; Murmann, A.; Pellinger, C.; Bruckmeier, A.; Kern, T.; Mongin, T.

2018-02-01

The expansion of capacities in the German transmission grid is a necessity for further integration of renewable energy sources into the electricity sector. In this paper, the grid optimisation measures ‘Overhead Line Monitoring’, ‘Power-to-Heat’ and ‘Demand Response in the Industry’ are evaluated and compared against conventional grid expansion for the year 2030. Initially, the methodical approach of the simulation model is presented and detailed descriptions of the grid model and the used grid data, which partly originates from open-source platforms, are provided. Further, this paper explains how ‘Curtailment’ and ‘Redispatch’ can be reduced by implementing grid optimisation measures and how the depreciation of economic costs can be determined considering construction costs. The developed simulations show that the conventional grid expansion is more efficient and implies more grid relieving effects than the evaluated grid optimisation measures.

Topology Optimisation of Wideband Coaxial-to-Waveguide Transitions

PubMed Central

Hassan, Emadeldeen; Noreland, Daniel; Wadbro, Eddie; Berggren, Martin

2017-01-01

To maximize the matching between a coaxial cable and rectangular waveguides, we present a computational topology optimisation approach that decides for each point in a given domain whether to hold a good conductor or a good dielectric. The conductivity is determined by a gradient-based optimisation method that relies on finite-difference time-domain solutions to the 3D Maxwell’s equations. Unlike previously reported results in the literature for this kind of problems, our design algorithm can efficiently handle tens of thousands of design variables that can allow novel conceptual waveguide designs. We demonstrate the effectiveness of the approach by presenting optimised transitions with reflection coefficients lower than −15 dB over more than a 60% bandwidth, both for right-angle and end-launcher configurations. The performance of the proposed transitions is cross-verified with a commercial software, and one design case is validated experimentally. PMID:28332585

VLSI Technology for Cognitive Radio

NASA Astrophysics Data System (ADS)

VIJAYALAKSHMI, B.; SIDDAIAH, P.

2017-08-01

One of the most challenging tasks of cognitive radio is the efficiency in the spectrum sensing scheme to overcome the spectrum scarcity problem. The popular and widely used spectrum sensing technique is the energy detection scheme as it is very simple and doesn’t require any previous information related to the signal. We propose one such approach which is an optimised spectrum sensing scheme with reduced filter structure. The optimisation is done in terms of area and power performance of the spectrum. The simulations of the VLSI structure of the optimised flexible spectrum is done using verilog coding by using the XILINX ISE software. Our method produces performance with 13% reduction in area and 66% reduction in power consumption in comparison to the flexible spectrum sensing scheme. All the results are tabulated and comparisons are made. A new scheme for optimised and effective spectrum sensing opens up with our model.

Achieving optimal SERS through enhanced experimental design.

PubMed

Fisk, Heidi; Westley, Chloe; Turner, Nicholas J; Goodacre, Royston

2016-01-01

One of the current limitations surrounding surface-enhanced Raman scattering (SERS) is the perceived lack of reproducibility. SERS is indeed challenging, and for analyte detection, it is vital that the analyte interacts with the metal surface. However, as this is analyte dependent, there is not a single set of SERS conditions that are universal. This means that experimental optimisation for optimum SERS response is vital. Most researchers optimise one factor at a time, where a single parameter is altered first before going onto optimise the next. This is a very inefficient way of searching the experimental landscape. In this review, we explore the use of more powerful multivariate approaches to SERS experimental optimisation based on design of experiments and evolutionary computational methods. We particularly focus on colloidal-based SERS rather than thin film preparations as a result of their popularity. © 2015 The Authors. Journal of Raman Spectroscopy published by John Wiley & Sons, Ltd.

Optimisation of decentralisation for effective Disaster Risk Reduction (DRR) through the case study of Indonesia

NASA Astrophysics Data System (ADS)

Grady, A.; Makarigakis, A.; Gersonius, B.

2015-09-01

This paper investigates how to optimise decentralisation for effective disaster risk reduction (DRR) in developing states. There is currently limited literature on empirical analysis of decentralisation for DRR. This paper evaluates decentralised governance for DRR in the case study of Indonesia and provides recommendations for its optimisation. Wider implications are drawn to optimise decentralisation for DRR in developing states more generally. A framework to evaluate the institutional and policy setting was developed which necessitated the use of a gap analysis, desk study and field investigation. Key challenges to decentralised DRR include capacity gaps at lower levels, low compliance with legislation, disconnected policies, issues in communication and coordination and inadequate resourcing. DRR authorities should lead coordination and advocacy on DRR. Sustainable multistakeholder platforms and civil society organisations should fill the capacity gap at lower levels. Dedicated and regulated resources for DRR should be compulsory.