Machine Learning, Human Factors and Security Analysis for the Remote Command of Driving: An MCity Pilot

Conducted under the U.S. DOT Office of the Assistant Secretary for Research and Technology’s (OST-R) University Transportation Centers (UTC) program.Both human drivers and autonomous vehicles are able to drive relatively well in frequently encountered settings, but fail in exceptional cases. These exceptional cases often arise suddenly, leaving human drivers with a few seconds at best to react—exactly the setting that people perform worst in. Autonomous systems also fail in exceptional cases, because ambiguous situations preceding crashes are not effectively captured in training datasets. This work introduces new methods for leveraging groups of people to provide on-demand assistance by coordinating responses and using collective answer distributions to generate responses to ambiguous scenarios using minimal time and effort. Unlike prior approaches, we introduce collective workflows that enable groups of people to significantly outperform any of the constituent individuals in terms of time and accuracy. First, we examine the latency and accuracy of crowd workers in a future state prediction task in visual driving scenes, and find that more than 50% of workers could provide accurate answers within one second. We found that using crowd predictions is a viable approach for determining critical future states to inform rapid decision making. Additionally, we characterize different estimation techniques that can be used to efficiently create collective answer distributions from crowd workers for visual tasks containing ambiguity. Surprisingly, we discovered that the most fine-grained and time-consuming methods were not the most accurate. Instead, having annotators choose all relevant responses they thought other annotators would select led to more accurate aggregate outcomes. This approach reduced human time required by 21.4% while maintaining the same level of accuracy as the baseline approach. These research results can inform the development of hybrid intelligence systems that accurately and rapidly address sudden and rare critical events, even when they are ambiguous or subjective.United States Department of Transportation Office of the Assistant Secretary for Research and TechnologyCenter for Connected and Automated Transportationhttp://deepblue.lib.umich.edu/bitstream/2027.42/156392/4/Machine Learning Human Factors and Security Analysis for the Remote Command of Driving - An Mcity Pilot.pd

Ineffectiveness of colchicine for the prevention of restenosis after coronary angioplasty

AbstractColchicine, an antimitogenic agent, has shown promise in preventing restenosis after coronary angioplasty in experimental animal models. A prospective trial was conducted involving 197 patients randomized in a 2:1 fashion to treatment with oral colchicine, 0.6 mg twice daily (130 patients), or placebo (67 patients) for 6 months after elective coronary angioplasty. Treatment in all patients began between 12 h before angioplasty and 24 h after angioplasty. Compliance monitoring revealed that 96% of all prescribed pills were ingested. Demographic characteristics were similar in colchicine- and placebo-treated groups. A mean of 2.7 lesions/patient were dilated. Side effects resulted in a 6.9% dropout rate in the colchicine-treated patients.Complete quantitative angiographic follow-up was obtained in 145 patients (74%) with 393 dilated lesions. Quantitative angiographic measurements were obtained in two orthogonal views at baseline before angioplasty and immediately and at 6 months after angioplasty. The quantitative mean lumen diameter stenosis before angioplasty was 67% both in the 152 lesions in the placebo-treated group and in the 241 lesions in the colchkine-treated group; this value was reduced to 24% immediately after angio-plasty in the lesions in both treatment groups.At the 6-month angiogram, lesions had restenosed to 47% lumen diameter narrowing in the placebo-treated group compared with 46% in the colchicine-treated group (p = NS). Forty-one percent of colchicine-treated patients developed restenosis in at least one lesion compared with 45% of the placebo-treated group (p = NS). In conclusion, colchicine was ineffective for preventing restenosis after coronary angioplasty

Gas emissions, minerals, and tars associated with three coal fires, Powder River Basin, USA.

