Maps - Science topic

The following links could help you:

Making Maps with R

https://bookdown.org/nicohahn/making_maps_with_r5/docs/introduction.html

3 ggplot2

https://bookdown.org/nicohahn/making_maps_with_r5/docs/ggplot2.html

Plotting points in map (long and lat) ggplot2

https://stackoverflow.com/questions/72268477/plotting-points-in-map-long-and-lat-ggplot2

Making maps in GGplot

https://rpubs.com/Luke_Brokensha/1096218

After life is the continuation of this world. Grasp today,and reap the fruits of life.

With one year of image data on NO2 and aerosols, you can produce much more specific statistics than just an average yearly value per pixel.

What about P99, P95 percentiles? I figger your imagery must contain different strata, hence produce percentiles for these strata, and you will learn much more about pollution behavior than just with a yearly average value. Instead of using Matplotlib, it is better to use ENVI and Statistica combined to do the job.

#Justsaying

Hello Madhushree,

I would recommend to discuss this issue in the FSL mailing list. Looks like an installation problem, but I can't really help here.

Best,

Martin

Openrouteservice.org

One way to go about this is using ArGIS online platform—if your institution is subscribed with ESRI then you can use the map viewer tool. Or another way is to use python geospatial packages to do so. I hope this helps

Navigating the landscape of sustainability frameworks and initiatives can indeed be complex, but here's a breakdown of the relationships between TNFD, TNFD-LEAP, SBTi, and SBTs for Nature, along with some advice on how to use them in business performance for the transportation sector:

By understanding the relationships between TNFD, TNFD-LEAP, SBTi, and SBTs for Nature, and applying these insights to your business performance strategies, you can effectively navigate the sustainability landscape and drive positive environmental and financial outcomes in the transportation sector.

Have you tried this: https://www.protectedplanet.net/en/thematic-areas/wdpa?tab=WDPA ?

Hi..you can for show map zoning risk areas drought in useing arc map ..classify and show prone areas with red color..in 4 classify or 6.

Can you use Network Analyst option in ArcGIS?

Yeas, it can be found an archive of synoptic solar maps by Patrick McIntosh

Transmitting the SHA-256 function output without any additional transmission involves sending the result along with the data it's derived from in a single transmission. This can be achieved by including the SHA-256 hash along with the original data. Here's how you can do it:

Here's a simple example in Python:

pythonCopy codeimport hashlib def transmit_data_with_hash(data): # Calculate the SHA-256 hash of the data hash_value = hashlib.sha256(data.encode()).hexdigest() # Transmit data and hash together transmitted_data = data + hash_value # Return the transmitted data return transmitted_data def verify_transmitted_data(transmitted_data): # Separate the data and hash data = transmitted_data[:-64] # Assuming SHA-256 hash length is 64 characters transmitted_hash = transmitted_data[-64:] # Recompute the hash of the received data computed_hash = hashlib.sha256(data.encode()).hexdigest() # Compare computed hash with transmitted hash if computed_hash == transmitted_hash: return "Data integrity verified. No alterations detected." else: return "Data integrity verification failed. Possible alterations detected." # Example usage original_data = "Hello, world!" transmitted_data = transmit_data_with_hash(original_data) print("Transmitted data with hash:", transmitted_data) # Simulating transmission... # Upon receiving transmitted_data, recipient verifies it verification_result = verify_transmitted_data(transmitted_data) print(verification_result)

This code demonstrates how to transmit data along with its SHA-256 hash and verify data integrity upon reception. Remember to adjust the code as needed for your specific use case and programming environment.

Dear Prof. Fayad!

I see the value in your work. I am not certain whether you aim at undergraduate, master's, or MBA-level practical courses. In any case, "project-based software engineering capstone" - approach is an option to consider:

Saara Tenhunen, Tomi Männistö, Matti Luukkainen, Petri Ihantola,

A systematic literature review of capstone courses in software engineering,

2023, https://doi.org/10.1016/j.infsof.2023.107191, Open access:

Yours sincerely, Bulcsu Szekely

I do not know what that map is attempting to portray ( or analyze ). To make something similar, the steps are very basic.

