Find research datasets worth reusing

Figure 1. The podocopid ostracod Aurila kiritsubo Yajima, 1982 in Functional morphology and light-gathering ability of podocopid ostracod eyes and the palaeontological implications

Figure 1. The podocopid ostracod Aurila kiritsubo Yajima, 1982; the right valve with a close-up of the cuticular lens. Scale bar = 100 µm.

Figure 8 in Functional morphology and light-gathering ability of podocopid ostracod eyes and the palaeontological implications

Figure 8. The relationship between the total irradiance of the microhabitat (%) of each species (where the total irradiance at the sea surface is 100%) and the light-gathering ability of eyes (G).

Figure 11. A in Functional morphology and light-gathering ability of podocopid ostracod eyes and the palaeontological implications

Figure 11. A, the relationship between the relative valve thickness (Tv) and the relative thickness of the lens (E1): r, correlation coefficient; P, significance level of the correlation. B, plots of the standardized curvature of the outer lens surface (R1) against the relative height of the ridge (Hr).

Figure 5 in Functional morphology and light-gathering ability of podocopid ostracod eyes and the palaeontological implications

Figure 5. Nine selected three-dimensional contour diagrams showing the theoretical morphospace consisting of parameters R1, R2, and G. The z-axis represents the G value corresponding to each combination of R1 and R2, for E1 = 2.0, 1.0, and 0.05, and E2 = 0.3, 0.6, and 0.9. Selected theoretical models are given for the corresponding regions in the morphospace.

Fig. 5 in Reproductive behavior, development and eye regression in the cave armored catfish, Ancistrus cryptophthalmus Reis, 1987 (Siluriformes: Loricariidae), breed in laboratory

Fig. 5. Left eye size (diameter, in mm) versus total length (in mm) in the seven specimens (respectively a to g) of Ancistrus cryptophthalmus of the Passa Três 2004 offspring.

Fig. 2 in Reproductive behavior, development and eye regression in the cave armored catfish, Ancistrus cryptophthalmus Reis, 1987 (Siluriformes: Loricariidae), breed in laboratory

Fig. 2. Size (total length, in mm) versus age (in days) in four specimens of Ancistrus cryptophthalmus from Passa Três Cave born in laboratory in March 2003.

Fig. 4 in Reproductive behavior, development and eye regression in the cave armored catfish, Ancistrus cryptophthalmus Reis, 1987 (Siluriformes: Loricariidae), breed in laboratory

Fig. 4. Size (total length, in mm) versus age (in days) of two wild caught specimens of Ancistrus cryptophthalmus from Angélica Cave kept in laboratory.

Fig. 1 in Reproductive behavior, development and eye regression in the cave armored catfish, Ancistrus cryptophthalmus Reis, 1987 (Siluriformes: Loricariidae), breed in laboratory

Fig. 1. (a) Reproductive adults of Ancistrus cryptophthalmus from Passa Três Cave kept in laboratory: two females (to the left) and male (to the right, dorso-posterior region of the head red-colored); arrow indicates the entrance of the shelter occupied by the male. Photograph taken on April 2004. (b) Cluster of eggs adhered to the ceiling of the shelter, average diameter = 4.0 mm. (c) Area around the shelter entrance (within the white circle) defended by the male (close to the center of the circle). (d) Clockwise from the top left: embrio (eyes visible), newly hatched larva (10.4 mm TL), more advanced larva (12.5 mm TL), with yolk-sac almost completely absorbed. (e) Top: 53 mm long juvenile from Passa Três Cave, with regressed eyes; arrow indicates the orbit reduced to a small depression covered with skin. Bottom: 53 mm long juvenile from Angélica Cave, probable the same age as the former, showing non-regressed eyes. (f) Detail of the head of the juvenile from Passa Três; arrows indicate the first primordia of tentacles.

Fig. 6 in Reproductive behavior, development and eye regression in the cave armored catfish, Ancistrus cryptophthalmus Reis, 1987 (Siluriformes: Loricariidae), breed in laboratory

Fig. 6. Eye size (diameter, in mm) versus age (in days) in three selected specimens (from left to right) of Ancistrus cryptophthalmus from Passa Três Cave; right eye on the top, left eye on the bottom.

opencc-by-4.0Nov 2022View details →

SYNTHETIC dataset attached to the paper "Grasp Pre-shape Selection by Synthetic Training: Eye-in-hand Shared Control on the Hannes Prosthesis"

