Using a Familiar Risk Comparison Within a Risk Ladder to Improve Risk Understanding by Low Numerates: A Study of Visual Attention

Previous experimental research provides evidence that a familiar risk comparison within a risk ladder is understood by low‐ and high‐numerate individuals. It especially helps low numerates to better evaluate risk. In the present study, an eye tracker was used to capture individuals’ visual attention to a familiar risk comparison, such as the risk associated with smoking. Two parameters of information processing—efficiency and level—were derived from visual attention. A random sample of participants from the general population (N= 68) interpreted a given risk level with the help of the risk ladder. Numeracy was negatively correlated with overall visual attention on the risk ladder (r_s=?0.28, p= 0.01), indicating that the lower the numeracy, the more the time spent looking at the whole risk ladder. Numeracy was positively correlated with the efficiency of processing relevant frequency (r_s= 0.34, p < 0.001) and relevant textual information (r_s= 0.34, p < 0.001), but not with the efficiency of processing relevant comparative information and numerical information. There was a significant negative correlation between numeracy and the level of processing of relevant comparative risk information (r_s=?0.21, p < 0.01), indicating that low numerates processed the comparative risk information more deeply than the high numerates. There was no correlation between numeracy and perceived risk. These results add to previous experimental research, indicating that the smoking risk comparison was crucial for low numerates to evaluate and understand risk. Furthermore, the eye‐tracker method is promising for studying information processing and improving risk communication formats.     

Dermal Uptake of 18 Dilute Aqueous Chemicals: In Vivo Disappearance‐Method Measures Greatly Exceed In Vitro‐Based Predictions

Average rates of total dermal uptake (K_up) from short‐term (e.g., bathing) contact with dilute aqueous organic chemicals (DAOCs) are typically estimated from steady‐state in vitro diffusion‐cell measures of chemical permeability (K_p) through skin into receptor solution. Widely used (“PCR‐vitro”) methods estimate K_up by applying diffusion theory to increase K_p predictions made by a physico‐chemical regression (PCR) model that was fit to a large set of K_p measures. Here, K_up predictions for 18 DAOCs made by three PCR‐vitro models (EPA, NIOSH, and MH) were compared to previous in vivo measures obtained by methods unlikely to underestimate K_up. A new PCR model fit to all 18 measures is accurate to within approximately threefold (r = 0.91, p < 10^?5), but the PCR‐vitro predictions (r > 0.63) all tend to underestimate the K_up measures by mean factors (UF, and p value for testing UF = 1) of 10 (EPA, p < 10^?6), 11 (NIOSH, p < 10^?8), and 6.2 (MH, p = 0.018). For all three PCR‐vitro models, log(UF) correlates negatively with molecular weight (r² = 0.31 to 0.84, p = 0.017 to < 10^?6) but not with log(vapor pressure) as an additional predictor (p > 0.05), so vapor pressure appears not to explain the significant in vivo/PCR‐vitro discrepancy. Until this discrepancy is explained, careful in vivo measures of K_up should be obtained for more chemicals, the expanded in vivo database should be compared to in vitro‐based predictions, and in vivo data should be considered in assessing aqueous dermal exposure and its uncertainty.     

Fast On-Line/Off-Line Algorithms for Optimal Reinforcement of a Network and its Connections with Principal Partition

The problem of computing the strength and performing optimal reinforcement for an edge-weighted graph G(V, E, w) is well-studied. In this paper, we present fast (sequential linear time and parallel logarithmic time) on-line algorithms for optimally reinforcing the graph when the reinforcement material is available continuously on-line. These are the first on-line algorithms for this problem. We invest O(|V|³|E|log|V|) time (equivalent to (|V|) invocations of the fastest known algorithms for optimal reinforcement) in preprocessing the graph before the start of our algorithms. It is shown that the output of our on-line algorithms is as good as that of the off-line algorithms. Thus our algorithms are better than the fastest off-line algorithms in situations when a sequence of more than (|V|) reinforcement problems need to be solved. The key idea is to make use of ideas underlying the theory of Principal Partition of a Graph. Our ideas are easily generalized to the general setting of polymatroid functions. We also present a new efficient algorithm for computation of the Principal Sequence of a graph.     

