Mapping - Science topic

Bibliometric analysis has recently become a popular and rigorous technique used for exploring and analyzing the literature in business and management. Prior studies principally focused on ‘how to do bibliometric analysis’, presenting an overview of the bibliometric methodology along with various techniques and step-by-step guidelines that can be relied on to rigorously conduct bibliometric analysis. However, the current body of evidence is limited in its ability to provide practical knowledge that can enhance the design and performance of bibliometric research. This claim is supported even by the fact that relevant studies refer to their work as ‘bibliometric analysis’ rather than ‘bibliometric research’. Accordingly, we endeavor to offer a more functional framework for researchers who wish to design/conduct bibliometric research on any field of research, especially business and management.

To conduct a systematic mapping review, define a broad research question, develop a protocol, and perform comprehensive literature searches followed by screening and data extraction. Present findings visually to highlight trends and gaps in the literature, ensuring clear documentation of the process.

To improve compound mapping in your LC-MS/MS metabolomics data, consider using alternative databases like METLIN and employing spectral matching tools such as GNPS or MassBank. Additionally, leverage cheminformatics tools for structure prediction and collaborate with experts to enhance compound identification.

Ok Iam gree

Creativity and innovation mapping is a powerful tool for fostering a culture of innovation and maximizing creative potential within any organization or community. By systematically visualizing and analyzing these processes, leaders can better support and cultivate an environment conducive to successful innovation.

Ref/

Brown, T. (2009). Change by design: How design thinking transforms organizations and inspires innovation. New York: HarperCollins.

This book Sandeep Savitaprakash Sharma emphasizes design thinking as a creative process that leads to innovation.

In engineering, a unified rule often refers to a standardized set of guidelines or principles that are applied consistently across various systems or processes to ensure uniformity and comparability. This concept can be particularly useful in fields like software engineering, where a unified rules engine might be used to manage and apply business rules consistently across different applications.

You can find a lot of material on the web... but I doubt there are any real applications...

How do you "find teaching it" ?

EDS can be done in differing ways (techniques). Not all method are equally accurate. My recommendation (based upon experience) is to not use the less analytical (every-day) methods (usually ZAF with a preexisting, internal standard).

If it does not already exist in publication, it will be necessary to create a “Quality standard.“ This can be done by analyzing your own material, or at least a similar or related material, several times, using the more analytical methodology (usually described within your EDS operating methodology instructions). Do not use your instrument’ s every-day methods (usually ZAF). Creat your standard (using the most analytical method your instrument software offers), (not ZAF). In my instrument that method is referred to as a “least squares“ technique. Repeat this method on your material at least 5-6 times, by multiple analyses of differing areas. Average those analytical results into a single quantitative result. Use that average in your most analytical EDS method “as a standard.“ There should be a way to introduce this “analytical average” into your software as the comparative standard. Then use that standard with every analysis from that time forward (for your quantitative mythology). Using this specific method, will give you the most accurate analytical method possible with your EDS system. I believe you will be as happy with this “very analytical“ method as I have been.

I agree with jon morant

The conservation of cultural heritage here in Germany is strongly decentralized and therefore the quality may vary, although since Germany is in a moderate climate zone, demands are probably a lot lower than in a tropical country like brazil.

In most places here the conservation itself works decently, but since many catalogues of the smaller archives are still not fully digitalized, we have new discoveries every once in a while.

The decently working conservation has its terribly spectacular exceptions, though. Two of the worst examples were the fire of the Anna-Amalia library, due to improper electric wiring, causing among other things the loss of some Joseph Haydn originals or the collapse of the Cologne city archive, due to a corrupt subway construction site in which a lot of the steel that was supposed to go into the concrete was sold on the black market, causing the loss of the Jacques Offenbach heritage.

Dear Sir,

Why you need to consider these factors has influence on main KPI's

I think these factors are different KPI's with minor effect.

you can consider some of these factors if you fill that they are still importance by increase the numbers of KPI's in your model.

if these factors are related to the main factors, PCA will eliminate them

Please check the attached paper

This is not that simple, there are various approaches, each having advantages and disadvantages. Maybe these paper will help to solve your problem.

Image could be drastically reduced - by text. Text (Meaning) could be drastically reduced - by code. Code could be drastically reduces - by cost (price). What is your aim? Reduce Leonardo's Mona Lisa to cost (USDXXXX.XX)? Or preserve the beauty? Therefore, the answer.

