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830 results for “INDUSTRY”
ORGANIZATION AND IMPROVEMENT OF PAYMENT OF WAGES IN INDUSTRIAL ENTERPRISES IN THE CONDITIONS OF ECONOMIC LIBERALIZATION
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EFFECTIVE USE OF ENERGY RESOURCES AND SAVING THEM IS THE GUARANTEE OF ECONOMIC EFFICIENCY OF INDUSTRIAL ENTERPRISES.
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POHIS-PROCEEDINGS OF OCCUPATIONAL HEALTH AND INDUSTRIAL SAFETY
<h1>POHIS-PROCEEDINGS OF OCCUPATIONAL HEALTH AND INDUSTRIAL SAFETY</h1>
Global remote industrial heat sources dataset
<p>Data content: Based on the VIIRS (Visible Infrared Imaging Radiometer Suite) sensor medium resolution 375mNPP-VIIRS active thermal anomaly data, field research, and other big data of the earth, we constructed the global continental region of high-energy-consuming industrial heat source product data set, totaling 25,544 data. After validation 23232 items are industrial heat source objects, and the recognition accuracy is 90.95%. The output format is shapefile.</p> <p>Time range of data:2012-2021<br> Spatial scope: Global continental area<br> Projection method: WGS84<br> Volume of data: The total volume of data is about 3346kb.<br> Type of data: Vector<br> </p>
Results of visual servoing architecture of mobile manipulators for precise industrial operations on moving objects
<p>Results obtained during the experiment of screw fastening on moving objects using a mobile manipulator.</p>
Impact of Digital Inclusive Finance on Agricultural Total Factor Productivity in Zhejiang Province from the Perspective of Integrated Development of Rural Industries
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DIGITIZING SERVICES: AUTOMATION, AI, AND BLOCKCHAIN'S ROLE IN MODERN SERVICE INDUSTRIES
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APPLICATION OF MARKETING CONCEPTS AT INDUSTRIAL ENTERPRISES: PROBLEMS AND SOLUTIONS
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THE CONCEPT OF HUMAN CAPITAL IN INDUSTRIAL ENTERPRISES AND ITS METHODOLOGICAL FOUNDATIONS
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SOCIO-ECONOMIC MECHANISMS OF USING INTEGRATED MARKETING COMMUNICATIONS AT INDUSTRIAL ENTERPRISES
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Self-regulation in the peruvian mining industry: tackling the challenge of sustainable water management
<p>Ponencia - IV Congreso Latinoamericano de Marketing Social</p>
SOCIO-ECONOMIC MECHANISM OF INCREASING THE EFFICIENCY OF INNOVATION PROCESSES AT INDUSTRIAL ENTERPRISES
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Data of industrial heat source between 2012 and 2021 using long-term Active Fire/Hotspot data in China
<p>Industrial heat sources serve as crucial indicators of energy consumption levels and air pollution. Energy-intensive industries are facing substantial challenges in transforming and upgrading in China. Therefore, accurately identifying industrial heat source locations and monitoring their temporal patterns are becoming utmost importance. In this study, a long-term industrial heat source datasets between 2012 and 2021 in China using long-term Active Fire/Hotspots (ACF) data has been constructed to monitor and analyze large-scale industrial heat sources. Firstly, density segmentation method based on an improved k-means algorithm using long-term ACF data and spatial topological correlation analysis was conducted to build industrial heat sources. Then, 4410 industrial heat sources were obtained between 2012 and 2021 in China, with an identification accuracy of 95.08% by manual verification using high-resolution remote sensing images and point of interest (POI) data. Finally, the trend in the spatio-temporal variation of industrial heat sources was analyzed using long-term series. The results from 2012 to 2021 showed that the spatial distribution of industrial heat sources in China exhibits local aggregation and a gradual shift from east to west.And,the number of industrial heat sources in China has followed a trend of an initial increase from 2012 to 2014, followed by a decrease since 2014, consistent with national energy reform-related policies.The result of this study indicated the temporal variation of industrial heat sources, enhanced the accuracy of fire points category identification, and demonstrated potential for advancing energy efficiency, emission reduction, and sustainable development in China.</p>