In Data View:

1. Download some shapefiles for the appropriate jurisdictional areas - maybe villages, but that example map doesn't match up with the official village boundaries ( those can change overtime ). Maybe shapefiles for the other higher level jurisdictions up to the national boundary if you want some sort of context map inset, or for filtering the village dataset.

2. Select the village polygons you need and export from that layer to a new layer.

3. Generate the polygons centroids of the new layer to get the node points.

4. Create a new empty polyline layer. Use the Edit tools to 'connect the dots' between the nodes you want connected.

Switch to Layout View:

5. Adjust the symbology of the layers to suit.

6. place and size your data

7. Add whatever annotations, markup, notes, scales etc. needed.

This does not give you a 'road network' map. It merely approximates the technique sued to make the example map.

That figure looks like an origin-destination analysis. Here is the relevant ArcGIS Pro online documentation: https://pro.arcgis.com/en/pro-app/3.1/tool-reference/analysis/generate-origin-destination-links.htm Good luck!

Dear Aleksandr Kirsanov Please do well to recommend my answer if helpful.

Maps depicting the distribution of solid minerals on the Arctic shelf can be obtained from various sources, including government agencies, research institutions, and international organizations. Here are some places where you might find such maps:

1. **Geological Surveys and Government Agencies:**

- Check the geological surveys or natural resources departments of Arctic countries. These agencies often conduct surveys and may provide maps of solid minerals on the Arctic shelf.

- Examples include the United States Geological Survey (USGS), Geological Survey of Canada, Geological Survey of Norway, and similar institutions in other Arctic nations.

2. **International Organizations:**

- Organizations like the Arctic Council or the International Seabed Authority may provide resources or links to maps related to the Arctic region's solid minerals.

3. **Research Institutions and Universities:**

- Academic institutions conducting research on Arctic geology or marine resources may have maps or datasets related to solid minerals. Explore the websites of universities with expertise in Arctic studies.

4. **Online Databases and Platforms:**

- Explore online databases that focus on geological and mineral resources, such as the World Data Center for Marine Environmental Sciences (WDC-MARE) or the International Geological Map Index (IGMI).

- GIS (Geographic Information System) platforms like ArcGIS Online might host relevant maps or datasets. Institutions using GIS for Arctic studies may share their findings through such platforms.

5. **Arctic Research Reports and Publications:**

- Scientific journals, research reports, and publications related to Arctic geology and mineral resources may include maps. Search for articles or reports from reputable sources.

6. **Government Geological Websites:**

- Visit the geological websites of Arctic nations and look for sections on offshore or marine resources. They might provide access to maps and data related to solid minerals.

7. **Library Resources:**

- Check with university or national libraries, especially those with strong Earth Sciences collections. Librarians may guide you to relevant publications or maps.

Remember that access to certain maps or data may be restricted due to national security, proprietary information, or environmental sensitivity. It's advisable to comply with any usage terms or permissions associated with the data you seek. If you have a specific country or region in mind, narrowing down your search to that particular area may also be helpful.

Hello,

Toward this spatial representation, ArcMap software would be an option. Compile country-specific data in an Excel file, then add it to the attribute table associated with the world map of countries. ArcMap offers you diverse spatial mapping patterns.

There could be several reasons why you're encountering difficulties calculating the K/eTh ratio or F-parameter in your gamma-ray spectrometry data for K-enrichment delineation. Here are some possibilities to explore:

By systematically investigating these potential causes and seeking additional resources, you should be able to identify the source of your problem and successfully calculate the K/eTh ratio or F-parameter for your K-enrichment delineation project.

you can use NAMD energy.

ResearchGate Link:

(PDF) Improving Lean engagement through utilising improved communication, recognition and digitalisation during the COVID-19 pandemic in JLR's powertrain machining facility (researchgate.net)

You can use the following sites:

(https://viewer.nationalmap.gov/)

(https://worldview.earthdata.nasa.gov/)

(https://www.ncei.noaa.gov/)

(https://www.loc.gov/maps/)

Hi,

Do you mean A map removal sensitivity analysis? I have done this in the paper below:

Taghavi, N., Niven, R. K., Kramer, M. & Paull, D. J. (2023). Comparison of DRASTIC and DRASTICL groundwater vulnerability assessments of the Burdekin Basin, Queensland, Australia. Science of The Total Environment, 159945. DOI: https://doi.org/10.1016/j.scitotenv.2022.159945.

