Performance monitoring of energy efficient retrofits – 4 case study properties in Northern Ireland

Approximately half of the houses in Northern Ireland were built before any form of minimum thermal specification (U-value) or energy efficiency standard were available. At present, 44% of households are categorised as being in fuel poverty; spending more than 10% of the household income to heat the house to an acceptable level. This paper presents the results from long term performance monitoring of 4 case study houses that have undergone retrofits to improve energy efficiency in Northern Ireland. There is some uncertainty associated with some of the marketed retrofit measures in terms of their effectiveness in reducing energy usage and their potential to cause detrimental impacts on the internal environment of a house. Using wireless sensor technology internal conditions such as temperature and humidity were measured alongside gas and electricity usage for a year. External weather conditions were also monitored. The paper considers the effectiveness of the different retrofit measures implemented based on the long term data monitoring and short term building performance evaluation tests that were completed.

Celecoxib plus hormone therapy versus hormone therapy alone for hormone-sensitive prostate cancer: first results from the STAMPEDE multiarm, multistage, randomised controlled trial

BACKGROUND:
Long-term hormone therapy alone is standard care for metastatic or high-risk, non-metastatic prostate cancer. STAMPEDE--an international, open-label, randomised controlled trial--uses a novel multiarm, multistage design to assess whether the early additional use of one or two drugs (docetaxel, zoledronic acid, celecoxib, zoledronic acid and docetaxel, or zoledronic acid and celecoxib) improves survival in men starting first-line, long-term hormone therapy. Here, we report the preplanned, second intermediate analysis comparing hormone therapy plus celecoxib (arm D) with hormone therapy alone (control arm A).
METHODS:
Eligible patients were men with newly diagnosed or rapidly relapsing prostate cancer who were starting long-term hormone therapy for the first time. Hormone therapy was given as standard care in all trial arms, with local radiotherapy encouraged for newly diagnosed patients without distant metastasis. Randomisation was done using minimisation with a random element across seven stratification factors. Patients randomly allocated to arm D received celecoxib 400 mg twice daily, given orally, until 1 year or disease progression (including prostate-specific antigen [PSA] failure). The intermediate outcome was failure-free survival (FFS) in three activity stages; the primary outcome was overall survival in a subsequent efficacy stage. Research arms were compared pairwise against the control arm on an intention-to-treat basis. Accrual of further patients was discontinued in any research arm showing safety concerns or insufficient evidence of activity (lack of benefit) compared with the control arm. The minimum targeted activity at the second intermediate activity stage was a hazard ratio (HR) of 0·92. This trial is registered with ClinicalTrials.gov, number NCT00268476, and with Current Controlled Trials, number ISRCTN78818544.
FINDINGS:
2043 patients were enrolled in the trial from Oct 17, 2005, to Jan 31, 2011, of whom 584 were randomly allocated to receive hormone therapy alone (control group; arm A) and 291 to receive hormone therapy plus celecoxib (arm D). At the preplanned analysis of the second intermediate activity stage, with 305 FFS events (209 in arm A, 96 in arm D), there was no evidence of an advantage for hormone therapy plus celecoxib over hormone therapy alone: HR 0·94 (95% CI 0·74-1·20). [corrected]. 2-year FFS was 51% (95% CI 46-56) in arm A and 51% (95% CI 43-58) in arm D. There was no evidence of differences in the incidence of adverse events between groups (events of grade 3 or higher were noted at any time in 123 [23%, 95% CI 20-27] patients in arm A and 64 [25%, 19-30] in arm D). The most common grade 3-5 events adverse effects in both groups were endocrine disorders (55 [11%] of patients in arm A vs 19 [7%] in arm D) and musculoskeletal disorders (30 [6%] of patients in arm A vs 15 [6%] in arm D). The independent data monitoring committee recommended stopping accrual to both celecoxib-containing arms on grounds of lack of benefit and discontinuing celecoxib for patients currently on treatment, which was endorsed by the trial steering committee.
INTERPRETATION:
Celecoxib 400 mg twice daily for up to 1 year is insufficiently active in patients starting hormone therapy for high-risk prostate cancer, and we do not recommend its use in this setting. Accrual continues seamlessly to the other research arms and follow-up of all arms will continue to assess effects on overall survival.