The Interplay of Goals and Promises of Pay-for-Performance on Individual and Group Performance: An Operant Interpretation

ABSTRACT

Building upon the work of Fellner and Sulzer-Azaroff (1984), an operant model of goal setting is presented from which the effects of goals as well as monetary reinforcers can be examined and compared. The model is premised upon the assumption that the effectiveness of individual and group goals and financial reinforcers can be predicted following a detailed examination of an individual's reinforcement history, level of deprivation and satisfaction and the prevailing behavioral contingencies. The effectiveness of the two discriminative stimuli—goals and promises of pay-for-peformance—are discussed in relationship to operant principles.     

Bootstrap Unit Root Tests

We consider the bootstrap unit root tests based on finite order autoregressive integrated models driven by iid innovations, with or without deterministic time trends. A general methodology is developed to approximate asymptotic distributions for the models driven by integrated time series, and used to obtain asymptotic expansions for the Dickey–Fuller unit root tests. The second‐order terms in their expansions are of stochastic orders O_p(n^−1/4) and O_p(n^−1/2), and involve functionals of Brownian motions and normal random variates. The asymptotic expansions for the bootstrap tests are also derived and compared with those of the Dickey–Fuller tests. We show in particular that the bootstrap offers asymptotic refinements for the Dickey–Fuller tests, i.e., it corrects their second‐order errors. More precisely, it is shown that the critical values obtained by the bootstrap resampling are correct up to the second‐order terms, and the errors in rejection probabilities are of order o(n^−1/2) if the tests are based upon the bootstrap critical values. Through simulations, we investigate how effective is the bootstrap correction in small samples.     

Risk Communication,Values Clarification,and Vaccination Decisions

Many health‐related decisions require choosing between two options, each with risks and benefits. When presented with such tradeoffs, people often make choices that fail to align with scientific evidence or with their own values. This study tested whether risk communication and values clarification methods could help parents and guardians make evidence‐based, values‐congruent decisions about children's influenza vaccinations. In 2013–2014 we conducted an online 2×2 factorial experiment in which a diverse sample of U.S. parents and guardians (n = 407) were randomly assigned to view either standard information about influenza vaccines or risk communication using absolute and incremental risk formats. Participants were then either presented or not presented with an interactive values clarification interface with constrained sliders and dynamic visual feedback. Participants randomized to the risk communication condition combined with the values clarification interface were more likely to indicate intentions to vaccinate (β = 2.10, t(399) = 2.63, p < 0.01). The effect was particularly notable among participants who had previously demonstrated less interest in having their children vaccinated against influenza (β = –2.14, t(399) = –2.06, p < 0.05). When assessing vaccination status reported by participants who agreed to participate in a follow‐up study six months later (n = 116), vaccination intentions significantly predicted vaccination status (OR = 1.66, 95%CI (1.13, 2.44), p < 0.05) and rates of informed choice (OR = 1.51, 95%CI (1.07, 2.13), p < 0.012), although there were no direct effects of experimental factors on vaccination rates. Qualitative analysis suggested that logistical barriers impeded immunization rates. Risk communication and values clarification methods may contribute to increased vaccination intentions, which may, in turn, predict vaccination status if logistical barriers are also addressed.     

