Results 61 to 70 of about 10,135,005 (257)
FEBS Open Bio, EarlyView.The dFoCC pipeline starts with observed DED and resting‐state coordinates, which are then used to generate a library of triggered states. Correlation analysis of the calculated DED features of each candidate vs observed DED permits quantitative evaluation of candidate structural quality.
Meng Iao Fong +3 more
wiley +1 more source
Glance behaviours when using an in-vehicle smart driving aid : a real-world, on-road driving study [PDF]
, 2014 In-vehicle information systems (IVIS) are commonplace in modern vehicles, from the initial satellite navigation and in-car infotainment systems, to the more recent driving related Smartphone applications.
Fowkes, Mark, Birrell, Stewart A.
core +1 more source
Affective Use Cases for Empathic Vehicles in Highly Automated Driving: Results of an Expert Workshop
, 2022 S.89-100Improving user experience of highly automated vehicles is crucial for increasing their acceptance. One possibility to realize this is the design of empathic vehicles that are capable of assessing the emotional state of vehicle occupants and react
Ihme, Klas +4 more
core +1 more source
RoundMi: A quantitative method to analyze mitochondrial morphology in mitotic cells
FEBS Open Bio, EarlyView.RoundMi is a workflow for rapid analysis of mitochondrial morphology in mitotic cells. By combining adaptive preprocessing with automated segmentation and quantification, it enables accurate measurements from single focal plane images, reducing acquisition time and computational demands while remaining compatible with high‐throughput fixed and live ...
Elmira Parvindokht Bararpour +2 more
wiley +1 more source
Path Tracking for Automated Driving: A Tutorial on Control System Formulations and Ongoing Research
, 2017 In automated driving system architectures (see the classification according to [1]), three layers can be typically defined [2]: (i) The perception layer, aimed at detecting the conditions of the environment surrounding the vehicle, e.g., by identifying ...
Sorniotti, A, De Pinto, S, Barber, P
core +1 more source
Directed evolution of enzymes at the crossroads of tradition and innovation
FEBS Open Bio, EarlyView.An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova +2 more
wiley +1 more source
Risk Management Core—Toward an Explicit Representation of Risk in Automated Driving
IEEE AccessWhile current automotive safety standards provide implicit guidance on how unreasonable risk can be avoided, manufacturers are required to specify risk acceptance criteria for Automated Driving Systems (SAE Level 3 and higher).
Nayel Fabian Salem +6 more
doaj +1 more source
FEBS Open Bio, EarlyView.Hyperosmotic stress triggers the relocation of the CFIm complex from the nucleus to the cytoplasm. This shift creates a nuclear ‘stoichiometric bottleneck’, limiting CFIm availability for mRNA processing. Consequently, specific mRNAs like NUDT21 and DICER1 undergo targeted 3′UTR shortening, demonstrating how spatial protein dynamics drive rapid ...
Hitomi Soumiya +2 more
wiley +1 more source
IEEE Access, 2020 Engaging in non-driving related tasks (NDRTs) while driving can be considered distracting and safety detrimental. However, with the introduction of highly automated driving systems that relieve drivers from driving, more NDRTs will be feasible.
Maria Klingegard +4 more
doaj +1 more source
Testing of automated driving systems
, 2022 The automated driving requires new testing approaches, which are more complex than the current testing systems. The complexity and requirements for accuracy is important, because of interconnection of virtual with physical testing.
Matawa, Robert +3 more
core +1 more source