Line scan is mostly taken across interfaces. Matrix-precipitate, Matrix-grain boundary phase etc.

Prior to that, you must have an idea of the elements present in both matrix and precipitate. In order to get an idea, take point scans on precipitate and adjacent matrix (3 points each would be good, statistically).

Analyze the elements and take line scans with the desirable elements.

PS: For line scans, use dark colours.

Dear @Preston Guynn

Thank you very much for your reply.

However, I think you have not understood the meaning of my question. My question is very direct and clear, ‘Doubts about General Relativity - Is Space-Time Bend a Motion?’This is questioning whether ‘Space-Time Curvature’ is a true physical curvature, or a mathematical intrinsic curvature. If curvature is a physical motion, then Space-Time Curvature must be able to manifest itself; if not, where does this intrinsic nature manifest itself in space-time？ If we have to resort to the concept of discrete spacetime to solve this problem, does it mean that spacetime curvature is not intrinsic and is still produced by motion? My point is clear, a mathematical expression that cannot be mapped to physics cannot be realistic, i.e. it cannot be the final concept. Either the concept of curvature or the structure of spacetime has to be changed.

You cite the concept of ‘gravitational lensing’ to justify the curvature of spacetime, but we should know that there is no curvature of index of refraction of a lens, whether n is uniform or non-uniform. We also know that the early hesitations about the concept of spacetime curvature were not limited to ordinary physicists, but included Dirac, Feynman, and even Einstein himself.

Researchgate is a free and open community for the exchange of views on scientific research. What do you think is the proper or correct motivation for a person to post a ‘Question’, ‘Discussion’ or ‘Doubt’? I would like to hear your opinion. My opinion is here:

Confucius (551BC-479BC) said, "When I walk along with two others, they may serve me as my teachers. I will select their good qualities and follow them, their bad qualities and avoid them." Therefore, I learn from anyone, including from you, but Learning’not equal to 'accepting’, it won't be all of them.

Best Regards, Chian

The exact PVE can vary depending on the genetic background of the population, the precision of the phenotyping, and the environmental conditions. However, in a well-controlled study, the PVE for a single dominant gene is often in the higher range (20%-50% or more). If it is a single dominant gene, one can check from the recombination frequency of the marker and the trait, if it's co-segregating with trait its completely linked.

It looks like Addgene has it, you can download the sequence with Addgene's auto-annotation as either a SnapGene or Genbank file.

have you had a peak into this publication-- maybe it can help? https://academic.oup.com/bioinformaticsadvances/article/3/1/vbad060/7156835

Yudong Chen 陈煜东

Hi :

In Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) mapping imaging, encountering sub-mineral inclusions like galena (PbS) within pyrite (FeS₂) that cause high counts and trailing effects in the mass spectrum can complicate data interpretation. Here are detailed steps and techniques to eliminate or correct these effects post-experiment:

1. Data Filtering and Smoothing

2. Image Processing Techniques

3. Mathematical and Statistical Corrections

4. Software Tools and Algorithms

5. Machine Learning Approaches

Example Workflow for Correction

import numpy as np

3. Smoothing:

def moving_average(data, window_size=3):

return np.convolve(data, np.ones(window_size)/window_size, mode='valid')

4. Background Subtraction:

from scipy.signal import savgol_filter

def background_subtraction(data, window_size=51, poly_order=3):

background = savgol_filter(data, window_size, poly_order)

corrected_data = data - background

return corrected_data

5. Visualization and Validation: Re-visualize the corrected data to ensure the artifacts are minimized without losing important signal information.

By following these steps and utilizing the appropriate tools and algorithms, you can effectively eliminate or correct the effects caused by sub-mineral inclusions in LA-ICP-MS mapping imaging.

