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Journal articles on the topic 'Time of Adaptation'

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Published: 28 June 2021
Last updated: 9 February 2022

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1

Pezzotta, Elisa. "The Magic of Time inLolita: The Time Traveller Humbert Humbert." Adaptation 8, no. 3 (April 29, 2015): 297–320. http://dx.doi.org/10.1093/adaptation/apv010.

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2

Ní Fhlainn, Sorcha. "‘There’s Something Very Familiar About All This’: Time Machines, Cultural Tangents, and Mastering Time in H.G. Wells’sThe Time Machineand theBack to the Futuretrilogy." Adaptation 9, no. 2 (November 18, 2015): 164–84. http://dx.doi.org/10.1093/adaptation/apv028.

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3

Chen, Stephanie, and Christof Büskens. "Real-time model adaptation." PAMM 17, no. 1 (December 2017): 837–38. http://dx.doi.org/10.1002/pamm.201710386.

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4

Pedersen, Anita L., Keith A. Crnic, Bruce L. Baker, and Jan Blacher. "Reconceptualizing Family Adaptation to Developmental Delay." American Journal on Intellectual and Developmental Disabilities 120, no. 4 (July 1, 2015): 346–70. http://dx.doi.org/10.1352/1944-7558-120.4.346.

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Abstract This study explores accurate conceptualization of the adaptation construct in families of children with developmental delay aged 3 to 8 years. Parents’ self-reported measures of adaptation and observed dyadic relationship variables were examined. Confirmatory factor analysis and longitudinal growth modeling were used to evaluate the nature of adaptational processes. Results indicate that adaptational processes vary across adaptation index, child developmental level, and parent gender. Adaptation indices did not load onto a single construct at any time point. Several adaptational processes remained stable across time, although others showed linear or quadratic change. The findings of the current study indicate that it is time for a change in how adaptation is conceived for families of children with developmental delay.
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5

Arpaci-Dusseau, Remzi H. "Run-time adaptation in river." ACM Transactions on Computer Systems 21, no. 1 (February 2003): 36–86. http://dx.doi.org/10.1145/592637.592639.

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6

Robinson, Linda A. "Crinolines and Pantalettes: What MGM’s Switch in Time Did to Pride and Prejudice (1940)." Adaptation 6, no. 3 (April 18, 2013): 283–304. http://dx.doi.org/10.1093/adaptation/apt003.

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7

Boothroyd, R. G. "Non-relativistic time, existence and adaptation." International Journal of Design & Nature and Ecodynamics 10, no. 3 (September 30, 2015): 199–212. http://dx.doi.org/10.2495/dne-v10-n3-199-212.

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8

TAYAMA, Tadayuki, Yuya MAEKAWA, and Quingyao SHAO. "Time Perception under Temporal-Frequency Adaptation." Proceedings of the Annual Convention of the Japanese Psychological Association 76 (September 11, 2012): 1AMA19. http://dx.doi.org/10.4992/pacjpa.76.0_1ama19.

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9

Shevell, Steven K. "The time course of chromatic adaptation." Color Research & Application 26, S1 (2000): S170—S173. http://dx.doi.org/10.1002/1520-6378(2001)26:1+<::aid-col37>3.0.co;2-5.

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10

Chachuat, B., B. Srinivasan, and D. Bonvin. "Adaptation strategies for real-time optimization." Computers & Chemical Engineering 33, no. 10 (October 2009): 1557–67. http://dx.doi.org/10.1016/j.compchemeng.2009.04.014.

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11

Buehner, M. J., S. K. Rushton, and J. Kennedy. "Adaptation to space and to time." Journal of Vision 9, no. 8 (March 23, 2010): 4. http://dx.doi.org/10.1167/9.8.4.

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12

Bihari, Thomas E., and Karsten Schwan. "Dynamic adaptation of real-time software." ACM Transactions on Computer Systems 9, no. 2 (May 1991): 143–74. http://dx.doi.org/10.1145/103720.103723.

