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267 results for “combat”
List of capacity building resources for combating climate mis/disinformation created by EU-funded projects
<p>This dataset is the result of collaborative work for Deliverable 1.3 (WP1; T1.3) of the AGORA project. It compiles resources from projects funded by the European Commission under the last two Framework Programmes (Horizon 2020 and Horizon Europe) and focused on combating climate change misinformation and disinformation. The resources identified and analysed include training materials, guidelines and interactive digital platforms designed for various target groups.</p>
Land Productivity Dynamics (LPD) maps based on approaches recommended by the United Nations Convention to Combat Desertification (UNCCD) for the Brazilian Semiarid Region (BSR).
<p>Maps of the land productivity dynamic (LPD) based on approaches recommended by the United Nations Convention to Combat Desertification (UNCCD) for the Brazilian Semiarid Region for the period 2001-2015. LPD from Trends.Earth (TE), LPD from the Joint Research Center (JRC-LPD), and LPD from the Food and Agriculture Organization – World Overview of Conservation Approaches and Technologies (FAO-WOCAT LPD). In addition, TE-based LPD with climate correction based on Rain Use Efficiency (RUE), Residual Trend Analysis (RESTREND), and Water Use Efficiency (WUE) calculated using the procedures described in the second version of the Good Practice Guidance for SDG Indicator 15.3.1. The annual LCLU maps from the MapBiomas project at 30 m spatial resolution for 2001 and 2015, and the 16-day MOD13Q1 NDVI dataset from 2001 to 2015 were used as inputs.</p> <p>**********************</p> <p>A total of seven GeoTIFF files in Geographic Tagged Image File Format (GeoTIFF) format are provided at 250 m spatial resolution.</p> <p>Coding for the LPDs.</p> <p>Value Meaning</p> <p>-32768 No data</p> <p>1 Declining</p> <p>2 Moderate decline</p> <p>3 Stressed</p> <p>4 Stable</p> <p>5 Increasing</p> <p>Funding: this study was undertaken as part of the Satellite Desertification Monitoring Program in the Brazilian Semiarid Region [Grant Number 403223/2021-0] supported by the CNPq. It also had the support of Capes, through Notice no. 28/2022 – PDPG Social Vulnerability & Human Rights [Grant Number 88881.705050/2022-01].</p>
Lista de municípios prioritários no combate ao desmatamento na Amazônia e Cerrado (Deforestation priority list of municipalities in the Amazon and Cerrado)
<h4>Português</h4> <p>A Lista Negra do desmatamento, da Amazônia e do Cerrado, é atualizada pelo Diário Oficial da União (DOU), e determina a identificação de municípios com taxas elevadas de desmatamento. Mais detalhes sobre essa política pública podem ser encontrados em <a href="http://dx.doi.org/10.5380/dma.v42i0.53542" target="_blank" rel="noopener">Bizzo et al. (2017)</a>. </p> <p>Os critérios de inclusão de um município na lista da Amazônia são: área total de floresta desmatada; área total de floresta desmatada nos últimos três anos; e aumento da taxa de desmatamento em pelo menos três, dos últimos cinco anos. As consequências da inclusão na lista são: maior monitoramento e fiscalização; não aprovação de créditos para atividade agropecuária; embargo de atividades relacionadas ao desmatamento; aplicação de multas; divulgação de dados do imóvel rural em que ocorreu a infração, e seu titular. Para a remoção da lista, o município deve: Possuir 80% de seu território, em propriedades rurais, monitorado pelo Cadastro Ambiental Rural (CAR); e manter taxa de desmatamento anual abaixo do limite estabelecido em portaria do Ministério do Meio Ambiente.</p> <p>Os critérios de inclusão para os municípios do Cerrado são: média de desmatamento dos últimos dois anos superior a 25 quilômetros quadrados; desmatamento acima de 20% em áreas de vegetação nativa remanescente no município; ou a exploração da madeira em áreas protegidas. Para o Cerrado, não foram estabelecidos critérios para exclusão da lista.