2,405 research outputs found
Weighted ancestors in suffix trees
The classical, ubiquitous, predecessor problem is to construct a data
structure for a set of integers that supports fast predecessor queries. Its
generalization to weighted trees, a.k.a. the weighted ancestor problem, has
been extensively explored and successfully reduced to the predecessor problem.
It is known that any solution for both problems with an input set from a
polynomially bounded universe that preprocesses a weighted tree in O(n
polylog(n)) space requires \Omega(loglogn) query time. Perhaps the most
important and frequent application of the weighted ancestors problem is for
suffix trees. It has been a long-standing open question whether the weighted
ancestors problem has better bounds for suffix trees. We answer this question
positively: we show that a suffix tree built for a text w[1..n] can be
preprocessed using O(n) extra space, so that queries can be answered in O(1)
time. Thus we improve the running times of several applications. Our
improvement is based on a number of data structure tools and a
periodicity-based insight into the combinatorial structure of a suffix tree.Comment: 27 pages, LNCS format. A condensed version will appear in ESA 201
Beyond Brain Mapping: Using Neural Measures to Predict Real-World Outcomes
One goal of social science in general, and of psychology in particular, is to understand and predict human behavior. Psychologists have traditionally used self-report measures and performance on laboratory tasks to achieve this end. However, these measures are limited in their ability to predict behavior in certain contexts. We argue that current neuroscientific knowledge has reached a point where it can complement other existing psychological measures in predicting behavior and other important outcomes. This brain-as-predictor approach integrates traditional neuroimaging methods with measures of behavioral outcomes that extend beyond the immediate experimental session. Previously, most neuroimaging experiments focused on understanding basic psychological processes that could be directly observed in the laboratory. However, recent experiments have demonstrated that brain measures can predict outcomes (e.g., purchasing decisions, clinical outcomes) over longer timescales in ways that go beyond what was previously possible with self-report data alone. This approach can be used to reveal the connections between neural activity in laboratory contexts and longer-term, ecologically valid outcomes. We describe this approach and discuss its potential theoretical implications. We also review recent examples of studies that have used this approach, discuss methodological considerations, and provide specific guidelines for using it in future research
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Ban the ban: A scientific and cultural analysis of the FDA’s ban on blood donations from men who have sex with men
In recent years, the Lesbian Gay Bisexual Transsexual Queer (LGBTQ) community has experienced a number of triumphs. From the end of the military’s “Don’t Ask, Don’t Tell” policy to the repeal of the Defense of Marriage Act, the political and social landscape in the United States is becoming more inclusive of homosexuality.1 While there still remain many discriminatory practices, a particularly egregious one is the U.S. Food and Drug Administration’s (FDA) ban on blood donations by men who have sex with men. In addition to being societally regressive, this policy frustrates efforts to overcome the nation’s blood shortage. In May 2015, the FDA released a draft guidance document suggesting a shift from the existing lifetime ban to a twelve-month deferral period. While this is a progressive step in the right direction, the new regulation would require donors to remain celibate for twelve months prior to donation, which maintains the categorical association between gay sex, risky sex, and HIV. This updated policy is as discriminatory as the lifetime ban and will not significantly increase the number of eligible donors. A shift away from a categorical and unnecessary ban towards a systematic and scientifically based series of tests and screenings that focus on indicators of risky sex would grow America’s pool of blood donors without increasing the risk of transfusion-related transmission of HIV. Support within the academic community and populations unaffected by the ban would be effective strategies to challenge and ultimately demand the ban’s complete removal
In the Trenches of Real-World Self-Control: Neural Correlates of Breaking the Link Between Craving and Smoking
Successful goal pursuit involves repeatedly engaging self-control against temptations or distractions that arise along the way. Laboratory studies have identified the brain systems recruited during isolated instances of self-control, and ecological studies have linked self-control capacity to goal outcomes. However, no study has identified the neural systems of everyday self-control during long-term goal pursuit. The present study integrated neuroimaging and experience-sampling methods to investigate the brain systems of successful self-control among smokers attempting to quit. A sample of 27 cigarette smokers completed a go/no-go task during functional magnetic resonance imaging before they attempted to quit smoking and then reported everyday self-control using experience sampling eight times daily for 3 weeks while they attempted to quit. Increased activation in right inferior frontal gyrus, pre-supplementary motor area, and basal ganglia regions of interest during response inhibition at baseline was associated with an attenuated association between cravings and subsequent smoking. These findings support the ecological validity of neurocognitive tasks as indices of everyday response inhibition
From Neural Responses to Population Behavior: Neural Focus Group Predicts Population-Level Media Effects
Can neural responses of a small group of individuals predict the behavior of large-scale populations? In this investigation, brain activations were recorded while smokers viewed three different television campaigns promoting the National Cancer Institute’s telephone hotline to help smokers quit (1-800-QUIT-NOW). The smokers also provided self-report predictions of the campaigns’ relative effectiveness. Population measures of the success of each campaign were computed by comparing call volume to 1-800-QUIT-NOW in the month before and the month after the launch of each campaign. This approach allowed us to directly compare the predictive value of self-reports with neural predictors of message effectiveness. Neural activity in a medial prefrontal region of interest, previously associated with individual behavior change, predicted the population response, whereas self-report judgments did not. This finding suggests a novel way of connecting neural signals to population responses that has not been previously demonstrated and provides information that may be difficult to obtain otherwise
Interactive Effects of Three Core Goal Pursuit Processes on Brain Control Systems: Goal Maintenance, Performance Monitoring, and Response Inhibition
Goal attainment relies in part on one’s ability to maintain a cognitive representation of the desired goal (goal maintenance), monitor the current state vis-à -vis the targeted end state and remain vigilant for lapses in progress (performance monitoring), and inhibit counter-goal behaviors (response inhibition). Because neurocognitive studies have typically examined these three processes in isolation from one another, little is known regarding if and how they interact during goal pursuit. However, these processes frequently co-occur during online, real-world goal pursuit. The present study employed a novel task to investigate how goal maintenance, performance monitoring, and response inhibition interact with one another. We identified functional activations distinct to each of the processes that correspond to results of prior investigations. In addition, we report interactive effects between response inhibition and goal maintenance in the dorsal anterior cingulate cortex and between performance monitoring and goal maintenance in the superior frontal gyrus and supramarginal gyrus. Implications for studying the neural systems of in situ goals include the need for both experimental designs that distinguish between process, but also more complex, realistic tasks to begin to map interactions among these neurocognitive processes and how they are altered by the presence or absence of one another
Neural Activity During Health Messaging Predicts Reductions in Smoking Above and Beyond Self-Report
Objective: The current study tested whether neural activity in response to messages designed to help smokers quit could predict smoking reduction, above and beyond self-report.
