Completeness and timeliness: Cancer registries could/should improve their performance

Cancer registries must provide complete and reliable incidence information with the shortest possible delay for use in studies such as comparability, clustering, cancer in the elderly and adequacy of cancer surveillance. Methods of varying complexity are available to registries for monitoring completeness and timeliness. We wished to know which methods are currently in use among cancer registries, and to compare the results of our findings to those of a survey carried out in 2006.

Methods
In the framework of the EUROCOURSE project, and to prepare cancer registries for participation in the ERA-net scheme, we launched a survey on the methods used to assess completeness, and also on the timeliness and methods of dissemination of results by registries. We sent the questionnaire to all general registries (GCRs) and specialised registries (SCRs) active in Europe and within the European Network of Cancer Registries (ENCR).

Results
With a response rate of 66% among GCRs and 59% among SCRs, we obtained data for analysis from 116 registries with a population coverage of ∼280 million. The most common methods used were comparison of trends (79%) and mortality/incidence ratios (more than 60%). More complex methods were used less commonly: capture–recapture by 30%, flow method by 18% and death certificate notification (DCN) methods with the Ajiki formula by 9%.

The median latency for completion of ascertainment of incidence was 18 months. Additional time required for dissemination was of the order of 3–6 months, depending on the method: print or electronic. One fifth (21%) did not publish results for their own registry but only as a contribution to larger national or international data repositories and publications; this introduced a further delay in the availability of data.

Conclusions
Cancer registries should improve the practice of measuring their completeness regularly and should move from traditional to more quantitative methods. This could also have implications in the timeliness of data publication.

Encouraging children to think counterfactually enhances blocking in a causal learning task

According to a higher order reasoning account, inferential reasoning processes underpin the widely observed cue competition effect of blocking in causal learning. The inference required for blocking has been described as modus tollens (if p then q, not q therefore not p). Young children are known to have difficulties with this type of inference, but research with adults suggests that this inference is easier if participants think counterfactually. In this study, 100 children (51 five-year-olds and 49 six- to seven-year-olds) were assigned to two types of pretraining groups. The counterfactual group observed demonstrations of cues paired with outcomes and answered questions about what the outcome would have been if the causal status of cues had been different, whereas the factual group answered factual questions about the same demonstrations. Children then completed a causal learning task. Counterfactual pretraining enhanced levels of blocking as well as modus tollens reasoning but only for the younger children. These findings provide new evidence for an important role for inferential reasoning in causal learning.

Blocking in children's causal learning depends on working memory and reasoning abilities.

A sample of 99 children completed a causal learning task that was an analogue of the food allergy paradigm used with adults. The cue competition effects of blocking and unovershadowing were assessed under forward and backward presentation conditions. Children also answered questions probing their ability to make the inference posited to be necessary for blocking by a reasoning account of cue competition. For the first time, children's working memory and general verbal ability were also measured alongside their causal learning. The magnitude of blocking and unovershadowing effects increased with age. However, analyses showed that the best predictor of both blocking and unovershadowing effects was children's performance on the reasoning questions. The magnitude of the blocking effect was also predicted by children's working memory abilities. These findings provide new evidence that cue competition effects such as blocking are underpinned by effortful reasoning processes. 

INTERPLAY OF CAF2 SUBSTRATE ROUGHENING AND FILM DEPOSITION RATE ON RADIATIVE SCATTERING OF SURFACE-PLASMON POLARITONS FROM AG FILMS

