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2,721 results for “CONNECTIVITY”
Figure 3 from: Carvalho-Batista A, Negri M, Pileggi LG, Castilho AL, Costa RC, Mantelatto FL (2014) Inferring population connectivity across the range of distribution of the stiletto shrimp Artemesia longinaris Spence Bate, 1888 (Decapoda, Penaeidae) from DNA barcoding: implications for fishery management. In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 271-288. https://doi.org/10.3897/zookeys.457.6569
Figure 3 - Phylogram for individuals of Artemesia longinaris inferred from Maximum Likelihood analysis of COI gene sequences. Localities represent analyzed specimens. Numbers are bootstrap support values (1000 replicates); values below 50% are not shown.
High genetic diversity but spatially restricted genetic connectivity in a Tropical Montane Cloud Forest tree (Magnolia schiedeana)
Magnolias are representative shrub and tree species of the Tropical Montane Cloud Forest (TMCF) in Mexico, which is one of the most endangered ecosystems due to anthropogenic landscape degradation and climate change. Magnolia schiedeana is a vulnerable and restricted endemic TMCF species, occurring in scattered TMCF fragments in the Sierra Madre Oriental. In this study, we investigated spatial patterns of genetic diversity across the M. schiedeana species range and assessed whether gene flow was influenced by topographic and environmental factors. We sampled eleven remnant populations across the species range and genotyped 180 individuals at eight nuclear microsatellite loci. Our data showed a strong spatial structure in five genetic clusters, which match the patchy geographic distribution of M. schiedeana. Contemporary migration rates between these genetic clusters were very low. Levels of genetic diversity within populations were moderate to high, and no evidence of inbreeding was found. Our results from landscape genetic analysis showed that isolation by distance, rather than topography or environmental variation, was the main process shaping genetic differentiation. Urgent actions are needed to protect M. schiedeana populations as most of them persist isolated within agricultural and urban landscapes. Ex-situ management actions would be crucial to ensure the conservation of genetically diverse germplasm for the in-situ propagation where it has gone locally extinct.
Hydrologic Connectivity Regulates Lacustrine Groundwater Discharge Adjacent to Large Rivers
<p>Supporting Information</p>
Hydrologic Connectivity Regulates Lacustrine Groundwater Discharge Adjacent to Large Rivers
<p>Map data</p>
Text-fig. 16. Scanning electron microscope (SEM) images of "Stamen fragments with in situ Clavatipollenites- or Asteropollis-type pollen" (sp. 1: a–c; sp. 2: d–f; sp. 3: g–i); Catefica locality, Portugal. a) Stamen fragment showing pollen sacs; b) Distal view of pollen grain from (a) showing semitectate-reticulate tectum; c) Detail of pollen wall showing the semitectate-reticulate tectum and long, scattered, columellae supporting muri with fine pits and rounded supratectal ornamentation; note orbiculae with a finely spiny surface (arrows); d) Stamen showing very short filament, lateral pollen sacs and short apical extension of the narrow connective; e) Folded pollen grain from (d) showing semitectate-reticulate tectum; f) Detail of pollen wall from (d) showing the semitectatereticulate tectum and muri with fine rounded ornamentation; g) Stamen fragment; h, i) Detail of pollen grains from (g) showing the semitectate-reticulate tectum with smooth muri, long scattered columellae and tiny scattered orbicules (arrow). Specimens, Catefica 50-S170395 (a–c), Catefica 49-S172561 (d–f), Catefica 50-S170390 (g–i). Scale bars = 600 Μm (a, d, g), 6 Μm (b, e, h), 1.5 Μm (c, f, i). in The Early Cretaceous Mesofossil Flora Of Catefica, Portugal: Angiosperms
Text-fig. 16. Scanning electron microscope (SEM) images of "Stamen fragments with in situ Clavatipollenites- or Asteropollis-type pollen" (sp. 1: a–c; sp. 2: d–f; sp. 3: g–i); Catefica locality, Portugal. a) Stamen fragment showing pollen sacs; b) Distal view of pollen grain from (a) showing semitectate-reticulate tectum; c) Detail of pollen wall showing the semitectate-reticulate tectum and long, scattered, columellae supporting muri with fine pits and rounded supratectal ornamentation; note orbiculae with a finely spiny surface (arrows); d) Stamen showing very short filament, lateral pollen sacs and short apical extension of the narrow connective; e) Folded pollen grain from (d) showing semitectate-reticulate tectum; f) Detail of pollen wall from (d) showing the semitectatereticulate tectum and muri with fine rounded ornamentation; g) Stamen fragment; h, i) Detail of pollen grains from (g) showing the semitectate-reticulate tectum with smooth muri, long scattered columellae and tiny scattered orbicules (arrow). Specimens, Catefica 50-S170395 (a–c), Catefica 49-S172561 (d–f), Catefica 50-S170390 (g–i). Scale bars = 600 Μm (a, d, g), 6 Μm (b, e, h), 1.5 Μm (c, f, i).
