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The development of Shared Automated Vehicles (SAVs) is well underway to provide mobility as a service (MaaS) and bring benefits such as reduced traffic congestion, reduced reliance on privately owned vehicles and increased independence to non-drivers. To realise the benefits of SAVs, adoption by private vehicle users is crucial. Previous research has shown this subset of users as the least likely to adopt SAVs, and it is not well understood what factors are important to achieve such adoption. The purpose of this study is to obtain an in-depth understanding of attitudes, perceptions and preferences that influence the acceptance of future SAVs for drivers. This paper presents the results from an online asynchronous focus group study with 21 British drivers as participants. From the analysis, Service Quality, Trust and Price Value emerged as the three most prominent factors to understand user acceptance of SAVs. These three main factors may be of prime importance for convincing naive private car owners to accept high-speed SAVs. Productive use of travel time has been frequently mentioned in previous research as a benefit of vehicle automation but was scarcely mentioned by participants in this study. Shared Space Quality in introduced as an indicator for Service Quality, together with Security and Trusting Co-passengers as two indicators of Trust. Based on the findings, this paper concludes with a conceptual SAV technology acceptance model is introduced, with the results added as extended model predictors to the Unified Theory of Acceptance and Use of Technology (UTAUT2).

Background Live oral pentavalent bovine-human reassortant rotavirus (RV) vaccine, RotaTeq®, contains bovine rotaviruses reassorted with human G-types G1, G2, G3 and G4, and P-type P[8]. Shedding of RotaTeq® vaccine, as studied by RT-PCR, has been shown to be more common than initially reported, and may include formation of vaccine-derived double-reassortant G1P[8] RVs. We studied the extent and duration of RotaTeq® vaccine virus shedding, genotypes shed, and clinical symptoms associated with shedding. Material and methods We enrolled a total of 301 infants who received RotaTeq® vaccine according to Finnish schedule at 2, 3 and 5 months of age. Stool samples were collected 5–10 days after the first and 0–7 days before the third dose of the vaccine. Additional stool samples 6 and 12 weeks later were collected if the second stool sample was positive. All stools were studied with RT-PCR for RV VP7, VP4 and VP6. Parents filled a symptom diary for a week after each vaccine dose. Results We found that 93% of the vaccinees shed vaccine related viral particles in one sample taken 5–10 days after the first dose, indicating that stool shedding is very common and may be regarded as a marker of successful vaccination. Genotype G1 was the predominant genotype in shedding, often in association with P[8], and the only genotype found in long-term shedding. Also G4 was commonly detected whereas other vaccine G-types and bovine-type P[5] were not. Conclusions Shedding of RotaTeq® vaccine-derived viruses is a sign for successful vaccination. Intense shedding of G1 with or without P[8]reflects effective multiplication and may be an important factor in the induction of protective immunity. Shedding of G1 containing vaccine viruses may be prolonged up to 8 months of age. These results suggest that the pentavalent vaccine functions largely like a monovalent G1 vaccine. Eudra-CT: 2014-004252-60.

Context Software startups develop innovative products through which they scale their business rapidly, and thus, provide value to the economy, including job generation. However, most startups fail within two years of their launch because of a poor problem-solution fit and negligence of the learning process during minimum viable product (MVP) development. An ideal startup ecosystem can assist in MVP development by providing the necessary entrepreneurial education and technical skills to founding team members for identifying problem-solution fit for their product idea, allowing them to find the right product-market fit. However, existing knowledge on the effect of the startup ecosystem elements on the MVP development is limited. Objective The empirical study presented in this article aims to identify the effect of the six ecosystem elements (entrepreneurs, technology, market, support factors, finance, and human capital) on MVP development. Method We conducted a study with 13 software startups and five supporting organizations (accelerators, incubator, co-working space, and investment firm) in the startup ecosystem of the city of Oulu in Finland. Data were collected through semi-structured interviews, observation, and materials. Results The study results showed that internal sources are most common for identifying requirements for the product idea for MVP development. The findings indicate that supporting factors, such as incubators and accelerators, can influence MVP development by providing young founders with the necessary entrepreneurship skills and education needed to create the right product-market fit. Conclusions We conclude from this study of a regional startup ecosystem that the MVP development process is most affected by founding team members’ experiences and skill sets and by advanced technologies. Furthermore, a constructive startup ecosystem around software startups can boost up the creation of an effective MVP to test product ideas and find a product-market fit.

