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183 results for “indicators of effectiveness”
Dataset: Brain negativity as an indicator of predictive error processing: The contribution of visual action effect monitoring
<p>There are two files for each subject:</p> <p>1. sub##_error.dat -> Contains EEG Segments, that were recorded while the subject executed a clear target miss (minimal distance between the center of the ball and target > 12 cm) in the task (segment and electrode information can be found below).</p> <p>2. sub##_hit.dat -> Contains EEG Segments, that were recorded while the subject executed a clear target hit (minimal distance between the center of the ball and the target < 7 cm) in the task (segment and electrode information can be found below).</p> <p><br> The data in the *.dat-files are stored in a two dimensional matrix: n*1400 datapoints x 15 electrodes</p> <p>n represents the number of segments. 1400 datapoints per segment translate to a segment length of 2800 ms (from 600 ms before to 2200 ms after ball release). The ball´s release is located at the 301st datapoint and the feedback was presented at datapoint 726 (850 ms after ball release) in every segment.</p> <p>datapoints: The first dimension (rows) includes the measured neural activations in microvolts. The data is stored vectorized,<br> i.e. hit/error #1 -> row 1 to 1400, hit/error #2 -> row 1401 to 2800, ..., hit/error #n -> (n-1) * 1400 + 1 to n * 1400</p> <p>electrodes: The second dimension (columns) consists of the 15 different electrodes that were used during data recording in this exact order: [F3 Fz F4 C4 Cz C3 P3 Pz P4 VEOGu VEOGo HEOGre HEOGli FCz Mastre]</p>
Dataset on Physics-Based Indicators for Optimizing Phase Change Material Effectiveness in Building Design
<p>This research dataset includes the results as well as the EnrgyPlus models developed to investigate and validate newly proposed indicators to quantify the effectiveness of phase change materials in buildings.</p>
Data for: Multi-generational fitness effects of natural immigration indicate strong heterosis and epistatic breakdown in a wild bird population
<p><span>The fitness of immigrants and their descendants produced within recipient populations fundamentally underpins the genetic </span><span>and population dynamic</span><span> consequences of immigration. </span><span>I</span><span>mmigrants can </span><span>in principle </span><span>induce contrasting genetic effects on fitness across generations, reflecting multi-faceted additive, dominance, and epistatic effects. Y</span><span>et, full multi-generational and sex-specific fitness effects of regular immigration have not been quantified within naturally structured systems, precluding inference on underlying genetic architectures </span><span>and population outcomes</span><span>. We used four decades of song sparrow </span><span>(<em>Melospiza melodia</em>)</span> <span>life-history and pedigree data to quantify fitness of natural immigrants, natives, and their F1, F2, and backcross descendants, and test for evidence of non-additive genetic effects. Values of key fitness components (including adult lifetime reproductive success and zygote survival) of F1 offspring of immigrant-native matings substantially exceeded their parent mean, indicating strong heterosis. Meanwhile, F2 offspring of F1-F1 matings had notably low values, indicating surprisingly strong epistatic breakdown. Further, magnitudes of effects varied among fitness components, and</span> <span>differed between female</span><span>s</span><span> and male</span><span>s</span><span> descendants. These results demonstrate that strong non-additive genetic effects on fitness can arise within </span><span>weakly </span><span>structured </span><span>and fragmented </span><span>populations </span><span>experiencing </span><span>frequent </span><span>natural </span><span>immigration. </span><span>Such effects will substantially affect the net </span><span>degree of effective gene flow and resulting local genetic introgression and adaptation.</span></p>
Figure 2 in Effects of methyl farnesoate injection on spermatozoa number and reproductive indices in the narrow-clawed crayfish Pontastacus leptodactylus
Figure 2. Effect of MF injection on reproductive system weight and GSI in male Pontastacus leptodactylus. Letters indicate significant difference groupings (P <0.05) (mean ± S.D; n = 15).
