Disruption Prediction Research Articles

The role of approach‐avoidance versus task and ego goals in enjoyment and cognitive anxiety in youth sport

This study investigated whether approach‐avoidance goals predicted enjoyment, concentration disruption, and worry, and compared approach‐avoidance versus task/ego goals in predicting these variables. British youth athletes (139 males, 110 females, 5 did not report gender), with a mean age of 13.57 (SD = 1.69) years and a mean sport experience of 4.81 (SD = 2.80) years, completed questionnaires measuring approach‐avoidance and task/ego goals, enjoyment, concentration disruption, worry, and perceived competence. Mastery‐approach goals positively predicted enjoyment, and negatively predicted concentration disruption and worry. The two avoidance goals positively predicted concentration disruption and worry, while performance‐approach goals did not predict any outcome variable. In hierarchical regression analyses, task/ego goals were the most important predictors of enjoyment, whereas approach‐avoidance goals were the most important predictors of concentration disruption and worry. Both sets of goals accounted for unique variance in the variables examined, suggesting the approach‐avoidance distinction is a valuable addition to achievement goal theory

Feature extraction for improved disruption prediction analysis at JET

Disruptions are major instabilities and remain one of the main problems in tokomaks. Using Joint European Torus database, a disruption predictor is developed by computational methods including supervised learning techniques. The main objectives of the work are to develop accurate automatic classifiers, to test their performances, and to determine how much in advance of the disruption they can operate with acceptable reliability.

Prototype of an adaptive disruption predictor for JET based on fuzzy logic and regression trees

Disruptions remain one of the most hazardous events in the operation of a tokamak device, since they can cause damage to the vacuum vessel and surrounding structures. Their potential danger increases with the plasma volume and energy content and therefore they will constitute an even more serious issue for the next generation of machines. For these reasons, in the recent years a lot of attention has been devoted to devise predictors, capable of foreseeing the imminence of a disruption sufficiently in advance, to allow time for undertaking remedial actions. In this paper, the results of applying fuzzy logic and classification and regression trees (CART) to the problem of predicting disruptions at JET are reported. The conceptual tools of fuzzy logic, in addition to being well suited to accommodate the opinion of experts even if not formulated in mathematical but linguistic terms, are also fully transparent, since their governing rules are human defined. They can therefore help not only in forecasting disruptions but also in studying their behaviour. The analysis leading to the rules of the fuzzy predictor has been complemented with a systematic investigation of the correlation between the various experimental signals and the imminence of a disruption. This has been performed with an exhaustive, non-linear and unbiased method based on decision trees. This investigation has confirmed that the relative importance of various signals can change significantly depending on the plasma conditions. On the basis of the results provided by CART on the information content of the various quantities, the prototype of an adaptive fuzzy logic predictor was trained and tested on JET database. Its performance is significantly better than the previous static one, proving that more flexible prediction strategies, not uniform over the whole discharge but tuned to the operational region of the plasma at any given time, can be very competitive and should be investigated systematically.

A Disruption Predictor Based on Fuzzy Logic Applied to JET Database

Disruptions remain a serious issue for International Thermonuclear Experimental Reactor (ITER) and the commercial reactor. In the past years, significant efforts have been devoted to the development of reliable disruption predictors. In this paper, the potential of fuzzy logic in this field is explored. A new disruption predictor for Joint European Torus (JET), which is based on fuzzy logic, was tested off-line using data collected during several JET campaigns, covering a very wide range of scenarios and plasma parameters. In the standard configuration, it was able to predict 92% of disruptions with about 18% of false alarms (FAs). The flexibility of the approach, which is to provide a different tradeoff between missed and FAs, depending on the desired results in terms of safety, is demonstrated. The potential of the technique to help quantifying the risks that are associated with the operation outside the already explored parameter space is also discussed.

Overview of HL-2A experiment results

Recent experiment results from the HL-2A tokamak are presented in this paper. Supersonic molecular beam injection (SMBI) with liquid nitrogen temperature propellant is used. Low temperature SMBI can form hydrogen clusters that penetrate into the plasma more deeply and efficiently. Particle diffusion coefficient and convection velocity (D = 0.5–1.5 m2 s−1 and Vconv < 40 m s−1, respectively) are obtained at the plasma periphery using modulated SMBI. Multi-probe measurements reveal the m = 0–1, n = 0 symmetries of directly measured low frequency (7–9 kHz) electric potential and field are simultaneously observed for the first time. Impurity transport is determined with the laser blow-off system and transport code. A disruption predictor has been derived based on MHD activity observations and statistical analysis. Sawtooth characteristics during ECRH are investigated and coupling between m = 1 and m/n = 2/1 modes is studied. Detachment features of HL-2A divertor are numerically and experimentally studied using the code SOLPS5.0 and measured data. The long divertor legs and thin divertor throats in HL-2A pose MHD shaping problems resulting in momentum losses even at low densities and strongly enhanced main chamber losses.

