In-Vehicle Human Machine Interface: Investigating the Effects of Tactile Displays on Information Presentation in Automated Vehicles

Background: Semi-autonomous vehicles still require human drivers to take over when the automated systems can no longer perform the driving task. Objective: The goal of this study was to design and test the effects of six meaningful tactile signal types, representing six driving scenarios (i.e., navigation, speed, surrounding vehicles, over the speed limit, headway reductions, and pedestrian status) respectively, and two pattern durations (lower and higher urgencies), on drivers\u27 perception and performance during automated driving. Methods: Sixteen volunteers participated in an experiment utilizing a medium-fidelity driving simulator presenting vibrotactile signals via 20 tactors embedded in the seat back, pan, and belt. Participants completed four separate driving sessions with 30 tactile signals presented randomly throughout each drive. Reaction times (RT), interpretation accuracy, and subjective ratings were measured. Results: Results illustrated shorter RTs and higher intuitive ratings for higher urgency patterns than lower urgency patterns. Pedestrian status and headway reduction signals were associated with shorter RTs and increased confidence ratings, compared to other tactile signal types. Lastly, among six tactile signals, surrounding vehicle and navigation signal types had the highest interpretation accuracy. Conclusion: These results will be used as preliminary data for future studies that aim to investigate the effects of meaningful tactile displays on automated vehicle takeover performance in complex situations (e.g., urban areas) where actual takeovers are required. The findings of this study will inform the design of next-generation in-vehicle human-machine interfaces

Exploring the Effects of Meaningful Tactile Display on Perception and Preference in Automated Vehicles

There is an existing issue in human-machine interaction, such that drivers of semi-autonomous vehicles are still required to take over control of the vehicle during system limitations. A possible solution may lie in tactile displays, which can present status, direction, and position information while avoiding sensory (e.g., visual and auditory) channels overload to reliably help drivers make timely decisions and execute actions to successfully take over. However, limited work has investigated the effects of meaningful tactile signals on takeover performance. This study synthesizes literature investigating the effects of tactile displays on takeover performance in automated vehicles and conducts a human-subject study to design and test the effects of six meaningful tactile signal types and two pattern durations on drivers’ perception and performance during automated driving. The research team performed a literature review of 18 articles that conducted human-subjects experiments on takeover performance utilizing tactile displays as takeover requests. Takeover performance in these studies were highlighted, such as response times, workload, and accuracy. The team then conducted a human-subject experiment, which included 16 participants that used a driving simulator to present 30 meaningful vibrotactile signals, randomly across four driving sessions measuring for reaction times (RTs), interpretation accuracy, and subjective ratings. Results from the literature suggest that tactile displays can present meaningful vibrotactile patterns via various in-vehicle locations to help improve drivers’ performance during the takeover and can be used to assist in the design of human-machine interfaces (HMI) for automated vehicles. The experiment yielded results illustrating higher urgency patterns were associated with shorter RTs and higher intuitive ratings. Also, pedestrian status and headway reduction signals presented shorter RTs and increased confidence ratings compared to other tactile signal types. Finally, the signal types that yielded the highest accuracy were the surrounding vehicle and navigation signal types. Implications of these findings may lie in informing the design of next-generation in-vehicle HMIs and future human factors studies on human-automation interactions

Stellar and Planetary Parameters for K2's Late-type Dwarf Systems from C1 to C5

The NASA K2 mission uses photometry to find planets transiting stars of various types. M dwarfs are of high interest since they host more short-period planets than any other type of main-sequence star and transiting planets around M dwarfs have deeper transits compared to other main-sequence stars. In this paper, we present stellar parameters from K and M dwarfs hosting transiting planet candidates discovered by our team. Using the SOFI spectrograph on the European Southern Observatory's New Technology Telescope, we obtained R ≈ 1000 J-, H-, and K-band (0.95–2.52 μm) spectra of 34 late-type K2 planet and candidate planet host systems and 12 bright K4–M5 dwarfs with interferometrically measured radii and effective temperatures. Out of our 34 late-type K2 targets, we identify 27 of these stars as M dwarfs. We measure equivalent widths of spectral features, derive calibration relations using stars with interferometric measurements, and estimate stellar radii, effective temperatures, masses, and luminosities for the K2 planet hosts. Our calibrations provide radii and temperatures with median uncertainties of 0.059 R⊙ (16.09%) and 160 K (4.33%), respectively. We then reassess the radii and equilibrium temperatures of known and candidate planets based on our spectroscopically derived stellar parameters. Since a planet's radius and equilibrium temperature depend on the parameters of its host star, our study provides more precise planetary parameters for planets and candidates orbiting late-type stars observed with K2. We find a median planet radius and an equilibrium temperature of approximately 3 R⊕ and 500 K, respectively, with several systems (K2-18b and K2-72e) receiving near-Earth-like levels of incident irradiation