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13

Federico, Marcello, and Nicola Bertoldi. "Broadcast news LM adaptation over time." Computer Speech & Language 18, no. 4 (October 2004): 417–35. http://dx.doi.org/10.1016/j.csl.2003.10.001.

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14

Bogdan, Grzegorz, Konrad Godziszewski, and Yevhen Yashchyshyn. "Time-Modulated Antenna Array for Real-Time Adaptation in Wideband Wireless Systems—Part II: Adaptation Study." IEEE Transactions on Antennas and Propagation 68, no. 10 (October 2020): 6973–81. http://dx.doi.org/10.1109/tap.2020.3008633.

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15

Granda, A. M., J. R. Dearworth, C. A. Kittila, and W. D. Boyd. "The pupillary response to light in the turtle." Visual Neuroscience 12, no. 6 (November 1995): 1127–33. http://dx.doi.org/10.1017/s0952523800006763.

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AbstractWhen intense adapting lights are turned off, the pupil of the turtle, Pseudemys scripta elegans, enlarges. The recovery functions for pupillary dilation have different time constants that are defined by red- and green-sensitive cones and rods as they are affected by prior light adaptation and time in the dark. Pupillary area related to dilation responds over at least a three- to four-fold range. Following white-light adaptation, the course of pupil dilation in the dark shows a three-legged curve of differing time constants. With spectral-light adaptations, the contributions of separate classes of photoreceptors can be isolated. Red- and green-sensitive cones contribute shorter time constants of 3.31 and 3.65 min to prior white-light adaptation—4.81 and 4.18 min to prior spectral-light adaptations. Rods contribute a much longer time constant of 6.69 min to prior white-light adaptation—7.60 min to prior spectral-light adaptation. The ratios are in keeping with the flash sensitivities of photoreceptors in this same animal, as well as with psychophysical visual threshold mechanisms of color sensitivity.
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16

Spieringhs, Rik M., Michael J. Murdoch, and Ingrid M. L. C. Vogels. "Time course of chromatic adaptation under dynamic lighting." Color and Imaging Conference 2019, no. 1 (October 21, 2019): 13–18. http://dx.doi.org/10.2352/issn.2169-2629.2019.27.4.

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Chromatic adaptation is an extensively studied concept. However, less is known about the time course of chromatic adaptation under gradually-changing lighting. Two experiments were carried out to quantify the time course of chromatic adaptation under dynamic lighting. In the first experiment, a step change in lighting chromaticity was used. The time course of adaptation was well described by the Rinner and Gegenfurtner slow adaptation exponential model [Vision Research, 40(14), 2000], and the adaptation state after saturation differed between observers. In the second experiment, chromatic adaptation was measured in response to two different speeds of lighting chromaticity transitions. An adjusted exponential model was able to fit the observed time course of adaptation for both lighting transition speeds.
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17

Obermaisser, Roman, Hamidreza Ahmadian, Adele Maleki, Yosab Bebawy, Alina Lenz, and Babak Sorkhpour. "Adaptive Time-Triggered Multi-Core Architecture." Designs 3, no. 1 (January 22, 2019): 7. http://dx.doi.org/10.3390/designs3010007.

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The static resource allocation in time-triggered systems offers significant benefits for the safety arguments of dependable systems. However, adaptation is a key factor for energy efficiency and fault recovery in Cyber-Physical System (CPS). This paper introduces the Adaptive Time-Triggered Multi-Core Architecture (ATMA), which supports adaptation using multi-schedule graphs while preserving the key properties of time-triggered systems including implicit synchronization, temporal predictability and avoidance of resource conflicts. ATMA is an overall architecture for safety-critical CPS based on a network-on-a-chip with building blocks for context agreement and adaptation. Context information is established in a globally consistent manner, providing the foundation for the temporally aligned switching of schedules in the network interfaces. A meta-scheduling algorithm computes schedule graphs and avoids state explosion with reconvergence horizons for events. For each tile, the relevant part of the schedule graph is efficiently stored using difference encodings and interpreted by the adaptation logic. The architecture was evaluated using an FPGA-based implementation and example scenarios employing adaptation for improved energy efficiency. The evaluation demonstrated the benefits of adaptation while showing the overhead and the trade-off between the degree of adaptation and the memory consumption for multi-schedule graphs.
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18