Semgrep*: Further Improving Static Application Security Testing (SAST) Tools: An Industry Case-Study
<p>Scripts to download and build data.</p> <p> </p> <p>Yaml files for additional SAST rules.</p>
Appendix_Data_Industrial application of Multi-Robot Partial Destructive Disassembly Line Balancing for Multi-Product Scenarios_v1.docx
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Dataset: First comprehensive assessment of industrial-era land heat uptake from multiple sources
<p><strong>Dataset Overview</strong></p> <p>This Zenodo repository contains a comprehensive dataset of global mean yearly land heat uptake (LHU) estimates for the historical period (all data sources) and the SSP585 scenario (exclusively for CMIP6 models). The dataset includes estimates from multiple data sources: gridded observations (OBS, 5 sources), reanalyses (REA, 7 sources), and CMIP6 simulations (CMIP6, 37 models). These LHU estimates were developed and first analyzed in <a href="https://doi.org/10.5194/esd-15-547-2024" target="_blank" rel="noopener">García-Pereira et al. (2024)</a>.</p> <p>The estimates were obtained using the one-dimensional heat conduction forward model (ConForM; <a href="https://doi.org/10.5281/zenodo.10371439" target="_blank" rel="noopener">García-Pereira et al., 2023</a>), forced with yearly global mean ground surface temperature data from each source over various time periods. The time periods include the full available range (fromINIT), as well as specific periods starting in 1950, 1960, and 1971, extending to the most recent data available. For a detailed explanation of the methods, rationale, main findings, and comparisons with previous geothermal LHU estimates, refer to <a href="https://doi.org/10.5194/esd-15-547-2024" target="_blank" rel="noopener">García-Pereira et al. (2024)</a>.</p> <p><br><strong>Dataset Contents</strong></p> <p>The dataset is provided in NetCDF format and is organized by data source type (OBS, REA, CMIP6) and time period (fromINIT, from1950, from1960, from1971). Each file follows the naming convention:</p> <blockquote> <p><em><source_type>_LHU_ym_gb_sum_<period>.nc</em></p> </blockquote> <p>where <em><source_type></em> indicates the data source (OBS, REA, CMIP6) and <em><period></em> specifies the starting time (fromINIT, from1950, from1960, from1971). For example, <em>OBS_LHU_ym_gb_sum_from1971.nc</em> contains LHU estimates derived from observational data starting in 1971. For files corresponding to from1950, from1960, and from1971, the dataset also includes mean and standard deviation calculations. Additionally, raw LHU estimates derived from CMIP6 subsurface temperature data are provided in the file <em>CMIP6/CMIP6raw_LHU_ym_gb_sum.nc</em>.</p> <p><br><strong>Citation instructions</strong></p> <p>If you use this dataset, please cite the following references:</p> <blockquote> <p>Garcia-Pereira, F. and González-Rouco, J. F. : "ConForM: a one-dimensional heat Conduction Forward Model", Zenodo, <a href="https://doi.org/10.5281/zenodo.10371439" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10371439</a>, 2023.</p> <p>García-Pereira, F., González-Rouco, J. F., Melo-Aguilar, C., Steinert, N. J., García-Bustamante, E., de Vrese, P., Jungclaus, J., Lorenz, S., Hagemann, S., Cuesta-Valero, F. J., García-García, A., and Beltrami, H.: "First comprehensive assessment of industrial-era land heat uptake from multiple sources", Earth Syst. Dynam., 15, 547–564, <a href="https://doi.org/10.5194/esd-15-547-2024" target="_blank" rel="noopener">https://doi.org/10.5194/esd-15-547-2024</a>, 2024.