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Journal articles on the topic 'Fixation prediction'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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1

Lu, Quan, Jiyue Zhang, Jing Chen, and Ji Li. "Predicting readers’ domain knowledge based on eye-tracking measures." Electronic Library 36, no. 6 (2018): 1027–42. http://dx.doi.org/10.1108/el-05-2017-0108.

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Purpose This paper aims to examine the effect of domain knowledge on eye-tracking measures and predict readers’ domain knowledge from these measures in a navigational table of contents (N-TOC) system. Design/methodology/approach A controlled experiment of three reading tasks was conducted in an N-TOC system for 24 postgraduates of Wuhan University. Data including fixation duration, fixation count and inter-scanning transitions were collected and calculated. Participants’ domain knowledge was measured by pre-experiment questionnaires. Logistic regression analysis was leveraged to build the pred

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2

Pervez, Humayon, Martyn J. Parker, and Sarah Vowler. "Prediction of fixation failure after sliding hip screw fixation." Injury 35, no. 10 (2004): 994–98. http://dx.doi.org/10.1016/j.injury.2003.10.028.

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Haidar, S. G., and B. Thomas. "Prediction of fixation failure after sliding hip screw fixation." Injury 36, no. 12 (2005): 1491. http://dx.doi.org/10.1016/j.injury.2005.07.043.

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Min, Xiongkuo, Guangtao Zhai, Ke Gu, and Xiaokang Yang. "Fixation Prediction through Multimodal Analysis." ACM Transactions on Multimedia Computing, Communications, and Applications 13, no. 1 (2017): 1–23. http://dx.doi.org/10.1145/2996463.

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Sakai, Rina, Roland Steck, Gongfa Chen, et al. "Prediction of the fixation conditions of murine fracture fixation plates." Journal of the Society of Biomechanisms 35, no. 2 (2011): 130–36. http://dx.doi.org/10.3951/sobim.35.130.

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6

XU, Linfeng, Liaoyuan ZENG, and Zhengning WANG. "Learning a Saliency Map for Fixation Prediction." IEICE Transactions on Information and Systems E96.D, no. 10 (2013): 2294–97. http://dx.doi.org/10.1587/transinf.e96.d.2294.

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Kümmerer, Matthias, Thomas S. A. Wallis, and Matthias Bethge. "Information-theoretic model comparison unifies saliency metrics." Proceedings of the National Academy of Sciences 112, no. 52 (2015): 16054–59. http://dx.doi.org/10.1073/pnas.1510393112.

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Learning the properties of an image associated with human gaze placement is important both for understanding how biological systems explore the environment and for computer vision applications. There is a large literature on quantitative eye movement models that seeks to predict fixations from images (sometimes termed “saliency” prediction). A major problem known to the field is that existing model comparison metrics give inconsistent results, causing confusion. We argue that the primary reason for these inconsistencies is because different metrics and models use different definitions of what

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Kumar, A., and N. Kumar. "Prediction of fixation failure after sliding hip screw fixation [Injury 2004;35:994–8]." Injury 36, no. 8 (2005): 984–85. http://dx.doi.org/10.1016/j.injury.2004.12.042.

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Parker, M. "Prediction of fixation failure after sliding hip screw fixation [Injury 2004;35:994–8]." Injury 36, no. 8 (2005): 985. http://dx.doi.org/10.1016/j.injury.2004.12.043.

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Yanulevskaya, Victoria, Jan Bernard Marsman, Frans Cornelissen, and Jan-Mark Geusebroek. "An Image Statistics–Based Model for Fixation Prediction." Cognitive Computation 3, no. 1 (2010): 94–104. http://dx.doi.org/10.1007/s12559-010-9087-7.

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Rezazadegan Tavakoli, Hamed, Esa Rahtu, and Janne Heikkilä. "Stochastic bottom–up fixation prediction and saccade generation." Image and Vision Computing 31, no. 9 (2013): 686–93. http://dx.doi.org/10.1016/j.imavis.2013.06.006.

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Pan, Chen, Wenlong Xu, Dan Shen, and Yong Yang. "Leukocyte Image Segmentation Using Novel Saliency Detection Based on Positive Feedback of Visual Perception." Journal of Healthcare Engineering 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/5098973.