SYNTHETIC dataset to replicate the results in "Grasp Pre-shape Selection by Synthetic Training: Eye-in-hand Shared Control on the Hannes Prosthesis", accepted to IEEE/RSJ IROS 2022. In order to fully reproduce the experiments, download also the REAL dataset.  To automatically download the REAL and SYNTHETIC dataset, run the script provided at the link below. Code to replicate the results available at: https://github.com/hsp-iit/prosthetic-grasping-experiments

opencc-by-4.0Nov 2022View details →

REAL dataset attached to the paper "Grasp Pre-shape Selection by Synthetic Training: Eye-in-hand Shared Control on the Hannes Prosthesis"

REAL dataset to replicate the results in "Grasp Pre-shape Selection by Synthetic Training: Eye-in-hand Shared Control on the Hannes Prosthesis", accepted to IEEE/RSJ IROS 2022. In order to fully reproduce the experiments, download also the SYNTHETIC dataset.  To automatically download the REAL and SYNTHETIC dataset, run the script provided at the link below. Code to replicate the results available at: https://github.com/hsp-iit/prosthetic-grasping-experiments

opencc-by-4.0Dec 2022View details →

Fig. 2. Andromma Simon, 1893. A–E. Eye patterns, dorsal view. F. Spinnerets, ventral view. G. ALS, ventral view. A–B in Studies in the Liocranidae (Araneae): revision of Andromma Simon, 1893

Fig. 2. Andromma Simon, 1893. A–E. Eye patterns, dorsal view. F. Spinnerets, ventral view. G. ALS, ventral view. A–B. Andromma deogratias sp. nov. A. ♂, paratype (BE_RMCA_ARA.Ara 246048). B. ♀, paratype (BE_RMCA_ARA.Ara 246054). C–D. Andromma divinagraciae sp. nov. C. ♂, holotype (BE_ RMCA_ARA.Ara 246051). D. ♀, paratype (BE_RMCA_ARA.Ara 246055). E. Andromma ghesquierei sp. nov., ♀, paratype (BE_RMCA_ARA.Ara 84109). F–G. Andromma divinagraciae sp. nov., ♂, paratype (BE_RMCA_ARA.Ara 246056). Scale bars: A–E = 0.2 mm; F = 0.1 mm; G = 0.01 mm.

opencc-by-4.0Apr 2022View details →

Watching with Argus Eyes: Characterization of emotional and physiological responding in adults exposed to childhood maltreatment and/or recent adversity

Background: Exposure to adverse experiences is a well-established major risk factor for affective psychopathology. The vulnerability of deleterious sequelae is assumed in maladaptive processes of the defensive system, particularly in emotional processing. More specifically, childhood maltreatment has been suggested to be associated with the recruitment of specific and distinct defensive response profiles. To date it remains unclear whether these are specific or generalisable to recent adversity in adulthood. Method: This preregistered study aimed to investigate the impact of exposure to childhood and recent adversity on emotional processing in 685 healthy adults with the “Affective Startle Modulation” Paradigm (ASM). Results: First, we replicated higher trait anxiety and depression levels in individuals exposed to both types of adversity. Second, we observed blunted general skin conductance reactivity in individuals exposed to recent adversity. Third, individuals exposed to childhood maltreatment showed reduced, while individuals exposed to recent adversity showed increased discrimination between pictures of negative and neutral valence, compared to non-exposed individuals in SCR. No association between exposure to adversity and fear potentiated startle was observed. Furthermore, explorative analyses revealed moderate dimensional and categorical agreement between two childhood maltreatment questionnaires and provide insight into potential adversity-type specific effects. Conclusion: Our results support experience-dependent plasticity in sympathetic nervous system reactivity and suggest distinct response profiles in affective modulation in individuals exposed to early versus recent adversity. We emphasise the need to further explore distinct adversity profiles to further our understanding on specific psychophysiological profiles and their potential implication for prevention and intervention.

opencc-by-4.0Jan 2022View details →

COLET: A Dataset for Cognitive workLoad estimation based on Eye-Tracking

Cognitive workload is an important component in performance psychology, ergonomics, and human factors. Unfortunately, benchmarks and publicly available datasets are scarce, making it difficult to establish new approaches and comparative studies. In this work, COLET-COgnitive workLoad state estimation based on Eye-Tracking dataset is presented. Forty-seven (47) individuals' eye movements were monitored as they solved puzzles involving visual search tasks of varying complexity and duration. The authors give an in-depth study of the participants' performance during the experiments while eye and gaze features were derived from low-level eye recorded metrics, and their relationships with the experiment tasks were investigated. Finally, the results from the classification of cognitive workload levels solely based on eye and gaze data, by employing and testing a set of machine learning algorithms are provided. The dataset is made available to the public.   Please cite the following work:  Ktistakis, E., Skaramagkas, V., Manousos, D., Tachos, N. S., Tripoliti, E., Fotiadis, D. I., & Tsiknakis, M. (2022). Colet: A dataset for cognitive workload estimation based on eye-tracking. Computer Methods and Programs in Biomedicine, 106989. https://doi.org/10.1016/j.cmpb.2022.106989