Listeria monocytogenes causes the foodborne illness listeriosis, which exhibits high fatality among people in risk groups. The incidence of listeriosis has increased in Europe, which raises concerns about L. monocytogenes occurrence in foodstuffs. Ready-to-eat seafood products are considered particularly risky vehicles. Poor hygiene at processing facilities predisposes them to L. monocytogenes contamination, which can be controlled by stringent self-checking system measures. We examined the association of fish-processing plant operational and hygiene practices with the occurrence of L. monocytogenes in vacuum-packaged gravad (cold-salted) and cold-smoked salmon and rainbow trout products. Product sampling of 21 fish-processing plants was carried out, and operational procedures relating to L. monocytogenes control were surveyed using an in-depth risk assessment questionnaire. L. monocytogenes occurred only in sliced and mainly in gravad products of seven fish-processing plants. Shortages in preventive measures were discovered predominantly among the L. monocytogenes positive fish-processing plants. Using generalized linear modeling, we identified the following features associated with L. monocytogenes product contamination: the number of processing machines, deficiencies in the processing environment and machinery sanitation, and staff movement from areas of low toward high hygiene. Furthermore, performing frequent periodic thorough sanitation alongside everyday sanitation practices associated with a decreased risk of product contamination.

Driving simulators can be used to test vehicle designs earlier, prior to building physical prototypes. One area of particular interest is winter testing since testing is limited to specific times of year and specific regions in the world. To ensure that the simulator is fit for purpose, an objective assessment is required. In this study a simulator and real world comparison was performed with three simulator configurations (standard, no steering torque, no motion) to assess the ability of a utility triplet of analyses to be able to quantify the differences between the real world and the different simulator configurations. The results suggest that the utility triplet is effective in measuring the differences in simulator configurations and that the developed “Virtual Sweden” environment achieved rather good behavioural fidelity in the sense of preserving absolute levels of many measures of behaviour. The main limitation in the simulated environment seemed to be the poor match of the dynamic lateral friction limit on snow and ice when compared to the real world.

The popularity of continuous integration (CI) is increasing as a result of market pressure to release product features or updates frequently. The ability of CI to deliver quality at speed depends on reliable test automation. In this paper, we present an empirical study to observe the effect of test automation maturity (assessed by standard best practices in the literature) on product quality, test automation effort, and release cycle in the CI context of open source projects. We run our test automation maturity survey and got responses from 37 open source java projects. We also mined software repositories of the same projects. The main results of regression analysis reveal that, higher levels of test automation maturity are positively associated with higher product quality (p-value=0.000624) and shorter release cycle (p-value=0.01891); There is no statistically significant evidence of increased test automation effort due to higher levels of test automation maturity and product quality. Thus, we conclude that, a potential benefit of improving test automation maturity (using standard best practices) is product quality improvement and release cycle acceleration in the CI context of open source projects. We encourage future research to extend our findings by adding more datasets with different programming languages and CI tools, closed source projects, and large-scale industrial projects. Our recommendation to practitioners (in the similar CI context) is to utilize standard best practices to improve test automation maturity.

Previous studies have shown the effect of a lead vehicle’s speed, deceleration rate and headway distance on drivers’ brake response times. However, how drivers perceive this information and use it to determine when to apply braking is still not quite clear. To better understand the underlying mechanisms, a driving simulator experiment was performed where each participant experienced nine deceleration scenarios. Previously reported effects of the lead vehicle’s speed, deceleration rate and headway distance on brake response time were firstly verified in this paper, using a multilevel model. Then, as an alternative to measures of speed, deceleration rate and distance, two visual looming-based metrics (angular expansion rate θ ˙ of the lead vehicle on the driver’s retina, and inverse tau τ - 1 , the ratio between θ ˙ and the optical size θ ), considered to be more in line with typical human psycho-perceptual responses, were adopted to quantify situation urgency. These metrics were used in two previously proposed mechanistic models predicting brake onset: either when looming surpasses a threshold, or when the accumulated evidence (looming and other cues) reaches a threshold. Results showed that the looming threshold model did not capture the distribution of brake response time. However, regardless of looming metric, the accumulator models fitted the distribution of brake response times better than the pure threshold models. Accumulator models, including brake lights, provided a better model fit than looming-only versions. For all versions of the mechanistic models, models using τ - 1 as the measure of looming fitted better than those using θ ˙ , indicating that the visual cues drivers used during rear-end collision avoidance may be more close to τ - 1 .