Media exposure,threat processing,and mitigation behaviors in Gulf Coast residents facing the co-occurring threats of COVID-19 and hurricanes

The 2020 hurricane season threatened millions of Americans concurrently grappling with COVID-19. Processes guiding individual-level mitigation for these conceptually distinct threats, one novel and chronic (COVID-19), the other familiar and episodic (hurricanes), are unknown. Theories of health protective behaviors suggest that inputs from external stimuli (e.g., traditional and social media) lead to threat processing, including perceived efficacy (self- and response) and perceived threat (susceptibility and severity), guiding mitigation behavior. We surveyed a representative sample of Florida and Texas residents (N = 1846) between April 14, 2020 and April 27, 2020; many had previous hurricane exposure; all were previously assessed between September 8, 2017 and September 11, 2017. Using preregistered analyses, two generalized structural equation models tested direct and indirect effects of media exposure (traditional media, social media) on self-reported (1) COVID-19 mitigation (handwashing, mask-wearing, social distancing) and (2) hurricane mitigation (preparation behaviors), as mediated through perceived efficacy (self- and response) and perceived threat (susceptibility and severity). Self-efficacy and response efficacy were associated with social distancing (p = .002), handwashing, mask-wearing, and hurricane preparation (ps < 0.001). Perceived susceptibility was positively associated with social distancing (p = 0.017) and hurricane preparation (p < 0.001). Perceived severity was positively associated with social distancing (p < 0.001). Traditional media exhibited indirect effects on COVID-19 mitigation through increased response efficacy (ps < 0.05), and to a lesser extent self-efficacy (p < 0.05), and on hurricane preparation through increased self-efficacy and response efficacy and perceived susceptibility (ps < 0.05). Social media did not exhibit indirect effects on COVID-19 or hurricane mitigation. Communications targeting efficacy and susceptibility may encourage mitigation behavior; research should explore how social media campaigns can more effectively target threat processing, guiding protective actions.     

Effort-reward imbalance,overcommitment and sleep in a working population

The relationship between workplace characteristics and nocturnal sleep in a working population was investigated. Data from 709 employees (mean age=39 years; 87% men) from two German companies were analysed at the entry of the longitudinal cohort study (overall accrual 73%). We investigated the association between the effort-reward imbalance model at work (Siegrist, ) and self-reported sleep quality and sleep disturbances, as assessed by the Jenkins Sleep Quality Index. Effort and overcommitment were found to be higher, and reward was lower in participants with lower (N=328) vs. higher sleep quality (N=381), as well as in participants with (N=217) vs. without (N=492) disturbed sleep (all ps<.001). In regression analyses, lower sleep quality (R ²=.33) and sleep disturbances (R ² _Nagelkerke=.33) were predicted by older age, female gender (only significant for sleep disturbances), shift-work, lower physical and mental health functioning, and higher overcommitment. Individuals were 1.7 times more likely to report disturbed sleep per standard deviation increase in overcommitment. Gender-stratified analyses revealed that higher overcommitment was associated with unfavourable sleep in men, while in women poor sleep was related to lower reward. The findings suggest that overcommitment at work interferes with restful sleep in men, while in women disturbed sleep may be associated with the amount of overcommitment and perceived job reward and sleep quality associated with the perceived reward.     

Sensitivity of the Optimum to Perturbations of the Profit or Weight of an Item in the Binary Knapsack Problem

In the binary single constraint Knapsack Problem, denoted KP, we are given a knapsack of fixed capacity c and a set of n items. Each item j, j = 1,...,n, has an associated size or weight w_j and a profit p_j. The goal is to determine whether or not item j, j = 1,...,n, should be included in the knapsack. The objective is to maximize the total profit without exceeding the capacity c of the knapsack. In this paper, we study the sensitivity of the optimum of the KP to perturbations of either the profit or the weight of an item. We give approximate and exact interval limits for both cases (profit and weight) and propose several polynomial time algorithms able to reach these interval limits. The performance of the proposed algorithms are evaluated on a large number of problem instances.     