Prenatal Tobacco Smoke Exposure Is Associated with Childhood DNA CpG Methylation

Background: Smoking while pregnant is associated with a myriad of negative health outcomes in the child. Some of the detrimental effects may be due to epigenetic modifications, although few studies have investigated this hypothesis in detail.Objectives: To characterize site-specific epigenetic modifications conferred by prenatal smoking exposure within asthmatic children.Methods: Using Illumina HumanMethylation27 microarrays, we estimated the degree of methylation at 27,578 distinct DNA sequences located primarily in gene promoters using whole blood DNA samples from the Childhood Asthma Management Program (CAMP) subset of Asthma BRIDGE childhood asthmatics (n = 527) ages 5–12 with prenatal smoking exposure data available. Using beta-regression, we screened loci for differential methylation related to prenatal smoke exposure, adjusting for gender, age and clinical site, and accounting for multiple comparisons by FDR.Results: Of 27,578 loci evaluated, 22,131 (80%) passed quality control assessment and were analyzed. Sixty-five children (12%) had a history of prenatal smoke exposure. At an FDR of 0.05, we identified 19 CpG loci significantly associated with prenatal smoke, of which two replicated in two independent populations. Exposure was associated with a 2% increase in mean CpG methylation in FRMD4A (p = 0.01) and Cllorf52 (p = 0.001) compared to no exposure. Four additional genes, XPNPEP1, PPEF2, SMPD3 and CRYGN, were nominally associated in at least one replication group.Conclusions: These data suggest that prenatal exposure to tobacco smoke is associated with reproducible epigenetic changes that persist well into childhood. However, the biological significance of these altered loci remains unknown.</p

Prenatal Tobacco Smoke Exposure Is Associated with Childhood DNA CpG Methylation

Background: Smoking while pregnant is associated with a myriad of negative health outcomes in the child. Some of the detrimental effects may be due to epigenetic modifications, although few studies have investigated this hypothesis in detail. Objectives: To characterize site-specific epigenetic modifications conferred by prenatal smoking exposure within asthmatic children. Methods: Using Illumina HumanMethylation27 microarrays, we estimated the degree of methylation at 27,578 distinct DNA sequences located primarily in gene promoters using whole blood DNA samples from the Childhood Asthma Management Program (CAMP) subset of Asthma BRIDGE childhood asthmatics (n = 527) ages 5–12 with prenatal smoking exposure data available. Using beta-regression, we screened loci for differential methylation related to prenatal smoke exposure, adjusting for gender, age and clinical site, and accounting for multiple comparisons by FDR. Results: Of 27,578 loci evaluated, 22,131 (80%) passed quality control assessment and were analyzed. Sixty-five children (12%) had a history of prenatal smoke exposure. At an FDR of 0.05, we identified 19 CpG loci significantly associated with prenatal smoke, of which two replicated in two independent populations. Exposure was associated with a 2% increase in mean CpG methylation in FRMD4A (p = 0.01) and Cllorf52 (p = 0.001) compared to no exposure. Four additional genes, XPNPEP1, PPEF2, SMPD3 and CRYGN, were nominally associated in at least one replication group. Conclusions: These data suggest that prenatal exposure to tobacco smoke is associated with reproducible epigenetic changes that persist well into childhood. However, the biological significance of these altered loci remains unknown

Toward a chemical reanalysis in a coupled chemistry-climate model: an evaluation of MOPITT CO assimilation and its impact on tropospheric composition

We examine in detail a 1 year global reanalysis of carbon monoxide (CO) that is based on joint assimilation of conventional meteorological observations and Measurement of Pollution in The Troposphere (MOPITT) multispectral CO retrievals in the Community Earth System Model (CESM). Our focus is to assess the impact to the chemical system when CO distribution is constrained in a coupled full chemistry-climate model like CESM. To do this, we first evaluate the joint reanalysis (MOPITT Reanalysis) against four sets of independent observations and compare its performance against a reanalysis with no MOPITT assimilation (Control Run). We then investigate the CO burden and chemical response with the aid of tagged sectoral CO tracers. We estimate the total tropospheric CO burden in 2002 (from ensemble mean and spread) to be 371 ± 12% Tg for MOPITT Reanalysis and 291 ± 9% Tg for Control Run. Our multispecies analysis of this difference suggests that (a) direct emissions of CO and hydrocarbons are too low in the inventory used in this study and (b) chemical oxidation, transport, and deposition processes are not accurately and consistently represented in the model. Increases in CO led to net reduction of OH and subsequent longer lifetime of CH4 (Control Run: 8.7 years versus MOPITT Reanalysis: 9.3 years). Yet at the same time, this increase led to 5-10% enhancement of Northern Hemisphere O3 and overall photochemical activity via HOx recycling. Such nonlinear effects further complicate the attribution to uncertainties in direct emissions alone. This has implications to chemistry-climate modeling and inversion studies of longer-lived species

Carcinogen metabolism genes, red meat and poultry intake, and colorectal cancer risk

Diets high in red meat are established risk factors for colorectal cancer (CRC). Carcinogenic compounds generated during meat cooking have been implicated as causal agents. We conducted a family-based case-control study to investigate the association between polymorphisms in carcinogen metabolism genes (CYP1A2 -154A>C, CYP1B1 Leu432Val, CYP2E1 -1054C>T, GSTP1 Ile105Val, PTGS2 5UTR -765, EPHX1 Tyr113His, NAT2 Ile114Thr, NAT2 Arg197Gln and NAT2 Gly286Glu) and CRC risk. We tested for gene-environment interactions using case-only analyses (N = 577) and compared statistically significant results to those obtained using case-unaffected sibling comparisons (N = 307 sibships)

Polymorphisms in Base Excision Repair Genes as Colorectal Cancer Risk Factors and Modifiers of the Effect of Diets High in Red Meat

A diet high in red meat is an established colorectal cancer (CRC) risk factor. Carcinogens generated during meat cooking have been implicated as causal agents, and can induce oxidative DNA damage, which elicits repair by the base excision repair (BER) pathway