Detecting Distracted Driving with Deep Learning

© Springer International Publishing AG 2017Driver distraction is the leading factor in most car crashes and near-crashes. This paper discusses the types, causes and impacts of distracted driving. A deep learning approach is then presented for the detection of such driving behaviors using images of the driver, where an enhancement has been made to a standard convolutional neural network (CNN). Experimental results on Kaggle challenge dataset have confirmed the capability of a convolutional neural network (CNN) in this complicated computer vision task and illustrated the contribution of the CNN enhancement to a better pattern recognition accuracy.Peer reviewe

Crash dieting: The effects of eating and drinking on driving performance

Previous research suggests that compared to mobile phone use, eating and drinking while driving is more common and is seen as lower risk by drivers. Nevertheless, snacking at the wheel can affect vehicle control to a similar extent as using a hands-free phone, and is actually a causal factor in more crashes. So far, though, there has not been a controlled empirical study of this problem. In an effort to fill this gap in the literature, we used the Brunel University Driving Simulator to test participants on a typical urban scenario. At designated points on the drive, which coincided with instructions to eat or drink, a critical incident was simulated by programming a pedestrian to walk in front of the car. Whilst the driving performance variables measured were relatively unaffected by eating and drinking, perceived driver workload was significantly higher and there were more crashes in the critical incident when compared to driving normally. Despite some methodological limitations of the study, when taken together with previous research, the evidence suggests that the physical demands of eating and drinking while driving can increase the risk of a crash

Ultrafast Structural Dynamics of BlsA, a Photoreceptor from the Pathogenic Bacterium Acinetobacter baumannii

Acinetobacter baumannii is an important human pathogen that can form biofilms and persist under harsh environmental conditions. Biofilm formation and virulence are modulated by blue light, which is thought to be regulated by a BLUF protein, BlsA. To understand the molecular mechanism of light sensing, we have used steady-state and ultrafast vibrational spectroscopy to compare the photoactivation mechanism of BlsA to the BLUF photosensor AppA from Rhodobacter sphaeroides. Although similar photocycles are observed, vibrational data together with homology modeling identify significant differences in the β5 strand in BlsA caused by photoactivation, which are proposed to be directly linked to downstream signaling

BLUF Domain Function Does Not Require a Metastable Radical Intermediate State

BLUF (blue light using flavin) domain proteins are an important family of blue light-sensing proteins which control a wide variety of functions in cells. The primary light-activated step in the BLUF domain is not yet established. A number of experimental and theoretical studies points to a role for photoinduced electron transfer (PET) between a highly conserved tyrosine and the flavin chromophore to form a radical intermediate state. Here we investigate the role of PET in three different BLUF proteins, using ultrafast broadband transient infrared spectroscopy. We characterize and identify infrared active marker modes for excited and ground state species and use them to record photochemical dynamics in the proteins. We also generate mutants which unambiguously show PET and, through isotope labeling of the protein and the chromophore, are able to assign modes characteristic of both flavin and protein radical states. We find that these radical intermediates are not observed in two of the three BLUF domains studied, casting doubt on the importance of the formation of a population of radical intermediates in the BLUF photocycle. Further, unnatural amino acid mutagenesis is used to replace the conserved tyrosine with fluorotyrosines, thus modifying the driving force for the proposed electron transfer reaction; the rate changes observed are also not consistent with a PET mechanism. Thus, while intermediates of PET reactions can be observed in BLUF proteins they are not correlated with photoactivity, suggesting that radical intermediates are not central to their operation. Alternative nonradical pathways including a keto–enol tautomerization induced by electronic excitation of the flavin ring are considered

Femtosecond Stimulated Raman Study of the Photoactive Flavoprotein AppABLUF

Femtosecond stimulated Raman Spectroscopy (FSRS) is applied to study the photocycle of a blue light using flavin (BLUF) domain photoreceptor, AppABLUF. It is shown that FSRS spectra are sensitive to the light adapted state of the protein and probe its excited state dynamics. The dominant contribution to the most sensitive excited state Raman active modes is from flavin ring modes. However, TD-DFT calculations for excited state structures indicate that reproduction and assignment of the experimentally observed spectral shift will require high level calculations on the flavin in its specific protein environment

Mechanistic Studies of the Photoactive Protein AppA

The blue light using flavin (BLUF) domain proteins are a novel class of photosensors that bind flavin noncovalently in order to sense and respond to high intensity blue (450 nm) light. The transcriptional antirepressor AppA, is a BLUF photosensor that utilizes a non-covalently bound flavin chromophore which is unable to undergo large scale structural change upon light absorption in contrast to most photoreceptors such as rhodopsin, which undergo structural alterations such as trans/cis isomerization upon irradiation. It is thus of great interest to understand how the BLUF protein matrix senses and responds to flavin photoexcitation. In order to probe the mechanism of photoactivation, the excited state photochemistry of wild-type and mutant AppA proteins has been analyzed using ultrafast time resolved infrared (TRIR) spectroscopy. Reconstitution of the protein with isotopically labeled flavin has permitted unambiguous assignment of the ground and excited state modes associated with the flavin C2=O and C4=O groups which participate in a hydrogen bonding network that surrounds the flavin. This approach has allowed us to probe the role of the hydrogen bonding network in AppA activation. Isotope labeling of the Q63E mutant allowed assignment of a protein mode that appears within 100 fs of excitation, demonstrating that the protein matrix responds instantaneously to flavin excitation. These data have led to a detailed understanding of the photoexcitation mechanism, which involves a tautomerization followed by rotation of residue Q63. Additional insight into photoactivation of AppA has also been obtained by replacing a key tyrosine in the hydrogen bonding network with unnatural fluorotyrosine analogs that have altered pKa values. These data have established the acidity of residue Y21 is crucial in stabilizing the light activated form of the protein. | 205 page

Qualitative Methods and Sight-impairment: developing a toolkit for inclusive teaching.