Text-fig. 15. Scanning electron microscope (SEM) images of stamen with "Asteropollis-type pollen sp. 2"; Catefica locality, Portugal. a) Stamen with pollen in situ showing the dome-shaped extension of the connective with hairs; b–d) Pollen in situ in stamen in (a) showing poorly defined pentachotomocolpate (b, d) and possibly tetrachotomocolpate (c) apertures and semitectate-reticulate tectum; e) Detail of broken pollen grains showing the loosely attached reticulum, long scattered columellae and thick foot layer. Specimen, Catefica 49-S101209 (a–e). Scale bars = 600 Μm (a), 6 Μm (b–e). in The Early Cretaceous Mesofossil Flora Of Catefica, Portugal: Angiosperms
Text-fig. 15. Scanning electron microscope (SEM) images of stamen with "Asteropollis-type pollen sp. 2"; Catefica locality, Portugal. a) Stamen with pollen in situ showing the dome-shaped extension of the connective with hairs; b–d) Pollen in situ in stamen in (a) showing poorly defined pentachotomocolpate (b, d) and possibly tetrachotomocolpate (c) apertures and semitectate-reticulate tectum; e) Detail of broken pollen grains showing the loosely attached reticulum, long scattered columellae and thick foot layer. Specimen, Catefica 49-S101209 (a–e). Scale bars = 600 Μm (a), 6 Μm (b–e).
Hydrologic Connectivity Regulates Lacustrine Groundwater Discharge Adjacent to Large Rivers
<p>supporting information</p>
Enhancing Mixing During Groundwater Remediation via Engineered Injection-Extraction: The Issue of Connectivity
<p>Output data used to elaborate the main figures in section 6: Results and discussion.</p>
Two connected neurons
SciDraw upload
Two connected neurons
SciDraw upload
EAPBSdata: Energy consumption and bee dataset of five connected beehives of one high season in France
<p><strong>1- Introduction</strong></p> <p>This dataset was developed in the context of our work [1] that focuses on the orchestration of tasks between edge devices and cloud servers, and the energy optimization of orchestration scenarios applied to smart beehives. [1] introduces an energy-aware precision beekeeping system capable of collecting bee-related data and its own energy consumption. This system was deployed during the 2022 beekeeping high season in 5 beehives, 3 of which located in Lyon, France, and the 2 others in Cachan, France.</p> <p><strong>2- Description</strong></p> <p><strong>Hardware</strong></p> <p>The energy-aware precision beekeeping system relies on the Raspberry Pis:</p> <ul> <li>One Raspberry Pi 3b+ that periodically wakes up, collects bee-related data, transfers them and shuts down.</li> <li>One Raspberry Pi Zero WH that constantly collects the energy consumption of itself, the Raspberry Pi 3b+ and the photovoltaic intake.</li> </ul> <p>The energy node of our system relies on a solar panel, current converter, and battery. The solar panel is a monocrystalline 30 W panel. The battery is a 20 000 mAh power bank. Between the two, the current is converted to 5 volts (the adequate voltage for the battery) with a DC/DC Step-Down 5 volts/3 amperes converter.</p> <p>The current sensors connected to the Raspberry Pi Zero are Grove ±5A DC/AC current sensors based on the Allegro ACS70331 current sensor, which is based on giant magneto-resistivity sensing technology. This sensor is selected because of its adapted sensing range (0 to 5 A) and its wide temperature operating range (-40°C to 85°C), as the later-introduced setup operates in a sealed case in an outdoor environment. The current collection script is written in Python 3 and relies on Grove’s package functions.</p> <p><strong>Data collection routines</strong></p> <p>The Raspberry Pi Zero, which records the current, is always switched on. Every twelve minutes (except for beehive 5, where this frequency varies), it sends a signal through GPIO to wake up the other Raspberry Pi, the beehive data recorder. Once the Raspberry Pi 3b+ wakes up, it collects data from all its sensors, including three 10-second audio samples collected at the same time, five 800×600 pixels images spread over five seconds and temperature and humidity measurements of the inside of a beehive, and it transfers the data through Wi-Fi to a remote data storage cloud server. In addition, at regular intervals, the Raspberry Pi Zero WH transfers the latest consumption data.