The radiative decay of surface plasmon polaritons has been investigated in an attempt to characterize the surface roughness of Ag films prepared under different conditions. The polaritons were excited by the method of attenuated total reflection of light. The films were deposited on the face of a 60-degrees BK-7 glass prism at a rate that was deliberately fixed in two different ranges (centred on 0.1 and 10 nm s-1) and in some cases a CaF2 underlayer was used to roughen the film surfaces. The intensity of the scattered light emitted from the opposite face of the films was measured as a function of direction for each using the same sensitivity scale and was correlated with the preparation of the film. It was found that on nominally smooth substrates fast-deposited thinner films give out more light and are deduced to have greater short wavelength (300-600 nm) roughness amplitude. There is also evidence for long wavelenth (7 mum) periodic roughness due to the prism substrate itself. On CaF2 roughened surfaces the light output from the films is further increased and the peak intensity is backward directed with respect to the exciting laser beam direction. Here roughness on a lateral scale of 350 nm is responsible. Also, elastic scattering of surface plasmon polaritons at grain boundaries reduces the light output from fast deposited, small grain, films on CaF2 roughened surfaces. Overall, a consistent picture of roughness induced radiative polariton decay emerges for all cases studied.

Cyclic nanoindentation and nano-impact fatigue characterisation of functionally graded TiN/TiNi shape memory film

This paper investigates the mechanism of nanoscale fatigue of functionally graded TiN/TiNi films using nano-impact and multiple-loading-cycle nanoindentation tests. The functionally graded films were deposited on silicon substrate, in which TiNi films maintain shape memory and pseudo elastic behavior, while a modified TiN surface layer provides tribological and anti-corrosion properties. Nanomechanical tests were performed to comprehend the localized film performance and failure modes of the functionally graded film using NanoTestTM equipped with Berkovich and conical indenter between 100 μN to 500 mN loads. The loading mechanism and load history are critical to define film failure modes (i.e. backward depth deviation) including the shape memory effect of the functionally graded layer. The results are sensitive to the applied load, loading type (e.g. semi-static, dynamic) and probe geometry. Based on indentation force-depth profiles, depth-time data and post-test surface observations of films, it is concluded that the shape of the nanoindenter is critical in inducing the localized indentation stress and film failure, including shape recovery at the lower load range. Elastic-plastic finite element (FE) simulation during nanoindentation loading indicated that the location of subsurface maximum stress near the interface influences the backward depth deviation type of film failure. A standalone, molecular dynamics simulation was performed with the help of a long range potential energy function to simulate the tensile test of TiN nanowire with two different aspect ratios to investigate the theory of its failure mechanism.

Domestic fridge-freezer load aggregation to support ancillary services

Grid operators and electricity retailers in Ireland manage peak demand, power system balancing and grid congestion by offering relevant incentives to consumers to reduce or shift their load. The need for active consumers in the home using smart appliances has never been greater, due to increased variable renewable generation and grid constraints. In this paper an aggregated model of a single compressor fridge-freezer population is developed. A price control strategy is examined to quantify and value demand response savings during a representative winter and summer week for Ireland in 2020. The results show an average reduction in fridge-freezer operating cost of 8.2% during winter and significantly lower during summer in Ireland. A peak reduction of at least 68% of the average winter refrigeration load is achieved consistently during the week analysed using a staggering control mode. An analysis of the current ancillary service payments confirms that these are insufficient to ensure widespread uptake by the small consumer, and new mechanisms need to be developed to make becoming an active consumer attractive. Demand response is proposed as a new ancillary service called ramping capability, as the need for this service will increase with more renewable energy penetration on the power system.

Facilities management: Tracing its development trajectory

Purpose – The purpose of this paper is to provide facilities management (FM) practitioners and researchers with a better understanding of the FM industry sector by analyzing the trend of its development.
Design/methodology/approach – Semi-structured interview is adopted in this research as the main methodology. In total, 30 FM professionals in the UK were interviewed to explore the past, present and future of FM. The analysis of interview results helps to identify the key areas in which FM has changed, is changing and will change. It also helps to explain the implications of FM development in each key area.
Findings – FM evolves and matures continuously. It is important for FM organizations and practitioners to recognize the dynamic nature of this industry sector, based on which they can develop appropriate strategies to adapt to changing circumstances. This is probably the only way for them to
keep pace with the times.
Originality/value – Both backward looking and forward looking are crucial to the development of an industry sector. However, existing studies on FM development are conducted through either review or outlook. On the other hand, most of these studies focus on one particular management area or one particular industry sector. Based on 30 expert interviews, this research attempts to bridge the knowledge gap and analyze the trend of FM development in a systematic way. A better understanding of the trend provides a possibility and a guide for FM organizations and practitioners to pursue best practice.