Support vector machines for disruption prediction and novelty detection at JET

In the last years there has been a growing interest on black box approaches to disruption prediction. The drawback of these approaches is that the system could deteriorate its performance once it does not get updated. This could be the case of a disruption predictor for JET, where new plasma configurations might present features completely different from those observed in the experiments used during the training phase. This ‘novelty’ can be incorrectly classified by the system. A novelty detection method, which determines the novelty of the input of the prediction system, can be used to assess the system reliability. This paper presents a support vector machines disruption predictor for JET, wherein multiple plasma diagnostic signals are combined to provide a composite impending disruption warning indicator. In a support vector machine the analysis of the decision function value gives useful information about the novelty of an input and, on the reliability of the predictor output, during on-line applications. Results show the suitability of support vector machines both for prediction and novelty detection tasks at JET.

Who disrupts from placement in foster and kinship care?

Objective To identify reliable, inexpensive predictors of foster care placement disruption that could be used to assess risk of placement failure. Methods Using the Parent Daily Report Checklist (PDR), foster or kinship parents of 246 children (5–12 years old) in California were interviewed three times about whether or not their foster child engaged in any of the 30 problem behaviors during the previous 24 h. PDR was conducted during telephone contacts (5–10 min each) that occurred from 1 to 3 days apart at baseline. Disruptions were tracked for the subsequent 12 months. Other potential predictors of disruption were examined, including the child's age, gender, and ethnicity, the foster parent's ethnicity, the number of other children in the foster home, and the type of placement (kin or non-kin). Results Foster/kin parents reported an average of 5.77 child problems per day on the PDR checklist. The number of problem behaviors was linearly related to the child's risk of placement disruption during the subsequent year. The threshold for the number of problem behaviors per day that foster and kinship parents tolerated without increased risk of placement disruption for these latency-aged children was 6 or fewer. Children in non-kin placements were more likely to disrupt than those in kinship placements. There was a trend for increased risk of disruption as the number of children in the home increased. Conclusions The PDR Checklist may be useful in predicting which placements are at most risk of future disruption, allowing for targeted services and supports.

Placement disruption and negative placement outcomes among adolescents in long-term foster care: The role of behavior problems

Objective This study examined risk of placement disruption and negative placement outcomes (e.g., residential treatment and incarceration) among adolescents placed in traditional family foster care for a year or longer. A foster parent's report of externalizing behavior problems was expected to be a stronger predictor of disruption and negative outcomes than a caseworker's report. Additionally, the association between behavior problems and placement disruption was expected to be mediated by the youth's degree of belonging and integration in the foster home. Method The caseworkers and foster parents of 179 randomly selected 12–13-year-old adolescents placed in traditional foster care were interviewed by telephone. Interviews included standardized measures of externalizing behavioral problems and several other variables that have been previously associated with placement movement. Disruption from the youth's foster home at the time of the interview was prospectively tracked for 5 years. Results Over half of the youth experienced a disruption of their placement. Contrary to expectations, behavior problems as reported by caseworkers, but not foster parents, were predictive of placement disruption. However, the foster parent's report of behavior problems predicted risk of negative outcome after a period of 5 years. As hypothesized, integration in the foster home was highly predictive of placement stability and mediated the association between behavior problems and risk of disruption. Conclusions Results suggest that integration in the foster home might be an important dimension of placement adaptation that should be considered during service planning for foster youth in long-term foster care. In addition, using standardized measures of behavior with both foster parents and caseworkers might be necessary to assess both long-term risk of negative outcomes and more immediate risk of placement disruption.