Rufus, Freeman, George Vachtsevanos, and Bonnie Heck. "Real-Time Adaptation of Mode Transition Controllers." Journal of Guidance, Control, and Dynamics 25, no. 1 (January 2002): 167–75. http://dx.doi.org/10.2514/2.4863.

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19

Sebastián-Gallés, Núria, Emmanuel Dupoux, Albert Costa, and Jacques Mehler. "Adaptation to time-compressed speech: Phonological determinants." Perception & Psychophysics 62, no. 4 (January 2000): 834–42. http://dx.doi.org/10.3758/bf03206926.

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20

Pham, Hubert, Justin Mazzola Paluska, Umar Saif, Chris Stawarz, Chris Terman, and Steve Ward. "A dynamic platform for run-time adaptation." Pervasive and Mobile Computing 5, no. 6 (December 2009): 676–96. http://dx.doi.org/10.1016/j.pmcj.2009.07.003.

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21

Marchetti, A., B. Chachuat, and D. Bonvin. "Modifier-Adaptation Methodology for Real-Time Optimization." Industrial & Engineering Chemistry Research 48, no. 13 (July 2009): 6022–33. http://dx.doi.org/10.1021/ie801352x.

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22

Jamieson, Donald G., and Margaret F. Cheesman. "The adaptation of produced voice-onset time." Journal of Phonetics 15, no. 1 (January 1987): 15–27. http://dx.doi.org/10.1016/s0095-4470(19)30534-0.

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23

Chatterjee, N., and J. A. Campbell. "Interpolation of plans for time-critical adaptation." Knowledge-Based Systems 12, no. 4 (August 1999): 171–82. http://dx.doi.org/10.1016/s0950-7051(99)00029-5.

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24

Lee, B. B., D. M. Dacey, V. C. Smith, and J. Pokorny. "The time course of outer retinal adaptation." Journal of Vision 4, no. 11 (November 1, 2004): 34. http://dx.doi.org/10.1167/4.11.34.

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25

Joosten, Eef, and Therese Collins. "The human saccadic adaptation field across time." Journal of Vision 18, no. 10 (September 1, 2018): 1012. http://dx.doi.org/10.1167/18.10.1012.

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26

Miller, Robert M. "The horse's response time —A physiological adaptation." Journal of Equine Veterinary Science 15, no. 6 (June 1995): 264–65. http://dx.doi.org/10.1016/s0737-0806(07)80492-8.

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27

Ortega, L., E. Guzman-Martinez, M. Grabowecky, and S. Suzuki. "Orientation-specific flicker adaptation dilates static time." Journal of Vision 10, no. 7 (August 17, 2010): 1415. http://dx.doi.org/10.1167/10.7.1415.

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28

Çelik, Eyüp, Ümit Sahranç, Mehmet Kaya, and Mehmet Emin Turan. "Adolescent Time Attitude Scale: Adaptation into Turkish." Universal Journal of Educational Research 5, no. 2 (December 2017): 249–54. http://dx.doi.org/10.13189/ujer.2017.050210.

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29

McGregor, Simon, and Pedro A. M. Mediano. "Adaptation Is Not Just Improvement over Time." Artificial Life 24, no. 3 (November 2018): 182–98. http://dx.doi.org/10.1162/artl_a_00268.