</p> <p>A série temporal contendo os municípios que foram incluídos na lista de prioridade e monitoramento para o controle do desmatamento. A série temporal vai de 2008 a 2022. Os dados foram coletados do Diário Oficial da União (DOU), publicado pelo governo brasileiro.</p> <p>A série temporal completa encontra-se no arquivo "priority_list.csv".</p> <h4>English</h4> <p>Time series containing the municipalities that were included in the priority and monitoring list for deforestation control. The time series ranges from 2008 and 2022. The data were gathered from the Diário Oficial da União (DOU), published by the Brazilian government.</p> <p>The complete time series is found in the "priority_list.csv" file.</p>
COMBAT TB Tuberculosis genome annotation database
<p>A Neo4j (version 2.3.3) format graph database containing annotation related to the M. tuberculosis H37Rv genome, created as part of the COMBAT TB project at the South African National Bioinformatics Institute.</p>
Differential Gene Expression Datasets for "Identification of candidate repurposable drugs to combat COVID‑19 using a signature‑based approach"
<p>This dataset has the unfiltered transcriptome differential expression results used in the paper "Identification of candidate repurposable drugs to combat COVID‑19 using a signature‑based approach". </p>
F I G U R E 2 in Female-female aggression in Bactrocera tryoni (Diptera: Tephritidae) and the influence of fruit quality on combat intensity
F I G U R E 2 Mean (±SE) time (in seconds) taken for a female Bactrocera tryoni to perform the first antagonistic behavioural event against a conspecific female when on one of three host fruit types. N = 15 female pairs per fruit type. Columns surmounted by different letters are significantly different at p = 0.05.
F I G U R E 1 in Female-female aggression in Bactrocera tryoni (Diptera: Tephritidae) and the influence of fruit quality on combat intensity
F I G U R E 1 Ethogram of antagonistic behaviours of female Bactrocera tryoni competing for a single host fruit. The size of the behavioural boxes and number within represent the frequency in which the individual behaviours occurred that led to a transitional flow to another behaviour. The number associated with the arrow represents the proportion of transition frequencies made by the females to other behaviours from a given behaviour and will sum to 1. For example, from a total number of observed behavioural events recorded for crabbing, a proportion of 0.381 of all transitions led to further crabbing (after the first crabbing had finished), 0.237 led to supination, 0.130 led to pushing, 0.091 led to tiptoe, 0.083 led to probing, 0.033 led to butting, 0.032 led to retreat and 0.014 led to chasing. The ethogram is based on 45 replicate recordings, each 1 h long of two sexually mature females competing for access to a single fruit resource for oviposition. The ethogram thus represents the combined behaviours of 90 individuals.
F I G U R E 4 in Female-female aggression in Bactrocera tryoni (Diptera: Tephritidae) and the influence of fruit quality on combat intensity
F I G U R E 4 Mean (±1 SE) number of occurrences of aggressive behaviours exhibited by Bactrocera tryoni females on three fruit types: cherry tomato, apple and mango. N = 15 replicate female–female pairs per fruit type. Columns surmounted by different letters are significantly different at p = 0.05.
F I G U R E 3 in Female-female aggression in Bactrocera tryoni (Diptera: Tephritidae) and the influence of fruit quality on combat intensity
F I G U R E 3 Mean (±1 SE) number of antagonistic events carried out by Bactrocera tryoni females against conspecific females when on one of three host fruit types. N = 15 female pairs per fruit type. Columns surmounted by different letters are significantly different at p = 0.05.
