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opencc-by-4.0Dec 2012View details →

Figs 1–4 in The types of Lygistorrhinidae and Mycetophilidae (Diptera: Bibionomorpha) in the KwaZulu-Natal Museum, Pietermaritzburg, South Africa

Figs 1–4. (1) Lygistorrhina sanctaecatharinae Thompson, paratype "NMSA-Dip. 11308"; (2) Dinempheria enigmata Väisänen, holotype; (3) Dziedzickia peckorum Matile, paratype "NMSA-DIP 66399"; (4) Dziedzickia stuckenbergorum Matile, holotype. Scale bars = 1 mm.

opencc-by-4.0Dec 2012View details →

Figs 3, 4 in The megadrile fauna (Annelida: Oligochaeta) of Queen Elizabeth Park, South Africa: species composition and distribution within different vegetation types

Figs 3, 4. Tritogenia howickiana: (3) anterior part of the body, showing papillae and tubercula pubertatis ventrally; (4) dorsal dissection showing thickened septa. Abbreviations: Cl – clitellum, DB – double blood vessel, P – papillae of 15–17, S – septa 4/5–6/7, Tp – tubercula pubertatis,.

opencc-by-4.0Dec 2011View details →

Fig. 2 in Pupa menkeana Pfeiffer, 1853, type species of the speciose land snail genus Gulella Pfeiffer, 1856: correction of longstanding PLVLGHQWL¿FDWLRQ DQG GHVLJQDWLRQ RI QHRW\SH (Mollusca: Eupulmonata: Streptaxidae)

Fig. 2. (A, B) lectotype and paralectotype of Ennea adamsiana Pfeiffer, 1859 in 1854–1860, 'Port Natal, M.C. [Mus. Cuming]', length 8.45 and 8.1 mm (NHMUK 20110168); (C, D) syntypes of Ennea impervia Melvill & Ponsonby, 1896, 'Natal', length 8.8 and 8.75 mm (NHMUK 1903.3.11.85–86); (E) holotype of Ennea aurisleporis Melvill & Ponsonby, 1898, 'Natal', length 6.65 mm (NHMUK 1903.3.11.69); (F) holotype of Ennea socratica Melvill & Ponsonby, 1893, 'Pietermaritzburg', length 8.45 mm (NHMUK 1903.3.11.78); (G) Gulella menkeana, small inland form, Cumberland, Pietermaritzburg, length 7.2 mm (NMSA V9709); (H) G. menkeana, large form from coastal E. Cape, Port St Johns, length 9.24 mm (NMSA W561); (I) Pupa wahlbergi Krauss, 1848, probable paratype in SMNH, length 10.1 mm (SMNH-Type-2112); (J, K) P. wahlbergi Krauss, 1848, neotype, Durban Bluff, length 9.84 mm, diameter 4.92 mm (NMSA W7942/T2669); (L) holotype of Ennea formosa Melvill & Ponsonby, 1898, Pietermaritzburg, length 7.75 mm (NHMUK 1903.3.11.79).

opencc-by-4.0Dec 2011View details →

Figs 3, 4 in Primary types in the collection of molluscs in the KwaZulu-Natal Museum: Scaphopoda and Cephalopoda

Figs 3, 4. Sepia acuminata, SDUDOHFWRW\SHV 106$: () 2ΟΙ/7474, 4Ϭ.7î2Ι.2 PP>= Sepia hieronis (Robson, 1924)]; (4) 3200/T474, 48.6×21.7 mm.

opencc-by-4.0Dec 2011View details →

Figs 5–8 in Primary types in the collection of molluscs in the KwaZulu-Natal Museum: Scaphopoda and Cephalopoda

Figs 5–8. (5) Sepia confusa, syntype NMSA 3212/T475, 42.2×9.1 mm; (6) S. insignis, syntype NMSA 3210/T476, 18.4×5.8 mm; (7) S. incerta, syntype NMSA 3477/T477, 77.9×13.8 mm; (8) S. incerta, syntype NMSA 3207/T477, 35.1×9.8 mm.

Figure 6 in Recovery of Dermatophagoides pteronyssinus (Acariformes: Astigmata: Pyroglyphidae) is influenced by vacuuming protocol, fabric type and the viability of dust mites

Figure 6 Scanning electron microscope for mites on fabrics: A – Cotton – LM (A1), DM (A2); B – Denim – LM (B1), DM (B2); C – Fleece - LM (C1), DM (C2).

Figure 3 in Recovery of Dermatophagoides pteronyssinus (Acariformes: Astigmata: Pyroglyphidae) is influenced by vacuuming protocol, fabric type and the viability of dust mites

Figure 3 Mean number of LM (Live Mites), DM (Dead Mites) and EM (Euthanized Mites post fabric seeding) recovered according to each treatment applied irrespective of fabric type and duration of vacuuming. ∆ Mean value, and the central line in boxes represents median value of recovered mites.

Figure 5 in Recovery of Dermatophagoides pteronyssinus (Acariformes: Astigmata: Pyroglyphidae) is influenced by vacuuming protocol, fabric type and the viability of dust mites

Figure 5 Scanning Electron Microscope image of the weave structure for fabrics used in this study. A – Cotton; B – Denim; C – Fleece.