Jianjun Shangguan

W.K.N.C. Withanage

John Hatzopoulos

Frank Veroustraete

Flood mapping assessment leveraging a combination of topography and development alignment presents a robust approach to identifying flood-prone locations. By integrating topographic data, including elevation, slope, and hydrological features, with information on urban development patterns such as land use, infrastructure, and population density, a comprehensive understanding of flood vulnerability can be achieved. High-resolution elevation models facilitate the delineation of floodplains and drainage networks, enabling the identification of areas susceptible to inundation. Additionally, analyzing the alignment of urban development with natural drainage pathways and low-lying areas provides insights into areas at heightened risk of flooding due to factors like impervious surfaces, inadequate drainage infrastructure, and encroachment into flood-prone zones. Geographic Information Systems (GIS) and remote sensing technologies offer valuable tools for integrating and analyzing these diverse datasets, enabling the creation of detailed flood hazard maps. By employing this integrated approach, planners, policymakers, and emergency responders can prioritize mitigation measures, land use planning, and infrastructure investments to enhance resilience and reduce the impact of flooding on communities and infrastructure.

Ok i am glad to participate on it

Mohammed Jalal Tazi

Salam Alaikum

Here are some of the best satellites for mapping hydrothermal alteration and the factors that influence the choice:

Best Satellites for Hydrothermal Alteration Mapping

Factors Influencing the Choice of Satellite

Recommendations

Syed Hussain

Salam Alaikum

Here's a structured approach to identify novel research gaps and topics within this domain:

Research Gaps and Novel Topics

Steps to Explore and Develop Your Topic

Example Research Questions

By addressing these gaps and exploring these novel topics, you can contribute significantly to the field of flood mapping and enhance the capabilities of current systems.

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

land use, slope, and rainfall. ArcGIS can be used to determine flood-prone areas, calculate the weight of each flood factor, 20-year return period, hydrological analysis, and rain distribution maps. These parameters are analyzed using ArcGIS overlay intersection and are weighted with the Analytical Hierarchy Process (AHP) method.

I'd like contribute in groundwater contaminations.

Do you have an example spectrum? Usually you can restrict your fitting range by the parameter settings. Additionally, what are these unwanted peaks? Cosmic rays?

Remote sensing support the identification of land uses while GIS enabe the creation of land use maps. Some remote sensing softwares can be linked to GIS softwares and some data formats are identified by GIS so the user can further process remote sensing data or outputs from remote sensing softwares into GIS environments.

Hello Ali

Follow the steps to get MEP as follows:

1- First, open the CHK or FCHK file in GaussView

2- In the result tab, select the surfaces/contour section

3- From the cube action section, you must select new cube. type=total density and density matrix=SCF

4- It takes some time to complete this process.

5- In the surface actions section, you must select new mapped surface. And then Generate values only at surface points.

type=ESP & Density Matrix=SCF

Now you can see the MEP of your molecule.

Note, this process needs to be generated and your cpu will be involved. If you are using a weak system, this process may cause damage to your computer. There are some computing companies that will do this for you. For example, MolQube.com company. You can email them:

ISRIC – World Soil Information https://www.isric.org/explore , and https://soilgrids.org/ - Standards: https://www.isric.org/about/standards

Main procedures and standards in use at ISRIC — World Soil Information cover the whole data life cycle from field sampling to serving quality-assessed soil data to the world community.

The choice of mapping method and tools for bridging-type research depends on the specific requirements and objectives of the study. Bridging research often involves integrating information from different sources, disciplines, or domains to create a comprehensive understanding.

Mohamed Fathi Said

Salam Alaikum,

The two methods you mentioned and discuss their suitability for your task.

a. Bias Correction:- Pros: Simple and widely used. Corrects systematic errors. - Cons: May not capture spatial variability well.

b. Equiratio Quantile Mapping:- Pros: Addresses biases and spatial variability. - Cons: Can be complex to implement.

Both methods have their merits, but Equiratio Quantile Mapping tends to be more robust in capturing spatial patterns and non-linear relationships. If you're looking for a method that considers both biases and spatial variability, this could be a good choice.

Implementing Equiratio Quantile Mapping involves statistical calculations. While I can't provide the entire code here, I can guide you on where to find resources:

When implementing the code, ensure that it aligns with the specifics of your dataset and the goals of your downscaling process. If you encounter challenges or need clarification on specific aspects of the code, feel free to ask for guidance.

Remember to document your methodology and validate the results against observed data to ensure the downscaling technique is suitable for your specific climate change dataset. If you have further questions or need more assistance.

红伟 李宏伟

In recent years, the integration of deep learning and machine learning with sensors has opened up exciting possibilities in various fields. Let me explain this in simple terms.

Imagine you have a sensor that can measure something, like temperature. Traditionally, these sensors are designed with specific ranges, for example, from -10°C to 100°C. But what if you want to measure a wider range, like -50°C to 150°C? This is where deep learning and machine learning come into play.