An Experimental Test of Lanchester's Models of Combat in the Neotropical Termite Nasutitermes corniger (Blattodea: Termitidae)
<p><span>Lanchester's models of combat have been invoked to explain the mechanics of group fighting in social animals. Specifically, Lanchester's square law posits that the fighting ability of the group is proportional to the square of the number of combatants. Although used to explain a variety of ecological phenomena, the models have not been thoroughly tested. We tested the Lanchester models using group battles between colonies of the termite <em>Nasutitermes corniger</em>. Our main goals were to determine if mortality rates fit the Lanchester models, and if so, whether the behavioural mechanisms underlying a group's success match those used in deriving the model. We initiated battles between pairs of colonies with different ratios of fighters and recorded deaths over time. We found that the numerically larger army has an advantage, but that the advantage is not as pronounced as predicted by Lanchester's square law. We also video-recorded battles to analyse individual behaviour, which did not support the mechanisms invoked by Lanchester. Instead, the killing power of an individual is increased by the presence of nestmates, giving the larger group a disproportionate advantage. Although the behavioural mechanisms leading to the advantage may differ, our results still support some of the proposed ecological phenomena.</span></p>
Fig. 1 in Incorporation of biorational insecticides with neonicotinoids to combat resurgence of Tetranychus urticae (Prostigmata: Tetranychidae) on rose
Fig. 1. Preference and non-preference test for spider mites by pro- viding imidacloprid (IMD)-or acetamiprid (ACT)-treated and untreated rose leaves as 2 choices at different days afer treatment (DAT) and observing the percentage of spider mites reaching a specific choice. Asterisk indicates significant difference between treatment and untreated control (P = 0.05, χ2 goodness of fit).
Combat-TB-NeoDB: fostering Tuberculosis research through integrative analysis using graph database technologies.
<p>NeoDB is a free and open source integrated M.tuberculosis ‘omics’ knowledge-base. NeoDB is based on Neo4j and enables researchers to execute complex federated queries by linking well-known, curated and widely used biological data resources, and supplementary TB variants data from published literature.</p> <p>Documentation can be found at https://combat-tb-db.readthedocs.io</p>
Figure 5 in Assessing a ReviTec Measure to Combat Soil Degradation by studying Acari and Collembola from Ngaoundéré, Adamawa, Cameroon
Figure 5. Temporal variation of total Acari and Collembola in the ReviTec plots (ctrl1: ReviTec control; cpmy: compost + mycorrhiza; cpbcbo: compost + biochar + bokashi). Details as in Fig. 3.
Figure 3 in Assessing a ReviTec Measure to Combat Soil Degradation by studying Acari and Collembola from Ngaoundéré, Adamawa, Cameroon
Figure 3. Temporal variation of total Acari and Collembola in control plots (sav: savanna; ctrl1: ReviTec control plot; tsd. ind./m2, 0–10 cm). Significant differences between 2017 sampling campains are marked by different letters.(n = 5); Asterisk: Difference to sav significant (n = 5, p <0.05). (Kruskal-Wallis test with subsequent Mann-Whitney U-test to test pairs [p ˂ 0.05]). Error bars: standard error.
Reference collection of combat wear traces on replicas of Bronze Age spears
<p>This Dataset comprises a collection of photographs of combat wear traces produced during various experiments focusing on the use of bronze spears in combat experiments as described in the paper <em>Gentile V., van Dijk C.J., ter Mors O., (2024): Multi-stage experiments in Bronze Age spear combat: insights on wear </em><em>formation, trauma, and combat contexts. Journal of Archaeological science (<a href="https://doi.org/10.1016/j.jas.2024.106044">https://doi.org/10.1016/j.jas.2024.106044</a></em><em>).</em> <br><br>Please read the README file for information on how to navigate the dataset. <br><br>This dataset is distributed under CC BY-NC 4.0 license: <a href="https://creativecommons.org/licenses/by-nc/4.0/">https://creativecommons.org/licenses/by-nc/4.0/ </a><br>For other uses, please contact the creator.</p> <p> </p>
An Experimental Test of Lanchester’s Models of Combat in the Neotropical Termite Nasutitermes corniger (Blattodea: Termitidae)
Open the record for dataset details and reuse information.