Ground-based surveys of three coal fires and airborne surveys of two of the fires were conducted near Sheridan, Wyoming. The fires occur in natural outcrops and in abandoned mines, all containing Paleocene-age subbituminous coals. Diffuse (carbon dioxide (CO(2)) only) and vent (CO(2), carbon monoxide (CO), methane, hydrogen sulfide (H(2)S), and elemental mercury) emission estimates were made for each of the fires. Additionally, gas samples were collected for volatile organic compound (VOC) analysis and showed a large range in variation between vents. The fires produce locally dangerous levels of CO, CO(2), H(2)S, and benzene, among other gases. At one fire in an abandoned coal mine, trends in gas and tar composition followed a change in topography. Total CO(2) fluxes for the fires from airborne, ground-based, and rate of fire advancement estimates ranged from 0.9 to 780mg/s/m(2) and are comparable to other coal fires worldwide. Samples of tar and coal-fire minerals collected from the mouth of vents provided insight into the behavior and formation of the coal fires

A novel approach to model cumulative stress:Area under the s-factor curve

OBJECTIVE: Using a large longitudinal sample of adults from the Midlife in the United States (MIDUS) study, the present study extended a recently developed hierarchical model to determine how best to model the accumulation of stressors, and to determine whether the rate of change in stressors or traditional composite scores of stressors are stronger predictors of health outcomes.METHOD: We used factor analysis to estimate a stress-factor score and then, to operationalize the accumulation of stressors we examined five approaches to aggregating information about repeated exposures to multiple stressors. The predictive validity of these approaches was then assessed in relation to different health outcomes.RESULTS: The prediction of chronic conditions, body mass index, difficulty with activities of daily living, executive function, and episodic memory later in life was strongest when the accumulation of stressors was modeled using total area under the curve (AUC) of estimated factor scores, compared to composite scores that have traditionally been used in studies of cumulative stress, as well as linear rates of change.CONCLUSIONS: Like endogenous, biological markers of stress reactivity, AUC for individual trajectories of self-reported stressors shows promise as a data reduction technique to model the accumulation of stressors in longitudinal studies. Overall, our results indicate that considering different quantitative models is critical to understanding the sequelae and predictive power of psychosocial stressors from midlife to late adulthood.</p

Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time

Background Laser-Doppler imaging (LDI) of cutaneous blood flow is beginning to be used by burn surgeons to predict the healing time of burn wounds; predicted healing time is used to determine wound treatment as either dressings or surgery. In this paper, we do a statistical analysis of the performance of the technique. Methods We used data from a study carried out by five burn centers: LDI was done once between days 2 to 5 post burn, and healing was assessed at both 14 days and 21 days post burn. Random-effects ordinal logistic regression and other models such as the continuation ratio model were used to model healing-time as a function of the LDI data, and of demographic and wound history variables. Statistical methods were also used to study the false-color palette, which enables the laser-Doppler imager to be used by clinicians as a decision-support tool. Results Overall performance is that diagnoses are over 90% correct. Related questions addressed were what was the best blood flow summary statistic and whether, given the blood flow measurements, demographic and observational variables had any additional predictive power (age, sex, race, % total body surface area burned (%TBSA), site and cause of burn, day of LDI scan, burn center). It was found that mean laser-Doppler flux over a wound area was the best statistic, and that, given the same mean flux, women recover slightly more slowly than men. Further, the likely degradation in predictive performance on moving to a patient group with larger %TBSA than those in the data sample was studied, and shown to be small. Conclusion Modeling healing time is a complex statistical problem, with random effects due to multiple burn areas per individual, and censoring caused by patients missing hospital visits and undergoing surgery. This analysis applies state-of-the art statistical methods such as the bootstrap and permutation tests to a medical problem of topical interest. New medical findings are that age and %TBSA are not important predictors of healing time when the LDI results are known, whereas gender does influence recovery time, even when blood flow is controlled for. The conclusion regarding the palette is that an optimum three-color palette can be chosen 'automatically', but the optimum choice of a 5-color palette cannot be made solely by optimizing the percentage of correct diagnoses

Encouraging eyewitnesses to falsely corroborate allegations: effects of rapport-building and incriminating evidence