I'm happy to help.

In VOSviewer, save the map and the network files. Open the saved map file with Notepad++. Select the entire text and under the Edit menu, navigate to Convert Case to Proper Case. Go back to VOSviewer, and open the map file. You will realize the terms in the map will have their initials capitalized.@Abhishek Kumar.

See "A researcher has wrongly claimed co-authorship of my publication" in https://help.researchgate.net/hc/en-us/articles/14292798510993 for instructions how to correct this. But unlike this help page suggests, most probably it was not the other author himself who wrongly claimed authorship, but ResearchGate's automatic algorithm wrongly identified him as the author and assigned your publication to his profile. This is a frequent problem in ResearchGate in case of similar names.

Do you mean determining rainfall patterns?

Thanks, don't know what I was thinking.

Hello Mr.Jaiswal, i think the issue is the version of Qgis that you are using. Since, Molusce is not updated in quite recent years it is only compaitable with versions lesser than QGis 3.0. I hope you might have figured this by now as you have asked question long back.

Michael John Patrick As I understand, main philosophy of Inforgram are interactivity. But I found a print button with selection of high quality PNG, JPG, PDF, GIF and MP4. Unfortunately, all printing options are available only after payment. Only "print screen" save us :-)

Hi Cédric, thanks for sharing us the link. Could you please send me a link that indicates the descriptions of each class in the agroecological zones.

When using the MAP Solution function in ABAQUS for Mesh-to-Mesh solution Mapping (MSM) during the penetration analysis of a rigid pile into soil, it seems that the function is unable to accurately map normal contact stresses between the old and new meshes when two bodies are in contact. This can lead to underestimated reactions and results that resemble a wish-in-place condition.

Additionally, you can make use of this comprehensive soil simulation tutorial:

Hi,

on top of the mentioned suggestions, if you can get historical images from Landsat, orthophoto... that can help to reconstruct DEM. You can use Land evolution models (LEM) to analyze the morphological change, or simply check the Difference of DEMS (DoD). Currently, I'm using CAESAR-Lisflood to analyze channel morphological change in different time frame, it works well.

Las empresas de EXPLORACIÓN MINERA, levantan perfiles espacio/temporales de los sustratos geológicos.

Thank you for help. Give me information

Dear Jaydeep,

Check the Species Distribution Models.

Best

Nasson

One could use the Urban-TEP data sets ( https://urban-tep.eu/#! ) like Global Urban Footprint (GUF) ".... 2015 Worldwide inventory of human settlements (urban & rural) using one global coverage of SAR data with 0.4 arcsec (~12 m) ground resolution collected by the satellites TerraSAR-X / TanDEM-X in 2011-2013." and / or the Human Settlement Layer - along with the 2015 The TimeScan-Landsat-2000 layer "... for such aspects as the state of vegetation, water cover, or bare ground (e.g., built-up, rock, soil). For each of the indices temporal statistics" and or the ESA Land Cover CCI dataset".

As Carl Alexander Frisk pointed out, such a global query would involve some complex taxonomy and lexicon issues to refine - the toponyms used by the locals will vary considerably, along with temporal variation ( ex. Global Surface Water 1984-2021 at https://global-surface-water.appspot.com/download ), i.e. a 'lake' frequently is also a 'reservoir', so if it is empty, is it still a 'lake' for your purposes. There are actually some more refined geomorphological definitions, but those are usually specific to domain and jurisdiction.

With some clever up front design effort along with being explicit about your definitions, you could come up with a 'count' via a relatively straightforward pipeline of simple raster operations.