Vosaroxin and vosaroxin plus low-dose Ara-C (LDAC) vs low-dose Ara-C alone in older patients with acute myeloid leukemia

The development of new treatments for older patients with acute myeloid leukemia is an active area, but has met with limited success. Vosaroxin, a quinolone-derived intercalating agent has several properties that could prove beneficial. Initial clinical studies showed it to be well-tolerated in older patients with relapsed/refractory disease. In vitro data suggested synergy with cytarabine (Ara-C). To evaluate vosaroxin, we performed 2 randomized comparisons within the "Pick a Winner" program. A total of 104 patients were randomized to vosaroxin vs low-dose Ara-C (LDAC) and 104 to vosaroxin + LDAC vs LDAC. When comparing vosaroxin with LDAC, neither response rate (complete recovery [CR]/complete recovery with incomplete count recovery [CRi], 26% vs 30%; odds ratio [OR], 1.16 (0.49-2.72); P = .7) nor 12-month survival (12% vs 31%; hazard ratio [HR], 1.94 [1.26-3.00]; P = .003) showed benefit for vosaroxin. Likewise, in the vosaroxin + LDAC vs LDAC comparison, neither response rate (CR/CRi, 38% vs 34%; OR, 0.83 [0.37-1.84]; P = .6) nor survival (33% vs 37%; HR, 1.30 [0.81-2.07]; P = .3) was improved. A major reason for this lack of benefit was excess early mortality in the vosaroxin + LDAC arm, most obviously in the second month following randomization. At its first interim analysis, the Data Monitoring and Ethics Committee recommended closure of the vosaroxin-containing trial arms because a clinically relevant benefit was unlikely.

Epirubicin, oxaliplatin, and capecitabine with or without panitumumab for patients with previously untreated advanced oesophagogastric cancer (REAL3): a randomised, open-label phase 3 trial.

BACKGROUND: EGFR overexpression occurs in 27-55% of oesophagogastric adenocarcinomas, and correlates with poor prognosis. We aimed to assess addition of the anti-EGFR antibody panitumumab to epirubicin, oxaliplatin, and capecitabine (EOC) in patients with advanced oesophagogastric adenocarcinoma. METHODS: In this randomised, open-label phase 3 trial (REAL3), we enrolled patients with untreated, metastatic, or locally advanced oesophagogastric adenocarcinoma at 63 centres (tertiary referral centres, teaching hospitals, and district general hospitals) in the UK. Eligible patients were randomly allocated (1:1) to receive up to eight 21-day cycles of open-label EOC (epirubicin 50 mg/m(2) and oxaliplatin 130 mg/m(2) on day 1 and capecitabine 1250 mg/m(2) per day on days 1-21) or modified-dose EOC plus panitumumab (mEOC+P; epirubicin 50 mg/m(2) and oxaliplatin 100 mg/m(2) on day 1, capecitabine 1000 mg/m(2) per day on days 1-21, and panitumumab 9 mg/kg on day 1). Randomisation was blocked and stratified for centre region, extent of disease, and performance status. The primary endpoint was overall survival in the intention-to-treat population. We assessed safety in all patients who received at least one dose of study drug. After a preplanned independent data monitoring committee review in October, 2011, trial recruitment was halted and panitumumab withdrawn. Data for patients on treatment were censored at this timepoint. This study is registered with ClinicalTrials.gov, number NCT00824785. FINDINGS: Between June 2, 2008, and Oct 17, 2011, we enrolled 553 eligible patients. Median overall survival in 275 patients allocated EOC was 11.3 months (95% CI 9.6-13.0) compared with 8.8 months (7.7-9.8) in 278 patients allocated mEOC+P (hazard ratio [HR] 1.37, 95% CI 1.07-1.76; p=0.013). mEOC+P was associated with increased incidence of grade 3-4 diarrhoea (48 [17%] of 276 patients allocated mEOC+P vs 29 [11%] of 266 patients allocated EOC), rash (29 [11%] vs two [1%]), mucositis (14 [5%] vs none), and hypomagnesaemia (13 [5%] vs none) but reduced incidence of haematological toxicity (grade ≥ 3 neutropenia 35 [13%] vs 74 [28%]). INTERPRETATION: Addition of panitumumab to EOC chemotherapy does not increase overall survival and cannot be recommended for use in an unselected population with advanced oesophagogastric adenocarcinoma. FUNDING: Amgen, UK National Institute for Health Research Biomedical Research Centre.