Predictors of outcome for unrelated adoptive placements made during middle childhood

ABSTRACTThis paper reports on a follow‐up to adolescence of two longitudinal prospective studies of children placed from public care with non‐related adoptive families in the UK. Factors associated with outcome are presented for 99 children (one index child per adoptive family) who were between 5 and 11 years of age at placement. Information concerning the children's backgrounds and care histories was obtained shortly after placement (T1), from social workers. Adopters were interviewed at T1 and again at the end of the first year (T2). A further follow‐up was conducted an average of six years after placement (T3).Outcomes at T3 were classified as either disrupted, which was true for 23%, continuing and ‘positive’ (49%) or continuing but ‘difficult’ (28%). Bivariate analyses revealed a number of attributes, related to both the child and the adoptive parents, which were associated with differential outcomes. Logistic regression produced five predictors of placement disruption: age at placement, behavioural problems, preferential rejection, time in care and the child's degree of attachment to the new mother. Differences were found between ‘positive’ and ‘difficult’ outcomes in continuing placements as well as between continuing and disrupted placements. The analysis suggests that adoption should certainly be considered as an option for children over 5 years of age while recognizing the need for both preparation and post‐placement support. Evidence of differential outcome in continuing placements provides support for efforts to reduce the number of placements and returns home that a child at risk experiences.

A cross-tokamak neural network disruption predictor for the JET and ASDEX Upgrade tokamaks

First results are reported on the prediction of disruptions in one tokamak, based on neural networks trained on another tokamak. The studies use data from the JET and ASDEX Upgrade devices, with a neural network trained on just seven normalized plasma parameters. In this way, a simple single layer perceptron network trained solely on JET correctly anticipated 67% of disruptions on ASDEX Upgrade in advance of 0.01 s before the disruption. The converse test led to a 69% success rate in advance of 0.04 s before the disruption in JET. Only one overall time scaling parameter is allowed between the devices, which can be introduced from theoretical arguments. Disruption prediction performance based on such networks trained and tested on the same device shows even higher success rates (JET, 86%; ASDEX Upgrade, 90%), despite the small number of inputs used and simplicity of the network. It is found that while performance for networks trained and tested on the same device can be improved with more complex networks and many adjustable weights, for cross-machine testing the best approach is a simple single layer perceptron. This offers the basis of a potentially useful technique for large future devices such as ITER, which with further development might help to reduce disruption frequency and minimize the need for a large disruption campaign to train disruption avoidance systems.

Evidence of reperfusion injury, exacerbated by thrombolytic therapy, in human focal brain ischemia using a novel imaging marker of early blood-brain barrier disruption.

Loss of integrity of the blood-brain barrier (BBB) resulting from ischemia and reperfusion is a hypothesized precursor to hemorrhagic transformation (HT) and worse clinical outcome than would be expected from the beneficial effects of reperfusion. We used a novel magnetic resonance imaging marker to characterize early BBB disruption in acute focal brain ischemia and tested associations with reperfusion, HT, and poor outcome (modified Rankin score >2). The BBB disruption was evident as delayed gadolinium enhancement of cerebrospinal fluid space on fluid-attenuated inversion recovery (FLAIR) images and, for convenience, has been termed hyperintense acute reperfusion marker (HARM). HARM was found in 47 of 144 (33%) ischemic stroke patients. Reperfusion was found to be the strongest independent predictor of early BBB disruption (P=0.018) in multivariate analysis. HARM was associated with HT and worse clinical outcome (after adjustment for initial severity). It was also associated with more severe strokes at onset and greater age. Because the timing of the disruption was early enough (median estimate 3.8 hours from onset) to make it relevant to acute thrombolytic therapy, early BBB disruption as defined by HARM may be a promising target for adjunctive therapy to reduce the complications associated with thrombolytic therapy, broaden the therapeutic window, and improve clinical outcome.

Neural-net disruption predictor in JT-60U

The prediction of major disruptions caused by the density limit, the plasma current ramp-down with high internal inductance li, the low density locked mode and the β-limit has been investigated in JT-60U. The concept of ‘stability level’, newly proposed in this paper to predict the occurrence of a major disruption, is calculated from nine input parameters every 2 ms by the neural network and the start of a major disruption is predicted when the stability level decreases to a certain level, the ‘alarm level’. The neural network is trained in two steps. It is first trained with 12 disruptive and six non-disruptive shots (total of 8011 data points). Second, the target output data for 12 disruptive shots are modified and the network is trained again with additional data points generated by the operator. The ‘neural-net disruption predictor’ obtained has been tested for 300 disruptive shots (128 945 data points) and 1008 non-disruptive shots (982 800 data points) selected from nine years of operation (1991–1999) of JT-60U. Major disruptions except for those caused by the β-limit have been predicted with a prediction success rate of 97–98% at 10 ms prior to the disruption and higher than 90% at 30 ms prior to the disruption while the false alarm rate is 2.1% for non-disruptive shots. This prediction performance has been confirmed for 120 disruptive shots (56 163 data points), caused by the density limit, as well as 1032 non-disruptive shots (1004 611 data points) in the last four years of operation (1999–2002) of JT-60U. A careful selection of the input parameters supplied to the network and the newly developed two-step training of the network have reduced the false alarm rate resulting in a considerable improvement of the prediction success rate.