</p> </blockquote> <p><br><strong>Additional Resources</strong></p> <p>For further insight into the evolution of LHU, its role in terrestrial energy partitioning, and the limitations of state-of-the-art Earth System Models in representing it, we recommend exploring these additional publications:</p> <blockquote> <p>Cuesta-Valero, F. J., García-García, A., Beltrami, H., Smerdon J. E.: "First assessment of continental energy storage in CMIP5 simulations", Geophys. Res. Lett., 43, 5326–5335, <a href="https://doi.org/10.1002/2016GL068496" target="_blank" rel="noopener">https://doi.org/10.1002/2016GL068496</a>, 2016.</p> <p>Cuesta-Valero, F. J., García-García, A., Beltrami, H., González-Rouco, J. F., and García-Bustamante, E.: "Long-term global ground heat flux and continental heat storage from geothermal data", Clim. Past, 17, 451–468, <a href="https://doi.org/10.5194/cp-17-451-2021" target="_blank" rel="noopener">https://doi.org/10.5194/cp-17-451-2021</a>, 2021.</p> <p>Cuesta-Valero, F. J., Beltrami, H., García-García, A., Krinner, G., Langer, M., MacDougall, A. H., Nitzbon, J., Peng, J., von Schuckmann, K., Seneviratne, S. I., Thiery, W., Vanderkelen, I., and Wu, T.: "Continental heat storage: contributions from the ground, inland waters, and permafrost thawing", Earth Syst. Dynam., 14, 609–627, <a href="https://doi.org/10.5194/esd-14-609-2023" target="_blank" rel="noopener">https://doi.org/10.5194/esd-14-609-2023</a>, 2023.</p> <p>González-Rouco, J. F., Steinert, N. J., García-Bustamante, E., Hagemann, S., de Vrese, P., Jungclaus, J. H., Lorenz, S. J., Melo-Aguilar, C., García-Pereira, F., and Navarro, J.: "Increasing the depth of a Land Surface Model. Part I: Impacts on the soil thermal regime and energy storage", Journal of Hydrometeorology, 22(12), 3211-3230, <a href="https://doi.org/10.1175/JHM-D-21-0024.1" target="_blank" rel="noopener">https://doi.org/10.1175/JHM-D-21-0024.1</a>, 2021.</p> <p>Steinert N. J., González-Rouco, J. F., Melo Aguilar, C. A., García Pereira, F., García-Bustamante, E., de Vrese, P. Alexeev, V., Jungclaus, J. H., Lorenz, S. J., and Hagemann, S.: "Agreement of analytical and simulation-based estimates of the required land depth in climate models", Geophysical Research Letters, 48, e2021GL094273, <a href="https://doi.org/10.1029/2021GL094273" target="_blank" rel="noopener">https://doi.org/10.1029/2021GL094273</a>, 2021.</p> <p>Steinert, N. J., Cuesta-Valero, F. J., García-Pereira, F., de Vrese, P., Melo Aguilar, C. A., García-Bustamante, E., Jungclaus, J., González-Rouco, J. F.: "Underestimated land heat uptake alters the global energy distribution in CMIP6 climate models", Geophysical Research Letters, 51, e2023GL107613, <a href="https://doi.org/10.1029/2023GL107613" target="_blank" rel="noopener">https://doi.org/10.1029/2023GL107613</a>, 2024.</p> <p>von Schuckmann, K., Minière, A., Gues, F., Cuesta-Valero, F. J., Kirchengast, G., Adusumilli, S., Straneo, F., Ablain, M., Allan, R. P., Barker, P. M., Beltrami, H., Blazquez, A., Boyer, T., Cheng, L., Church, J., Desbruyeres, D., Dolman, H., Domingues, C. M., García-García, A., Giglio, D., Gilson, J. E., Gorfer, M., Haimberger, L., Hakuba, M. Z., Hendricks, S., Hosoda, S., Johnson, G. C., Killick, R., King, B., Kolodziejczyk, N., Korosov, A., Krinner, G., Kuusela, M., Landerer, F. W., Langer, M., Lavergne, T., Lawrence, I., Li, Y., Lyman, J., Marti, F., Marzeion, B., Mayer, M., MacDougall, A. H., McDougall, T., Monselesan, D. P., Nitzbon, J., Otosaka, I., Peng, J., Purkey, S., Roemmich, D., Sato, K., Sato, K., Savita, A., Schweiger, A., Shepherd, A., Seneviratne, S. I., Simons, L., Slater, D. A., Slater, T., Steiner, A. K., Suga, T., Szekely, T., Thiery, W., Timmermans, M.-L., Vanderkelen, I., Wjiffels, S. E., Wu, T., and Zemp, M.: "Heat stored in the Earth system 1960–2020: where does the energy go?", Earth Syst. Sci. Data, 15, 1675–1709, <a href="https://doi.org/10.5194/essd-15-1675-2023" target="_blank" rel="noopener">https://doi.org/10.5194/essd-15-1675-2023</a>, 2023.</p> </blockquote>
The industrial solvent 1,4-Dioxane causes hyperalgesia by targeting capsaicin receptor TRPV1