Improved Nonlinear PCA for Process Monitoring Using Support Vector Data Description

Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.

Multivariate analysis of regional-scale geochemical data for environmental monitoring

A compositional multivariate approach is used to analyse regional scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey Northern Ireland (GSNI). The multi-element total concentration data presented comprise XRF analyses of 6862 rural soil samples collected at 20cm depths on a non-aligned grid at one site per 2 km2. Censored data were imputed using published detection limits. Using these imputed values for 46 elements (including LOI), each soil sample site was assigned to the regional geology map provided by GSNI initially using the dominant lithology for the map polygon. Northern Ireland includes a diversity of geology representing a stratigraphic record from the Mesoproterozoic, up to and including the Palaeogene. However, the advance of ice sheets and their meltwaters over the last 100,000 years has left at least 80% of the bedrock covered by superficial deposits, including glacial till and post-glacial alluvium and peat. The question is to what extent the soil geochemistry reflects the underlying geology or superficial deposits. To address this, the geochemical data were transformed using centered log ratios (clr) to observe the requirements of compositional data analysis and avoid closure issues. Following this, compositional multivariate techniques including compositional Principal Component Analysis (PCA) and minimum/maximum autocorrelation factor (MAF) analysis method were used to determine the influence of underlying geology on the soil geochemistry signature. PCA showed that 72% of the variation was determined by the first four principal components (PC’s) implying “significant” structure in the data. Analysis of variance showed that only 10 PC’s were necessary to classify the soil geochemical data. To consider an improvement over PCA that uses the spatial relationships of the data, a classification based on MAF analysis was undertaken using the first 6 dominant factors. Understanding the relationship between soil geochemistry and superficial deposits is important for environmental monitoring of fragile ecosystems such as peat. To explore whether peat cover could be predicted from the classification, the lithology designation was adapted to include the presence of peat, based on GSNI superficial deposit polygons and linear discriminant analysis (LDA) undertaken. Prediction accuracy for LDA classification improved from 60.98% based on PCA using 10 principal components to 64.73% using MAF based on the 6 most dominant factors. The misclassification of peat may reflect degradation of peat covered areas since the creation of superficial deposit classification. Further work will examine the influence of underlying lithologies on elemental concentrations in peat composition and the effect of this in classification analysis.

Analysis of Extended Partial Least Squares for Monitoring Large-Scale Processes

This paper theoretically analysis the recently proposed "Extended Partial Least Squares" (EPLS) algorithm. After pointing out some conceptual deficiencies, a revised algorithm is introduced that covers the middle ground between Partial Least Squares and Principal Component Analysis. It maximises a covariance criterion between a cause and an effect variable set (partial least squares) and allows a complete reconstruction of the recorded data (principal component analysis). The new and conceptually simpler EPLS algorithm has successfully been applied in detecting and diagnosing various fault conditions, where the original EPLS algorithm did only offer fault detection.

Statistical Monitoring of Dynamic Multivariate Processes: Part II: Identifying Fault Magnitude and Signature

This paper builds on work presented in the first paper, Part 1 [1] and is of equal significance. The paper proposes a novel compensation method to preserve the integrity of step-fault signatures prevalent in various processes that can be masked during the removal of both auto- and cross correlation. Using industrial data, the paper demonstrates the benefit of the proposed method, which is applicable to chemical, electrical, and mechanical process monitoring. This paper, (and Part 1 [1]), has led to further work supported by EPSRC grant GR/S84354/01 involving kernel PCA methods.