Circadian rhythms in SAMP8: a longitudinal study of the effects of age and experience

Age-related effects on circadian rhythms include reductions of rhythm amplitude, alterations in re-entrainment, and increased fragmentation. Currently, the pattern of these changes across an individuals’ lifespan is unknown. The present study used a cross-sequential experimental design to determine the pattern of circadian rhythm changes, identify predictors of later circadian rhythm disruption, and assess the effect of prior run-wheel experience on circadian rhythms. Run-wheel activity was assessed in senescence-accelerated mice (SAMP8) at 2, 7, and 12 months of age. Age-related changes included decrease of run-wheel activity, decrease in circadian rhythm amplitude, increase in proportion of light activity, and increase in split activity rhythms. Proportion of light activity at 2 months was a good predictor of circadian rhythm disruption at 7 months. Run-wheel experience increased overall activity and decreased proportion of light activity, but did not alter rhythm amplitude or period. These results demonstrate that aging produces several patterns of circadian rhythm changes, describe predictive measures of future rhythm disruptions, and suggest an intervention to reduce circadian rhythm disruptions.

The effect of anisosmotic conditions on the morphology of the metaphase II spindle of human oocytes, and its relevance to cryopreservation

The effect of anisosmotic conditions on the morphology of the metaphase II spindle of human oocytes, and its relevance to cryopreservation

Self-esteem and optimism in men and women infected with HIV.

Self-esteem and optimism have been associated with appraisal and outcomes in a variety of situations. The degree to which the contribution of self-esteem and optimism to outcomes over time is accounted for by the differences in threat (primary) or resource (secondary) appraisal has not been established in persons with human immunodeficiency virus (HIV). To examine the longitudinal relationship of personality (self-esteem and optimism) on primary and secondary appraisal and outcomes of well-being, mood, CD4+ T-lymphocyte count, and selected activities. Men (n = 56) and women (n = 42) infected with HIV completed eight self-report measures twice over 18 months. Hierarchical Multiple Regressions were used to examine the relationship of personality variables on appraisals and outcomes. The mediating effects of primary and secondary appraisals were explored. Self-esteem uniquely accounted for 6% of the variance in primary appraisal and 5% in secondary appraisal. Optimism accounted for 8% of the unique variance in secondary appraisal. Primary and secondary appraisal mediated differently between personality and outcome variables. A strong predictor of well-being, mood disturbance, and activity disruption at Time 2 was participants' initial level of these variables. Socioeconomic status was a strong predictor of mood. Self-esteem and optimism are important but different resources for adapting to HIV disease. Strategies for reducing threats and increasing resources associated with HIV may improve an individual's mood and sense of well-being.

Till Discord Do Us Part: The Role of Physical and Verbal Conflict in Union Disruption

The focus of this study was the extent to which physical aggression and, to a lesser extent, verbal conflict predict relationship dissolution in a national sample. Data were from a 5‐ to 7‐year follow‐up of 3,508 married and cohabiting couples in the National Survey of Families and Households. Controlling for demographic factors and verbal conflict, male violence significantly elevated the risk of disruption between waves. Female violence was not a predictor of disruption. Much of the effect of male violence was accounted for by its association with reduced relationship quality. The impact of male violence did not appear to differ according to the female partner's socioeconomic resources or whether couples were in formal or informal unions.

Factors Predicting Sleep Disruption in Type II Diabetes

This study investigated four correlates of diabetes as potential predictors of sleep disruption in people with Type II diabetes. A tentative causal model proposed obesity would lead to more severe diabetes, which would result in increased physical complications, which might in turn affect emotional adjustment, and all of these might combine to cause sleep disruption. It was found that within a diabetic sample, severity of diabetes was related to sleep disruption. Path analysis indicated that the relationship between Type II diabetes and sleep disruption was mediated by physical complications of the disease (pain and nocturia), and not by either obesity or emotional adjustment.