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This paper presents a novel method for salient object detection in nature image by simulating microsaccades in fixational eye movements. Due to a nucleated cell usually stained that is salient obviously, the proposed method is suitable to segment nucleated cell. Firstly, the existing fixation prediction method is utilized to produce an initial fixation area. Followed EPELM (ensemble of polyharmonic extreme learning machine) is trained on-line by the pixels sampling from the fixation and nonfixation area. Then the model of EPELM could be used to classify image pixels to form new binary fixation

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Anantrasirichai, Nantheera, Katherine A. J. Daniels, Jeremy F. Burn, Iain D. Gilchrist, and David R. Bull. "Fixation Prediction and Visual Priority Maps for Biped Locomotion." IEEE Transactions on Cybernetics 48, no. 8 (2018): 2294–306. http://dx.doi.org/10.1109/tcyb.2017.2734946.

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14

Tang, He, Chuanbo Chen, and Yanan Bie. "Prediction of Human Eye Fixation by a Single Filter." Journal of Signal Processing Systems 87, no. 2 (2016): 197–202. http://dx.doi.org/10.1007/s11265-016-1131-8.

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15

Li, Aoqi, and Zhenzhong Chen. "Semantic meaning modulates object importance in human fixation prediction." Journal of Visual Communication and Image Representation 79 (August 2021): 103206. http://dx.doi.org/10.1016/j.jvcir.2021.103206.

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16

Spering, Miriam, Alexander C. Schütz, Doris I. Braun, and Karl R. Gegenfurtner. "Keep your eyes on the ball: smooth pursuit eye movements enhance prediction of visual motion." Journal of Neurophysiology 105, no. 4 (2011): 1756–67. http://dx.doi.org/10.1152/jn.00344.2010.

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Success of motor behavior often depends on the ability to predict the path of moving objects. Here we asked whether tracking a visual object with smooth pursuit eye movements helps to predict its motion direction. We developed a paradigm, “eye soccer,” in which observers had to either track or fixate a visual target (ball) and judge whether it would have hit or missed a stationary vertical line segment (goal). Ball and goal were presented briefly for 100–500 ms and disappeared from the screen together before the perceptual judgment was prompted. In pursuit conditions, the ball moved towards th

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Mantokoudis, Georgios, Thomas Wyss, Ewa Zamaro, et al. "Stroke Prediction Based on the Spontaneous Nystagmus Suppression Test in Dizzy Patients." Neurology 97, no. 1 (2021): e42-e51. http://dx.doi.org/10.1212/wnl.0000000000012176.

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ObjectiveFailure of fixation suppression of spontaneous nystagmus is sometimes seen in patients with vestibular strokes involving the cerebellum or brainstem; however, the accuracy of this test for the discrimination between peripheral and central causes in patients with an acute vestibular syndrome (AVS) is unknown.MethodsPatients with AVS were screened and recruited (convenience sample) as part of a prospective cross-sectional study in the emergency department between 2015 and 2020. All patients received neuroimaging, which served as a reference standard. We recorded fixation suppression wit

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Liu, Chong, Zide Zhang, Yuan Ma, et al. "Predicting the Failure Risk of Internal Fixation Devices in Chinese Patients Undergoing Spinal Internal Fixation Surgery: Development and Assessment of a New Predictive Nomogram." BioMed Research International 2021 (January 26, 2021): 1–13. http://dx.doi.org/10.1155/2021/8840107.

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The current study is aimed at developing and validating a nomogram of the risk of failure of internal fixation devices in Chinese patients undergoing spinal internal fixation. We collected data from a total of 1139 patients admitted for spinal internal fixation surgery at the First Affiliated Hospital of Guangxi Medical University from May 2012 to February 2019. Of these, 1050 patients were included in the spinal internal fixation group and 89 patients in the spinal internal fixation device failure group. Patients were divided into training and validation tests. The risk assessment of the fail

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Claessen, Femke M. A. P., Nicky Stoop, Job N. Doornberg, et al. "Interpretation of Post-operative Distal Humerus Radiographs After Internal Fixation: Prediction of Later Loss of Fixation." Journal of Hand Surgery 41, no. 10 (2016): e337-e341. http://dx.doi.org/10.1016/j.jhsa.2016.07.094.

