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1,488 results for “helping”
Complementary water and nutrient utilization of perianth structural units help maintain long floral lifespan in Dendrobium
<p><span>Most orchids have high ornamental value with long-lived flower. However, the mechanisms by which orchids maintain floral longevity are poorly understood. Here, we hypothesized that long floral longevity in Dendrobium is maintained by high resource investment and complementary water and nutrient utilization in different structural units of the perianth. To test this hypothesis, we determined which water- and nutrient-related traits are correlated with flower longevity in twenty-three Dendrobium species or cultivars and examined the variations of the related traits during flower development of one long-lived cultivar. We found that floral longevity was correlated with dry mas per unit area of perianths and total flower biomass, which indicates that maintaining long floral longevity requires increased resource investment. During development of long-lived flowers, labella showed high capacity for water storage and nutrient reutilization, which can partly remedy high water demand and biomass investment. Sepals and petals, in contrast, had stronger desiccation avoidance and higher metabolic activity with lower biomass investment. These findings indicate that Dendrobium flowers maintain longevity by complementary water and utilization strategies in the sepals, petals and labella, with labella consuming more water and nutrients to extend flower display, while sepals and petals use a more conservative strategy.</span></p>
Identification of Technical Roles of Users to help Recruitment
<p>Response on RQ(3)</p>
The ROMI platform: a helping hand to farming communities
<p><strong>The following video describes the ROMI platform and explains how the set of tools can be adapted to different farming contexts. Funded by EU Grant 773875.</strong></p> <p><em>Videos are available in:</em></p> <ul> <li>Hi-res (1080p Apple ProRes)</li> <li>Mid-res (1080p H265)</li> </ul> <p><strong>Video script:</strong></p> <p>(MINCHIN) ROMI is robotics for micro-farms. It consists of a platform of robotic tools that can be customised, adapted to local situations. So understanding that these tools can be used in different ways is absolutely crucial to the project.<br> <br> (HANAPPE) We try to work on a number of tools that are open hardware, like the cable bot like the rover like the plant imager these are bricks that can be reused in different contexts different types of farms and that gradually what we want to build upon.<br> <br> (MINCHIN) Over four years of development and testing we've developed a platform of tools that can work together and that really goes from the ground-based rover which has got an ability to move around a plant and move to a plant in a field. We have above that a cable system, a cable bot which can be strung in a greenhouse situation or along a polyculture farm such as this one. We are using drones to be able to have an overall vision of the landscape and changes within the environment finally there's a phenotyping robot which is able to scan in detail a plant in a laboratory to help biologists or plant development biologists understand and map growth. These come together in what we're calling the farmers dashboard which allows somebody in situ to understand what they're seeing understand and analyse things which they can't see, and also provide data and data sets back into a laboratory or a computational situation to try and track and understand a complexity in much more depth, than has ever been able to be done before.<br> <br> (BAORI) Agricultural equipment in general you're looking at a hundred thousand pounds hundred thousand euros you name your your kind of uh your range but you're not accessible to someone who's got a very small farm okay so you're looking at a lot of money um the rover at the moment costs approximately seven to eight thousand euros to build. Now as a piece of industrial equipment, agricultural equipment that's that's very very cheap. We do have a very simple web interface that you can run on your phone to connect to the robot to tell it; I want a hoe for the next 25 meters, I want to do weeding. We use a playstation controller actually for just driving the rover around the field and this is something that anybody can learn to use very very quickly. We're kind of targeting somebody with very minimal technical knowledge so although you can build this and if you're a maker you can change the code you can change it to do what you want. We kind of envisage a situation where actually people will just download a complete package put it onto an Arduino, put it onto the raspberry pi. In fact that will install everything and then you're ready to go.<br> <br> (HANAPPE) The rover we intend to be the sort of most practical device, we've specialised it for weeding which is something for which there is a demand today.<br> <br> (OKADA) Our enemies i would say are the weeds as you can see and in summer it's terrible.<br> <br> (MINCHIN) One of the crucial demonstrators of the ROMI project is the weeding tool. Farmers dealing with complexity of a number of crops spend at least twenty percent of their time weeding. When we are able to weed mechanically this means that we don't use herbicides. And so weeding mechanically affords us a more organic way of agriculture and in this way the the weeding tool developed by ROMI is a demonstrator of what could be done to support some of these farmers dealing with a labor-intensive complexity on their farm. but the software the programming and the drivers of that sort of computation don't stop at weeding and we are able to go beyond mechanically into a whole potential of solutions.<br> <br> (HANAPPE) We would like to get them, these tools, in the field as soon as possible so that we can work with farmers and have their feedback but at the same time try to build a community around it, multi-disciplinary of farmers, engineers, researchers to improve these tools, augment their possibilities and then we'll see how far we get.<br> <br> (BESNARD) the ROMI project is interested in getting important information from the plant architecture and from the plant growth process it's very important for a farmer to get this information just to detect very early on if possible any deviations from the normal curves, if you have a pathogen attack for example you just notice very early sign of stress in your plants, and that's generally the pathogen is not like everywhere so it's much easier to to counter attack especially like in organic farming when you know like a lot of chemicals to do it. And at the same time we are developing a tool a technology to get as much information as we can from plant architecture and this has an application towards farmers to just monitor the growth of their crops. But this can have also another application for basic scientists like me just to understand the basic process of our plant built its own architecture which is a basic question.</p>
"The main message is that sustainability would help" – Reflections on takeaway messages of climate change data visualizations.
