Advancing polar prediction capabilities on daily to seasonal time scales

It is argued that existing polar prediction systems do not yet meet users’ needs; and possible ways forward in advancing prediction capacity in polar regions and beyond are outlined. The polar regions have been attracting more and more attention in recent years, fuelled by the perceptible impacts of anthropogenic climate change. Polar climate change provides new opportunities, such as shorter shipping routes between Europe and East Asia, but also new risks such as the potential for industrial accidents or emergencies in ice-covered seas. Here, it is argued that environmental prediction systems for the polar regions are less developed than elsewhere. There are many reasons for this situation, including the polar regions being (historically) lower priority, with less in situ observations, and with numerous local physical processes that are less well-represented by models. By contrasting the relative importance of different physical processes in polar and lower latitudes, the need for a dedicated polar prediction effort is illustrated. Research priorities are identified that will help to advance environmental polar prediction capabilities. Examples include an improvement of the polar observing system; the use of coupled atmosphere-sea ice-ocean models, even for short-term prediction; and insight into polar-lower latitude linkages and their role for forecasting. Given the enormity of some of the challenges ahead, in a harsh and remote environment such as the polar regions, it is argued that rapid progress will only be possible with a coordinated international effort. More specifically, it is proposed to hold a Year of Polar Prediction (YOPP) from mid-2017 to mid-2019 in which the international research and operational forecasting community will work together with stakeholders in a period of intensive observing, modelling, prediction, verification, user-engagement and educational activities.

Speed prediction for triggering vehicle activated signs

Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for large-scale systems. Nonetheless, a critical obstacle, which needs to be overcome in MPC, is the large computational burden when a large-scale system is considered or a long prediction horizon is involved. In order to solve this problem, we use an adaptive prediction accuracy (APA) approach that can reduce the computational burden almost by half. The proposed MPC scheme with this scheme is tested on the northern Dutch water system, which comprises Lake IJssel, Lake Marker, the River IJssel and the North Sea Canal. The simulation results show that by using the MPC-APA scheme, the computational time can be reduced to a large extent and a flood protection problem over longer prediction horizons can be well solved.

Estimation of variance components and prediction of breeding values in rubber tree breeding using the REML/BLUP procedure

The present paper deals with estimation of variance components, prediction of breeding values and selection in a population of rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Müell.-Arg.] from Rio Branco, State of Acre, Brazil. The REML/BLUP (restricted maximum likelihood/best linear unbiased prediction) procedure was applied. For this purpose, 37 rubber tree families were obtained and assessed in a randomized complete block design, with three unbalanced replications. The field trial was carried out at the Experimental Station of UNESP, located in Selvíria, State of Mato Grosso do Sul, Brazil. The quantitative traits evaluated were: girth (G), bark thickness (BT), number of latex vessel rings (NR), and plant height (PH). Given the unbalanced condition of the progeny test, the REML/BLUP procedure was used for estimation. The narrow-sense individual heritability estimates were 0.43 for G, 0.18 for BT, 0.01 for NR, and 0.51 for PH. Two selection strategies were adopted: one short-term (ST - selection intensity of 8.85%) and the other long-term (LT - selection intensity of 26.56%). For G, the estimated genetic gains in relation to the population average were 26.80% and 17.94%, respectively, according to the ST and LT strategies. The effective population sizes were 22.35 and 46.03, respectively. The LT and ST strategies maintained 45.80% and 28.24%, respectively, of the original genetic diversity represented in the progeny test. So, it can be inferred that this population has potential for both breeding and ex situ genetic conservation as a supplier of genetic material for advanced rubber tree breeding programs. Copyright by the Brazilian Society of Genetics.