Instead of designing a new sensor for each range, researchers are using these advanced techniques to teach the sensor how to understand and respond to a broader range of inputs. It's like training a dog to do tricks; you're teaching the sensor to be smarter.

Now, to answer your first question about drawbacks. Yes, there are some challenges. One of the main drawbacks is the need for a large amount of data for training. You have to expose the sensor to many different conditions to teach it effectively. Additionally, the complexity of the models used in deep learning can be a challenge to implement in practical applications.

As for how likely it is to work in practice, it's quite promising. Many researchers have already made significant progress in using machine learning to expand the measurement range and sensitivity of sensors. In some cases, it has worked brilliantly, opening up new possibilities in fields like environmental monitoring, healthcare, and industrial processes.

However, it's important to remember that it's not a one-size-fits-all solution. The success of this approach depends on the specific application and the quality of the data used for training. It's an exciting area of research, and I believe we will continue to see advancements in the practical application of deep learning and machine learning with sensors in the coming years.

A search with keywords "weak fixed point property" (which is the official name of the property you are interested in) and with "weak normal structure" (which is a widely used sufficient condition for this property) may give you a lot of information on the subject.

Hello. From the CMhyd software, you can perform microscale statistical methods to extract the daily rainfall of climate change scenarios.

Convolutional Neural Networks (CNNs) and ground-penetrating radar (GPR) can help

Good Work. Congratulations and best regards

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:

If I am correct, complex variables can only be mapped in two dimensions defined by the real and imaginary coefficients. A third dimension can be added over the two-dimensional map.

Use the galaxy platform MiModD tools to do SNP mapping. Here is a protocol that roughly follows Doitsidou, 2010 which I used on C. elegans:

Remove adapter sequences on the raw reads with the Cutadapt tool set to use Paired-end reads (depends what sort of sequencing you did) before alignment against a reference genome sequence using the Map with BWA-MEM tool.

Put the output BAM format file was put through the MiModD Reheader tool to change the sample name before performing variant calling using the MiModD Variant Calling tool with the reference genome set to the one rom the previous step.

The resulting bcf format file is used as the input for the MiModD Extract Variant Sites tool using an independently generated vcf data set.

Linkage maps are then generated using the MiModD NacreousMap tool to visualize the genomic region of interest before using MiModD Rebase Sites to realign the vcf file to any more modern annotation of the genome (http://hgdownload.soe.ucsc.edu/goldenPath/ is a good source) as the input chain file.

The realigned vcf file then has the variants annotated using the SnpEff eff tool with a reference genome from the SnpEff download tool as the genome source before MiModD VCF Filter is applied to focus on the genomic region of interest which is then visualized with the MiModD Report Variants tool.

The three issues you raised are familiar to me either as practitioner, researcher or educator in Africa (including Kenya).

"Scoping" is standard practice in [Strategic] Environmental Impact assessments (SEA/EIA). You may have a look at my two pertinent publications on ResearchGate whether this may help you in your field of expertise as well. In short, scoping includes literature review, but goes beyond it. Especially by identifying the relevant unknows that are not covered in the literature. This requires a wider level of expertise than literature review.

"Literature review" is part of all research, from design, project proposal to publication. In technical reports and MSc theses an explicit section on literature reviews may be included. But this is unusual in papers published in journals. There are also specific review papers in most journals.

"Map reviews", in the sense of critically reviewing one map or a set of related maps, is rather rare compared with the above categories. You may enjoy a look at our recent paper on comparing vegetation/landscape maps of Namibia and a much older paper exploring the issue on a global and conceptual level.

Your research on Covid, HIV and Malaria is very thorough and relevant. Therefore, I am willing to share my unpublished "field" experiences on all three with your institution.

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

Dear Catherene Julie Aarthy C

I am pleased to help you.

you can contact me.

Dear Mr. Frisk, I'm attaching my CV. Could you please take a look at it?

At community level, official data are often non-existent, and those that exist are far less useful than information collected from the people themselves.

There are often local health workers who can advise you on which households have people in the target age group. Community nurses, for example, or traditional birth attendants. You can compile a sample frame from this information and then sample households. This often will yield more than one eligible participant per household, but you can use robust estimation of variance to account for clustering within household.