Mycotoxins were not associated with environmental enteropathy in a cohort of Tanzanian children

Enteropathy is a pathophysiological condition characterized by decreased intestinal barrier function and absorption. Past studies have hypothesized that mycotoxins might impair children's growth by causing intestinal enteropathy, including interactions between mycotoxins and pathogens. We investigated the association of two mycotoxins, aflatoxin B₁ (AFB₁) and fumonisin B₁ (FB₁), independently and in conjunction with microbial pathogens, with fecal biomarkers of environmental enteropathy in children. As part of a larger MAL-ED study, 196 children were recruited in Haydom, Tanzania, and followed for the first 36 months of life. The gut inflammation biomarkers myeloperoxidase (MPO), neopterin (NEO), and alpha-1-antitrypsin (A1AT) were analyzed in stool samples at 24 months; with mean concentrations 5332.5 ng/L MPO, 807.2 nmol/L NEO, and 0.18 mg/g A1AT. Forty-eight children were measured for AFB₁-lys, with a mean of 5.30 (95% CI: 3.93-6.66) pg/mg albumin; and 87 were measured for FB₁, with a mean of 1.25 (95% CI: 0.72–1.76) ng/ml urine. Although the pathogens adenovirus and Campylobacter were associated with A1AT (p = 0.049) and NEO (p = 0.004), respectively, no association was observed between aflatoxin (MPO, p = 0.30; NEO, p = 0.08; A1AT, p = 0.24) or fumonisin (MPO, p = 0.38; NEO, p = 0.65; A1AT, p = 0.20) exposure and any gut inflammation biomarkers; nor were interactive effects found between mycotoxins and pathogens in contributing to intestinal enteropathy in this cohort. Although further studies are needed to confirm these results, it is possible that mycotoxins contribute to child growth impairment via mechanisms other than disrupting children's intestinal function.     

Approximating the Independence Number and the Chromatic Number in Expected Polynomial Time

The independence number of a graph and its chromatic number are known to be hard to approximate. Due to recent complexity results, unless coRP = NP, there is no polynomial time algorithm which approximates any of these quantities within a factor of n ^1– for graphs on n vertices.We show that the situation is significantly better for the average case. For every edge probability p = p(n) in the range n ^–1/2+ p 3/4, we present an approximation algorithm for the independence number of graphs on n vertices, whose approximation ratio is O((np)^1/2/log n) and whose expected running time over the probability space G(n, p) is polynomial. An algorithm with similar features is described also for the chromatic number.A key ingredient in the analysis of both algorithms is a new large deviation inequality for eigenvalues of random matrices, obtained through an application of Talagrand's inequality.     

The complexity of VLSI power-delay optimization by?interconnect resizing

The lithography used for 32 nanometers and smaller VLSI process technologies restricts the interconnect widths and spaces to a very small set of admissible values. Until recently the sizes of interconnects were allowed to change continuously and the implied power-delay optimal tradeoff could be formulated as a convex programming problem, for which classical search algorithms are applicable. Once the admissible geometries become discrete, continuous search techniques are inappropriate and new combinatorial optimization solutions are in order. A first step towards such solutions is to study the complexity of the problem, which this paper is aiming at. Though dynamic programming has been shown lately to solve the problem, we show that it is NP-complete. Two typical VLSI design scenarios are considered. The first trades off power and sum of delays (L ₁), and is shown to be NP-complete by reduction of PARTITION. The second considers power and max delays (L _∞), and is shown to be NP-complete by reduction of SUBSET_SUM.     

A Characterization of Rationalizable Consumer Behavior

For an arbitrary data set D = {(p, x)} ⊆ (ℝ₊^m∖ {0}) × ℝ₊^m, finite or infinite, it is shown that the following three conditions are equivalent: (a) D satisfies GARP; (b) D can be rationalized by a utility function; (c) D can be rationalized by a utility function that is quasiconcave, nondecreasing, and that strictly increases when all its coordinates strictly increase. Examples of infinite data sets satisfying GARP are provided for which every utility rationalization fails to be lower semicontinuous, upper semicontinuous, or concave. Thus condition (c) cannot be substantively improved upon.     