Yes, densities parts of the equipotential maps illustrate where the electrical field is strongest lines are angled. This means that the greater the angles, the greater the spreading. Therefore, the electric field is indeed strongest near the electrodes. The equipotential lines can be drawn by making them perpendicular to the electric field lines, if those are known. Note that the potential is greatest near the positive charge and least near the negative charge. Equipotential surfaces have equal potentials everywhere on them. For stronger fields, equipotential surfaces are closer to each other! These equipotential surfaces are always perpendicular to the electric field direction, at every point. The electric field is the gradient of the potential. If the equipotential lines are closer together, the potential changes by the same amount over a shorter distance. Consequently, the electric field is stronger in this case. Electric field lines begin on positive charges and radiate away from them toward negative charges, where they terminate. Equipotential lines are lines connecting points of the same electric potential. All electric field lines cross all equipotential lines perpendicularly. The electric field strength is represented by the distance between the equipotential lines. The closer together the equipotential lines are, the stronger the electric field. The potential is the same along each equipotential line, meaning that no work is required to move a charge anywhere along one of those lines. Work is needed to move a charge from one equipotential line to another. Equipotential lines are perpendicular to electric field lines in every case. W = −ΔPE = −qΔV = 0. Electric field lines are perpendicular to the equipotential lines, and point "downhill" and a conductor forms an equipotential surface when lines are close to each other, the electric field is strong.

Vivek Verma

Hi,

The NPCR (Number of Pixel Change Rate) and UACI (Unified Average Change Intensity) tests are commonly used to evaluate the quality of encrypted images in terms of their resistance against attacks and the level of diffusion achieved. The higher the NPCR and the lower the UACI, the better the diffusion properties of the encryption algorithm.

If the NPCR and UACI results you obtained are significantly lower than the expected values of 99.60 and 33.46, respectively, it suggests that the diffusion process in your encryption algorithm may not be effective enough. This could be due to a variety of reasons, including the choice of the chaotic map, the implementation of the diffusion process, or errors in the encryption algorithm.

Here are a few things you can consider to improve the NPCR and UACI results:

Chaotic map selection: Ensure that the chaotic map you are using has good statistical properties and provides sufficient diffusion. Different chaotic maps have different properties, and some may be better suited for image encryption than others. You could try experimenting with different chaotic maps to see if they improve the diffusion properties of your algorithm.

Diffusion process: Review the diffusion process in your encryption algorithm. It's possible that the diffusion process is not adequately spreading the pixel changes throughout the encrypted image. You may need to revisit the diffusion mechanism and consider alternative techniques to enhance the diffusion properties.

Implementation errors: Double-check your implementation of the encryption algorithm and the diffusion process. Small errors or inconsistencies in the code could lead to suboptimal results. Make sure you are correctly applying the diffusion operations and that there are no unintended biases or patterns in the encrypted image.

Parameter tuning: Some encryption algorithms rely on adjustable parameters that can impact the diffusion properties. Experiment with different parameter values to find the optimal settings that provide better NPCR and UACI results.

Comparison with existing algorithms: Compare your results with other established encryption algorithms that use similar techniques or chaotic maps. This can help you identify any major discrepancies and provide insights into potential improvements.

Additionally, it's worth noting that achieving the exact NPCR and UACI values reported in the literature may not always be feasible due to variations in implementation, image datasets, and testing methodologies. However, it's important to strive for results that are close to the reported values to ensure the robustness of your encryption algorithm.

Laura Natalia Serkovic Loli

Hi ,

I can provide you with some common causes of electronic drive unit malfunction in turbo pumps based on my knowledge.

When electronic components of the drive unit have burnt and have been replaced, but the unit still isn't working properly, there could be several reasons for this issue. Here are some possible causes and troubleshooting steps to consider:

Incorrect replacement: Ensure that the burnt electronic components were replaced with the correct parts and that they are compatible with the turbo pump's specifications.

Power supply issues: Check the power supply to the electronic drive unit. Make sure it is providing the correct voltage and that there are no fluctuations or power surges that could damage the components.

Wiring and connections: Inspect the wiring and connections between the electronic drive unit and the turbo pump. Ensure that all connections are secure and properly connected. Check for any loose or damaged wires that could be causing a malfunction.

Overheating: Verify that the cooling system for the electronic drive unit is functioning properly. Overheating can cause damage to the components and lead to malfunctions. Clean any dust or debris from the cooling system and ensure proper airflow.

Faulty electronic components: Although you have replaced the burnt components, it is possible that there are other faulty components in the electronic drive unit. Consider having a professional technician or engineer inspect the unit to identify any additional faulty components.