The Impact of Husbands' and Wives' Relative Earnings on Marital Disruption

In the last several decades a shift has occurred in the relative contributions of married women to household earnings. Yet we know little about the impact of relative earnings of husbands and wives on the likelihood of marital disruption. This study estimates a discrete-time hazard model using data on first married couples from the 1986-1989 waves of the [U.S.] Panel Study of Income Dynamics. The relative earnings of husbands and wives are a significant predictor of marital disruption although the relationship is nonlinear. We suggest this nonlinear effect is linked to the varying economic circumstances of different groups of couples. (EXCERPT)

A Longitudinal Study of Marital Problems and Subsequent Divorce

This study investigated the extent to which reports of marital problems in 1980 predicted between 1980 and 1992, the extent to which these problems mediated the impact of demographic and life course variables on divorce, and gender differences in reports of particular marital problems and in the extent to which these reports predicted divorce. Wives reported more marital problems than husbands did, although this was due to husbands ' tendency to report relatively few problems caused by their spouses. A variety of marital problems predicted up to 12 years in the future. A parsimonious set of marital problems involving infidelity, spending money foolishly, drinking or drug use or both, jealousy, moodiness, and irritating habits mediated moderate proportions of the associations between demographic and life course variables and divorce. Key Words: divorce, gender, longitudinal studies, marital problems. Researchers trying to determine the causes of have approached the problem in two ways. Some researchers have focused on demographic and life course variables that affect the risk of divorce, variables such as age at marriage, social class, race, religiosity, and parental divorce. Others have adopted a subjective perspective and asked previously married individuals why their marriages ended. In her 1990 review of the previous decade's research on predictors of divorce, White (1990) noted the relatively small number of studies in the latter group (e.g., Bloom, Niles, & Tatcher, 1985; Burns, 1984; Cleek & Pearson, 1985; Kitson & Sussman, 1982; Spanier & Thompson, 1987). She argued that personal accounts are useful and provocative, but these studies only include divorced respondents, they can tell us little about the extent to which these factors predict divorce (p. 908). She also pointed out that there is little integration between studies of personal accounts of and studies that focus on demographic and life course predictors of marital dissolution. Finally, she recommended more research that focuses on marital processes as predictors of divorce. The study presented here responds to White's call for more research on the links between marital processes and marital dissolution. Our study goes beyond prior research in three ways. First, in contrast to previous studies that used divorced people's retrospective accounts of marital problems, we use panel data from a nationally representative sample of married persons to investigate the extent to which marital problems in 1980 predict between 1980 and 1992. In doing so, we address questions about the validity and usefulness of people's self-reports of marital problems as predictors of divorce. Second, we integrate data on specific marital problems (which we view as proximal causes of divorce) with data on the demographic and life course predictors of marital disruption identified in most prior sociological research (which we view as distal causes of divorce). To accomplish this, we assess the extent to which particular marital problems in 1980 mediate the associations between demographic and life course variables and divorce. Finally, because previous evidence suggests that men and women experience marriage and differently (Bernard, 1972; Kitson, 1992; Thompson & Walker, 1989), we consider gender differences, both in the frequency of reports of marital problems in 1980 and in the extent to which these problems predict between 1980 and 1992. MARITAL PROBLEMS AND DIVORCE Marital Problems as Predictors of Divorce Despite the substantial body of research on marital disruption, few prospective studies illustrate the extent to which specific characteristics of a relationship predict divorce. One exception is the work of Gottman and his colleagues, who have investigated some of the linkages among marital interaction, conflict resolution, and (Gottman, 1994). …

The Effects of Marital Disagreement Style, Frequency, and Outcome on Marital Disruption

Studies of the relationship between marital conflict behaviors and marital functioning have focused almost exclusively on conflict resolution styles to the neglect of other components of marital conflict. The present study takes a first step toward addressing this limitation by examining the comparative and interactive effects of marital disagreement style, frequency and outcome on the occurrence of marital disruption (separation or divorce) over a 3-year period. The study is based on a general population sample of 691 married couples. Results of exploratory factor analysis show that self-reports of frequency, style and outcome of marital disagreements share a common underlying structure best described as negativity. Logistic regression analysis documents that while each of the components of negativity is a significant predictor of marital disruption, frequency and negativity are more powerful than either style or outcome. Multivariate analyses reveal that disruption is most powerfully predicted by self-reported negativity among the recently married and by self-reported disagreement frequency among the longer married. The report closes with a discussion of the implications of these results for future research on marital functioning.