Another reason for using trusted community workers is that they can then introduce the survey (pay them for this!) and help to create a bridge of trust between participants and the research team.

Clearly, getting community participation should be the goal - I hardly have to remind you to involve them as much as possible in the design and conduct of your study. But I mention it because much LMIC research is carried out by white idiots jumping out of a 4x4 with clipboards.

Belhadj Maha Attached you can find some articles about! Good luck in your research!

Navoda Wijesuriya

Thank you for reaching out about this genomics analysis challenge. Assessing copy number variation of SSR loci through read mapping is an excellent technique. Let me offer some guidance based on best practices:

First, align your sample reads against a reference genome using a tool like BWA-MEM. This creates a BAM file mapping each read. Then use software like SAMtools to identify reads mapping to your target SSR coordinates.

The read depth or coverage at an SSR locus indicates copy number. A consistent depth close to the genome-wide average implies a single copy locus. Significantly higher coverage suggests multiple copies. You can statistically compare depth distributions to identify outliers.

There are robust tools like CNVnator that can automate and streamline the analysis process for you. But manually inspecting alignments in a genome browser is also insightful for small-scale assessment.

Feel free to reach out if you need help interpreting results or finding suitable software. Optimizing these bioinformatic techniques does involve some initial learning. But you are pursuing a very fruitful approach to characterize your SSRs.

Thanks for th information Jens Kleb

The simple answer is "you can do whatever you want', the complex part is the burden you have explaining why you undertook this particular approach and further, why it would be of interest to others. That goes to the context you provide, the expected consumer of your research, and what the goal is. there is almost infinite number of types, and even more techniques and methods, as long as your upfront and honest, and not make any overly broad claims.

Consider medical research: https://news.harvard.edu/gazette/story/2004/04/scientists-discuss-experiments-on-self/ "Examples of self-experimentation range from physician Santorio Santorio’s 30-year, daily measurements of his weight, food intake, and bodily waste in the 16th century, to physician and physiologist Werner Forssmann’s experiments in 1929 and 1935 in which he inserted a catheter into a vein in his arm and pushed the tube up into his heart (he later won a Nobel Prize), to less harrowing contemporary practices such as blood draws, knee MRIs, and urine analyses."

Google Scholar is your friend: https://scholar.google.com/ ... if you look through the references of the top search results, and the 'cited by', you will most likely find what folks are using currently.

Dear Jocelyn Sukluta Please do recommend my answer if helpful

Structural mapping using Geographic Information Systems (GIS) and remote sensing involves the integration of geospatial data and satellite imagery to analyze and visualize geological structures and features on the Earth's surface. This technique is widely used in geological and environmental studies, mining, natural resource management, and land-use planning. Here's how structural mapping using GIS and remote sensing works:

Structural mapping using GIS and remote sensing allows geologists and other stakeholders to gain a better understanding of the Earth's subsurface structures, which can have significant implications for various industries and environmental management. It enables more informed decision-making and resource exploration while reducing the need for extensive fieldwork.

1. ASTER L1B数据是需要做几何校正的，参考数据通常为OLI数据。而ASTER L1T数据是不需要做几何校正的。

2. ENVI 打开ASTER L1B数据时，软件会自动做辐射定标。而ENVI 处理ASTER L1T数据时，需要单独做辐射定标。

3. 你可以去我的主页参考我的论文。

Yes it is interesting but your wording is incorrect it makes title to long so reword it

Thank you sir

Yes, there are privacy and security considerations that need to be addressed when using AI for laboratory mapping or any application involving the collection, processing, and analysis of data, especially in sensitive environments like research laboratories. Here are some key considerations:

Addressing these privacy and security considerations is critical to ensure the responsible and secure use of AI for laboratory mapping. It helps protect sensitive research data, maintain the integrity of research findings, and safeguard the privacy of individuals involved in the research process. Additionally, involving data privacy and cybersecurity experts in the planning and implementation of AI projects in laboratory settings is advisable to mitigate risks effectively.

Dear Dave, 1 second is equal to 1000 milliseconds. Note that rounding errors may occur due to that you must put in your formula: 500x0.001,

, so always check the results, 500 x 0.001 x 7700 ---> 3,850 ft.