<p>As part of a larger project investigating expert opinions on public climate change communication and the role of data visualizations1, we conducted semi-structured interviews with 17 experts in the fields of climate change, science communication, or data visualization. We also interviewed six members of the general public with no professional background in either of these areas, who we refer to as lay participants. In the following, lay participants are identified as L-1 to L-6 and expert participants as E-1 to E-17.</p> <p>We used two example visualizations from online news sources (if preferred, translated to German) as a discussion basis and asked participants about the main takeaway message the visualization author wanted to convey. Example visualization 1 was also shown to 17 experts, resulting in a total of 23 formulated takeaway messages. Example visualization 2 was shown to all six lay participants and to seven experts, resulting in a total of 13 messages. For both example visualizations and an overall count of 36 formulated takeaway messages for thematic analysis, we have observed variations in the included contents and the length/abstraction of messages, as well as in the sensemaking process itself among the two participant groups, but also between lay and expert participants. This document provides an overview of those 36 takeaway messages formulated by the study participants.</p>
Genetic impacts on DNA methylation help elucidate regulatory genomic processes
<p><strong>Background</strong>: Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk.</p> <p><strong>Results</strong>: We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2,358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are <em>cis</em>-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1,520 co-localisations across 1,325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as <em>USP1</em> and <em>DOCK7</em> (total cholesterol levels), and <em>ICOSLG</em> (inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying <em>cis</em>-meQTLs, (e.g. through disruption of transcription factor binding sites for CTCF and SMC3), and <em>trans</em>-meQTLs (e.g. through regulating the expression of <em>ACD</em> and <em>SENP7 </em>which can modulate DNA methylation at distal sites).</p> <p><strong>Conclusions</strong>: Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at <a href="https://epicmeqtl.kcl.ac.uk/">https://epicmeqtl.kcl.ac.uk/</a>.</p>
On the Helpfulness of Answering Developer Questions on Discord with Similar Conversations and Posts from the Past
<p>Replication Package for "On the Helpfulness of Answering Developer Questions on Discord with Similar Conversations and Posts from the Past".</p>
FIGURE 4 in A flower in paradise: citizen science helps to discover Thismia paradisiaca (Thismiaceae), a new species from the Chocó Biogeographic region in Colombia
FIGURE 4. Pollen morphology of Thismia paradisiaca; LM (A–D) and SEM (E–H) images. A. pollen grain without fuchsin staining (showing amb circular and thin intectate exine). B–D. Fuchsin-stained pollen grains (showing psilate sculpture and a single simple circular pore). E–F. Pollen grains (showing an amb circular to slightly elliptic, spherical shape and a single pore) H. Dehydrated pollen grains.
FIGURE 1 in A flower in paradise: citizen science helps to discover Thismia paradisiaca (Thismiaceae), a new species from the Chocó Biogeographic region in Colombia
FIGURE 1. Habitat and ecology of Thismia. A. Mountains of the Pacific slope of the Western Cordillera of the Andes. B. Riparian forests of the Danubio Stream. C. Litter accumulated in cavities formed by surface roots above ground. D. Trail towards the Danubio River (arrow indicating the area where the type locality is found). E. Fly (Diptera) recorded in the floral chamber. Photographs by Santiago GuzmánGuzmán (A, B. D and E) and Dairo Utima (C).
FIGURE 2. Thismia paradisiaca. A1. Individual with anthetic flower and immature fruit. A2. Tuber. A3 in A flower in paradise: citizen science helps to discover Thismia paradisiaca (Thismiaceae), a new species from the Chocó Biogeographic region in Colombia
FIGURE 2. Thismia paradisiaca. A1. Individual with anthetic flower and immature fruit. A2. Tuber. A3. Outer surface of hypanthium. B. Flower (3/4 view). C. Flower (top view). D1. Flower with longitudinally dissected hypanthium. D2. Dorsal stamens (inner=abaxial view). E. Stigma (top view). F. Immature fruit (side view). B.C. Corrales Restrepo, S. Guzmán-Guzmán & E. Restrepo 001. Photographs and plate by Eugenio Restrepo.