Software or firmware issues: Check if there are any software or firmware updates available for the electronic drive unit. Updating the software or firmware may resolve any compatibility issues or bugs that could be causing the malfunction.

Manufacturer support: If you have tried the above troubleshooting steps and the electronic drive unit still isn't working properly, it may be necessary to contact the manufacturer for further assistance. They can provide specific guidance and support based on the model and specifications of your turbo pump.

Great job, you can validate in two ways:

1. use Google earth or

2. Ground truthing (actual fieldwork visit with selected georeferenced points)

Kindly review the literature to gain an understanding of the different threshold values, which may not necessarily apply to your study area.

It is also recommended that you apply NDBI on your imagery and verify the classes against values using Google Earth images and/or field verification.

You can search online what's the minimum spatial resolution required for urban-scale applications. As suggested above, the minimum pixel size should be 10m. Having said that, you will find papers utilizing lower spatial resolution data. This doesn't necessarly mean that they are wrong, but you need to be careful about what conclusions you can make when using lower spatial resolution data.

Example of a simplified process map outlining the breast cancer patient journey:

1. Awareness and Screening:

- Patient becomes aware of breast cancer through education, campaigns, or personal risk factors.

- Patient undergoes regular breast cancer screenings, such as mammograms or self-examinations.

2. Diagnosis:

- Patient identifies a potential breast abnormality or experiences symptoms.

- Patient visits a primary care physician or specialist for further evaluation.

- Medical examinations, imaging tests (mammogram, ultrasound, MRI), and biopsies are performed.

- Diagnosis of breast cancer is confirmed.

3. Treatment Planning:

- Patient meets with an oncologist or a multidisciplinary team to discuss treatment options.

- Comprehensive assessment of the cancer stage, grade, and other relevant factors.

- Treatment options are presented, including surgery, chemotherapy, radiation therapy, hormonal therapy, or targeted therapy.

- Patient and healthcare team collaboratively develop a personalized treatment plan.

4. Treatment:

- Surgery: Patient undergoes surgical procedures, such as lumpectomy, mastectomy, or lymph node removal.

- Systemic Therapy: Patient receives chemotherapy, targeted therapy, or hormonal therapy.

- Radiation Therapy: Patient undergoes a course of radiation treatments.

- Supportive Care: Patient may receive supportive therapies, such as pain management or counseling.

5. Monitoring and Follow-up:

- Patient goes through regular follow-up visits and monitoring to assess treatment response and potential side effects.

- Imaging tests (mammograms, CT scans, etc.) and blood tests are conducted at specified intervals.

- Adjustments to the treatment plan may be made based on monitoring results.

6. Survivorship and Rehabilitation:

- Patient transitions into the survivorship phase, focusing on physical and emotional well-being.

- Rehabilitation programs, including physical therapy or counseling, may be recommended.

- Support groups and survivorship care plans may be provided to address long-term needs.

It's important to note that the patient journey can vary based on individual circumstances, treatment protocols, and healthcare systems. The above process map provides a general overview and may require customization based on specific contexts.

Hope it helps:credit AI

Most mining claims in various countries are handled through various federal and state registries like https://tenementregister.sarig.sa.gov.au/ and https://www.business.qld.gov.au/industries/mining-energy-water/resources/landholders/searches and https://www.qld.gov.au/environment/land/management/abandoned-mines ... "Sites are classed as ‘abandoned’ once a mining tenure no longer exists. There are about 120 complex abandoned mine sites in Queensland. Some, such as Mount Morgan, Mount Oxide, and Hopeland (ex-Linc Energy), are currently managed through the Abandoned Mine Lands Program (AMLP). The program also manages subsidence issues at Collingwood Park and remediation of smaller mine sites." and https://www.business.qld.gov.au/industries/mining-energy-water/resources/minerals-coal/online-services/georesglobe ...

Your mileage may vary. Where I live, the state has actually scanned the original engineering drawings, some from the 1800's because the area is honeycombed with shafts and tunnels. Real estate developers get upset when their bulldozers vanish down a shaft.

Also, any interesting area has rock hound clubs and some even are specifically around amateur activities like panning and smelting - they also collect mining memorabilia like maps, tools, etc.