The Chilean earthquake of 27 February 2010 an overview

Includes bibliography

Analysis of ensemble models in the medium term hydropower scheduling

The medium term hydropower scheduling (MTHS) problem involves an attempt to determine, for each time stage of the planning period, the amount of generation at each hydro plant which will maximize the expected future benefits throughout the planning period, while respecting plant operational constraints. Besides, it is important to emphasize that this decision-making has been done based mainly on inflow earliness knowledge. To perform the forecast of a determinate basin, it is possible to use some intelligent computational approaches. In this paper one considers the Dynamic Programming (DP) with the inflows given by their average values, thus turning the problem into a deterministic one which the solution can be obtained by deterministic DP (DDP). The performance of the DDP technique in the MTHS problem was assessed by simulation using the ensemble prediction models. Features and sensitivities of these models are discussed. © 2012 IEEE.

MVP expression in the prediction of clinical outcome of locally advanced oral squamous cell carcinoma patients treated with radiotherapy

[EN] Objective: To explore the role of Major Vault Protein (MVP) in oral cavity squamous cell carcinoma patients. Subjects and Methods: 131 consecutive patients suffering from oral cavity squamous cell carcinoma were included in the study. In the whole series, the mean follow-up for survivors was 123.11 ± 40.36 months. Patients in tumour stages I and II were referred to surgery; patients in stage III-IV to postoperative radiotherapy (mean dose = 62.13 ± 7.74 Gy in 1.8–2 Gy/fraction). MVP expression was studied by immunohistochemistry in paraffin-embedded tumour tissue. Results: MVP expression was positive in 112 patients (85.5%) and no relation was found with clinic pathological variables. MVP overexpression (those tumours with moderate or strong expression of the protein) was related to insulin-like growth factor receptor-1 (IGF-1R) expression (P = 0.014). Tumour stage of the disease was the most important prognostic factor related to survival. Tumours overexpressing MVP and IGF-1R were strongly related to poor disease-free survival (P = 0.008, Exp(B) = 2.730, CI95% (1.302-5.724)) and cause-specific survival (P = 0.014, Exp(B) = 2.570, CI95% (1.215-5.437)) in patients achieving tumour stages III-IV, in multivariate analysis. Conclusions: MVP and IGF-1R expression were related in oral squamous cell carcinoma and conferred reduced long-term survival in patients suffering from advanced stages of the disease.

Correlation and prediction of mixing thermodynamic properties of ester-containing systems Ester+alkane and ester+ester binary systems and the ternary dodecane+ethyl pentonoate+ethyl ethanoate

[EN]Excess thermodynamic properties VE m and HE m, have been measured for the ternary mixture dodecane + ethyl pentanoate + ethyl ethanoate and for the corresponding binaries dodecane + ethyl pentanoate, dodecane + ethyl ethanoate, ethyl pentanoate + ethyl ethanoate at 298.15 K. All mixtures show endothermic and expansive effects. Experimental results are correlated with a suitable equation whose final form for the excess ternary quantity ME contains the particular contributions of the three binaries (i–j) and a last term corresponding to the ternary, all of them obtained considering fourth-order interactions.

A Phase Space Box-counting based Method for Arrhythmia Prediction from Electrocardiogram Time Series

Arrhythmia is one kind of cardiovascular diseases that give rise to the number of deaths and potentially yields immedicable danger. Arrhythmia is a life threatening condition originating from disorganized propagation of electrical signals in heart resulting in desynchronization among different chambers of the heart. Fundamentally, the synchronization process means that the phase relationship of electrical activities between the chambers remains coherent, maintaining a constant phase difference over time. If desynchronization occurs due to arrhythmia, the coherent phase relationship breaks down resulting in chaotic rhythm affecting the regular pumping mechanism of heart. This phenomenon was explored by using the phase space reconstruction technique which is a standard analysis technique of time series data generated from nonlinear dynamical system. In this project a novel index is presented for predicting the onset of ventricular arrhythmias. Analysis of continuously captured long-term ECG data recordings was conducted up to the onset of arrhythmia by the phase space reconstruction method, obtaining 2-dimensional images, analysed by the box counting method. The method was tested using the ECG data set of three different kinds including normal (NR), Ventricular Tachycardia (VT), Ventricular Fibrillation (VF), extracted from the Physionet ECG database. Statistical measures like mean (μ), standard deviation (σ) and coefficient of variation (σ/μ) for the box-counting in phase space diagrams are derived for a sliding window of 10 beats of ECG signal. From the results of these statistical analyses, a threshold was derived as an upper bound of Coefficient of Variation (CV) for box-counting of ECG phase portraits which is capable of reliably predicting the impeding arrhythmia long before its actual occurrence. As future work of research, it was planned to validate this prediction tool over a wider population of patients affected by different kind of arrhythmia, like atrial fibrillation, bundle and brunch block, and set different thresholds for them, in order to confirm its clinical applicability.