An Efficient LS-SVM-Based Method for Fuzzy System Construction

This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.

Urban high-density construction sites and their surrounding community:issues encountered and strategiesadopted by contractors

Inner city developments are a common feature within many urban environments. Where these construction sites are not managed effectively, they can negatively impact their surrounding community. The aim of this paper is to identify and document, in an urban context, the numerous issues encounter and subsequent strategies adopted by on-site contractors and local people, in the mitigation of factors which negatively impact their surrounding community. The objectives in achieving this aim are to identify what effect, if any, an urban construction site has on its surrounding environment, the issues and resulting strategies adopted by contractors on the factors identified, and also what measures are put in place to minimise such disturbances to the local community. In order to meet the requirements, a mixed methodology is adopted culminating in a literature review, case study analysis, contractor and community interviews, concluding in the development of two specific questions for both perspectives in question. The data is assessed using severity indices based on mean testing in the development of key findings. The results indicate that the main forms of disturbance to the local community from an urban development include noise, dust and traffic congestion. With respect to a contractor on-site, the key issues include damaging surrounding buildings, noise control and off-site parking. The resulting strategies identified in the mitigation of such issues include the implementation of noise and dust containment measures and minimising disruption to local infrastructure. It is envisaged that the results of this study will provide contractors operating in such environments, with the required information which can assist in minimising disruption and therefore, avoiding disputes with the local community members. By consulting with and surveying those most affected, this research will illustrate to on-site management, the difficulties faced by those who accommodate such developments within their living environment.

Two-Stage Orthogonal Least Squares Methods for Neural Network Construction

A number of neural networks can be formulated as the linear-in-the-parameters models. Training such networks can be transformed to a model selection problem where a compact model is selected from all the candidates using subset selection algorithms. Forward selection methods are popular fast subset selection approaches. However, they may only produce suboptimal models and can be trapped into a local minimum. More recently, a two-stage fast recursive algorithm (TSFRA) combining forward selection and backward model refinement has been proposed to improve the compactness and generalization performance of the model. This paper proposes unified two-stage orthogonal least squares methods instead of the fast recursive-based methods. In contrast to the TSFRA, this paper derives a new simplified relationship between the forward and the backward stages to avoid repetitive computations using the inherent orthogonal properties of the least squares methods. Furthermore, a new term exchanging scheme for backward model refinement is introduced to reduce computational demand. Finally, given the error reduction ratio criterion, effective and efficient forward and backward subset selection procedures are proposed. Extensive examples are presented to demonstrate the improved model compactness constructed by the proposed technique in comparison with some popular methods.

Kernel based approaches to local nonlinear non-parametric variable selection

In this paper, we consider the variable selection problem for a nonlinear non-parametric system. Two approaches are proposed, one top-down approach and one bottom-up approach. The top-down algorithm selects a variable by detecting if the corresponding partial derivative is zero or not at the point of interest. The algorithm is shown to have not only the parameter but also the set convergence. This is critical because the variable selection problem is binary, a variable is either selected or not selected. The bottom-up approach is based on the forward/backward stepwise selection which is designed to work if the data length is limited. Both approaches determine the most important variables locally and allow the unknown non-parametric nonlinear system to have different local dimensions at different points of interest. Further, two potential applications along with numerical simulations are provided to illustrate the usefulness of the proposed algorithms.

The prognostic and therapeutic value of EpHA2 in early colorectal cancer (CRC).

