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Fig. 2 in New Insights into the Male Morphotypes of the Amphidromous Shrimp (Weigmann, 1836) (Caridea: Palaemonidae) and a Discussion on Social Dominance Hierarchies.
Fig. 2. Macrobrachium olfersii (Wiegmann, 1836). Principal Component Analysis (PCA) of morphometric variables. Values indicate the projection of components 1 and 2 (PC1 and PC2).
Fig. 1 in New Insights into the Male Morphotypes of the Amphidromous Shrimp (Weigmann, 1836) (Caridea: Palaemonidae) and a Discussion on Social Dominance Hierarchies.
Fig. 1. (A) Carapace of Macrobrachium olfersii (Wiegmann, 1836). Dimension of carapace length (CL) measurements. (B) Major cheliped of Macrobrachium olfersii. Exemplification of the dimensions used to measure the length and height of the articles of the larger cheliped. The same measurements were used for the smaller cheliped. (C) Propodus of the larger cheliped of Macrobrachium olfersii in the standard position used in the geometric morphometric analyses. Red and blue circles are the landmarks and semilandmarks, respectively. CL = Carapace length; IL = Ischium length; ML = Merus length; CaL = Carpus length; PrL = Propodus length; DL = Dactylus length; PrH = Propodus height.
Fig. 5 in New Insights into the Male Morphotypes of the Amphidromous Shrimp (Weigmann, 1836) (Caridea: Palaemonidae) and a Discussion on Social Dominance Hierarchies.
Fig. 5. Macrobrachium olfersii (Wiegmann, 1836). Specimens and chelipeds of the male morphotypes, (A and B) Juvenile, (C and D) Morphotype 1, (E and F) Morphotype 2, and (G and H) Morphotype 3. All scale bars correspond to 10 mm, except for the scale bar present in 6B, which corresponds to 5 mm.
Fig. 6 in New Insights into the Male Morphotypes of the Amphidromous Shrimp (Weigmann, 1836) (Caridea: Palaemonidae) and a Discussion on Social Dominance Hierarchies.
Fig. 6. Macrobrachium olfersii (Wiegmann, 1836). (A) Scatter plot of canonical variation analysis (CVA) performed with the coordinates of variation in the propodus shape of the male morphotypes. (B) Variation in the propodus shape of each male morphotype. M3 presents evident differences in the shape of the palm region and also in the fixed finger in relation to the other morphotypes.
Fig. 2. Maximum likelihood tree for Crematogaster rothneyi and C. yaharai inferred from 12S in Fig. 7 in Effect of Kleptoparasitic Ants on the Foraging Behavior of a Social Spider ( Karsch, 1891).
Fig. 2. Maximum likelihood tree for Crematogaster rothneyi and C. yaharai inferred from 12S rRNA sequences (12S, 387 bp). Numbers above nodes indicate the bootstrap values. Please note, only one sequence from each population was available.
Fig. 3 in Fig. 7 in Effect of Kleptoparasitic Ants on the Foraging Behavior of a Social Spider ( Karsch, 1891).
Fig. 3. Crematogaster rothneyi. (A, B, C) non-type worker from Calcutta, India (HW 0.8; WL 0.9). (A) body in lateral view; (B) full-face view of head; (C) dorsal view of mesosoma, petiole and postpetiole. (D, E, F) non-type worker from Sulawesi, Indonesia (HW 0.74; WL 0.88). (D) body in lateral view; (E) full-face view of head; (F) dorsal view of mesosoma, petiole and postpetiole.
Fig. 1 in Fig. 7 in Effect of Kleptoparasitic Ants on the Foraging Behavior of a Social Spider ( Karsch, 1891).
Fig. 1. Distribution map of the Crematogaster rothneyi group. Closed circle indicates C. rothneyi, closed triangle indicates C. rothneyi haputalensis, closed square indicates C. yaharai.
Fig. 5 in Fig. 7 in Effect of Kleptoparasitic Ants on the Foraging Behavior of a Social Spider ( Karsch, 1891).
Fig. 5. Left antenna. (A) Crematogaster rothneyi; (B) Crematogaster yaharai. Arrow indicates antennal segments V and VI.
Fig. 4 in Fig. 7 in Effect of Kleptoparasitic Ants on the Foraging Behavior of a Social Spider ( Karsch, 1891).
Fig. 4. Crematogaster yaharai, paratype worker from Cambodia (HW 0.72; WL 0.83). (A) body in lateral view; (B) full-face view of head; (C) dorsal view of mesosoma, petiole and postpetiole.
Fig. 7 in Effect of Kleptoparasitic Ants on the Foraging Behavior of a Social Spider ( Karsch, 1891).
Fig. 7. Handling time (minutes) of both K unexposed (Ku, n = 3 groups) and K exposed (Ke, n = 3 groups) spider groups recorded during three different times (9 am, 1 pm and 5 pm) of the four experimental days.
Fig. 4 in Effect of Kleptoparasitic Ants on the Foraging Behavior of a Social Spider ( Karsch, 1891).
Fig. 4. Web rebuilding ability (Size of the web (cm2 ± SEM) of the K unexposed (Kleptoparasite "K" is O. smaragdina) spider groups (Fasted (n = 3 groups) and Fed (n = 3 groups)) during the 4 experimental days. The regression lines, blue line (Fasted spider) has the Intercept a = 236.94, Slope b = 71.812 and Coefficient of Determination R² = 0.966 and the red line (Fed spider) has a = 78.925, b = 55.61 and R² = 0.955.