Driver distraction is one of the main causes of motor-vehicle accidents. However, the impact on traffic safety of tasks that impose cognitive (non-visual) distraction remains debated. One particularly intriguing finding is that cognitive load seems to improve lane keeping performance, most often quantified as reduced standard deviation of lateral position (SDLP). The main competing hypotheses, supported by current empirical evidence, suggest that cognitive load improves lane keeping via either increased physical arousal, or higher gaze concentration toward the road center, but views are mixed regarding if, and how, these possible mediators influence lane keeping performance. Hence, a simulator study was conducted, with participants driving on a straight city road section whilst completing a cognitive task at different levels of difficulty. In line with previous studies, cognitive load led to increased physical arousal, higher gaze concentration toward the road center, and higher levels of micro-steering activity, accompanied by improved lane keeping performance. More importantly, during the high cognitive task, both physical arousal and gaze concentration changed earlier in time than micro-steering activity, which in turn changed earlier than lane keeping performance. In addition, our results did not show a significant correlation between gaze concentration and physical arousal on the level of individual task recordings. Based on these findings, various multilevel models for micro-steering activity and lane keeping performance were conducted and compared, and the results suggest that all of the mechanisms proposed by existing hypotheses could be simultaneously involved. In other words, it is suggested that cognitive load leads to: (i) an increase in arousal, causing increased micro-steering activity, which in turn improves lane keeping performance, and (ii) an increase in gaze concentration, causing lane keeping improvement through both (a) further increased micro-steering activity and (b) a tendency to steer toward the gaze target.

Studies on the effect of cognitive load (CL) on driving performance suggest that lane keeping performance is improved by cognitive distraction, due to a reduction in measures of the standard deviation of lateral position (SDLP). However, the effect of CL on drivers’ lateral control is still not fully understood, and previous studies have shown mixed conclusions regarding the effect of CL on time-to-line crossing (TLC) safety margins. Hence, a driving simulator experiment was performed, requiring performance an auditory-response working memory task (CL task), during driving, presented at of three difficulty levels. Similar to previous studies, CL led to increased micro-steering activity, as well as a diminished SDLP, implying a better lane keeping performance. However, a systematic comparison of TLC calculations showed that the TLC values consistently decreased with the CL task, suggesting a degraded safety margin of lane keeping. While these decreased TLCs did not bring the vehicle close to actual lane departure, they do put into question the general finding that lane keeping is improved by cognitive distraction. We discuss how the increased micro-steering activity could lead to the somewhat counterintuitive simultaneous decrease in both SDLP and TLC. In addition, we suggest the use of a new method for TLC calculations, assuming constant lateral acceleration. We argue that by involving short time windows (3–5 s) of chunking, this method may be useful for assessing drivers’ safety behavior, and correct detection of unsafe cognitive distraction.

Background The relative importance of individual and country-level factors influencing access to diagnosis and treatment for depression across the world is fairly unknown. Methods We analysed cross-national data from the WHO World Health Surveys. Depression diagnosis and access to health care were ascertained using a structured interview. Logistic Bayesian Multilevel analyses were performed to establish individual and country level factors associated with: (1) receiving a diagnosis and (2) accessing treatment for depression if a diagnosis was ascertained. Results The sample included 7,870 individuals from 49 countries who met ICD-10 criteria for depressive episode in the past 12 months. A third (32%) of these individuals had ever been diagnosed with depression in their lifetime. Among those diagnosed with depression, 66% reported to have ever received treatment for depression. Although individual factors were more important determinants of access to treatment for depression, country-level factors explained 27.6% of the variance in access to diagnosis and 24.1% in access to treatment. Access to treatment for depression improved with increasing country income. Female gender, better education, the presence of physical co-morbidity, more material assets, and living in urban areas were individual level determinants of better access. Limitations Data on other contextual factors was not available. Unmet need was likely underestimated, since only lifetime treatment data was available. Conclusion This study highlights major inequalities in access to a diagnosis and treatment of depression. Unlike the prevalence of depression, where contextual factors have shown to have less importance, a significant proportion of the variance in access to depression care was explained by country-level income.