Corpus callosum index and long-term disability in multiple sclerosis patients

Prediction of long-term disability in patients with multiple sclerosis (MS) is essential. Magnetic resonance imaging (MRI) measurement of brain volume may be of predictive value but sophisticated MRI techniques are often inaccessible in clinical practice. The corpus callosum index (CCI) is a normalized measurement that reflects changes of brain volume. We investigated medical records and 533 MRI scans at diagnosis and during clinical follow-up of 169 MS patients (mean age 42 +/- 11 years, 86% relapsing-remitting MS, time since first relapse 11 +/- 9 years). CCI at diagnosis was 0.345 +/- 0.04 and correlated with duration of disease (p = 0.002; r = -0.234) and expanded disability status scale (EDSS) score at diagnosis (r = -0.428; p < 0.001). Linear regression analyses identified age, duration of disease, relapse rate and EDSS at diagnosis as independent predictors for disability after mean of 7.1 years (Nagelkerkes' R:0.56). Annual CCI decrease was 0.01 +/- 0.02 (annual tissue loss: 1.3%). In secondary progressive MS patients, CCI decrease was double compared to that in relapsing-remitting MS patients (p = 0.04). There was a trend of greater CCI decrease in untreated patients compared to those who received disease modifying drugs (p = 0.2). CCI is an easy to use MRI marker for estimating brain atrophy in patients with MS. Brain atrophy as measured with CCI was associated with disability progression but it was not an independent predictor of long-term disability.

Dysphonic newborn cries allow prediction of their perceived meaning

Can adults attribute different meanings to the cries produced by the newborns on the basis of physical-acoustic cues in different communication conditions? In order to test this hypothesis, 20 females were asked to evaluate (according to four scales: anguish, anger, annoyance, care-seeking) 24 cries from 12 healthy full-term newborns (4-7h old): 6 newborns previously exposed to tactile communication (Group 1); 6 newborns without communication (Group 2). Annoyance category was not reliable and it was excluded from analyses. The 20 females attributed a higher rate of anger and anguish to the cries from Group 2, and a higher rate of care-seeking to the cries from Group 1. They attributed different meanings to the cries from Group 1, and undifferentiated meanings to the cries from Group 2. Consistent with bivariate analyses, Dysphonic Cry was the strongest predictor of anger/anguish. Although the Hyperphonic Cry was quantitatively not relevant, its absence was the first predictor for care-seeking.

Early molecular and cytogenetic response is predictive for long-term progression-free and overall survival in chronic myeloid leukemia (CML)

In the face of competing first-line treatment options for CML, early prediction of prognosis on imatinib is desirable to assure favorable survival or otherwise consider the use of a second-generation tyrosine kinase inhibitor (TKI). A total of 1303 newly diagnosed imatinib-treated patients (pts) were investigated to correlate molecular and cytogenetic response at 3 and 6 months with progression-free and overall survival (PFS, OS). The persistence of BCR-ABL transcript levels >10% according to the international scale (BCR-ABL(IS)) at 3 months separated a high-risk group (28% of pts; 5-year OS: 87%) from a group with >1-10% BCR-ABL(IS) (41% of pts; 5-year OS: 94%; P=0.012) and from a group with 1% BCR-ABL(IS) (31% of pts; 5-year OS: 97%; P=0.004). Cytogenetics identified high-risk pts by >35% Philadelphia chromosome-positive metaphases (Ph+, 27% of pts; 5-year OS: 87%) compared with 35% Ph+ (73% of pts; 5-year OS: 95%; P=0.036). At 6 months, >1% BCR-ABL(IS) (37% of pts; 5-year OS: 89%) was associated with inferior survival compared with 1% (63% of pts; 5-year OS: 97%; P<0.001) and correspondingly >0% Ph+ (34% of pts; 5-year OS: 91%) compared with 0% Ph+ (66% of pts; 5-year OS: 97%; P=0.015). Treatment optimization is recommended for pts missing these landmarks.