FIGURE 5. Comparison between Thismia paradisiaca and T. panamensis. A, C. B.C in A flower in paradise: citizen science helps to discover Thismia paradisiaca (Thismiaceae), a new species from the Chocó Biogeographic region in Colombia
FIGURE 5. Comparison between Thismia paradisiaca and T. panamensis. A, C. B.C. Corrales Restrepo et al. 001. E. B.C. Corrales Restrepo et al. 002. B, D, F. Santiago Guzmán-Guzmán 593.A–B. Lateral view of the flower. C–D. 3/4 view of the flower. E–F. Inner view of the flower, showing annulus and stamens. Photographs by Brayan Camilo Restrepo (C), Mauricio Morales (B and D) and Santiago Guzmán-Guzmán (A, E and F).
College Student's Academic Help-Seeking Behavior: A Systematic Review
<p>The CCAT User Guide provides detailed explanations and references for how each category item can be scored.</p>
Replication package for: "Helping Children Catch Up: Early Life Shocks and the PROGRESA Experiment"
<p>Adhvaryu, A., Molina, T., Nyshadham, A., and Tamayo, J. (forthcoming). Helping Children Catch Up: Early Life Shocks and the PROGRESA Experiment. <em>The Economic Journal</em></p>
Can Guided Decomposition Help End-Users Write Larger Block-Based Programs? A Mobile Robot Experiment. (supplementary materials)
<p>Supplementary Material for the research paper "<strong>Can Guided Decomposition Help End-users Write Larger Block-based Programs? a Mobile Robot Experiment</strong>", published at the <em>Conference on Object-oriented Programming, Systems, Languages (OOPSLA 22).</em></p> <p>Paper DOI: <a href="http://doi.org/10.1145/3563296">http://doi.org/10.1145/3563296</a> </p> <p>This archive contains:</p> <ul> <li>An interactive demonstration of the used tutorials and tasks (in the folders tut1-3/ and task1-3/).</li> <li>An interactive playground to test out the presented development environments (onecanvas.html and twocanvas.html in the root folder).</li> <li>The raw data collected throughout the controlled experiment presented in the paper (mobilerobots-data.csv and mobilerobots-data.html)</li> <li>An overview page that allows convenient access to each of the previously described contents.</li> </ul> <p>A non-archival version of the contents is also available here: <a href="https://vcuse.github.io/alvo/first-experiment/">vcuse.github.io/alvo/first-experiment/</a></p> <p><em>Note: The interactive demonstrations work locally. However, several other files and folders contained in the archive are required to run the interactive demonstrations. Deleting or moving any parts of the archive may break the interactive elements. This demo was tested to work as intended on all commonly used web browsers in their most recent versions of 2022. Use at own risk</em></p>
"ChatGPT is here to help, not to replace anybody" - An Evaluation of Students' Opinions On Integrating ChatGPT In CS Courses - Student Survey Raw Data
<p>This dataset contains a CSV file with computer science students' replies to the survey used to evaluate their opinions about the academic and professional usage of ChatGPT as a code generator. It is the raw data that was used to calculate the reply distributions and other details that are presented in the paper.</p> <p>To support international readers, the question names (CSV headers) were translated to English and/or match the numbering that appear in the paper. Most of the data is numeric. However, the student's textual replies to the open ended question were left in their original language, Portuguese.</p>
KOPPeling: Help From Your Own Circle
ClinicalTrials.gov study NCT05829408. IPD Sharing: NO. Countries: 1. Publications: 5.
Testing a New Self-help Intervention for Infertility Related Distress: a Pilot Study
ClinicalTrials.gov study NCT05103982. IPD Sharing: NO. Countries: 1. Publications: 1.
Optimising an Online Self-help Program for Coping With the Loss of a Spouse
ClinicalTrials.gov study NCT05280041. IPD Sharing: NO. Countries: 1. Publications: 12.
Genetic Counseling or Usual Care in Helping Women With Newly Diagnosed Ductal Carcinoma In Situ or Stage I, Stage II, or Stage IIIA Breast Cancer Make Treatment Decisions
ClinicalTrials.gov study NCT00262899. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Web-based Guided Self-help CBT-E vs Online G-CBT-E for Binge Eating Behavior
ClinicalTrials.gov study NCT05873127. IPD Sharing: YES. Countries: 1. Publications: 4.
Can Genetics Predict Treatment Response to a Computerized Self-help Program for Depression?
ClinicalTrials.gov study NCT01818453. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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.