Background: EpHA2 is a 130 kD transmembrane glycoprotein belonging to ephrin receptor subfamily and involved in angiogenesis/tumour neovascularisation. High EpHA2 mRNA level has recently been implicated in cetuximab resistance. Previously, we found high EpHA2 levels in a panel of invasive colorectal cancer (CRC) cells, which was associated with high levels of stem-cell marker CD44. Our aim was to investigate the prognostic value of EpHA2 and subsequently correlate expression levels to known clinico-pathological variables in early stage CRC. Methods: Tissue samples from 509 CRC patients were analysed. EpHA2 expression was measured using IHC. Kaplan-Meier graphs were used. Univariate and multivariate analyses employed Cox Proportional Hazards Ratio (HR) method. A backward selection method (Akaike’s information criterion) was used to determine a refined multivariate model. Results: EpHA2 was highly expressed in CRC adenocarcinoma compared to matched normal colon tissue. In support of our preclinical invasive models, strong correlation was found between EpHA2 expression and CD44 and Lgr5 staining (p<0.001). In addition, high EpHA2 expression significantly correlated with vascular invasion (p=0.03).HR for OS for stage II/III patients with high EpHA2 expression was 1.69 (95%CI: 1.164-2.439; p=0.003). When stage II/III was broken down into individual stages, there was significant correlation between high EpHA2 expression and poor 5-years OS in stage II patients (HR: 2.18; 95%CI: 1.28-3.71; p=0.005).HR in the stage III group showed a trend to statistical significance (HR: 1.48; 95%CI=0.87-2.51; p=0.05). In both univariate and multivariate analyses of stage II patients, high EpHA2 expression was the only significant factor and was retained in the final multivariate model. Higher levels of EpHA2 were noted in our RAS and BRAF mutant CRC cells, and silencing EpHA2 resulted in significant decreases in migration/invasion in parental and invasive CRC sublines. Correlation between KRAS/NRAS/BRAFmutational status and EpHA2 expression in clinical samples is ongoing. Conclusions: Taken together, our study is the first to indicate that EpHA2 expression is a predictor of poor clinical outcome and a potential novel target in early stage CRC.

Public health risk communication by text message in response to a cluster of invasive meningococcal infection in a primary school

Public health risk communication during emergencies should be rapid and accurate in order to allow the audience to take steps to prevent adverse outcomes. Delays to official communications may cause unnecessary anxiety due to uncertainty or inaccurate information circulating within the at-risk group. Modern electronic communications present opportunities for rapid, targeted public health risk communication. We present a case report of a cluster of invasive meningococcal disease in a primary school in which we used the school's mass short message service (SMS) text message system to inform parents and guardians of pupils about the incident, to tell them that chemoprophylaxis would be offered to all pupils and staff, and to advise them when to attend the school to obtain further information and antibiotics. Following notification to public health on a Saturday, an incident team met on Sunday, sent the SMS messages that afternoon, and administered chemoprophyaxis to 93% of 404 pupils on Monday. The use of mass SMS messages enabled rapid communication from an official source and greatly aided the public health response to the cluster.

Remembering forwards: or how to live together in the future with divided memories

Memory is thought to be about the past. The past is a problem in conflict transformation. This lecture suggests memory can also be about the future. It introduces the notion of remembering forwards, which is contrasted with remembering backwards. The distinction between these two forms of remembering defines the burden of memory in post-conflict societies generally and specifically in Ireland. In societies emerging out of conflict, where divided memories in part constituted the conflict, social memory privileges remembering backward. Collective and personal memories elide within social memory to perpetuate divided group identities and contested personal narratives. Above all, social memory works to arbitrate the future, by predisposing an extreme memory culture that locks people into the past. Forgetting the past is impossible and undesirable. What is needed in societies emerging out of conflict is to be released from the hold that oppressive and haunting memories have over people. This lecture will suggest that this is found in the idea of remembering forwards. This is not the same as forgetting. It is remembering to cease to remember oppressive and haunting memories. It does not involve non-remembrance but active remembering: remembering to cease to remember the past. While the past lives in us always, remembering forwards assists us in not living in the past. Remembering forwards thus allows us to live in tolerance in the future despite the reality that divided memories endure and live on. The lecture further argues that these enduring divided memories need to be reimagined by the application of truth, tolerance, togetherness and trajectory. The lecture suggests that it is through remembering forwards with truth, tolerance, togetherness and trajectory that people in post-conflict societies can inherit the future despite their divided pasts and live in tolerance in the midst of contested memories.