Fluctuation analysis of lung function as a predictor of long-term response to beta2-agonists

The response to beta(2)-agonists differs between asthmatics and has been linked to subsequent adverse events, even death. Possible determinants include beta(2)-adrenoceptor genotype at position 16, lung function and airway hyperresponsiveness. Fluctuation analysis provides a simple parameter alpha measuring the complex correlation properties of day-to-day peak expiratory flow. The present study investigated whether alpha predicts clinical response to beta(2)-agonist treatment, taking into account other conventional predictors. Analysis was performed on previously published twice-daily peak expiratory flow measurements in 66 asthmatic adults over three 6-month randomised order treatment periods: placebo, salbutamol and salmeterol. Multiple linear regression was used to determine the association between alpha during the placebo period and response to treatment (change in the number of days with symptoms), taking into account other predictors namely beta(2)-adrenoceptor genotype, lung function and its variability, and airway hyperresponsiveness. The current authors found that alpha measured during the placebo period considerably improved the prediction of response to salmeterol treatment, taking into account genotype, lung function or its variability, or airway hyperresponsiveness. The present study provides further evidence that response to beta(2)-agonists is related to the time correlation properties of lung function in asthma. The current authors conclude that fluctuation analysis of lung function offers a novel predictor to identify patients who may respond well or poorly to treatment.

Using a Prediction and Option Generation Paradigm to Understand Decision Making

In many complex and dynamic domains, the ability to generate and then select the appropriate course of action is based on the decision maker's "reading" of the situation--in other words, their ability to assess the situation and predict how it will evolve over the next few seconds. Current theories regarding option generation during the situation assessment and response phases of decision making offer contrasting views on the cognitive mechanisms that support superior performance. The Recognition-Primed Decision-making model (RPD; Klein, 1989) and Take-The-First heuristic (TTF; Johnson & Raab, 2003) suggest that superior decisions are made by generating few options, and then selecting the first option as the final one. Long-Term Working Memory theory (LTWM; Ericsson & Kintsch, 1995), on the other hand, posits that skilled decision makers construct rich, detailed situation models, and that as a result, skilled performers should have the ability to generate more of the available task-relevant options. The main goal of this dissertation was to use these theories about option generation as a way to further the understanding of how police officers anticipate a perpetrator's actions, and make decisions about how to respond, during dynamic law enforcement situations. An additional goal was to gather information that can be used, in the future, to design training based on the anticipation skills, decision strategies, and processes of experienced officers. Two studies were conducted to achieve these goals. Study 1 identified video-based law enforcement scenarios that could be used to discriminate between experienced and less-experienced police officers, in terms of their ability to anticipate the outcome. The discriminating scenarios were used as the stimuli in Study 2; 23 experienced and 26 less-experienced police officers observed temporally-occluded versions of the scenarios, and then completed assessment and response option-generation tasks. The results provided mixed support for the nature of option generation in these situations. Consistent with RPD and TTF, participants typically selected the first-generated option as their final one, and did so during both the assessment and response phases of decision making. Consistent with LTWM theory, participants--regardless of experience level--generated more task-relevant assessment options than task-irrelevant options. However, an expected interaction between experience level and option-relevance was not observed. Collectively, the two studies provide a deeper understanding of how police officers make decisions in dynamic situations. The methods developed and employed in the studies can be used to investigate anticipation and decision making in other critical domains (e.g., nursing, military). The results are discussed in relation to how they can inform future studies of option-generation performance, and how they could be applied to develop training for law enforcement officers.