An empathy map is a tool used in design thinking and customer experience to help teams understand and empathize with their target users or customers. It is a visual representation that helps teams to gain a deeper understanding of the thoughts, feelings, and motivations of their users by considering their needs, desires, fears, and pain points. The empathy map typically includes sections for what the user says, thinks, does, and feels, providing a comprehensive view of the user's experience. This tool can be used to inform product development, marketing strategies, and customer service initiatives.

It's important to note that while AI tools can greatly assist in the literature review process, they are complements to, rather than replacements for, the researcher's critical thinking, analytical skills, and domain expertise. The final interpretation, synthesis, and conclusions drawn from the literature remain a deeply human and intellectual endeavor.

If you're using or considering any specific AI tools for your literature review, I'd be interested to know

Oh, I have got the reply from Nees Jan as follows on Sep 14, 2021

Dear Zahid,

When exporting data from Scopus, make sure that the references of documents are included in the export. By default, they are not included, so you need to overrule the default settings and indicate that references should be included. The references should be included in order to be able to create citation-based maps in VOSviewer.

I hope this is helpful.

Best regards,

Nees

Contacter sur email

First, you need to install the OR-Tools library if you haven't already

pip install ortools

from ortools.constraint_solver import routing_enums_pb2

from ortools.constraint_solver import pywrapcp

# Define the distance matrix (replace this with your actual distance matrix)

distance_matrix = [

[0, 20, 23, 19, 13, 16, 38, 38, 24, 12, 18, 13],

[20, 0, 5, 33.4, 31.6, 28.5, 37.8, 54.5, 47.5, 30, 36.2, 14.2],

[23, 5, 0, 40, 35, 32.6, 41.6, 62, 47.3, 40, 40.3, 18.6],

[19, 33.4, 40, 0, 13, 17.6, 15.5, 32, 37.5, 28, 37.8, 32.8],

[13, 31.6, 32.6, 13, 0, 43, 8, 22, 19.3, 23, 24, 20],

[16, 28.5, 35, 17.6, 13, 0, 10, 10, 15, 22, 20, 16],

[38, 37.8, 41.6, 15.5, 8, 10, 0, 17, 20, 23, 24, 26.2],

[38, 54.5, 62, 32, 22, 10, 17, 0, 14, 24, 26, 46],

[24, 47.5, 47.3, 37.5, 19.3, 15, 20, 14, 0, 10, 12, 31],

[12, 30, 40, 28, 23, 22, 23, 24, 10, 0, 12, 23],

[18, 36.2, 40.3, 37.8, 24, 24, 24, 26, 12, 12, 0, 20],

[13, 14.2, 18.6, 32.8, 20, 16, 26.2, 46, 31, 23, 20, 0]

]

# Create a routing model

def create_data_model():

data = {}

data['distance_matrix'] = distance_matrix

data['num_vehicles'] = 3 # Number of vehicles

data['depot'] = 0 # The depot is node 0

return data

def main():

# Instantiate the data problem

data = create_data_model()

# Create the routing index manager

manager = pywrapcp.RoutingIndexManager(len(data['distance_matrix']),

data['num_vehicles'], data['depot'])

# Create Routing Model

routing = pywrapcp.RoutingModel(manager)

# Create and register a transit callback

def distance_callback(from_index, to_index):

from_node = manager.IndexToNode(from_index)

to_node = manager.IndexToNode(to_index)

return data['distance_matrix'][from_node][to_node]

transit_callback_index = routing.RegisterTransitCallback(distance_callback)

# Define cost of each arc

routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)

# Set 10 seconds as the maximum time allowed per each vehicle

search_parameters = pywrapcp.DefaultRoutingSearchParameters()

search_parameters.time_limit.seconds = 10

# Solve the problem

solution = routing.SolveWithParameters(search_parameters)

# Print solution if found

if solution:

print_solution(manager, routing, solution)

def print_solution(manager, routing, solution):

print('Objective: {} units of milk traveled'.format(solution.ObjectiveValue()))

for vehicle_id in range(manager.GetNumberOfVehicles()):

index = routing.Start(vehicle_id)

plan_output = 'Route for vehicle {}:\n'.format(vehicle_id + 1)

while not routing.IsEnd(index):

plan_output += ' {} ->'.format(manager.IndexToNode(index))

index = solution.Value(routing.NextVar(index))

plan_output += ' {}\n'.format(manager.IndexToNode(index))

print(plan_output)

if __name__ == '__main__':

main()

This code sets up the VRP instance for your problem with three vehicles and multiple destinations, calculates the optimal routes, and prints the results. You can replace the distance_matrix with your actual distance matrix. Make sure that the depot is defined as node 0, and the number of vehicles (num_vehicles) is set to 3 as per your problem description.