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20

Sernbo, Ingemar, Hans Holmquist, Inga Redlund-johnell, and Olof Johnell. "Radiographic prediction of failure after fixation of cervical hip fracture." Acta Orthopaedica Scandinavica 65, no. 3 (1994): 295–98. http://dx.doi.org/10.3109/17453679408995456.

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21

Liu, Di, and Zhenzhong Chen. "Disparity tuning guided stereoscopic saliency detection for eye fixation prediction." Journal of Visual Communication and Image Representation 57 (November 2018): 218–27. http://dx.doi.org/10.1016/j.jvcir.2018.10.002.

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22

Tang, He, Chuanbo Chen, and Xiaobing Pei. "Saliency detection from one time sampling for eye fixation prediction." Multimedia Tools and Applications 77, no. 1 (2016): 165–84. http://dx.doi.org/10.1007/s11042-016-4248-7.

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23

Wang, Jingwei, Ali Borji, C. C. Jay Kuo, and Laurent Itti. "Learning a Combined Model of Visual Saliency for Fixation Prediction." IEEE Transactions on Image Processing 25, no. 4 (2016): 1566–79. http://dx.doi.org/10.1109/tip.2016.2522380.

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24

Chen, Yi-sheng, Yan-xian Cai, Xue-ran Kang, et al. "Predicting the risk of sarcopenia in elderly patients with patellar fracture: development and assessment of a new predictive nomogram." PeerJ 8 (April 15, 2020): e8793. http://dx.doi.org/10.7717/peerj.8793.

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Purpose To develop a risk prediction model for postoperative sarcopenia in elderly patients with patellar fractures in China. Patients and methods We conducted a community survey of patients aged ≥55 years who underwent surgery for patellar fractures between January 2013 and October 2018, through telephone interviews, community visits, and outpatient follow-up. We established a predictive model for assessing the risk of sarcopenia after patellar fractures. We developed the prediction model by combining multivariate logistic regression analysis with the least absolute shrinkage model and select

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25

Diaz, Gabriel, Joseph Cooper, and Mary Hayhoe. "Memory and prediction in natural gaze control." Philosophical Transactions of the Royal Society B: Biological Sciences 368, no. 1628 (2013): 20130064. http://dx.doi.org/10.1098/rstb.2013.0064.

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In addition to stimulus properties and task factors, memory is an important determinant of the allocation of attention and gaze in the natural world. One way that the role of memory is revealed is by predictive eye movements. Both smooth pursuit and saccadic eye movements demonstrate predictive effects based on previous experience. We have previously shown that unskilled subjects make highly accurate predictive saccades to the anticipated location of a ball prior to a bounce in a virtual racquetball setting. In this experiment, we examined this predictive behaviour. We asked whether the period

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Izawa, Yuta, Yoshihiko Tsuchida, Kentaro Futamura, Hironori Ochi, and Tomonori Baba. "Plate coverage predicts failure for volarly unstable distal radius fractures with volar lunate facet fragments." SICOT-J 6 (2020): 29. http://dx.doi.org/10.1051/sicotj/2020026.

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Introduction: Loss of reduction after operative fixation of volarly unstable distal radius fractures with a volar lunate facet fragment (VLF) is considered problematic because it results in carpal subluxation or dislocation and subsequent impaired function. We hypothesized that the indicator of loss of reduction of the VLF after fixation is plate coverage of the bony fragment. We investigated the relationship between the plate coverage of the VLF and loss of reduction after fixation, and calculated the plate coverage that was associated with failure of fixation of the VLF. Materials and method

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27

Merzon, Liya, Tatiana Malevich, Georgiy Zhulikov, Sofia Krasovskaya, and W. Joseph MacInnes. "Temporal Limitations of the Standard Leaky Integrate and Fire Model." Brain Sciences 10, no. 1 (2019): 16. http://dx.doi.org/10.3390/brainsci10010016.