Figure 4 in Recovery of Dermatophagoides pteronyssinus (Acariformes: Astigmata: Pyroglyphidae) is influenced by vacuuming protocol, fabric type and the viability of dust mites

Figure 4 Mean number of LM (Live Mites), DM (Dead Mites) and EM (Euthanized Mites post fabric seeding) recovered from each fabric type according to duration of sampling irrespective of fabric type and vacuuming protocol applied. "*", "**" represent values for outliers (observations outside the interquartile range), ∆ Mean value. The central line in boxes represents median value of recovered mites.

Figure 2 in Recovery of Dermatophagoides pteronyssinus (Acariformes: Astigmata: Pyroglyphidae) is influenced by vacuuming protocol, fabric type and the viability of dust mites

Figure 2 Mean number of LM (Live Mites), DM (Dead Mites) and EM (Mites euthanized post fabric seeding) recovered from each fabric type irrespective of the vacuuming protocol used and duration of vacuuming. "*", "**" represent values for outliers (outliers are observations outside the interquartile range), ∆ Mean value, and the central line in boxes represents median of recovered mites.

opencc-zeroMay 2023View details →

dryad40/100

Data and code for: Building use-inspired species distribution models: using multiple data types to examine and improve model performance

Species distribution models (SDMs) are becoming an important tool for marine conservation and management. Yet while there is an increasing diversity and volume of marine biodiversity data for training SDMs, little practical guidance is available on how to leverage distinct data types to build robust models. We explored the effect of different data types on the fit, performance and predictive ability of SDMs by comparing models trained with four data types for a heavily exploited pelagic fish, the blue shark (Prionace glauca), in the Northwest Atlantic: two fishery-dependent (conventional mark-recapture tags, fisheries observer records) and two fishery-independent (satellite-linked electronic tags, pop-up archival tags). We found that all four data types can result in robust models, but differences among spatial predictions highlighted the need to consider ecological realism in model selection and interpretation regardless of data type. Differences among models were primarily attributed to biases in how each data type, and the associated representation of absences, sampled the environment and summarized the resulting species distributions. Outputs from model ensembles and a model trained on all pooled data both proved effective for combining inferences across data types and provided more ecologically realistic predictions than individual models. Our results provide valuable guidance for practitioners developing SDMs. With increasing access to diverse data sources, future work should further develop truly integrative modeling approaches that can explicitly leverage strengths of individual data types while statistically accounting for limitations, such as sampling biases.

opencc-by-4.0Dec 2016View details →

Figure 1 in An additional larval type in the genus Chironomus - the yama-type

Figure 1. Photograph (left) and drawing (right) of the posterior prolegs and anal tubules of a yama-type larva.

Distinct frequencies balance segregation with interaction between different memory types within a prefrontal circuit

2023-05-30 This archive holds the original data used to derive the results reported in the publication: 'Distinct frequencies balance segregation with interaction between different memory types within a prefrontal circuit' Authors: Martina Bracco, Tuomas P. Mutanen, Domenica Veniero, Gregor Thut & Edwin M. Robertson Corresponding Author: Edwin M. Robertson Contact: edwin.robertson@glasgow.ac.uk Please refer to the License for the correct use of the data.  If the use of this data leads to any public dissemination, including (but not restricted to) scientific articles, conference presentations, and posters, please remember to cite the original article. General Description The dataset is shared in BIDS format. To facilitate the upload of files to Zenodo, each subject folder was compressed separately. To ensure a valid bids structure of the dataset, extract the contents of each zip file and place them in the same directory as the other files from the dataset. By doing so, you will have all the necessary files in the correct structure for the BIDS format. Data type: raw TMS-EEG data organized in BIDS format, and epoched ±800 ms around the pulse.            preprocessed motor skill and word recall data organized in BIDS format (.tsv = data file; .json = data description). Key to Filenames: sub = Participant                   ses-preLearning = Session 1 data folder                   ses-postLearnng = Session 2 data folder                   eeg = TMS-EEG data folder                   beh = behaviral data folder Participants: 45 healthy participants (30 females, 23.9±3.6 years; mean ± std)             Groups: Participants were randomly assigned to three different groups with different behavioural conditions:     - In the 'motorSkill'-group, participants performed a sequential motor-skill task followed by a wordlist memory task.          (sub-01 to sub-15)     - In the 'wordRecall'-group,  participants performed a  wordlist memory followed by a sequential task motor-skill task.        (sub-16 to sub-30)     - In the 'control'-group, participants performed a random motor-skill task followed by a wordlist memory task.         (sub-31 to sub-45) TMS-EEG data description Stimulation sites: Right dorsolateral prefrontal cortex (rDLPFC).                     Left primary motor cortex (lM1). Sessions: Session 1: TMS-EEG recordings before the behavioural tasks.           Session 2: TMS-EEG recordings after the behavioural tasks. Number of TMS pulses: 126 pulses delivered to either DLPFC or M1 before, before and after behavioural tasks (a total of 252 pulses for Session 1 and Session 2, each). Inter-Stimulus Interval: 4-6 s (4.9±0.6 s, mean ± std). TMS intensity: 80% of participants' individual motor threshold. TMS machine: Magstim Rapid2, Magstim Company. Coil: figure-of-eight coil (Double 70-mm Alpha Coil). Number of channels: 62-channel EEG channels (AFz and TP9 are used as reference and ground, respectively)                      + 1 FDI EMG channel                 + 1 electrode on the outer canthus of the left eye to monitor eye movements. Sampling rate: 5000 Hz.  Voltage resolution: 0.1 uV. EEG system: TMS-EEG compatible BrainAmp (Brain Products). Noise masking during TMS-EEG recordings: Yes.    Memory tasks data description Motor skill task 'motorSkill'-group (sub-01 to sub-15): TestSerial; averaged response time of the last 50 serial trials immediately after learning.                        TestRandom; averaged response time for the 50 subsequent random trials immediately after learning.                         RetestSerial; averaged response time for the last 50 serial trials 10h after learning.                                        RetestRandom; averaged response time for the 50 subsequent random trials 10h after learning. 'wordRecall'-group (sub-16 to sub-30): TestSerial; averaged response time for the last 50 serial trials immediately after learning.                        TestRandom; averaged response time for the 50 subsequent random trials immediately after learning.       'control'-group (sub-31 to sub-45):    TestRandom; averaged response time of the last 100 random trials at testing.                        RetestRandom; averaged response time of the last 100 random trials 10h after the tasks. Word recall task 'motorSkill'-group (sub-01 to sub-15): Test; number of words recalled immediately after learning. 'wordRecall'-group (sub-16 to sub-30): Test; number of words recalled immediately after learning.                        Retest; number of words recalled 10h after learning.       'control'-group (sub-31 to sub-45):    Test; number of words recalled immediately after learning.