Dynamic, in situ optical, magnetic and magneto-optical monitoring of the growth of Co/Au and Pd/Co/Au multilayer systems

The growth of magnetron sputtered Co/Au and Pd/Co/Au superlattices on Au and Pd buffer layers, deposited onto glass substrates, has been monitored optically and magneto-optically in real time, using rotating analyser ellipsometry and Kerr polarimetry, at a wavelength of 633 nm. The magneto-optical traces, combined with ex situ and in situ hysteresis loops, provide a detailed and informative fingerprint of the optical and magnetic properties of the films as they evolve during growth. For Co/Au, oscillations in the polar magneto-optical effect developed during the deposition of An overlayers on Co and these may be attributed to quantum well states. However, the hysteresis measurements show that the magnetic field required to maintain saturation magnetization throughout the experiment was larger than available in situ, introducing a degree of confusion concerning the interpretation of the data. This problem was overcome by the incorporation of Pd layers into the Co/Au structure, thereby eliminating variation in magnetic orientation during growth of the Au layers as a contributory factor to the observations.

Improved Process Monitoring Using Nonlinear Principal Component Models

This paper presents two new approaches for use in complete process monitoring. The firstconcerns the identification of nonlinear principal component models. This involves the application of linear
principal component analysis (PCA), prior to the identification of a modified autoassociative neural network (AAN) as the required nonlinear PCA (NLPCA) model. The benefits are that (i) the number of the reduced set of linear principal components (PCs) is smaller than the number of recorded process variables, and (ii) the set of PCs is better conditioned as redundant information is removed. The result is a new set of input data for a modified neural representation, referred to as a T2T network. The T2T NLPCA model is then used for complete process monitoring, involving fault detection, identification and isolation. The second approach introduces a new variable reconstruction algorithm, developed from the T2T NLPCA model. Variable reconstruction can enhance the findings of the contribution charts still widely used in industry by reconstructing the outputs from faulty sensors to produce more accurate fault isolation. These ideas are illustrated using recorded industrial data relating to developing cracks in an industrial glass melter process. A comparison of linear and nonlinear models, together with the combined use of contribution charts and variable reconstruction, is presented.

The design of a navigation guidance and control system for an unmanned surface vehicle for environmental monitoring

Maintaining the ecosystem is one of the main concerns in this modern age. With the fear of ever-increasing global warming, the UK is one of the key players to participate actively in taking measures to slow down at least its phenomenal rate. As an ingredient to this process, the Springer vehicle was designed and developed for environmental monitoring and pollutant tracking. This special issue paper highlighted the Springer hardware and software architecture including various navigational sensors, a speed controller, and an environmental monitoring unit. In addition, details regarding the modelling of the vessel were outlined based mainly on experimental data. The formulation of a fault tolerant multi-sensor data fusion technique was also presented. Moreover, control strategy based on a linear quadratic Gaussian controller was developed and simulated on the Springer model.
Gaussian controller is developed and simulated on the Springer model.

In situ cross-calibration of in-fibre Bragg Grating and Electrical Resistance Strain Gauges for structural monitoring using an extensometer

Special issue on Sensor Systems for Structural Health Monitoring Abstract—This study addresses the direct calibration of optical fiber strain sensors used for structural monitoring and is carried out in situ. The behavior of fiber-Bragg-grating-based sensor systems when attached to metal bars, in a manner representative of their use as reinforcement bars in structures, was examined and their response calibrated. To ensure the validity of the measurements,this was done using an extensometer with a further calibrationagainst the response of electrical resistance strain gauges, often conventionally used, for comparison. The results show a repeatable calibration generating a suitable geometric factor of extension to strain for these sensors, to enable accurate strain data to be obtained when the fiber-optic sensor system is in use in structural monitoring applications.