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Itti and Koch’s Saliency Model has been used extensively to simulate fixation selection in a variety of tasks from visual search to simple reaction times. Although the Saliency Model has been tested for its spatial prediction of fixations in visual salience, it has not been well tested for their temporal accuracy. Visual tasks, like search, invariably result in a positively skewed distribution of saccadic reaction times over large numbers of samples, yet we show that the leaky integrate and fire (LIF) neuronal model included in the classic implementation of the model tends to produce a distrib

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28

Zou, Da, Aikeremujiang Muheremu, Zhuoran Sun, Woquan Zhong, Shuai Jiang, and Weishi Li. "Computed tomography Hounsfield unit–based prediction of pedicle screw loosening after surgery for degenerative lumbar spine disease." Journal of Neurosurgery: Spine 32, no. 5 (2020): 716–21. http://dx.doi.org/10.3171/2019.11.spine19868.

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OBJECTIVEThe authors investigated the relation between Hounsfield unit (HU) values measured on CT and the risk of pedicle screw loosening in patients who underwent lumbar pedicle screw fixation for degenerative lumbar spine disease.METHODSPatients who were treated with lumbar pedicle screw fixation between July 2011 and December 2015 at the authors’ department were reviewed. Age, sex, BMI, smoking and diabetes histories, range of fixation, and fusion method were recorded as the basic patient information. The HU values for lumbar bone mineral density (BMD) for the L1, L2, L3, and L4 vertebra we

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Mešić, Elmedin, Adil Muminović, Mirsad Čolić, Marin Petrović, and Nedim Pervan. "Development and Experimental Verification of a Generative CAD/FEM Model of an External Fixation Device." Tehnički glasnik 14, no. 1 (2020): 1–6. http://dx.doi.org/10.31803/tg-20191112161707.

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This paper presents the development and experimental verification of a generative CAD/FEM model of an external bone fixation device. The generative CAD model is based on the development of a parameterized skeleton algorithm and sub-algorithms for parametric modeling and positioning of components within a fixator assembly using the CATIA CAD/CAM/CAE system. After a structural analysis performed in the same system, the FEM model was used to follow interfragmentary fracture displacements, axial displacements at the loading site, as well as principal and Von Mises stresses at the fixator connectin

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Widmer, Jonas, Marie-Rosa Fasser, Eleonora Croci, José Spirig, Jess G. Snedeker, and Mazda Farshad. "Individualized prediction of pedicle screw fixation strength with a finite element model." Computer Methods in Biomechanics and Biomedical Engineering 23, no. 4 (2020): 155–67. http://dx.doi.org/10.1080/10255842.2019.1709173.

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Lv, Ying, Wujie Zhou, Jingsheng Lei, Lv Ye, and Ting Luo. "Attention-based fusion network for human eye-fixation prediction in 3D images." Optics Express 27, no. 23 (2019): 34056. http://dx.doi.org/10.1364/oe.27.034056.

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32

HAGHJOO, MAJID, REZA MOLLAZADEH, AMIR ASLANI, et al. "Prediction of Midterm Performance of Active-Fixation Leads Using Current of Injury." Pacing and Clinical Electrophysiology 37, no. 2 (2013): 231–36. http://dx.doi.org/10.1111/pace.12262.

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33

Yang, Jian, Yang Shen, and Yuhui Shi. "Visual fixation prediction with incomplete attention map based on brain storm optimization." Applied Soft Computing 96 (November 2020): 106653. http://dx.doi.org/10.1016/j.asoc.2020.106653.

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34

Parker, M. J. "Prediction of fracture union after internal fixation of intracapsular femoral neck fractures." Injury 25 (January 1994): SB3—SB6. http://dx.doi.org/10.1016/0020-1383(94)90192-9.

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Parker, M. "Prediction of fracture union after internal fixation of intracapsular femoral neck fractures." Injury 25 (January 1994): SB23. http://dx.doi.org/10.1016/0020-1383(94)90229-1.

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36

yue, Miao, Li Wei, and Li chunle. "Human eye-fixation prediction based on Convolutional Neural Network in RGB images." Journal of Physics: Conference Series 1827, no. 1 (2021): 012020. http://dx.doi.org/10.1088/1742-6596/1827/1/012020.

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37

Luft, Joan L., and Michael D. Shields. "Why Does Fixation Persist? Experimental Evidence on the Judgment Performance Effects of Expensing Intangibles." Accounting Review 76, no. 4 (2001): 561–87. http://dx.doi.org/10.2308/accr.2001.76.4.561.