Nano MOFs as targeted drug delivery agents to combat antibiotic resistant bacterial infections
<p>The drug resistance of bacteria is a significant threat to human civilization while the action of antibiotics against drug-resistant bacteria is severely limited due to the hydrophobic nature of drug molecules, which unquestionably inhibit its permanency for clinical applications. The antibacterial action of nanomaterials offers major modalities to combat drug resistance of bacteria. The current work reports, the use of nano MOFs encapsulating drug molecules to enhance its antibacterial activity against model drug-resistant free living bacteria and biofilm of the bacteria. We have attached rifampicin (RF), a well-documented antituberculosis drug with tremendous pharmacological significance, into the pore surface of zeolitic imidazolate framework 8 (ZIF8) by a <span><span>simple synthetic procedure</span></span><span>.</span> The synthesized ZIF8 has been characterized using X-ray diffraction (XRD) method before and after drug encapsulation. The electron microscopic strategies such as scanning electron microscope (SEM) and transmission electron microscope (TEM) methods was performed to characterize the binding between ZIF8 and RF. We have also performed picosecond resolved fluorescence spectroscopy to validate the formation of the ZIF8-RF nanohybrids (NHs). The drug release profile experiment demonstrates that ZIF8-RF depicts pH-responsive drug delivery and ideal for targeting bacterial disease corresponding to its inherent acidic nature. Most remarkably, ZIF8-RF gives enhanced antibacterial activity against methicillin-resistant <i>S. aureus</i> (MRSA) bacteria and also prompts entire damage of structurally robust bacterial biofilms. Overall, the present study depicts a detailed physical insight for manufactured antibiotic-encapsulated NHs presenting tremendous antimicrobial activity that can be beneficial for manifold practical applications.</p>
Data from: Artificial refuges to combat habitat loss for an endangered marsupial predator: how do they measure up?
<p>One technique used to combat the growing global species extinction crisis has been to create artificial refuges—human-made replacements for natural refuges destroyed during habitat modification. However, there is limited knowledge of how closely artificial refuges replicate the natural refuges they seek to replace. Mining threatens many species worldwide through large-scale habitat modification, and artificial refuges have been proposed as a method to offset the resulting habitat loss. Here, we examined the microclimatic, physical, and biotic characteristics of natural dens occupied by the northern quoll (<i>Dasyurus hallucatus</i>)—an endangered marsupial threatened by habitat loss—and compared these to 1) superficially similar unoccupied crevices, and 2) artificial dens created by mining companies for northern quolls. Northern quolls occupied natural dens that were cooer and deeper than unoccupied crevices, likely to avoid lethal air temperatures as well as predators. Artificial dens provided similar thermal properties to occupied dens, but lacked key characteristics in having shallower den cavities, less complex surrounding habitat, increased feral cat visitation, and less small mammal prey compared to occupied dens. This study highlights the need to consider multiple facets when constructing artificial refuges, in order to avoid perverse outcomes, such as inadequate shelter, increased predation and food shortages.</p>
Monumentos de combate, Las Coimas
El Monumento del Combate de Las Coimas recuerda la victoria de Mariano Necochea y sus tropas sobre las fuerzas realistas en el sector de Las Coimas en Putaendo, un 7 de febrero de 1817. El monumento se construye cerca de 1940 y en el año de 2010 se realiza una mejora en honor a la tercera victoria del Ejército de los Andes en tierras chilenas. http://www.cityp.org/ Source: Objaverse 1.0 / Sketchfab
COMBAT TB Tuberculosis genome annotation database
<p>This is a Neo4j format *M. tuberculosis* reference annotation database. To view it you need a Neo4j (v 2.3) instance. There is a script (<strong>run_db.sh</strong>) that will start a Neo4j instance for you based on this data, using docker. Run that (<strong>bash run_db.sh</strong>) and connect to http://localhost:7474.</p> <p>The database was created by the COMBAT TB project (http://christoffels.sanbi.ac.za/index.php/projects/combat-tb) at the South African National Bioinformatics Institute (SANBI).<br /> <br /> Authors: Thoba Lose, Peter van Heusden, Ziphozakhe Mashologu, Alan Christoffels .</p> <p>The COMBAT TB project is funded by the South African Medical Research Council (MRC) and was supported by the South African<br /> Research Chairs Initiative of the Department of Science and Technology and National Research Foundation of South Africa.</p>
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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.