I will help you with your other questions, Cheers, Mario

Hello Alwielland Q. Bello

Information Mapping is a strategy or methodology used to organize and present information clearly and in a structured way. Robert E. Horn developed it in the 1960s to improve the communication of complex information. The main goal of information mapping is to make information more accessible, understandable, and usable for the intended audience.

The strategy involves breaking down complex information into smaller, manageable chunks and arranging them logically and hierarchically. This hierarchy typically involves a top-down approach, presenting overarching concepts first, followed by supporting details and specific information.

For more information, kindly go through these articles:

Best Regards!

Ali YOUNES

Here's how you can process and visualize Raman mapping data using position mapping:

By using position mapping, you can gain deeper insights into the spatial distribution of vibrational modes across your sample, which can be particularly useful for understanding complex materials or heterogeneous structures. Keep in mind that the specific steps and tools you use might vary based on your experimental setup, equipment, and software preferences.

Dear Sophia Morley , as was mentioned by Ameer K Ibraheem , there are two methods of X-ray quantitive analysis - standardless and with standards. If you used standardless EDS and WDS (EPMA) with standards, you can safely discard EDS results as less reliable. However, 0.70% and 0.88% are pretty close results for X-ray microanalysis (EDS and WDS). If your aim is to compare both methods, you may want (actually, you must) to take a statistical approach, to acquire results for multiple spots. Theese small differences may be due to non homogeneity of your thin film, surface roughness, variations in thickness, etc.

Yes, without GCPs and RTK/PPK, it is highly possible to obtain wrong or inaccurate geometric information in UAV-based photogrammetric mapping. When dealing with large areas, relying solely on the drone's GNSS information can lead to distortions in the 3D model or orthomosaic. GCPs not only add global georeferenced accuracy but also help decrease errors in the scale of the results, making them essential for reliable measurements.

The accuracy of UAS-based photogrammetric mapping depends on several factors, including Ground Control Points (GCPs), flight height, camera resolution, GNSS accuracy of the device, weather conditions, processing software, user experience, etc. While it is possible to obtain satisfactory 3D models without GCPs or RTK/PPK, for precise measurements such as surface area or volume calculations, GCPs are essential. For more in-depth information, you can refer to my MSc thesis and the following articles. In the following studies, you can find comparisons of processing with and without GCPs as well.

MSc Thesis:

Good luck on your journey of exploration and innovation!

you can follow these general steps:

Keep in mind that the specific steps and options in Origin may vary depending on the version of the software you are using. The above steps provide a general guide to creating a 2D graph for your temperature-dependent PL measurement data. For more detailed instructions and tutorials, refer to the official Origin documentation or user guides, or explore online resources and tutorials specific to your version of Origin.

Appana Kiran Kumar

To prove the fixed-point theorem using different types of contraction mappings, it's essential to understand what a contraction mapping is and how it relates to the fixed-point theorem. A contraction mapping is a function on a metric space that shrinks the distance between two points. Specifically, a function f: X → X, where X is a metric space with distance metric d, is called a contraction mapping if there exists a constant k (0 < k < 1) such that:

d(f(x), f(y)) ≤ k * d(x, y) for all x, y ∈ X.

The fixed-point theorem states that every contraction mapping on a complete metric space has a unique fixed point, i.e., a point x ∈ X such that f(x) = x.

Different types of contraction mappings can be used to prove the fixed-point theorem, and here are a few examples:

Ciric (Ćirić) Contraction: A function f: X → X is a Ciric contraction if there exists a constant k (0 < k < 1) such that:

d(f(x), f(y)) ≤ k * [d(f(x), x) + d(f(y), y)] for all x, y ∈ X.

Rus-Contractions: A function f: X → X is a Rus contraction if there exists a constant k (0 < k < 1) such that:

d(f(x), f(y)) ≤ k * max[d(f(x), x), d(f(y), y)] for all x, y ∈ X.

F-Contraction (F-Map): A function f: X → X is an F-contraction if there exists a function g: [0, ∞) → [0, ∞) such that g(0) = 0 and:

d(f(x), f(y)) ≤ g(d(x, y)) for all x, y ∈ X.

Suzuki Contraction: A function f: X → X is a Suzuki contraction if there exists a constant k (0 < k < 1) such that:

d(f(x), f(y)) ≤ k * [d(x, f(x)) + d(y, f(y)) + d(x, y)] for all x, y ∈ X.

These are just a few examples of different types of contraction mappings. There are other variations and generalizations that researchers have explored.