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This study shows experimentally that when individuals use information on intangibles expenditures to predict future profits, expensing (vs. capitalizing) the expenditures significantly reduces the accuracy, consistency, consensus, and self-insight of individuals' subjective profit predictions. The experimental design allows us to eliminate several competing explanations for this apparent fixation on accounting. Subjects do not base their judgments on a nai¨ve prior belief that expensing precludes effects on future profits; a preexperiment question shows that subjects expect intangibles expendi

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Lu, Sheng, Michael Carl, Xinyue Yao, and Wenchao Su. "Predicting translation behaviorsby using Hidden Markov Model." Translation, Cognition & Behavior 3, no. 1 (2020): 76–99. http://dx.doi.org/10.1075/tcb.00035.lu.

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Abstract The translation process can be studied as sequences of activity units. The application of machine learning technology offers researchers new possibilities in the study of the translation process. This research project developed a program, activity unit predictor, using the Hidden Markov Model. The program takes in duration, translation phase, target language and fixation as the input and produces an activity unit type as the output. The highest prediction accuracy reached is 61%. As one of the first endeavors, the program demonstrates strong potential of applying machine learning in t

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Stojić, Hrvoje, Jacob L. Orquin, Peter Dayan, Raymond J. Dolan, and Maarten Speekenbrink. "Uncertainty in learning, choice, and visual fixation." Proceedings of the National Academy of Sciences 117, no. 6 (2020): 3291–300. http://dx.doi.org/10.1073/pnas.1911348117.

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Uncertainty plays a critical role in reinforcement learning and decision making. However, exactly how it influences behavior remains unclear. Multiarmed-bandit tasks offer an ideal test bed, since computational tools such as approximate Kalman filters can closely characterize the interplay between trial-by-trial values, uncertainty, learning, and choice. To gain additional insight into learning and choice processes, we obtained data from subjects’ overt allocation of gaze. The estimated value and estimation uncertainty of options influenced what subjects looked at before choosing; these same q

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Wang, Guangying, Kai Chen, Jing Zhang, et al. "Drivers of Mating Type Composition in Tetrahymena thermophila." Genome Biology and Evolution 12, no. 12 (2020): 2328–43. http://dx.doi.org/10.1093/gbe/evaa197.

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Abstract Sex offers advantages even in primarily asexual species. Some ciliates appear to utilize such reproductive strategy with many mating types. However, the factors determining the composition of mating types in the unicellular ciliate Tetrahymena thermophila are poorly understood, and this is further complicated by non-Mendelian determination of mating type in the offspring. We therefore developed a novel population genetics model to predict how various factors influence the dynamics of mating type composition, including natural selection. The model predicted either the coexistence of al

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41

Crowe, David A., Bruno B. Averbeck, Matthew V. Chafee, John H. Anderson, and Apostolos P. Georgopoulos. "Mental Maze Solving." Journal of Cognitive Neuroscience 12, no. 5 (2000): 813–27. http://dx.doi.org/10.1162/089892900562426.

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We sought to determine how a visual maze is mentally solved. Human subjects (N = 13) viewed mazes with orthogonal, unbranched paths; each subject solved 200-600 mazes in any specific experiment below. There were four to six openings at the perimeter of the maze, of which four were labeled: one was the entry point and the remainder were potential exits marked by Arabic numerals. Starting at the entry point, in some mazes the path exited, whereas in others it terminated within the maze. Subjects were required to type the number corresponding to the true exit (if the path exited) or type zero (if

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Coppe, Sébastien, Jean-Jacques Orban de Xivry, Demet Yüksel, Adrian Ivanoiu, and Philippe Lefèvre. "Dramatic impairment of prediction due to frontal lobe degeneration." Journal of Neurophysiology 108, no. 11 (2012): 2957–66. http://dx.doi.org/10.1152/jn.00582.2012.

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Prediction is essential for motor function in everyday life. For instance, predictive mechanisms improve the perception of a moving target by increasing eye speed anticipatively, thus reducing motion blur on the retina. Subregions of the frontal lobes play a key role in eye movements in general and in smooth pursuit in particular, but their precise function is not firmly established. Here, the role of frontal lobes in the timing of predictive action is demonstrated by studying predictive smooth pursuit during transient blanking of a moving target in mild frontotemporal lobar degeneration (FTLD

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Li, Hongyan, Zhifeng Zhao, Qinghai Cai, Lichang Yin, and Jingxiang Zhao. "Nitrogen electroreduction performance of transition metal dimers embedded into N-doped graphene: a theoretical prediction." Journal of Materials Chemistry A 8, no. 8 (2020): 4533–43. http://dx.doi.org/10.1039/c9ta13599e.

