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How can artificial intelligence such as ChatGPT and Big Data Analytics be used to analyse the level of innovation of new economic projects that new startups that are planning to develop implementing innovative business solutions, technological innovations, environmental innovations, energy innovations and other types of innovations?
The economic development of a country is determined by a number of factors, which include the level of innovativeness of economic processes, the creation of new technological solutions in research and development centres, research institutes, laboratories of universities and business entities and their implementation into the economic processes of companies and enterprises. In the modern economy, the level of innovativeness of the economy is also shaped by the effectiveness of innovation policy, which influences the formation of innovative startups and their effective development. The economic activity of innovative startups generates a high investment risk and for the institution financing the development of startups this generates a high credit risk. As a result, many banks do not finance business ventures led by innovative startups. As part of the development of systemic financing programmes for the development of start-ups from national public funds or international innovation support funds, financial grants are organised, which can be provided as non-refundable financial assistance if a startup successfully develops certain business ventures according to the original plan entered in the application for external funding. Non-refundable grant programmes can thus activate the development of innovative business ventures carried out in specific areas, sectors and industries of the economy, including, for example, innovative green business ventures that pursue sustainable development goals and are part of green economy transformation trends. Institutions distributing non-returnable financial grants should constantly improve their systems of analysing the level of innovativeness of business ventures planned to be implemented by startups described in applications for funding as innovative. As part of improving systems for verifying the level of innovativeness of business ventures and the fulfilment of specific set goals, e.g. sustainable development goals, green economy transformation goals, etc., new Industry 4.0 technologies implemented in Business Intelligence analytical platforms can be used. Within the framework of Industry 4.0 technologies, which can be used to improve systems for verifying the level of innovativeness of business ventures, machine learning, deep learning, artificial intelligence (including e.g. ChatGPT), Business Intelligence analytical platforms with implemented Big Data Analytics, cloud computing, multi-criteria simulation models, etc., can be used. In view of the above, in the situation of having at one's disposal appropriate IT equipment, including computers equipped with new generation processors characterised by high computing power, it is possible to use artificial intelligence, e.g. ChatGPT and Big Data Analytics and other Industry 4.0 technologies to analyse the level of innovativeness of new economic projects that plan to develop new start-ups implementing innovative business solutions, technological, ecological, energy and other types of innovations.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
How can artificial intelligence such as ChatGPT and Big Data Analytics be used to analyse the level of innovation of new economic projects that plan to develop new startups implementing innovative business solutions, technological innovations, ecological innovations, energy innovations and other types of innovations?
What do you think?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Thank you very much,
Warm regards,
Dariusz Prokopowicz
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Enhancements to Tableau for Slack focuses on sharing, search and insights with automated workflows for tools like Accelerator. The goal: empower decision makers and CRM teams to put big data to work...
The changes also presage what’s coming next: integration of recently announced generative AI model Einstein GPT, the fruit of Salesforce’s collaboration with ChatGPT maker OpenAI, with natural language-enabled interfaces to make wrangling big data a low-code/no-code operation...
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Currently, I try to visualize knowledge about sustainable behaviour. I.e., I'd like to construct diagrams showing (primary causal) argumentations about why certain behaviours are (un-)sustainable. It would be an aim, to visualize the consequences of our actions and their environmental and societal impacts and to encourage discussions about the underlying argumentations, based on these visual representations. Ideally, such diagrams could be developed cooperatively.
Does anyone know about related work?
Does anyone even know about the existence of such "sustainability knowledge modelling languages"?
(Or do you think, the idea to visualize such sustainability-knowledge would be unproductive?)
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The Club of Rome essentially did what you are asking for in its 1972 publication, "The Limits to Growth", by modelling a number of different scenarios. The results only of these scenarios were shown in a series of graphs, but not the underlying structure of the models. However, the structure of these models and subsequent models can be viewed and run using dynamic simulation software. One free software package is Vensim PLE. When using Vensim PLE (and other similar software) a conceptual model is first developed graphically using symbols for stocks, flows, and linkages. The direction of influence (positive and negative feedbacks) are then added. Quantification of influence is established by using equations and the model is then validated by comparing simulations against historical data and making necessary adjustments to the model. The validated model can then be used to create different scenarios by using slide controls to change the values of various parameters in the model. I recommend John Sterman's book "Business Dynamics: Systems Thinking and Modeling for a Complex World".