opencc-by-4.0Jan 2022View details →

eSEEd: emotional State Estimation based on Eye-tracking dataset

We present eSEEd- emotional State Estimation based on Eye-tracking database. Eye movements of 48 participants were recorded as they watched 10 emotion evoking videos each of them followed by a neutral video. Participants rated five emotions (tenderness, anger, disgust, sadness, neutral) on a scale from 0 to 10, later translated in terms of emotional arousal and valence levels. Furthermore, each participant filled 3 self-assessment questionnaires. An extensive analysis of the participants' answers to the questionnaires self-assessment scores as well as their ratings during the experiments is presented. Moreover, eye and gaze features were extracted from the low level eye recorded metrics and their correlations with the participants' ratings are investigated. Finally, analysis and results are presented for machine learning approaches, for the classification of various arousal and valence levels based solely on eye and gaze features. The dataset is made publicly available and we encourage other researchers to use it for testing new methods and analytic pipelines for the estimation of an individual's affective state. TO USE THIS DATASET PLEASE CITE: Skaramagkas, V.; Ktistakis, E.; Manousos, D.; Kazantzaki, E.; Tachos, N.S.; Tripoliti, E.; Fotiadis, D.I.; Tsiknakis, M. eSEE-d: Emotional State Estimation Based on Eye-Tracking Dataset. Brain Sci. 2023, 13, 589. https://doi.org/10.3390/brainsci13040589

opencc-by-4.0May 2023View details →

DynamicRead: Eye Movement Data of Reading on Handheld Mobile Devices under Dynamic Conditions

The DynamicRead dataset contains eye movement data from 20 participants engaged in reading tasks on a handheld mobile device, while sitting and walking. Participants read 10 texts using four gaze interaction methods based on scrolling techniques, as well as one touch-based interaction method. The dataset captures the impact of motion on eye movement and features an unstable eye-movement sampling frequency ranging from 8-12fps/hz, which poses a challenge for traditional eye-movement toolkits. This dataset can be valuable for academic research on the impacts of motion on eye movement and the development of robust gaze interaction methods for handheld mobile devices under dynamic conditions. ### Folder Structure: -'eye_data'         -- contains eye movement of reading data -'text_screenshot'     -- contains different reading material screenshot -'heatmap_img'        -- contains heat map of each reading page  -'scanpath_img'        -- contains scan path of each reading page -'text'            -- contains reading material -'code'         -- contains R code for reading eye movement visualisation Name Method - GAP1_GazeA_log.txt -- Group A, Participant No1, Scrolling technique: GazeA - Gaze A: Auto-scrolling - Gaze B: Heatbox - Gaze C: Eye-Swipe - Gaze D: Moving-bar

Figs 64–66 in A revision of the southern African two-eyed spider genus Diploglena (Araneae: Caponiidae)

Figs 64–66. Left male palp of Diploglena proxila sp. n. in prolateral (64), ventral (65) and retrolateral views (66). Scale bars = 0.25 mm.

Fig. 63 in A revision of the southern African two-eyed spider genus Diploglena (Araneae: Caponiidae)

Fig. 63. Distribution of Diploglena arida sp. n. (black circles), D. capensis Purcell, 1904 (open circles), D. dippenaarae sp. n. (black squares), D. karooica sp. n. (open squares), D. major Lawrence, 1928 (black triangles), D. proxila sp. n. (white circle) and undetermined Diploglena immatures (open triangles) in southern Africa.

Figs 60–62 in A revision of the southern African two-eyed spider genus Diploglena (Araneae: Caponiidae)

Figs 60–62. Left male palp of Diploglena major Lawrence, 1928 in prolateral (60), ventral (61) and retrolateral views (62). Scale bars = 0.25 mm.

Figs 54–59 in A revision of the southern African two-eyed spider genus Diploglena (Araneae: Caponiidae)

Figs 54–59. Left male palps of Diploglena dippenaarae sp. n. (54–56) and D. karooica sp. n. (57–59): (54, 57) prolateral view; (55, 58) ventral view; (56, 59) retrolateral view. Scale bars = 0.25 mm.