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The idea that an agent's actions can impact its actual long-term survival is a very appealing one, underlying influential treatments such as Di Paolo's (2005). However, this presents a tension with understanding the agent and environment as possessing specific objective physical microstates. More specifically, we show that such an approach leads to undesirable outcomes, for example, all organisms being maladaptive on average. We suggest that this problematic intuition of improvement over time may stem from Bayesian inference. We illustrate our arguments using a recent model of autopoietic agency in a model protocell, showing the limitations of previous approaches in this model and specific instantiations of Bayesian inference by ignorant observers in certain scenarios.
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30

Baum, Seth D., and William E. Easterling. "Space-time discounting in climate change adaptation." Mitigation and Adaptation Strategies for Global Change 15, no. 6 (June 16, 2010): 591–609. http://dx.doi.org/10.1007/s11027-010-9239-9.

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31

Modabber, M., J. Neva, M. Gill, I. Budge, and D. Henriques. "Learning and retaining visuomotor adaptation across time." Journal of Vision 8, no. 6 (March 27, 2010): 610. http://dx.doi.org/10.1167/8.6.610.

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32

Polechová, Jitka, Nick Barton, and Glenn Marion. "Species' Range: Adaptation in Space and Time." American Naturalist 174, no. 5 (November 2009): E186—E204. http://dx.doi.org/10.1086/605958.

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33

Wolpert, D. M., R. C. Miall, B. Cumming, and S. J. Boniface. "Retinal adaptation of visual processing time delays." Vision Research 33, no. 10 (July 1993): 1421–30. http://dx.doi.org/10.1016/0042-6989(93)90048-2.

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34

Rogers, Steve. "Linear time-varying systems: Control and adaptation." Control Engineering Practice 3, no. 3 (March 1995): 440–41. http://dx.doi.org/10.1016/0967-0661(95)90074-8.

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35

Frassinetti, Francesca, Barbara Magnani, and Massimiliano Oliveri. "Prismatic Lenses Shift Time Perception." Psychological Science 20, no. 8 (August 2009): 949–54. http://dx.doi.org/10.1111/j.1467-9280.2009.02390.x.

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Previous studies have demonstrated the involvement of spatial codes in the representation of time and numbers. We took advantage of a well-known spatial modulation (prismatic adaptation) to test the hypothesis that the representation of time is spatially oriented from left to right, with smaller time intervals being represented to the left of larger time intervals. Healthy subjects performed a time-reproduction task and a time-bisection task, before and after leftward and rightward prismatic adaptation. Results showed that prismatic adaptation inducing a rightward orientation of spatial attention produced an overestimation of time intervals, whereas prismatic adaptation inducing a leftward shift of spatial attention produced an underestimation of time intervals. These findings not only confirm that temporal intervals are represented as horizontally arranged in space, but also reveal that spatial modulation of time processing most likely occurs via cuing of spatial attention, and that spatial attention can influence the spatial coding of quantity in different dimensions.
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36

Han, Ruofan Connie, Joanna Monika Gray, Jennie Han, Robert E. Maclaren, and Jasleen Kaur Jolly. "Optimisation of dark adaptation time required for mesopic microperimetry." British Journal of Ophthalmology 103, no. 8 (September 29, 2018): 1092–98. http://dx.doi.org/10.1136/bjophthalmol-2018-312253.

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BackgroundMacular Integrity Assessment (MAIA) microperimetry is increasingly used in clinical and research settings to assess point retinal sensitivity and fixation stability. Testing occurs under mesopic conditions, commonly after a period of dark adaptation. Our aim was to identify the minimum length of adaptation required to optimise microperimetry performance.MethodsMAIA microperimetry using the 10-2 grid was performed on 40 right eyes of 40 healthy participants aged 18–73 with no ocular pathology and vision of at least 0.1 logMAR after ambient light exposure, with 0, 5, 10, 15, 20 and 30 min of adaptation in mesopic settings. Ten right eyes of 10 participants with choroideremia were also tested following 0 and 20 min of adaptation. We further tested 10 right eyes of 10 healthy participants after bright light exposure, with 0, 10 and 20 min of adaptation. We compared changes in threshold sensitivity and fixation stability across time points.ResultsMicroperimetry performance did not improve with increasing adaptation time in healthy participants or patients with choroideremia after ambient light exposure. After bright light exposure, we found microperimetry thresholds improved after 10 min of adaptation, but did not improve further at 20 min.ConclusionMesopic adaptation is not required before MAIA microperimetry after exposure to ambient light. Ten minutes of adaptation is sufficient after exposure to a bright light stimulus, such as ophthalmoscopy or retinal imaging. The brief time of dark adaptation required corresponds to cone adaptation curves and provides further evidence for cone-mediated central retinal function under mesopic conditions.
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37