When you want to prove the fixed-point theorem using any of these contraction mappings, you'll typically show that the mapping satisfies the required contraction condition, and then you can invoke the fixed-point theorem to conclude the existence of a unique fixed point.

Remember that the fixed-point theorem and its applications have significance in various fields, including functional analysis, optimization, computer science, and various areas of mathematics.

Dear friend Cheshini Malavipathirana

Ah, air quality mapping through remote sensing, an intriguing endeavor indeed! I am here to shed some light on this captivating topic.

To utilize remote sensing data for air quality mapping, we can deploy various techniques and indices. Here's how we can go about it:

1. Satellite Imagery: Satellites equipped with sensors can capture data from different regions of the Earth's atmosphere. By analyzing this data, we can obtain valuable insights into various air pollutants, such as particulate matter, nitrogen dioxide, sulfur dioxide, ozone, and carbon monoxide.

2. Spectral Bands: Remote sensing instruments often use specific spectral bands that are sensitive to certain air pollutants. By analyzing the reflectance or absorption patterns in these bands, we can estimate pollutant concentrations in the atmosphere.

3. Aerosol Optical Depth (AOD): AOD is a common index used to assess particulate matter concentrations. It measures the attenuation of sunlight by aerosols in the atmosphere. High AOD values indicate higher levels of particulate matter, indicating poorer air quality.

4. Nitrogen Dioxide (NO2) Tropospheric Columns: Remote sensing can estimate the vertical column density of NO2 in the troposphere. Elevated NO2 levels are associated with urban pollution and traffic emissions.

5. Total Ozone Mapping Spectrometer (TOMS): TOMS instruments onboard satellites can monitor the total ozone content in the atmosphere. Changes in total ozone levels can be indicative of air pollution events or ozone layer depletion.

6. Thermal Infrared Sensors: These sensors can help detect heat anomalies associated with industrial emissions, wildfires, or other sources of air pollution.

7. Multispectral Data: Combining data from multiple sensors can provide a comprehensive view of various pollutants and their spatial distribution.

By leveraging these remote sensing techniques and indices, we can create detailed air quality maps, identify pollution hotspots, monitor changes over time, and implement targeted mitigation strategies. It's a powerful tool in the battle for cleaner and healthier air for all!

Please note that while I can present this information, the implementation and accuracy of remote sensing for air quality mapping may vary depending on the specific technology, data sources, and analysis methods used.

Some useful articles are:

samples are the key points in molecular biology and higher technologies. did you check for quality of your samples before going to library preparation. low quality (RIN) will give low target assignment.

you can also check after sequencing quality using multiQC tools but the worst is done.

fred

In addition to the excellent approach mentioned by Enda William O'Brien, which involves statistical adjustments based on available data, it is also possible to adopt approaches that take into account the scarcity of available data. One such approach is spatial interpolation, which is highly useful for estimating precipitation values in locations with insufficient data. By utilizing information from nearby stations with more complete records, it is possible to fill in the data gaps of recently installed stations.

Furthermore, historical data analysis from nearby stations with longer precipitation records can be employed to infer precipitation patterns in the area and fill in the data gaps of the new station, allowing for a better understanding of the climatic context in which the Standardized Precipitation Index (SPI) is being calculated.

very interesting!!

There is an Australian soil carbon accreditation scheme

Dear Mr. Ghosh,

Thank you for your kind response. Your answers were very helpful. However, if possible, could you please share a sample report, article, or any real-life experiences that you have had in this area? I am eager and looking forward to hearing from you.

Greetings, Naser Dehghanian,

Indeed, flood risk mapping in urban and rural areas is feasible by integrating diverse data sources, innovative tools, and advanced techniques.

Several data sources such as topographic maps, hydrological models, rainfall data, land use and land cover data, and historical flood data can be used with remote sensing, Geographic Information Systems (GIS) and field observations to generate accurate and comprehensive flood risk maps.

Furthermore, community engagement and participation hold significant importance in flood risk mapping as local knowledge and expertise can offer valuable insights into a particular area's specific flood risks and vulnerabilities.

I recommend reviewing the literature to enhance your understanding and knowledge in this field. Numerous high-quality research papers provide insightful perspectives on urban flood risk mapping and assessment.

Please find below a selection of potential sources for your consideration:

Ali YOUNES,