The General Data Protection Regulation (GDPR) will come into force in the European Union (EU) in May 2018 to meet current challenges related to personal data protection and to harmonise data protection across the EU. Although the GDPR is anticipated to benefit companies by offering consistency in data protection activities and liabilities across the EU countries and by enabling more integrated EU-wide data protection policies, it poses new challenges to companies. They are not necessarily prepared for the changes and may lack awareness of the upcoming requirements and the GDPR's coercive measures. The implementation of the GDPR requirements demands substantial financial and human resources, as well as training of employees; hence, companies need guidance to support them in this transition. The purposes of this study were to compare the current Data Protection Directive 95/46/EC with the GDPR by systematically analysing their differences and to identify the GDPR's practical implications, specifically for companies that provide services based on personal data. This study aimed to identify and discuss the changes introduced by the GDPR that would have the most practical relevance to these companies and possibly affect their data management and usage practices. Therefore, a review and a thematic analysis and synthesis of the article-level changes were carried out. Through the analysis, the key practical implications of the changes were identified and classified. As a synthesis of the results, a framework was developed, presenting 12 aspects of these implications and the corresponding guidance on how to prepare for the new requirements. These aspects cover business strategies and practices, as well as organisational and technical measures.

Supercritical carbon dioxide (scCO2) treatment was employed for rapid formation of a zinc patina layer on hot dip galvanized (HDG) steel. In the presence of H2O and a Cu precursor, an artificial patina consisting of two distinctive phases was formed: a dense ~ 1 μm layer of anhydrous ZnCO3 adjacent to native zinc coating, and a needle-like porous structure showing resemblance to hydrozincite (Zn5(CO3)2(OH)6). The artificial patina layer significantly decreased the surface free energy of HDG, which was evidenced also by good wettability by a polyester melamine coating. Furthermore, the needle-like patina surface structure stayed intact through the coating process, indicating improved coating adhesion. ScCO2 treatment facilitates rapid and impurity-free surface treatment of hot dip galvanized steel, and could be used to tailor novel adhesion and corrosion promoting surface morphologies.

This driving simulator study, conducted as part of the EU AdaptIVe project, investigated drivers’ performance in critical traffic events, during the resumption of control from an automated driving system. Prior to the critical events, using a between-participant design, 75 drivers were exposed to various screen manipulations that varied the amount of available visual information from the road environment and automation state, which aimed to take them progressively further ‘out-of-the-loop’ (OoTL). The current paper presents an analysis of the timing, type, and rate of drivers’ collision avoidance response, also investigating how these were influenced by the criticality of the unfolding situation. Results showed that the amount of visual information available to drivers during automation impacted on how quickly they resumed manual control, with less information associated with slower take-over times, however, this did not influence the timing of when drivers began a collision avoidance manoeuvre. Instead, the observed behaviour is in line with recent accounts emphasising the role of scenario kinematics in the timing of driver avoidance response. When considering collision incidents in particular, avoidance manoeuvres were initiated when the situation criticality exceeded an Inverse Time To Collision value of ≈0.3 s −1 . Our results suggest that take-over time and timing and quality of avoidance response appear to be largely independent, and while long take-over time did not predict collision outcome, kinematically late initiation of avoidance did. Hence, system design should focus on achieving kinematically early avoidance initiation, rather than short take-over times.

We investigated if alexithymia, a personality construct with difficulties in emotional processing, is stable in the general population.Altogether 3083 unselected subjects aged 30 and older in Finland completed the 20-item Toronto Alexithymia Scale (TAS-20) in the longitudinal Health 2000 and Health 2011 general population surveys (BRIF8901). The stability of alexithymia at the 11-year follow-up was assessed with t-tests, correlations, and separate linear regression models with base-line and follow-up age, gender, marital status, education, and 12-month depressive and anxiety disorders as confounders.The mean score (SD) of the TAS-20 for the whole sample was 44.2 (10.4) in 2000 and 44.2 (10.9) in 2011 (p=0.731). The mean score of the TAS-20 subscale Difficulty Identifying Feelings increased by 0.3 points, Difficulty Describing Feelings decreased by 0.6 points and Externally Oriented Thinking increased by 0.3 points. The effect sizes of the changes varied from negligible to small. Age had little effect except for the group of the oldest subjects (75-97years): the TAS-20 mean (SD) score was 49.1 (10.1) in 2000 and 53.1 (10.3) in 2011 (p0.001), the effect size for the increase was medium. TAS-20 score in 2000 explained a significant proportion of variance in TAS-20 score in 2011. Controlling for all baseline confounders improved the model incrementally; the same applied to controlling for confounders at follow-up. Baseline depression or anxiety disorders were not associated with the TAS-20 scores in 2011, whereas current diagnoses were.According to our large longitudinal study both the absolute and relative stability of alexithymia assessed with the TAS-20 are high in the adult general population.