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 Environmental degradation and atmospheric pollution is one of problems of the world over. There have been increased cry about climate change, global warming kept on threatening yet, natural resources like forest that regulates an appealing atmosphere is being cut down. Industries are growing and making use of natural resources without properly accounting for them.
The world at large has need to evaluate, assess and effect accounting reporting for raw materials, energy consumption and use of natural resources which have gradually depleted the environment. 
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El marco metodológico más importante hasta la fecha para aordar estos problemas es es el MAE, la dirección es la siguiente:
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I am just scanning some zooplankton images from a recent expedition to Sognefjord, Norway. The images were taken with the LOKI system, a high-resolution, in-situ optical plankton sampling device (link below). 
On several images I find copepods, which obviously carry ebibionts. Examples can be seen on the attached images. For each image environmental data are available...
So far i just had a first look at the data. But these (probably) epibionts appear a little too often to be artifacts.Could this be someone like Vorticella? Haven't seen such things on copepods that often.
My first impression is, that these images are more common closely behind the sill and at greater depth (below the freshwater influenced surface) -> in the stagnant higher saline waters behind the sill. But that is a very first guess...
So far, i found these 'epibionts' on copepods only; neither on ostracods, nor mysids... Samples were taken in October 2014 and during daytime only.
Is there someone who could give me a hint or some literature?
Best regards and thanks
Environmental information:
20141020 153412 772-> Depth: 294.2 m, Sal: 34.7, Temp: 7.45°C, OxySat: 67.0%
20141020 153700 517-> Depth: 202.4 m, Sal: 34.6, Temp: 7.51°C, OxySat: 69.3%
20141021 073935 824-> Depth: 183.2 m, Sal: 34.6, Temp: 7.62°C, OxySat: 72.8%
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Dear Jan, I cannot tell much about your pictures of epibionts (low resolution and too high contrast); however, it seems obvious to me the "epibionts" Levent showed are actually parasitic protists. They are well described for marine systems in the paper of Skovgaard and Saiz 2007 I attach. 
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Recently, I used the CMIP 5 datas download from the website( And I want to draw a plot like the one below, but I didn't how to draw it. So, I need some helps. 
Thank you very much!
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you'll find detailed information in the manual(s)/tutorials in R/ggplot. is really worth the effort!
below is only a very rough and non-comprehensive sketch...just to show the plot functionality (i didn't reproduce the data from your example but just took the rawdata from
code (assuming that the files are in current R working directory):
# load the data tables into variables
tmp <- read.table("global_tas_Amon_CCSM4_rcp26_r4i1p1.dat")
tmp2 <- read.table("global_tas_Amon_CCSM4_rcp45_r4i1p1.dat")
tmp3 <- read.table("global_tas_Amon_CCSM4_rcp60_r4i1p1.dat")
# load library for plotting (assuming it is already install - if not see next comment for install command)
#install.packages("ggplot2",dependencies = TRUE)
#create a file tmp.png in the working directory, open a "plot environment" (so, everything that is plotted now will go into the file tmp.png)
#create a variable tmp.plot with plotting instructions
tmp.plot <- ggplot(tmp, aes(V1,V2)) + # rcp26 data
geom_line(col = "green") + geom_smooth() +
geom_line(aes(tmp2$V1,tmp2$V3),col = "red") + # rcp45 data
geom_smooth(aes(tmp2$V1,tmp2$V3)) +
geom_line(aes(tmp3$V1,tmp3$V3),col = "yellow") + # rcp60 data
#close plotting environment and close file
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My research led me to conclude that environmental information is useful for decision making but it is not presented in a way unifome in the financial reports of listed companies. I want to study the rules of presentation of environmental information in financial reports and see the main types of information that are broadcast environnemtales. Where can I find documentation about this?
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There are some experiencies of regulation of environmental issues in financial reports as Spain. You can find more info (in Spanish) via Google writing "Resolucion ICAC 2002 medio ambiente". Also the European Union has a recommendation about this (in the European languagues, like English and French). Write on Google "Commission issues Recommendation on environmental issues in companies' annual accounts and reports".