Publish as much as you can before you even defend your thesis. This would make the defense easier and give you exposure

Robert Adolf Brinzer I will try that. Thank you!

Yes, there are free software programs available for Windows machines that can be used to generate electron density maps, typically for use in the field of computational chemistry and crystallography. Here are a few options:

PyMOL: PyMOL is a widely used molecular visualization tool that can generate electron density maps. While the free version of PyMOL has limited functionality, it can still be used for basic electron density map visualization. You can download the open-source version known as "PyMOL2" for free.

Website: https://pymol.org/2/

Avogadro: Avogadro is an open-source molecular editor and visualization tool that can also generate electron density maps. It is designed for general chemistry, and it's user-friendly.

Website: https://avogadro.cc/

Jmol: Jmol is another open-source molecular visualization program that can be used to visualize electron density maps. It's not as feature-rich as some other tools, but it's free and relatively easy to use.

Website: http://jmol.sourceforge.net/

XCrySDen: While primarily a crystallography visualization tool, XCrySDen can also generate electron density maps. It's open source and supports a variety of file formats.

Website: http://www.xcrysden.org/

Vesta: Vesta is a visualization program for structural models, and it can display electron density maps generated from crystallographic data. It's free and widely used in the crystallography community.

Website: https://jp-minerals.org/vesta/en/

Remember that the availability and features of these software programs may change over time, so it's a good idea to visit their official websites for the latest information and downloads. Additionally, the quality and accuracy of electron density maps may depend on the underlying computational methods and data used, so it's essential to ensure that you have appropriate input data and settings for your specific research needs.

I know I'm a little late, but nevertheless, the initial step involves copying the data into an Excel (.csv) or text file. To begin, select the "irradiance maps" option and transfer the data to an Excel file, resulting in gridwise data. However, it's essential to note that Ansys interprets flux data based on X, Y, and Z coordinates rather than a grid. Therefore, the next step entails converting the grid data into coordinates. You can accomplish this using software such as Matlab, Python, or any other suitable tool. If you require assistance with the code for this conversion, please don't hesitate to reach out to me.

Tom Koch This is the answer.

This is a very generic answer, from looking at the dates in the GitHub repository, the DropBox file dates, etc. - Software is like bananas, so many of the version numbers are a decade old at this point.

Your grief ( guess follows ) is probably related to the exact versions and relationships of the Operating system, SPHY, QGIS, and their respective dependencies ( the 'Environment'). The relationships in the code can be explicit ( as in a configuration file(s) which give exact paths to the desired components or implicit (assumed). The classic case is when MS issues some sort of update which breaks things. Usually, when this is important, one uses a tool like Conda (or Anaconda) which allows the software to execute in a controlled 'bubble', where exactly the correct versions can be installed, and not worry that some other software has altered a path to some important component. Your best best bet is to formulate an exact description of your installation, what works and what doesn't ( don't expect people to ask twenty questions back and forth just to get to the problem ) in the SPHY user group, which seems to be fairly active. And most import, give a specific and relevant subject to your post: https://groups.google.com/g/sphy-model-user ... you can also scroll down and read if others have had the same issue before posting. Also, read the Release Notes on https://sphy.readthedocs.io/en/latest/

Let me know how it goes, and post the resolution here so others can learn from the experience.

yeah, I am trying to calculate the fire weather variables from the normal weather variables using some R library package fwi, but its kind of tedious.