Hot dip galvanized zinc coatings (containing about 0.2% of aluminum) were studied with surface analytical techniques. A few nanometer thick aluminum oxide (Al2O3) layer dominated the very outermost surface of such zinc coatings. The inert Al2O3 layer formed a continuous impermeable barrier on zinc, providing short term humidity resistance. However, this barrier effect was largely lost during temper rolling. Residues of Al2O3 were shown to prevent titanium hexafluoride pretreatment chemical from reacting with the zinc surface. Segregated aluminum/iron (Al/Fe) intermetallic compounds were also detected at the surface of the zinc coating. The Al/Fe compounds populated the surface immediately beneath the Al2O3 layer. The Al/Fe precipitates were found predominantly in the dendritic valleys. Repulsion between the Al/Fe precipitates and the pretreatment chemical was observed.

Driver braking behavior was analyzed using time-series recordings from naturalistic rear-end conflicts (116 crashes and 241 near-crashes), including events with and without visual distraction among drivers of cars, heavy trucks, and buses. A simple piecewise linear model could be successfully fitted, per event, to the observed driver decelerations, allowing a detailed elucidation of when drivers initiated braking and how they controlled it. Most notably, it was found that, across vehicle types, driver braking behavior was strongly dependent on the urgency of the given rear-end scenario's kinematics, quantified in terms of visual looming of the lead vehicle on the driver's retina. In contrast with previous suggestions of brake reaction times (BRTs) of 1.5 s or more after onset of an unexpected hazard (e.g., brake light onset), it was found here that braking could be described as typically starting less than a second after the kinematic urgency reached certain threshold levels, with even faster reactions at higher urgencies. The rate at which drivers then increased their deceleration (towards a maximum) was also highly dependent on urgency. Probability distributions are provided that quantitatively capture these various patterns of kinematics-dependent behavioral response. Possible underlying mechanisms are suggested, including looming response thresholds and neural evidence accumulation. These accounts argue that a naturalistic braking response should not be thought of as a slow reaction to some single, researcher-defined "hazard onset", but instead as a relatively fast response to the visual looming cues that build up later on in the evolving traffic scenario.

Experimental data revealed that drivers performing a visual secondary task exhibited deteriorated lane keeping performance, but that the same drivers performing a cognitive secondary exhibited an improvement in lane keeping compared to baseline driving. In this paper we present a computational cybernetic driver model that characterizes the effect of difference in eye fixation durations between on and off road glances across the three task conditions on straight lane keeping performance. The model uses perceptual cues as control input, maintains internal representations of these cues across fixations through Bayesian updating, and each time a change in cue magnitude is perceived based on mechanisms akin to signal detection theory a change in control is applied. The model is shown to be able to capture the experimental results encouragingly well. The model also sheds light on the relative magnitude of lane keeping performance degradation caused by glancing away from the road and the fact that internal representations are degraded each time a saccade takes place. The adopted approach to modeling driver perception during and across fixations is expected to lead to new insights into the effects that various in-vehicle activities have on driving performance and risk.

Most daily driving tasks are of low bandwidth and therefore the relatively slow visual system provides enough cue information to perform the task in a manner that is statistically indistinguishable from reality. On the other hand, evasive maneuvers are of such a high bandwidth that waiting for the visual cues to change is too slow and skilled drivers use steering torques and vestibular motion cues to know how the car is responding in order to make rapid corrective actions. In this study we show for evasive maneuvers on snow and ice, for which we have real world data from skilled test drivers, that the choice of motion cuing algorithm (MCA) settings has a tremendous impact on the saliency of motion cues and their similarity with reality. We demonstrate this by introducing a novel optimization scheme to optimize the classic MCA in the context of an MCA-Simulator-Driver triplet of constraints. We incorporate the following four elements to tune the MCA for a particular maneuver: 1) acceleration profiles of the maneuver observed in reality, 2) vestibular motion perception model, 3) motion envelope constraints of the simulator, and 4) a set of heuristics extracted from the literature about human motion perception (i.e. coherence zones). Including these elements in the tuning process, notwithstanding the easiness of the tuning process, respects motion platform constraints and considers human perception. Moreover the inevitable phase and gain errors arising as a major consequence of MCA are always kept within the human coherence zones, and subsequently are not perceptible as false cues. It is expected that this approach to MCA tuning will increase the transfer of training from simulator to reality for evasive driving maneuvers where students need training most and are most dangerous to perform in reality.