Building rapport involves developing a harmonious relationship with another person and conveying understanding and acceptance towards that person. Law enforcement officers use rapport-building to help gather information from witnesses. But could rapport-building, in some situations, work to contaminate eyewitness testimony? Research shows that compelling incriminating evidence can lead people to corroborate false accusations made against another person. We investigated whether rapport-building – when combined with either Verbal or Verbal+Visual false evidence – might boost these corroboration rates. Subjects took part in a pseudo-gambling task, in which their counterpart was falsely accused of cheating. Using a 2 (Rapport: Rapport vs. No-rapport) × 2 (Incriminating Evidence: Verbal vs. Verbal+Visual) between-subjects design, we persuaded subjects to corroborate the accusation. We found that both rapport and verbal+visual incriminating evidence increased the compliance rate. Even when the incriminating evidence was only presented verbally, rapport-building subjects were almost three times as likely to corroborate a false accusation compared to subjects who did not undergo rapport-building. Our results suggest that although there is widespread and strong support for using rapport-building in interviews, doing so also has the potential to aggravate the contaminating power of suggestive interview techniques

Enhancement of a modified Mediterranean-style, low glycemic load diet with specific phytochemicals improves cardiometabolic risk factors in subjects with metabolic syndrome and hypercholesterolemia in a randomized trial

<p>Abstract</p> <p>Background</p> <p>As the worldwide dietary pattern becomes more westernized, the metabolic syndrome is reaching epidemic proportions. Lifestyle modifications including diet and exercise are recommended as first-line intervention for treating metabolic syndrome. Previously, we reported that a modified Mediterranean-style, low glycemic load diet with soy protein and phytosterols had a more favorable impact than the American Heart Association Step 1 diet on cardiovascular disease (CVD) risk factors. Subsequently, we screened for phytochemicals with a history of safe use that were capable of increasing insulin sensitivity through modulation of protein kinases, and identified hops <it>rho </it>iso-alpha acid and acacia proanthocyanidins. The objective of this study was to investigate whether enhancement of a modified Mediterranean-style, low glycemic load diet (MED) with specific phytochemicals (soy protein, phytosterols, <it>rho </it>iso-alpha acids and proanthocyanidins; PED) could improve cardiometabolic risk factors in subjects with metabolic syndrome and hypercholesterolemia.</p> <p>Methods</p> <p>Forty-nine subjects with metabolic syndrome and hypercholesterolemia, aged 25–80, entered a randomized, 2-arm, 12-week intervention trial; 23 randomized to the MED arm; 26 to the PED arm. Forty-four subjects completed at least 8 weeks [MED (<it>n </it>= 19); PED (<it>n </it>= 25)]. All subjects were instructed to follow the same aerobic exercise program. Three-day diet diaries and 7-day exercise diaries were assessed at each visit. Fasting blood samples were collected at baseline, 8 and 12 weeks for analysis.</p> <p>Results</p> <p>Both arms experienced equal weight loss (MED: -5.7 kg; PED: -5.9 kg). However, at 12 weeks, the PED arm experienced greater reductions (<it>P </it>< 0.05) in cholesterol, non-HDL cholesterol, triglycerides (TG), cholesterol/HDL and TG/HDL compared with the MED arm. Only the PED arm experienced increased HDL (<it>P </it>< 0.05) and decreased TG/HDL (<it>P </it>< 0.01), and continued reduction in apo B/apo A-I from 8 to 12 weeks. Furthermore, 43% of PED subjects vs. only 22% of MED subjects had net resolution of metabolic syndrome. The Framingham 10-year CVD risk score decreased by 5.6% in the PED arm (<it>P </it>< 0.01) and 2.9% in the MED arm (<it>P </it>< 0.05).</p> <p>Conclusion</p> <p>These results demonstrate that specific phytochemical supplementation increased the effectiveness of the modified Mediterranean-style low glycemic load dietary program on variables associated with metabolic syndrome and CVD.</p

Understanding how perceptions of tobacco constituents and the FDA relate to effective and credible tobacco risk messaging: A national phone survey of U.S. adults, 2014–2015

As reported in the original paper [1], the Center for Regulatory Research on Tobacco Communication conducted a telephone survey in 2014–2015 with a national sample of adults ages 18 and older living in the United States (N = 5014). Poverty level was determined using the household size and income reported by the respondents and applying the federal poverty numbers available from the U.S. Department of Health and Human Services in 2014. A coding error was made during the data recoding process such that 2.7% of respondents (n = 129) were incorrectly classified as living above the poverty line. Below are updated Tables 1, 2 and 4 presenting both the original and corrected estimates. No substantive conclusions reported in the paper were affected by this correction