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By means of comprehensive density functional theory computations, the FeRh dimer embedded in N-doped graphene was screened as a quite promising electrocatalyst with dual-atom centered sites for ammonia synthesis from N<sub>2</sub> fixation.

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Pitocchi, Jonathan, Mariska Wesseling, Gerrit Harry van Lenthe, and María Angeles Pérez. "Finite Element Analysis of Custom Shoulder Implants Provides Accurate Prediction of Initial Stability." Mathematics 8, no. 7 (2020): 1113. http://dx.doi.org/10.3390/math8071113.

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Custom reverse shoulder implants represent a valuable solution for patients with large bone defects. Since each implant has unique patient-specific features, finite element (FE) analysis has the potential to guide the design process by virtually comparing the stability of multiple configurations without the need of a mechanical test. The aim of this study was to develop an automated virtual bench test to evaluate the initial stability of custom shoulder implants during the design phase, by simulating a fixation experiment as defined by ASTM F2028-14. Three-dimensional (3D) FE models were gener

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Johnson, Solwin, and T. D. Subha. "A Study on Eye Fixation Prediction and Salient Object Detection in Supervised Saliency." Materials Today: Proceedings 4, no. 2 (2017): 4169–81. http://dx.doi.org/10.1016/j.matpr.2017.02.119.

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Deng, Tao, Hongmei Yan, and Yong-Jie Li. "Learning to Boost Bottom-Up Fixation Prediction in Driving Environments via Random Forest." IEEE Transactions on Intelligent Transportation Systems 19, no. 9 (2018): 3059–67. http://dx.doi.org/10.1109/tits.2017.2766216.

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Cheng, Zhangkai J., Regina M. Bromley, Brad Oborn, Martin Carolan, and Jeremy T. Booth. "On the accuracy of dose prediction near metal fixation devices for spine SBRT." Journal of Applied Clinical Medical Physics 17, no. 3 (2016): 475–85. http://dx.doi.org/10.1120/jacmp.v17i3.5536.

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48

Mahdi, Ali, Mei Su, Matthew Schlesinger, and Jun Qin. "A Comparison Study of Saliency Models for Fixation Prediction on Infants and Adults." IEEE Transactions on Cognitive and Developmental Systems 10, no. 3 (2018): 485–98. http://dx.doi.org/10.1109/tcds.2017.2696439.

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Ravanelli, Marco, Alberto Paderno, Francesca Del Bon, et al. "Prediction of Posterior Paraglottic Space and Cricoarytenoid Unit Involvement in Endoscopically T3 Glottic Cancer with Arytenoid Fixation by Magnetic Resonance with Surface Coils." Cancers 11, no. 1 (2019): 67. http://dx.doi.org/10.3390/cancers11010067.

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Discrimination of the etiology of arytenoid fixation in cT3 laryngeal squamous cell carcinoma (SCC) is crucial for treatment planning. The aim of this retrospective study was to differentiate among possible causes of arytenoid fixation (edema, inflammation, mass effect, or tumor invasion) by analyzing related signal patterns of magnetic resonance (MR) in the posterior laryngeal compartment (PLC) and crico-arytenoid unit (CAU). Seventeen patients affected by cT3 glottic SCC with arytenoid fixation were preoperatively studied by state-of-the-art MR with surface coils. Different signal patterns w

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Pollert, Anna. "The `Flexible Firm': Fixation or Fact?" Work, Employment and Society 2, no. 3 (1988): 281–316. http://dx.doi.org/10.1177/0950017088002003002.

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The model of the `flexible firm' has gained a prominent role in shaping debate about labour market flexibility and employment restructuring in the 1980s. It argues that employers are increasingly segmenting their workers between a permanent `core' of full-time employees, and a `periphery' of part-time, temporary, subcontract and `outsourced' workers. The `core' provides `functional flexibility' through lowered job demarcations and multi-skilling, while the `periphery' provides `numerical flexibility'. This paper argues that these generalisations are based on very selective cases, and reviews e

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