Combinatorial Optimization in Real-Time Scheduling: Theory and Algorithms

Real-time computer systems are essential for many applications, such as robot control, avionics, medical instrumentation, manufacturing, etc. The correctness of the system depends on the temporal correctness as well as the functional correctness of the task executions. In order to assure temporal correctness it is necessary that the resources be scheduled to meet the temporal requirements of applications. When we consider the problem of nonpreemptive scheduling of a set of tasks in a processor for which no feasible solution exists, some tasks may have to be rejected so that a schedule can be generated for the rest. In this paper, we consider the problem of generating an optimal schedule such that the number of rejected tasks is minimized, and then the finish time is minimized for the accepted tasks. We propose to use an analytic approach to solve this problem. We first discuss the super sequence based technique which was originally proposed for reducing the search space in testing the feasibility of a task set. Then we show by the Conformation theorem that the super sequence constructed from the task set also provides a valid and reduced search space for the optimization problem. While the complexity of our scheduling algorithm in the worst case remains exponential, our simulation results show that the cost is reasonable for the average case.     

Perceptions and Expected Immediate Reactions to Severe Storm Displays

The National Weather Service has adopted warning polygons that more specifically indicate the risk area than its previous county‐wide warnings. However, these polygons are not defined in terms of numerical strike probabilities (p_s). To better understand people's interpretations of warning polygons, 167 participants were shown 23 hypothetical scenarios in one of three information conditions—polygon‐only (Condition A), polygon + tornadic storm cell (Condition B), and polygon + tornadic storm cell + flanking nontornadic storm cells (Condition C). Participants judged each polygon's p_s and reported the likelihood of taking nine different response actions. The polygon‐only condition replicated the results of previous studies; p_s was highest at the polygon's centroid and declined in all directions from there. The two conditions displaying storm cells differed from the polygon‐only condition only in having p_s just as high at the polygon's edge nearest the storm cell as at its centroid. Overall, p_s values were positively correlated with expectations of continuing normal activities, seeking information from social sources, seeking shelter, and evacuating by car. These results indicate that participants make more appropriate p_s judgments when polygons are presented in their natural context of radar displays than when they are presented in isolation. However, the fact that p_s judgments had moderately positive correlations with both sheltering (a generally appropriate response) and evacuation (a generally inappropriate response) suggests that experiment participants experience the same ambivalence about these two protective actions as people threatened by actual tornadoes.     

Is There a Curse of Dimensionality for Contraction Fixed Points in the Worst Case?

This paper analyzes the complexity of the contraction fixed point problem: compute an ε‐approximation to the fixed point V*Γ(V*) of a contraction mapping Γ that maps a Banach space B_d of continuous functions of d variables into itself. We focus on quasi linear contractions where Γ is a nonlinear functional of a finite number of conditional expectation operators. This class includes contractive Fredholm integral equations that arise in asset pricing applications and the contractive Bellman equation from dynamic programming. In the absence of further restrictions on the domain of Γ, the quasi linear fixed point problem is subject to the curse of dimensionality, i.e., in the worst case the minimal number of function evaluations and arithmetic operations required to compute an ε‐approximation to a fixed point V*∈B_d increases exponentially in d. We show that the curse of dimensionality disappears if the domain of Γ has additional special structure. We identify a particular type of special structure for which the problem is strongly tractable even in the worst case, i.e., the number of function evaluations and arithmetic operations needed to compute an ε‐approximation of V* is bounded by Cε^−p where C and p are constants independent of d. We present examples of economic problems that have this type of special structure including a class of rational expectations asset pricing problems for which the optimal exponent p1 is nearly achieved.     

Maximizing Profits of Routing in WDM Networks

Let G = (V, E) be a ring (or chain) network representing an optical wavelength division multiplexing (WDM) network with k channels, where each edge e_j has an integer capacity c_j. A request s_i,t_i is a pair of two nodes in G. Given m requests s_i,t_i, i = 1, 2, ..., m, each with a profit value p_i, we would like to design/route a k-colorable set of paths for some (may not be all) of the m requests such that each edge e_j in G is used at most c_j times and the total profit of the set of designed paths is maximized. Here two paths cannot have the same color (channel) if they share some common edge(s).This problem arises in optical communication networks. In this paper, we present a polynomial-time algorithm to solve the problem when G is a chain. When G is a ring, however, the optimization problem is NP-hard (Wan and Liu, 1998), we present a 2-approximation algorithm based on our solution to the chain network. Similarly, some results in a bidirected chain and a bidirected ring are obtained.     