Source data for paper "Mapping disease regulatory circuits at cell-type resolution from single-cell multiomics data"

Sample-paired scRNA-seq and scATAC-seq data collected from human peripheral blood mononuclear cells with Staphylococcus aureus infection. ScATAC-seq data collected from human peripheral blood mononuclear cells with COVID-19 infection.

UEyes: Understanding Visual Saliency across User Interface Types

UEyes is a large eye-tracking-based dataset including 62 participants and 1,980 UI screenshots, covering four major UI types: webpage, desktop UI, mobile UI, and poster.  Please cite the following paper: UEyes: Understanding Visual Saliency across User Interface Types https://dl.acm.org/doi/10.1145/3544548.3581096 Yue Jiang, Luis A. Leiva, Hamed Rezazadegan Tavakoli, Paul R. B. Houssel, Julia Kylmälä, and Antti Oulasvirta. 2023. UEyes: Understanding Visual Saliency across User Interface Types. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23). Association for Computing Machinery, New York, NY, USA, Article 285, 1–21. https://doi.org/10.1145/3544548.3581096

Fig. 5. Data labels. A. Xylocopamoerens Perty, 1833 in The primary types of some species of Centris bees described by European entomologists in the 18 and 20 centuries (Hymenoptera: Apidae)

Fig. 5. Data labels. A. Xylocopamoerens Perty, 1833 (lectotype ♀). B. Xylocopaxanthocnemis Perty, 1833 (lectotype ♂).

Fig. 1. Data labels. A. Centris debilis Dominique, 1898 in The primary types of some species of Centris bees described by European entomologists in the 18 and 20 centuries (Hymenoptera: Apidae)

Fig. 1. Data labels. A. Centris debilis Dominique, 1898 (lectotype ♂). B. Centris dominiquella Dominique, 1898 (lectotype ♀).

Fig 2. Data labels. A. Centris zonalis Dominique, 1898 in The primary types of some species of Centris bees described by European entomologists in the 18 and 20 centuries (Hymenoptera: Apidae)

Fig 2. Data labels. A. Centris zonalis Dominique, 1898 (lectotype ♀). B. Centris lyngbyei Jensen- Haarup, 1908 (lectotype ♂).

Fig. 4. Data labels. A in The primary types of some species of Centris bees described by European entomologists in the 18 and 20 centuries (Hymenoptera: Apidae)

Fig. 4. Data labels. A. Centrisrhodophthalma Pérez, 1911 (lectotype ♀). B. Centristransversa Pérez, 1905 (lectotype ♀).

Alert Type Frequency Assessment of Open-Source Static Analysis Tools and Codebases

This includes all data needed to replicate and validate our frequency analysis of static analysis (SA) alerts produced using open-source SA tools on several OSS codebases. It includes instructions how to get and run the SA tools, a Dockerfile to conveniently get and use the SA tools, raw SA tool output, some python scripts to parse that output, parsed SA data and aggregate analyses, and SA data augmented with CERT coding rule and CWE data.   The SA tools used: <ul> <li>clang-tidy version 15.07   </li> <li>cppcheck version 2.9   </li> <li>CERT Rosecheckers   </li> </ul> The codebases analyzed: <ul> <li>zeek version 5.1.1</li> <li>git version 2.39.0</li> <li>dos2unix version 7.4.3</li> </ul>