</p> <p>For now, we share the current data and the temperature/humidity. Later, we will share the audio and the image datasets.</p> <p>The date of the beehive data files from beehives 1, 2 and 3 do not match the current data due to the lack of network during the acquisition process. It prevented the Raspberry Pi 3b+ to update its internal clock during wake-up.</p> <p><strong>File Structure:</strong></p> <p>Beehives 1, 2 and 3 are located on the roof of a university (ENS de Lyon) in Lyon, whereas beehives 4 and 5 are located on the roof a university (aivancity Paris-Cachan) in Cachan. Beehives 1 and 4 met technical difficulties which lowered the amount of collected data, whereas beehives 2, 3 and 5 gathered data from April to July 2022</p> <table> <tbody> <tr> <td> <p><strong>Folder</strong></p> </td> <td> <p><strong>Number of files</strong></p> </td> </tr> <tr> <td> <p>beehive1/consumption</p> </td> <td> <p>6</p> </td> </tr> <tr> <td> <p>beehive1/temphumi</p> </td> <td> <p>37</p> </td> </tr> <tr> <td> <p>beehive2/consumption</p> </td> <td> <p>4158</p> </td> </tr> <tr> <td> <p>beehive2/temphumi</p> </td> <td> <p>2598</p> </td> </tr> <tr> <td> <p>beehive3/consumption</p> </td> <td> <p>3503</p> </td> </tr> <tr> <td> <p>beehive3/temphumi</p> </td> <td> <p>3120</p> </td> </tr> <tr> <td> <p>beehive4/consumption</p> </td> <td> <p>182</p> </td> </tr> <tr> <td> <p>beehive4/temphumi</p> </td> <td> <p>261</p> </td> </tr> <tr> <td> <p>beehive5/consumption</p> </td> <td> <p>1915</p> </td> </tr> <tr> <td> <p>beehive5/temphumi</p> </td> <td> <p>1736</p> </td> </tr> </tbody> </table> <p><strong>3- Citation</strong></p> <p>Works citing this dataset should also refer to [1] as the article that introduces the system used to collect the data.</p> <p><strong>4- Acknowledgment </strong></p> <p>The research that led to this dataset was made possible thanks to the funding from aivancity School for Technology, Business & Society Paris Cachan, and the contribution of École Normale Supérieure for the hardware.</p> <p> </p> <p>[1] H. Hadjur, D. Ammar, and L. Lefèvre, “Services Orchestration at the Edge and in the Cloud for Energy-Aware Precision Beekeeping Systems” 5th Workshop on Parallel AI and Systems for the Edge (PAISE 2023), an IPDPS workshop, 2023.</p> <p> </p>
Simulation files for 'Discerning Rise Time Constants: Connecting the Time and Frequency Domain Response of Perovskite Solar Cells'
<p>.parx files for SETFOS simulations and .py file for equivalent circuit simulations</p>
Glycolonitrile TS27 connecting MIN1 and MIN10 of the CRN
<p>DFT-calculated IRCs for TS27 connecting MIN1 and MIN10 of the glyconitrile CRN</p>
Effectiveness of Fluticasone Furoate/ Umeclidinium/ Vilanterol (FF/UMEC/VI) Using the Connected Inhaler System (CIS) as Compared With Fluticasone Proprionate/ Salmeterol (FP/SAL) Plus Tiotropium (TIO)
ClinicalTrials.gov study NCT03376932. IPD Sharing: YES. Countries: 0. Publications: 1.
Connected Prehabilitation Program During Neo Adjuvant Chemotherapy
ClinicalTrials.gov study NCT04451369. IPD Sharing: NO. Countries: 0. Publications: 1.
RADx-UP CDCC Rapid Research Pilot Program "Culturally-relevant Community Connections (C3) to Increase COVID-19 Testing
ClinicalTrials.gov study NCT05918952. IPD Sharing: NO. Countries: 1. Publications: 0.
Efficacy Trial of the FMF Connect Mobile Health Intervention
ClinicalTrials.gov study NCT05028517. IPD Sharing: YES. Countries: 1. Publications: 0.
Effect of Bio-activation on Epithelial and Connective Cell Adhesion to Titanium Abutments: Split Mouth Clinical Trial
ClinicalTrials.gov study NCT07069231. IPD Sharing: UNDECIDED. Countries: 0. Publications: 1.
Connecting Breath and Mind for CYP With Long COVID
ClinicalTrials.gov study NCT05705154. IPD Sharing: NO. Countries: 1. Publications: 0.
Connective Tissue Disease Patients With Pulmonary Hypertension
ClinicalTrials.gov study NCT05980728. IPD Sharing: NO. Countries: 0. Publications: 3.
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.