PARRY, N. R. A., I. J. MURRAY, and D. J. McKEEFRY. "Reaction time measures of adaptation to chromatic contrast." Visual Neuroscience 25, no. 3 (May 2008): 405–10. http://dx.doi.org/10.1017/s0952523808080449.

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Simple reaction times (RTs) were measured to brief temporally blurred (total onset 570 ms) Gaussian isoluminant chromatic patches (s.d. 0.5°) whose chromaticities lay along the cardinal chromatic axes (0°, 90°, 180°, and 270° in MBDKL color space). Bipolar adapting stimuli were employed (0° versus 180° or 90° versus 270°). These were larger Gaussian blobs (s.d. 1°), modulating sinusoidally between the two hues at 1 Hz. Throughout, the background was illuminant “C” (x = 0.31, y = 0.316, L = 12.5). In a single run, a series of 64 or 32 stimuli were presented without adaptation, followed by 64 or 32 stimuli each of which was preceded by 3 s of adaptation, either along the same or the orthogonal chromatic axis. Finally, 192 or 128 RTs were recorded to measure the time course of recovery from adaptation. Both adapting and test stimuli were presented at fixed supra-threshold contrasts. The effect of adaptation was seen as a lengthening of the RT, which occurred in the first few seconds of the adaptation period. After cessation of adaptation, there was a similarly rapid shortening of RT, although full recovery took 60–90 s. Adaptation gain functions suggested that the S-(L + M) system was less prone to adaptation than L-M.
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38

HENDRY, ANDREW P., and TROY DAY. "Population structure attributable to reproductive time: isolation by time and adaptation by time." Molecular Ecology 14, no. 4 (March 16, 2005): 901–16. http://dx.doi.org/10.1111/j.1365-294x.2005.02480.x.

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39

Liu, Changjiang, and Qiuping Wang. "Simulating Human Visual Perception in Tunnel Portals." Sustainability 13, no. 7 (March 27, 2021): 3741. http://dx.doi.org/10.3390/su13073741.

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To study the characteristics of light and dark adaptation in tunnel portals, and to determine the influencing factors in light–dark vision adaptation, basic tunnel lighting and linear design data were obtained. In this study, we used a light-shielded tent to simulate the dark environment of a tunnel, observe the driver recognition time for target objects during the light–dark adaptation process, and analyze the light–dark adaptation time of human vision. Based on the experimental data, we examined the relationships between age, gender, illuminance, and light and dark adaptation times, and established a model for these relationships. The experimental results show that the dark adaptation time is generally longer than the light adaptation time. The dark adaptation time is positively related to age and exhibits a cubic relationship. There is no significant correlation between the light adaptation time and age, but the overall trend is for the light adaptation time to gradually increase with increasing age. There is no correlation between gender and light and dark adaptation times, but there is a notable correlation between light and dark adaptation times and illuminance. When the illuminance ranges from 11,000 to 13,000 lux, the light and dark adaptation times are the longest.
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40

Wen, Bo, Grace I. Wang, Isabel Dean, and Bertrand Delgutte. "Time course of dynamic range adaptation in the auditory nerve." Journal of Neurophysiology 108, no. 1 (July 1, 2012): 69–82. http://dx.doi.org/10.1152/jn.00055.2012.