Experience-weighted Attraction Learning in Normal Form Games

In ‘experience-weighted attraction’ (EWA) learning, strategies have attractions that reflect initial predispositions, are updated based on payoff experience, and determine choice probabilities according to some rule (e.g., logit). A key feature is a parameter δ that weights the strength of hypothetical reinforcement of strategies that were not chosen according to the payoff they would have yielded, relative to reinforcement of chosen strategies according to received payoffs. The other key features are two discount rates, φ and ρ, which separately discount previous attractions, and an experience weight. EWA includes reinforcement learning and weighted fictitious play (belief learning) as special cases, and hybridizes their key elements. When δ= 0 and ρ= 0, cumulative choice reinforcement results. When δ= 1 and ρ=φ, levels of reinforcement of strategies are exactly the same as expected payoffs given weighted fictitious play beliefs. Using three sets of experimental data, parameter estimates of the model were calibrated on part of the data and used to predict a holdout sample. Estimates of δ are generally around .50, φ around .8 − 1, and ρ varies from 0 to φ. Reinforcement and belief-learning special cases are generally rejected in favor of EWA, though belief models do better in some constant-sum games. EWA is able to combine the best features of previous approaches, allowing attractions to begin and grow flexibly as choice reinforcement does, but reinforcing unchosen strategies substantially as belief-based models implicitly do.     

A best on-line algorithm for the single machine parallel-batch scheduling with restricted delivery times

We consider a single batch machine on-line scheduling problem with delivery times. In this paper on-line means that jobs arrive over time and the characteristics of jobs are unknown until their arrival times. Once the processing of a job is completed it is delivered to the destination. The objective is to minimize the time by which all jobs have been delivered. For each job J _j , its processing time and delivery time are denoted by p _j and q _j , respectively. We consider two restricted models: (1) the jobs have small delivery times, i.e., for each job J _j , q _j ≤p _j ; (2) the jobs have agreeable processing and delivery times, i.e., for any two jobs J _i and J _j , p _i >p _j implies q _i ≥q _j . We provide an on-line algorithm with competitive ratio for both problems, and the results are the best possible. Project supported by NSFC (10671183).     

Probability of Exporting Infected Carcasses from Vaccinated Pigs Following a Foot‐and‐Mouth Disease Epidemic

Emergency vaccination is an effective control strategy for foot‐and‐mouth disease (FMD) epidemics in densely populated livestock areas, but results in a six‐month waiting period before exports can be resumed, incurring severe economic consequences for pig exporting countries. In the European Union, a one‐month waiting period has been discussed based on negative test results in a final screening. The objective of this study was to analyze the risk of exporting FMD‐infected pig carcasses from a vaccinated area: (1) directly after final screening and (2) after a six‐month waiting period. A risk model has been developed to estimate the probability that a processed carcass was derived from an FMD‐infected pig (P_carc). Key variables were herd prevalence (P_H), within‐herd prevalence (P_A), and the probability of detection at slaughter (P_SL). P_H and P_A were estimated using Bayesian inference under the assumption that, despite all negative test results, ≥1 infected pigs were present. Model calculations indicated that P_carc was on average 2.0 × 10^?5 directly after final screening, and 1.7 × 10^?5 after a six‐month waiting period. Therefore, the additional waiting time did not substantially reduce P_carc. The estimated values were worst‐case scenarios because only viraemic pigs pose a risk for disease transmission, while seropositive pigs do not. The risk of exporting FMD via pig carcasses from a vaccinated area can further be reduced by heat treatment of pork and/or by excluding high‐risk pork products from export.