Direct and indirect phenotypic effects on sociability indicate potential to evolve
<p class="MsoNormal">The decision to leave or join a group is important as group size influences many aspects of organisms' lives and their fitness. This tendency to socialise with others, sociability, should be influenced by genes carried by focal individuals (direct genetic effects) and by genes in partner individuals (indirect genetic effects), indicating the trait's evolution could be slower or faster than expected. However, estimating these genetic parameters is difficult. Here, in a laboratory population of the cockroach <em>Blaptica dubia</em>, I estimate phenotypic parameters for sociability: repeatability (<em><span>R</span></em>) and repeatable influence (<em><span>RI</span></em>), which indicate whether direct and indirect genetic effects respectively are likely. I also estimate the interaction coefficient (<em><span>Ψ</span></em><em>)</em>, which quantifies how strongly a partner's trait influences the phenotype of the focal individual and is key in models for the evolution of interacting phenotypes. Focal individuals were somewhat repeatable for sociability across a three-week period (<em><span>R</span></em> = 0.080), and partners also had marginally consistent effects on focal sociability (<em><span>RI</span></em> = 0.053). The interaction coefficient was non-zero, although in the opposite sign for the sexes; males preferred to associate with larger individuals (<em><span>Ψ</span></em><sub>male </sub>= -0.129) while females preferred to associate with smaller individuals (<em><span>Ψ</span></em><sub>female</sub><strong><sub> </sub></strong>= 0.071). Individual sociability was consistent between dyadic trials and in social networks of groups. These results provide phenotypic evidence that direct and indirect genetic effects have limited influence on sociability, with perhaps the most evolutionary potential stemming from heritable effects of the body mass of partners. Sex-specific interaction coefficients may produce sexual conflict and the evolution of sexual dimorphism in social behaviour.</p>
Host Data from: [O II] as an Effective Indicator of the Dependence Between the Standardised Luminosities of Type Ia Supernovae and the Properties of their Host Galaxies
<p>Spectral properties of the Foundation Host Galaxies presented in the paper: <span>[O</span> II<span>] as an Effective Indicator of the Dependence Between the </span><span>Standardised Luminosities of Type Ia Supernovae and the Properties of </span><span>their Host Galaxies.</span></p> <p><span>Spectra were taken using the WiFeS instrument on the ANU 2.3m Telescope.</span></p>
Success in Mobile and Ubiquitous Learning: Indicators of Effectiveness-Figure 9. Proportion of indicators used in the case studies
<p>Figure 9 presents the indicators used for evaluating the effectiveness of mobile and ubiquitous learning practices. Learning achievements (64%) and perceived usefulness (56%) were the two most frequently used, followed by motivation (26%), ease of use (26%) and satisfaction (24%).<br> cognitive load (12%), system usage (8%), self-efficacy (6%) and social engagement (2%). Those indicators were usually adopted in the studies using qualitative methods for data collection. The results suggest a possible relationship between the data collection methods and the indicators. The choices of indicators represent, in principle, how the effectiveness of mobile and ubiquitous learning practices can be most appropriately evaluated and presented using particular study methods.</p>
Success in Mobile and Ubiquitous Learning: Indicators of Effectiveness-Figure 8. Functions of the mobile devices used in the practices (Note: Each case could involve the use of more than one function.)
<p>Figure 8 captures the functions of mobile devices used in the practices. The results show that tailor-made applications for specific practices were most common (74%), followed by the use of a speaker (32%) and a camera (26%), where learners had to listen to audio materials using speakers or access online information by scanning QR-codes through cameras. In the various practices, other functions were also used, such as messaging (16%) for interacting with diverse parties and GPS (14%) for outdoor learning activities. For the practices using older models of mobile devices without cameras, tools such as an RFID reader (8%) were used for accessing information via communication tags.</p>
Success in Mobile and Ubiquitous Learning: Indicators of Effectiveness-Figure 5. Level of intervention of the studies
<p>Figure 5 illustrates the levels of intervention of the studies. Most studies concentrated on the course level (76.9%) and some on either the programme level (13.5%) or the institutional level (9.6%). Two studies were conducted at more than one level. These results supplement the above number of participants where most of the studies were conducted on a small scale.</p>
Success in Mobile and Ubiquitous Learning: Indicators of Effectiveness-Figure 6. Purposes of using mobile devices for learning
<p>Figure 6 shows the purposes of mobile and ubiquitous learning in the studies. A majority of the cases were multi-purpose (54%). Those with a single specific purpose were focused on “practice or revision” (34%) and “knowledge acquisition” (10%). There was a case where the application was to help new students to become familiar with the campus and teach them about the use of the facilities.</p>
Success in Mobile and Ubiquitous Learning: Indicators of Effectiveness-Figure 1. Geographical distribution of the case studies
<p>The 50 cases of mobile and ubiquitous learning practices covered 14 countries/regions, including China, Japan, Taiwan, Korea, Sri Lanka, Turkey, Spain, Greece, the Netherlands, Britain, Australia, New Zealand, South Africa and the USA. Figure 1 shows the geographical distribution of the cases. Among the 50 cases, 70% were conducted in Asia, 16% in Europe, 4% in Oceania, 4% in Africa, and 2% in North America. Therefore, the results of this study represent more of the situation in Asia.</p>
Success in Mobile and Ubiquitous Learning: Indicators of Effectiveness-Figure 7. Level of interactivity of the studies
<p>Figure 7 presents the level of interactivity in using mobile devices. Sixty percent of the cases involved only one-way access for information either online or offline, while 8% involved social interaction with information exchange among learners. Also 32% of the cases included both levels of interactivity in learning.</p>
Success in Mobile and Ubiquitous Learning: Indicators of Effectiveness-Figure 4. Number of participants in the studies
<p>Figure 4 shows the number of participants in the studies, with the majority being on a small scale, having less than 100 participants (72%). Twenty percent of the studies involved over 100 but less than 1,000 participants, and only two cases included more than 1,000 participants (4%).</p>
Success in Mobile and Ubiquitous Learning: Indicators of Effectiveness-Figure 2. Data collection methods of the studies (Note: A study may involve more than one method.)