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Auditory adaptation to sound-level statistics occurs as early as in the auditory nerve (AN), the first stage of neural auditory processing. In addition to firing rate adaptation characterized by a rate decrement dependent on previous spike activity, AN fibers show dynamic range adaptation, which is characterized by a shift of the rate-level function or dynamic range toward the most frequently occurring levels in a dynamic stimulus, thereby improving the precision of coding of the most common sound levels (Wen B, Wang GI, Dean I, Delgutte B. J Neurosci 29: 13797–13808, 2009). We investigated the time course of dynamic range adaptation by recording from AN fibers with a stimulus in which the sound levels periodically switch from one nonuniform level distribution to another (Dean I, Robinson BL, Harper NS, McAlpine D. J Neurosci 28: 6430–6438, 2008). Dynamic range adaptation occurred rapidly, but its exact time course was difficult to determine directly from the data because of the concomitant firing rate adaptation. To characterize the time course of dynamic range adaptation without the confound of firing rate adaptation, we developed a phenomenological “dual adaptation” model that accounts for both forms of AN adaptation. When fitted to the data, the model predicts that dynamic range adaptation occurs as rapidly as firing rate adaptation, over 100–400 ms, and the time constants of the two forms of adaptation are correlated. These findings suggest that adaptive processing in the auditory periphery in response to changes in mean sound level occurs rapidly enough to have significant impact on the coding of natural sounds.
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41

Antoniou, Zinonas C., Andreas S. Panayides, Marios Pantzaris, Anthony G. Constantinides, Constantinos S. Pattichis, and Marios S. Pattichis. "Real-Time Adaptation to Time-Varying Constraints for Medical Video Communications." IEEE Journal of Biomedical and Health Informatics 22, no. 4 (July 2018): 1177–88. http://dx.doi.org/10.1109/jbhi.2017.2726180.

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42

Blanquart, François, and Sylvain Gandon. "Time-shift experiments and patterns of adaptation across time and space." Ecology Letters 16, no. 1 (October 4, 2012): 31–38. http://dx.doi.org/10.1111/ele.12007.

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43

Yeo, Chang-Yeon, Mun-Hwan Choi, Byoung-Jin Kim, and Sung-Hyun Choi. "Coherence Time Estimation for Performance Improvement of IEEE 802.11n Link Adaptation." Journal of Korean Institute of Communications and Information Sciences 36, no. 3A (March 31, 2011): 232–39. http://dx.doi.org/10.7840/kics.2011.36a.3.232.

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44

Leung, Y. Y., S. J. Bensmaïa, S. S. Hsiao, and K. O. Johnson. "Time-Course of Vibratory Adaptation and Recovery in Cutaneous Mechanoreceptive Afferents." Journal of Neurophysiology 94, no. 5 (November 2005): 3037–45. http://dx.doi.org/10.1152/jn.00001.2005.

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Extended suprathreshold vibratory stimulation applied to the skin results in a desensitization of cutaneous mechanoreceptive afferents. In a companion paper, we describe the dependence of the threshold shift on the parameters of the adapting stimulus and discuss neural mechanisms underlying afferent adaptation. Here we describe the time-course of afferent adaptation and recovery. We found that absolute and entrainment thresholds rise and fall exponentially during adaptation and recovery with time constants that vary with fiber type. slowly adapting type I (SA1) afferents adapt most rapidly, and pacinian (PC) afferents adapt most slowly, whereas rapidly adapting (RA) afferents exhibit intermediate rates of adaptation; SA1 fibers also recover more rapidly from adaptation than RA and PC fibers. We also showed that threshold adaptation is accompanied by a shift in the timing of the spikes within individual cycles of the adapting stimulus (i.e., a shift in the impulse phase). We invoked an integrate-and-fire model to explore possible mechanisms underlying afferent adaptation. Finally, we found that the time-course of afferent adaptation is more rapid than that of its psychophysical counterpart, as is the time-course of recovery from adaptation, suggesting that central factors play a role in the psychophysical phenomenon.
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45

Kesting, Arne, and Martin Treiber. "How Reaction Time, Update Time, and Adaptation Time Influence the Stability of Traffic Flow." Computer-Aided Civil and Infrastructure Engineering 23, no. 2 (January 7, 2008): 125–37. http://dx.doi.org/10.1111/j.1467-8667.2007.00529.x.