<p><strong>Background</strong>: The synthetic chemical 1,4-dioxane is used as industrial solvent, food and care product additive. 1,4-Dioxane has been noted to influence the nervous system in long-term animal experiments and in humans, but the molecular mechanisms underlying its effects on animals were not previously known.</p> <p><strong>Results:</strong> Here, we report that 1,4-dioxane potentiates the capsaicin-sensitive transient receptor potential (TRP) channel TRPV1, thereby causing hyperalgesia in mouse model. This effect was abolished by CRISPR/Cas9-mediated genetic deletion of TRPV1 in sensory neurons, but enhanced under inflammatory conditions. 1,4-Dioxane lowered the temperature threshold for TRPV1 thermal activation and potentiated the channel sensitivity to agonistic stimuli. 1,3-dioxane and tetrahydrofuran which are structurally related to 1,4-dioxane also potentiated TRPV1 activation. The residue M572 in the S4-S5 linker region of TRPV1 was found to be crucial for direct activation of the channel by 1,4-dioxane and its analogues. A single residue mutation M572V abrogated the 1,4-dioxane-evoked currents while largely preserving the capsaicin responses. Our results further demonstrate that this residue exerts a gating effect through hydrophobic interactions and support the existence of discrete domains for multimodal gating of TRPV1 channel.</p> <p><strong>Conclusions</strong>: Our results suggest TRPV1 is a co-receptor for 1,4-dioxane, and that this accounts for its ability to dysregulate body nociceptive sensation.</p>
Supplementary Material: Predictive model using Cross Industry Standard Process for Data Mining
<p>The Supplementary Material of the paper "Supplementary Material: Predictive model using Cross Industry Standard Process for Data Mining" includes: <br> 1) APPENDIX 1: SQL Statements for data extraction. Appendix 2: Interview for operating Staff.<br> 2) The DataSet of the normalized data to define the predictive model.</p>
Data from: A critical evaluation of the volume, relevance and quality of evidence submitted by the tobacco industry to oppose standardised packaging of tobacco products
Objectives: To examine the volume, relevance and quality of transnational tobacco corporations' (TTCs) evidence that standardised packaging of tobacco products 'won't work', following the UK government's decision to 'wait and see' until further evidence is available. Design Content analysis. Setting: We analysed the evidence cited in submissions by the UK's four largest TTCs to the UK Department of Health consultation on standardised packaging in 2012. Outcome measures: The volume, relevance (subject matter) and quality (as measured by independence from industry and peer-review) of evidence cited by TTCs was compared with evidence from a systematic review of standardised packaging . Fisher's exact test was used to assess differences in the quality of TTC and systematic review evidence. 100% of the data were second-coded to validate the findings: 94.7% intercoder reliability; all differences were resolved. Results: 77/143 pieces of TTC-cited evidence were used to promote their claim that standardised packaging 'won't work'. Of these, just 17/77 addressed standardised packaging: 14 were industry connected and none were published in peer-reviewed journals. Comparison of TTC and systematic review evidence on standardised packaging showed that the industry evidence was of significantly lower quality in terms of tobacco industry connections and peer-review (p<0.0001). The most relevant TTC evidence (on standardised packaging or packaging generally, n=26) was of significantly lower quality (p<0.0001) than the least relevant (on other topics, n=51). Across the dataset, TTC-connected evidence was significantly less likely to be published in a peer-reviewed journal (p=0.0045). Conclusions: With few exceptions, evidence cited by TTCs to promote their claim that standardised packaging 'won't work' lacks either policy relevance or key indicators of quality. Policymakers could use these three criteria—subject matter, independence and peer-review status—to critically assess evidence submitted to them by corporate interests via Better Regulation processes.
Demos of attacks against industrial robots
<p>Demos of attacks against industrial robots.</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.