Amena Muzaffar Shumi

Supratim Guha

Hi ,

It seems like you're experiencing an issue with the Spatial Processes in Hydrology (SPHY) model while working with the preprocessor module in the Sikkim Himalayan region, which is part of the High Mountain Asia (HMA) region. Specifically, you've encountered a problem where only the GlacFrac map appears in the table of contents after running the preprocessing step, and it indicates that "temp2" and "temp3.tif" have been removed in the Python console.

This issue might be related to several factors, so let's troubleshoot it step by step:

By systematically checking these aspects and addressing any discrepancies or errors, you should be able to identify and resolve the problem with the SPHY model's preprocessing tool.

If you encounter specific error messages or have further details, please provide them for more targeted assistance.

Thanks Samanin Apa.

Dear Martin Elsner ,

I have sent a similar query to Dave Gardiner in private seven days ago, but he didn't answer until now.

A relevant answer to such a question can only be given if we have more information!

Regards,

Laszlo

Really difficult to make conclusions without looking into the reads and reference genome. It might be for several reasons:

1. Wrong reference genome sequence

2. reads sequence is very poor

3. wrong platform to make your analysis

4. reads are not from Sanger??!

Es necesario levantar, en el terreno, un mapa digital temático con precisión suficiente para no posicionar erróneamente los componentes para su actividad.

El software SIG, disponible, posee herramientas para levantar la cartografía necesaria y genera nueva información geométrica del espacio y todos los elementos necesarios, según sus objetivos.

You can measure concept maps using numbers (quantitatively) to see how good they are. Some things we look at include how many things are connected, how many connections there are, how organized it is, and how many words or labels are used. But remember, it's important to use numbers along with looking at it carefully to really understand if the concept map is good for what we need.

Thank for your reply, I will be very happy to discuss this scientific topic with you.

ArcGIS has Geographically Weighted Regression (GWR) which can be used to regress a dependent variable over independent variables. It also takes into account spatial autocorrelation effects.

Akula Komuraiah

The error message you provided indicates a check failure related to the number of vehicles in the Vehicle Routing Problem (VRP) solution. Specifically, it states that the check failed because the number of vehicles specified is 4, but the problem instance has 100 vehicles.

To resolve this issue, you need to ensure that the number of vehicles specified in your code matches the actual number of vehicles in your VRP instance. Double-check the part of your code where you define and set the number of vehicles and make sure it is correctly assigned as 3, which is the number you mentioned in your question.

Here's a general example of how you can define the number of vehicles using the OR-Tools library in Python:

```python

from ortools.constraint_solver import routing_enums_pb2

from ortools.constraint_solver import pywrapcp

def solve_vrp(distance_matrix, num_vehicles):

# Create the routing model and manager.

manager = pywrapcp.RoutingIndexManager(len(distance_matrix), num_vehicles, 0)

# Create the routing model.

routing = pywrapcp.RoutingModel(manager)

# ... Rest of your code ...

# Solve the problem.

solution = routing.Solve()

# ... Rest of your code ...

# Example usage

distance_matrix = ... # Provide your distance matrix here

num_vehicles = 3 # Set the number of vehicles

solve_vrp(distance_matrix, num_vehicles)

```

Make sure that you have correctly assigned the value of `num_vehicles` to 3 in your code to match your problem instance. If the issue persists, please provide more details about your code implementation, including the relevant sections where you define the number of vehicles and how you set up the problem, so that I can assist you further.

Good luck!!

Thankyou so much for your response .

It was resolved by adding the annotation file

Any interpretation of Bouguer gravity data should be built upon a realistic model with reasonable density values. Gravity data is non-unique so multiple hypotheses are possible. The best hypotheses are built from density data from boreholes. If an idea cannot be modeled due to lack of density data, any publication should also discuss alternative ideas. Such a paper might be valuable to generate discussion. If data exists and the idea cannot be modeled, it should be rejected and then other ideas should be modeled.

I would like to use the program adehabitat HS but failed after downloading the program. Is there any example either in video or ppt of the codes?

Thank you for the time and help.

Thank you, Ajit Singh. I highly appreciate your prompt response. It is very helpful.

Kind regards,

Here are some steps to troubleshoot and address the issue:

By systematically going through these steps, you should be able to identify the cause of the issue and take appropriate actions to ensure that all layers within the layer group are displayed correctly in your web application.