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46

Chimento, Thomas C., and Christoph E. Schreiner. "Time course of adaptation and recovery from adaptation in the cat auditory‐nerve neurophonic." Journal of the Acoustical Society of America 88, no. 2 (August 1990): 857–64. http://dx.doi.org/10.1121/1.399735.

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47

Jane Wilkinson, Sara. "How buildings learn." Facilities 32, no. 7/8 (April 28, 2014): 382–95. http://dx.doi.org/10.1108/f-12-2012-0100.

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Purpose – This paper aims to study the adaptation of low grade commercial buildings for sustainability in Melbourne. Informed adaptation of existing stock is imperative because the challenge of attaining sustainable development in the 21st century will be won or lost in urban areas. Local authorities promote adaptation to reduce building related energy consumption and greenhouse gas emissions. The City of Melbourne aims to retrofit 1,200 central business district (CBD) properties before 2020 as part of their carbon-neutral city strategy. Australian cities date from the early 1800s to the present day and the concepts of adaptation and evolution of buildings and suburbs is not as well-developed or entrenched as in other continents. As such, there is a pressing need for greater knowledge and awareness of what happens to buildings over time. Design/methodology/approach – This research examines all building adaptation from 1998 to 2008 within the Melbourne CBD. This paper concentrates on the question: what is the pattern of adaptation within low grade office buildings over time? Using the Melbourne CBD as a case study, the research analysed all commercial building adaptations in Melbourne. Here a range of office building types are selected and profiled to discover what happened to them during the period and to ascertain what may be learned as a result to inform future adaptation strategies and policies. Findings – Adaptation of existing buildings is vital to deliver the emission reductions required to transition to carbon-neutral urban settlements. In the short-term, it is opportune to capitalise on existing behaviour patterns in respect of adaptation and to “learn how buildings learn”, rather than seek to instigate major changes in behaviour. Research limitations/implications – The researcher acknowledges that the depth of analysis for each individual case does not attain levels achieved through a purely qualitative approach to data collection and that this is a limitation of this method of data collection. Practical implications – Examination of adaptation patterns showed that the events were similar regardless of age or location and typically involved multiple adaptations to separate areas within buildings such as office floors, lobbies and foyers. Such a pattern misses the opportunity to benefit from economies of scale or to incorporate more extensive adaptations to reduce environmental impact of the building as a whole. Social implications – The patterns of ownership and relatively short-term multiple tenancies compound the piecemeal approach to adaptations in this sector of the market. Moving forward, a more holistic approach is required to optimise adaptation and sustainability benefits and to minimise unnecessary waste. Originality/value – A real danger is that numerous adaptations over time which may seem “sustainable” within the context of the one adaptation may not be sustainable in the context of the entire building over the whole lifecycle or the city over the long–term, and this is a challenge we must attend to.
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48

Tayama, Tadayuki, and Yusuke Okumura. "Cross-modal influences of adaptation on time perception." Proceedings of the Annual Convention of the Japanese Psychological Association 82 (September 25, 2018): 1AM—056–1AM—056. http://dx.doi.org/10.4992/pacjpa.82.0_1am-056.

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49

Hollins, Mark, Alan K. Goble, Barry L. Whitsel, and Mark Tommerdahl. "Time Course and Action Spectrum of Vibrotactile Adaptation." Somatosensory & Motor Research 7, no. 2 (January 1990): 205–21. http://dx.doi.org/10.3109/08990229009144707.

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50

Khorasani, Fatemeh, Afshin Salajegheh, and Ali Moeini. "A Model for Run-Time Software Architecture Adaptation." International Journal of Software Engineering & Applications 6, no. 1 (January 31, 2015): 11–23. http://dx.doi.org/10.5121/ijsea.2015.6102.

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