Design: Using neural activity in an a priori region of interest (a subregion of medial prefrontal cortex [MPFC]), in response to ads designed to help smokers quit smoking, we prospectively predicted reductions in smoking in a community sample of smokers (N = 28) who were attempting to quit smoking. Smoking was assessed via expired carbon monoxide (CO; a biological measure of recent smoking) at baseline and 1 month following exposure to professionally developed quitting ads. Results: A positive relationship was observed between activity in the MPFC region of interest and successful quitting (increased activity in MPFC was associated with a greater decrease in expired CO). The addition of neural activity to a model predicting changes in CO from self-reported intentions, self-efficacy, and ability to relate to the messages significantly improved model fit, doubling the variance explained (R²self-report = .15, R²self-report + neural activity = .35, R²change = .20).
Conclusion: Neural activity is a useful complement to existing self-report measures. In this investigation, we extend prior work predicting behavior change based on neural activity in response to persuasive media to an important health domain and discuss potential psychological interpretations of the brain–behavior link. Our results support a novel use of neuroimaging technology for understanding the psychology of behavior change and facilitating health promotion
Using SMS Text Messaging to Assess Moderators of Smoking Reduction: Validating a New Tool for Ecological Measurement of Health Behaviors
Objective: Understanding the psychological processes that contribute to smoking reduction will yield population health benefits. Negative mood may moderate smoking lapse during cessation, but this relationship has been difficult to measure in ongoing daily experience. We used a novel form of ecological momentary assessment to test a self-control model of negative mood and craving leading to smoking lapse.
Design: We validated short message service (SMS) text as a user-friendly and low-cost option for ecologically measuring real-time health behaviors. We sent text messages to cigarette smokers attempting to quit eight times daily for the first 21 days of cessation (N-obs = 3,811).
Main outcome measures: Approximately every two hours, we assessed cigarette count, mood, and cravings, and examined between- and within-day patterns and time-lagged relationships among these variables. Exhaled carbon monoxide was assessed pre- and posttreatment.
Results: Negative mood and craving predicted smoking two hours later, but craving mediated the mood–smoking relationship. Also, this mediation relationship predicted smoking over the next two, but not four, hours.
Conclusion: Results clarify conflicting previous findings on the relation between affect and smoking, validate a new low-cost and user-friendly method for collecting fine-grained health behavior assessments, and emphasize the importance of rapid, real-time measurement of smoking moderators
Predicting Persuasion-Induced Behavior Change From the Brain
Although persuasive messages often alter people\u27s self-reported attitudes and intentions to perform behaviors, these self-reports do not necessarily predict behavior change. We demonstrate that neural responses to persuasive messages can predict variability in behavior change in the subsequent week. Specifically, an a priori region of interest (ROI) in medial prefrontal cortex (MPFC) was reliably associated with behavior change (r = 0.49, p \u3c 0.05). Additionally, an iterative cross-validation approach using activity in this MPFC ROI predicted an average 23% of the variance in behavior change beyond the variance predicted by self-reported attitudes and intentions. Thus, neural signals can predict behavioral changes that are not predicted from self-reported attitudes and intentions alone. Additionally, this is the first functional magnetic resonance imaging study to demonstrate that a neural signal can predict complex real world behavior days in advance
One-variable word equations in linear time
In this paper we consider word equations with one variable (and arbitrary
many appearances of it). A recent technique of recompression, which is
applicable to general word equations, is shown to be suitable also in this
case. While in general case it is non-deterministic, it determinises in case of
one variable and the obtained running time is O(n + #_X log n), where #_X is
the number of appearances of the variable in the equation. This matches the
previously-best algorithm due to D\k{a}browski and Plandowski. Then, using a
couple of heuristics as well as more detailed time analysis the running time is
lowered to O(n) in RAM model. Unfortunately no new properties of solutions are
shown.Comment: submitted to a journal, general overhaul over the previous versio
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