Fig. 3 in Effect of Kleptoparasitic Ants on the Foraging Behavior of a Social Spider ( Karsch, 1891).
Fig. 3. Kleptoparasites of S. sarasinorum. (A) Argyrodes kumadai (Dewdrop spider). (B) Hyllus semicupreus (Heavy-bodied jumper). (C) Phintella vittata (Banded phintella). (D) Oxyopes javanus (Lynx spider). (E) Oecophylla smaragdina (Weaver ant). (F) Anoplolepis gracilipes (Yellow crazy ant). Photo courtesy of: Karunnappilli S. Nafin.
Fig. 6 in Effect of Kleptoparasitic Ants on the Foraging Behavior of a Social Spider ( Karsch, 1891).
Fig. 6. Size of the web (cm2 ± SEM) built by fed and fasted (K unexposed ("- K exposure"): n = 3 groups) and K exposed ("+ K exposure"): n = 3 groups) spider groups.
Fig. 2 in Effect of Kleptoparasitic Ants on the Foraging Behavior of a Social Spider ( Karsch, 1891).
Fig. 2. (A) An individual colony of S. sarasinorum. (B) Experimental set-up for the study. (C) Spiders (Host) in captivity- Ant (Kleptoparasite- O. smaragdina) exposed.
Fig. 5 in Effect of Kleptoparasitic Ants on the Foraging Behavior of a Social Spider ( Karsch, 1891).
Fig. 5. Web rebuilding ability (Size of the web (cm2 ± SEM)) of the K exposed (Kleptoparasite "K" is O. smaragdina) spider groups (Fasted (n = 3 groups) and Fed (n = 3 groups)) during the 4 experimental days. The regression lines, blue line (Fasted spider) has the Intercept a = 64.13, Slope b = 73.361 and Coefficient of Determination R2 = 0.96 and the red line (Fed spider) has a = 41.5, b = 65.25 and R2 = 0.948.
Fig. 1 in Effect of Kleptoparasitic Ants on the Foraging Behavior of a Social Spider ( Karsch, 1891).
Fig. 1. Map of the study area – Social spider web colonies (Marked as red spot) on Christ College Irinjalakuda.
Towards suitable practices for the integration of social life cycle assessment into the ecodesign framework of hydrogen-related products
<p>The hydrogen sector is envisaged as one of the key enablers of the energy transition that the European Union is facing to accomplish its decarbonization targets. However, regarding the technologies that enable the deployment of a hydrogen economy, a growing concern exists about potential burden-shifting across sustainability<br>dimensions. In this sense, social life cycle assessment arises as a promising methodology to evaluate the social implications of hydrogen technologies along their supply chains. In the context of the European projects eGHOST and SH2E, this study seeks to advance on key methodological aspects of social life cycle assessment when it<br>comes to guiding the ecodesign of two relevant hydrogen-related products: a 5 kW solid oxide electrolysis cell stack for hydrogen production, and a 48 kW proton-exchange membrane fuel cell stack for mobility applications.<br>Based on the social life cycle assessment results for both case studies under alternative approaches, the definition of a product-specific supply chain, making use of appropriate cut-off criteria, was found to be the preferable choice when addressing system boundaries definition. Moreover, performing calculations according to the activity variable approach was found to provide valuable results in terms of social hotspots identification to support subsequent decision-making processes on ecodesign, while the direct calculation approach is foreseen as a complement to ease the interpretation of social scores. It is concluded that advancements in the formalization of<br>such suitable practices could foster the integration of social metrics into the sustainable-by-design framework of hydrogen-related products.</p>
Disclosure Privacy Information Social Media on TikTok
<p><em><span>With the rapid development of technology, the use of social media by the public, especially among young people, is increasing. One of the social media platforms currently used by young people is the TikTok application. It is a video-based TikTok feature accompanied by music, writing, and pictures that are considered attractive, so teenagers like it to show their existence and self-disclosure. Therefore, this study aims to examine the intention of users to disclose their privacy. As the basis of the theory, this study deployed the privacy calculus theory, where the perceived benefits and perceived risks play crucial roles in the intention to disclose their privacy</span></em></p>
Social Science Preregistration Metadata Crosswalk
<p>This spreadsheet tries to create a crosswalk for the main four social science study preregistration platfroms:</p> <ul> <li>OSF (Based on the fields for the preregistration challenge)</li> <li>EGAP</li> <li>The AEA's Social Science Registry</li> <li>RIDIE</li> </ul> <p>as well as the DataCite 4.0 Metadata Kernel</p>
Figure 11. Cognitive architecture of the process of social signals perception-Gestalt Processing in Human-Robot Interaction: A Novel Account for Autism Research
<p>A possible cognitive architecture and formalization of the process of learning via<br> multisensory integration is presented in figure 11. The formal description of the proposed cognitive<br> architecture, capable of interpreting social-communication signals, signs and symbols, is based on<br> multisensory integration at the level of perception, parallel processing at the level of interpretation<br> and decision making followed by verbalization, as well as performing an action (eye contact,<br> gesture, mimicking) at the level of behaviour.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.