Background Research methods is a key component of a psychology degree and recognised as a challenging topic to learn and teach. However, students who have sight-impairments experience additional barriers to its study, which could inhibit life-long learning in this area. Despite a growing body of literature to guide inclusive teaching practices for quantitative methods, little (if anything) is available for qualitative methods. However, these methods are traditionally taught using visual techniques (e.g. thematic maps), presenting barriers to learners with sight-impairments. This (ongoing) project explores the experience of learning qualitative methods from the perspectives of both students and tutors, in order to develop a “toolkit” to guide inclusive teaching-practice. Developing more inclusive teaching practice would likely benefit all students and help to promote engagement and learning of research methods. Design This inductive qualitative research forms part of a “Students as Academic Partners” project, due to be completed by May 2018. Methods Students and tutors from the University of Worcester, with experience of learning/teaching qualitative methods in relation to sight-impairment will be recruited using opportunistic and snowball sampling. Data will be collected using semi-structured interviews and analysed using thematic analysis. Results Barriers to learning qualitative methods and strategies adopted to manage these will be explored. In particular, it is important tutors recognise sight-impairment is not “one thing”, and that a range of strategies for adapting teaching-practice is required for diverse needs to be met. Conclusions The experience of learning qualitative methods for students who have sight-impairments has received little attention, making it difficult to identify inclusive teaching-practice in this area. This research outlines a toolkit with practical recommendations that tutors can draw on so their practice can better meet the needs of learners with sight-impairments

The impact of remote teaching on statistics learning and anxiety

In March 2020, staff and students at UK universities had to suddenly transition from on-campus teaching to remote learning as a result of the pandemic, which continued throughout the 2020/21 academic year. Unlike traditional online learners, students may lack the motivation or confidence to learn as effectively online particularly for modules such as statistics which students often find difficult or stressful face to face.This paper uses survey results from students studying elective and compulsory statistics modules in the 2020/21 academic year to gain an insight into remote learning of statistics from the students’ perspective.When compared to previous face to face teaching of statistics, students were less likely to actively engage with material, ask for help or work with peers remotely. Emotional wellbeing, motivation to learn, statistics anxiety and having a suitable learning environment all impacted on being able to learn statistics remotely. Although statistics anxiety in online teaching situations was generally lower, there was no evidence to suggest anxious students would benefit from online learning going forward

The Prevalence and Volumetry of Pituitary Cysts in Children with Growth Hormone Deficiency and Idiopathic Short Stature

Background Pituitary cysts have been speculated to cause endocrinopathies. We sought to describe the prevalence and volumetry of pituitary cysts in patients with growth hormone deficiency (GHD) and idiopathic short stature (ISS). Methods Six hundred and eighteen children evaluated for growth failure at the Division of Pediatric Endocrinology at New York Medical College between the years 2002 and 2012, who underwent GH stimulation testing and had a brain magnetic resonance imaging (MRI) prior to initiating GH treatment were randomly selected to be a part of this study. High resolution MRI was used to evaluate the pituitary gland for size and the presence of a cyst. Cyst prevalence, cyst volume and percentage of the gland occupied by the cyst (POGO) were documented. Results Fifty-six patients had a cyst, giving an overall prevalence of 9.1%. The prevalence of cysts in GHD patients compared to ISS patients was not significant (13.5% vs. 5.7%, p=0.46). Mean cyst volume was greater in GHD patients than ISS patients (62.0 mm3 vs. 29.4 mm3, p=0.01). POGO for GHD patients was significantly greater (p=0.003) than for ISS patients (15.3%+/-12.8 vs. 7.1%+/-8.0). Observers were blinded to patient groups. Conclusions GHD patients had a significantly greater volume and POGO compared to ISS patients. This raises the question of whether cysts are implicated in the pathology of growth failure

Are students too anxious for statistics anxiety workshops?

Statistics is a widely taught subject in Higher Education but for many students, anxiety about statistics interferes with the learning process. Statistics anxiety workshops to help students understand and reduce statistics anxiety were developed by the authors and in 2020/21 delivered collaboratively and remotely with specific cohorts of students at three institutions. Prior to the workshops, all students within the targeted cohorts were asked to complete a survey which included measures of statistics anxiety, and asked if they were interested in attending the voluntary workshop. This enabled a comparison of the characteristics of groups who were interested or not. The workshops successfully attracted the targeted students, since those attending had higher overall statistics anxiety, software and maths anxiety, and anxiety around learning statistics. However, students with higher help seeking anxiety were less likely to attend