<p>Figure 2 shows the data collection methods applied in the studies. Surveys were used in most of the selected cases (94%), followed by interviews (38%) and experiments (34%). Apart from these approaches, observation (12%), field materials (8%), video recordings (6%) and discussion threads (2%) were also used in some of the studies. Thirty of the cases involved the use of more than one method, mostly combining a survey and another one or more method. These suggest that most of the studies involved quantitative data at least in part.</p>
Success in Mobile and Ubiquitous Learning: Indicators of Effectiveness-Figure 3. Education level of the studies
<p>Figure 3 presents the education levels of the mobile and ubiquitous learning practices. Most studies took place at the tertiary level (66.7%). Also, 25.5% of the studies were conducted at the primary school level and 7.8% at the secondary school level.</p>
Dataset for: Effects of constant versus fluctuating temperatures on fitness indicators of the aphid Dysaphis plantaginea and the parasitoid Aphidius matricariae
<p>This is the dataset for the article entitled: Effects of constant versus fluctuating temperatures on fitness indicators of the aphid Dysaphis plantaginea and the parasitoid Aphidius matricariae.</p> <p>Like all organisms, insects encounter temperatures that fluctuate on different time scales: within a day, between days, or throughout the seasons. However, most studies on the impact of temperature on insect physiology, behaviour, morphology or ecology have focused on constant temperatures tested in the laboratory. In our study, we wanted to know if fluctuating temperatures during the day (7—17°C, average 12°C) can affect insects differently compared to a constant temperature of 12°C. We use as a model the apple aphid <em>Dysaphis plantaginea</em>, a major threat to apple orchards worldwide, and its parasitoid <em>Aphidius matricariae</em>, which is used in biological control. We found that many traits—but not all—were affected. In particular, the fluctuating thermal regime decreased the development time of aphids and parasitoids, improved the rate of parasitism, and tended (albeit slightly) to improve the survival of both species. In contrast, we did not find strong effects on morphological traits. Our results can be used to better predict how these agronomically important insects behave in orchards, how fluctuating temperatures affect host-parasitoid relationships, and ultimately what the implications are in the context of climate change and biological control.</p> <p> </p>
Fig. 1 in The effect of rearing temperature in larval development of pejerrey, Odontesthes bonariensis - Morphological indicators of development
Fig. 1. Embryonic stages of pejerrey. A) One cell stage: bd, blastodisc; f, adherent filaments; od, oil droplets; pv, perivitelline space; B) Two cells stage: bm, blastomeres; C) Blastula stage: b, blastula; D) Animal pole view at 25% epiboly stage, es, embryonic shield; gr, germinal ring; E) Vitelline veins stage: ol, ocular lenses; op, optic capsule, ot; otic capsules; sod, single oil drop; F) Pectorals fins stage: bv, bile vesicle; pf, pectoral fins; vv, vitelline veins. G) Hatching: n, notochord; o, otoliths; sb, swim bladder; sod, single oil droplet. A-F) bar = 0.5 mm; G) bar = 1 mm.
Fig. 6 in The effect of rearing temperature in larval development of pejerrey, Odontesthes bonariensis - Morphological indicators of development
Fig. 6. Differences in the rate of fin fold restructuration among larvae. A-B) same age, same temperature and different finfold stages; C-D) same age, different temperature and different finfold stage; B-D) different temperature, same age and same finfold stage. A) 24ºC, 14 dph, TL=9.1 mm; B) 24ºC 14 dph, TL=11.7 mm; C) 17ºC 14 dph, TL=8.1 mm; D) 29ºC 14 dph, TL=11.1 mm. Bar = 1 cm.
Fig. 2. Fin fold reabsorption during larvae-juvenile transition. A in The effect of rearing temperature in larval development of pejerrey, Odontesthes bonariensis - Morphological indicators of development
Fig. 2. Fin fold reabsorption during larvae-juvenile transition. A) The characteristic lobulated caudal fin showing the first fin rays (arrowhead) and the straight notochord (arrow); B) The second segment appeared (arrowhead) and the ray started to be aligned with the rostro-caudal axis (arrow); C) The ray aligned with the rostro-caudal axis (arrow); D) The forked homocercal caudal fin; E) Bifurcation of the central fin rays (arrowhead); F) The remnant fin-fold between the anus and the anal fin; G) The body shape acquires the adult conformation. A-F, bar = 0.5 mm; G = 1 mm.
Fig. 5 in The effect of rearing temperature in larval development of pejerrey, Odontesthes bonariensis - Morphological indicators of development
Fig. 5. Body shape (DA applied on un-standardized residuals, N = 287, P <0.001). Discriminant function 2 versus discriminant function 1. Rearing temperature is indicated as black circles (FPT), triangles (MixPT) and black squares (MTP). Means and 95% confidence intervals correspond to FPT (circle), MixPT (triangle), and MTP (square).
ScienceDex guides
Understand access before you commit
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.